In-Ga-Zn-O-TFT differential amplifier comparison.
\\n\\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
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Scattering of light by molecules can be elastic, Rayleigh scattering, or inelastic, Raman scattering. In the elastic case, the photon’s energy and the state of the molecule after the scattering events are unchanged. Hence, Rayleigh scattered light does not contain much information on the structure of molecular states [1]. In inelastic scattering, the frequency of photons of monochromatic light changes upon interaction with the vibrational states, or modes, of a molecule. The effect was postulated theoretically by Smekal et al. in 1923 but was first discovered experimentally by C.V. Raman in 1928 in an experiment using the sun as a light source [2, 3, 4]. In Raman scattering, two inelastic processes can occur:
Stokes process: An incident photon hν0 excites a molecular vibration hνvib and is thus scattered with the corresponding difference in energy h(ν0 − νvib) (red shift).
Anti-Stokes process: The photon acquires vibrational energy and is scattered with a higher energy h(ν0 + νvib) (blue shift).
This shift provides information about vibrational, rotational, and other low-frequency transitions in molecules. Raman spectroscopy can be used to study solid, liquid, and gaseous samples.
Raman scattering can be explained using the molecular polarizability [5]. If a molecule is placed in an electric field, electrons and nuclei get displaced. Due to the separation of charged species, an electric dipole moment is induced in the molecule, and it is said to be polarized. If E is the strength of the electric field and μ is the magnitude of the induced dipole moment, then
where α is the polarizability of the molecule. If a sample is subjected to an electromagnetic wave of frequency ν, the electric field experienced by each molecule of the sample varies as
where E0 is the amplitude of the electromagnetic wave. From Eq. (1)
Thus, Eq. (3) implies that interaction of electromagnetic radiation of frequency ν induces a molecular dipole moment that oscillates and emits radiation of the same frequency, and this is the classical explanation of Rayleigh scattering. However, the ability to perturb the local electron cloud of a molecular structure depends on the relative location of the individual atoms; hence, the polarizability is a function of the instantaneous position of the constituent atoms. So, the polarizability changes with small displacement from equilibrium position (i.e., molecular vibration) and is given by
where α0 is equilibrium polarizability and qeq and q are bond lengths at equilibrium position and any instant, respectively. If a molecule executes simple harmonic motion, the displacement can be represented as
where νvib is the vibrational frequency of a molecule and qmax is the maximum separation distance between atoms relative to their equilibrium position. Substituting Eq. (5) into Eq. (4) gives
Substituting Eq. (6) into Eq. (3) gives
or
or
The first term in Eq. (9) represents Rayleigh scattering and occurs at the excitation frequency ν. The second and third terms correspond to Stokes (ν − νvib) and anti-Stokes (ν + νvib) scattering. In both inelastic scatterings, the excitation frequency is modulated by the vibrational frequency of the bond.
Besides, from Eq. (9), the molecules that have Raman-active vibration modes must experience a change in polarizability during a vibration
Raman scattering can be easily understood in terms of the quantum theory of radiation. In the quantum model, the molecules exist in quantized energy levels corresponding to possible stationary states of the molecule. When radiation having an energy hν incident on a sample, it is considered that the photons undergo collisions with the molecules. When the collision is elastic, the photons will be deflected unchanged, but it is also possible that during the collision, energy is exchanged between the photon and molecule, and as a result, the molecule can gain or lose energy ΔE, where ΔE = hνvib represents a difference in the vibrational or rotational energy levels of that molecule [6]. In quantum mechanical terms, the scattering can be considered as an excitation to a virtual state lower in energy than a real electronic state. When the molecule gains energy ΔE, the photon will be scattered with energy hν − hνvib, and the scattering is known as Stokes’ scattering. Conversely, if the molecule loses energy ΔE, the scattered photon will have energy hν + hνvib, and this type of scattering is known as anti-Stokes’ scattering. Generally, Stokes’ radiation is stronger than the anti-Stokes’ radiation. Figure 1 illustrates the energy level diagram for scattering [7].
Energy level diagram for Rayleigh and Raman scattering, where ΔE = hνvib represents the difference in vibration energy levels [7].
One of the limitations of the Raman effect is that it is a very weak phenomenon. About one in 107 photons undergo Raman scattering. Therefore the Raman signal is very low from low concentrations of the analyte or poor Raman scatterers. Sometimes the high fluorescence from the molecule obscures the Raman signals. Surface-enhanced Raman spectroscopy (SERS) is all about amplifying Raman signals from molecules, by several orders of magnitude [8]. SERS is a technique where molecules undergo much higher scattering efficiencies when adsorbed on metal colloidal nanoparticles or rough metal surfaces. The SERS effect was discovered in 1974 by Fleischmann et al. [9]. The group discovered an anomalously large enhancement of the Raman signal of pyridine in the presence of a roughened silver electrode. The enhancement was initially attributed to greater than expected, or fractal-like, surface area, but subsequent reports showed that the anomalous intensity could not be accounted for by increased surface area and was, in fact, a new phenomenon, giving rise to the idea of the SERS cross-section [10, 11]. However, while SERS has become a large and extremely active field of study, there is still a debate on the exact details of its mechanism and its magnitude [12, 13].
Since then, several enhancement mechanisms were proposed in the early days of SERS. However, only two mechanisms are now broadly accepted, i.e., electromagnetic (EM) theory and chemical enhancement (CE) theory [8, 14, 15]. The electromagnetic models treat the molecule as a point dipole which responds to the enhanced local fields at or near the metal surface [16]. These enhanced fields, in turn, arise from roughness features that couple the incident field to surface plasmons [17]. On the other hand, chemical models attribute SERS intensity to modification of the molecular polarizability by interaction with the metal with ensuing molecular resonances, giving rise to enhancements such as those associated with resonance Raman scattering [18]. CE theory depends on the chemical interaction between probe molecules and the noble metal and is said to contribute only a maximum of about two to three orders of magnitude [19]. Both of these enhancements work simultaneously but are yet to be fully understood because of the difficulties in investigating the enhancements separately. Considering that the Raman signal is proportional to the square of dipole moment,
where
From Eq. (10), it follows that the Raman intensity can be enhanced in three ways:
by increasing the number of molecules that are on the metal surface compared to the smooth surface;
by increasing the Raman cross section; and
by increasing the electromagnetic surface averaged intensity enhancement factors.
Experiments have proved that by increasing the surface roughness, the number of absorbed molecules was changed only a few times, leaving us with the last two possibilities. They are electromagnetic (EM) and chemical contributions to the enhancement of Raman signal.
CE requires the probe to be chemically bound to the SERS substrate. The CE can be grouped into three contributions to the chemical mechanism: (i) a resonance Raman (RR) effect due to the incident light matching an electronic transition in the molecule (103–106 contribution), (ii) a charge-transfer (CT) effect where the incident light is in resonance with a metal-molecule or molecule-metal transition. (10–104 contribution), (iii) a nonresonant chemical (CHEM) effect due to ground-state orbital overlap between the molecule and the metal (≤10–100 contribution) [21].
