Radiation particle types, their flux, and energies on the lunar surface [72, 73, 74, 75, 76, 77, 78].
\r\n\tThis book will intend to look at different migrant patterns, voluntary and involuntary migration, over the last three centuries. What influenced people to leave their home countries, family, and friends and settle somewhere else? The book may include histories of the 19th century, consider tragedies and movements activated by political events in the 20th century, and/or look at recent events of the 21st century. Push and pull factors are important points. While most of us may be influenced in a negative way by the current happenings in Eastern Europe, the Russian invasion and resulting tragedies also demonstrate some very positive human traits – the preparedness of Ukraine’s surrounding countries to help those in need and to provide a safe place for the present.
\r\n\tWhether one looks at voluntary or involuntary migration into any country, after a period of adjustment, migrants do play a positive role. The research found that migrants contribute to the economy (food, shelter, employment, tax) and enrich a country’s cultural norms. Prerequisites for successful settlements are that the host society adopts a tolerant approach and that the migrants recognize the law and the language of the host country. Nothing is ever easy or without controversy, but I am a migrant (German Australian), and life in Australia has been relatively harmonious. Issues that could be considered in the book are multicultural societies (do monocultural societies still exist?) and theories of acculturation versus integration (settlement processes).
\r\n\tTwo further issues are very important in relation to human migration. There is climate change, global warming, and the environment, which clearly affect people’s movement. Small island populations are very concerned about rising sea levels. 2021 has also seen floods costing human lives: Turkey (August 2021), Brazil (December 2021), Chile (January 2021), and South India (November 2021), to name but a few. In Australia (March 2022), farms and whole townships in New South Wales and Queensland have been flooded for the second time in five years, and plans to resettle these towns are considered. Official and social media provide ample coverage of the events, which leads me to the next issue. There is today’s very important role of the media, of the official and social media. We are constantly bombarded with images of human war tragedies and flood victims. People in industrialized, western countries must be the best-informed populace. How far do the images and up-to-date TV news influence us, make us change our behavior, and perhaps even consider us more generous than we have been?
\r\n\tClimate change and the media are relatively new to the human migration debate, but both issues play important parts, and some interesting discussions are appreciated.
\r\n\t
Preparing for life on another planet or a planetary object requires an enormous effort from scientists and engineers [1]. The first steps toward extraterrestrial life are the crewed missions to the Moon, aiming to build the basis for the future long-term presence of humans beyond Earth. A remarkable amount of research and feasibility studies are being done by the European Space Agency (ESA) in Europe [2] and the National Aeronautics and Space Administration (NASA) in the USA [3, 4] on how to construct a “new home in space,” in a manner to eliminate the need for supply materials from Earth.
In this context, the use of space resources is one of the key directions in preparation for future human missions to the Moon. The so-called
In space and on the lunar surface, there are many factors potentially leading to damage in materials, such as exposure to vacuum, extreme thermal conditions, impact collisions with micrometeoroids, and radiation [14]. Among these, radiation is considered particularly harmful for different functional components and instruments of spacecraft and lunar surface missions. Radiation can induce structural defects that evolve from nanoscale to micro- and macro-damage, causing degradation of the mechanical, thermal, and electrical properties of materials or can even lead to direct failure in electronic signals before interacting with the very structural composition of the material. Therefore, improving the radiation resistance of materials to be used in space missions and searching for more radiation-resistant materials is of utmost importance. The research effort is directed toward finding composite materials that can better withstand radiation and other challenges faced by mission components in space and on space bodies and exhibit self-healing capabilities [15].
In this chapter, we first introduce some relevant materials for two of the most critical applications on the Moon, i.e., habitat construction and energy production. Then, we provide an overview of the radiation environment on the lunar surface and different radiation effects that can be induced in materials by such an environment. We then discuss the ways of combining traditional methods commonly used to study radiation effects with recent advanced approaches in materials modeling and provide examples of radiation-effects modeling studies on different materials. Additionally, we discuss the possibilities of using novel promising materials with exceptional properties relevant for space exploration, with an emphasis on their radiation resistance.
NASA has identified the most important components of the lunar mission as (i) design and construction of habitats and (ii) resource and power management [16]. In particular, the emphasis is on lightweight materials that will be critical for mass reduction and thus increase the science return of the mission. Both components mentioned above will strongly rely on ISRU, i.e.,
Constructing a habitat on the Moon can be done in two ways, by delivering materials from Earth and by using local resources. Although the latter option is more sustainable, the first one cannot be completely avoided. An important consideration that needs to be made when choosing materials is the type of habitat. NASA considers several types of habitat for different use, namely rigid (metals, alloys, and concrete) [18], inflatable (e.g., inflatable concrete [19]), or hybrid structures, as well as underground construction [20]. Depending on the type of habitat, different materials will be used [16, 21]. For example, unprocessed lunar regolith may be used for radiation shielding of habitat (e.g., lunar regolith geopolymer) [22, 23, 24, 25], as well as for construction when converted into concrete [26, 27], 3D-printed [28, 29, 30], or processed into other construction material (e.g., bricks and glass) [16, 21]. For materials delivered from Earth, it is crucial to ensure their low weight, as well as resistance to very high and very low temperatures (which change from 127°C in the daytime to −173°C at night on the Moon surface) and radiation, durability, reusability, and structural reliability [16].
Metals and alloys are essential structural materials for construction given their compressive strength and good tensile properties and for other applications, such as energy carrier/storage (wires) [31] or equipment (e.g., excavation tools, molds, and rovers) [32]. Al, Ca, Fe, Ti, and Mg are the most abundant metals in the lunar regolith, which also contains smaller amounts of Ni, Cr, Mn, Zr, and V [5, 20]. These metals—together with Si, also abundant on the Moon—can be used to produce alloys. However, only Fe can be easily separated from regolith (using magnets). Other metals are present in the form of oxides and thus have to be obtained by manufacturing. Metal and alloy manufacturing will be extremely important for the exploration of the Moon as they represent an essential part of the construction and are critical ingredients for most technologies.
One of the crucial steps toward the Moon exploration and settlement is a reliable energy technology for electricity generation and power storage [33, 34] that would withstand the temperature gradients, high levels of radiation, and impact. The primary energy sources considered for future crewed lunar missions are solar power [35, 36], nuclear power [37], and fuel cells [38, 39]. Other ways may include the production of electricity from the excess heat from the sunlight collected by an “evergreen” inflatable dome [40]. In this chapter, we focus on solar cells, a safe and reliable source of electricity in space.
In the past decades, solar cells for space applications have evolved from single-crystalline Si-based cells to multi-junction (MJ) ones based on GaInP, GaAs, and Ge [41, 42, 43]. A promising class of materials for next-generation lightweight and high-power-conversion efficiency [44] solar cells are hybrid organic-inorganic perovskites (HOIPs) [45, 46, 47], which are considered as potential candidates for use on future lunar bases [34].
HOIPs possess a unique combination of properties, such as enhanced charge carrier mobility [48, 49, 50, 51], diffusion length, and lifetime [48, 52, 53], high optical absorption [54, 55], and low production costs [56], representing a paradigm shift in solar cell technology [57] on Earth [58] and for space applications [59, 60, 61, 62]. Given their flexibility [63], low weight, small dimensions (0.5 μm as compared to 200 μm for Si solar cells), the possibility of
The radiation environment on the Moon is constituted, apart from solar electromagnetic radiation, by three radiation “populations”—the constant solar wind, the intense but sporadic Solar Energetic Particles (SEPs), and the constant background of Galactic Cosmic Rays (GCRs). A summary of the radiation environment on the lunar surface is given in Table 1.
