1.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National Institute of Standards and TechnologyUS134 papers
- University of Maryland, College ParkUS31 papers
- Physical Measurement LaboratoryUS30 papers
- Theiss ResearchUS19 papers
- Joint Quantum InstituteUS12 papers
- Northwestern UniversityUS12 papers
- Argonne National LaboratoryUS11 papers
- NIST Center for Neutron ResearchUS11 papers
- Lawrence Berkeley National LaboratoryUS9 papers
- SLAC National Accelerator LaboratoryUS9 papers
- Princeton UniversityUS8 papers
- University of TorontoCA8 papers
87 papers · 1 filter
DiffractGPT: Atomic Structure Determination from X-ray Diffraction Patterns using Generative Pre-trained Transformer
Kamal Choudhary
Crystal structure determination from powder diffraction patterns is a complex challenge in materials science, often requiring extensive expertise and computational resources. This…
Assembly of High-Performance van der Waals Devices Using Commercial Polyvinyl Chloride Films
Son T. Le, Jeffrey J. Schwartz, Tsegereda K. Esatu +5
Control over the position, orientation, and stacking order of two-dimensional (2D) materials within van der Waals heterostructures is crucial for applications in electronics, spint…
A practical guide to machine learning interatomic potentials -- Status and future
Ryan Jacobs, Dane Morgan, Siamak Attarian +27
The rapid development and large body of literature on machine learning interatomic potentials (MLIPs) can make it difficult to know how to proceed for researchers who are not exper…
The JARVIS Infrastructure is All You Need for Materials Design
Kamal Choudhary
The Joint Automated Repository for Various Integrated Simulations (JARVIS) is a unified platform for multiscale, multimodal, forward, and inverse materials design. It integrates di…
Intrinsic Direct Air Capture
Austin McDannald, Daniel W. Siderius, Brian DeCost +2
We present new metrics to evaluate solid sorbent materials for Direct Air Capture (DAC). These new metrics provide a theoretical upper bound on CO2 captured per energy as well as a…
Revealing the Origin and Nature of the Buried Metal-Substrate Interface Layer in Ta/Sapphire Superconducting Films
Aswin kumar Anbalagan, Rebecca Cummings, Chenyu Zhou +14
Despite constituting a smaller fraction of the qubits electromagnetic mode, surfaces and interfaces can exert significant influence as sources of high-loss tangents, which brings f…
Quantum Monte Carlo and density functional theory study of strain and magnetism in 2D 1T-VSe with charge density wave states
Daniel Wines, Akram Ibrahim, Nishwanth Gudibandla +18
Two-dimensional (2D) 1T-VSe has prompted significant interest due to the discrepancies regarding alleged ferromagnetism (FM) at room temperature, charge density wave (CDW) stat…
Probing out-of-distribution generalization in machine learning for materials
Kangming Li, Andre Niyongabo Rubungo, Xiangyun Lei +5
Scientific machine learning (ML) endeavors to develop generalizable models with broad applicability. However, the assessment of generalizability is often based on heuristics. Here,…
Efficient first principles based modeling via machine learning: from simple representations to high entropy materials
Kangming Li, Kamal Choudhary, Brian DeCost +2
High-entropy materials (HEMs) have recently emerged as a significant category of materials, offering highly tunable properties. However, the scarcity of HEM data in existing densit…
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
Matthew L. Evans, Johan Bergsma, Andrius Merkys +56
The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enh…
InterMat: Accelerating Band Offset Prediction in Semiconductor Interfaces with DFT and Deep Learning
Kamal Choudhary, Kevin Garrity
We introduce a computational framework (InterMat) to predict band offsets of semiconductor interfaces using density functional theory (DFT) and graph neural networks (GNN). As a fi…
Data-driven Design of High Pressure Hydride Superconductors using DFT and Deep Learning
Daniel Wines, Kamal Choudhary
The observation of superconductivity in hydride-based materials under ultrahigh pressures (for example, HS and LaH) has fueled the interest in a more data-driven approac…
Post deposition interfacial Néel temperature tuning in magnetoelectric B:Cr2O3
Ather Mahmood, Jamie Weaver, Syed Qamar Abbas Shah +4
Boron (B) alloying transforms the magnetoelectric antiferromagnet Cr2O3 into a multifunctional single-phase material which enables electric field driven π/2 rotation of the Néel ve…
Diamond Surface Functionalization via Visible Light-Driven C-H Activation for Nanoscale Quantum Sensing
Lila V. H. Rodgers, Suong T. Nguyen, James H. Cox +16
Nitrogen-vacancy centers in diamond are a promising platform for nanoscale nuclear magnetic resonance sensing. Despite significant progress towards using NV centers to detect and l…
Modeling Chemical Exfoliation of Non-van der Waals Chromium Sulfides by Machine Learning Interatomic Potentials and Monte Carlo Simulations
Akram Ibrahim, Daniel Wines, Can Ataca
The chemical exfoliation of non-van der Waals (vdW) materials to ultrathin nanosheets remains a formidable challenge. This difficulty arises from the strong preference of these mat…
Titanium and titanium oxides at the K- and L-edges: validating theoretical calculations of X-ray absorption and X-ray emission spectra with measurements
Karina Bzheumikhova, John Vinson, Rainer Unterumsberger +5
Using well-calibrated experimental data we validate theoretical X-ray absorption spectroscopy (XAS) as well as X-ray emission spectroscopy (XES) calculations for titanium (Ti), tit…
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Kevin Maik Jablonka, Qianxiang Ai, Alexander Al-Feghali +50
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To…
JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods
Kamal Choudhary, Daniel Wines, Kangming Li +35
Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experiment…
Recent progress in the JARVIS infrastructure for next-generation data-driven materials design
Daniel Wines, Ramya Gurunathan, Kevin F. Garrity +4
The Joint Automated Repository for Various Integrated Simulations (JARVIS) infrastructure at the National Institute of Standards and Technology (NIST) is a large-scale collection o…
On the redundancy in large material datasets: efficient and robust learning with less data
Kangming Li, Daniel Persaud, Kamal Choudhary +3
Extensive efforts to gather materials data have largely overlooked potential data redundancy. In this study, we present evidence of a significant degree of redundancy across multip…
Why is EXAFS analysis for multicomponent metals so hard? Challenges and opportunities for measuring ordering in complex concentrated alloys using x-ray absorption spectroscopy
Howie Joress, Bruce Ravel, Elaf Anber +5
Short range order is a critical driver of properties (e.g. corrosion resistance and tensile strength) in multicomponent alloys such as complex concentrated alloys (CCAs). Extended…
Correlating Chemical Reaction and Mass Transport in Hydrogen-based Direct Reduction of Iron Oxide
Xueli Zheng, Subhechchha Paul, Lauren Moghimi +16
Steelmaking contributes 8% to the total CO2 emissions globally, primarily due to coal-based iron ore reduction. Clean hydrogen-based ironmaking has variable performance because the…
Multi-code Benchmark on Simulated Ti K-edge X-ray Absorption Spectra of Ti-O Compounds
Fanchen Meng, Benedikt Maurer, Fabian Peschel +7
X-ray absorption spectroscopy (XAS) is an element-specific materials characterization technique that is sensitive to structural and electronic properties. First-principles simulate…
A High Throughput Aqueous Passivation Testing Methodology for Compositionally Complex Alloys using Scanning Droplet Cell
Debashish Sur, Howie Joress, Jason Hattrick-Simpers +1
Compositionally complex alloy systems containing more than five principal elements allow exploring a wide range of compositions, processing, and structural variables with the hope…