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Adam M. Krajewski
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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
402021
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
392022
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
312021
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
28*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
242021
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
112023
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
ML Evans, J Bergsma, A Merkys, CW Andersen, OB Andersson, D Beltrán, ...
Digital Discovery 3 (8), 1509-1533, 2024
92024
Efficient generation of grids and traversal graphs in compositional spaces towards exploration and path planning
AM Krajewski, AM Beese, WF Reinhart, ZK Liu
npj Unconventional Computing 1 (1), 12, 2024
3*2024
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
32024
Efficient structure-informed featurization and property prediction of ordered, dilute, and random atomic structures
AM Krajewski, JW Siegel, ZK Liu
Computational Materials Science 247, 113495, 2024
22024
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
12024
Data-driven inverse design of MoNbTiVWZr refractory multicomponent alloys: Microstructure and mechanical properties
L Raman, A Debnath, E Furton, S Lin, A Krajewski, S Ghosh, N Liu, M Ahn, ...
Materials Science and Engineering: A 918, 147475, 2024
2024
nimCSO: A Nim package for Compositional Space Optimization
K Adam M., A Debnath, WF Reinhart, AM Beese, ZK Liu
Journal of Open Source Software 9 (103), 6731, 2024
2024
Efficient Materials Informatics between Rockets and Electrons
AM Krajewski
The Pennsylvania State University, 2024
2024
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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