RR is a molecular resonance mechanism that arises from the incident light being resonant with a molecule, and without a metal surface, this leads to resonance Raman scattering. RR involves the formation of a surface complex involving the metal and the analyte, leading to a change in the properties of the molecule (such as the possibility of resonance Raman scattering). The RR effect is typically thought of as a molecular property, and it has been included as a SERS mechanism since the presence of the metal surface can alter where this resonance lies. The CT effect only appears when the molecule and metal are close enough to allow for a sufficient overlap of their wave functions. In this mechanism, tunneling of electrons between the metal and adsorbate molecules takes place. Due to the transfer of an electron from metal to molecule or from molecule to metal, a negative ion is formed. Enhancement occurs when the energy of the negative ion is resonant with the incident photon. This mechanism is explained by considering the molecule and metal system as a whole. It is considered that the Fermi level of the metal layer lies between the molecular ground level and one or more excited states of the molecule. The charge transfer mechanism is short-ranged (0.1–0.5 nm) and strongly dependent on the geometry, bonding, and the molecule energy level [22]. The CHEM effect is the least studied and most difficult to quantify experimentally due to its small contribution to the overall enhancement. The formation of metal-molecular complexes mainly causes the CHEM effect due to chemical bonding [23]. This modifies the ability of the dipole to radiate energy, i.e., it can effectively oppose or amplify the dipole amplitude (Figure 2).
Schematic diagram of the four-step process of the photon-driven charge transfer model for a molecule adsorbed on an electrode.
In theory, EM enhancement is analyte independent, while CE is probe-dependent and requires some chemical interaction to the metal surface [24]. Most of SERS enhancements are due to the EM enhancement mechanism and are a direct consequence of the roughness present on the noble metal surfaces [25]. The nanostructure can be formed on the substrate itself or by depositing noble metal nanoparticles. These metal nanoparticles can interact with the excitation light because of unique properties caused by their low dimensions (10–100 nm). The small size of the metal nanoparticles makes a special kind of light-induced electric polarization possible for their surface electrons. Collective oscillations of these electrons, driven by the alternating electric field of the light wave, are called surface plasma oscillations. At a particular frequency, plasmon oscillations are resonant with light; then electric field intensity and Raman scattering from the molecules attached to the nanostructures are enhanced [8, 26]. A locally strong light-induced electric field of plasmons in metal nanoparticle causes the increase of
The surface electron oscillations in metal nanoparticles can be derived from the classical Drude model, describing metal as a lattice of ions immersed into the “gas” consisting of the free electrons [27, 28]. In a static electric field, the internal field of the metals, generated by the displacement of free electrons, shield the external electric field. As a result, the external electrostatic field cannot create the electric field inside the metal. As a result, if electrostatic fields are applied to the metals, their dielectric permittivity is ambiguous. The dielectric permittivity is the measure of how much the electric field inside a material differs from that of a vacuum. However, when a high-frequency electric field is applied, the free electrons inside the metal cannot completely follow in time with the high-frequency oscillations of the electric field. It creates a situation where at very high frequencies, metal can pass the electric field from the incident light, i.e., behave as a dielectric. The high transparency of these metals in the ultraviolet region can be explained by the fact that they have a lot of free electrons. Electrons of such metals as Al, Cu, Au, and Ag are not completely free but partially bounded.
The surface plasmon frequency
Hence at the resonant frequency
From Eq. (12), it follows that the permittivity of metal should have a negative value. Few metals such as Cu, Ag, and Au exhibit strong visible light plasmon resonance, whereas other transition metals show only broadband in the ultraviolet region. Ag, in particular, is suitable for SERS applications in the visible and near IR because it has a tiny imaginary component in this region and thus is less “lossy” than other metals [30].
When monochromatic radiation of frequency ν0 and electric filed E interacts with a molecule, it induces a Raman dipole oscillating at a frequency
The electromagnetic field at the metallic surface can be dramatically increased and may result in a possible local field enhancement.
The radiation properties of the Raman dipole, μ, are affected by the metallic environment and may result in a possible radiation enhancement.
Raman spectrum can give rich information of analyte molecules, and SERS due to its higher signal intensity make it possible to detect analyte molecules in very low concentration, which enhances its practical applications [21]. This technique has a large number of applications in various fields, including trace chemical detection [21, 36], such as dye molecules [37, 38, 39], food additives [40, 41], pesticide trace detection [42, 43, 44], bioanalysis [45, 46, 47, 48, 49], and explosive detection [50, 51]. The detection of a trace amount of hazardous chemicals is also in high demand because of the increasing threat from toxic environments and unreliable food safety [52]. Melamine is a chemical compound and has been widely used in milk and pet food as an additive to increase protein percentage. However, since 2007, melamine, with its contaminant cyanuric acid, has become prominent because of the milk scandal. As a facile and simple spectroscopy technique, SERS has been used to detect melamine content [53, 54]. Apart from this, SERS has been widely used for bioanalysis, i.e., in the detection of biomolecules [55], cancer diagnosis [56, 57], urine component detection [58, 59], and in vivo molecular probing in live cells [60, 61], which play an important role in the life science for health care or treatment. Biomolecules, such as DNA, can also be detected using SERS [62, 63].
Transition metal dichalcogenides, as the names suggest, are a class of material that is made up of the transition metals (M = Mo, W, Ta, Pt) and chalcogenides (X = S, Se, Te). The unit cell of bulk MX2 consists of X–M–X units, where one M plane is sandwiched between two X planes. Depending upon how these units are stacked, different kinds of polytypes are formed, for example:
1T (one X–M–X unit in the unit cell, octahedral coordination, tetragonal symmetry, T stands for trigonal)
2H (two X–M–X layers per repeat unit, trigonal prismatic coordination, hexagonal symmetry, H stands for hexagonal)
3R (three X–M–X layers per repeat unit, trigonal prismatic coordination, rhombohedral symmetry, R stands for rhombohedral)
The schematic diagram of these polytypes is given in Figure 3.
Structural representation of 1T, 2H, and 3R TMC polytypes and their corresponding metal atom coordination. The side and top view of layered forms are shown [61].
In recent years, Raman spectroscopy is adopted to address the challenges in the characterization of these TMDs due to: (1) Many possible structures (generally the stacking of layers has a rotational (or translational) freedom with reference to an axis perpendicular to (or also along) a 2D plane, giving them non-uniqueness); (2) weak interlayer interaction, which is much smaller than the intralayer interactions; and (3) observation of inner layers (the physical properties of each layer within the stacked TMDs are not selectively accessible except for the outermost layer). Other than resolving these challenges, Raman spectroscopy can identify functional groups, structural damage, unwanted by-products, and chemical modifications introduced during synthesis, processing, or its placement on the various substrates during device fabrication. It is spectroscopy, which is nondestructive, quick, and noninvasive for characterizing the TMD materials with high selectivity [64, 65, 66].
