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Integrating Materials and Manufacturing Innovation - Most Cited Articles of 2023

1. Perspectives on the Impact of Machine Learning, Deep Learning, and Artificial Intelligence on Materials, Processes, and Structures Engineering (this opens in a new tab)

Dimiduk, Dennis M.; Holm, Elizabeth A.; Niezgoda, Stephen R.

2. Benchmark Study of Thermal Behavior, Surface Topography, and Dendritic Microstructure in Selective Laser Melting of Inconel 625 (this opens in a new tab)

Gan, Zhengtao; Lian, Yanping; Lin, Stephen E.; Jones, Kevontrez K.; Liu, Wing Kam; Wagner, Gregory J.

3. High-Dimensional Materials and Process Optimization Using Data-Driven Experimental Design with Well-Calibrated Uncertainty Estimates (this opens in a new tab)

Ling, Julia; Hutchinson, Maxwell; Antono, Erin; Paradiso, Sean; Meredig, Bryce

4. Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data (this opens in a new tab)

Popova, Evdokia; Rodgers, Theron M.; Gong, Xinyi; Cecen, Ahmet; Madison, Jonathan D.; Kalidindi, Surya R.

5. Machine Learning Prediction of Heat Capacity for Solid Inorganics (this opens in a new tab)

Kauwe, Steven K.; Graser, Jake; Vazquez, Antonio; Sparks, Taylor D.

6. UHCSDB: UltraHigh Carbon Steel Micrograph DataBase Tools for Exploring Large Heterogeneous Microstructure Datasets (this opens in a new tab)

DeCost, Brian L.; Hecht, Matthew D.; Francis, Toby; Webler, Bryan A.; Picard, Yoosuf N.; Holm, Elizabeth A.

7. Is Domain Knowledge Necessary for Machine Learning Materials Properties? (this opens in a new tab)

Murdock, Ryan J.; Kauwe, Steven K.; Wang, Anthony Yu-Tung; Sparks, Taylor D.

8. Measurements of Melt Pool Geometry and Cooling Rates of Individual Laser Traces on IN625 Bare Plates (this opens in a new tab)

Lane, Brandon; Heigel, Jarred; Ricker, Richard; Zhirnov, Ivan; Khromschenko, Vladimir; Weaver, Jordan; Phan, Thien; Stoudt, Mark; Mekhontsev, Sergey; Levine, Lyle

9. A Comparative Study of Feature Selection Methods for Stress Hotspot Classification in Materials (this opens in a new tab)

Mangal, Ankita; Holm, Elizabeth A.

10. Residual Strain Predictions for a Powder Bed Fusion Inconel 625 Single Cantilever Part (this opens in a new tab)

Yang, Yangzhan; Allen, Madie; London, Tyler; Oancea, Victor

11. Machine Learning-Based Reduce Order Crystal Plasticity Modeling for ICME Applications (this opens in a new tab) Yuan, Mengfei; Paradiso, Sean; Meredig, Bryce; Niezgoda, Stephen R.
12. MAUD Rietveld Refinement Software for Neutron Diffraction Texture Studies of Single- and Dual-Phase Materials (this opens in a new tab) Saville, Alec I.; Creuziger, Adam; Mitchell, Emily B.; Vogel, Sven C.; Benzing, Jake T.; Klemm-Toole, Jonah; Clarke, Kester D.; Clarke, Amy J.
13. Microstructure Cluster Analysis with Transfer Learning and Unsupervised Learning (this opens in a new tab) Kitahara, Andrew R.; Holm, Elizabeth A.
14. Effects of Boundary Conditions on Microstructure-Sensitive Fatigue Crystal Plasticity Analysis (this opens in a new tab) Stopka, Krzysztof S.; Yaghoobi, Mohammadreza; Allison, John E.; McDowell, David L.
15. Model Selection and Evaluation for Machine Learning: Deep Learning in Materials Processing (this opens in a new tab) Kopper, Adam; Karkare, Rasika; Paffenroth, Randy C.; Apelian, Diran
16. Effect of Particle Spreading Dynamics on Powder Bed Quality in Metal Additive Manufacturing (this opens in a new tab) Lee, Yousub; Gurnon, A. Kate; Bodner, David; Simunovic, Srdjan
17. Unsupervised Machine Learning Via Transfer Learning and k-Means Clustering to Classify Materials Image Data (this opens in a new tab) Cohn, Ryan; Holm, Elizabeth
18. Numerical Evaluation of Advanced Laser Control Strategies Influence on Residual Stresses for Laser Powder Bed Fusion Systems (this opens in a new tab) Carraturo, Massimo; Lane, Brandon; Yeung, Ho; Kollmannsberger, Stefan; Reali, Alessandro; Auricchio, Ferdinando
19. Outcomes and Conclusions from the 2018 AM-Bench Measurements, Challenge Problems, Modeling Submissions, and Conference (this opens in a new tab) Levine, Lyle; Lane, Brandon; Heigel, Jarred; Migler, Kalman; Stoudt, Mark; Phan, Thien; Ricker, Richard; Strantza, Maria; Hill, Michael; Zhang, Fan; Seppala, Jonathan; Garboczi, Edward; Bain, Erich; Cole, Daniel; Allen, Andrew; Fox, Jason; Campbell, Carelyn
20. Elastic Residual Strain and Stress Measurements and Corresponding Part Deflections of 3D Additive Manufacturing Builds of IN625 AM-Bench Artifacts Using Neutron Diffraction, Synchrotron X-Ray Diffraction, and Contour Method (this opens in a new tab) Phan, Thien Q.; Strantza, Maria; Hill, Michael R.; Gnaupel-Herold, Thomas H.; Heigel, Jarred; D'Elia, Christopher R.; DeWald, Adrian T.; Clausen, Bjorn; Pagan, Darren C.; Ko, J. Y. Peter; Brown, Donald W.; Levine, Lyle E.
21. Uncertainty Quantification and Propagation in Computational Materials Science and Simulation-Assisted Materials Design (this opens in a new tab) Honarmandi, Pejman; Arroyave, Raymundo
22. Estimation of Local Strain Fields in Two-Phase Elastic Composite Materials Using UNet-Based Deep Learning (this opens in a new tab) Raj, Mayank; Thakre, Sanket; Annabattula, Ratna Kumar; Kanjarla, Anand K.
23. The AFRL Additive Manufacturing Modeling Challenge: Predicting Micromechanical Fields in AM IN625 Using an FFT-Based Method with Direct Input from a 3D Microstructural Image (this opens in a new tab) Cocke, Carter K.; Rollett, Anthony D.; Lebensohn, Ricardo A.; Spear, Ashley D.
24. Integrated Modeling of Carburizing-Quenching-Tempering of Steel Gears for an ICME Framework (this opens in a new tab) Khan, Danish; Gautham, B. P.
25. 3D Grain Shape Generation in Polycrystals Using Generative Adversarial Networks (this opens in a new tab) Jangid, Devendra K.; Brodnik, Neal R.; Khan, Amil; Goebel, Michael G.; Echlin, McLean P.; Pollock, Tresa M.; Daly, Samantha H.; Manjunath, B. S.

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