270 citations · 358 across the 8 of their papers we have counts for
8 papers
Sustainability-informed materials design
Rachel Woods-Robinson, Amalie Trewartha
While material innovation can enable sustainable development, environmental and social impacts of emerging materials are often assessed only after design choices are "locked in." H…
The potential and viability of V2G for California BEV drivers
Clement Wong, Amalie Trewartha, Steven B. Torrisi +1
Vehicle-to-Grid (V2G) adoption is hindered by uncertainties regarding its effects on battery lifetime and vehicle usability. These uncertainties are compounded by limited insight i…
A treatment of particle-electrolyte sharp interface fracture in solid-state batteries with multi-field discontinuities
Xiaoxuan Zhang, Tryaksh Gupta, Zhenlin Wang +3
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 inter…
Text-mined dataset of gold nanoparticle synthesis procedures, morphologies, and size entities
Kevin Cruse, Amalie Trewartha, Sanghoon Lee +6
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 particl…
Machine-learning rationalization and prediction of solid-state synthesis conditions
Haoyan Huo, Christopher J. Bartel, Tanjin He +5
There currently exist no quantitative methods to determine the appropriate conditions for solid-state synthesis. This not only hinders the experimental realization of novel materia…
Dataset of gold nanoparticle sizes and morphologies extracted from literature-mined microscopy images
Akshay Subramanian, Kevin Cruse, Amalie Trewartha +3
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…
COVIDScholar: An automated COVID-19 research aggregation and analysis platform
Amalie Trewartha, John Dagdelen, Haoyan Huo +8
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 res…
A critical examination of compound stability predictions from machine-learned formation energies
Christopher J. Bartel, Amalie Trewartha, Qi Wang +3
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…