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Troy D Loeffler

Showing results (11-20 of 17) with videos related to

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ACS Applied Materials & Interfaces|August 24, 2021
Retraction of "Promoting Noncovalent Intermolecular Interactions Using a C60 Core Particle in Aqueous PC60s-Covered Colloids for Ultraefficient Photoinduced Particle Activity"Yu Jin Kim, Troy D Loeffler, Zhaowei Chen, et al.
The Journal of Physical Chemistry. B|June 21, 2018
Configurational-Bias Monte Carlo Back-Mapping Algorithm for Efficient and Rapid Conversion of Coarse-Grained Water Structures into Atomistic ModelsTroy D Loeffler, Henry Chan, Badri Narayanan, et al.
ACS Applied Materials & Interfaces|April 9, 2024
Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition MetalsBilvin Varughese, Sukriti Manna, Troy D Loeffler, et al.
Nature Communications|January 24, 2019
Machine learning coarse grained models for waterHenry Chan, Mathew J Cherukara, Badri Narayanan, et al.
The Journal of Physical Chemistry Letters|February 17, 2022
Multi-reward Reinforcement Learning Based Bond-Order Potential to Study Strain-Assisted Phase Transitions in PhosphoreneAditya Koneru, Rohit Batra, Sukriti Manna, et al.
Nature Chemistry|November 1, 2022
Machine learning overcomes human bias in the discovery of self-assembling peptidesRohit Batra, Troy D Loeffler, Henry Chan, et al.
Nature Communications|January 19, 2022
Learning in continuous action space for developing high dimensional potential energy modelsSukriti Manna, Troy D Loeffler, Rohit Batra, et al.
Pageof 2

Showing results (11-20 of 17) with videos related to

Sort By:
Pageof 2
You have reached the last page of results.This site can display upto 17 results.
ACS Applied Materials & Interfaces|August 24, 2021
Retraction of "Promoting Noncovalent Intermolecular Interactions Using a C60 Core Particle in Aqueous PC60s-Covered Colloids for Ultraefficient Photoinduced Particle Activity"Yu Jin Kim, Troy D Loeffler, Zhaowei Chen, et al.
The Journal of Physical Chemistry. B|June 21, 2018
Configurational-Bias Monte Carlo Back-Mapping Algorithm for Efficient and Rapid Conversion of Coarse-Grained Water Structures into Atomistic ModelsTroy D Loeffler, Henry Chan, Badri Narayanan, et al.
ACS Applied Materials & Interfaces|April 9, 2024
Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition MetalsBilvin Varughese, Sukriti Manna, Troy D Loeffler, et al.
Nature Communications|January 24, 2019
Machine learning coarse grained models for waterHenry Chan, Mathew J Cherukara, Badri Narayanan, et al.
The Journal of Physical Chemistry Letters|February 17, 2022
Multi-reward Reinforcement Learning Based Bond-Order Potential to Study Strain-Assisted Phase Transitions in PhosphoreneAditya Koneru, Rohit Batra, Sukriti Manna, et al.
Nature Chemistry|November 1, 2022
Machine learning overcomes human bias in the discovery of self-assembling peptidesRohit Batra, Troy D Loeffler, Henry Chan, et al.
Nature Communications|January 19, 2022
Learning in continuous action space for developing high dimensional potential energy modelsSukriti Manna, Troy D Loeffler, Rohit Batra, et al.
Pageof 2