In general, the Raman spectroscopy has been widely used to determine the layers of the TMDs. For all the layered materials, which also includes TMDs, there are typically two categories of Raman vibrations. One is intralayer vibrations, which occur within a layer and normally appear in the high-frequency region of the spectra. The second category of Raman vibrations is observed due to the relative motion of the layers. These vibrations give the interlayer Raman modes, which are normally observed in the low-frequency region of the spectra (<100 cm−1).
In the layered TMDs, to determine the number of layers N for few-layer TMDs, high-frequency intralayer Raman modes can be used [67, 68]. For example, the layer number (N) dependence of the peak position and width for
(a) Raman spectra of NL-(N = 1–8, 10, 14 and 18) and bulk MoS2. The two gray-dashed lines indicate Pos(E2g1 E1 2g) and Pos(A1g) in bulk MoS2. (b) Frequency (ω) of E2g1 and A1g and the frequency difference (Δω) between E2g1and A1g as a function of 1/N. For 1 ≤ N ≤ 5, the linear fitting gives Δω(A–E) =25.8–8.4/N. (c) Polarized Raman spectra of 1–5L and bulk WS2, with the frequencies of E2g1and A1g frequency difference, I(A1g)/I(E2g1), and peak width summarized in (d) [66, 73].
The position of (
However, these two modes would decrease in frequency from 2L to 1L based on the linear chain model (only van der Waals interactions are included). This unexpected behavior of
Molina-Sanchez et al. [72] carefully examined and reported the relationship between the number of monolayers and the Raman active modes (A1g and
In the case of the WS2, the proximity of the 2LA(M) and
Conducting polymers are widely used in organic light-emitting diodes, heterojunction diodes, organic thin-film transistors, solar cells, actuators, sensors, etc. [75, 76, 77, 78, 79]. Poly(3,4-ethylenedioxythiophene)-poly(styrene sulfonate) (PEDOT:PSS) is extensively used conducting polymer because of its high conductivity, excellent thermal stability, transparency, structural stability. PEDOT:PSS polymer is a promising candidate as a transparent electrode for optoelectronic devices. The solvent treatment of PEDOT:PSS films may affect the conformation of the polymer. The structure of the PEDOT chain changes from benzoid to quinoid structure after solvent treatment [75, 80]. The effect of the conformation of the PEDOT chains in the PEDOT:PSS film before and after the dimethyl sulfoxide (DMSO) treatment was studied by Raman spectroscopy. Figure 5 shows the Raman spectra of PEDOT:PSS with different concentrations of DMSO. The most obvious change was observed for the strongest band between 1400 and 1500 cm−1. The highly conductive PEDOT:PSS film exhibits a narrower band. This change is similar to that of PEDOT:PSS film treated with ethylene glycols reported by Xia et al. [81]. These vibrational modes correspond to the stretching vibrations of Cα = Cβ on the five-member ring of PEDOT.
Raman spectra of PEDOT:PSS films with 0–8 vol.% DMSO.
The band at 1440 cm−1 is associated with the Cα〓Cβ symmetric vibration. The band near about 1368 cm−1 is associated with the Cβ▬Cβ stretching. Raman peaks located at 1508 and 1568 cm−1 are associated with the Cα〓Cβ asymmetric stretching vibrations. The band at 1540 cm−1 has been related to the splitting of these asymmetrical stretching vibrations [79, 81, 82, 83, 84]. Two kinds of resonant structures have been proposed for PEDOT, namely, benzoid and quinoid structure. For coil conformation, benzoid structure is the favorite structure, and quinoid structure is the favorite structure for linear and expanded-coil structure. Both benzoid and quinoid resonant structures exist simultaneously in pristine PEDOT:PSS film. The benzoid structure may be transformed into the quinoid structure after DMSO treatment so that quinoid structure becomes dominant in the highly conductive PEDOT:PSS film. The conducting PEDOT:PSS films are vastly used in optoelectronic devices.
“SERS substrates” are any nanostructured metallic platform that supports plasmon resonance and amplifies Raman signals [85]. Herein, SERS substrates are classified into two broad distinctions:
Random morphology SERS substrates include roughened electrodes, metallic silver and gold colloids, metal-island film on planer substrate, and other related substrates.
Ordered or periodic metallic SERS substrates include arrays of regular morphology metallic nanotextures created on planar substrates using nanolithography and other physical vapor deposition techniques.
Random morphology SERS substrates are inhomogeneous and are not highly reproducible [86]. Roughened electrodes are the most primitive SERS substrate and were discovered by Fleischmann et al. [9]. These substrates are typically created by running the redox cycle in an electrochemical cell containing a metallic salt solution. Such substrates have gained popularity due to an ability to adjust electrode potential to understand the charge transfer phenomenon between adsorbate and metallic surface [87]. Regardless, the importance of this substrate is decreasing substantially due to relatively low enhancement factors.
Among the random morphology SERS substrates, silver or gold colloids are the most common substrates used in both early and more recent studies. Since colloids are easy to produce in a laboratory and tend to generate large enhancement factors, most researchers are still involved in colloid-based SERS rather than more sophisticated substrates [88, 89]. Metallic colloids are also of historic significance related to SERS development, as the first single-molecule SERS detection was reported using colloid substrates [90]. In colloid-based methods, nanoparticle size and geometry can be controlled by altering experimental conditions. One of the most popular methods for controlling nanoparticle morphology stems from the polyol synthesis of silver nanocubes by Sun and Xia [78]. In addition to the nanocubes, various groups have produced octahedra and cuboctahedra [91] and octapods [92]. El-Sayed et al. have contributed to the control of particle morphology, yielding a variety of interesting and useful structures [93, 94, 95]. Since the size, shape, and material of the particles govern the resulting plasmonic resonance characteristics, significant effort has been exerted in the control of plasmon resonance via core-shell and alloyed particles, to which the Halas group has a large contribution [96, 97, 98].
SERS substrates have also been fabricated by depositing nanoparticles onto different surfaces. These simple deposition approaches include micro pipetting [99], soaking [100], screen-printing [101], filtration [102], and inkjet printing [103]. However, a major concern with these simple deposition processes is that the hotspots are generated and distributed randomly over the substrate. The differences in metallic particle sizes and their shapes due to the differences in preparation recipes can lead to several orders of magnitude difference in the SERS enhancement factor.
In order to obtain more consistent hotspots from nanoparticles, researchers have explored both self-assembly [99] and directed assembly techniques, such as the Langmuir-Blodgett techniques [91], to create regular arrays of nanoparticles. However, these techniques also introduce more complexity to the fabrication process.
