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Jupyter notebooks and data for our Chemistry of Materials article "Data-driven First Principles Methods for the Study and Design of Alkali Superionic Conductors"

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Introduction

This repository contains the Jupyter notebooks and data for our Chemistry of Materials article "Data-driven First Principles Methods for the Study and Design of Alkali Superionic Conductors".

In this article, we present a detailed exposition of how first principles methods can be used to guide alkali superionic conductor (ASIC) study and design. Using the argyrodite Li6PS5Cl as a case study, we demonstrate how modern information technology (IT) infrastructure and software tools can facilitate the assessment of alkali superionic conductors in terms of various critical properties of interest such as phase and electrochemical stability, and ionic conductivity. The emphasis is on well-documented, reproducible analysis code that can be readily generalized to other materials systems and design problems.

You can find the article at the Materials Virtual Lab's publication page or at the Chemistry of Materials website.

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Jupyter notebooks and data for our Chemistry of Materials article "Data-driven First Principles Methods for the Study and Design of Alkali Superionic Conductors"

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