940 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Ames National LaboratoryUS155 papers
- Iowa State UniversityUS152 papers
- Argonne National LaboratoryUS49 papers
- University of GlasgowGB49 papers
- University of OxfordGB49 papers
- Sapienza University of RomeIT46 papers
- The Ohio State UniversityUS46 papers
- University College LondonGB45 papers
- University of Wisconsin–MadisonUS43 papers
- Lomonosov Moscow State UniversityRU40 papers
- University of BonnDE32 papers
- University of California, Santa CruzUS32 papers
80 papers · 1 filter
Revealing the Role of Confined Molecular H in the Passivation of Defective Silicon Using First-Principles Simulations
Hania Azzam, Tobias Binninger, Benedikt Fischer +2
The passivation of silicon dangling bonds by hydrogen is a crucial requirement for silicon-based optoelectronic technology, especially for solar cells. Recent experiments on intens…
Discovery and Synthesis of a Family of Boride Altermagnets
Zhen Zhang, Eranga H. Gamage, Genevieve Amobi +6
Borides are a rich material family. To push the boundaries of borides' properties and applications into broader fields, we have conducted systematic theoretical and experimental se…
A Map of the Zintl AM2Pn2 Compounds: Influence of Chemistry on Stability and Electronic Structure
Andrew Pike, Zhenkun Yuan, Gideon Kassa +9
The AM2Pn2 (A= Ca, Sr, Ba, Yb, Mg; M= Mn, Zn, Cd, Mg; and Pn=N, P, As, Sb, Bi) family of Zintl phases has been known as thermoelectric materials and has recently gained much attent…
Microwave-driven synthesis and modification of nanocarbons and hybrids in liquid and solid phases
Nagaraj Nandihalli
Over the past 20 years, nanocarbons have become more significant as nanostructured fillers in composites and, more recently, as functional elements in a brand-new class of hybrid m…
Multiple magnetic interactions and large inverse magnetocaloric effect in TbSi and TbSiGe
Ajay Kumar, Prashant Singh, Andrew Doyle +2
We present a comprehensive investigation of the electronic structure, magnetization, specific heat, and crystallography of TbSi (FeB structure type) and TbSiGe (CrB…
Exploring the formation of gold/silver nanoalloys with gas-phase synthesis and machine-learning assisted simulations
Quentin Gromoff, Patrizio Benzo, Wissam A. Saidi +6
While nanoalloys are of paramount scientific and practical interests, the main processes leading to their formation are still poorly understood. Key structural features in the allo…
Density Functional Theory of Material Design: Fundamentals and Applications -- I
Prashant Singh, Manoj K Harbola
This article is part-I of a review of density-functional theory (DFT) that is the most widely used method for calculating electronic structure of materials. The accuracy and ease o…
Stacking up electron-rich and electron-deficient monolayers to achieve extraordinary mid- to far-infrared excitonic absorption: Interlayer excitons in the C3B/C3N bilayer
Zhao Tang, Greis J. Cruz, Fanhao Jia +3
Our ability to efficiently detect and generate far-infrared (i.e., terahertz) radiation is vital in areas spanning from biomedical imaging to interstellar spectroscopy. Despite dec…
Vacancy formation energies and migration barriers in multi-principal element alloys
Ankit Roy, Prashant Singh, Ganesh Balasubramanian +1
Multi-principal element alloys (MPEAs) continue to garner interest as structural and plasma-facing materials due to their structure stability and increased resistance to radiation…
Machine-learning enabled thermodynamic model for the design of new rare-earth compounds
Prashant Singh, Tyler Del Rose, Guillermo Vazquez +2
We employ a descriptor based machine-learning approach to assess the effect of chemical alloying on formation-enthalpy of rare-earth intermetallics. Application of machine-learning…
Effect of substitutional doping and disorder on the phase stability, magnetism, and half-metallicity of Heusler alloys
Nikolai A Zarkevich, Prashant Singh, A. V. Smirnov +1
Spintronics is the fast growing field that will play a key role in optimizing power consumption, memory, and processing capabilities of nanoelectronic devices. Heusler alloys are p…
