The bonding in a cronstedtite layer was studied using a ninefold ordered supercell band structure calculation. The tight-binding scheme based upon the extended Hückel method was used to predict the electronic structure. The size of the problem was 162 atoms with 798 valence orbitals. The calculation showed different orbital interactions of oxygen p-orbitals with neighboring atoms with respect to the position in the layer. Substitution of Fe for Si in the terahedra reduced the role of the valence p-orbitals of the central Fe atoms. The d-orbitals of Fe were split in accordance with the rule of t2g-eg splitting. Although the density of states at the Fermi level was high, the partially filled 3d-bands were too narrow to permit normal metallic conduction.

The computational tool integrating empirical tight binding and full configuration interaction method is utilized to study the structural and optical properties of spherical PbX (X = S, Se, and Te) nanocrystals under various diameters. The nanocrystal architecture plays an essential role in the control of the structural and optical properties. The appearance of the quantum confinement is caused by the reduction of the optical band gaps with the increasing diameters. By changing the chalcogenide types and diameters, the band gaps are modified, with their wavelengths from 380 to 2500 nm, technologically applying for the visible and near-infrared optical devices. The tight-binding band gaps agree well with previously published theoretical and experimental values. The atomistic electron–hole interactions are mainly influenced by the diameters and chalcogenide types. Using the Stokes shift and fine structure splitting, PbS nanocrystal with the immense size may be implemented as a source of entangled photon pairs and optical filter. Finally, the theoretical study reveals the distinctive properties of PbX (X = S, Se, and Te) nanocrystals by changing their architecture for applications in optoelectronic devices and microscopy.

Ab initio design of polymer nanocomposite materials for high breakdown strength requires prediction of localized trap states at the polymer–filler interface. Systematic first-principles calculations of realistic interfaces can be challenging, particularly for amorphous polymers and fillers that necessitate the calculation of ensembles of large unit cells with hundreds of atoms. We present a computational approach for automatically generating reasonable structures for amorphous polymer–filler interfaces, combining classical molecular dynamics and Monte Carlo simulations. We identify trap states by analyzing the localization of electronic eigenstates calculated using density functional theory on ensembles of interface structures, clearly distinguishing shallow trap states from delocalized band-edge states. Applying this approach to silica–polyethylene interfaces as an initial example, we find under-coordination and distorted coordination structures at amorphous silica surfaces contribute a combination of deep and shallow traps at these interfaces, whereas polyethylene does not generate localized interfacial states.

Nihonium, Nh, is one of the newly synthesized elements. It has a high atomic number of 113, putting it in the same group as thallium, Tl. The properties of this element are largely unknown, and it is of interest to assess its (hypothetical) properties in the solid state. Elements in the same group of the periodic table as Nh are known to form binary and even tertiary compounds that have important semiconductor properties. This also makes studies on Nh attractive. We performed an ab initio computational study of its electronic structure adopting the local density and generalized gradient approximations for the exchange-correlation potential. The energy band diagrams, the total energies per volume of unit cells and density of states of Nh were compared to the known experimental and theoretical properties of elemental Tl , which lies in the same column above Nh in the periodic table. Within the limits of density-functional theory, it was found that solid Nh is expected to be a metal that is most stable in a hexagonal close packing structure.

In the present study we employ electronic structure calculations (based on Density Functional Theory -DFT approach) and Fully Atomistic Reactive Molecular Dynamics (FARMD) simulations (based on ReaxFF reactive force field) to evaluate the reactivity of branched polyfuran (PF) derivatives and identify promising systems for chemical sensing. Condensed-to-atoms Fukui indexes (CAFI) were employed to identify the most reactive sites on the oligomers structure. The chemical sensing abilities of the most promising systems were evaluated via FARMD simulations in the presence of distinct gaseous compounds. The results indicate the derivatives PF-CCH and PF-NO₂ (i.e. CCH and NO2 as side groups) as the most promising systems for chemical sensor applications, presenting higher reactivity on the most accessible sites. An interesting correspondence between DFT and MD results was also identified, suggesting the plausibility of using CAFI parameters for the identification of improved materials for chemical sensors.

Crystal structure and electronic structure of YMnO3 were investigated by X-ray diffraction and transmission electron microscopy related techniques. According to the density of states (DOS), the individual interband transitions to energy loss peaks in the low energy loss spectrum were assigned. The hybridization of O 2p with Mn 3d and Y 4d analyzed by the partial DOS was critical to the ferroelectric nature of YMnO3. From the simulation of the energy loss near-edge structure, the fine structure of O K-edge was in good agreement with the experimental spectrum. The valence state of Mn (+3) in YMnO3 was determined by a comparison between experiment and calculations.

