800 citations · 3.2k across the 56 of their papers we have counts for
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Machine learning and high-throughput robust design of P3HT-CNT composite thin films for high electrical conductivity
Daniil Bash, Yongqiang Cai, Vijila Chellappan +16
Combining high-throughput experiments with machine learning allows quick optimization of parameter spaces towards achieving target properties. In this study, we demonstrate that ma…
A robust low data solution: dimension prediction of semiconductor nanorods
Xiaoli Liu, Yang Xu, Jiali Li +4
Precise control over dimension of nanocrystals is critical to tune the properties for various applications. However, the traditional control through experimental optimization is sl…
An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties
Zekun Ren, Siyu Isaac Parker Tian, Juhwan Noh +14
Realizing general inverse design could greatly accelerate the discovery of new materials with user-defined properties. However, state-of-the-art generative models tend to be limite…
Bridging the gap between photovoltaics R&D and manufacturing with data-driven optimization
Felipe Oviedo, Zekun Ren, Xue Hansong +12
Novel photovoltaics, such as perovskites and perovskite-inspired materials, have shown great promise due to high efficiency and potentially low manufacturing cost. So far, solar ce…
Techno-economic model of a second-life energy storage system for utility-scale solar power considering li-ion calendar and cycle aging
Ian Mathews, Bolun Xu, Wei He +3
While the use of energy storage combined with grid-scale photovoltaic power plants continues to grow, given current lithium-ion battery prices, there remains uncertainty about the…