Data obtained for PANI-MMT and their tentative assignments
\r\n\t2) The divergence between the levels of reliability required (twelve-9’s are not uncommon requirements) and the ability to identify or test failure modes that are increasingly unknown and unknowable
\r\n\t3) The divergence between the vulnerability of critical systems and the amount of damage that an individual ‘bad actor’ is able to inflict.
\r\n\t
\r\n\tThe book examines pioneering work to address these challenges and to ensure the timely arrival of antifragile critical systems into a world that currently sees humanity at the edge of a precipice.
The term clay can assume different meanings for different groups of people. For the farmer, clays are the mechanical and chemical environment where most plants grow. For the ceramist, it is the raw material of his works for over 4000 years. To the editor, it gives softness to the paper’s surface in high-quality prints. In the medical area, it may be for the relief of diarrhea and so on. In fact, there is no uniform nomenclature for clay and clay materials [1, 2]. Georgius Agricola (1494–1555), the founder of geology, was apparently the first to propose a definition for clay [3]. The last definition is that the term clay can be considered as natural fine-grained minerals with plastic behavior at appropriate water contents that will harden when dried or fired. Generally, in the area of geology, clays are considered as particles with a size dimension of <4 μm, while in colloid science, a value of <1 μm is more acceptable [4, 5]. Likewise, the term “clay mineral” is difficult to define. As a first approximation, the term signifies a class of hydrate phyllosilicates making up the fine-grained fraction of rocks, sediments, and soils. The definition that the JNCs have proposed is “...phyllosilicate minerals and minerals which impart plasticity to clay and which harden upon drying or firing” [3] Since the origin of the mineral is not part of the definition, clay mineral (unlike clay) may be synthetic.
Hence, clay minerals are extremely fine materials that can only be studied in detail by using X-ray techniques or sophisticated microscopic techniques, such as the electron scanning microscope [6]. They are primarily hydrated aluminosilicates in which the magnesium and iron can replace the aluminum wholly or partly with alkaline or alkaline earth elements. Thus, its chemical composition is variable, such as the nature of the interlayer cations and water content. The different clay minerals have different dehydration properties, structural failure limits, decomposition products, cation exchange capacity (CEC), and other useful properties of economic interest.
Clays layers are formed from tetrahedral sheets in which a silicon atom is surrounded by four oxygen atoms and octahedral sheets in which a metal such as aluminum or magnesium is surrounded by eight oxygen atoms [1-3, 7]. The tetrahedral (T) and octahedral (O) sheets are bonded by the oxygen atoms. Unshared oxygen atoms are present in hydroxyl form. Two main arrangements of T and O layers are observed in major parts of clays. One tetrahedral fused to one octahedral (1:1) is known as the kaolin group, with a general composition of Al2Si2O5(OH)5 and a layer thickness of ~0.7 nm. Phyllosilicates are formed by one octahedral sheet bonded between two tetrahedral sheets (2:1) with a total thickness of 0.94 nm. When the aluminum cations in the octahedral layers are partially substituted by divalent magnesium or iron cations, the smectite clay group is formed, whose structure consists of a central sheet containing groups MO4(OH)2 of octahedral symmetry associated with two tetrahedral sheets (MO4) producing layers designated as T:O:T (see Figure 1.) [7]. The octahedral sites are occupied by ions of aluminum, iron and magnesium, while the centers accommodate tetrahedrons of silicon and aluminum ions. The negative charges from the T:O:T lamellae are neutralized by hydrated alkaline cations that can be exchanged with any other cationic species. Mainly, smectite clays exhibit surface adsorption and catalytic activity in organic reactions.
Schematic representation of montmorillonite clay (MMT)
Finally, the ceramics are defined [8-10] as the art and science of making products and articles (a) chiefly or entirely from "earthy" raw materials, that is, from the so-called nonmetallics excepting fuels and ores of metals; and (b) with a high-temperature treatment involved, either in manufacturing or in service. The technology of clays in the field of ceramics includes consideration of both the room-temperature properties and the behavior at elevated temperatures. When clays are used in ceramics, one of several functions is generally served. Most clays, alone or in mixtures, are used for their contribution to the working properties, drying strength of the ceramic masses which they comprise or to which they have been added. Some clays, however, are used more because they offer an inexpensive body constituent or filler of the desired chemical composition, already subdivided by nature to a convenient grain size.
A polymer–clay material is made by the combination of a polymer and synthetic or natural clay. The presence of clay can improve the mechanical, thermal, barrier and fire retardancy properties of the polymer. If the polymer–clay material has at least one phase with organization in the nanometer scale, the material is called a nanocomposite. It is important to emphasize that the main characteristics of the polymer–clay materials are strongly related to the physical and chemical peculiarities of each component and also due to the nano size aspect and interfacial adhesion bettween the nanocomposite parts [11, 12].
Polymer nanocomposites are formed at least with one part in the nanometer scale (<100 nm). Despite the term nanocomposite being very recent, in fact, has been possible to reconize in the nature a diverse range of materials, such as bones, shells and wood that can be considered nanocomposites because they are formed by carbohydrates, lipids and proteins organized in the nanometer regime [13]. In recent years, the characterization and control of structures at the nanoscale level have been studied, investigated and exploited. Consequently, the nanocomposite technology has emerged as an efficient and powerful strategy to upgrade the structural and functional properties of synthetic polymers. Polymer nanocomposites have attracted great attention due to the exhibition of superior properties such as strength, toughness and fire barrier far from those of conventional microcomposites and comparable with those of metals. The presence of one nanoscale phase leads to tremendous interfacial contacts between the polymer and clay and, as a consequence, the improvement of the polymer bulk phase, such as mechanical, thermal, barrier, durability, chemical stability, flame retardancy, scratch/wear resistance, biodegradability as well as optical, magnetic and electrical properties [14-17]. The increased performance of the mechanical properties of nanocomposites is related to the clay content and the aspect ratio of the clay [18].
Schematic representation of two types of preparations of polymer–clay nanocomposites
Clays have been widely used for the preparation of polymer nanocomposites. Recently, there has been a growing interest for the development of polymer–clay nanocomposites due to their dramatically improved properties compared to conventional polymer composites in a very low fraction [19, 20]. Polymer–clay nanocomposites can be prepared by direct mixture of two aqueous solutions containing the monomer and the clay suspension (see Figure 2.); afterward, the polymer can be formed by adding a polymerization agent, or induced by thermal or light exposition. The resulting material is called an ex situ nanocomposite because the major part of the polymer if found outside the interspaces of the clay. It is important to mention that the initial clay concentration can be modulated and, in some cases, the clay layers are completly separated, as a consequence, the resulting material is known as exfoliated polymer–clay nanocomposite. In a second method (see Figure 2.), the monomer is intercalated in the interlayer space of the clays by charge exchange or by difusion inside the clay galleries previously modified with an organic salt. Afterward, the intercalated polymer can be polymerized and the resulting material is known as an in situ nanocomposite because the major part of the polymeric content is inside the clay interspaces.
In this chapter, we will only provide a summary of the main characteristics found in the polymer–clay nanocomposites. Here, we divide the section between polymer–clay nanocomposites formed by intrinsic nonconducting polymers or by conducting polymers. Traditionally, the clay layers must be previously treated with an organic agent (this point was not explicitly discussed in Figure 2.) to ensure good dispersion of clay layers within the polymer matrix. The dispersion of clay plates into the polymeric matrix is very difficult, mainly by stacking forces between the clay layers and its hydrophilic character. Hence, it is necessary to modify the clay layers in order to increase the chemical compatibility with hydrophobic polymer chains. Only a few hydrophilic polymers such as polyethylene oxide and polyvinyl alcohol can be miscible with clay layers [21].
The origin of polymer–clay hybrids starts with the creation of nylon-6-clay hybrid (NCH) developed in 1986 under Toyota Central Research and Development Laboratories. Afterward, the use of modified clays as precursors to nanocomposite formation was extended into various polymer systems including epoxies, polyurethanes, polyimides, nitrile rubber, polyesters, polypropylene, polystyrene and polysiloxanes, among others. For true nanocomposites, the clay nanolayers must be uniformly dispersed and exfoliated in the polymer matrix. The presence of aggregated tactoids in conventional polymer–clay composites improves rigidity but sacrifices strength, elongation and toughness. However, exfoliated clay nanocomposites, such as NCH, show enhancement in all aspects of their mechanical performance.
The intrinsically conducting polymers (ICPs), or simply synthetic metals, form one of the largest classes of molecular conductors [22]. The preparation of stable poly(acetylene) (PA) films was achieved in the 1970s by Shirakawa and Ikeda [23, 24]. However, it was only in 1977 that the possibility of doping PA using Lewis’s acid (or base) was discovered [25]. During the process of doping [26, 27], the conductivity typically ranges from 10–10 to 10–5 S cm–1, and the polymer is converted into a "metallic" regime. The addition of nonstoichiometric chemical species in quantities that are commonly low (≤10%) results in dramatic changes in the electronic, electrical, magnetic, optical and structural properties of the polymer. The doping is reversible, and the polymer can return to its original state without major changes in its structure. In the doped state, the presence of counterions stabilizes the doped state. All conductive polymers, for example, poly(para-phenylene) (a), poly(p-phenylene-vinylene) (b), poly(pyrrole) (c), poly(thiophene) (d), poly(furan) (e), poly(heteroaromatic vinylene) (f), (where Y = NH, NR, S, O), poly(aniline) (g), poly(para-phenylenediamine) (h), poly(benzidine) (i), poly(ortho-phenylenediamine) (j), among others (see Figure 3.), may be doped by p (oxidation) or n (reduction) through chemical and/or electrochemical process.
Schematic representation of the chemical structures of the most common conducting polymers
In this chapter, we will give special attention to the polymer–clay nanocomposites formed by polyaniline (PANI) and its derivates. Among the different types of hosts used in the formation of nanocomposites with PANI, lamelar materials are undoubtedly the most widely employed. The main reason is that the distance between the layers can be modified, facilitating the intercalation of various chemical species. Hosts, such as MoO3 [28], V2O5 [29, 30], α-Zr(HPO4)2H2O [31], HUO2PO4.4H2O [32], FeOCl [33], layered double hydroxide (LDH) [34] and MoS2 [35], and most frequently, clays were used for intercalation of PANI [36-50].
The adsorption of aniline on MMT clay has been studied a long time ago, and since then, it has been well-known that clays have a property to generate colored species by the adsorption of aromatic amines. The best known case is the blue color generated by the adsorption of benzidine (4, 4′-diaminobiphenyl) in clay [37]. Among the earlier studies [38-40], it was reported that films of MMT containing metal ions become black after immersion in aniline; the authors suggest that this is due to the polymerization of monomers. Soma and Soma [41, 42] and Soma et al. [43-45] used resonance Raman spectroscopy (RR) in the study of oxidation of aromatic compounds (benzene and derivatives) adsorbed on clay, and showed that when the adsorption of aniline on Cu2+ or Fe3+-MMT is made in the liquid phase, polymer formation occurs. Soma and Soma proposed that the polymer formed was equal to that generated electrochemically (PANI-ES), but with the presence of azo linkages (─N=N─). Also, Mehrotra and Giannelis [46] synthesized PANI intercalated in a synthetic hectorite containing Cu2+ ions, the UV-vis-NIR spectrum was very similar to that observed for PANI-EB, and the polymer was converted to conductive PANI-ES form, simply by exposing the material to HCl vapors. Other work done by Chang et al. [47] reported the polymerization of PANI into MMT clay galleries. The intercalation was confirmed by measures of X-ray diffraction, and the interlayer distance obtained was changed from 1.47 to 0.36 nm after the polymerization of aniline. Absorption bands of the PANI-ES form were observed at 420 and 800 nm in the UV-vis-NIR spectrum of the material. In addition, the IR bands at 1568, 1505, 1311 and 1246 cm–1 were upshifted in comparison to the free polymer, probably due to intercalation.
Wu et al. [48, 49] also obtained PANI-MMT using ammonium persulphate as an oxidizing agent, the electronic spectrum of the material obtained was very similar to that obtained for secondarily doped PANI-CSA, suggesting that the PANI was obtained in an extended conformation. The formation of PANI-ES was confirmed by the presence of bands at 1489, 1562 and 1311 cm–1 in the FTIR spectrum of the material. Despite the high organization level of PANI chains into the MMT clay, the conductivity of the material, ca. 10–3 S.cm–1, was not much higher than those obtained previously. The justification of the authors is that there are few polymeric connections between the particles of clay, which significantly reduces the conductivity observed for the material. Later, other authors reported the synthesis of PANI into MMT clay by the intercalation of anilinium ions into MMT followed by oxidation with ammonium persulphate as a standard method to obtain PANI-MMT nanocomposites [50-62].
