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Recent Publications
Predicting self-assembly of sequence-controlled copolymers with stochastic sequence variation
Curtis, K. A., Statt, A. & Reinhart, W. F., 2025, (Accepted/In press) In: Soft matter.Research output: Contribution to journal › Article › peer-review
Overcoming sparse datasets with multi-task learning as applied to high entropy alloys
Debnath, A. & Reinhart, W. F., Mar 31 2025, In: Machine Learning: Science and Technology. 6, 1, 015046.Research output: Contribution to journal › Article › peer-review
Damage localization using differentiable physics and displacement-based structural identification
Farnod, B. R., Reinhart, W. F. & Napolitano, R. K., Jan 2025, In: Structures. 71, 108142.Research output: Contribution to journal › Article › peer-review
A bio-lattice deep learning framework for modeling discrete biological materials
Kumar, M., Upadhyay, N., Barai, S., Reinhart, W. F. & Peco, C., Apr 2025, In: Journal of the Mechanical Behavior of Biomedical Materials. 164, 106900.Research output: Contribution to journal › Article › peer-review
Data-driven evaluation of building materials using Ground Penetrating Radar
Alam, A. N., Reinhart, W. F. & Napolitano, R. K., Oct 15 2024, In: Journal of Building Engineering. 95, 110188.Research output: Contribution to journal › Article › peer-review
Large Language Models as Molecular Design Engines
Bhattacharya, D., Cassady, H. J., Hickner, M. A. & Reinhart, W. F., Sep 23 2024, In: Journal of Chemical Information and Modeling. 64, 18, p. 7086-7096 11 p.Research output: Contribution to journal › Article › peer-review
Design and validation of refractory alloys using machine learning, CALPHAD, and experiments
Li, W., Raman, L., Debnath, A., Ahn, M., Lin, S., Krajewski, A. M., Shang, S., Priya, S., Reinhart, W. F., Liu, Z. K. & Beese, A. M., Jun 2024, In: International Journal of Refractory Metals and Hard Materials. 121, 106673.Research output: Contribution to journal › Article › peer-review
Crystal growth characterization of WSe2 thin film using machine learning
Moses, I. A., Wu, C. & Reinhart, W. F., Jun 2024, In: Materials Today Advances. 22, 100483.Research output: Contribution to journal › Article › peer-review
Quantitative analysis of MoS2 thin film micrographs with machine learning
Moses, I. A. & Reinhart, W. F., Mar 2024, In: Materials Characterization. 209, 113701.Research output: Contribution to journal › Article › peer-review
Transfer learning for multi-material classification of transition metal dichalcogenides with atomic force microscopy
Moses, I. A. & Reinhart, W. F., Dec 1 2024, In: Machine Learning: Science and Technology. 5, 4, 045081.Research output: Contribution to journal › Article › peer-review
Data-Driven Design Space Analysis for Multimaterial Thermoplastic Composites Manufactured by Fused Filament Fabrication
Oturak, S., McKeehan, M., Zawaski, C. & Reinhart, W. F., 2024, (Accepted/In press) In: 3D Printing and Additive Manufacturing.Research output: Contribution to journal › Article › peer-review
Data-driven inverse design of MoNbTiVWZr refractory multicomponent alloys: Microstructure and mechanical properties
Raman, L., Debnath, A., Furton, E., Lin, S., Krajewski, A., Ghosh, S., Liu, N., Ahn, M., Poudel, B., Shang, S., Priya, S., Liu, Z. K., Beese, A. M., Reinhart, W. & Li, W., Dec 2024, In: Materials Science and Engineering: A. 918, 147475.Research output: Contribution to journal › Article › peer-review
Large language models design sequence-defined macromolecules via evolutionary optimization
Reinhart, W. F. & Statt, A., Dec 2024, In: npj Computational Materials. 10, 1, 262.Research output: Contribution to journal › Article › peer-review
Using Data-Science Approaches to Unravel Insights for Enhanced Transport of Lithium Ions in Single-Ion Conducting Polymer Electrolytes
Zhu, Q., Liu, Y., Shepard, L. B., Bhattacharya, D., Sinnott, S. B., Reinhart, W. F., Cooper, V. R. & Kumar, R., Dec 24 2024, In: Chemistry of Materials. 36, 24, p. 11934-11946 13 p.Research output: Contribution to journal › Article › peer-review
Comparing forward and inverse design paradigms: A case study on refractory high-entropy alloys
Debnath, A., Raman, L., Li, W., Krajewski, A. M., Ahn, M., Lin, S., Shang, S., Beese, A. M., Liu, Z. K. & Reinhart, W. F., Sep 14 2023, In: Journal of Materials Research. 38, 17, p. 4107-4117 11 p.Research output: Contribution to journal › Article › peer-review