Atomically resolved imaging of materials enabled by the advent of aberration-corrected scanning transmission electron microscopy (STEM) has become a mainstay of modern materials science. However, much of the wealth of quantitative information contained in the fine details of atomic structure or spectra remains largely unexplored. In this article, we discuss new opportunities enabled by physics-informed big data and machine learning technologies to extract physical information from static and dynamic STEM images, ranging from statistical thermodynamics of alloys to kinetics of solid-state reactions at a single defect level. The synergy of deep-learning image analytics and real-time feedback further allows harnessing beam-induced atomic and bond dynamics to enable direct atom-by-atom fabrication. Examples of direct atomic motion over mesoscopic distances, engineered doping at selected lattice sites, and assembly of multiatomic structures are reviewed. These advances position the scanning transmission electron microscope to transition from a mere imaging tool toward a complete nanoscale laboratory for exploring electronic, phonon, and quantum phenomena in atomically engineered structures.

While rhenium has proven to be an ideal material in fast-cycling high-temperature applications such as rocket nozzles, its prohibitive cost limits its continued use and motivates a search for viable cost-effective substitutes. We show that a simple design principle that trades off average valence electron count and cost considerations proves helpful in identifying a promising pool of candidate substitute alloys: The Mo–Ru–Ta–W quaternary system. We demonstrate how this picture can be combined with a computational thermodynamic model of phase stability, based on high-throughput ab initio calculations, to further narrow down the search and deliver alloys that maintain rhenium’s desirable hcp crystal structure. This thermodynamic model is validated with comparisons to known binary phase diagram sections and corroborated by experimental synthesis and structural characterization demonstrating multiprinciple-element hcp solid-solution samples selected from a promising composition range.

A series of ${\left\hbox[ {{{\left\hbox( {{\rm{SnSe}}} \right\hbox)}_{1 \hbox+ \delta }}} \right\hbox]_m}{\left\hbox[ {{\rm{TiS}}{{\rm{e}}_2}} \right\hbox]_2}$ heterostructure thin films built up from repeating units of m bilayers of SnSe and two layers of TiSe2 were synthesized from designed precursors. The electronic structure of the films was investigated using X-ray photoelectron spectroscopy for samples with m = 1, 2, 3, and 7 and compared to binary samples of TiSe2 and SnSe. The observed binding energies of core levels and valence bands of the heterostructures are largely independent of m. For the SnSe layers, we can observe a rigid band shift in the heterostructures compared to the binary, which can be explained by electron transfer from SnSe to TiSe2. The electronic structure of the TiSe2 layers shows a more complicated behavior, as a small shift can be observed in the valence band and Se3d spectra, but the Ti2p core level remains at a constant energy. Complementary UV photoemission spectroscopy measurements confirm a charge transfer mechanism where the SnSe layers donate electrons into empty Ti3d states at the Fermi energy.

The discovery, design, and development of new alloys have long been critical elements of advanced engineering systems. Challenged by their chemical and structural complexity, this design process is, however, often too slow. This article highlights progress in theory, computation, data, and advanced experimental techniques that are advancing our capabilities for rapid discovery and design of new multicomponent alloys. Applied across the length scales, these new capabilities support exploration across broad composition spaces; examples of new materials and associated advances in the understanding of underlying thermochemical and thermomechanical phenomena are presented. We highlight current challenges, gaps, and specific areas that, if further developed, could have future high payoff.

Density functional theory (DFT) has proved to be exceptionally successful in rationalizing trends in activity and functionality for electrochemical functional materials. With continued increases in computing power, there has been an increased interest in “high-throughput” materials discovery and design based on a few descriptors to scan the phase space en masse for thousands of potential candidates, which could be made technologically and commercially viable. However, given fundamental accuracy limitations associated with DFT, the success of high-throughput material discovery efforts has been limited. In this review, we suggest an additional dimension to aid in high-throughput material discovery related to uncertainty quantification and propagation, which provides a more realistic picture of the likelihood of new candidate materials to improve upon known materials. We demonstrate the approach and its utility through two case studies: (1) electrocatalyst materials for their activity and selectivity for the oxygen reduction reaction, and (2) cathode materials for Li-ion batteries based on Ni-Mn-Co oxides. The ease with which uncertainty quantification and propagation can be incorporated into traditional high-throughput material discovery with almost no additional computational cost allows for its proposed wide usage.

Porphyrins are a class of conjugated molecules that structurally and functionally resemble natural photosynthetic and enzymatic chromophores. Crystalline solids self-assembled from anionic and cationic porphyrins yield a new class of multifunctional optoelectronic micro- and nanomaterials. In this article, we provide details on the concept of binary ionic self-assembly (ISA) and ionized forms of porphyrins, as well as formation of hierarchical structures, including nanotubes, rods and ribbons, sheets, and three-dimensional clover-like shapes, spheres, and sheaf-like structures. We summarize key physical properties from ultraviolet–visible characterizations of J-aggregate, exciton delocalization and extended π–π stacking, and related electronic and light-harvesting properties of the structures. Depending on the molecular subunits, the functionalities of the ISA materials are altered. These ISA nanostructures possess attractive light-harvesting and charge- and energy-transport functionalities and allow access to a novel class of nanomaterials with potential for applications in sensors, photovoltaics, photocatalysis, and solar power.