Some studies were performed by varying the aniline/clay ratio during intercalation, and it was possible to show the increase of interlayer space and the amount of intercalated PANI as well as the increase of the conductivity of the material [63]. The synthesis of PANI with clay in a medium containing surfactants (dodecylbenzenesulfonic acid, DBSA, and camphorsulfonic acid, HCSA) was also used [56-58]. Intercalation was confirmed by X-ray diffraction data, with interlayer distances of ~1.5 nm and ~1.6 nm being obtained for composites of PANI-DBSA-MMT and PANI-CSA-MMT, respectively. DC conductivity values for PANI-DBSA-MMT and PANI-CSA-MMT at room temperature were near 0.3 S.cm–1 and 1.0 S.cm–1, respectively. The intercalated PANI was also obtained by electrochemical polymerization of aniline, using modified clay electrodes [59], graphite electrode–modified clay [60], Pt electrode–modified clay [61] and electrode stainless steel [62]. Inoue and Yoneyama [59] used a clay-modified electrode and intercalation was performed by immersing the electrode in an aniline solution. An interlayer distance value of 0.54 nm was obtained for MMT clay after immersion. Another work using graphite or Pt electrode modified with clay also reported the formation of PANI, as confirmed by the voltammogram profile curves. The oxidation of a suspension of aniline containing MMT clay intercalated with stainless steel electrodes produced a polymer-MMT–valued interlayer distance of 0.51 nm. The FTIR spectrum of the material presented bands at 1579, 1490 and 1311 cm–1, similar to that obtained by Wu et al. [48] in the chemical polymerization of aniline with ammonium persulphate.
Using resonance Raman (RR) and X-ray absorption spectroscopy, it was possible to show that the structure of intercalated PANI was different from the free PANI structure [64-71]. At early polymerization stages, the presence of radical cations, dications and benzidine dications were observed in the RR spectra by head-to-tail and tail-to-tail coupling of aniline monomers. However, at the final stages, the RR spectra showed different bands, this indicates coupling between the initial segments with the formation of new chromophoric segments. In order to elucidate the structure of the intercalated polymer, the use of XANES spectroscopy was decisive. The XANES spectroscopy opens the possibility of investigating the chemical environments of both clays and polymers.
A large number of spectroscopic techniques are routinely used in clay and clay materials science research in order to identify elemental, molecular, and crystalline aspects of the samples. Among them, X-ray spectroscopy has a unique capability to obtain atom-specific information as it measures the excitation of core electrons of selected atoms. An X-ray absorption spectrum (XAS) reflects the excitation of a core electron to unoccupied states. As a consequence, it reflects the electronic structure of unoccupied states of a specific atom in the sample; in fact, it is sensitive to the local environment of the selected element. The X-ray intensity (I) is attenuated when it penetrates into a solid material. This decrease is analogous to the Beer–Lambert law [72], i.e., showing that
X-ray absorption occurs if the incident photon energy is transferred to an electron strongly bounded to the atom. Figure 4 schematically represents the absorption of a K shell electron (1s level) of an atom bonded in a solid material. The absorption coefficient decreases with increasing incident photon energy, but there are sudden changes. These variations correspond to different absorption edges present in the material.
Considering photons with energy lower than the ionization threshold (hν1), they are poorly absorbed by the material since there are no unoccupied states below this energy. However, when the energy of the photon reaches the hν2 value, there is a sharp increase in the absorption, corresponding to the K edge absorption, this energy is called the ionization threshold for the 1s electron. If the photon energy increases (hν3), the atom can be ionized; as a consequence, the absorption coefficient has the same magnitude as the cross-section of the photoelectric effect. If the value of the photon energy continues to increase, absorption begins to degrade, but there may be new sudden jumps, since there are other edges in the absorption material [74-76].
The detection of a chemical element in a material is only the simplest information that is available from the X-ray absorption spectra. In fact, the phenomenon of X-ray absorption is much more complex, and therefore carries much more information. Generally, the absorption spectra are complex; possessing a set of variations that extend over a wide range of energies (tens of units of eV). Figure 5 represents a typical X-ray absorption spectrum, which has a large absorption near the edge and a series of oscillations that will lose intensity as it moves away from the absorption edge. The region near the edge is called XANES (X-ray absorption near-edge structure) and the second one is known as EXAFS (near-edge X-ray absorption fine structure). The XANES region includes a range of energies before the absorption edge up to the beginning of the EXAFS region. The definition of the boundary between these two regions is arbitrary, but there is some consensus that the XANES region extends to 50 eV after the absorption edge. The EXAFS region can be defined as the point where the wavelength of ejected electrons is equal to the distance between the absorber atom and its neighbor atoms, this region can extend up to 1000 eV after the edge [77].
Schematic representation of photons with different energies compared in relation to the ionization threshold for a given material. The hν1 photon has low energy to produce ionization; the photon hν2 has the exact energy for ionization, so there is a sudden jump in the absorption coefficient that is the experimental characterization of the absorption edge, and finally the photon hν3 has much more energy than the edge.
The oscillations in the absorption spectrum were caused by the different final states and contain information related to the structure around the atom that absorbed the radiation.
The EXAFS spectrum originates from interference effects between the excited atoms [77-79]. The wave function of the excited electron propagates beyond the atom and is partially reflected by neighboring atoms. The interference between the wave that spreads and reflected by neighboring atoms causes ripples in the absorption spectrum [78, 79]. The interference can be constructive or destructive, depending on the wavelength associated with the electron and with the interatomic distance. Figure 5 schematically illustrates the origin of the X-ray absorption spectrum. The process can also be visualized as an electronic transition from a core orbital to an unoccupied level with the formation of a core-hole configuration. Photoabsorption coefficient, μ, or photoabsorption cross-section can be generally described by Fermi’s “Golden Rule” as
where
The core-hole configuration must be included in the one-electron approximation. The electronic relaxation associated with the presence of the core-hole and excited electron need to be accounted for if one wants to reproduce the experimental spectra by first principles calculations using Eq. (2). Under the dipole approximation, where
There are two different methods to resolve Eq. (2). The first way is called multiple scattering methods, and the second way is by band-structure methods under periodic boundary conditions.
Hence, through treatment with XANES/EXAFS data, it is possible to determine the interatomic distances between the atoms that have suffered excitation and its neighbor atoms [80-82]. The XANES spectrum contains information similar to the EXAFS spectrum, but the information is more difficult to extract from the math standpoint [80, 83, 84]. This is largely due to the different possibilities of transitions that may occur in the solids in the XANES region, which in the language of scattering theory means that there is multiple scattering in the XANES region. The intensity of absorption is influenced by the number of electrons that occupy the initial state and may therefore participate in absorption, and it also depends on the density of the unoccupied states and the transition momentum. The unoccupied energy levels depend on the oxidation state and the nature of the chemical bond so that this atom, with its neighbors, makes it possible through the XANES spectra, to distinguish the different states of oxidation of this element. The observed modulations into the XANES spectra are also influenced by the oxidation state and nature of chemical bonds of the materials under study. In the following paragraphs, the focus will be on the analysis of XANES spectra at different edges in order to investigate the structure of clays and clay derivate materials. The absorption measurements are only possible in conditions of ultrahigh vacuum (the pressure inside the chamber is ca. 10–7 mbar). What is measured is a signal that is directly proportional to the amount of photons absorbed [85]. Upon absorption, emissions occur from the electrons (photoelectrons, electrons Auger and secondary electrons) whose intensities are proportional to the amount of photons absorbed; to keep the sample electrically neutral, it grounds the sample compartment so that the current replacement of the electrons in the sample (typically, the current is of the order of 10–12 A) is proportional to the intensity of photons absorbed. It can be described as:
Another concern is about the number of samples that can be placed at one time in the compartment because it takes between 3 and 5 h to reach the required pressure inside the chamber. The arrangement used in our experiments is displayed in Figure 6. Another grooved rod is placed over the main rod to delimit the area (ca. 0.2 cm2) and prevent the mixing of the samples, since the measurements are made with the rod positioned vertically in the sample chamber.
Experimental setup used for XANES measurements.
XANES spectroscopy has been widely used for the investigation of clay structures, metal sites in the clays and also for polymer–clay nanocomposites. By selecting the appropriate energy in the X-ray source, it is possible to investigate the silicon, oxygen and aluminum sites in the clay layers; the metal ions incorporated into the clay layers; as well as the carbon, nitrogen, oxygen and other atoms in the polymer chains. In addition, it is possible to measure the absorption, emission and photoejection signals from the clay materials.
The XANES data supported by DFT calculations were essential to verify the differences into the oxygen sites observed for montmorillonite (MMT) and muscovite mica (MT) clays. The hydroxyl groups localized in these cavities and van der Waals forces contributed significantly to adsorption processes. In both clays, the oxygen surface sites are directly affected by the intralayer interaction through hydroxyl groups. The chemical environment of the hydroxyl groups is distinct in the MMT and MT structures. In fact, the oxygen atoms in the apical position in MT layers are less influenced by van der Waals forces. In addition, the silicon surfaces in MT are more sensitive to the Si-O apical-Al changes and have no disturbance on hydroxyl groups than in MMT clay (86). In another very recent work, the XAS data associated with DFT calculations were used to the study of the electronic structure of synthetic and natural kaolinite clay. This can serve as a model system for engineered and natural clay materials. It was possible to correlate the XANES features with the structural defects present in the clay layers. In both synthetic and natural kaolinite, oxygen replaces hydrogen in the Al (001)-hydroxyl groups on the kaolinite clay sheets. The energy levels associated with these defects are situated in the band gap, and its value decreases by about 3.2 eV as this defect is formed [87].
The presence of metals in clays has also been investigated. Many soils around the globe are contaminated with metals due to inputs from anthropogenic activities; however, the long-term processes that retain these metals in soils remain unclear. Changes in Mn K-edge XANES with soil depth were consistent with a mixing of different pools of Mn. In particular, the proportions of Mn(II)/Mn(III) present in the mineral soil increased relative to Mn(IV) with increasing depth. Mn can be preferentially retained in soils relative to other elements due to this process of uptake and immobilization. The Mn that is taken up into the plant’s biomass exists mostly as aqueous and organic Mn(II) compounds that are immobilized as Mn(III)/(IV) oxides during decomposition [88]. Another work studied the interaction of CO2 and O2 gases in volcanic soils containing different minerals and clays having Fe(II/III) ions, which was investigated by using the XANES spectroscopy at Fe K-edge. The authors also measured the Fe K-XANES spectra for a great number of reference materials, thus permitting the determination of Fe species during the cycle of CO2 and O2 interactions [89].
Top: N K XANES spectra of powered samples of PANI-MMT nanocomposites. Experimental spectra are represented by the black continuous line (─). The Voigt bands used in the deconvolution of the experimental spectrum are shown below the experimental data (dashed red line, – – –). The sum spectrum of the Voigt bands is also displayed (dotted red line, ⋯). Deconvolution of the experimental N K XANES spectra was done using SPSS (1995) with Voigt bands (Voigt area mode with varying widths) and linear baseline (linear, D2 mode). The Si K XANES spectra of powered samples of MMT and PANI-MMT are also shown inside the figure. Scheme of PANI-MMT nanocomposites and the intercalated PANI structure are also shown at the top of the figure. Bottom: Tentative assignments of bands observed in N K XANES of PANI-MMT, PBZ-MMT and PpPD-MMT nanocomposites. The band positions were calibrated using the first resonance band value for KNO3 salt (the beam line has a resolution of 0.1 eV; the N K XANES were calibrated considering the value 405.5 eV, according to ref. [91]).
XANES permits the investigation of the confined polymer into clay galleries, differently from surface techniques, such as X-ray photoelectron spectroscopy. The N K XANES spectrum of polyaniline-montmorillonite prepared by in situ polymerization within the cavities of the MMT clay is displayed in Figure 7. The spectrum of PANI-MMT nanocomposites contains bands with different patterns than the spectra of “free” PANI forms [90]. It is interesting to observe that the structure of MMT clay is not changed because there is no modification of the XANES spectra of MMT at the Si K-edge after PANI formation (see Figure 7). Comparing the set of N K XANES spectra obtained for several organic molecules with nitrogen atoms in different electronic environments [67-69] it was possible to assign the observed bands. Table 1 summarizes the data obtained for PANI-MMT and displays the tentative assignments for the various transitions observed.
