KC
Kamal Choudhary
cond-mat.mtrl-scics.LGphysics.comp-phcond-mat.supr-condensity functional theorycond-mat.str-elphysics.chem-phhigh-throughputmaterials discoveryphysics.app-ph
On Valency
published · living versionsW_b37rygbz·v1 · currentpublished
Quantum 3xplorer: AI-Native Engine for Next-Generation Quantum Materials Modeling
with Vsevolod Biryukov, Sergey V. Barabash, Pranab Kumar Das, Jack Deslippe +10
1 version
W_gdbs8br9·v1published
Preprints & journals
100 papers in the corpus · 2014–2026Strain-Induced Interfacial Bond Evolution and Facet-dependent Strain Response of Electronic Properties in Oxidized Silicon Nanowires2610.28967v1 · Yasir Mahmood, Daniel Wines, Viviana Dovale-Farelo et al.2026 · 0 citationsarXivon Valency
pymatgen: 15 years of community growth, new functionality, and future prospects2610.23538v1 · Janine George, Matthew K. Horton, Aaron D. Kaplan et al.2026 · 0 citationsarXiv
ALIGNN 2.0: A Unified Line-Graph Neural Network Framework for Materials Screening, Force Fields, Inverse Design, Spectroscopy, and Microscopy2609.19487v1 · Jaehyung Lee, Charles Rhys Campbell, Akshaya Ajith et al.2026 · 0 citationsarXiv
AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org.42301888 · Lee, Jaehyung, Ely, Justin, Zhang, Kent et al.2026 · 3 citationsThe journal of physical chemistry letters. 2026;17(26):7221-7231
Mesh Graph Neural Network Framework for Accelerating Finite Element Simulation for Arbitrary Geometries2606.08287v1 · Josiah D. Kunz, Kamal Choudhary2026 · 0 citationsarXiv
RamanGPT: Bidirectional Mapping Between Crystal Structures and Raman Spectra with Graph Neural Networks and Generative Transformers2606.03764v1 · Frank M. Abel, Jaehyung Lee, Charles R. Campbell et al.2026 · 0 citationsarXiv
Lessons Learned from the 2025 Agentic AI for Science Hackathon10.26434/chemrxiv.15001345/v1 · Jaehyung Lee, Harichandana Neralla, Charles Rhys Campbell et al.2026 · 0 citationsChemRxiv
M-CODE: Materials Categorization via Ontology, Dimensionality and Evolution2602.14384v1 · Vsevolod Biryukov, Kamal Choudhary, Timur Bazhirov2026 · 0 citations10.1016/j.commatsci.2026.114901
CHIPS-TB: Evaluating Tight-Binding Models for Metals, Semiconductors, and Insulators.41737060 · Park, In Jun, Choudhary, Kamal2026 · 0 citationsThe journal of physical chemistry. C, Nanomaterials and interfaces. 2026;130(7):2814-2824
Machine Learning for Predicting Magnetization from X-ray Diffraction of Iron Oxide Nanoparticles Using Simple Physics-Based Data Generation2512.13909v1 · Frank M. Abel, Paige Burke, Daniel Wines et al.2025 · 0 citationsarXiv
AtomBench: A Benchmarking Framework for Generative Crystal Reconstruction Models in Conventional Superconductors2510.16165v2 · Charles Rhys Campbell, Aldo H. Romero, Kamal Choudhary2025 · 0 citationsarXiv
SlaKoNet: A Unified Slater-Koster Tight-Binding Framework Using Neural Network Infrastructure for the Periodic Table.41103152 · Choudhary, Kamal2025 · 4 citationsThe journal of physical chemistry letters. 2025;16(43):11109-11119
Accelerated prediction of dielectric functions in solar cell materials with graph neural networks2510.08738v1 · Caden Ginter, Kamal Choudhary, Subhasish Mandal2025 · 1 citationarXiv
Intrinsic direct air capture.40936611 · McDannald, Austin, Siderius, Daniel W, DeCost, Brian et al.2025 · 5 citationsChemical science. 2025;16(39):18352-18363
BenchQC: A Benchmarking Toolkit for Quantum Computation.40755323 · Pollard, Nia, Choudhary, Kamal2025 · 8 citationsJournal of computational chemistry. 2025;46(21):e70202
