DFT-1/2 and shell DFT-1/2 methods: electronic structure calculation for semiconductors at LDA complexity.

It is known that the Kohn-Sham eigenvalues do not characterize experimental excitation energies directly, and the band gap of a semiconductor is typically underestimated by local density approximation (LDA) of density functional theory (DFT). An embarrassing situation is that one usually uses LDA+Ufor strongly correlated materials with rectified band gaps, but for non-strongly-correlated semiconductors one has to resort to expensive methods like hybrid functionals orGW. In spite of the state-of-the-art meta-generalized gradient approximation functionals like TB-mBJ and SCAN, methods with LDA-level complexity to rectify the semiconductor band gaps are in high demand. DFT-1/2 stands as a feasible approach and has been more widely used in recent years. In this work we give a detailed derivation of the Slater half occupation technique, and review the assumptions made by DFT-1/2 in semiconductor band structure calculations. In particular, the self-energy potential approach is verified through mathematical derivations. The aims, features and principles of shell DFT-1/2 for covalent semiconductors are also accounted for in great detail. Other developments of DFT-1/2 including conduction band correction, DFT+A-1/2, empirical formula for the self-energy potential cutoff radius, etc, are further reviewed. The relations of DFT-1/2 to hybrid functional, sX-LDA,GW, self-interaction correction, scissor's operator as well as DFT+Uare explained. Applications, issues and limitations of DFT-1/2 are comprehensively included in this review.

HfOx /AlOy Superlattice-Like Memristive Synapse.

The adjustable conductance of a two-terminal memristor in a crossbar array can facilitate vector-matrix multiplication in one step, making the memristor a promising synapse for efficiently implementing neuromorphic computing. To achieve controllable and gradual switching of multi-level conductance, important for neuromorphic computing, a theoretical design of a superlattice-like (SLL) structure switching layer for the multi-level memristor is proposed and validated, refining the growth of conductive filaments (CFs) and preventing CFs from the abrupt formation and rupture. Ti/(HfOx /AlOy )SLL /TiN memristors are shown with transmission electron microscopy , X-ray photoelectron spectroscopy , and ab initio calculation findings corroborate the SLL structure of HfOx /AlOy film. The optimized SLL memristor achieves outstanding conductance modulation performance with linearly synaptic weight update (nonlinear factor α = 1.06), and the convolutional neural network based on the SLL memristive synapse improves the handwritten digit recognition accuracy to 94.95%. Meanwhile, this improved synaptic device has a fast operating speed (30 ns), a long data retention time (≥ 104 s at 85 â„ƒ), scalability, and CMOS process compatibility. Finally, its physical nature is explored and the CF evolution process is characterized using nudged elastic band calculations and the conduction mechanism fitting. In this work, as an example the HfOx /AlOy SLL memristor provides a design viewpoint and optimization strategy for neuromorphic computing.

Evolution of the conductive filament system in HfO2-based memristors observed by direct atomic-scale imaging.

The resistive switching effect in memristors typically stems from the formation and rupture of localized conductive filament paths, and HfO2 has been accepted as one of the most promising resistive switching materials. However, the dynamic changes in the resistive switching process, including the composition and structure of conductive filaments, and especially the evolution of conductive filament surroundings, remain controversial in HfO2-based memristors. Here, the conductive filament system in the amorphous HfO2-based memristors with various top electrodes is revealed to be with a quasi-core-shell structure consisting of metallic hexagonal-Hf6O and its crystalline surroundings (monoclinic or tetragonal HfOx). The phase of the HfOx shell varies with the oxygen reservation capability of the top electrode. According to extensive high-resolution transmission electron microscopy observations and ab initio calculations, the phase transition of the conductive filament shell between monoclinic and tetragonal HfO2 is proposed to depend on the comprehensive effects of Joule heat from the conductive filament current and the concentration of oxygen vacancies. The quasi-core-shell conductive filament system with an intrinsic barrier, which prohibits conductive filament oxidation, ensures the extreme scalability of resistive switching memristors. This study renovates the understanding of the conductive filament evolution in HfO2-based memristors and provides potential inspirations to improve oxide memristors for nonvolatile storage-class memory applications.

A new family of two-dimensional ferroelastic semiconductors with negative Poisson's ratios.

Two-dimensional (2D) materials with both ferroelasticity and negative Poisson's ratios have attracted intensive interest, but it is very rare to have both ferroelasticity and negative Poisson's ratios in a single material. Directional positive and negative Poisson's ratios in a switchable ferroelastic dielectric may enable non-destructive readout in ferroelastic data storage. Herein, we propose 14 kinds of stable 2D semiconductors: AB monolayers (A = Sc, Y, La; B = N, P, As, Sb, Bi) based on first-principles calculations. The band gaps of AB monolayers cover a wide range from 0.69 eV to 2.15 eV. Mechanical analysis reveals that these materials are flexible and 12 of 14 are predicted to possess an in-plane negative Poisson's ratio (NPR). Moreover, 10 of these 14 systems possess an out-of-plane NPR. More encouragingly, all AB monolayers are identified as 2D ferroelastic materials with reversible strains of around 5.94% to 20.30%. The ferroelastic switching barriers, mechanical properties and electronic structures of these materials are discussed in detail. Such outstanding properties make the AB monolayers very promising as switchable anisotropic 2D materials for nanoelectronics and micromechanical applications.