Although metallic colloidal particles are known for their high SERS EF and possibility to accomplish SERS spectra of a single molecule, it is often challenging to reproduce or routinely deliver such a high performing SERS feature. To overcome this issue, a few alternatives have been introduced on engineering periodic arrays of metallic nanostructured SERS substrates. Nanosphere lithography (NSL), developed by Van Duyne et al., is one of the most extensively used nano-fabrication procedures used in understanding SERS phenomena and performing plasmonic-based sensing [104, 105, 106]. It involves the assembly of polystyrene nanospheres into a regular array, using this as a mask to create periodic nanostructures, sometimes called “metal island films,” by the evaporation of Ag or Au through the gaps created by the packing of the nanospheres, followed by removal of the nanospheres. A variation on this method, called “metal film over nanospheres,” is to evaporate a metal film directly onto the nanosphere template, using closely-packed nanospheres to pattern the substrate surface itself [107]. Electron beam lithography (EBL) is another most widely used conventional nanofabrication technique in designing uniform and controlled morphology SERS substrates [108, 109]. In the literature, there are many SERS-active surface designs prepared with EBL [110, 111]. These designs are mainly periodic arrays of simple nano-structures, and generally, the relation between the LSP resonance wavelength and SERS signal enhancement is studied. For example, Le Ru et al. have taken SERS measurements, from periodic gold dot, square, and triangle arrays, from “Rhodamine 6G” [112]. They demonstrated that the localized plasmon resonances, which are at the origin of visible-NIR extinction spectra and the SERS effect, can be tuned to any desired wavelength by varying the particle shape/size and spacing, thus tuning the Raman amplification. In a very similar study, Gunnarsson et al. studied similar Ag structures on a silicon wafer for the same molecule and reported that better results are obtained than nano-roughened Ag film [110]. They investigated the size and geometry dependence of the SERS effect on supported particles, by manufacturing artificial structures by modern nanofabrication techniques. Arrays of 100–200 nm silver particles of different shapes were prepared on a Si wafer by electron beam lithography. Kahl et al. have shown that the SERS measurements of “Rhodamine 6G” on gold periodic nano-dot arrays and grating structures resulted in order of magnitude better SERS enhancement when compared with metal-island film substrates [113]. They demonstrated two different methods of substrate fabrication by e-beam lithography. In the first method, regular fields of nanoparticles are produced by the lift-off technique. A silver layer is evaporated on the structured resist, and the resist is removed afterward. In the second method, gratings or crossed gratings are transferred into a silicon wafer with a thermal oxide surface layer by reactive ion etching (RIE). Then, the e-beam resist is removed, and finally, a silver layer is evaporated. Hatab et al. have demonstrated significant SERS enhancement factors exceeding 1011, resulting from a new configuration of elevated gold bowtie nano-antenna arrays with optimized array periodicity [114]. A process combining nanofabrication steps of pattern definition by EBL, metal deposition, lift-off, and RIE arranged in a particular sequence was used to fabricate the elevated gold bowtie arrays on Si wafers. The elevated bowties allow the manifestation of intrinsic plasmonic coupling effects in suspended nanocavities, or the tip-to-tip nanogaps, from structures that are not in physical contact with a substrate. This configuration results in up to two orders of additional magnitude enhancement in SERS response compared to that of nonelevated bowtie arrays. The diversity of designs is endless when fabrication with EBL is considered. However, these techniques, while excellent at making SERS substrates with defined characteristics, are hampered by the slow, serial nature and high cost of the processes used in their fabrication.
The SERS enhancement strongly depends on the substrate. As already discussed earlier, various techniques have been proposed and identified for the fabrication of the SERS substrate. However, only a few methods are available to develop uniform, reproducible, robust, stable, and cost-effective SERS substrates. Recently, silver columnar thin films fabricated by glancing angle deposition (GLAD) have been identified as high sensitivity SERS active substrates [115, 116, 117, 118, 119, 120, 121, 122]. A remarkable SERS enhancement factor with applications in sensing the biomolecules at very low concentrations has been observed on the silver nanorod arrays [123]. To understand the SERS mechanism and attain a maximum possible enhancement, large numbers of studies have been performed on the Ag nanorod (AgNR) arrays. In an interesting study, Chaney et al. have investigated the SERS response as a function of the nanorod length using trans-1,2-bis(4-pyridyl)ethane (BPE) as a probe molecule at an excitation wavelength of 785 nm [124]. They found that the SERS intensity increases dramatically with nanorod length. Zhou et al. fabricated aligned, single-crystalline AgNRs on planar Si substrates by GLAD technique, with sample substrate cooled by liquid nitrogen in the e-beam deposition system [125]. They were successful in detecting aqueous solution of 10−12 molL−1 Rhodamine 6G by the porous Ag film with nanorods. They also deposited AgNRs on Ag, Al, Si, and Ti thin films with a thickness of 100 and 400 nm, respectively, to achieve layers with different reflectivities. The SERS intensity of the AgNRs grown on Ag thin film was found to be higher than others, and the SERS intensity of the AgNRs on Al film was larger than that on Ti film, and the AgNRs on Si film showed the minimum SERS intensity. They concluded that the larger the under-layer reflectivity, the larger the SERS performance of substrate. So, the pre-deposition of Ag layer under AgNRs can be an effective way to promote the SERS performance of AgNRs. Zhang et al. have made AgNRs in film grow into periodic patterns at a micro-nano scale, and they showed that the AgNR film with periodic patterns exhibits better SERS performance than Ag film with nanorods arranged randomly as before [126]. He et al. also reported a new scalable strategy based on dynamic shadowing growth (DSG) to fabricate large-scale chiral Swiss roll nanostructures. They developed a chiral conical Swiss roll nanostructure by helically stacking Ag films on a SiO2 frustum with SiO2 films as insulating layers [127]. They also showed that the chiral dichroism (CD) spectral feature can be tuned by changing the bead diameter. They achieved a broadband CD response in visible to near-IR region by making the bead diameter a few hundred nanometers. Mark et al. combined the low-temperature shadow deposition with nanoscale patterning to fabricate nanocolloids with anisotropic three-dimensional shapes, feature sizes down to 20 nm [128]. They first deposited a uniform hexagonal array of Au nanodots deposited onto a Si wafer by micellar nanolithography. Then they deposited material onto the substrate by physical vapor deposition at grazing incidence. To reduce the adatoms’ mobility and reduce the diffuse during growth, they cooled the substrate. So, by combining the uniform nano-seeding and low-temperature growth, they fabricated various complex hybrid nanostructures of many materials like from Al2O3, Ti, and Cu. GLAD has also emerged as a powerful tool for the fabrication of 3D chiral plasmonic nanostructures. Titus et al. investigated the optical properties of Ti-doped Ag helices in the visible and near-infrared ranges using transmission ellipsometry and spectroscopy fabricated by GLAD [129]. Nair et al. reported the fabrication of wafer-scale 3D chiral nanoplasmonic substrates with different dielectric templates, namely, silica, magnesium fluoride, and titanium dioxide using GLAD [130]. They have also investigated the effect of interparticle separation on the chiroptical response of chiral nanohelices [131].