Source | Particles | Energy, MeV/nuc | Flux, nuc/cm2/s |
---|---|---|---|
Solar Wind | Protons & electrons | ||
SEPs | Protons | 0 – | |
GCRs | Protons | 2–4 |
The solar wind is a constant flux of plasma from the upper atmosphere of the Sun. It consists mainly of ionized hydrogen (protons and electrons), a small percentage of
SEPs originate from solar transient events, such as coronal mass ejections or flares, and consist in a sudden intense flux of high-energy protons and electrons (and a small amount of
GCRs constitute the slowly varying, low-intensity (few particles/cm2(m2) per second), highly-energetic radiation background in space. They are mainly associated with supernova explosions in the galaxy, but extra-galactic contributions also exist. GCRs are constituted by
The annual exposure caused by GCRs on the lunar surface is
The effects of radiation on materials and devices can be cumulative (long term) and noncumulative (caused even by a single particle). The so-called Single Event Effects (SEEs) can occur when an ionizing particle passing through an electronic device carries a charge large enough to affect the device’s performance. SEEs in aerospace technology can lead to errors, corrupt the data, create noise, reset the device, or even cause fatal part failure [92, 93, 94, 95]. Cumulative radiation damage, on the other hand, occurs through continuous radiation exposure or exposure to intense flux due to SEPs events and can lead to the degradation of optical components and solar cells, eventually causing permanent damage. The total ionizing dose experienced by an electronic device can cause variations in threshold voltage or leakage current.
Cumulative non-ionizing damage in materials due to protons, electrons, and neutrons (originating from the interaction of energetic protons and electrons with the lunar surface) leads to defect formation (displacement damage) [94]. The types and sources of radiation, as well as the effects it can cause in materials, are summarized in Table 2.
Particle type | Energy | Sources | Radiation effects |
---|---|---|---|
Electrons | SEPs | Ionization radiation damage | |
Protons | SEPs | Surface damage to materials | |
Protons | SEPs accelerated in shocks | Displacement damage in solar cells | |
Protons | SEPs and GCRs | Ionization and displacement damage, background counting in sensors | |
Protons | SEPs and GCRs | Single event effects | |
Ions | SEPs and GCRs | Single event effects |
Sources and types of radiation and the effects it causes in materials and devices [96].
Cumulative radiation damage is a multiscale process in terms of time and length. A schematic representation of the so-called displacement damage cascade is shown in Figure 1. At first, an energetic external particle approaches (Figure 1(1)) and enters the target (Figure 1(2)). As the particle passes through the material, it first transfers its kinetic energy to electronic degrees of freedom of the target (electronic stopping) (Figure 1(3)). Electronic excitations happen at a very short time scale (
Schematic representation of different stages of the damage cascade in a crystalline material under irradiation.
Atomic displacements described above lead to defect clustering and eventual amorphization in crystalline materials. Consequently, mechanical, physical, and other properties of the irradiated material can be significantly altered. The scale of the changes depends on the energy of incoming particles and the actual number and spatial distribution of survived defects after eventual self-healing [98].
The radiation-induced effects after atomic displacements strongly depend on the type of material. For metals and metallic alloys, the main effect of radiation is the generation of dislocation loops and point defects which cause significant radiation-induced strengthening or hardening. As a result, the ductility and fracture toughness of the metals (alloys) can be reduced, leading to brittle behavior [99]. Ductile-to-brittle transition is especially pronounced at low temperatures at which the defect mobility, and consequently the annealing of defects, is reduced.
As to other materials, such as semiconductors in solar cells, cumulative exposure to space radiation or high SEPs fluxes can strongly affect the performance of MJ solar cells [100]. Moreover, the impacting radiation can reduce the transmittance of the protective SiO2 cover-glass on top of MJ cells by inducing color centers in the oxide material. The color centers appear when electrons excited by radiation become trapped by impurities in the oxide to form stable defect complexes. On the other hand, the radiation which is not blocked by the cover-glass causes damage in the functional layers of MJ solar cells by displacing atoms. Different energy levels can be created within the bandgap as a consequence of such structural defects. Such electronic defect levels affect the electrical performance of MJ solar cells acting as traps, recombination centers, or carrier removal sites which reduce free carrier concentration [100, 101].
Below, we will present different methods used to describe radiation-induced effects in materials focusing on the description of cumulative effects related to atomic displacements.
High-energy charged particles undergo a daunting number of interactions with target materials. Such interactions include:
electronic collisions leading to ionization and excitation;
multiple Coulomb scattering at small angles (elastic deflection without energy loss, or minimal inelastic loss);
inelastic nuclear reactions, that is, high-energy reactions in which a nucleus in the target struck by an incident particle (with energy
elastic nuclear interactions (
The most commonly used approach to study radiation-induced effects in materials is the Monte Carlo (MC) particle transport method [102, 103]. In MC particle transport, the interactions of individual primary ions and their secondaries are sampled to build a history of charged particle passage and energy deposition in the target [104], with a large enough statistical sample of trajectories. The energy- and angle-dependent cross sections for different interactions are provided by theoretical models of the elementary interactions and/or experimental data, depending on the energy window. Codes, such as Geant4 [105], MCNP6 [106, 107, 108], FLUKA [109], PHITS [110], and HETC-HEDS [111], have been successfully applied to study the radiation at a hemispherical dome made of lunar regolith used to simulate a lunar habitat [112, 113] and the radiation environment around the Moon [114, 115].
Several relevant radiation-induced effects in materials are due to particles with an energy of a few MeV to a few tenths of MeV, as can be seen in Table 2. In this regime, below hadronic interactions causing fragmentation/spallation, atomic displacements are induced in the target by elastic nuclear interactions. Two concepts describe the slowing down of the impacting particles (and the induced secondaries), (i) the
A displacement cascade in MC particle transport simulations is generally modeled within the Binary Collision Approximation (BCA) [119] which assumes a series of independent two-body collisions. Between collisions, particles travel in a straight line. The BCA is valid when (i) the projectile energy is higher than 1 keV per nucleon, which, for PKAs, could be relevant energy, and (ii) the target material has low density, in which case the collisions between the incoming particle and the target atoms occur rarely. BCA allows reducing the computational complexity of the ion-matter interactions compared to a full many-body simulation (e.g., molecular dynamics, discussed in Section 5) and allows for reaching large dimensions with reduced computational needs. However, this method is valid for linear collisions only and describes only primary damage, that is, it does not account for the dynamic evolution of induced defects at later times (Figure 2).
Time and length scales and corresponding methods can be applied to study different stages of radiation damage.
One of the most popular tools in which the BCA is implemented is the Stopping and Range of Ions in Matter (SRIM) code [120]. Besides containing semiempirical data for the electronic stopping power of a variety of targets, SRIM can be applied to model the linear cascades and estimate the number of defects in any material and any ion energy up to 1 GeV. Nuclear stopping in very low-energy intervals uses the so-called ZBL (Ziegler-Biersack-Littmark) universal potential that combines classical Coulomb potential with a semiempirical screening function [120]. The electronic and nuclear degrees of freedom are completely separated in SRIM as well as in other MC particle transport tools used by the particle physics community and the space radiation effects community. Finally, it is important to remark that materials are static in MC particle transport methods—there is no dynamics induced in them by the impact of primaries and the generation and passage of secondaries. Thus, more accurate methods are needed to get access to the processes missing in MC particle transport calculations. Such methods are described in the next section.