\n\t\t\t\tSamples\n\t\t\t | \n\t\t\t\n\t\t\t\tTentative assignments\n\t\t\t | \n\t\t||||
\n\t\t\t\tPANI-MMT\n\t\t\t | \n\t\t\t\n\t\t\t\tPBZ-MMT\n\t\t\t | \n\t\t\t\n\t\t\t\tPpPD-MMT\n\t\t\t | \n\t\t|||
bands/cm–1 (linewidths of the bands/cm–1) | \n\t\t|||||
398.99 ± 0.05 (0.32) | \n\t\t\t398.8 ± 0.1 (1.3) | \n\t\t\t398.8 ± 0.1 (1.5) | \n\t\t\t1s → π*\n\t\t\t | \n\t\t\t—N= of phenazine-like rings and/or —N=N— of azo bonds | \n\t\t|
399.46 ± 0.05 (0.47) | \n\t\t\t− | \n\t\t\t399.64 ± 0.05 (0.88) | \n\t\t\t1s → π*\n\t\t\t | \n\t\t\t—H2N+= or = N+= of phenazine-like rings and/or dications of PANI | \n\t\t|
400.57 ± 0.05 (0.75) | \n\t\t\t400.18 ± 0.05 (1.4) | \n\t\t\t400.26 ± 0.05 (0.56) | \n\t\t\t1s → π*\n\t\t\t | \n\t\t\tπ-Conjugated nitrogen | \n\t\t|
401.74 ± 0.05 (0.54) | \n\t\t\t401.75 ± 0.05 (0.66) | \n\t\t\t− | \n\t\t\t1s → π*\n\t\t\t | \n\t\t\tAmine nitrogen | \n\t\t|
402.7 ± 0.1 (1.4) | \n\t\t\t− | \n\t\t\t402.2 ± 0.1 (1.1) | \n\t\t\t1s → π*\n\t\t\t | \n\t\t\tAmine nitrogen | \n\t\t|
406.0 ± 0.1 (1.4) | \n\t\t\t405.1 ± 0.1 (1.0) | \n\t\t\t406.0 ± 0.1 (2.0) | \n\t\t\t1s → π*\n\t\t\t | \n\t\t\t—H2N+—+NH2— | \n\t\t|
408.8 ± 0.1 (1.4) | \n\t\t\t408.7 ± 0.1 (2.4) | \n\t\t\t− | \n\t\t\t1s → σ*\n\t\t\t | \n\t\t\t—N=N— | \n\t\t|
410.1 ± 0.1 (1.6) | \n\t\t\t410.9 ± 0.1 (2.7) | \n\t\t\t409.2 ± 0.1 (4.8) | \n\t\t\t1s → σ*\n\t\t\t | \n\t\t\t—H2N+—+NH2— | \n\t\t|
412.2 ± 0.1 (2.4) | \n\t\t\t− | \n\t\t\t412.7 ± 0.1 (2.7) | \n\t\t\t1s → σ*\n\t\t\t | \n\t\t\t− | \n\t\t|
414.8 ± 0.1 (2.4) | \n\t\t\t− | \n\t\t\t− | \n\t\t\t1s → σ*\n\t\t\t | \n\t\t\t− | \n\t\t
Data obtained for PANI-MMT and their tentative assignments
It should be mentioned that all N K XANES bands (for 1s → π* and 1s → σ* transitions) observed for intercalated PANI have lower linewidths than those observed for “free” PANI. Structural limitations of the polymer lead to an electronic reorganization and shorter electronic bands; as a consequence, the absorption bands are narrower than those for “free” PANI. The same behavior was observed for polybenzidine (PBZ) and poly(p-phenylediamine) (PpPD) intercalated in the MMT clay. Hence, the N K XANES bands for intercalated PANI can be related to nitrogen atoms bonded in the phenazine-like rings and azo bonds; a similar behavior was also observed for intercalated PpPD. In the case of intercalated PBZ, the bands related to the azo bonds were more intense. The most intense band observed for all spectra of the nanocomposites is near 405−406 eV and can be assigned to protonated azo bonds (hydrazinium bonds); it also confirms the presence of new segments in the intercalated polymers. Finally, it was observed that the structure of confined polymers contains new segments in comparison to that observed for “free” polymers.
Much fewer works deal with EXAFS of clays and its derivate materials compared to XANES data. However, it is possible to find studies on the experimental and theoretical determination of Cu(II) sites in clay surfaces and interlayer. Cu(II) in the fully hydrated, Cu-saturated MMT has a singlet 1st derivative XANES spectrum. FEFF calculations show that this singlet feature originates from a quasi-regular octahedral coordination of water molecules around the interlayer Cu(II) atom. All other samples and models have doublet 1st derivative XANES spectra. FEFF calculations suggest that the doublet features arise from an axially elongated octahedral coordination under the Jahn–Teller effect or square planar coordination. FEFF calculations of the EXAFS spectra as a function of the axial oxygen bond length demonstrate that a destructive interference between backscattering from equatorial oxygen (O-eq) and that from axial oxygen (O-ax) atoms leads to an apparent coordination number (CN) less than six expected for the tetragonal coordination, with the farther, loosely bound axial oxygen atoms making a minor, yet negative, contribution to the CN determined by the EXAFS analysis. This study shows that Cu(II) has interchangeable octahedral, tetragonal and square planar coordination in the MMT interlayer, depending on Cu(II) loading and degree of hydration. The quasi-regular octahedral coordination of the interlayer Cu(II) in MMT is a new finding of this study [92]. In another work [93], the authors studied the sorption mechanism of Cu(II) on hectorite clay. The XAS spectra show an angular dependence between the Cu-O-eq atomic pair and the direction perpendicular to the clay layer plane. Based on the number of Mg/Al and Si nearest neighbors, the Cu(O-eq)4(O-ax)1–2 polyhedron is attached to the clay surface by sharing one to three edges with the structural Al/Mg octahedral and zero to three corners with the Si/Al tetrahedral. Copper has an unusually high coordination on the two dioctahedral aluminous clays, as explained by the presence of distorted empty cavities at their surface, which can accommodate irregular coordination polyhedrals. The steric match between the distorted empty octahedral cavities and the Jahn–Teller distorted Cu polyhedral provides a rationale to explain the higher affinity of Cu(II) for Al octahedral sheets.
X-ray absorption spectroscopy is now a powerful tool for the investigation of clays and its derivates. However, their use in clay science is still in its infancy. In fact, there are plenty of investigation possibilities in clay science, since the studies of surface aspects about the Si, Fe, Al and O sites, where the specificity of the XAS signal can give atomic information around the absorbing atom and up to the characterization of intercalated metals, molecules, biomolecules, and polymers and so on. The XANES data, supported by DFT calculations, were essential to verify the differences in the oxygen sites observed in clays. The hydroxyl groups localized in these cavities and van der Waals forces contribute significantly to adsorption processes. The oxygen surface sites are directly affected by the interlayer interaction through hydroxyl groups. Experimental and theoretical EXAFS studies of clays with Cu(II) show that Cu(II) has interchangeable octahedral, tetragonal and square planar coordination in the clay interlayer, depending on Cu(II) loading and degree of hydration. The angular dependence between the Cu-O-eq atomic pair and the direction perpendicular to the clay layer plane was also observed and the consequences of different coordination sites where the Cu ions can be found. XANES data of intercalated PANI show new bands at 398.8 eV and 405−406 eV. These new bands were assigned to phenazine-like rings and azo bonds in the structure of the polymers (polyaniline, polybenzidine and poly(p-phenylediamine) within the galleries of Montmorillonite clay. The investigation of the electronic structure of the conducting polymer–clay nanocomposites through XANES spectroscopy has been decisive in the determination of their structure and also in the study of the interactions between the polymeric chains and the clay layers. The force of these interactions is responsible for guidance in the formation of a polymeric backbone with a distinct structure to that observed in the free polymer. We believe that the XANES/EXAFS studies of the structural pattern of the metal–clay, molecules–clay and polymer–clay nanocomposites will be decisive for their applications.
This work is dedicated to my parents (Iara Ap. Morari do Nascimento and Romualdo J. do Nascimento). Many thanks to the National Synchrotron Light Laboratory (LNLS, Campinas-Brazil) for XANES measurements.
Rock physics is often called a “velocity-porosity” science. The idea behind this name is to predict the elastic-wave velocities in porous rock from its porosity or implement an inverse operation and interpret the velocity measured in a well or using seismic tomography or reflection techniques for the porosity of rock. It is important to mention that the elastic-wave velocities are related to the elastic moduli of rock as follows:
where
where
Important elastic constants used in rock physics are the bulk (
Most of natural rocks contain more than one mineral. In this situation,
where
The same rule applies to the density of the pore fluid:
where
and
Because of the link between the elastic-wave velocities and elastic moduli as given by Eq. (1), it is often instructive to relate these elastic moduli to porosity. Such approach opens an avenue to using the so-called effective medium theories where the elastic moduli are theoretically related to porosity and the geometry of rock, referring to the spatial arrangement of pores and grains, as well as shapes of these pores and grains.
It has been discovered early that the velocity and elastic moduli not only depend on porosity, but also on the properties of the mineral frame. A rule of thumb is that at the same porosity, the softer the mineral frame, the smaller the elastic moduli of rock. For example, at the same porosity, rocks containing soft clays have velocities smaller than rocks dominated by stiffer quartz. Hence, rock physics is not only a “velocity-porosity” science but also a “velocity-porosity-mineralogy” science.
The situation becomes more complex if we consider the effects of the pore fluid on the elastic moduli (and velocities) of a porous composite. It is intuitively clear that the less compressible the pore fluid (water versus gas), the stiffer the entire rock, meaning that its bulk modulus is higher. Now we are talking about “velocity-porosity-mineralogy-fluid.”
The science of rock physics also includes understanding and quantification of other rock properties, such as hydraulic permeability and electrical resistivity, and their relation to other attributes, namely, porosity, rock texture, and mineralogy.
Generally, contemporary rock physics treats natural rock as a holistic object whose various properties (attributes) are extracted from experiments simulating processes, such as elastic-wave propagation, fluid and electrical transport, nuclear magnetic resonance (NMR), and breakage. We seek a theoretical understanding of interrelations between such attributes and their mathematical quantification. Such relations are also called rock physics models (RPM) or transforms. Needless to say that such quantification has to be “as simple as possible but not simpler.”
Finally, the newest branch of rock physics is digital rock physics (DRP) whose mandate is to “image and compute,” image rock at the pore scale and digitally simulate various processes within the digital image. For example, simulations of viscous fluid flow yield permeability, simulations of electrical charge transport yield resistivity, and simulations of deformation under stress yield the elastic moduli.
Let us now review some of historic developments in rock physics.
Arguably, the first rock physics velocity-porosity transform was introduced by Wyllie et al. [2]. It simply states that the total P-wave traveltime through rock with porosity
where
Vp versus porosity according to the Wyllie et al. [2] and Raymer et al. [3] transforms for quartz, dolomite, and mixed mineralogy. Legend in the middle refers to all plots.
Equation (8) is purely empirical in spite of its physically meaningful form. Indeed, in real rock, the mineral and fluid parts are not arranged in layers to enable a simple summation of the respective traveltimes. Still, this equation gives a reasonably accurate approximation for
Equation (8) has dominated petrophysical interpretation of velocity for porosity for a long time. It gave rise to the so-called sonic porosity computed from wireline velocity data as
The next historic equation was introduced by Raymer et al. [3]:
As Eq. (8), it is purely empirical, derived from wireline data. Still, it is very meaningful as it can be applied to rock with any fluid inside, even where
We conclude this section by presenting equations relating the electrical resistivity to porosity and absolute hydraulic permeability to porosity.
The former transform relates the resistivity
where
Left: F versus porosity according to Eq. (11) for m = 1.5, 2.0, and 2.5 with Fontainebleau experimental data shown as symbols. Right: RtS/Rw ratio versus water saturation for ϕ = 0.2 and m = n = 2.0 (Eq. (12)).
At partial brine saturation,
where
Both Eqs. (11) and (12) were discovered by Archie in 1942 [6] and remain the cornerstone of resistivity interpretation for hydrocarbon saturation in the wellbore. Various modifications of these equations dealing with resistivity interpretation in sediments containing clays and shales are discussed in Mavko et al. [1].
The historic absolute permeability prediction equation is called the Kozeny-Carman [7] formula. It is based on an extremely idealized representation of pores as a set of parallel pipes inclined to the direction of pore pressure gradient at an angle
The permeability
A variable alternative to
The Kozeny-Carman equation reads [1]
A modified version of this equation is based on the assumption that
It follows from Eq. (15) that the unit of absolute permeability is length squared. However, traditionally, the permeability unit is Darcy (D) or milli-Darcy (mD). One D is 10−13 m2, while one mD = 10−15 m2.