Hence, we can see that the development of fabrication and application of substrates for SERS is driven by nanotechnology and the development of high-end fabrication processes. Increasingly SERS substrates with high sensitivity and reproducibility are invented by electrochemical deposition, physical vapor deposition of the metal film, metal nanoparticle colloids, and so forth and applied into various fields, such as detection of pollutants at trace level, surface analysis, biomolecule, and bacteria detection. With the development of SERS substrate, advancement in Raman spectrometers, and tip-enhanced Raman scattering (as the combination of SERS and atomic force microscopy), SERS is becoming increasingly popular as a detection and diagnostic tool.
Active matrix OLED (AMOLED) displays are today’s mainstream consumer displays available in various form factors, such as smart watches, mobile displays, and large area television. They are highly appealing because of their wide viewing angles, nice color saturation and great potential for curved, flexible and/or rollable format. There are several options for (flexible) backplane technologies based on thin-film transistors (TFTs), namely, metal-oxide TFTs (such as indium gallium zinc oxide or IGZO), low-temperature polycrystalline silicon (LTPS) TFTs, or a combination of IGZO and LTPS, more precisely LTPO or low-temperature polycrystalline silicon and metal oxide. All these technologies have their pros and cons. Among others, IGZO semiconductors are n-type only which is sufficient for a backplane driving an OLED but is less adequate for peripheral circuits. Another key important asset of IGZO is the ultralow source-drain leakage current due to the large bandgap of the semiconductor, enabling long retention times of data storing, i.e., pixels are not leaking. In contrary, LTPS has both n- and p-type devices and thus the capability of CMOS circuits. LTPS transistors can drive larger currents due to the intrinsically higher mobility, enabling complex in-pixel compensation schemes and peripheral circuits. However, with LTPS transistors the leakage will be larger. This is a key reason why LTPO has been developed: this technology combines the ultralow leakage current of IGZO and a p-type LTPS transistor resulting in a hybrid complementary technology. An OLED is an organic LED emitting light directly proportional to its forward current. Therefore it requires a current source as driver in the pixel. In many cases, this is achieved by placing a TFT in series with the OLED and driving it in saturation.
\nIn this chapter, we will investigate the potential to embed additional functionalities in the display. Therefore, several strategies will be discussed focusing on improving the resolution of the current displays, by technology optimization introducing photolithography patterning of the OLED and by design evaluating external compensation vs. internal compensation. The extra space in the pixel, due to the combination of photolithography and simple pixel circuit, provides opportunities to include extra functions at the same original area. The focus in this book chapter is to add a photosensitive detector for fingerprint and palmprint readout.
\nResolution (number of pixels) and pixel pitch (size and spacing of pixels) are two main parameters defining the architecture of the display arrays. The first, expressed typically in megapixels, is standardized by the content type, resulting in different generations of TVs: VGA, full HD, 4K, and, most recently, 8K. The latter, expressed typically in pixels per inch (ppi) or pixels per degree (ppd), is used as a benchmark for smartphones, with high-end models featuring densities in the range of 600 ppi. This is a value that gives a good enough image quality for hand-held devices, with the viewing distance of approximately 30 cm (1 foot). At the same time, future near-to-eye augmented reality/virtual reality (AR/VR) displays impose ultrahigh definition, as the pixel density needs to be beyond the pattern resolving capabilities of the human retina (30 cycles per degree) [1, 2]. The resolution should be maximized to provide the highest possible output within the eye box in any given point of the 180° field of view (FOV), also to enable foveated rendering. An aperture ratio close to unity will eliminate the screen door effect and ensure natural experience. Transparency is necessary to avoid sense of isolation from the real-world view and to diversify from the virtual reality (VR) headsets (Figure 1). To realize all of the above, we need both the microdisplay-like pixel pitch down-scaling [3] and the flat-panel-display-like (FPD) backplane size up-scaling [4, 5]. Switching to advanced nodes in flat panel backplane manufacturing can result in ultrahigh-definition, direct-view AR displays fabricated in a cost-effective way.
\nColor-by-white vs. RGB OLED frontplane can be fabricated on top of CMOS or TFT backplane. Each combination is suitable for different applications.
In order to realize an ultrahigh resolution display, all elements of the system (backplane, frontplane, and driving) need to provide appropriate pixel density. On the frontplane side, several options for the light source can be chosen (Figure 2). OLED technology currently dominates the smartphone display industry not only with performance but also with the cost structure. In this case, the colors are defined by depositing separate device stacks for each color, which is typically referred to as side-by-side, red-green-blue (RGB) array. In OLED TVs, one common white OLED stack is combined with a color filter array (CFA). The limitation of the side-by-side RGB array is the pixel density, limited by the fine metal masking (FMM) technology, which uses deposition through a metal mesh. The white OLED array can achieve very small pixel pitch, which is only limited by the backplane and CFA resolution but imposes brightness loss due to CF transmission. Patterning multicolor OLEDs by photolithography can address the needs of ultralow pixel pitch for the future AR displays by realizing side-by-side OLED stacks with extreme density.
\nVarious display configuration options.
Patterning OLEDs by photolithography is an emerging, disruptive fabrication technique. The main challenge is the extreme chemical sensitivity of OLED materials with solvent, moisture, air, and temperature exposure responsible for performance degradation. The choice of appropriate photolithography chemistry is crucial, with fluorinated [6] or non-fluorinated systems [7] as the dominant options. Figure 3 shows the concept of using a negative-type photoresist to define patterns on top of OLED in a subtractive approach. First, the OLED stack is deposited as a plain layer over the entire substrate, on top of a pixel definition layer (PDL). This defines the active area of the light emitter. Second, photoresist is deposited on top of the entire substrate. Then, it is exposed through a lithography mask and developed to obtain the required pattern. Afterwards, the OLED layers that are not covered by the photoresist are etched away (typically with dry etching, such as reactive ion etch). In the end, the photoresist is stripped to achieve patterned OLED islands.
\nProcess flow for photolithography patterning of OLED stacks.
Photolithography allows pattern transfer beyond 1 μm resolution, enabling high-density lines and spaces. Transfer of small islands means that, with appropriate alignment (e.g., with an i-line stepper), a pixel density of a few thousand pixels per inch (ppi) can be realized. Transfer of openings means that pixel spacing can be minimized, resulting in a high aspect ratio. This is applicable for both TFT-based flat panel displays and CMOS-based microdisplays. Tests on patterning the OLED emission layer have shown that it is possible to achieve 1 μm pitch lines and spaces (Figure 4). Furthermore, the photoluminescence signal of the EML is maintained proving compatibility of this process with OLED material. 1 μm presented here is not a fundamental limit of the approach but rather a limit of the lithography mask design used in the experiment.
