Beyond metals: theoretical discovery of semiconducting MAX phases and their potential application in thermoelectrics.

MAX phase is a family of ceramic compounds, typically known for their metallic properties. However, we show here that some of them may be narrow bandgap semiconductors. Using a series of first-principles calculations, we have investigated the electronic structures of 861 dynamically stable MAX phases.

D-Band Engineering in Pd-Based Nanowire Networks for Further Enhancement in Ethanol Electrooxidation Reaction.

The development of highly efficient electrocatalysts for the ethanol oxidation reaction (EOR) is essential for the commercialization of direct ethanol fuel cells, yet challenges remain. In this study, a one-pot solution-phase method to synthesize Pd nanowire networks (NNWs) with very high surface-to-volume ratio having numerous twin and grain boundaries is developed. Using the same method, the Pd lattice is further engineered by introducing Ag and Cu atoms to produce AgPd, and CuPd alloy structure which significantly shifts the Pd d-band center upward and downward, respectively due to strain and ligand effects.

Magneto-transport in the monolayer MoSmaterial system for high-performance field-effect transistor applications.

Electronic transport in monolayer MoSis significantly constrained by several extrinsic factors despite showing good prospects as a transistor channel material. Our paper aims to unveil the underlying mechanisms of the electrical and magneto-transport in monolayer MoS. In order to quantitatively interpret the magneto-transport behavior of monolayer MoSon different substrate materials, identify the underlying bottlenecks, and provide guidelines for subsequent improvements, we present a deep analysis of the magneto-transport properties in the diffusive limit.

WS-Graphene van der Waals Heterostructure as Promising Anode Material for Lithium-Ion Batteries: A First-Principles Approach.

In this work, we report the results of density functional theory (DFT) calculations on a van der Waals (VdW) heterostructure formed by vertically stacking single-layers of tungsten disulfide and graphene (WS2/graphene) for use as an anode material in lithium-ion batteries (LIBs). The electronic properties of the heterostructure reveal that the graphene layer improves the electronic conductivity of this hybrid system. Phonon calculations demonstrate that the WS2/graphene heterostructure is dynamically stable.

Insights into Heterogeneous Catalysis on Surfaces with 3d Transition Metals: Spin-Dependent Chemisorption Models and Magnetic Field Effects.

This Perspective provides an overview of recent developments in the field of 3d transition metal (TM) catalysts for different reactions, including oxygen-based reactions such as the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). The spin moments of 3d TMs can be exploited to influence chemical reactions, and recent advances in this area, including the theory of chemisorption based on spin-dependent d-band centers and magnetic field effects, are discussed. The Perspective also explores the use of scaling relationships and surface magnetic moments in catalyst design as well as the effect of magnetism on chemisorption and vice versa.

Combining First-Principles Modeling and Symbolic Regression for Designing Efficient Single-Atom Catalysts in the Oxygen Evolution Reaction on MoCO MXenes.

In this study, we address the significant challenge of overcoming limitations in the catalytic efficiency for the oxygen evolution reaction (OER). The current linear scaling relationships hinder the optimization of the electrocatalytic performance. To tackle this issue, we investigate the potential of designing single-atom catalysts (SACs) on MoCO MXenes for electrochemical OER using first-principles modeling simulations.

Spin torques and anomalous velocity in spin textures induced by fast electron injection from topological ferromagnets: The role of gauge fields.

A new method for analyzing magnetization dynamics in spin textures under the influence of fast electron injection from topological ferromagnetic sources such as Dirac half metals has been proposed. These electrons, traveling at a velocitywith a non-negligible value ofv/c(whereis the speed of light), generate a non-equilibrium magnetization density in the spin-texture region, which is related to an electric dipole moment via relativistic interactions. When this resulting dipole moment interacts with gauge fields in the spin-texture region, an effective field is created that produces spin torques.

Chemical Bonding in Large Systems Using Projected Population Analysis from Real-Space Density Functional Theory Calculations.

We present an efficient and scalable computational approach for conducting projected population analysis from real-space finite-element (FE)-based Kohn-Sham density functional theory calculations (). This work provides an important direction toward extracting chemical bonding information from large-scale DFT calculations on materials systems involving thousands of atoms while accommodating periodic, semiperiodic, or fully nonperiodic boundary conditions. Toward this, we derive the relevant mathematical expressions and develop efficient numerical implementation procedures that are scalable on multinode CPU architectures to compute the projected overlap and Hamilton populations.

Can magnetotransport properties provide insight into the functional groups in semiconducting MXenes?

Hall scattering factors of ScCF, ScCO and ScC(OH) are calculated using Rode's iterative approach by solving the Boltzmann transport equation. This is carried out in conjunction with calculations based on density functional theory. The electrical transport in ScCF, ScCO and ScC(OH) is modelled by accounting for both elastic (acoustic and piezoelectric) and inelastic (polar optical phonon) scattering.

Computational design of novel MAX phase alloys as potential hydrogen storage media combining first principles and cluster expansion methods.