Figure 3 shows experimental permeability data for Fountainebleau sandstone and two North Sea sand sets with an Eq. (16) curve superimposed for
Permeability versus porosity plots as explained in the text.
Laboratory experiments measuring the elastic-wave velocities in rock often show that the presence of the fluid in the pores strongly affects the elastic properties (Figure 4). Such dramatic results, especially for
Vp (left) and Vs (right) of high-porosity unconsolidated sand versus hydrostatic confining pressure. The pore pressure is constant 0.1 MPa. Squares are data obtained in ultrasonic pulse transmission experiments on the water-saturated sample. Circles are for the room-dry sample (after Zimmer [8]).
Arguably, the most important contribution to rock physics is Gassmann’s fluid substitution theory [9]. This theory allows us to compute the bulk modulus of porous rock filled with Fluid A if this modulus is known (measured) in the same rock but filled with Fluid B. These derivations were conducted under the assumption that the wave-induced pore pressure oscillations equilibrate within the sample over the wave period, meaning that Gassmann’s is a low-frequency theory. Hence, it is applicable at the wireline and seismic frequency ranges. It helps predict the seismic response of rock filled with any hypothetical fluid if it is measured in situ where the pore fluid is known. For example, if the elastic properties of rock are measured in situ in rock 100% filled with water, we can predict these properties in the same rock but filled with oil or gas.
Gassmann’s theory provides the bulk modulus in fluid-saturated rock (
The latter equation can be rearranged as follows:
Equations (17) and (18) provide us with a fluid substitution recipe as follows. Assume that we know the bulk modulus
The bulk modulus
where
Of course, the shear modulus of the rock remains the same, no matter what fluid it is saturated with.
It is important to remember that the bulk density
where
Finally, we can compute the elastic-wave velocities, as well as other seismic attributes, once we know the elastic moduli:
and
where
Let us refer to a later important development in theoretical fluid substitution. It stemmed from the fact that Gassmann’s theory [9] requires the knowledge of the bulk modulus that can only be computed using Eq. (1) if both
Figure 5 shows an example of the results of fluid substitution (pure water) on the elastic properties of high-porosity sand measured in the laboratory [11] at room-dry conditions. Clearly, the pore fluid has a dramatic effect on Poisson’s ratio. Such plots are basis for in situ fluid identification from seismic data.
Sand experimental data and fluid substitution. Left. The bulk and shear moduli versus confining pressure as measured (dry) and water-substituted using Gassmann’s theory [9]. Middle. Vp and Vs versus confining pressure as measured (dry) and water-substituted. Right. The P-wave impedance versus Poisson’s ratio as measured (dry) and water-substituted, color-coded by the confining pressure.
Let us finally describe the details required in practical fluid substitution, specifically the computation of
The elastic moduli of the multi-mineral rock matrix
where
where
The bulk modulus of the pore fluid is
where
In addition to the pore fluid, there are two more important variables influencing the elastic properties of rocks, their mineralogy and the differential pressure
Of course there are other influencing factors, such as rock texture (clastics versus carbonates versus unconventional shale), temperature, and diagenetic history. Here we only concentrate on the abovementioned two.
Mineralogy. As an example, let us examine the Han [13] laboratory dataset obtained on a large suite of sandstones with porosity ranging from zero to 30% and clay content between zero and 50%. Figure 6 shows
Dry rock Vp (top) and Vs (bottom) versus porosity, color-coded by the clay content, at confining pressure 50 MPa (left) and 5 MPa (right) (after Han [13]).
Obviously, the clay content plays a dramatic role acting to reduce both
Another striking example of velocity discrimination due to mineralogy comes from unconventional shale with data obtained by wireline logging in a vertical well (Figure 7). The data shown in this figure is for 100% wet rock, obtained by fluid substitution from in situ conditions. The velocity-porosity dataset forms an amorphous cloud (Figure 7, top) with both
100% wet rock Vp (left) and Vs (right) without accounting for mineralogy (top) and color-coded by the sum of clay and kerogen contents (bottom) (adopted from Dvorkin et al. [14]).
The Raymer et al. [3] model also predicts a strong dependence of the velocity on mineralogy (Figure 8), as well as the pore fluid, the latter well pronounced at higher porosity.
Vp versus porosity according to the Raymer et al. [3] model for dry rock (left) and 100% water-saturated rock (right). The mineralogy is quartz and clay. The upper curves is for zero clay content, while the bottom curve is for 100% clay. The in-between curves are for gradually increasing clay content with increment 10% (top to bottom).
Stress. The effect of the confining pressure on the velocity in sand can be clearly seen in Figure 5 with
Vp (left) and Vs (right) versus pressure for two dry sandstone samples from the North Sea (top) and Gulf of Mexico (bottom).
The velocity in carbonate rocks is often not as affected by stress as it is in clastic samples. The magnitude of this effect is often influenced by the presence of compliant cracks in the rock. Such cracks act to strongly affect the velocity at low pressure while they are open. As the pressure increases, these cracks close acting to increase the velocity (Figure 10, Sample A). In samples where the cracks are absent, the velocity hardly varies as a function of pressure (Figure 10, Sample B).
Same as Figure 9 but for two chalk samples from Ekofisk field in the North Sea. Velocities in sample A (porosity 0.38) is pressure dependent, while the velocities in sample B (porosity 0.31) hardly vary with pressure.
Notice that both historic velocity-porosity model by Wyllie et al. [2] and Raymer et al. [3] do not account for the dependence of the elastic-wave velocities on the confining stress. Both models are suitable for predicting the elastic properties at high, but not at low stress.
The velocity-stress dependence is important in understanding and predicting the seismic responses during hydrocarbon recovery, a process where the differential pressure may increase during production if the reservoir is depleted and the pore pressure is reduced, while the overburden remains constant. This differential pressure may decrease during enhanced oil recovery where water or gas are injected into the reservoir at high pressure, acting to reduce the difference between the overburden and pore pressure. Plots similar to that shown in Figure 5 (right-hand frame) are useful in simultaneously assessing the effects of the pore fluid and differential pressure on the elastic attributes.
There are two kinds of elastic moduli versus porosity effective medium models: (a) inclusion models and (b) grain-based models. The first kind models build a rock from the zero-porosity endpoint by placing inclusions into the solid matrix [1]. These models are perhaps relevant to some carbonate rocks where the pores appear as inclusions in calcite or dolomite matrix. The second kind assumes that the rock is formed by solid grains which comprise an uncemented grain pack at the high-porosity endpoint (also called the critical porosity) and, as the porosity is reduced, the original pack is altered either by grain contact cement or by smaller grains deposited in the pore space between the original larger grains, or a combination of these two processes.
As an example of the inclusion models, consider the differential effective medium model (DEM), where spheroidal pores are placed inside the solid matrix. A spheroid is an ellipsoid with two large diameters equal to each other and the third diameter smaller or equal to these two. The ratio of the small to large diameter is called the aspect ratio
Figure 11 (top) shows how the bulk and shear moduli depend on the total porosity for pure calcite rock with the bulk and shear moduli of the mineral 76.8 and 32.0 GPa, respectively, and its density 2.71 g/cc. The pores are empty, meaning the bulk and shear moduli of the inclusions are zero. In the same figure (bottom), we plot the respective
Elastic moduli (top) and velocities (bottom) versus porosity computed using DEM model for a pure calcite rock. The aspect ratio corresponding to the top curves is 1.00 and for the bottom curve 0.01. The aspect ratio gradually decreases to 0.50, 0.20, and 0.10 for the curves in between (top to bottom).
Figure 12 is the same as Figure 11 except that we use a single aspect ratio 0.10 and compare the results for empty inclusions with those for water-filled inclusions where the bulk modulus is 2.25 GPa and density is 1.00 g/cc.
Same as Figure 11 but for a single aspect ratio 0.10 and for empty pores (black) and pores filled with water (blue).
We observe that both the bulk and shear moduli increase for pores filled with water as compared to empty pores. So do
Notice that DEM curves connect two endpoints, one at zero porosity where the elastic moduli of rock are those of the mineral matrix and the other at 100% porosity where the elastic moduli are those of the inclusions (fluid in the pores). About three decades ago, Nur observed that most natural rocks simply do not exist in the entire zero to 100% porosity range. The maximum geologically plausible porosity for clastic rocks (sands and sandstones) is about 0.40. It may be higher in carbonates, such as chalks, that can have porosity up to 0.50. This porosity can be even higher for foam-like formations, such as volcanic rock (pumice) or artificially manufactured glass foam. This maximum porosity is called the critical porosity. This concept was formalized in Nur et al. [15].
One implication of the critical porosity concept is that the high-porosity endpoint should be at the critical porosity rather than at 100% porosity. It gave rise to the so-called modified elastic bounds. The simplest example is based on the upper elastic bound (also called the Voigt bound) for a composite made of two elastic components (“1” and “2”) with the compressional and shear moduli
Assume that
These two curves are plotted in Figure 13. In the same figure, we plot Han’s [13] data for low-clay-content samples at 50 MPa confining pressure. These data fall way below the upper bound curves for pure quartz with
Upper and modified upper elastic bounds for the compressional (left) and shear (right) moduli versus porosity. The critical porosity is 0.36. Data are from Han’s [13] sandstone dataset for the clay content below 7% and with the elastic-wave velocities measured on dry samples at 50 MPa confining pressure.
The modified bounds use the same equations, but with porosity scaled by the critical porosity
giving modified curves that are much closer to the data (Figure 13).
All grain-based theories exploit the critical porosity concept. We start with the contact-cement theory where it is assumed that the grains are not subjected to any confining stress at
Schematic modes of porosity reduction. From top to bottom: Contact-cement and stiff-sand model; soft-sand model; and constant-cement model (adopted from Dvorkin et al. [4]).
The soft-sand model assumes that at the critical porosity and the elastic properties of the grain pack are given by the Hertz-Mindlin [16] contact theory. This theory assumes that the grain pack is made of identical spherical grains whose elastic properties are those of the mineral (solid) matrix as given by Eq. (25). Combined with the mean field approximation that assumes that all grains are subject to identical local stresses and have the same average number of contacts per grain
where
The coordination number
It is assumed in Eq. (31) that the grains have infinite friction (no slip) at their contacts. If we allow only the fraction
This parameter
Finally, to obtain the dry rock bulk (
It is important to emphasize that the critical porosity endpoints here do not necessarily have to be given by the Hertz-Mindlin contact theory. Alternatively, these values can be selected from experimental data. What is most important in this model is the usage of the “soft” connection between the two porosity endpoints.
An alternative “stiff” connection between the aforementioned endpoints is given by the modified upper Hashin-Shtrikman bound as
where, once again,
This stiff connection, also called the stiff-sand model, can serve to connect the contact-cement curve with the zero-porosity endpoint.
Yet another model belonging to this family is the constant-cement model. It assumes that the grains have initial contact cementation with further porosity reduction due to the placement of small particles away from grain contacts (Figure 14). The functional form of this model is the same as in the soft-sand model (Eq. (33)) but with artificially high coordination number.
Examples of velocity-porosity curves according to the aforementioned grain-based theories are shown in Figure 15, where we assumed that both the grain and cement materials are pure quartz;
Velocity-porosity curves according to the soft-sand, stiff-sand, contact-cement, and constant-cement models as explained in the text.
Figure 16 shows an example of using the constant-cement model to describe the elastic behavior of unconventional gas shale, while Figure 17 is an example of applying the stiff-sand model to carbonate reservoirs. The parameters of the models are provided in the captions. These two examples show that the grain-based theories given here are appropriate not only for clastic sediments but also in very different lithological settings.
Vp (left) and Vs (right) versus porosity for gas shale from wireline data adjusted for 100% water saturation. The color code is the sum of the clay and kerogen volume fractions (red for high and blue for low). The model curves are computed to bound the data. These curves are from the constant-cement model with the coordination number 12, differential pressure 26 MPa, critical porosity 0.40, and shear stiffness correction factor 1 (adopted from Dvorkin et al. [14]).
Velocity- (left) and impedance-porosity (middle) plots showing chalk (gray) and lower-porosity carbonate (black) data points from wireline data adjusted for 100% water saturation. Graph on the left is the impedance versus Poison’s ratio plot, also for 100% water saturation conditions. The curves are from the stiff-sand model with the coordination number 6, differential pressure 30 MPa, critical porosity 0.40, and shear stiffness correction factor 1. The two model curves are for the two slightly different properties of the pure calcite end member (adopted from Dvorkin and Alabbad [17]).