\nOLED patterns of 1, 2, 3 and 4 μm: optical and corresponding photoluminescence pictures of red EML patterned as lines (left) and spaces (right).
The achievable pixel density of the frontplane is limited not only by the photoresist used but also by the critical dimension (CD) and alignment/overlay accuracy of the litho tools used. In the i-line steppers typical for flat panel manufacturing, the achievable CD is 1.5 μm with an overlay between 0.25 and 0.5 μm. In contrast, CMOS fabs used for microdisplay manufacturing feature more advanced semiconductor nodes, with 248 nm KrF or 193 nm ArF light sources. Assuming a minimum PDL opening (defining the active area) of 500 nm, a 1.5 μm node imposes a density limit of 3500 ppi (for RGB) with an aperture ratio below 5%. Going to KrF steppers, the achievable density increases to 10,000 ppi while keeping the aperture ratio above 35%. This demonstrates the need of a tooling upgrade for future AR displays, both for the frontplane and the backplane. Denser and more efficient packing of pixels requires scaling down of the technology node, especially in FPD manufacturing.
\nOLED patterning by photolithography means that the deposition of the stack is interrupted (vacuum break) and the photoresist interacts with the organic materials. In the most simple case, the photolithography process is performed in a clean room in ambient atmosphere. The devices are loaded back into the glove box after the etch step for each color and after the photoresist strip when all colors are finished. This raises a serious challenge for the device lifetime. If the process is not optimized for compatibility with the stack, the current-voltage-luminance (IVL) curve shifts to the right (increased turn-on voltage) and to the bottom (reduced luminance). As a consequence, the brightness of the patterned OLED drops very fast and disappears even after a few minutes (Figure 5). Optimization of the photoresist system, of the OLED stack [8] and of the fabrication process, is needed to achieve OLED performance enabling implementation into devices. At imec, we demonstrated phosphorescent green OLED with T90 lifetime of >150 h at the starting brightness of 1000 nit. Efficiency remained above 85 cd/A before and after patterning. Current performance is considered an important step on the path to industrial technology readiness level, estimated to be T97 of at least 1000 h (for the green stack) [8].
\nIVL and lifetime curves for reference OLED and the possible effects of degradation by patterning.
\nFigure 6 shows an example comparison of unpatterned and patterned OLED lifetime curve at initial brightness of 1000 nit. The performance improvement can bring the two curves closer together.
\nLifetime curves of a phosphorescent green OLED at 1000 nit starting brightness for unpatterned and patterned stack.
OLED photolithography was used to fabricate passive displays with a 1400 × 1400 pixel array (almost 2 megapixels). 6 μm metal lines and 10 μm line pitch with SiN pixel definition layer (PDL) were used on glass substrate. Green and red OLED stacks were deposited by thermal evaporation in ultrahigh vacuum. After deposition of the first color (until above emission layer), photoresist was spin-coated, baked, exposed, and developed. Then, the OLED stack not covered by the photoresist was removed by dry etching. After that, the sample went back to the ultrahigh vacuum chamber for second color deposition, and the patterning process was repeated, this time finishing with stripping the photoresist. A semitransparent top contact stack was subsequently deposited, and the display was encapsulated with cavity glass. Both colors can be driven separately, and the PDL design allows for emission of a fixed image specified for each color (Figure 7). Subpixel pitch of 10 μm resulted in smooth edges and excellent feature representation. The device was tested for tens of hours with both colors on. No drop of brightness nor appearance of defects could be observed [9].
\nPassive 1250 ppi patterned OLED display with 1400 × 1400 pixels, 10 μm subpixel pitch, and independent color driving: general view (left) and detailed view for different color drivings (right).
This fabrication process is compatible with both CMOS backplanes and flexible TFT backplanes. The frontplane can thus be implemented in an active matrix display. Of course, photolithography can be used several times to realize more colors for a full-color display.
\nTo increase the display resolution, not only the technology (backplane and frontplane) but also the pixel driving techniques should be optimized. The OLED light output is dependent on the drain current of the driving TFTs of the AMOLED displays. Due to inherent variations in AMOLED displays, some compensation methods to the drain current of the TFTs are required to achieve uniform brightness. This can be implemented through either in-pixel compensation [10] or external compensation [11, 12]. Since in-pixel compensation schemes typically require more transistors inside the pixel, external compensation methods are preferred for high-resolution applications. Figure 8 shows pixel circuits and a possible layout for in-pixel compensation, using an 8T1C [10] pixel, and external compensation using a 3T2C [11] and, respectively, a 2T1C [12] pixel. For all these layouts, the same design rules were used. It is clear from this figure that a display with external compensation, especially the 2T1C pixel circuit, can achieve a much higher pixel density.
\nPixel circuits and corresponding layouts for (left) 8T1C, (middle) 3T2C, and (right) 2T1C pixels.
The achievable pixel density depends on both the pixel circuit and the design rules imposed by the technology, such as the critical dimension (CD) of the lithography tool. Figure 9 compares the achievable resolutions for different CDs for the 8T1C, the 3T2C, and the 2T1C pixel circuit. Although the CD of 1.5 μm, as currently achievable with typical i-line steppers, only yields a maximum pixel density of 565 ppi for the 8T1C pixel circuit, the same CD already yields a significant improvement for the pixel circuits using external compensation, namely, 847 ppi for the 3T2C pixel circuit and 1210 ppi for the 2T1C pixel circuit, respectively. Furthermore, improvements in technology allowing smaller CD will even further increase the achievable pixel density, up to 9070 ppi for the 2T1C pixel circuit, when using a CD of 0.2 μm.
\nPixel resolution vs. critical dimension (CD) for various pixel schemes.
The compensation principle for the 3T2C pixel circuit relies on the fact that applying a voltage on the backgate of a transistor will shift the threshold voltage (VT) of that transistor. By applying the correct compensation voltage to the backgate of the drive transistor of each pixel, all VT variations can be eliminated, resulting in a more uniform display. This compensation method uses three different modes of operation for the display. The first mode of operation is the calibration mode. In this mode, the correct compensation voltage is determined for each pixel by applying a certain reference voltage to the frontgate and measuring the current through the pixel while varying the backgate. When the measured current matches a predetermined reference current, the voltage on the backgate is the correct compensation voltage, which will be stored both on the capacitor connected to the backgate and in external memory. Once the correct backgate voltage is set for every pixel, the display can be switched to normal operation. In this mode, the display is driven with the normal video data, which is written to the frontgate of each pixel. Since the CAL signal is low in this mode, the charge on the capacitor will remain, and hence the backgate voltage will be the compensated voltage. However, due to leakage, this charge will slowly change over time. Therefore, a third mode of operation is added, namely, the calibration refresh. In this mode, the SEL signal is kept low, but the CAL signal is running through the display, while the compensation data is applied to the data lines. This way the compensation voltage is restored on the backgate, to ensure the VT uniformity remains over time. This compensation method shows a significant improvement in current variation, as demonstrated in Figure 10.
