Zobrazeno 1 - 10
of 864
pro vyhledávání: '"Trewartha A"'
Autor:
Zhang, Xiaoxuan, Gupta, Tryaksh, Wang, Zhenlin, Trewartha, Amalie, Anapolsky, Abraham, Garikipati, Krishna
In this work, we present a computational framework for coupled electro-chemo-(nonlinear) mechanics at the particle scale for solid-state batteries. The framework accounts for interfacial fracture between the active particles and solid electrolyte due
Externí odkaz:
http://arxiv.org/abs/2309.13463
Publikováno v:
PeerJ, Vol 12, p e17896 (2024)
Ground reaction force (GRF) data is often collected for the biomechanical analysis of running, due to the performance and injury risk insights that GRF analysis can provide. Traditional methods typically limit GRF collection to controlled lab environ
Externí odkaz:
https://doaj.org/article/ecda545797e44a3bb3e9f240f496fb63
Autor:
Cruse, Kevin, Trewartha, Amalie, Lee, Sanghoon, Wang, Zheren, Huo, Haoyan, He, Tanjin, Kononova, Olga, Jain, Anubhav, Ceder, Gerbrand
Gold nanoparticles are highly desired for a range of technological applications due to their tunable properties, which are dictated by the size and shape of the constituent particles. Many heuristic methods for controlling the morphological character
Externí odkaz:
http://arxiv.org/abs/2204.10379
Autor:
Huo, Haoyan, Bartel, Christopher J., He, Tanjin, Trewartha, Amalie, Dunn, Alexander, Ouyang, Bin, Jain, Anubhav, Ceder, Gerbrand
Publikováno v:
Chemistry of Materials, 2022
There currently exist no quantitative methods to determine the appropriate conditions for solid-state synthesis. This not only hinders the experimental realization of novel materials but also complicates the interpretation and understanding of solid-
Externí odkaz:
http://arxiv.org/abs/2204.08151
Publikováno v:
In Journal of Biomechanics December 2024 177
Autor:
Subramanian, Akshay, Cruse, Kevin, Trewartha, Amalie, Wang, Xingzhi, Alivisatos, A. Paul, Ceder, Gerbrand
The factors controlling the size and morphology of nanoparticles have so far been poorly understood. Data-driven techniques are an exciting avenue to explore this field through the identification of trends and correlations in data. However, for these
Externí odkaz:
http://arxiv.org/abs/2112.01689
Publikováno v:
In Journal of Energy Storage 15 March 2024 81
Autor:
Zhang, Xiaoxuan, Gupta, Tryaksh, Wang, Zhenlin, Trewartha, Amalie, Anapolsky, Abraham, Garikipati, Krishna
Publikováno v:
In Journal of the Mechanics and Physics of Solids January 2024 182
Autor:
Trewartha, Amalie, Dagdelen, John, Huo, Haoyan, Cruse, Kevin, Wang, Zheren, He, Tanjin, Subramanian, Akshay, Fei, Yuxing, Justus, Benjamin, Persson, Kristin, Ceder, Gerbrand
The ongoing COVID-19 pandemic has had far-reaching effects throughout society, and science is no exception. The scale, speed, and breadth of the scientific community's COVID-19 response has lead to the emergence of new research literature on a remark
Externí odkaz:
http://arxiv.org/abs/2012.03891
Autor:
Bartel, Christopher J., Trewartha, Amalie, Wang, Qi, Dunn, Alexander, Jain, Anubhav, Ceder, Gerbrand
Publikováno v:
npj Computational Materials 6, 97 (2020)
Machine learning has emerged as a novel tool for the efficient prediction of materials properties, and claims have been made that machine-learned models for the formation energy of compounds can approach the accuracy of Density Functional Theory (DFT
Externí odkaz:
http://arxiv.org/abs/2001.10591