Figure 18 shows laboratory data obtained at 30 MPa confining pressure on dry high-porosity, almost pure-quartz sand samples from the North Sea. In this classic example, the higher-velocity dataset is contact-cemented turbidite sand, while the lower-velocity dataset is friable and virtually uncemented sand. The former data can be matched by the contact-cement curves transitioning into the stiff-sand trajectories. The latter data are matched by the soft-sand curves.
Vp (left) and Vs (right) versus porosity for two high-porosity sand datasets as explained in the text. The model curves marked in the plots are computed for 30 MPa differential pressure, critical porosity 0.40, coordination number 7, shear stiffness correction factor 1, and dry rock.
Digital rock physics is based on the concept “image and compute,” image rock at the pore scale (Figure 19) and then simulate in the computer various processes in such an image to arrive at a desired rock property. These simulations include viscous fluid flow to arrive at hydraulic permeability, electrical charge flow to arrive at electrical resistivity, as well as elastic deformation to arrive at the elastic moduli and velocities.
Segmented digital images of loose sand (porosity about 30%), sandstone (porosity about 20%), and carbonate (porosity about 15%) showing the mineral matrix and pores. The images are a few mm across.
The advantage of such digital approach is that the same sample can be reused multiple times, unlike in physical experiments where a sample is altered after every test; the sample can be digitally altered by, e.g., introducing digenetic cementation, which is hardly possible in physical experiments, as well as subsampling of a digital volume to investigate how various rock properties vary within the volume and how relations between rock properties depend on the spatial scale of investigation.
Although the aforementioned concept is simple, its implementation is not. First, the imaging has to be conducted at the appropriate scale and resolution to reveal the salient features of natural rock relevant to the process under examination. Second, the image has to be segmented to separate minerals from pores and segregate various minerals within the solid matrix, as well as fluid phases inside the pores. Third, powerful computational engines have to be utilized and verified to simulate processes relevant to the physical experiment.
In spite of these complexities, during the last decade, DRP has emerged as a powerful technique complementing (if not replacing) physical testing, mostly due to the recent advances in imaging hardware and image processing and computational software, the latter combined with steadily improving computational power. Not only DRP has become a novel research tool in academia and national labs, but is has also been adopted by leading oil and service companies.
There is one more inherent feature of DRP that needs to be accounted for. Pore-scale rock images are only a few mm in size, and the higher the resolution needed to revel the salient features, the smaller the field of view. At the same time, these computational results have to be relevant at much larger spatial scales of feet for wireline measurement interpretations in the well or tens and hundreds of feet in seismic prospecting. Even such basic property as porosity may be different if measured on an inch-sized sample an on mm-sized fragment of the same sample.
One way out of this conundrum is instead of directly comparing data points generated by different methods of measurement, compare trends formed by such data points, such as permeability versus porosity trends. Dvorkin et al. [18] show that such trends are often hidden inside a very small digital sample and can be derived by subsampling it. Moreover, these computational trends often match relevant physical trends and/or theoretical rock physics transforms, hence validating computational results and making them relevant at much coarser spatial scales.
The approach is to subsample a digital volume into 23, 33, or 43 subvolumes (Figure 20) and then compute the desired property pairs (e.g., porosity and permeability) on each of these subvolumes. Very often, the property pairs thus computed form a meaningful trend supported by physical measurements and/or theories (see examples in Figures 21–23). We can call this subsampling approach “to see the rock in a grain of sand.”
Illustration of the subsampling approach.
Permeability versus porosity in Fontainebleau sandstone. Left: Laboratory data matched with a Kozeny-Carman theoretical curve. Right: Multiple permeability versus porosity data points computed from a few digital Fontainebleau samples and subsamples thereof (adopted from Dvorkin et al. [18]).
Formation factor versus porosity computed on carbonate cuttings. The curves are from Archie’s equation with the cementation exponent m 2.0, 2.5, and 3.0 (bottom to top) (adopted from Dvorkin et al. [18]).
Vp versus porosity for Fontainebleau sandstone as computed from a few digital samples and subsamples thereof (squares). Gray circles are from laboratory measurements of dry samples. The curve is from the stiff-sand model (adopted from Dvorkin et al. [18]).
These results open ways to a meaningful utilization of DRP in research and industry. Publications related to DRP are many and the number is growing. We refer the reader to Kameda and Dvorkin [19], Dvorkin et al. [20], Dvorkin and Derzhi [21], and Andra et al. [22, 23].
This chapter presents an overview of rock physics, starting with its history and ending with the most recent development, the digital rock physics. This chapter can be used as a basic reference pointing towards published sources where the topic is developed in-depth and detailed equations, tables, and experimental results are given. One of such comprehensive sources is the third edition of the Rock Physics Handbook [24].
Rock physics remains a key component in interpreting seismic and other remote sensing data for the underlying properties and conditions of the subsurface. A plethora of such practical results has appeared and continues to appear in geophysical journals, such as Geophysics (Society of Exploration Geophysicists), Journal of Geophysical Research (American Geophysical Union), and First Break (European Association of Geoscientists and Engineers), as well as presented at conferences worldwide.
An important topic not addressed in this chapter is a simultaneous interpretation of different remote sensing sources, such as seismic prospecting, electric and electromagnetic sensing, and gravity methods. Once again, such materials can be found in the proceedings and books from the aforementioned professional societies.
We feel that the material presented can serve as a detailed introduction into the extensive field of physics of rocks and be of use to graduate students, as well as advanced professional in earth and environmental sciences.
Supporting women in scientific research and encouraging more women to pursue careers in STEM fields has been an issue on the global agenda for many years. But there is still much to be done. And IntechOpen wants to help.
",metaTitle:"IntechOpen Women in Science Program",metaDescription:"Supporting women in scientific research and encouraging more women to pursue careers in STEM fields has been an issue on the global agenda for many years. But there is still much to be done. And IntechOpen wants to help.",metaKeywords:null,canonicalURL:null,contentRaw:'[{"type":"htmlEditorComponent","content":"At IntechOpen, we’re laying the foundations for the future by publishing the best research by women in STEM – Open Access and available to all. Our Women in Science program already includes six books in progress by award-winning women scientists on topics ranging from physics to robotics, medicine to environmental science. Our editors come from all over the globe and include L’Oreal–UNESCO For Women in Science award-winners and National Science Foundation and European Commission grant recipients.
\\n\\nWe aim to publish 100 books in our Women in Science program over the next three years. We are looking for books written, edited, or co-edited by women. Contributing chapters by men are welcome. As always, the quality of the research we publish is paramount.
\\n\\nAll project proposals go through a two-stage peer review process and are selected based on the following criteria:
\\n\\nPlus, we want this project to have an impact beyond scientific circles. We will publicize the research in the Women in Science program for a wider general audience through:
\\n\\nInterested? If you have an idea for an edited volume or a monograph, we’d love to hear from you! Contact Ana Pantar at book.idea@intechopen.com.
\\n\\n“My scientific path has given me the opportunity to work with colleagues all over Europe, including Germany, France, and Norway. Editing the book Graph Theory: Advanced Algorithms and Applications with IntechOpen emphasized for me the importance of providing valuable, Open Access literature to our scientific colleagues around the world. So I am highly enthusiastic about the Women in Science book collection, which will highlight the outstanding accomplishments of women scientists and encourage others to walk the challenging path to becoming a recognized scientist." Beril Sirmacek, TU Delft, The Netherlands
\\n\\nAdvantages of Publishing with IntechOpen
\\n\\n\\n"}]'},components:[{type:"htmlEditorComponent",content:'At IntechOpen, we’re laying the foundations for the future by publishing the best research by women in STEM – Open Access and available to all. Our Women in Science program already includes six books in progress by award-winning women scientists on topics ranging from physics to robotics, medicine to environmental science. Our editors come from all over the globe and include L’Oreal–UNESCO For Women in Science award-winners and National Science Foundation and European Commission grant recipients.
\n\nWe aim to publish 100 books in our Women in Science program over the next three years. We are looking for books written, edited, or co-edited by women. Contributing chapters by men are welcome. As always, the quality of the research we publish is paramount.
\n\nAll project proposals go through a two-stage peer review process and are selected based on the following criteria:
\n\nPlus, we want this project to have an impact beyond scientific circles. We will publicize the research in the Women in Science program for a wider general audience through:
\n\nInterested? If you have an idea for an edited volume or a monograph, we’d love to hear from you! Contact Ana Pantar at book.idea@intechopen.com.
\n\n“My scientific path has given me the opportunity to work with colleagues all over Europe, including Germany, France, and Norway. Editing the book Graph Theory: Advanced Algorithms and Applications with IntechOpen emphasized for me the importance of providing valuable, Open Access literature to our scientific colleagues around the world. So I am highly enthusiastic about the Women in Science book collection, which will highlight the outstanding accomplishments of women scientists and encourage others to walk the challenging path to becoming a recognized scientist." Beril Sirmacek, TU Delft, The Netherlands
