Extensible structure-informed prediction of formation energy with improved accuracy and usability employing neural networks AM Krajewski, JW Siegel, J Xu, ZK Liu Computational Materials Science 208, 111254, 2022 | 30 | 2022 |
Generative deep learning as a tool for inverse design of high-entropy refractory alloys A Debnath, AM Krajewski, H Sun, S Lin, M Ahn, W Li, S Priya, J Singh, ... Journal of Materials Informatics 1 (3), 2021 | 28 | 2021 |
Correlation analysis of materials properties by machine learning: Illustrated with stacking fault energy from first-principles calculations in dilute fcc-based alloys X Chong, SL Shang, AM Krajewski, JD Shimanek, W Du, Y Wang, J Feng, ... Journal of Physics: Condensed Matter 33 (29), 295702, 2021 | 22 | 2021 |
Thermodynamic properties of the Nd-Bi system via emf measurements, DFT calculations, machine learning, and CALPHAD modeling S Im, SL Shang, ND Smith, AM Krajewski, T Lichtenstein, H Sun, ... Acta Materialia 223, 117448, 2022 | 20* | 2022 |
Forming mechanism of equilibrium and non-equilibrium metallurgical phases in dissimilar aluminum/steel (Al–Fe) joints SL Shang, H Sun, B Pan, Y Wang, AM Krajewski, M Banu, J Li, ZK Liu Scientific reports 11 (1), 24251, 2021 | 19 | 2021 |
Efficient Generation of Grids and Traversal Graphs in Compositional Spaces towards Exploration and Path Planning Exemplified in Materials AM Krajewski, AM Beese, WF Reinhart, ZK Liu arXiv preprint arXiv:2402.03528, 2024 | 2 | 2024 |
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange M Evans, J Bergsma, A Merkys, C Andersen, OB Andersson, D Beltrán, ... Digital Discovery, 2024 | 2 | 2024 |
Comparing forward and inverse design paradigms: A case study on refractory high-entropy alloys A Debnath, L Raman, W Li, AM Krajewski, M Ahn, S Lin, S Shang, ... Journal of Materials Research 38 (17), 4107-4117, 2023 | 2 | 2023 |
Design and validation of refractory alloys using machine learning, CALPHAD, and experiments W Li, L Raman, A Debnath, M Ahn, S Lin, AM Krajewski, S Shang, S Priya, ... International Journal of Refractory Metals and Hard Materials 121, 106673, 2024 | 1 | 2024 |
MaterialsMap: A CALPHAD-Based Tool to Design Composition Pathways through feasibility map for Desired Dissimilar Materials, demonstrated with resistance spot welding Joining of … H Sun, B Pan, Z Yang, AM Krajewski, B Bocklund, SL Shang, J Li, ... Materialia, 102153, 2024 | | 2024 |
Efficient Structure-Informed Featurization and Property Prediction of Ordered, Dilute, and Random Atomic Structures AM Krajewski, JW Siegel, ZK Liu arXiv preprint arXiv:2404.02849, 2024 | | 2024 |
nimCSO: A Nim package for Compositional Space Optimization AM Krajewski, A Debnath, WF Reinhart, AM Beese, ZK Liu arXiv preprint arXiv:2403.02340, 2024 | | 2024 |