There is a large variety of methods used in condensed matter physics and materials science to study radiation effects in materials, each of them describing a particular aspect of the damage process. Figure 2 shows a schematic representation of the different time and length scales with the corresponding computational methods that can be applied to study different stages of radiation damage [97, 121, 122]. The very first stage, at the smallest time-length scale, is the electronic stopping regime. For decades, the semiempirical SRIM code discussed in the previous section has been the most widely used tool to calculate electronic stopping power. Nowadays, the electronic stopping power (and the induced electronic excitations in the target) can be described by
For a complete and accurate description of every aspect of radiation damage, as well as the interplay between them, one has to adopt a combined approach. In recent years, researchers have realized the importance of a multiscale approach to studying radiation damage, as follows from many publications and reviews [121, 122, 130, 131, 132, 133, 134]. Each of the methods presented in Figure 2, as well the ways of combining them, will be discussed below in the order of increasing complexity. The main focus will be on classical MD, AIMD, and TDDFT, which are fundamental for the description of primary radiation damage at the atomic scale.
The most widely used approach in materials science to study the interaction of ions with matter (collision cascades) is MD [135]. MD offers a picture of the ion–ion interaction beyond the linear cascade of the pure BCA by including many-body effects. In MD, atoms are treated as classical particles, and their motion is described by Newtonian dynamics. No electronic effects are thus included.
Cascade simulations need large samples consisting of up to a million atoms (depending on the PKA’s energy), which prohibits using parameter-free methods (such as DFT, see Section 5.2) to compute the interatomic forces. Instead, in MD, the forces on atoms are calculated from empirical or semiempirical interatomic potentials (also called force fields) [136, 137, 138]. MD with empirical potentials proved to work well for large systems and long time scales [139].
In an MD cascade simulation, the system is usually modeled using periodic boundary conditions, that is, by replicating a small unit cell in all directions. Typically, prior to the cascade simulation itself, a regular MD simulation is done to thermally equilibrate the target system at the desired initial temperature. Then, with the equilibrated configuration, the cascade simulation is initiated by changing the velocity of one of the atoms (the PKA), giving it the desired amount of kinetic energy in the intended direction. The system is then evolved in time as in regular MD, that is, by integrating Newton’s equations along with a series of time-steps, which involves computing the atomic forces, velocities, and positions at each time-step (see Refs. [140, 141] for classical texts on MD). At the end of the cascade simulation, the number of defects is obtained by evaluating the final geometry of the system. Usually, cascade simulations are repeated several times, choosing a different PKA and/or a different direction of the PKA’s movement to obtain a statistical average of the number of final defects.
MD has been successfully applied to simulate radiation cascades in a variety of materials [139], from simple metals [142, 143] and compounds [144, 145, 146] to complex nanostructures [147], 2D materials [148], and novel multicomponent alloys [149, 150]. MD simulations can afford to access the processes taking place on a relatively long time scale up to ps or even ns which is enough to describe the damage cascade until the thermal spike of the collision has dissipated. Most of the MD codes, however, describe only elastic collisions between atoms and disregard the energy loss mechanisms such as electronic excitation and ionization. The possibility of including electronic excitations is discussed in Section 5.3.
After the primary damage has been formed, defects may continue diffusing, thus annihilating or forming defect clusters. Such processes occur on a much longer time scale, reaching at least seconds, not accessible via regular MD. The problem of simulating a process not accessible in a feasible amount of computational time has motivated the development of several enhanced sampling techniques [151], which in the case of MD simulations of materials have allowed to observe otherwise challenging processes, such as phase transitions.
KMC [127] simulations are commonly used to access long-time effects of radiation in materials [152, 153, 154, 155]. KMC is designed to model the time evolution of an atomic system. However, instead of solving the equations of motion, as it is done in MD, the KMC method is based on the assumption that the long-time dynamics of a system consists of diffusive jumps from state to state. Each of the states is treated independently, which makes KMC a very efficient method. The dynamics of the system, that is, the probability of transition from one state to another does not depend on the history of the system. The probability of a state-to-state transition is assigned randomly and the most probable transition is statistically chosen. This allows avoiding the complications related to the choice of interatomic potentials, thus overcoming the time limitations of MD simulations (usually
To further extend the problem into the macro-domain, the DD [128] and FEM [129, 156] methods, based on dividing a geometrical space on a number of finite (non-overlapping) segments, are usually applied. FEM has been used to study the response of a macro-object to external stress in engineering and has also been applied to study the behavior of solids under irradiation by extrapolating the known displacements and evaluating the geometry of a 3D object. DD method allows for calculating the motion of dislocations as well as evaluating the plastic deformation in the material induced by the collective motion of dislocations.
AIMD is one of the most important tools in quantum physics and chemistry [157]. In a typical AIMD simulation, it is assumed that the system consists of
Practical DFT calculations are based on the Kohn-Sham (KS) formalism [126], which replaces the complex problem of interacting electrons in the standard Schrödinger equation by a problem of non-interacting electrons moving in an effective potential
where
AIMD is used to simulate any physicochemical process where the electronic structure of the system changes significantly or when a detailed description of the structure is needed. A typical example would be the simulation of chemical reactions, where chemical bonds are formed or broken, which cannot be described via classical force fields.
Although the adiabatic BO approximation is the usual approximation in the methods described above, its applicability is only justified in near-equilibrium situations. However, under ion impact, the electronic subsystem is rapidly driven out of equilibrium.
A realistic description of the dynamics of the electrons in the target during the passage of fast ions can be obtained in the framework of TDDFT which gives access to the electron dynamics out of the electronic ground state. In particular, real-time TDDFT [160] provides a non-perturbative description of the electronic excitations upon an external perturbation and can be combined with the Ehrenfest MD scheme [161], which allows for coupling between electron and ion motion, contrary to the BO picture.
TDDFT consists in solving the time-dependent KS equations [123]:
where
where
The solution of the time-dependent KS equations in real time can be obtained by applying the so-called time-evolution operator, evolving the KS states in time [123]. The time-step of this propagation must be of the order of attoseconds to describe the fast dynamics of the electrons, in contrast to what occurs in AIMD and MD where the time-step is of the order of femtoseconds. The time-dependent electron density is calculated at each step, from which the total energy of the system is obtained. Knowing the total energy as a function of time, the electronic stopping power can be calculated as
Many examples of accurate first-principles calculations of the electronic stopping power are available in the literature [117, 118, 163, 164, 165, 166, 167, 168]. Recent studies have demonstrated that electronic excitations (induced by both the primary impacting ion and especially by PKAs and further displaced atoms) affect the cascade evolution [118, 169, 170, 171] and thus, they need to be accounted for. The electronic stopping effects can be included in MD cascade simulations through the so-called two-temperature (2T) model [118, 172]. In 2 T-MD, the electrons are included as a thermal bath. Each particle is subject to a friction force representing the electronic stopping and a stochastic force representing the coupling between the vibrational degrees of freedom of the lattice and the electrons. This model considers constant electronic density in the entire system and thus, the electronic stopping power is independent of the crystal direction. Recent studies have extended the 2T model by coupling the electronic and nuclear effects via many-body forces that act in a correlated way. This allowed for the construction of a unified model for ion-electron interactions [170, 171, 173, 174] with a complex energy-exchange process between the ionic and electronic subsystems [174].
