Temperature dependent Band gap Correction model using tight-binding approach for UTB device simulations

<div>Ultra-thin body (UTB) devices are being used in many electronic applications operating over a wide range of temperatures. The electrostatics of these devices depends on the band structure of the channel material, which varies with temperature as well as channel thickness. The semi-empirical tight binding (TB) approach is widely used for calculating channel thickness dependent band structure of any material, at a particular temperature, where TB parameters are defined. For elementary semiconductors like Si, Ge and compound semiconductors like GaAs, these TB parameters are generally defined at only 0 K and 300 K. This limits the ability of the TB approach to simulate the electrostatics of these devices at any other intermediate temperatures.</div><div>In this work, we analyze the variation of band structure for Si, Ge and GaAs over different channel thicknesses at 0 K and 300 K (for which TB parameters are available), and show that the band curvature at the band minima has minor variation with temperature, whereas the change of band gap significantly affects the channel electrostatics. Based on this finding, we propose an approach to simulate the electrostatics of UTB devices, at any temperature between 0 K and 300 K, using TB parameters defined at 0 K, along with a suitable channel thickness and temperature dependent band gap correction. </div>

Strongly localized states and giant optical absorption induced by multiple flat-bands in AA-stacked multilayer armchair graphenenanoribbons

We propose an AA-stacked multilayer graphene nanoribbon with two symmetrical armchair edges as a multiple flat-band (FB) material. Using the tight-binding Hamiltonian and Green’s function method, we find that the FBs are complete and merged into many dispersive bands. The FBs cause multiple strongly localized states (SLSs) at the sites of the odd lines in every sublayer and a giant optical absorption (GOA) at energy point 2t, where t is the electronic intralayer hopping energy between two nearest-neighbor sites. By driving an electric field perpendicular to the ribbon plane, the bandgaps of the FBs are tunable. Accordingly, the positions of the SLSs in the energy regime can be shifted. However, the position of the GOA is robust against such field, but its strength exhibits a collapse behavior with a fixed quantization step. On the contrary, by driving an electric field parallel to the ribbon plane, the completeness of FBs is destroyed. Resultantly, the SLSs and GOA are suppressed and even quenched. Therefore, such ribbons may be excellent candidates for the design of the controllable information-transmission and optical-electric nanodevices.

Temperature dependent Band gap Correction model using tight-binding approach for UTB device simulations

<div>Ultra-thin body (UTB) devices are being used in many electronic applications operating over a wide range of temperatures. The electrostatics of these devices depends on the band structure of the channel material, which varies with temperature as well as channel thickness. The semi-empirical tight binding (TB) approach is widely used for calculating channel thickness dependent band structure of any material, at a particular temperature, where TB parameters are defined. For elementary semiconductors like Si, Ge and compound semiconductors like GaAs, these TB parameters are generally defined at only 0 K and 300 K. This limits the ability of the TB approach to simulate the electrostatics of these devices at any other intermediate temperatures.</div><div>In this work, we analyze the variation of band structure for Si, Ge and GaAs over different channel thicknesses at 0 K and 300 K (for which TB parameters are available), and show that the band curvature at the band minima has minor variation with temperature, whereas the change of band gap significantly affects the channel electrostatics. Based on this finding, we propose an approach to simulate the electrostatics of UTB devices, at any temperature between 0 K and 300 K, using TB parameters defined at 0 K, along with a suitable channel thickness and temperature dependent band gap correction. </div>

Topological viewpoint of two-dimensional group III-V and IV-IV compounds in the presence of electric field and spin-orbit coupling by density functional theory and tight-binding model

Using the tight-binding model and density functional theory, the topological invariant of the two-dimensional (2D) group III-V and IV-IV compounds are studied in the absence and the presence of an external perpendicular electric field and spin-orbit coupling. It will be recognized that a critical value of these parameters changes the topological invariant of 2D graphene-like compounds. The significant effects of an external electric field and spin-orbit coupling are considered to the two-center overlap integrals of the Slater-Koster model involved in band structures, changing band-gap, and tuning the topological phase transition between ordinary and quantum spin Hall regime. These declare the good consistency between two theories: tight-binding and density functional. So, this study reveals topological phase transition in these materials. Our finding paves a way to extend an effective Hamiltonian, and may instantly clear some computation aspects of the study in the field of spintronic based on the first-principles methods.

A DFTB-Based Molecular Dynamics Investigation of an Explicitly Solvated Anatase Nanoparticle

We performed a self-consistent charge density functional tight-binding molecular dynamics (SCC DFTB-MD) simulation of an explicitly solvated anatase nanoparticle. From the 2 ps trajectory, we were able to calculate both dynamic and static properties, such as the energies of interaction and the formation of water layers at the surface, and compare them to the observed behaviour reported elsewhere. The high degree of agreement between our simulation and other sources, and the additional information gained from employing this methodology, highlights the oft-overlooked viability of DFTB-based methods for electronic structure calculations of large systems.