In this study, we investigated the elastic constants, moduli, hardness, and electronic structures of Ti–Al intermetallic compounds (TiAl, Ti3Al, and TiAl3) using first-principles calculations. The cohesive energy and formation enthalpy of these compounds are negative, which indicates that they are thermodynamically stable. We calculated the elastic constants and moduli using the stress–strain method and Voigt–Reuss–Hill approximation, respectively. We evaluated the mechanical anisotropy of these compounds using the anisotropic index and found that the results are in good agreement with other experimental and theoretical data. We evaluated the chemical bonding of these compounds by calculating their density of states, the results of which revealed that the bonding behavior of all Ti–Al intermetallic compounds involved a mixture of metallic and covalent bonds. We also estimated the Debye temperature and sound velocities of these Ti–Al intermetallic compounds.

Layered zirconium hydrogen phosphate intercalation compounds can be easily tuned, leading to potential applications in many fields, specifically by introducing them in different polymeric composites as nanofillers. Employing first-principles density functional theory based calculations, we have investigated ground state electronic structure properties of α-zirconium hydrogen phosphate (α-ZrP). We discuss the structure and electronic band structure, where projected density of states calculations have been discussed to understand the different atomic orbitals contributions to electronic bands. ZrP has numerous properties of interest for use in many semiconductor device structures, specifically, layered zirconium hydrogen phosphate has substantial promise for both optical devices and for high power electronics due to its large direct band gap. Our structural calculations suggest that layered zirconium hydrogen phosphate exhibits monoclinic structure. The calculated structural parameters and band gap are in good agreement with available experimental data.

We report on structural, magnetic, optical, and dielectric properties of rare earth (Er and Yb)-doped ZnO nanoparticles with Na-co-doping for charge compensation by sol-gel process. The effect of doping concentration on the structural and dielectric properties of ZnO has been studied under magnetic field and UV excitation. The magnetodielectric and photodielectric effects at room temperature of doped ZnO are discussed in the light of magnetic and optical properties of Er3+ and Yb3+ ions.

In recent years, modified graphene has been used in various biomedical applications due to its excellent properties that allow the development of devices capable of detecting macromolecules within the human organism, also for biomolecular analysis, discovery of biomarkers, bioimaging and target delivery. These applications involve interactions between enzymes, proteins, peptides, DNA, RNA, etc. and modified graphene, therefore the study and the theoretical and experimental investigation of these interactions is essential for the development of nanobio-technology. For example, many applications based on using modified graphene to detect macromolecules require studying the changes in the properties of doped graphene when interacting with macromolecules. In this work, DFT and molecular dynamics methods were used to obtain results of the changes in energy density of states of graphene doped with iron when it is made to interact with coenzyme A. Besides, we presented a study of molecular dynamics in order to determine the quantum factors that guide the interaction graphene-coenzyme A. The system was studied in aqueous medium which it was simulated by the dielectric constant of water. The results confirm that the methodology presented in this work can be used to theoretically detect various macromolecules.

MXenes are a novel class of two dimensional materials, discovered by Barsoum and Gogotsi [M. Naguib, J. Come, B. Dyatkin, V. Presser, P. Taberna, P. Simon, M. W. Barsoum, and Y. Gogotsi, Electrochemistry Communications 16, 61-64 (2012); B. Anasori, M. R. Lukatskaya, and Y. Gogotsi, Nature Reviews Materials vol. 2, 16098 (2017)]. Their large specific surface area and the tunability of their physicochemical properties as a function of the transition metal and surface terminal group make them a unique design platform for various applications, a primary example of which is pseudocapacitive energy storage. However, there is still incomplete understanding of how the transition metal chemistry and stoichiometry, and the surface termination affect charge storage mechanisms in MXene. In this study, we have performed systematic first-principles calculations for bulk MXene and found that the atomic charge of the metal cations, which is related to their valence, decreases across the d-electron metal series. Electronic-structure indicators of performance are examined to understand the energy storage behavior, whereby charges are stored between the terminal groups and adsorbing cations. Importantly, we found that the differential Bader charges show good agreement with theoretical capacitances and are useful in predicting charge storage trends in MXene-based pseudocapacitors. Furthermore, we have performed first-principles and grand canonical Monte Carlo calculations for the slab systems, finding that the solvent plays a critical role in enhancing the pseudocapacitive response.

We present a general purpose Pt-Pt density-functional tight-binding (DFTB) parameter for Pt clusters as well as bulk, using a genetic algorithm (GA) to automatize the parameterization effort. First we quantify the improvement possible by only optimizing the repulsive potential alone, and second we investigate the effect of improving the electronic parameter as well. During both parameterization efforts we employed our own training set and test sets, with one set containing ∼20,000 spin-polarized DFT structures. We analyze the performance of our two DFTB Pt-Pt parameter sets against density functional theory (DFT) as well as an earlier DFTB Pt-Pt parameters. Our study sheds light on the role of both repulsive and electronic parameters with regards to DFTB performance.