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Wei Xie

Researcher at University of California, Berkeley

Publications -  36
Citations -  1261

Wei Xie is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Computer science & GNSS applications. The author has an hindex of 13, co-authored 24 publications receiving 805 citations. Previous affiliations of Wei Xie include University of Wisconsin-Madison & Shanghai University.

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The MAterials Simulation Toolkit (MAST) for atomistic modeling of defects and diffusion

TL;DR: The MAterials Simulation Toolkit (MAST) is a workflow manager and post-processing tool for ab initio defect and diffusion workflows that allows for the generation and management of easily modified and reproducible workflows.
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Ab initio -aided CALPHAD thermodynamic modeling of the Sn-Pb binary system under current stressing

TL;DR: Ab initio-aided CALPHAD modeling is utilized to translate the electric current-induced effect into the excess Gibbs free energies of the phases, and shows the change in the phase stabilities of Pb-Sn solders under current stressing.
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Bistable Amphoteric Native Defect Model of Perovskite Photovoltaics.

TL;DR: A model based on bistable amphoteric native defects that accounts for all key characteristics of these photovoltaics and explains many idiosyncratic properties of halide perovskites, including hysteresis of J-V characteristics and ultraviolet light-induced degradation is presented.
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Combined ab initio and empirical model of the thermal conductivity of uranium, uranium-zirconium, and uranium-molybdenum

TL;DR: In this paper, the authors developed a practical and general modeling approach for thermal conductivity of metals and metal alloys that integrates ab initio and semi-empirical physics-based models to maximize the strengths of both techniques.
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Combined ab initio and empirical model of the thermal conductivity of uranium, uranium-zirconium, and uranium-molybdenum

TL;DR: In this article, the authors developed a practical and general modeling approach for thermal conductivity of metals and metal alloys that integrates ab initio and semi-empirical physics-based models to maximize the strengths of both techniques.