Finding a suitable material for hydrogen storage under ambient atmospheric conditions is challenging for material scientists and chemists. In this work, using a first principles based cluster expansion approach, the hydrogen storage capacity of the TiAC (A = Al, Ti, Cr, Mn, Fe, Co, Ni, Cu, and Zn) MAX phase and its alloys was studied. We found that hydrogen is energetically stable in Ti-A layers in which the tetrahedral site consisting of one A atom and three Ti atoms is energetically more favorable for hydrogen adsorption than other sites in the Ti-A layer.

Universal Ligands for Dispersion of Two-Dimensional MXene in Organic Solvents.

Ligands can control the surface chemistry, physicochemical properties, processing, and applications of nanomaterials. MXenes are the fastest growing family of two-dimensional (2D) nanomaterials, showing promise for energy, electronic, and environmental applications. However, complex oxidation states, surface terminal groups, and interaction with the environment have hindered the development of organic ligands suitable for MXenes.

Constructing electrospun spinel NiFeO nanofibers decorated with palladium ions as nanosheets heterostructure: boosting electrocatalytic activity of HER in alkaline water electrolysis.

The development of efficient electrocatalysts for the water splitting process and understanding their fundamental catalytic mechanisms are highly essential to achieving high performance in energy conversion technologies. Herein, we have synthesised spinel nickel ferrite nanofibers (NiFeO-NFs) an electrospinning (ES) method followed by a carbonization process. The resultant fiber was subjected to electrocatalytic water splitting reactions in alkaline medium.

Identifying the Critical Surface Descriptors for the Negative Slopes in the Adsorption Energy Scaling Relationships via Density Functional Theory and Compressed Sensing.

Adsorption energy scaling relationships have progressed beyond their original form, which was primarily focused on optimizing catalytic sites and lowering computational costs in simulations. The recent rise in interest in adsorption energy scaling relations is to investigate surfaces other than transition metals (TMs) as well as interactions involving complex compounds. In this work, we report our extensive study on the scaling relation (SR) between oxygen (O), with elements of neighboring groups such as boron (B), aluminum (Al), carbon (C), silicon (Si), nitrogen (N), phosphorus (P), and fluorine (F) on magnetic bimetallic surfaces.

DJMol: An open-source modeling platform for computational chemistry and materials science with a Python interpreter.

We present a modular and extendable software suite, DJMol, for performing molecular simulations and it is demonstrated with DFTB+, Siesta, Atomic Simulation Environment, and OpenMD codes. It supports many of the standard features of an integrated development environment and consists of a structure builder and viewer, which could be connected with these electronic structure codes along with a set of data analyzers. This program comprises Java and Python modules and its libraries to carry out a different set of modeling tasks in materials science and chemistry.

Population analysis with Wannier orbitals.

We formulate Wannier orbital overlap population and Wannier orbital Hamilton population to describe the contribution of different orbitals to electron distribution and their interactions. These methods, which are analogous to the well-known crystal orbital overlap population and crystal orbital Hamilton population, provide insight into the distribution of electrons at various atom centers and their contributions to bonding. We apply this formalism in the context of a plane-wave density functional theory calculation.

Cooperation and competition between magnetism and chemisorption.

Chemisorption on ferromagnetic and non-magnetic surfaces is discussed within the Newns-Anderson-Grimley model along with the Stoner model of ferromagnetism. In the case of ferromagnetic surfaces, the adsorption energy is formulated in terms of the change in surface magnetic moments. Using such a formulation, we address the issue of how an adsorbate's binding strength depends on the magnetic moments of the surface and how the adsorption process reduces/enhances the magnetic moments of the surface.

Adsorption energy scaling relation on bimetallic magnetic surfaces: role of surface magnetic moments.

The scaling relationships between the adsorption energies of different reaction intermediates have a tremendous effect in the field of surface science, particularly in predicting new catalytic materials. In the last few decades, these scaling laws have been extensively studied and interpreted by a number of research groups which makes them almost universally accepted. In this work, we report the breakdown of the standard scaling law in magnetic bimetallic transition metal (TM) surfaces for hydrogenated species of oxygen (O), carbon (C), and nitrogen (N), where the adsorption energies are estimated using density functional theory (DFT).

Transition metal substituted FeP: potential candidate for MRAM application.

We propose transition metal substituted FeP as a new promising material for spin-transfer torque magnetic random-access memory (STT-MRAM) application. Using first-principles calculations based on density functional theory and Monte Carlo simulations, we demonstrate that this material can be used as a ferromagnetic electrode in the magnetic tunnel junction (MTJ) of STT-MRAM due to its moderate perpendicular magnetic anisotropy, high ferromagnetic transition temperature, and large tunnel magnetoresistance. This work is expected to provide a basis for the development of a new class of FeP-based electrode materials for STT-MRAM devices.

Machine Learning and Scaling Laws for Prediction of Accurate Adsorption Energy.

Finding an "ideal" catalyst is a matter of great interest in the communities of chemists and material scientists, partly because of its wide spectrum of industrial applications. Information regarding a physical parameter termed "adsorption energy", which dictates the degrees of adhesion of an adsorbate on a substrate, is a primary requirement in selecting the catalyst for catalytic reactions. Both experiments and in silico modeling are extensively being used in estimating the adsorption energies, both of which are an Edisonian approach, demand plenty of resources, and are time-consuming.