Sim2Ls: FAIR simulation workflows and data.
- Published in:
- PLoS ONE, 2022, v. 17, n. 3, p. 1, doi. 10.1371/journal.pone.0264492
- By:
- Publication type:
- Article
Works by Strachan, Alejandro
Results: 21
1
2
Hypersonic Jets of Detonation Products in the Hydrodynamic Collapse of Macroscopic Voids.
- Published in:
- Propellants, Explosives, Pyrotechnics, 2025, v. 50, n. 6, p. 1, doi. 10.1002/prep.12055
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- Publication type:
- Article
3
Multi‐Task Multi‐Fidelity Learning of Properties for Energetic Materials.
- Published in:
- Propellants, Explosives, Pyrotechnics, 2025, v. 50, n. 1, p. 1, doi. 10.1002/prep.202400248
- By:
- Publication type:
- Article
4
Prediction of Solid Propellant Burning Rate Characteristics Using Machine Learning Techniques.
- Published in:
- Propellants, Explosives, Pyrotechnics, 2023, v. 48, n. 4, p. 1, doi. 10.1002/prep.202200267
- By:
- Publication type:
- Article
5
Prediction of Solid Propellant Burning Rate Characteristics Using Machine Learning Techniques.
- Published in:
- Propellants, Explosives, Pyrotechnics, 2023, v. 48, n. 4, p. 1, doi. 10.1002/prep.202200267
- By:
- Publication type:
- Article
6
Systematic Builder for All‐Atom Simulations of Plastically Bonded Explosives.
- Published in:
- Propellants, Explosives, Pyrotechnics, 2022, v. 47, n. 8, p. 1, doi. 10.1002/prep.202200003
- By:
- Publication type:
- Article
7
Discovery of new high-pressure phases – integrating high-throughput DFT simulations, graph neural networks, and active learning.
- Published in:
- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01682-7
- By:
- Publication type:
- Article
8
Thermodynamic Properties of Asphaltenes Through Computer Assisted Structure Elucidation and Atomistic Simulations. 1. Bulk Arabian Light Asphaltenes.
- Published in:
- Petroleum Science & Technology, 2004, v. 22, n. 7/8, p. 877, doi. 10.1081/LFT-120040254
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- Publication type:
- Article
9
Material property prediction of thermoset polymers by molecular dynamics simulations.
- Published in:
- Acta Mechanica, 2014, v. 225, n. 4-5, p. 1187, doi. 10.1007/s00707-013-1064-2
- By:
- Publication type:
- Article
10
Atomic origin of ultrafast resistance switching in nanoscale electrometallization cells.
- Published in:
- Nature Materials, 2015, v. 14, n. 4, p. 440, doi. 10.1038/nmat4221
- By:
- Publication type:
- Article
11
Harnessing mechanical instabilities at the nanoscale to achieve ultra-low stiffness metals.
- Published in:
- Nature Communications, 2017, v. 8, n. 1, p. 1, doi. 10.1038/s41467-017-01260-6
- By:
- Publication type:
- Article
12
Expanding Materials Selection Via Transfer Learning for High-Temperature Oxide Selection.
- Published in:
- JOM: The Journal of The Minerals, Metals & Materials Society (TMS), 2021, v. 73, n. 1, p. 103, doi. 10.1007/s11837-020-04411-1
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- Publication type:
- Article
13
Online Tools for Uncertainty Quantification in nanoHUB.
- Published in:
- JOM: The Journal of The Minerals, Metals & Materials Society (TMS), 2019, v. 71, n. 8, p. 2635, doi. 10.1007/s11837-019-03534-4
- By:
- Publication type:
- Article
14
Uncertainty Quantification in Materials Modeling.
- Published in:
- JOM: The Journal of The Minerals, Metals & Materials Society (TMS), 2014, v. 66, n. 7, p. 1342, doi. 10.1007/s11837-014-1049-1
- By:
- Publication type:
- Article
15
Graph neural network coarse-grain force field for the molecular crystal RDX.
- Published in:
- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01407-2
- By:
- Publication type:
- Article
16
Mapping microstructure to shock-induced temperature fields using deep learning.
- Published in:
- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01134-0
- By:
- Publication type:
- Article
17
Parsimonious neural networks learn interpretable physical laws.
- Published in:
- Scientific Reports, 2021, v. 11, n. 1, p. 1, doi. 10.1038/s41598-021-92278-w
- By:
- Publication type:
- Article
18
Neural network reactive force field for C, H, N, and O systems.
- Published in:
- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-020-00484-3
- By:
- Publication type:
- Article
19
High-throughput density functional theory screening of double transition metal MXene precursors.
- Published in:
- Scientific Data, 2023, v. 10, n. 1, p. 1, doi. 10.1038/s41597-023-02755-2
- By:
- Publication type:
- Article
20
An Active Learning Approach for the Design of Doped LLZO Ceramic Garnets for Battery Applications.
- Published in:
- Integrating Materials & Manufacturing Innovation, 2021, v. 10, n. 2, p. 299, doi. 10.1007/s40192-021-00214-7
- By:
- Publication type:
- Article
21
Lectures and Simulation Laboratories to Improve Learners' Conceptual Understanding.
- Published in:
- Advances in Engineering Education, 2013, v. 3, n. 3, p. 1
- By:
- Publication type:
- Article