The previous section provided an overview of computational methods that can be applied to study radiation damage in materials and discussed the advantages of combining such methods into a multiscale approach. This section mainly focuses on the effects of radiation on materials of practical use on the Moon, including several novel and promising materials. We overview the existing radiation damage studies for these novel materials, emphasizing multiscale modeling when available.
Generally, degradation of solar cells is modeled via the non-ionizing energy loss (NIEL) approach, the NIEL being the portion of energy loss per unit path length of the projectile converted into displacement damage. According to Akkerman et al. [175] (the definition used in most simulation tools), the NIEL is defined as:
where
On the basis of a large set of experimental observations, it is assumed that the degradation of a semiconductor device under irradiation can be linearly correlated with the NIEL [176]. In practice, this means that the number of defects should give a measure of the damage irrespective of their distribution, whether clustered in high density in small regions (as in the case of neutron damage) or homogeneously scattered over a relatively wide volume (as in the case of the low-energy proton or
Generally, the NIEL is calculated via MC particle transport codes, assuming amorphous target materials, a static
NIEL for protons and electrons in GaAs for different values of the threshold displacement energy
Another example of possible improvement in the NIEL model is a more precise calculation of the number of radiation-induced defects and of the “quality” of radiation-induced damage (which type of defects are induced). It has been observed that point-like and clustered defects contribute differently to some degradation parameters [191]. Recent MD studies [192, 193, 194] and experimental works [181, 195, 196] have proposed an effective or
On a parallel research stream, multiscale studies in a number of materials combining MD simulations of collision cascades with the electronic stopping from TDDFT offer a more accurate description of both the number and the nature of defects created under realistic conditions. The electronic degrees of freedom and their coupling to the phonons of the target affect the cascade evolution and morphology [170, 171, 173, 174]. This is of relevance for the NIEL which includes a part of energy dissipated to phonons. This fraction depends on the energy of the impinging particle but also on the properties of the material. Some studies have shown that the direction-dependence of the electronic stopping can influence the collision cascades [118]. Other studies have demonstrated that the formation of thermal spikes and therefore of amorphous pockets is sensitive to the electronic specific heat [199] and others that the choice of the model employed for the inclusion of the electronic effects and in particular the overestimation (or underestimation) of electron-phonon coupling can have a significant influence on the number of defects created [171].
As discussed in Section 2, HOIPs have a unique combination of properties particularly interesting for lunar exploration. The general chemical formula for perovskites is ABX3, where A and B are two metal ions with different ionic radii and X is an anion that is six coordinated to the B-site [200]. HOIPs, in particular, comprise a negatively charged lead-halide inorganic skeleton where B is a metal cation (Sn2+ or Pb2+), X is a halide anion (I−, Br−, and/or Cl−) and A is a monovalent positively charged organic cation, such as methylammonium (MA+ = CH3NH3X+, where X = I, Br, Cl) or formamidinium (
Structure of a HOIP: methylammonium cation (
Despite many advantages, several external factors, such as air, moisture [202], UV light [47, 203], heat, light soaking [204], and partially also radiation [205, 206], induce considerable structural instabilities in HOIPs. An intrinsic instability is also present, caused by a relatively weak cohesion between the organic cation and the inorganic octahedra and predominantly by the low-energy barriers for the migration of halide anions and organic cations, with halide migration being the most prevalent [201, 207, 208, 209, 210]. Phase segregation can be induced by large-scale ion migration [211]. However, some of the challenges that HOIPs-based solar cells face on Earth, such as degradation caused by moisture, are not relevant for space applications [212]. Thermal and vacuum stability, high power-conversion efficiency, and radiation resistance are the main challenges in the space context. A sensible choice of the chemical composition, of eventual use in tandem devices [212] (which also helps to reach an efficiency of up to 30%) or incorporation of a functionalized 2D metal-organic frameworks (MOFs) [213], can improve the long-term operational stability of HOIPs.
A relevant collection of DFT studies for HOIPs can be found in Ref. [214]. A recent study based on DFT + compressed sensing-symbolic regression has shown that mitigation of the propensity of halogens to migrate could be achieved by selectively strengthening specific bonds [215]. The study also unveiled the reasons for improved stability given by specific halogens, the origin of the higher stability offered by certain organic cations compared to others, and highlighted in a quantitative and first-principles manner how weak interactions have a significant role in binding the halogens more strongly.
The study of the radiation tolerance of perovskite solar cells is an extremely active field of research. Solar cells based on HOIPs as active layers have been recently sent to space via first campaigns [60, 216]. Several ground-testing experiments have been performed mostly using protons, either with an energy of several tenths of MeV [69, 211, 217] or with an energy of 150 keV, 100 keV, and 50 keV [70, 218, 219], of less relevance for realistic space conditions.
Superior radiation resistance of perovskite solar cells in comparison to commercially available crystalline Si-based cells has been demonstrated [69]. Moreover, experiments have shown that perovskite solar cells have remarkable self-healing capabilities (at room temperature) that lower the number of defects caused by proton irradiation [69]. Another experimental study has shown that the proton irradiation effects on the physical properties of HOIPs are strongly dependent on the synthesis method [220] which appeared to affect the strength of specific chemical bonds. In particular, HOIPs, produced by mechano-chemical synthesis, have shown practically no change in their physical properties after irradiation with a high-energy 10 MeV proton beam with doses of up to 1013 protons/cm2.
Recently, multi-junction tandem solar cells (combining HOIPs with previous technologies or technologies investigated in parallel) have also been studied under ion irradiation [217]. Lang et al. [217] carried out SRIM simulations of energy loss of high-energy protons as well as the energy transferred to the recoiling nuclei—a measure of the degradation of PV parameters—in tandem solar cells (Figure 5). The study [217] has shown that HOIP/CIGS tandem solar cells possess a high radiation hardness and retain over 85% of their initial performance even after 68 MeV proton irradiation and a dose of
3D scatter plots of the straggling of 68 MeV protons within the (A) HOIP/CIGS(Cu(In,Ga)Se
First-principles calculations of the atomic knock-on displacement events in HOIPs have shown that such displacements are significant and highly energy-dependent [221]. The work has shown that only certain types of atoms are prone to displacements suggesting that mitigation strategies should be directed toward some chemical species more than others. Overall, further studies are necessary, but existing research proves that HOIPs-based solar cells have a remarkable potential for power generation on missions to low Earth orbit, the Moon, and beyond [62].
Another promising class of novel materials for space applications is multi-principal element alloys (MPEAs) [222, 223], which combine superior mechanical properties and enhanced radiation resistance [224]. Also known as high-entropy alloys (HEAs) or concentrated solid-solution alloys (CSSAs), MPEAs consist of at least five principal elements with the concentration of each element from 5 to 35% [222]. Despite the complex composition, MPEAs often form single-phase solid solutions (Figure 6). The interest of researchers in MPEAs has been growing exponentially in recent years, as they exhibit a paradigm shift in alloy development. MPEAs indeed combine a set of outstanding properties, such as high strength, hardness, fracture toughness, corrosion resistance, strength retention at high temperature [226], good low-temperature performance [227], and recently discovered enhanced radiation resistance, superior to conventional alloys and pure metals [149, 222, 223, 228, 229, 230, 231, 232, 233]. Moreover, MPEAs have great potential as 3D printing materials [234]. MPEAs can be printed from a powder, providing manufacturing freedom for lightweight and customizable products of complex geometries for applications in the aerospace, energy, molding, tooling, and other industries, all of the great relevance for the exploration of the Moon.
