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Search Publications by: Dylan Kirsch (Fed)

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Displaying 1 - 3 of 3

A case study of multi-modal, multi-institutional data management for the combinatorial materials science community

March 22, 2024
Author(s)
Sarah Allec, Eric Muckley, Nathan Johnson, Christopher Borg, Dylan Kirsch, Joshua B. Martin, Ichiro Takeuchi, Andrew Lee, James Saal, Logan Ward, Apruva Mehta
Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functional materials and acceleration of their design will require addressing the

The development of an augmented machine learning approach for the additive manufacturing of thermoelectric materials

February 28, 2024
Author(s)
Connor V. Headley, Roberto J. Herrera del Valle, Ji Ma, Prasanna Balachandran, Vijayabarathi Ponnambalam, Saniya LeBlanc, Dylan Kirsch, Joshua B. Martin
Through the integration of machine learning (ML) techniques alongside additive manufacturing (AM) experimentation, we demonstrate an iterative process to rapidly predict laser-material interactions and melt pool geometries throughout the build parameter

High-throughput printing of combinatorial materials from aerosols

May 10, 2023
Author(s)
Minxiang Zeng, Yipu Du, Nicholas Kempf, Miles Bimrose, Jiahao Chen, Dylan Kirsch, Joshua B. Martin, Bowen Zhang, Tatsunori Hayashi, Mortaza Saeidi-Javash, Hirotaka Sakaue, Babak Anasori, Michael McMurtrey, Yanliang Zhang
The development of new materials and their compositional and microstructural optimization are essential in regard to next-generation technologies such as clean energy and environmental sustainability. However, materials discovery and optimization have been