T
Troy D. Loeffler
Researcher at Argonne National Laboratory
Publications - 46
Citations - 812
Troy D. Loeffler is an academic researcher from Argonne National Laboratory. The author has contributed to research in topics: Monte Carlo method & Computer science. The author has an hindex of 10, co-authored 39 publications receiving 412 citations. Previous affiliations of Troy D. Loeffler include Louisiana State University & University of Illinois at Chicago.
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Journal ArticleDOI
Machine learning enabled autonomous microstructural characterization in 3D samples
Henry Chan,Mathew J. Cherukara,Troy D. Loeffler,Badri Narayanan,Badri Narayanan,Subramanian K. R. S. Sankaranarayanan,Subramanian K. R. S. Sankaranarayanan +6 more
TL;DR: This work introduces an unsupervised machine learning (ML) based technique for the identification and characterization of microstructures in three-dimensional samples obtained from molecular dynamics simulations, particle tracking data, or experiments that combines topology classification, image processing, and clustering algorithms.
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Machine learning coarse grained models for water.
Henry Chan,Mathew J. Cherukara,Badri Narayanan,Badri Narayanan,Troy D. Loeffler,Chris J. Benmore,Stephen K. Gray,Stephen K. Gray,Subramanian K. R. S. Sankaranarayanan,Subramanian K. R. S. Sankaranarayanan +9 more
TL;DR: A machine-learned coarse-grained water model to elucidate the ice nucleation process much more efficiently than previous models is developed, in a significant departure from conventional force-field fitting.
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Inverse design of metasurfaces with non-local interactions
Haogang Cai,Srilok Srinivasan,David A. Czaplewski,Alex B. F. Martinson,David J. Gosztola,Liliana Stan,Troy D. Loeffler,Subramanian K. R. S. Sankaranarayanan,Subramanian K. R. S. Sankaranarayanan,Daniel Lopez +9 more
TL;DR: This work takes full advantage of the strong interactions among nanoresonators to improve the focusing efficiency of metalenses and demonstrates that efficiency improvements can be obtained by lowering the metasurface filling factors.
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Active Learning the Potential Energy Landscape for Water Clusters from Sparse Training Data
Troy D. Loeffler,Tarak K. Patra,Henry Chan,Mathew J. Cherukara,Subramanian K. R. S. Sankaranarayanan,Subramanian K. R. S. Sankaranarayanan +5 more
TL;DR: In this article, a technique for understanding dynamical evolution of systems with predefined functional forms is presented, which imposes limits on the physics that can be observed. But it is not suitable for the analysis of complex systems.
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Accelerating copolymer inverse design using monte carlo tree search.
Tarak K. Patra,Troy D. Loeffler,Troy D. Loeffler,Subramanian K. R. S. Sankaranarayanan,Subramanian K. R. S. Sankaranarayanan +4 more
TL;DR: This work interfaces MCTS with MD simulations and uses a representative example of designing a copolymer compatibilizer, where the goal is to identify sequence specific copolymers that lead to zero interfacial energy between two immiscible homopolymers.