Towards Stacking Fault Energy Engineering in FCC High Entropy Alloys
Tasneem Khan, Tanner Kirk, Guillermo Vazquez +5
Stacking Fault Energy (SFE) is an intrinsic alloy property that governs much of the plastic deformation mechanisms observed in fcc alloys. While SFE has been recognized for many ye…
Pseudoelastic deformation in Mo-based refractory multi-principal element alloys
Aayush Sharma, Prashant Singh, Tanner Kirk +5
Phase diagrams supported by density functional theory methods can be crucial for designing high-entropy alloys that are subset of multi-principalelement alloys. We present phase…
Effect of heterostructure engineering on electronic structure and transport properties of two-dimensional halide perovskites
Rahul Singh, Prashant Singh, Ganesh Balasubramania
Organic-inorganic halide perovskite solar cells have attracted much attention due to their low-cost fabrication, flexibility, and high-power conversion efficiency. More recent effo…
Designing order-disorder transformation in high-entropy ferritic steels
Singh, Prashant, Johnson +1
Order-disorder transformations hold an essential place in chemically complex high-entropy ferritic-steels (HEFSs) due to their critical technological application. The chemical inho…
On the martensitic transformation in FeMnCoCr high-entropy alloy
Prashant Singh, Sezer Picak, Aayush Sharma +4
High-entropy alloys (HEAs), and even medium-entropy alloys (MEAs), are an intriguing class of materials in that structure and property relations can be controlled via alloying and…
Neural-networks model for force prediction in multi-principal-element alloys
Rahul Singh, Prashant Singh, Aayush Sharma +6
Atomistic simulations can provide useful insights into the physical properties of multi-principal-element alloys. However, classical potentials mostly fail to capture key quantum (…
Reinvestigation of the intrinsic magnetic properties of (FeCo)B alloys and crystallization behavior of ribbons
Tej Nath Lamichhane, Olena Palasyuk, Vladimir P. Antropov +10
New determination of the magnetic anisotropy from single crystals of (FeCo)B alloys are presented. The anomalous temperature dependence of the anisotropy constant i…
Electron correlation effects on exchange interactions and spin excitations in 2D van der Waals materials
Liqin Ke, Mikhail I. Katsnelson
Despite serious effort, the nature of the magnetic interactions and the role of electron-correlation effects in magnetic two-dimensional (2D) van der Waals materials remain elusive…
First-order ferromagnetic transitions of lanthanide local moments in divalent compounds: An itinerant electron positive feedback mechanism and Fermi surface topological change
Eduardo Mendive-Tapia, Durga Paudyal, Leon Petit +1
Around discontinuous (first-order) magnetic phase transitions the strong caloric response of materials to the application of small fields is widely studied for the development of s…
Half-metallic compositional ranges for selected Heusler alloys
Nikolai A. Zarkevich, Prashant Singh, A. V. Smirnov +1
For a material that is a half-metal, there should exist a range of compositions for half-metallicity. This compositional range can be expressed in terms of electron count and compu…
Expansive Open Fermi Arcs and Connectivity Changes Induced by Infrared Phonons in ZrTe5
Lin-Lin Wang
Expansive open Fermi arcs covering most of the surface Brillouin zone (SBZ) are desirable for detection and control of many topological phenomena, but so far has been only reported…
Pressure tuning of structural and magnetic transitions in EuAgAs
Sergey L. Bud'ko, Li Xiang, Chaowei Hu +3
We report temperature dependent measurements of ambient pressure specific heat, magnetic susceptibility, anisotropic resistivity and thermal expansion as well as in-plane resistivi…
Parameterization of the Stoner-Wohlfarth model of magnetic hysteresis
Nikolai A. Zarkevich, Cajetan Ikenna Nlebedim, R. William McCallum
The Stoner-Wohlfarth is the most used model of magnetic hysteresis, but its computation is time-consuming. We use machine learning to approximate piecewise this model by easy-to-co…