\n\n\n\n\n'}]},successStories:{items:[]},authorsAndEditors:{filterParams:{sort:"featured,name"},profiles:[{id:"6700",title:"Dr.",name:"Abbass A.",middleName:null,surname:"Hashim",slug:"abbass-a.-hashim",fullName:"Abbass A. Hashim",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/6700/images/1864_n.jpg",biography:"Currently I am carrying out research in several areas of interest, mainly covering work on chemical and bio-sensors, semiconductor thin film device fabrication and characterisation.\nAt the moment I have very strong interest in radiation environmental pollution and bacteriology treatment. The teams of researchers are working very hard to bring novel results in this field. I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. I have served as the editor for many books, been a member of the editorial board in science journals, have published many papers and hold many patents.",institutionString:null,institution:{name:"Sheffield Hallam University",country:{name:"United Kingdom"}}},{id:"54525",title:"Prof.",name:"Abdul Latif",middleName:null,surname:"Ahmad",slug:"abdul-latif-ahmad",fullName:"Abdul Latif Ahmad",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"20567",title:"Prof.",name:"Ado",middleName:null,surname:"Jorio",slug:"ado-jorio",fullName:"Ado Jorio",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidade Federal de Minas Gerais",country:{name:"Brazil"}}},{id:"47940",title:"Dr.",name:"Alberto",middleName:null,surname:"Mantovani",slug:"alberto-mantovani",fullName:"Alberto Mantovani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"12392",title:"Mr.",name:"Alex",middleName:null,surname:"Lazinica",slug:"alex-lazinica",fullName:"Alex Lazinica",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/12392/images/7282_n.png",biography:"Alex Lazinica is the founder and CEO of IntechOpen. After obtaining a Master's degree in Mechanical Engineering, he continued his PhD studies in Robotics at the Vienna University of Technology. Here he worked as a robotic researcher with the university's Intelligent Manufacturing Systems Group as well as a guest researcher at various European universities, including the Swiss Federal Institute of Technology Lausanne (EPFL). During this time he published more than 20 scientific papers, gave presentations, served as a reviewer for major robotic journals and conferences and most importantly he co-founded and built the International Journal of Advanced Robotic Systems- world's first Open Access journal in the field of robotics. Starting this journal was a pivotal point in his career, since it was a pathway to founding IntechOpen - Open Access publisher focused on addressing academic researchers needs. Alex is a personification of IntechOpen key values being trusted, open and entrepreneurial. Today his focus is on defining the growth and development strategy for the company.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"19816",title:"Prof.",name:"Alexander",middleName:null,surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/19816/images/1607_n.jpg",biography:"Alexander I. Kokorin: born: 1947, Moscow; DSc., PhD; Principal Research Fellow (Research Professor) of Department of Kinetics and Catalysis, N. Semenov Institute of Chemical Physics, Russian Academy of Sciences, Moscow.\r\nArea of research interests: physical chemistry of complex-organized molecular and nanosized systems, including polymer-metal complexes; the surface of doped oxide semiconductors. He is an expert in structural, absorptive, catalytic and photocatalytic properties, in structural organization and dynamic features of ionic liquids, in magnetic interactions between paramagnetic centers. The author or co-author of 3 books, over 200 articles and reviews in scientific journals and books. He is an actual member of the International EPR/ESR Society, European Society on Quantum Solar Energy Conversion, Moscow House of Scientists, of the Board of Moscow Physical Society.",institutionString:null,institution:{name:"Semenov Institute of Chemical Physics",country:{name:"Russia"}}},{id:"62389",title:"PhD.",name:"Ali Demir",middleName:null,surname:"Sezer",slug:"ali-demir-sezer",fullName:"Ali Demir Sezer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62389/images/3413_n.jpg",biography:"Dr. Ali Demir Sezer has a Ph.D. from Pharmaceutical Biotechnology at the Faculty of Pharmacy, University of Marmara (Turkey). He is the member of many Pharmaceutical Associations and acts as a reviewer of scientific journals and European projects under different research areas such as: drug delivery systems, nanotechnology and pharmaceutical biotechnology. Dr. Sezer is the author of many scientific publications in peer-reviewed journals and poster communications. Focus of his research activity is drug delivery, physico-chemical characterization and biological evaluation of biopolymers micro and nanoparticles as modified drug delivery system, and colloidal drug carriers (liposomes, nanoparticles etc.).",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"61051",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"100762",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"St David's Medical Center",country:{name:"United States of America"}}},{id:"107416",title:"Dr.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Texas Cardiac Arrhythmia",country:{name:"United States of America"}}},{id:"64434",title:"Dr.",name:"Angkoon",middleName:null,surname:"Phinyomark",slug:"angkoon-phinyomark",fullName:"Angkoon Phinyomark",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/64434/images/2619_n.jpg",biography:"My name is Angkoon Phinyomark. I received a B.Eng. degree in Computer Engineering with First Class Honors in 2008 from Prince of Songkla University, Songkhla, Thailand, where I received a Ph.D. degree in Electrical Engineering. My research interests are primarily in the area of biomedical signal processing and classification notably EMG (electromyography signal), EOG (electrooculography signal), and EEG (electroencephalography signal), image analysis notably breast cancer analysis and optical coherence tomography, and rehabilitation engineering. I became a student member of IEEE in 2008. During October 2011-March 2012, I had worked at School of Computer Science and Electronic Engineering, University of Essex, Colchester, Essex, United Kingdom. In addition, during a B.Eng. I had been a visiting research student at Faculty of Computer Science, University of Murcia, Murcia, Spain for three months.\n\nI have published over 40 papers during 5 years in refereed journals, books, and conference proceedings in the areas of electro-physiological signals processing and classification, notably EMG and EOG signals, fractal analysis, wavelet analysis, texture analysis, feature extraction and machine learning algorithms, and assistive and rehabilitative devices. I have several computer programming language certificates, i.e. Sun Certified Programmer for the Java 2 Platform 1.4 (SCJP), Microsoft Certified Professional Developer, Web Developer (MCPD), Microsoft Certified Technology Specialist, .NET Framework 2.0 Web (MCTS). I am a Reviewer for several refereed journals and international conferences, such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Industrial Electronics, Optic Letters, Measurement Science Review, and also a member of the International Advisory Committee for 2012 IEEE Business Engineering and Industrial Applications and 2012 IEEE Symposium on Business, Engineering and Industrial Applications.",institutionString:null,institution:{name:"Joseph Fourier University",country:{name:"France"}}},{id:"55578",title:"Dr.",name:"Antonio",middleName:null,surname:"Jurado-Navas",slug:"antonio-jurado-navas",fullName:"Antonio Jurado-Navas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/55578/images/4574_n.png",biography:"Antonio Jurado-Navas received the M.S. degree (2002) and the Ph.D. degree (2009) in Telecommunication Engineering, both from the University of Málaga (Spain). He first worked as a consultant at Vodafone-Spain. From 2004 to 2011, he was a Research Assistant with the Communications Engineering Department at the University of Málaga. In 2011, he became an Assistant Professor in the same department. From 2012 to 2015, he was with Ericsson Spain, where he was working on geo-location\ntools for third generation mobile networks. Since 2015, he is a Marie-Curie fellow at the Denmark Technical University. His current research interests include the areas of mobile communication systems and channel modeling in addition to atmospheric optical communications, adaptive optics and statistics",institutionString:null,institution:{name:"University of Malaga",country:{name:"Spain"}}}],filtersByRegion:[{group:"region",caption:"North America",value:1,count:5766},{group:"region",caption:"Middle and South America",value:2,count:5227},{group:"region",caption:"Africa",value:3,count:1717},{group:"region",caption:"Asia",value:4,count:10367},{group:"region",caption:"Australia and Oceania",value:5,count:897},{group:"region",caption:"Europe",value:6,count:15789}],offset:12,limit:12,total:118188},chapterEmbeded:{data:{}},editorApplication:{success:null,errors:{}},ofsBooks:{filterParams:{sort:"dateEndThirdStepPublish"},books:[{type:"book",id:"10231",title:"Proton Therapy",subtitle:null,isOpenForSubmission:!0,hash:"f4a9009287953c8d1d89f0fa9b7597b0",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10231.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10652",title:"Visual Object Tracking",subtitle:null,isOpenForSubmission:!0,hash:"96f3ee634a7ba49fa195e50475412af4",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10652.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10653",title:"Optimization Algorithms",subtitle:null,isOpenForSubmission:!0,hash:"753812dbb9a6f6b57645431063114f6c",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10653.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10655",title:"Motion Planning",subtitle:null,isOpenForSubmission:!0,hash:"809b5e290cf2dade9e7e0a5ae0ef3df0",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10655.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10657",title:"Service Robots",subtitle:null,isOpenForSubmission:!0,hash:"5f81b9eea6eb3f9af984031b7af35588",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10657.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10662",title:"Pedagogy",subtitle:null,isOpenForSubmission:!0,hash:"c858e1c6fb878d3b895acbacec624576",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10662.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10673",title:"The Psychology of Trust",subtitle:null,isOpenForSubmission:!0,hash:"1f6cac41fd145f718ac0866264499cc8",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10673.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10675",title:"Hydrostatics",subtitle:null,isOpenForSubmission:!0,hash:"c86c2fa9f835d4ad5e7efd8b01921866",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10675.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10677",title:"Topology",subtitle:null,isOpenForSubmission:!0,hash:"85eac84b173d785f989522397616124e",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10677.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10678",title:"Biostatistics",subtitle:null,isOpenForSubmission:!0,hash:"f63db439474a574454a66894db8b394c",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10678.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10679",title:"Mass Production",subtitle:null,isOpenForSubmission:!0,hash:"2dae91102099b1a07be1a36a68852829",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10679.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10684",title:"Biorefineries",subtitle:null,isOpenForSubmission:!0,hash:"23962c6b77348bcbf247c673d34562f6",slug:null,bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/10684.jpg",editedByType:null,editors:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],filtersByTopic:[{group:"topic",caption:"Agricultural and Biological Sciences",value:5,count:14},{group:"topic",caption:"Biochemistry, Genetics and Molecular Biology",value:6,count:3},{group:"topic",caption:"Business, Management and Economics",value:7,count:1},{group:"topic",caption:"Chemistry",value:8,count:7},{group:"topic",caption:"Computer and Information Science",value:9,count:6},{group:"topic",caption:"Earth and Planetary Sciences",value:10,count:7},{group:"topic",caption:"Engineering",value:11,count:15},{group:"topic",caption:"Environmental Sciences",value:12,count:2},{group:"topic",caption:"Immunology and Microbiology",value:13,count:3},{group:"topic",caption:"Materials Science",value:14,count:5},{group:"topic",caption:"Mathematics",value:15,count:1},{group:"topic",caption:"Medicine",value:16,count:24},{group:"topic",caption:"Neuroscience",value:18,count:1},{group:"topic",caption:"Pharmacology, Toxicology and Pharmaceutical Science",value:19,count:2},{group:"topic",caption:"Physics",value:20,count:2},{group:"topic",caption:"Psychology",value:21,count:4},{group:"topic",caption:"Social Sciences",value:23,count:2},{group:"topic",caption:"Technology",value:24,count:1},{group:"topic",caption:"Veterinary Medicine and Science",value:25,count:1}],offset:12,limit:12,total:187},popularBooks:{featuredBooks:[],offset:0,limit:12,total:null},hotBookTopics:{hotBooks:[],offset:0,limit:12,total:null},publish:{},publishingProposal:{success:null,errors:{}},books:{featuredBooks:[{type:"book",id:"10065",title:"Wavelet Theory",subtitle:null,isOpenForSubmission:!1,hash:"d8868e332169597ba2182d9b004d60de",slug:"wavelet-theory",bookSignature:"Somayeh Mohammady",coverURL:"https://cdn.intechopen.com/books/images_new/10065.jpg",editors:[{id:"109280",title:"Dr.",name:"Somayeh",middleName:null,surname:"Mohammady",slug:"somayeh-mohammady",fullName:"Somayeh Mohammady"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9644",title:"Glaciers and the Polar Environment",subtitle:null,isOpenForSubmission:!1,hash:"e8cfdc161794e3753ced54e6ff30873b",slug:"glaciers-and-the-polar-environment",bookSignature:"Masaki