Atomic structure of a body-centered cubic (BCC) AlCoCrCuFeNi HEA. The Al, Fe, Co, Cr, Ni, and Cu atoms are shown in red, magenta, green, blue, cyan, and gray colors, respectively [
Recent experiments have shown that MPEAs have a higher resistance to defect formation due to high atomic-level stress and chemical heterogeneity [235]. MPEAs also possess lower void swelling and higher phase stability [236, 237] as compared to conventional alloys. Self-healing capability is another remarkable property of MPEAs [227, 236, 238].
The subclass of lightweight (LW) MPEAs have a great potential for space applications due to their high strength-to-weight ratio [239, 240, 241]. The main components of LWMPEAs are low-density elements, such as Al, Mg, Si, and Ti [240]. The latter is of extreme importance for ISRU since 99% of the lunar soil consists of Si, Al, Ca, Fe, Mg, and Ti oxides [5, 242].
Currently, the main focus of computational studies has been on the single-phase random solid-solution (SS) alloys based on transition metals with high densities (Co, Cr, Fe, Ni) for application in radiation environments, in particular in nuclear reactors [148, 149, 232, 236, 243, 244, 245]. MD simulations of displacement cascades applied to pure metals and multicomponent alloys [150, 244, 245, 246, 247, 248] confirm the experimentally observed reduction of the number of defects and defect clusters in MPEAs compared to pure metals (Figure 7).
The number of defects in Ni, NiFe, and NiCoCr from experiments and MD simulations [
The electronic stopping power for a proton in binary alloys has recently been calculated using real-time TDDFT [249]. The study has shown that the electronic stopping power of binary alloys is higher than that of pure Ni, suggesting that alloys more effectively stop the incoming particles. Moreover, the inclusion of the electronic stopping into MD simulations of defect formation significantly reduces the final number of surviving defects, as shown in Figure 8. The inclusion of both the electron-phonon coupling and the electronic stopping in the 2T-MD model not only reduces the actual number of defects but also notably impacts their final arrangement, namely leading to more isolated point defects and reducing the size of defect clusters in binary and ternary alloys [250, 251, 252, 253, 254].
Average number of surviving defects in the classical MD cascade, MD cascade including electronic stopping force, and the 2 T-MD cascade at the end of the simulation for 50 keV Ni cascade in Ni, Ni80Fe20, and NiFe [
The majority of MD studies focus on binary and ternary MPEAs due to the lack of force fields for alloys with more than three elements. However, some studies exist [233] on defect formation in NiCoFeCr alloy in which fewer defects have been found at the end of the displacement cascade with PKA energies from 10 to 50 keV, as compared with pure Ni. The limitations of the classical MD with force fields and the ways of solving this problem are discussed in the following.
Classical MD with empirical potentials is the method that proved to work well for large systems and long time scales [139] for the modeling of collision cascades. However, classical interatomic potentials cannot accurately reproduce interactions between the atoms in MPEAs due to their complex structure and lattice distortions leading to internal strain [149, 255, 256]. On the other hand,
Recent developments in machine learning (ML) approaches can provide a solution to this problem. ML-enhanced materials discovery is an emerging and extremely rapidly growing field. The combination of a precise model based on quantum mechanics and ML algorithms have the potential for an efficient and accurate description of materials properties [257, 258, 259]. Much progress has been made in recent years in the development of ML-based interatomic potentials with the input from electronic structure calculations. First applications have shown that accurate potentials can be obtained for many relevant systems [260, 261, 262, 263, 264, 265]. ML-assisted calculations have been applied to pure metals, binary, ternary alloys [266, 267], and MPEAs [268, 269, 270].
ML and artificial intelligence (AI) may become powerful tools for more accurate multiscale modeling of materials properties. Artificial Neural Networks (ANN) [271] combined with atomistic KMC have already been used to describe the microstructural changes in metals and alloys induced by irradiation [272]. Machine-learned interatomic potentials have been used to study defect formation in refractory MPEAs [273]. The results confirm experimental findings, showing that the 3D migration and increased mobility of defects in MPEAs promote defect recombination leading to more efficient healing. AI, thus, can provide a bridge between different methods, such as DFT, MD, and KMC, and allow for large-scale atomistic simulations of high accuracy, which will accelerate the discovery of new advanced materials.
Fiber-reinforced polymers (FRPs) are composite materials made of a polymer matrix reinforced with fibers. Typical polymers that are often used include epoxy, vinyl ester, polyester thermosetting plastic, and phenol-formaldehyde resins. Typical fibers include, but are not limited to, glass, carbon, and aramid. In a composite FRP material, the polymer and fiber often have significantly different physical and/or chemical properties, which remain separate and distinct within the finished structure but are complementary for tailored properties [274]. Because of their low density (lightweight), great moldability, specific strength, stiffness [275], excellent mechanical stability, and good thermal properties, FRPs are being increasingly used as structural materials in aerospace, automotive, marine industries, and civil infrastructures. Hence, FRPs are of great interest for many applications for lunar missions as potential structural materials [276]. Glass fibers (also “fiberglass”) can be directly produced from the lunar soil as well as from by-products of metal extraction and can be used to reinforce lunar concrete [277].
The radiation environment on the Moon presents challenges for FRPs with concerns on both the immediate reactions taking place in the materials (short-term effects) and continued post-exposure degradation processes (long-term effects) [276, 278]. In the past decades, many selected FRPs have been ground-tested at different kinds of radiation and particle accelerator facilities for their potential use in space-related radiation environments, including UV-light [279, 280],
Carbon-fiber composites have been widely used in aerospace industries due to their high-temperature stability and low density along with high strength, as well as superior beam-induced shock absorption [285, 286]. A combined modeling and experimental study of the radiation effect on carbon-fiber-reinforced molybdenum-graphite compound (MoGRCF) [285], including MC simulations of the energy deposited into a realistic structure by a 200-MeV proton beam (Figure 9) has show that carbon-fiber-reinforced composites have superior beam-induced shock absorption ability compared to that of graphite.
MC modeling of the energy deposition for a 200-MeV proton beam interacting with an irradiation target array (MoGRCF) in tandem with the isotope production array downstream [
In the 1980s, the degradation behavior of carbon-fiber-reinforced plastic (CFRP) under electron beam irradiation in various conditions simulating experiments in space has been studied by Sonoda et al. [283]. It has been observed that there is no change in mechanical properties of CFRP when irradiated by up to a dose of 50 MGy. MC simulations of radiation effects in FRPs have shown that by adding lead nanoparticles it is possible to increase their radiation resistance [287]. According to the study, the addition of 15 wt% of lead nanoparticles to FRPs led to a mass reduction of
An alternative to glass fiber for polymer reinforcement is basalt fiber which offers advantages, such as high specific mechanical and physicochemical properties, biodegradability, non-abrasive qualities, and cost-effectiveness [288]. Arnhof et al. [289] have recently studied mechanical properties of fiber-reinforced geopolymer (FRG) with basalt fiber (i.e., inorganic alumino-silicate polymer) made from lunar regolith simulant as potential shielding and structural material. As basalt fibers can be produced
The additive-manufacturing (AM) techniques for lunar construction from regolith, including FRP materials, and their suitability for ISRU has recently been reviewed in Refs. [292, 293]. The AM techniques for lunar construction include Cement Contour Crafting (CCC), Binder Jetting (BJ), Selective Solar Light Sintering (SSLS) and Selective Laser Sintering/Melting (SLS/SLM) for 3D printing and metal melting, Stereolithography/Digital Light Processing (SLA/DLP), among others. CCC and BJ technologies could be used for outdoor lunar civil engineering. SSLS could be applied to both direct compacting of lunar regolith to ceramic parts and 3D printing. SLA/DLP-based methods could be used for the indoor manufacturing of ceramic instruments, providing higher precision and printing quality and lower defect rate of the printed parts than other AM methods. In the last decade, studies have clearly shown that the 3D-printing technologies will become one of the cornerstones of lunar exploration, providing future astronauts with all the necessary infrastructure [293].
