Author

Nathan Linton

Institutions: Savannah River National Laboratory, Clemson University

Observed institutions: University of Wyoming, Savannah River National Laboratory, Idaho National Laboratory, Clemson University

ORCID: 0000-0003-1548-5613

Observed ORCID: 0000-0003-1548-5613

OpenAlex ID: A5012603904

Machine Learning Based Methodology to Predict Point Defect Energies in Multi-Principal Element Alloys

2021 · Anus Manzoor, Gaurav Arora, et al. · Frontiers in Materials · 40

A machine learning framework for elastic constants predictions in multi-principal element alloys

2023 · Nathan Linton, Dilpuneet S. Aidhy · APL Machine Learning · 29

Mechanistic understanding of vacancy formation energies in FCC concentrated alloys from DFT calculations

2025 · Nathan Linton, Dilpuneet S. Aidhy · Acta Materialia · 17

Elastic constants from charge density distribution in FCC high-entropy alloys using CNN and DFT

2024 · Hossein Mirzaee, Ramin Soltanmohammadi, et al. · APL Machine Learning · 11

Evaluation of adsorption and mechanical strength of 13X zeolite mixtures with phyllosilicate binders using molecular dynamics simulation and positron annihilation spectroscopy

2023 · Miu Lun Lau, Nathan Linton, et al. · Chemical Engineering Science · 6

Framework to completely bypass expensive DFT calculations via graph neural networks for vacancy formation energy predictions in FCC high entropy alloys

2026 · Nathan Linton, Parampreet Singh, et al. · npj Computational Materials · 4

Deep learning on DFT-derived charge densities for stacking fault energy predictions in high entropy alloys

2026 · Pouya Abasmirzaie, Ali Azarmi, et al. · Materials Characterization

AI/ML cross-machine transfer learning in laser-based powder bed fusion of polymers (PBF-LB/P) additive manufacturing [POSTER]

2026 · Nathan Linton, Camden Chatham, et al. · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)

Works count: 8

Citation count: 107

H-index: 5

I10-index: 4