Kanao, Danilo Godone and Niccolò Dematteis",coverURL:"https://cdn.intechopen.com/books/images_new/9644.jpg",editors:[{id:"51959",title:"Dr.",name:"Masaki",middleName:null,surname:"Kanao",slug:"masaki-kanao",fullName:"Masaki Kanao"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9385",title:"Renewable Energy",subtitle:"Technologies and Applications",isOpenForSubmission:!1,hash:"a6b446d19166f17f313008e6c056f3d8",slug:"renewable-energy-technologies-and-applications",bookSignature:"Tolga Taner, Archana Tiwari and Taha Selim Ustun",coverURL:"https://cdn.intechopen.com/books/images_new/9385.jpg",editors:[{id:"197240",title:"Associate Prof.",name:"Tolga",middleName:null,surname:"Taner",slug:"tolga-taner",fullName:"Tolga Taner"}],equalEditorOne:{id:"186791",title:"Dr.",name:"Archana",middleName:null,surname:"Tiwari",slug:"archana-tiwari",fullName:"Archana Tiwari",profilePictureURL:"https://mts.intechopen.com/storage/users/186791/images/system/186791.jpg",biography:"Dr. Archana Tiwari is Associate Professor at Amity University, India. Her research interests include renewable sources of energy from microalgae and further utilizing the residual biomass for the generation of value-added products, bioremediation through microalgae and microbial consortium, antioxidative enzymes and stress, and nutraceuticals from microalgae. She has been working on algal biotechnology for the last two decades. She has published her research in many international journals and has authored many books and chapters with renowned publishing houses. She has also delivered talks as an invited speaker at many national and international conferences. Dr. Tiwari is the recipient of several awards including Researcher of the Year and Distinguished Scientist.",institutionString:"Amity University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Amity University",institutionURL:null,country:{name:"India"}}},equalEditorTwo:{id:"197609",title:"Prof.",name:"Taha Selim",middleName:null,surname:"Ustun",slug:"taha-selim-ustun",fullName:"Taha Selim Ustun",profilePictureURL:"https://mts.intechopen.com/storage/users/197609/images/system/197609.jpeg",biography:"Dr. Taha Selim Ustun received a Ph.D. in Electrical Engineering from Victoria University, Melbourne, Australia. He is a researcher with the Fukushima Renewable Energy Institute, AIST (FREA), where he leads the Smart Grid Cybersecurity Laboratory. Prior to that, he was a faculty member with the School of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA. His current research interests include power systems protection, communication in power networks, distributed generation, microgrids, electric vehicle integration, and cybersecurity in smart grids. He serves on the editorial boards of IEEE Access, IEEE Transactions on Industrial Informatics, Energies, Electronics, Electricity, World Electric Vehicle and Information journals. Dr. Ustun is a member of the IEEE 2004 and 2800, IEC Renewable Energy Management WG 8, and IEC TC 57 WG17. He has been invited to run specialist courses in Africa, India, and China. He has delivered talks for the Qatar Foundation, the World Energy Council, the Waterloo Global Science Initiative, and the European Union Energy Initiative (EUEI). His research has attracted funding from prestigious programs in Japan, Australia, the European Union, and North America.",institutionString:"Fukushima Renewable Energy Institute, AIST (FREA)",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"National Institute of Advanced Industrial Science and Technology",institutionURL:null,country:{name:"Japan"}}},equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"8985",title:"Natural Resources Management and Biological Sciences",subtitle:null,isOpenForSubmission:!1,hash:"5c2e219a6c021a40b5a20c041dea88c4",slug:"natural-resources-management-and-biological-sciences",bookSignature:"Edward R. Rhodes and Humood Naser",coverURL:"https://cdn.intechopen.com/books/images_new/8985.jpg",editors:[{id:"280886",title:"Prof.",name:"Edward R",middleName:null,surname:"Rhodes",slug:"edward-r-rhodes",fullName:"Edward R Rhodes"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9671",title:"Macrophages",subtitle:null,isOpenForSubmission:!1,hash:"03b00fdc5f24b71d1ecdfd75076bfde6",slug:"macrophages",bookSignature:"Hridayesh Prakash",coverURL:"https://cdn.intechopen.com/books/images_new/9671.jpg",editors:[{id:"287184",title:"Dr.",name:"Hridayesh",middleName:null,surname:"Prakash",slug:"hridayesh-prakash",fullName:"Hridayesh Prakash"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9313",title:"Clay Science and Technology",subtitle:null,isOpenForSubmission:!1,hash:"6fa7e70396ff10620e032bb6cfa6fb72",slug:"clay-science-and-technology",bookSignature:"Gustavo Morari Do Nascimento",coverURL:"https://cdn.intechopen.com/books/images_new/9313.jpg",editors:[{id:"7153",title:"Prof.",name:"Gustavo",middleName:null,surname:"Morari Do Nascimento",slug:"gustavo-morari-do-nascimento",fullName:"Gustavo Morari Do Nascimento"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9888",title:"Nuclear Power Plants",subtitle:"The Processes from the Cradle to the Grave",isOpenForSubmission:!1,hash:"c2c8773e586f62155ab8221ebb72a849",slug:"nuclear-power-plants-the-processes-from-the-cradle-to-the-grave",bookSignature:"Nasser Awwad",coverURL:"https://cdn.intechopen.com/books/images_new/9888.jpg",editors:[{id:"145209",title:"Prof.",name:"Nasser",middleName:"S",surname:"Awwad",slug:"nasser-awwad",fullName:"Nasser Awwad"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"9027",title:"Human Blood Group Systems and Haemoglobinopathies",subtitle:null,isOpenForSubmission:!1,hash:"d00d8e40b11cfb2547d1122866531c7e",slug:"human-blood-group-systems-and-haemoglobinopathies",bookSignature:"Osaro Erhabor and Anjana Munshi",coverURL:"https://cdn.intechopen.com/books/images_new/9027.jpg",editors:[{id:"35140",title:null,name:"Osaro",middleName:null,surname:"Erhabor",slug:"osaro-erhabor",fullName:"Osaro Erhabor"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"10432",title:"Casting Processes and Modelling of Metallic Materials",subtitle:null,isOpenForSubmission:!1,hash:"2c5c9df938666bf5d1797727db203a6d",slug:"casting-processes-and-modelling-of-metallic-materials",bookSignature:"Zakaria Abdallah and Nada Aldoumani",coverURL:"https://cdn.intechopen.com/books/images_new/10432.jpg",editors:[{id:"201670",title:"Dr.",name:"Zak",middleName:null,surname:"Abdallah",slug:"zak-abdallah",fullName:"Zak Abdallah"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}},{type:"book",id:"7841",title:"New Insights Into Metabolic Syndrome",subtitle:null,isOpenForSubmission:!1,hash:"ef5accfac9772b9e2c9eff884f085510",slug:"new-insights-into-metabolic-syndrome",bookSignature:"Akikazu Takada",coverURL:"https://cdn.intechopen.com/books/images_new/7841.jpg",editors:[{id:"248459",title:"Dr.",name:"Akikazu",middleName:null,surname:"Takada",slug:"akikazu-takada",fullName:"Akikazu Takada"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}}],latestBooks:[{type:"book",id:"9550",title:"Entrepreneurship",subtitle:"Contemporary Issues",isOpenForSubmission:!1,hash:"9b4ac1ee5b743abf6f88495452b1e5e7",slug:"entrepreneurship-contemporary-issues",bookSignature:"Mladen Turuk",coverURL:"https://cdn.intechopen.com/books/images_new/9550.jpg",editedByType:"Edited by",editors:[{id:"319755",title:"Prof.",name:"Mladen",middleName:null,surname:"Turuk",slug:"mladen-turuk",fullName:"Mladen Turuk"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10065",title:"Wavelet Theory",subtitle:null,isOpenForSubmission:!1,hash:"d8868e332169597ba2182d9b004d60de",slug:"wavelet-theory",bookSignature:"Somayeh Mohammady",coverURL:"https://cdn.intechopen.com/books/images_new/10065.jpg",editedByType:"Edited by",editors:[{id:"109280",title:"Dr.",name:"Somayeh",middleName:null,surname:"Mohammady",slug:"somayeh-mohammady",fullName:"Somayeh Mohammady"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9313",title:"Clay Science and Technology",subtitle:null,isOpenForSubmission:!1,hash:"6fa7e70396ff10620e032bb6cfa6fb72",slug:"clay-science-and-technology",bookSignature:"Gustavo Morari Do Nascimento",coverURL:"https://cdn.intechopen.com/books/images_new/9313.jpg",editedByType:"Edited by",editors:[{id:"7153",title:"Prof.",name:"Gustavo",middleName:null,surname:"Morari Do Nascimento",slug:"gustavo-morari-do-nascimento",fullName:"Gustavo Morari Do Nascimento"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9888",title:"Nuclear Power Plants",subtitle:"The Processes from the Cradle to the Grave",isOpenForSubmission:!1,hash:"c2c8773e586f62155ab8221ebb72a849",slug:"nuclear-power-plants-the-processes-from-the-cradle-to-the-grave",bookSignature:"Nasser Awwad",coverURL:"https://cdn.intechopen.com/books/images_new/9888.jpg",editedByType:"Edited by",editors:[{id:"145209",title:"Prof.",name:"Nasser",middleName:"S",surname:"Awwad",slug:"nasser-awwad",fullName:"Nasser Awwad"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8098",title:"Resources of Water",subtitle:null,isOpenForSubmission:!1,hash:"d251652996624d932ef7b8ed62cf7cfc",slug:"resources-of-water",bookSignature:"Prathna Thanjavur Chandrasekaran, Muhammad Salik Javaid, Aftab Sadiq",coverURL:"https://cdn.intechopen.com/books/images_new/8098.jpg",editedByType:"Edited by",editors:[{id:"167917",title:"Dr.",name:"Prathna",middleName:null,surname:"Thanjavur Chandrasekaran",slug:"prathna-thanjavur-chandrasekaran",fullName:"Prathna Thanjavur Chandrasekaran"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9644",title:"Glaciers and the Polar Environment",subtitle:null,isOpenForSubmission:!1,hash:"e8cfdc161794e3753ced54e6ff30873b",slug:"glaciers-and-the-polar-environment",bookSignature:"Masaki Kanao, Danilo Godone and Niccolò Dematteis",coverURL:"https://cdn.intechopen.com/books/images_new/9644.jpg",editedByType:"Edited by",editors:[{id:"51959",title:"Dr.",name:"Masaki",middleName:null,surname:"Kanao",slug:"masaki-kanao",fullName:"Masaki Kanao"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10432",title:"Casting Processes and Modelling of Metallic Materials",subtitle:null,isOpenForSubmission:!1,hash:"2c5c9df938666bf5d1797727db203a6d",slug:"casting-processes-and-modelling-of-metallic-materials",bookSignature:"Zakaria Abdallah and Nada Aldoumani",coverURL:"https://cdn.intechopen.com/books/images_new/10432.jpg",editedByType:"Edited by",editors:[{id:"201670",title:"Dr.",name:"Zak",middleName:null,surname:"Abdallah",slug:"zak-abdallah",fullName:"Zak Abdallah"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9671",title:"Macrophages",subtitle:null,isOpenForSubmission:!1,hash:"03b00fdc5f24b71d1ecdfd75076bfde6",slug:"macrophages",bookSignature:"Hridayesh Prakash",coverURL:"https://cdn.intechopen.com/books/images_new/9671.jpg",editedByType:"Edited by",editors:[{id:"287184",title:"Dr.",name:"Hridayesh",middleName:null,surname:"Prakash",slug:"hridayesh-prakash",fullName:"Hridayesh Prakash"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8415",title:"Extremophilic Microbes and Metabolites",subtitle:"Diversity, Bioprospecting and Biotechnological Applications",isOpenForSubmission:!1,hash:"93e0321bc93b89ff73730157738f8f97",slug:"extremophilic-microbes-and-metabolites-diversity-bioprospecting-and-biotechnological-applications",bookSignature:"Afef Najjari, Ameur Cherif, Haïtham Sghaier and Hadda Imene Ouzari",coverURL:"https://cdn.intechopen.com/books/images_new/8415.jpg",editedByType:"Edited by",editors:[{id:"196823",title:"Dr.",name:"Afef",middleName:null,surname:"Najjari",slug:"afef-najjari",fullName:"Afef Najjari"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9731",title:"Oxidoreductase",subtitle:null,isOpenForSubmission:!1,hash:"852e6f862c85fc3adecdbaf822e64e6e",slug:"oxidoreductase",bookSignature:"Mahmoud Ahmed Mansour",coverURL:"https://cdn.intechopen.com/books/images_new/9731.jpg",editedByType:"Edited by",editors:[{id:"224662",title:"Prof.",name:"Mahmoud Ahmed",middleName:null,surname:"Mansour",slug:"mahmoud-ahmed-mansour",fullName:"Mahmoud Ahmed Mansour"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},subject:{topic:{id:"1175",title:"Neuroplasticity",slug:"neuroplasticity",parent:{title:"Neurobiology",slug:"life-sciences-neuroscience-neurobiology"},numberOfBooks:3,numberOfAuthorsAndEditors:70,numberOfWosCitations:20,numberOfCrossrefCitations:14,numberOfDimensionsCitations:43,videoUrl:null,fallbackUrl:null,description:null},booksByTopicFilter:{topicSlug:"neuroplasticity",sort:"-publishedDate",limit:12,offset:0},booksByTopicCollection:[{type:"book",id:"6250",title:"The Hippocampus",subtitle:"Plasticity and