Lunar concrete consisting of mined regolith with the addition of glass fibers (also made
It is worth mentioning that the 4D printing of a “smart material” with FRPs that responds to radiation-induced damages and aging in a programmable way could be realized in near future [296, 297]. In addition to experiments on the radiation environment in a lab, multiscale computational simulations as mentioned above could be helpful for gaining further insights into the radiation-induced molecular changes occurring in polymers.
In this chapter, we introduced some relevant materials for lunar habitat construction and power generation. We discussed the radiation environment on the Moon and the effects that radiation can cause in such materials. We provided an overview of computational methods used to study different stages of radiation damage in materials, focusing on the methods that allow simulating the behavior of materials with extreme accuracy down to the atomic scale. We emphasized that by coupling different methods, it is possible to account for different time and length scales in the evolution of the radiation-induced effects and to combine the electronic effects with atomic displacements.
Several particular examples of radiation damage studies have been discussed with the focus on novel materials with enhanced radiation resistance and other remarkable properties for use on the Moon that can revolutionize space exploration. Such materials include HOIPs for energy production and MPEAs and FRP composite materials for construction. The primary materials considered for lunar construction are FRGs with basalt or glass fibers, which have excellent mechanical properties, can benefit from ISRU, and provide necessary radiation shielding. We emphasized that researchers’ effort is mainly directed toward the development of additive manufacturing techniques, such as 3D printing for habitat construction from lunar regolith. 3D printing will allow producing complex and customizable products in a shorter time and with a lower cost and material consumption.
Nowadays, the radiation-induced effects in materials for space missions are mainly studied by MC particle transport modeling, inheriting the remarkable modeling and computational efforts by the high-energy physics community. However, with the development of first-principles methods and multiscale simulations, a more accurate understanding of radiation effects in materials can be achieved for the regime below hadronic interactions, with details down to atomic scale. It can be expected that the combination of first-principles methods, MC particle transport, and ML will contribute further to the investigation of materials to unravel their full potential for the application in harsh space radiation environments, in particular for what concerns the resistance and resilience to cumulative displacements effects.
The authors are grateful for the funding provided by the project ESC2RAD within the Horizon 2020 Research and Innovation program (grant agreement ID: 776410) and by the project PROIRICE within the program H2020-MSCA-IF 2016 of the Horizon 2020 program of the European Union (grant agreement ID: 748673).
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Saleh"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},subject:{topic:{id:"242",title:"Aerial Robotics",slug:"aerial-robotics",parent:{id:"22",title:"Robotics",slug:"physical-sciences-engineering-and-technology-robotics"},numberOfBooks:7,numberOfSeries:0,numberOfAuthorsAndEditors:63,numberOfWosCitations:319,numberOfCrossrefCitations:301,numberOfDimensionsCitations:481,videoUrl:null,fallbackUrl:null,description:null},booksByTopicFilter:{topicId:"242",sort:"-publishedDate",limit:12,offset:0},booksByTopicCollection:[{type:"book",id:"7792",title:"Unmanned Robotic Systems and Applications",subtitle:null,isOpenForSubmission:!1,hash:"53805f091c3107536edd2579c9987649",slug:"unmanned-robotic-systems-and-applications",bookSignature:"Mahmut Reyhanoglu and Geert De Cubber",coverURL:"https://cdn.intechopen.com/books/images_new/7792.jpg",editedByType:"Edited by",editors:[{id:"15068",title:"Dr.",name:"Mahmut",middleName:null,surname:"Reyhanoglu",slug:"mahmut-reyhanoglu",fullName:"Mahmut Reyhanoglu"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6465",title:"Drones",subtitle:"Applications",isOpenForSubmission:!1,hash:"50a345acb86d524f7a505e09d1f2fc49",slug:"drones-applications",bookSignature:"George Dekoulis",coverURL:"https://cdn.intechopen.com/books/images_new/6465.jpg",editedByType:"Edited by",editors:[{id:"9833",title:"Prof.",name:"George",middleName:null,surname:"Dekoulis",slug:"george-dekoulis",fullName:"George Dekoulis"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5905",title:"Robots Operating in Hazardous Environments",subtitle:null,isOpenForSubmission:!1,hash:"a22b4e4b02af1dd0727231b0d974f121",slug:"robots-operating-in-hazardous-environments",bookSignature:"Hüseyin Canbolat",coverURL:"https://cdn.intechopen.com/books/images_new/5905.jpg",editedByType:"Edited by",editors:[{id:"5887",title:"Dr.",name:"Hüseyin",middleName:null,surname:"Canbolat",slug:"huseyin-canbolat",fullName:"Hüseyin Canbolat"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6181",title:"Search and Rescue Robotics",subtitle:"From Theory to Practice",isOpenForSubmission:!1,hash:"e1ca88810595580ec90815aab3f1ec9a",slug:"search-and-rescue-robotics-from-theory-to-practice",bookSignature:"",coverURL:"https://cdn.intechopen.com/books/images_new/6181.jpg",editedByType:"Authored by",editors:null,equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"3",chapterContentType:"chapter",authoredCaption:"Authored by"}},{type:"book",id:"3642",title:"Mobile Robots Navigation",subtitle:null,isOpenForSubmission:!1,hash:null,slug:"mobile-robots-navigation",bookSignature:"Alejandra Barrera",coverURL:"https://cdn.intechopen.com/books/images_new/3642.jpg",editedByType:"Edited by",editors:[{id:"6195",title:"Prof.",name:"Alejandra",middleName:null,surname:"Barrera",slug:"alejandra-barrera",fullName:"Alejandra Barrera"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3696",title:"Aerial Vehicles",subtitle:null,isOpenForSubmission:!1,hash:null,slug:"aerial_vehicles",bookSignature:"Thanh Mung Lam",coverURL:"https://cdn.intechopen.com/books/images_new/3696.jpg",editedByType:"Edited by",editors:[{id:"130793",title:"Prof.",name:"T. 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This introductory chapter explains how a new tool can be added to this toolkit: robots. The use of robotic assets in search and rescue operations is explained and an overview is given of the worldwide efforts to incorporate robotic tools in search and rescue operations. Furthermore, the European Union ICARUS project on this subject is introduced. The ICARUS project proposes to equip first responders with a comprehensive and integrated set of unmanned search and rescue tools, to increase the situational awareness of human crisis managers, such that more work can be done in a shorter amount of time. The ICARUS tools consist of assistive unmanned air, ground, and sea vehicles, equipped with victim-detection sensors. The unmanned vehicles collaborate as a coordinated team, communicating via ad hoc cognitive radio networking. To ensure optimal human-robot collaboration, these tools are seamlessly integrated into the command and control equipment of the human crisis managers and a set of training and support tools is provided to them to learn to use the ICARUS system.",book:{id:"6181",slug:"search-and-rescue-robotics-from-theory-to-practice",title:"Search and Rescue Robotics",fullTitle:"Search and Rescue Robotics - From Theory to Practice"},signatures:"Geert De Cubber, Daniela Doroftei, Konrad Rudin, Karsten Berns,\nAnibal Matos, Daniel Serrano, Jose Sanchez, Shashank Govindaraj,\nJanusz Bedkowski, Rui Roda, Eduardo Silva and Stephane