MicroscopyGPT: Generating Atomic-Structure Captions from Microscopy Images of 2D Materials with Vision-Language Transformers.40590052 · Choudhary, Kamal2026 · 19 citationsThe journal of physical chemistry letters. 2025;16(27):7028-7035
Lean CNNs for mapping electron charge density fields to material properties2505.09826v1 · Pranoy Ray, Kamal Choudhury, Surya R. Kalidindi2025 · 7 citationsIntegrating Materials and Manufacturing Innovation, 1-13 (2025)
CHIPS-FF: Evaluating Universal Machine Learning Force Fields for Material Properties.40475806 · Wines, Daniel, Choudhary, Kamal2026 · 26 citationsACS materials letters. 2025;7(6):2105-2114
A practical guide to machine learning interatomic potentials -- Status and future2503.09814v1 · Ryan Jacobs, Dane Morgan, Siamak Attarian et al.2025 · 218 citationsCurrent Opinion in Solid State and Materials Science, 35, 101214 (2025)
Quantum Monte Carlo and Density Functional Theory Study of Strain and Magnetism in 2D 1T-VSe2 with Charge Density Wave States.40053912 · Wines, Daniel, Ibrahim, Akram, Gudibandla, Nishwanth et al.2025 · 10 citationsACS nano. 2025;19(10):9925-9935
The JARVIS Infrastructure is All You Need for Materials Design2503.04133v2 · Kamal Choudhary2025 · 12 citationsarXiv
DiffractGPT: Atomic Structure Determination from X-ray Diffraction Patterns Using a Generative Pretrained Transformer.39976483 · Choudhary, Kamal2025 · 15 citationsThe journal of physical chemistry letters. 2025;16(8):2110-2119
ParquetDB: A Lightweight Python Parquet-Based Database2502.05311v2 · Logan Lang, Eduardo Hernandez, Kamal Choudhary et al.2025 · 1 citationarXiv
DiffractGPT: Atomic Structure Determination from X-ray Diffraction Patterns using Generative Pre-trained Transformer10.26434/chemrxiv-2024-ztp85-v2 · Kamal Choudhary2024 · 0 citationsChemRxiv
Origin of unique electronic structures of single-atom alloys unraveled by interpretable deep learning.39435835 · Huang, Yang, Wang, Shih-Han, Achenie, Luke E K et al.2024 · 13 citationsThe Journal of chemical physics. 2024;161(16)
Examining Generalizability of AI Models for Catalysis10.26434/chemrxiv-2024-hj733 · Shih-Han Wang, Hongliang Xin, Luke Achenie et al.2024 · 6 citationsChemRxiv
SLMat: A Comprehensive Serverless Toolkit for Advanced Materials Design10.26434/chemrxiv-2024-fqq27 · Kamal Choudhary2024 · 2 citationsChemRxiv
AtomGPT: Atomistic Generative Pretrained Transformer for Forward and Inverse Materials Design.38935647 · Choudhary, Kamal2024 · 72 citationsThe journal of physical chemistry letters. 2024;15(27):6909-6917
Probing out-of-distribution generalization in machine learning for materials2406.06489v1 · Kangming Li, Andre Niyongabo Rubungo, Xiangyun Lei et al.2024 · 84 citationsCommun Mater 6, 9 (2025)
AtomGPT: Atomistic Generative Pre-trained Transformer for Forward and Inverse Materials Design2405.03680v2 · Kamal Choudhary2024 · 1 citationarXiv
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange.39118978 · Evans, Matthew L, Bergsma, Johan, Merkys, Andrius et al.2024 · 53 citationsDigital discovery. 2024;3(8):1509-1533
Efficient first principles based modeling via machine learning: from simple representations to high entropy materials2403.15579v1 · Kangming Li, Kamal Choudhary, Brian DeCost et al.2024 · 24 citationsJ. Mater. Chem. A, 2024,12, 12412-12422
InterMat: Accelerating Band Offset Prediction in Semiconductor Interfaces with DFT and Deep Learning2401.02021v2 · Kamal Choudhary, Kevin Garrity2024 · 26 citationsarXiv