Functions",isOpenForSubmission:!1,hash:"78f1e57726307f003f39510c175c3102",slug:"the-hippocampus-plasticity-and-functions",bookSignature:"Ales Stuchlik",coverURL:"https://cdn.intechopen.com/books/images_new/6250.jpg",editedByType:"Edited by",editors:[{id:"207908",title:"Dr.",name:"Ales",middleName:null,surname:"Stuchlik",slug:"ales-stuchlik",fullName:"Ales Stuchlik"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6092",title:"Neuroplasticity",subtitle:"Insights of Neural Reorganization",isOpenForSubmission:!1,hash:"1003fc63680b1c04e9135f3dea18a8c3",slug:"neuroplasticity-insights-of-neural-reorganization",bookSignature:"Victor V. Chaban",coverURL:"https://cdn.intechopen.com/books/images_new/6092.jpg",editedByType:"Edited by",editors:[{id:"83427",title:"Prof.",name:"Victor",middleName:null,surname:"Chaban",slug:"victor-chaban",fullName:"Victor Chaban"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5521",title:"Synaptic Plasticity",subtitle:null,isOpenForSubmission:!1,hash:"9eea3c7f926cd466ddd14ab777b663d8",slug:"synaptic-plasticity",bookSignature:"Thomas Heinbockel",coverURL:"https://cdn.intechopen.com/books/images_new/5521.jpg",editedByType:"Edited by",editors:[{id:"70569",title:"Dr.",name:"Thomas",middleName:null,surname:"Heinbockel",slug:"thomas-heinbockel",fullName:"Thomas Heinbockel"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:3,mostCitedChapters:[{id:"59437",doi:"10.5772/intechopen.74318",title:"Music and Brain Plasticity: How Sounds Trigger Neurogenerative Adaptations",slug:"music-and-brain-plasticity-how-sounds-trigger-neurogenerative-adaptations",totalDownloads:1392,totalCrossrefCites:2,totalDimensionsCites:6,book:{slug:"neuroplasticity-insights-of-neural-reorganization",title:"Neuroplasticity",fullTitle:"Neuroplasticity - Insights of Neural Reorganization"},signatures:"Mark Reybrouck, Peter Vuust and Elvira Brattico",authors:[{id:"196698",title:"Prof.",name:"Mark",middleName:null,surname:"Reybrouck",slug:"mark-reybrouck",fullName:"Mark Reybrouck"},{id:"209976",title:"Prof.",name:"Elvira",middleName:null,surname:"Brattico",slug:"elvira-brattico",fullName:"Elvira Brattico"},{id:"209977",title:"Prof.",name:"Peter",middleName:null,surname:"Vuust",slug:"peter-vuust",fullName:"Peter Vuust"}]},{id:"57827",doi:"10.5772/intechopen.71165",title:"A Role for the Longitudinal Axis of the Hippocampus in Multiscale Representations of Large and Complex Spatial Environments and Mnemonic Hierarchies",slug:"a-role-for-the-longitudinal-axis-of-the-hippocampus-in-multiscale-representations-of-large-and-compl",totalDownloads:734,totalCrossrefCites:3,totalDimensionsCites:6,book:{slug:"the-hippocampus-plasticity-and-functions",title:"The Hippocampus",fullTitle:"The Hippocampus - Plasticity and Functions"},signatures:"Bruce Harland, Marcos Contreras and Jean-Marc Fellous",authors:[{id:"210681",title:"Dr.",name:"Bruce",middleName:null,surname:"Harland",slug:"bruce-harland",fullName:"Bruce Harland"},{id:"210682",title:"Dr.",name:"Marco",middleName:null,surname:"Contreras",slug:"marco-contreras",fullName:"Marco Contreras"},{id:"210683",title:"Prof.",name:"Jean-Marc",middleName:null,surname:"Fellous",slug:"jean-marc-fellous",fullName:"Jean-Marc Fellous"}]},{id:"54143",doi:"10.5772/67127",title:"Plasticity of Dendritic Spines. Not Only for Cognitive Processes",slug:"plasticity-of-dendritic-spines-not-only-for-cognitive-processes",totalDownloads:974,totalCrossrefCites:0,totalDimensionsCites:6,book:{slug:"synaptic-plasticity",title:"Synaptic Plasticity",fullTitle:"Synaptic Plasticity"},signatures:"Ignacio González-Burgos, Dulce A. Velázquez-Zamora, David\nGonzález-Tapia, Nallely Vázquez-Hernández and Néstor I. Martínez-\nTorres",authors:[{id:"190521",title:"Dr.",name:"Ignacio",middleName:null,surname:"Gonzalez-Burgos",slug:"ignacio-gonzalez-burgos",fullName:"Ignacio Gonzalez-Burgos"},{id:"196267",title:"Dr.",name:"Dulce A",middleName:null,surname:"Velázquez-Zamora",slug:"dulce-a-velazquez-zamora",fullName:"Dulce A Velázquez-Zamora"},{id:"196269",title:"MSc.",name:"David",middleName:null,surname:"González-Tapia",slug:"david-gonzalez-tapia",fullName:"David González-Tapia"},{id:"196270",title:"MSc.",name:"Nallely",middleName:null,surname:"Vázquez-Hernández",slug:"nallely-vazquez-hernandez",fullName:"Nallely Vázquez-Hernández"},{id:"196271",title:"MSc.",name:"Nestor I",middleName:null,surname:"Martínez-Torres",slug:"nestor-i-martinez-torres",fullName:"Nestor I Martínez-Torres"}]}],mostDownloadedChaptersLast30Days:[{id:"59437",title:"Music and Brain Plasticity: How Sounds Trigger Neurogenerative Adaptations",slug:"music-and-brain-plasticity-how-sounds-trigger-neurogenerative-adaptations",totalDownloads:1390,totalCrossrefCites:2,totalDimensionsCites:6,book:{slug:"neuroplasticity-insights-of-neural-reorganization",title:"Neuroplasticity",fullTitle:"Neuroplasticity - Insights of Neural Reorganization"},signatures:"Mark Reybrouck, Peter Vuust and Elvira Brattico",authors:[{id:"196698",title:"Prof.",name:"Mark",middleName:null,surname:"Reybrouck",slug:"mark-reybrouck",fullName:"Mark Reybrouck"},{id:"209976",title:"Prof.",name:"Elvira",middleName:null,surname:"Brattico",slug:"elvira-brattico",fullName:"Elvira Brattico"},{id:"209977",title:"Prof.",name:"Peter",middleName:null,surname:"Vuust",slug:"peter-vuust",fullName:"Peter Vuust"}]},{id:"57312",title:"The Hippocampus as a Neural Link between Negative Affect and Vulnerability for Psychostimulant Relapse",slug:"the-hippocampus-as-a-neural-link-between-negative-affect-and-vulnerability-for-psychostimulant-relap",totalDownloads:944,totalCrossrefCites:1,totalDimensionsCites:4,book:{slug:"the-hippocampus-plasticity-and-functions",title:"The Hippocampus",fullTitle:"The Hippocampus - Plasticity and Functions"},signatures:"Jeffrey L. Barr, Brenna Bray and Gina L. Forster",authors:[{id:"145620",title:"Dr.",name:"Gina",middleName:null,surname:"Forster",slug:"gina-forster",fullName:"Gina Forster"},{id:"219827",title:"Dr.",name:"Jeffrey",middleName:null,surname:"Barr",slug:"jeffrey-barr",fullName:"Jeffrey Barr"},{id:"219828",title:"BSc.",name:"Brenna",middleName:null,surname:"Bray",slug:"brenna-bray",fullName:"Brenna Bray"}]},{id:"52720",title:"The Ghrelin Receptor Regulates Dendritic Spines and the NMDA Receptor–Mediated Synaptic Transmission in the Hippocampus",slug:"the-ghrelin-receptor-regulates-dendritic-spines-and-the-nmda-receptor-mediated-synaptic-transmission",totalDownloads:932,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"synaptic-plasticity",title:"Synaptic Plasticity",fullTitle:"Synaptic Plasticity"},signatures:"Masako Isokawa",authors:[{id:"191467",title:"Prof.",name:"Masako",middleName:null,surname:"Isokawa",slug:"masako-isokawa",fullName:"Masako Isokawa"}]},{id:"54566",title:"Introductory Chapter: Mechanisms and Function of Synaptic Plasticity",slug:"introductory-chapter-mechanisms-and-function-of-synaptic-plasticity",totalDownloads:1652,totalCrossrefCites:3,totalDimensionsCites:3,book:{slug:"synaptic-plasticity",title:"Synaptic Plasticity",fullTitle:"Synaptic Plasticity"},signatures:"Thomas Heinbockel",authors:[{id:"70569",title:"Dr.",name:"Thomas",middleName:null,surname:"Heinbockel",slug:"thomas-heinbockel",fullName:"Thomas Heinbockel"}]},{id:"58530",title:"Sleep Disorders in Multiple Sclerosis",slug:"sleep-disorders-in-multiple-sclerosis",totalDownloads:580,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"neuroplasticity-insights-of-neural-reorganization",title:"Neuroplasticity",fullTitle:"Neuroplasticity - Insights of Neural Reorganization"},signatures:"Montserrat González Platas and María Yaiza Pérez Martin",authors:[{id:"202099",title:"Dr.",name:"Montserrat",middleName:null,surname:"Gonzalez Platas",slug:"montserrat-gonzalez-platas",fullName:"Montserrat Gonzalez Platas"},{id:"231355",title:"Dr.",name:"Maria Yaiza",middleName:null,surname:"Perez Martín",slug:"maria-yaiza-perez-martin",fullName:"Maria Yaiza Perez Martín"}]},{id:"54067",title:"Neuroplasticity in Bipolar Disorder: Insights from Neuroimaging",slug:"neuroplasticity-in-bipolar-disorder-insights-from-neuroimaging",totalDownloads:1056,totalCrossrefCites:1,totalDimensionsCites:2,book:{slug:"synaptic-plasticity",title:"Synaptic Plasticity",fullTitle:"Synaptic Plasticity"},signatures:"Marlos Vasconcelos Rocha, Fabiana Nery, Amanda Galvão-de-\nAlmeida, Lucas de Castro Quarantini and Ângela Miranda-Scippa",authors:[{id:"192139",title:"Ph.D.",name:"Marlos",middleName:"Vasconcelos",surname:"Rocha",slug:"marlos-rocha",fullName:"Marlos Rocha"},{id:"192876",title:"Dr.",name:"Fabiana",middleName:null,surname:"Nery-Fernandes",slug:"fabiana-nery-fernandes",fullName:"Fabiana Nery-Fernandes"},{id:"192877",title:"Prof.",name:"Ângela",middleName:null,surname:"Miranda-Scippa",slug:"angela-miranda-scippa",fullName:"Ângela Miranda-Scippa"},{id:"192878",title:"Prof.",name:"Lucas",middleName:null,surname:"De Castro Quarantini",slug:"lucas-de-castro-quarantini",fullName:"Lucas De Castro Quarantini"},{id:"192879",title:"Dr.",name:"Giovanna",middleName:null,surname:"Ladeia-Rocha",slug:"giovanna-ladeia-rocha",fullName:"Giovanna Ladeia-Rocha"},{id:"192880",title:"Prof.",name:"Amanda",middleName:null,surname:"Galvão-de Almeida",slug:"amanda-galvao-de-almeida",fullName:"Amanda Galvão-de Almeida"}]},{id:"55453",title:"Synaptic Plasticity by Afferent Electrical Stimulation",slug:"synaptic-plasticity-by-afferent-electrical-stimulation",totalDownloads:1038,totalCrossrefCites:0,totalDimensionsCites:0,book:{slug:"synaptic-plasticity",title:"Synaptic Plasticity",fullTitle:"Synaptic Plasticity"},signatures:"Stefan Golaszewski",authors:[{id:"54888",title:"Prof.",name:"Stefan",middleName:null,surname:"Golaszewski",slug:"stefan-golaszewski",fullName:"Stefan Golaszewski"}]},{id:"53848",title:"Plasticity in Damaged Multisensory Networks",slug:"plasticity-in-damaged-multisensory-networks",totalDownloads:988,totalCrossrefCites:0,totalDimensionsCites:1,book:{slug:"synaptic-plasticity",title:"Synaptic Plasticity",fullTitle:"Synaptic Plasticity"},signatures:"Karolina A Bearss and Joseph FX DeSouza",authors:[{id:"192667",title:"Prof.",name:"Joseph",middleName:null,surname:"DeSouza",slug:"joseph-desouza",fullName:"Joseph DeSouza"},{id:"192780",title:"Ph.D.",name:"Karolina",middleName:"Anna",surname:"Bearss",slug:"karolina-bearss",fullName:"Karolina Bearss"}]},{id:"53927",title:"GABAergic Synapse Dysfunction and Repair in Temporal Lobe Epilepsy",slug:"gabaergic-synapse-dysfunction-and-repair-in-temporal-lobe-epilepsy",totalDownloads:1139,totalCrossrefCites:1,totalDimensionsCites:1,book:{slug:"synaptic-plasticity",title:"Synaptic Plasticity",fullTitle:"Synaptic Plasticity"},signatures:"Meghan A. Van Zandt and Janice R. Naegele",authors:[{id:"154904",title:"Prof.",name:"Janice",middleName:null,surname:"Naegele",slug:"janice-naegele",fullName:"Janice Naegele"},{id:"194530",title:"Ph.D. Student",name:"Meghan",middleName:null,surname:"Van Zandt",slug:"meghan-van-zandt",fullName:"Meghan Van Zandt"}]},{id:"57827",title:"A Role for the Longitudinal Axis of the Hippocampus in Multiscale Representations of Large and Complex Spatial Environments and Mnemonic Hierarchies",slug:"a-role-for-the-longitudinal-axis-of-the-hippocampus-in-multiscale-representations-of-large-and-compl",totalDownloads:732,totalCrossrefCites:3,totalDimensionsCites:6,book:{slug:"the-hippocampus-plasticity-and-functions",title:"The Hippocampus",fullTitle:"The Hippocampus - Plasticity and Functions"},signatures:"Bruce Harland, Marcos Contreras and Jean-Marc Fellous",authors:[{id:"210681",title:"Dr.",name:"Bruce",middleName:null,surname:"Harland",slug:"bruce-harland",fullName:"Bruce Harland"},{id:"210682",title:"Dr.",name:"Marco",middleName:null,surname:"Contreras",slug:"marco-contreras",fullName:"Marco Contreras"},{id:"210683",title:"Prof.",name:"Jean-Marc",middleName:null,surname:"Fellous",slug:"jean-marc-fellous",fullName:"Jean-Marc Fellous"}]}],onlineFirstChaptersFilter:{topicSlug:"neuroplasticity",limit:3,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[{type:"book",id:"10176",title:"Microgrids and Local Energy Systems",subtitle:null,isOpenForSubmission:!0,hash:"c32b4a5351a88f263074b0d0ca813a9c",slug:null,bookSignature:"Prof. Nick Jenkins",coverURL:"https://cdn.intechopen.com/books/images_new/10176.jpg",editedByType:null,editors:[{id:"55219",title:"Prof.",name:"Nick",middleName:null,surname:"Jenkins",slug:"nick-jenkins",fullName:"Nick Jenkins"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter"}}],offset:8,limit:8,total:1},route:{name:"book.detail",path:"/books/telemedicine-techniques-and-applications",hash:"",query:{},params:{book:"telemedicine-techniques-and-applications"},fullPath:"/books/telemedicine-techniques-and-applications",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()