\nCurrent variation of a 3T2C display before and after compensation.
The current through the drive TFT (IDS), and thus through the OLED, when operating in saturation regime can be calculated for a certain data voltage (VGS) by using Eq. (1):
\nCompensating only for VT can eliminate variations in current for one gray level; however, if the β-factor is different for each pixel, the current will still vary for different gray values, even after VT compensation. This is shown in Figure 11 for the 3T2C pixel. As a consequence, we propose a new compensation method to compensate for both β and VT variations. Similarly as the previous described compensation method, we will first characterize the current through each pixel for multiple data voltages, whereafter the measurements are fitted to Eq. (1).
\nCurrent variation of a 3T2C and 2T1C display before and after compensation.
For each pixel, the extracted β and VT values are stored. Based on these values, the VGS voltages can be calculated for each pixel by the driver IC for each desired gray level by using Eq. (2):
\nThis calculation is relative simple and straightforward, as it only requires a multiplication, a subtraction, and a square root calculation, which enables to display real-time video content by using this methodology. Figure 11 shows the current variation improvements directly obtained from our AMOLED displays, by utilizing the VT-only compensation method and comparing it to the VT and β compensation method. As mentioned above, the simple VT compensation method provides good variation results for a small range, whereas the combined parameter method improves the variation across all desired gray levels.
\nFingerprint sensor arrays (Figure 5.1) [13] are becoming a mainstream security mechanism for mobile devices and are today available as autonomous silicon-based component. The integration of the fingerprint sensor array together with AMOLED displays [14, 15, 16] would benefit the footprint of the mobile device and the functionality, enabling detection of multiple fingers at once or even a palmprint.
\nFingerprint sensors combined with AMOLED displays can be realized in three different configurations for the sensor pixels: (1) in the same plane of the display pixels and (2) under and (3) over the display pixels (Figure 12). With sensors in the same plane, the display module gains optical sensing capability by incorporating photodetector pixels between OLED pixels. Sensors, under or above the display, require a separate fingerprint module. A fingerprint module under the display would need a semitransparent display and light scattering management. A fingerprint module over the display requires a transparent imager to avoid changes in display emission. In the previous section, we have demonstrated that a higher resolution backplane can be achieved at the same critical dimension by introducing external compensation methods. This combined with the photolitho-based patterning method of OPD and OLED will the crucial enablers for such a configuration as analyzed in Paragraph 3.
\nFingerprint integration configurations in AMOLED displays.
The pixel circuit architecture of the sensor array can be either passive or active [17]. The passive pixel is depicted in Figure 13 and is comprised by the photoelement, a capacitor, and a select TFT. The main difference of the active pixel is that it requires an extra TFT acting as a local amplifier. For high-resolution applications, the active pixel is not recommended, since its footprint is larger than the footprint of passive pixels.
\nBlock diagram of the proposed in-panel fingerprint sensor array with integrated CSA for each line, multiplexer (MUX), and ADC. Power and driving electronics remain off-panel.
The integration of peripheral readout circuitry in panel side-by-side with the display peripherals is beneficial for resolution, connectivity, and potential lower system cost of the device. In this paragraph TFT-based integrated readout is demonstrated by using our IGZO n-type only TFTs.
\nThe necessary blocks to implement an in-panel readout system are a charge sense amplifier (CSA), a multiplexer (MUX), and an analog to digital converter (ADC). The CSA is reading out the charge stored in each pixel of the array. The MUX is multiplexing the CSA outputs directly to the ADC, decreasing the number of the required ADC converters. The ADC is converting the analog voltage received from the CSA to a digital code. Various TFT-based analog blocks have been demonstrated in the literature [18, 19, 20, 21, 22, 23, 24]. Metal-oxide TFT technologies are preferable due to uniformity over large areas, very low leakage currents, and lower cost over area. In the following section, fast and small footprint ADCs and charge sense amplifiers (CSA) are discussed to meet the specifications of an in-panel fingerprint array.
\nIn Figure 13, the high-level block diagram of the in-panel readout system is shown. The five main blocks are detailed: a two-dimensional (2-D) image sensor array, the CSAs connect on each row of the array, a multiplexer connects four or more rows (MUX), and ADC connects to every MUX and off-panel power and driving electronics. Each column of the 2D image sensor array is readout from the corresponding row by a CSA. The pixels are readout subsequently enabled by the “SELECT” signals from the columns and converted to digital code through the MUX and an ADC. The MUX enables a larger footprint for the ADC, up to 4 to 8 times larger compared to a single line (50 μm). Hence, the ADC and MUX needs to be 4 to 8 times faster than the CSA. A 1–2 fps readout of 1M pixel imager (1000 × 1000 pixels) sets a readout speed of 1–2 kS/s per line for each CSA. This translates to 4–8 kS/s for the ADC if a 4:1 MUX is used or 8–16 kS/s for a 8:1 MUX. The slower ADC configuration sets the specification limitation to the width of the ADC to 200 μm, whereby the faster allows a width of 400 μm.
\n\nFigure 14 (a) depicts the cross section of the dual-gate self-aligned metal-oxide (MO) technology on a 15-μm-thick polyimide film [25, 26]. The metal-oxide (IGZO or ITZO) TFTs are fabricated with two metal gates (M0, M1) and source-drain metal contacts (M2). An additional metal layer (M3), not shown in the cross section, is beneficial for footprint but also for performance and noise. The CSA experimental results shown in the following sections are designed with an extra metal layer, also used as anode layer.
\n(a) Cross section of dual-gate self-aligned metal-oxide technology on flexible polyimide substrate and (b) extracted on-current (ION) from experimental data of 480/20 (μm/μm) dual-gate self-aligned ITZO (red) and IGZO (orange) TFTs.
\nFigure 14(b) shows the distribution of the extracted on-current (ION) from the measured transfer characteristics of 480/20 (μm/μm) IGZO (red) and ITZO (orange) dual-gate TFTs. The IGZO TFTs exhibits a median ION of 54.4 μA, whereas the ITZO dual-gate TFT exhibits a median of 250.4 μA. Although the ION of the ITZO TFT is 5 times larger, the normalized spread of ION to the median over the wafer is double (15.4% for ITZO and 8.8% for IGZO). Threshold voltage is also extracted from the same measurements, yielding 1.16 V (and σVt = 242 mV) for ITZO and 1.77 V (and σVt = 94 mV) for IGZO TFTs. The 480/20 TFT is the largest footprint TFT used in the implemented designs. In Figure 15, microphotos of the (a) ADC and (b) the L = 3 μm CSA are shown.
\nMicrophotos of the (a) ADC and (b) L = 3 μm CSA on flexible substrate.