Ourevitch",authors:[{id:"206420",title:"Dr.",name:"Geert",middleName:null,surname:"De Cubber",slug:"geert-de-cubber",fullName:"Geert De Cubber"}]},{id:"56737",doi:"10.5772/intechopen.69738",title:"UAV for Landmine Detection Using SDR-Based GPR Technology",slug:"uav-for-landmine-detection-using-sdr-based-gpr-technology",totalDownloads:3444,totalCrossrefCites:14,totalDimensionsCites:17,abstract:"This chapter presents an approach for explosive-landmine detection on-board an autonomous aerial drone. The chapter describes the design, implementation and integration of a ground penetrating radar (GPR) using a software defined radio (SDR) platform into the aerial drone. The chapter?s goal is first to tackle in detail the development of a custom-designed lightweight GPR by approaching interplay between hardware and software radio on an SDR platform. The SDR-based GPR system results on a much lighter sensing device compared against the conventional GPR systems found in the literature and with the capability of re-configuration in real-time for different landmines and terrains, with the capability of detecting landmines under terrains with different dielectric characteristics. Secondly, the chapter introduce the integration of the SDR-based GPR into an autonomous drone by describing the mechanical integration, communication system, the graphical user interface (GUI) together with the landmine detection and geo-mapping. This chapter approach completely the hardware and software implementation topics of the on-board GPR system given first a comprehensive background of the software-defined radar technology and second presenting the main features of the Tx and Rx modules. Additional details are presented related with the mechanical and functional integration of the GPR into the UAV system.",book:{id:"5905",slug:"robots-operating-in-hazardous-environments",title:"Robots Operating in Hazardous Environments",fullTitle:"Robots Operating in Hazardous Environments"},signatures:"Manuel Ricardo Pérez Cerquera, Julian David Colorado Montaño\nand Iván Mondragón",authors:[{id:"177422",title:"Dr.",name:"Julian",middleName:null,surname:"Colorado",slug:"julian-colorado",fullName:"Julian Colorado"},{id:"197884",title:"Prof.",name:"Ivan",middleName:null,surname:"Mondragon",slug:"ivan-mondragon",fullName:"Ivan Mondragon"},{id:"199958",title:"Prof.",name:"Manuel",middleName:null,surname:"Perez",slug:"manuel-perez",fullName:"Manuel Perez"}]}],mostDownloadedChaptersLast30Days:[{id:"56737",title:"UAV for Landmine Detection Using SDR-Based GPR Technology",slug:"uav-for-landmine-detection-using-sdr-based-gpr-technology",totalDownloads:3443,totalCrossrefCites:14,totalDimensionsCites:17,abstract:"This chapter presents an approach for explosive-landmine detection on-board an autonomous aerial drone. The chapter describes the design, implementation and integration of a ground penetrating radar (GPR) using a software defined radio (SDR) platform into the aerial drone. The chapter?s goal is first to tackle in detail the development of a custom-designed lightweight GPR by approaching interplay between hardware and software radio on an SDR platform. The SDR-based GPR system results on a much lighter sensing device compared against the conventional GPR systems found in the literature and with the capability of re-configuration in real-time for different landmines and terrains, with the capability of detecting landmines under terrains with different dielectric characteristics. Secondly, the chapter introduce the integration of the SDR-based GPR into an autonomous drone by describing the mechanical integration, communication system, the graphical user interface (GUI) together with the landmine detection and geo-mapping. This chapter approach completely the hardware and software implementation topics of the on-board GPR system given first a comprehensive background of the software-defined radar technology and second presenting the main features of the Tx and Rx modules. Additional details are presented related with the mechanical and functional integration of the GPR into the UAV system.",book:{id:"5905",slug:"robots-operating-in-hazardous-environments",title:"Robots Operating in Hazardous Environments",fullTitle:"Robots Operating in Hazardous Environments"},signatures:"Manuel Ricardo Pérez Cerquera, Julian David Colorado Montaño\nand Iván Mondragón",authors:[{id:"177422",title:"Dr.",name:"Julian",middleName:null,surname:"Colorado",slug:"julian-colorado",fullName:"Julian Colorado"},{id:"197884",title:"Prof.",name:"Ivan",middleName:null,surname:"Mondragon",slug:"ivan-mondragon",fullName:"Ivan Mondragon"},{id:"199958",title:"Prof.",name:"Manuel",middleName:null,surname:"Perez",slug:"manuel-perez",fullName:"Manuel Perez"}]},{id:"67705",title:"Advanced UAVs Nonlinear Control Systems and Applications",slug:"advanced-uavs-nonlinear-control-systems-and-applications",totalDownloads:1971,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"Recent development of different control systems for UAVs has caught the attention of academic and industry, due to the wide range of their applications such as in surveillance, delivery, work assistant, and photography. In addition, arms, grippers, or tethers could be installed to UAVs so that they can assist in constructing, transporting, and carrying payloads. In this book chapter, the control laws of the attitude and position of a quadcopter UAV have been derived basically utilizing three methods including backstepping, sliding mode control, and feedback linearization incorporated with LQI optimal controller. The main contribution of this book chapter would be concluded in the strategy of deriving the control laws of the translational positions of a quadcopter UAV. The control laws for trajectory tracking using the proposed strategies have been validated by simulation using MATLAB®/Simulink and experimental results obtained from a quadcopter test bench. Simulation results show a comparison between the performances of each of the proposed techniques depending on the nonlinear model of the quadcopter system under investigation; the trajectory tracking has been achieved properly for different types of trajectories, i.e., spiral trajectory, in the presence of unknown disturbances. Moreover, the practical results coincided with the results of the simulation results.",book:{id:"7792",slug:"unmanned-robotic-systems-and-applications",title:"Unmanned Robotic Systems and Applications",fullTitle:"Unmanned Robotic Systems and Applications"},signatures:"Abdulkader Joukhadar, Mohammad Alchehabi and Adnan Jejeh",authors:null},{id:"60953",title:"Small to Medium UAVs for Civilian Applications in Indonesia",slug:"small-to-medium-uavs-for-civilian-applications-in-indonesia",totalDownloads:1339,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Indonesian government needs a well-built, easy to operate unmanned aircraft systems (UAS) to perform various civilian missions as UAS are a well-known platform for dirty, dull, and dangerous missions. Hence, the Indonesian government has an organization that performs research and development of UAS, named as Aeronautic Technology Center. This organization is placed underneath Indonesian National Institute of Aeronautics and Space. The UAS developments in this institute are primarily driven by civilian uses; therefore, the UAS size, sensor types, and mission payload are optimized for civilian missions. In order to produce the decent to the best quality of the aerial image, which is the essential product for various civilian missions, the UAS regularly flies under the cloud. For this reason, the Aeronautic Technology Center is only developing the LASE (low altitude, short-endurance) and the LALE (low altitude, long endurance) UAS type as of now. The UAS development was begun with LSU-01, followed by LSU-02, LSU-03, and LSU-05. The LSU-01, LSU-02, and LSU-03 are in the operational