1. Perspectives on the Impact of Machine Learning, Deep Learning, and Artificial Intelligence on Materials, Processes, and Structures Engineering | Dennis M. Dimiduk, Elizabeth A. Holm, Stephen R. Niezgoda |
2. In-process sensing in selective laser melting (SLM) additive manufacturing | Thomas G. Spears, Scott A. Gold |
3. DREAM.3D: A Digital Representation Environment for the Analysis of Microstructure in 3D | Michael A Groeber, Michael A Jackson |
4. Microstructure Characterization and Reconstruction in Python: MCRpy | Paul Seibert et al. |
5. Metal additive-manufacturing process and residual stress modeling | Mustafa Megahed et al. |
6. OpenCalphad - a free thermodynamic software | Bo Sundman, Ursula R Kattner, Mauro Palumbo, Suzana G Fries |
7. ITKMontage: A Software Module for Image Stitching | Dženan Zukić et al. |
8. Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters | Ankit Agrawal et al. |
9. Bi-directional Scan Pattern Effects on Residual Stresses and Distortion in As-built Nitinol Parts: A Trend Analysis Simulation Study | Medad C. C. Monu et al. |
10. Symmetric and asymmetric tilt grain boundary structure and energy in Cu and Al (and transferability to other fcc metals) | Mark A. Tschopp, Shawn P. Coleman, David L. McDowell |
11. Machine Learning Prediction of Heat Capacity for Solid Inorganics | Steven K. Kauwe, Jake Graser, Antonio Vazquez, Taylor D. Sparks |
12. Random Generation of Lattice Structures with Short-Range Order | Lauren T. W. Fey, Irene J. Beyerlein |
13. Quantitative Benchmarking of Acoustic Emission Machine Learning Frameworks for Damage Mechanism Identification | C. Muir et al. |
14. Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Toward ML-Assisted Advanced Manufacturing | Scott Howland et al. |
15. On the Fidelity of the Scaling Laws for Melt Pool Depth Analysis During Laser Powder Bed Fusion | M. Naderi, J. Weaver, D. Deisenroth, N. Iyyer, R. McCauley |
16. Compound Knowledge Graph-Enabled AI Assistant for Accelerated Materials Discovery | Kareem S. Aggour et al. |
17. CrabNet for Explainable Deep Learning in Materials Science: Bridging the Gap Between Academia and Industry | Anthony Yu-Tung Wang et al. |
18. A Novel Methodology for the Thermographic Cooling Rate Measurement during Powder Bed Fusion of Metals Using a Laser Beam | David L. Wenzler et al. |
19. Residual Strain Predictions for a Powder Bed Fusion Inconel 625 Single Cantilever Part | Yangzhan Yang, Madie Allen, Tyler London, Victor Oancea |
20. A Comparison of Statistically Equivalent and Realistic Microstructural Representative Volume Elements for Crystal Plasticity Models | Fatemeh Azhari et al. |
21. PRISMS-Plasticity TM: An Open-Source Rapid Texture Evolution Analysis Pipeline | Mohammadreza Yaghoobi, John E. Allison, Veera Sundararaghavan |
22. Overview of Additive Manufacturing Informatics: “A Digital Thread” | Deborah Mies, Will Marsden, Stephen Warde |
23. On the Prediction of Uniaxial Tensile Behavior Beyond the Yield Point of Wrought and Additively Manufactured Ti-6Al-4V | Maria J. Quintana, Andrew J. Temple, D. Gary Harlow, Peter C. Collins |
24. Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design | Yuwei Mao et al. |
25. Ontopanel: A Tool for Domain Experts Facilitating Visual Ontology Development and Mapping for FAIR Data Sharing in Materials Testing | Yue Chen et al. |