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  5. Optimal thermodynamic conditions to minimize kinetic byproducts in aqueous materials synthesis

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Preprint
en
2023

Optimal thermodynamic conditions to minimize kinetic byproducts in aqueous materials synthesis

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en
2023
DOI: 10.21203/rs.3.rs-2398824/v1

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Gerbrand Ceder
Gerbrand Ceder

University of California, Berkeley

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Zheren Wang
Yingzhi Sun
Kevin Cruse
+9 more

Abstract

Abstract Thermodynamics has strong predictive power for materials synthesis by identifying the stability region of target phases, but does not give explicit information about the relative competitiveness of undesired byproduct phases in synthesis. In this work, we propose a quantitative and computable measure to guide the selection of synthesis conditions. Defining thermodynamic competition as the difference in driving force between a target phase and its competing phases, we hypothesize that phase-pure synthesis becomes more likely when this thermodynamic competition is minimized. We systematically validate this hypothesis with two approaches: (1) we analyze large-scale solution synthesis procedures as text-mined from the literature, and show that experimentally-optimized synthesis conditions are near the predicted thermodynamic optimum point, and (2) direct experimental evaluation of synthesis in LiIn(IO3)4 and LiFePO4, which show that phase-pure synthesis occurs only when thermodynamic competition is minimized. Our work demonstrates that a quantitative assessment of thermodynamic competition is an effective descriptor for synthesis optimization and a promising tool for optimizing aqueous solution-based experimental synthesis conditions.

How to cite this publication

Zheren Wang, Yingzhi Sun, Kevin Cruse, Yan Zeng, Yuxing Fei, Zexuan Liu, Junyi Shangguan, Young‐Woon Byeon, KyuJung Jun, Tanjin He, Wenhao Sun, Gerbrand Ceder (2023). Optimal thermodynamic conditions to minimize kinetic byproducts in aqueous materials synthesis. , DOI: https://doi.org/10.21203/rs.3.rs-2398824/v1.

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Publication Details

Type

Preprint

Year

2023

Authors

12

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.21203/rs.3.rs-2398824/v1

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