Publisher Correction: Exploiting redundancy in large materials datasets for efficient machine learning with less data.38177139 · Li, Kangming, Persaud, Daniel, Choudhary, Kamal et al.2024 · 0 citationsNature communications. 2024;15(1):284
Data-driven Design of High Pressure Hydride Superconductors using DFT and Deep Learning.38841205 · Wines, Daniel, Choudhary, Kamal2026 · 19 citationsMaterials futures. 2024;3(2)
Exploiting redundancy in large materials datasets for efficient machine learning with less data.37949845 · Li, Kangming, Persaud, Daniel, Choudhary, Kamal et al.2024 · 122 citationsNature communications. 2023;14(1):7283
Approaches for Uncertainty Quantification of AI-predicted Material Properties: A Comparison2310.13136v1 · Francesca Tavazza, Kamal Choudhary, Brian DeCost2023 · 0 citationsarXiv
Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks2309.06423v2 · Md Habibur Rahman, Prince Gollapalli, Panayotis Manganaris et al.2023 · 39 citationsarXiv
14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon.38013906 · Jablonka, Kevin Maik, Ai, Qianxiang, Al-Feghali, Alexander et al.2026 · 221 citationsDigital discovery. 2023;2(5):1233-1250
Interpretable Ensemble Learning for Materials Property Prediction with Classical Interatomic Potentials: Carbon as an Example2308.10818v1 · Xinyu Jiang, Haofan Sun, Kamal Choudhary et al.2023 · 0 citationsarXiv
Inverse Design of Next-Generation Superconductors Using Data-Driven Deep Generative Models.37462366 · Wines, Daniel, Xie, Tian, Choudhary, Kamal2023 · 55 citationsThe journal of physical chemistry letters. 2023;14(29):6630-6638
JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods2306.11688v2 · Kamal Choudhary, Daniel Wines, Kangming Li et al.2023 · 66 citationsarXiv
Recent progress in the JARVIS infrastructure for next-generation data-driven materials design2305.11842v2 · Daniel Wines, Ramya Gurunathan, Kevin F. Garrity et al.2023 · 38 citationsAppl. Phys. Rev. 10, 041302 (2023)
Fast and accurate prediction of material properties with three-body tight-binding model for the periodic table.37274125 · Garrity, Kevin F, Choudhary, Kamal2025 · 19 citationsPhysical review materials. 2023;7(4)
MPpredictor: An Artificial Intelligence-Driven Web Tool for Composition-Based Material Property Prediction.36972592 · Gupta, Vishu, Choudhary, Kamal, Mao, Yuwei et al.2023 · 36 citationsJournal of chemical information and modeling. 2023;63(7):1865-1871
AtomVision: A Machine Vision Library for Atomistic Images.36857727 · Choudhary, Kamal, Gurunathan, Ramya, DeCost, Brian et al.2023 · 14 citationsJournal of chemical information and modeling. 2023;63(6):1708-1722
High-Throughput DFT-Based Discovery of Next Generation Two-Dimensional (2D) Superconductors.36715314 · Wines, Daniel, Choudhary, Kamal, Biacchi, Adam J et al.2023 · 63 citationsNano letters. 2023;23(3):969-978
Systematic DFT+U and Quantum Monte Carlo Benchmark of Magnetic Two-Dimensional (2D) CrX3 (X = I, Br, Cl, F).36727030 · Wines, Daniel, Choudhary, Kamal, Tavazza, Francesca2026 · 34 citationsThe journal of physical chemistry. C, Nanomaterials and interfaces. 2023;127(2)
A critical examination of robustness and generalizability of machine learning prediction of materials properties2210.13597v1 · Kangming Li, Brian DeCost, Kamal Choudhary et al.2022 · 148 citationsnpj Comput Mater 9, 55 (2023)
ChemNLP: A Natural Language Processing based Library for Materials Chemistry Text Data2209.08203v3 · Kamal Choudhary, Mathew L. Kelley2022 · 47 citationsarXiv
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