Localization Properties of a Quasiperiodic Ladder under Physical Gain and Loss: Tuning of Critical Points, Mixed-Phase Zone and Mobility Edge

We explore the localization properties of a double-stranded ladder within a tight-binding framework where the site energies of different lattice sites are distributed in the cosine form following the Aubry–André–Harper (AAH) model. An imaginary site energy, which can be positive or negative, referred to as physical gain or loss, is included in each of these lattice sites which makes the system a non-Hermitian (NH) one. Depending on the distribution of imaginary site energies, we obtain balanced and imbalanced NH ladders of different types, and for all these cases, we critically investigate localization phenomena. Each ladder can be decoupled into two effective one-dimensional (1D) chains which exhibit two distinct critical points of transition from metallic to insulating (MI) phase. Because of the existence of two distinct critical points, a mixed-phase (MP) zone emerges which yields the possibility of getting a mobility edge (ME). The conducting behaviors of different energy eigenstates are investigated in terms of inverse participation ratio (IPR). The critical points and thus the MP window can be selectively controlled by tuning the strength of the imaginary site energies which brings a new insight into the localization aspect. A brief discussion on phase transition considering a multi-stranded ladder was also given as a general case, to make the present communication a self-contained one. Our theoretical analysis can be utilized to investigate the localization phenomena in different kinds of simple and complex quasicrystals in the presence of physical gain and/or loss.

Artificial Neural Network Potentials for Mechanics and Fracture Dynamics of Materials

Atomistic understanding of mechanics and failure of materials is the key for engineering and applications. Modeling accurately brittle failure with crack propagation in covalent crystals requires a quantum mechanics-based description of individual bond-breaking events for large system sizes. Machine Learned (ML) potentials have emerged to overcome the traditional, physics-based modeling tradeoff between accuracy and accessible time and length scales. Previous studies have shown successful applications of ML potentials for describing the structure and dynamics of molecular systems and amorphous or liquid phases of materials. However, their application to deformation and failure processes in materials is yet uncommon. In this study, we discuss apparent limitations of ML potentials to describe deformation and fracture under loadings and propose a way to generate and select training data for their employment in simulations of deformation and fracture of crystals. We applied the proposed approach to 2D crystal graphene, utilizing the density-functional tight-binding (DFTB) method for more efficient and extensive data generation in place of density functional theory (DFT). Then, we explore how the data selection affects the accuracy of the developed artificial neural network potential (NNP), indicating that only the errors in total energies and atomic forces are insufficient to judge the NNP’s reliability. Therefore, we evaluate and select NNPs based on their performance in describing physical properties, e.g., stress-strain curves and geometric deformation. In sharp contrast to popular reactive bond order potentials, our optimized NNP predicts straight crack propagation in graphene along both armchair and zigzag lattice directions, as well as higher fracture toughness of zigzag edge direction. Our study provides significant insight into crack propagation mechanisms at atomic scales and highlights strategies for NNP developments of broader materials.

Molecular Mechanism of SARS-CoVs Orf6 Targeting the Rae1–Nup98 Complex to Compete With mRNA Nuclear Export

The accessory protein Orf6 is uniquely expressed in sarbecoviruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which is an ongoing pandemic. SARS-CoV-2 Orf6 antagonizes host interferon signaling by inhibition of mRNA nuclear export through its interactions with the ribonucleic acid export 1 (Rae1)–nucleoporin 98 (Nup98) complex. Here, we confirmed the direct tight binding of Orf6 to the Rae1-Nup98 complex, which competitively inhibits RNA binding. We determined the crystal structures of both SARS-CoV-2 and SARS-CoV-1 Orf6 C-termini in complex with the Rae1–Nup98 heterodimer. In each structure, SARS-CoV Orf6 occupies the same potential mRNA-binding groove of the Rae1–Nup98 complex, comparable to the previously reported structures of other viral proteins complexed with Rae1-Nup98, indicating that the Rae1–Nup98 complex is a common target for different viruses to impair the nuclear export pathway. Structural analysis and biochemical studies highlight the critical role of the highly conserved methionine (M58) of SARS-CoVs Orf6. Altogether our data unravel a mechanistic understanding of SARS-CoVs Orf6 targeting the mRNA-binding site of the Rae1–Nup98 complex to compete with the nuclear export of host mRNA, which further emphasizes that Orf6 is a critical virulence factor of SARS-CoVs.