| 1. Microstructure Characterization and Reconstruction in Python: MCRpy | Paul Seibert et al. |
| 2. CrabNet for Explainable Deep Learning in Materials Science: Bridging the Gap Between Academia and Industry | Anthony Yu-Tung Wang et al. |
| 3. A Comparison of Statistically Equivalent and Realistic Microstructural Representative Volume Elements for Crystal Plasticity Models | Fatemeh Azhari et al. |
| 4. Random Generation of Lattice Structures with Short-Range Order | Lauren T. W. Fey, Irene J. Beyerlein |
| 5. A Machine Learning Strategy for Race-Tracking Detection During Manufacturing of Composites by Liquid Moulding | Joaquín Fernández-León et al. |
| 6. 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 |
| 7. Ontopanel: A Tool for Domain Experts Facilitating Visual Ontology Development and Mapping for FAIR Data Sharing in Materials Testing | Yue Chen et al. |
| 8. Compound Knowledge Graph-Enabled AI Assistant for Accelerated Materials Discovery | Kareem S. Aggour et al. |
| 9. Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design | Yuwei Mao et al. |
| 10. 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. |
| 11. PRISMS-Plasticity TM: An Open-Source Rapid Texture Evolution Analysis Pipeline | Mohammadreza Yaghoobi, John E. Allison, Veera Sundararaghavan |
| 12. Consistent Quantification of Precipitate Shapes and Sizes in Two and Three Dimensions Using Central Moments | Felix Schleifer et al. |
| 13. Quantitative Benchmarking of Acoustic Emission Machine Learning Frameworks for Damage Mechanism Identification | C. Muir et al. |
| 14. Computational Alloy Design for Process-Related Uncertainties in Powder Metallurgy | T. T. Molla, A. Atthapreyangkul, G. B. Schaffer |
| 15. Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Toward ML-Assisted Advanced Manufacturing | Scott Howland et al. |
| 16. 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 |
| 17. A Novel Methodology for the Thermographic Cooling Rate Measurement during Powder Bed Fusion of Metals Using a Laser Beam | David L. Wenzler et al. |
| 18. A Framework for the Optimal Selection of High-Throughput Data Collection Workflows by Autonomous Experimentation Systems | Rohan Casukhela, Sriram Vijayan, Joerg R. Jinschek, Stephen R. Niezgoda |
| 19. Quantifying Dynamic Signal Spread in Real-Time High-Energy X-ray Diffraction | Daniel P. Banco et al. |
| 20. Temperature-Dependent Material Property Databases for Marine Steels—Part 3: HSLA-80 | Jennifer K. Semple, Daniel H. Bechetti, Wei Zhang, Charles R. Fisher |
| 21. 3D Minimum Channel Width Distribution in a Ni-Base Superalloy | Moritz Müller, Bernd Böttger, Felix Schleifer, Michael Fleck, Uwe Glatzel |
| 22. Feature Engineering for Microstructure–Property Mapping in Organic Photovoltaics | Sepideh Hashemi et al. |
| 23. Calcium-Treated Steel Cleanliness Prediction Using High-Dimensional Steelmaking Process Data | Stephano Piva et al. |
| 24. Physics-Informed Machine Learning and Uncertainty Quantification for Mechanics of Heterogeneous Materials | B. V. S. S. Bharadwaja et al. |
| 25. Computational Efficient Modeling of Supersolidus Liquid Phase Sintering in Multi-component Alloys for ICME Applications | Tesfaye T. Molla |