The schematic of the CSA is shown in the Figure 16(a). The schematic of the operational amplifier (OPAMP) used in the CSA is shown in Figure 16(b). The OPAMP comprises a differential pair and a load that is driven by a two-stage buffer, initiated by a start-up circuit. The driver consists of two diode-connected load inverters as input and output stages. The output stage is driven by a start-up circuit to initialize the operation and provide ~1 loop gain positive feedback bias to the n-type load of the differential amplifier such that gate voltage follows source voltage. A buffer is also included at the output nodes A and B to increase the speed of the amplifier.
\nSchematic of (a) charge sense amplifier (CSA) and (b) the OPAMP schematic using dual-gate self-aligned TFTs used in the CSA in (a).
The experimental results of open-loop experiments of the OPAMP are shown in Figure 17 for dual-gate self-aligned IGZO TFTs of minimum channel length of L = 5 μm. The maximum gain for the 5 μm design is 43.2 dB with a phase margin of 52°. Both parameters are critical for stable closed-loop operation of an OPAMP. The obtained bandwidth (BW) is 1.4 kHz, and gain-bandwidth reaches 205 kHz. These specs are compared to other publications in the state-of-the-art Table 1 using TFTs. The footprint of the CSA is 0.28 mm2 with the capacitors. The footprint of the CSA can be decreased to 0.07 mm2 if 3 μm design is implemented. These footprints will result in a bezel width of 5.5 mm (L = 5 μm) and 1.3 mm (L = 3 μm) [27] for a 50 μm pixel size.
\nExperimental bode plots of the OPAMP using dual-gate self-aligned IGZO technology for L = 5 μm.
Circuit | \nThis work | \n2018 [11] | \n2012 [8] | \n2013 [10] | \n2014 [9] | \n
---|---|---|---|---|---|
Supply (V) | \n15 | \n15 | \n10.5 | \n5 | \n50 | \n
Gain (dB) | \n43 | \n32 | \n~21 | \n18.7 | \n19.2 | \n
GBW (kHz) | \n205 | \n140 | \n2 | \n472 | \n100\n*\n\n | \n
pm (o) | \n52 | \n53 | \n50\n*\n\n | \nneg | \n46 | \n
Area (mm2) | \n0.28 | \n0.3 | \n\nDiscrete\n | \n2.08 | \n— | \n
Substrate | \nPI | \nPI | \n\n | PI | \nGlass | \n
L (μm) | \n5 | \n5 | \n10 | \n6 | \n10 | \n
In-Ga-Zn-O-TFT differential amplifier comparison.
Estimated.
The successive approximation C-2C architecture is selected as ADC architecture, due to the low power dissipation and the 0.1% uniformity of metal-insulator-metal capacitors across large-area thin-film wafers. The schematic of the ADC is shown in Figure 18. The comparator is the most critical building block of the ADC for speed and accuracy. To improve the accuracy of the comparator, open-loop offset cancelation [28] is used. The response of a L = 5 μm dual-gate self-aligned TFT-based comparator at 10 kHz for two inputs ΔVin = 0 and 10 mV is shown in Figure 19. The offset of the comparator is minimized to less than 10 mV using open-loop cancelation, even though the Vt variation of the TFTs is one order larger.
\nThe implemented SADG TFT ADC block diagram driven with offset compensation.
Measured comparator output with auto-zero offset cancelation for designs using TFTs of minimum L = 5 μm at 10 kHz.
The experimental results of the reconstructed samples from a sinusoidal analog wave applied at the input of the IGZO ADC are shown in Figure 20(a). The IGZO ADC achieves 6-bit resolution at a sampling speed of 133 S/s at 15 V power supply using a L = 20 μm comparator. The clock speed of the IGZO ADC is at 2 kHz matching the bandwidth of the comparator, and 15 clocks are required to complete the conversion. Two options are available to increase the sampling speed of the ADC as set by the specification for 1–2 fps fingerprint readout: channel length downscaling and/or change of TFT technology or change of ADC architecture to flash but then for 6-bit the area might increase dramatically due to the multiple resistors needed and 64 comparators.
\n(a) The applied analog input of 2.061 Hz sinewave signal to the ADC and the reconstructed output points from the digital output of the ADC at a clock frequency of 2 kHz for IGZO and (b) the applied analog input of 15.625 Hz sinewave to the 15 kHz clocked ITZO ADC and the reconstructed output.
The minimum length of the TFTs of the measured ADC is L = 20 μm. The length of the TFT of the comparator of the ADC defines the speed of the circuit. In Figure 19 the response of the L = 5 μm comparator is shown validating 10 kHz operation, 5 times faster compared to the 20 μm comparator used in the ADC. This indicates that 5 μm comparator can increase the sampling speed by 5 times.
\nAnother option to enable a larger increase of the ADC speed is to introduce ITZO TFT for the ADC. ITZO TFT exhibits 5 times larger ION which leads to faster responses [Figure 20(b)]. The ITZO ADC achieves a similar bit resolution of the applied sinusoidal wave at 1 kS/s sampling speed and at 10 V supply voltage. Combining both ITZO and downscaling of the length of the TFTs of the comparator will lead to sampling speeds above 4 kS/s as required for the in-panel readout system of 1 fps. The power dissipation of the ITZO ADC is at 550 μW at 10 V power supply and at 110 μW at 15 V power supply for the IGZO implementation.
\nIn conclusion, TFT-based in-panel analog circuits for 1 fps readout of a fingerprint or palmprints array is presented in this paragraph. The circuit blocks can be integrated side-by-side to the flat panel display with integrated sensor array. Two analog blocks are discussed, being an analog to digital converter and charge sense amplifier. ADCs and CSA downscaling to 5 μm including a 500% ION boost of the ITZO TFTs enable the 4 kS/s operation specifications for the in-panel readout circuits. The use of complementary technologies such as LTPS or LTPO would result an increased performance for important parameters such as the gain-bandwidth and the resolution and speed of the ADC. This will enable a better optimized system for this application.
\nIn this book chapter, we have discussed a roadmap to include additional functionalities on displays by adding a fourth pixel to the display. The purpose of the fourth pixel in this work was a photodetector pixel to realize an in-panel fingerprint or palmprinting function. Several options have been discussed to enable this roadmap. At first, we have elaborated several techniques to realize higher-resolution frontplane (OLED) and TFT backplanes. For the frontplanes, photolitho patterning of the OLED was introduced as a disruptive technology impacting significantly the frontplane resolution. External compensation techniques for the backplane when driving OLEDs are proposed in this book chapter, resulting in a uniform and higher-resolution display by using only 2T1C schemes. As photodetector pixel, we proposed a passive 1 T pixel, with included peripheral circuits to enable a lower system cost.
\nIntechOpen's Authorship Policy is based on ICMJE criteria for authorship. An Author, one must:
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