phase, while the LSU-05 is in the experimental Phase. In this chapter, the specification of the platforms and the sensor capabilities that are relevant with the demands of users in the civilian sector are described.",book:{id:"6465",slug:"drones-applications",title:"Drones",fullTitle:"Drones - Applications"},signatures:"Fuad Surastyo Pranoto, Ari Sugeng Budiyanta and Gunawan Setyo\nPrabowo",authors:[{id:"223333",title:"M.Sc.",name:"Fuad",middleName:"Surastyo",surname:"Pranoto",slug:"fuad-pranoto",fullName:"Fuad Pranoto"},{id:"223356",title:"MSc.",name:"Ari Sugeng",middleName:null,surname:"Budiyanta",slug:"ari-sugeng-budiyanta",fullName:"Ari Sugeng Budiyanta"},{id:"223357",title:"MSc.",name:"Gunawan Setyo",middleName:null,surname:"Prabowo",slug:"gunawan-setyo-prabowo",fullName:"Gunawan Setyo Prabowo"}]},{id:"67003",title:"Vision-Based Autonomous Control Schemes for Quadrotor Unmanned Aerial Vehicle",slug:"vision-based-autonomous-control-schemes-for-quadrotor-unmanned-aerial-vehicle",totalDownloads:978,totalCrossrefCites:0,totalDimensionsCites:4,abstract:"This chapter deals with the development of vision-based sliding mode control strategies for a quadrotor system that would enable it to perform autonomous tasks such as take-off, landing and visual inspection of structures. The aim of this work is to provide a basic understanding of the quadrotor dynamical model, key concepts in image processing and a detailed description of the sliding mode control, a widely used robust non-linear control scheme. Extensive MATLAB simulations are presented to enhance the understanding of the controller on the quadrotor system subjected to bounded disturbances and uncertainties. The vision algorithms developed in this chapter would provide the necessary reference trajectory to the controller enabling it to exercise control over the system. This work also describes, in brief, the implementation of the developed control and vision algorithms on the DJI Matrice 100 to present real-time experimental data to the readers of this chapter.",book:{id:"7792",slug:"unmanned-robotic-systems-and-applications",title:"Unmanned Robotic Systems and Applications",fullTitle:"Unmanned Robotic Systems and Applications"},signatures:"Archit Krishna Kamath, Vibhu Kumar Tripathi and Laxmidhar Behera",authors:null},{id:"59130",title:"The Use of Unmanned Aerial Vehicles by Urban Search and Rescue Groups",slug:"the-use-of-unmanned-aerial-vehicles-by-urban-search-and-rescue-groups",totalDownloads:1294,totalCrossrefCites:5,totalDimensionsCites:6,abstract:"In the case of natural or man-made disaster, the top priority of urban search and rescue (USAR) groups is to localise the victim as quickly as possible. Even minutes might play a crucial role in the victim’s survival. A number of standard operating procedures may be applied to achieve best performance. Rescue dogs are trained to search for alive victims; special inspection cameras are used, before heavy equipment is being implemented. To improve the effectiveness of USAR group operations, innovative technologies might be implemented. The most recent solution is currently designed in MOBNET project, founded by EU under the Horizon 2020 programme. The scope of the project is to combine both cellular technology and early Galileo services to localise the smartphones of potential victims. Integration tests give some promising outcomes. 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He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. 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Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. 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She has more than fifteen years of teaching and research experience. She has published more than 550 scientific publications/communications, including 15 books, 50 book chapters, 100 original research papers, 380 research communications in national and international conferences, and 12 patents. She is a member of the editorial board of five journals and acts as a reviewer for several national and international journals. 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He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:null,institution:null},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"417317",title:"Mrs.",name:"Chiedza",middleName:null,surname:"Elvina Mashiri",slug:"chiedza-elvina-mashiri",fullName:"Chiedza Elvina Mashiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"352140",title:"Dr.",name:"Edina",middleName:null,surname:"Chandiwana",slug:"edina-chandiwana",fullName:"Edina Chandiwana",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"342259",title:"B.Sc.",name:"Leonard",middleName:null,surname:"Mushunje",slug:"leonard-mushunje",fullName:"Leonard Mushunje",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"347042",title:"Mr.",name:"Maxwell",middleName:null,surname:"Mashasha",slug:"maxwell-mashasha",fullName:"Maxwell Mashasha",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"2941",title:"Dr.",name:"Alberto J.",middleName:"Jorge",surname:"Rosales-Silva",slug:"alberto-j.-rosales-silva",fullName:"Alberto J. Rosales-Silva",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"437913",title:"Dr.",name:"Guillermo",middleName:null,surname:"Urriolagoitia-Sosa",slug:"guillermo-urriolagoitia-sosa",fullName:"Guillermo Urriolagoitia-Sosa",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"435126",title:"Prof.",name:"Joaquim",middleName:null,surname:"José de Castro Ferreira",slug:"joaquim-jose-de-castro-ferreira",fullName:"Joaquim José de Castro Ferreira",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"437899",title:"MSc.",name:"Miguel Angel",middleName:null,surname:"Ángel Castillo-Martínez",slug:"miguel-angel-angel-castillo-martinez",fullName:"Miguel Angel Ángel Castillo-Martínez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"289955",title:"Dr.",name:"Raja",middleName:null,surname:"Kishor Duggirala",slug:"raja-kishor-duggirala",fullName:"Raja Kishor Duggirala",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Jawaharlal Nehru Technological University, Hyderabad",country:{name:"India"}}}]}},subseries:{item:{id:"4",type:"subseries",title:"Fungal Infectious Diseases",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment",scope:"Fungi are ubiquitous and there are almost no non-pathogenic fungi. Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",hasOnlineFirst:!0,hasPublishedBooks:!1,annualVolume:11400,editor:{id:"174134",title:"Dr.",name:"Yuping",middleName:null,surname:"Ran",slug:"yuping-ran",fullName:"Yuping Ran",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9d6QAC/Profile_Picture_1630330675373",biography:"Dr. Yuping Ran, Professor, Department of Dermatology, West China Hospital, Sichuan University, Chengdu, China. Completed the Course Medical Mycology, the Centraalbureau voor Schimmelcultures (CBS), Fungal Biodiversity Centre, Netherlands (2006). International Union of Microbiological Societies (IUMS) Fellow, and International Emerging Infectious Diseases (IEID) Fellow, Centers for Diseases Control and Prevention (CDC), Atlanta, USA. Diploma of Dermatological Scientist, Japanese Society for Investigative Dermatology. Ph.D. of Juntendo University, Japan. Bachelor’s and Master’s degree, Medicine, West China University of Medical Sciences. Chair of Sichuan Medical Association Dermatology Committee. General Secretary of The 19th Annual Meeting of Chinese Society of Dermatology and the Asia Pacific Society for Medical Mycology (2013). In charge of the Annual Medical Mycology Course over 20-years authorized by National Continue Medical Education Committee of China. Member of the board of directors of the Asia-Pacific Society for Medical Mycology (APSMM). Associate editor of Mycopathologia. Vice-chief of the editorial board of Chinses Journal of Mycology, China. 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