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- National Institute of Standards and TechnologyUS47 papers
- Material Measurement LaboratoryUS19 papers
- University of Maryland, College ParkUS14 papers
- Physical Measurement LaboratoryUS9 papers
- University of Massachusetts DartmouthUS8 papers
- University of Colorado BoulderUS6 papers
- Centre National de la Recherche ScientifiqueFR5 papers
- George Mason UniversityUS5 papers
- University of California, Los AngelesUS4 papers
- Alabama Agricultural and Mechanical UniversityUS3 papers
- Columbia UniversityUS3 papers
- Georgetown UniversityUS3 papers
6 papers · 2 filters
Graph Neural Network Predictions of Metal Organic Framework CO2 Adsorption Properties
Kamal Choudhary, Taner Yildirim, Daniel Siderius +3
The increasing CO2 level is a critical concern and suitable materials are needed to capture such gases from the environment. While experimental and conventional computational metho…
Recent Advances and Applications of Deep Learning Methods in Materials Science
Kamal Choudhary, Brian DeCost, Chi Chen +10
Deep learning (DL) is one of the fastest growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data mo…
Atomistic Line Graph Neural Network for Improved Materials Property Predictions
Kamal Choudhary, Brian DeCost
Graph neural networks (GNN) have been shown to provide substantial performance improvements for atomistic material representation and modeling compared with descriptor-based machin…
Distinguishing two-component anomalous Hall effect from topological Hall effect
Lixuan Tai, Bingqian Dai, Jie Li +14
In transport, the topological Hall effect (THE) presents itself as non-monotonic features (or humps and dips) in the Hall signal and is widely interpreted as a sign of chiral spin…
High-throughput search for magnetic topological materials using spin-orbit spillage, machine-learning and experiments
Kamal Choudhary, Kevin F. Garrity, Nirmal J. Ghimire +2
Magnetic topological insulators and semi-metals have a variety of properties that make them attractive for applications including spintronics and quantum computation, but very few…
Quantum Computation for Predicting Electron and Phonon Properties of Solids
Kamal Choudhary
Quantum chemistry is one of the most promising near-term applications of quantum computers. Quantum algorithms such as variational quantum eigen solver (VQE) and variational quantu…