TY - JOUR
T1 - Text Mining the Literature to Inform Experiments and Rationalize Impurity Phase Formation for BiFeO3
AU - Cruse, Kevin
AU - Baibakova, Viktoriia
AU - Abdelsamie, Maged
AU - Hong, Kootak
AU - Bartel, Christopher J.
AU - Trewartha, Amalie
AU - Jain, Anubhav
AU - Sutter-Fella, Carolin M.
AU - Ceder, Gerbrand
N1 - Publisher Copyright:
© 2023 The Authors. Published by American Chemical Society.
PY - 2024/1/23
Y1 - 2024/1/23
N2 - We used data-driven methods to understand the formation of impurity phases in BiFeO3 thin-film synthesis through the sol-gel technique. Using a high-quality dataset of 331 synthesis procedures and outcomes extracted manually from 177 scientific articles, we trained decision tree models that reinforce important experimental heuristics for the avoidance of phase impurities but ultimately show limited predictive capability. We find that several important synthesis features, identified by our model, are often not reported in the literature. To test our ability to correctly impute missing synthesis parameters, we attempted to reproduce nine syntheses from the literature with varying degrees of “missingness”. We demonstrate how a text-mined dataset can be made useful by informing new controlled experiments and forming a better understanding for impurity phase formation in this complex oxide system.
AB - We used data-driven methods to understand the formation of impurity phases in BiFeO3 thin-film synthesis through the sol-gel technique. Using a high-quality dataset of 331 synthesis procedures and outcomes extracted manually from 177 scientific articles, we trained decision tree models that reinforce important experimental heuristics for the avoidance of phase impurities but ultimately show limited predictive capability. We find that several important synthesis features, identified by our model, are often not reported in the literature. To test our ability to correctly impute missing synthesis parameters, we attempted to reproduce nine syntheses from the literature with varying degrees of “missingness”. We demonstrate how a text-mined dataset can be made useful by informing new controlled experiments and forming a better understanding for impurity phase formation in this complex oxide system.
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U2 - 10.1021/acs.chemmater.3c02203
DO - 10.1021/acs.chemmater.3c02203
M3 - Article
C2 - 38282687
AN - SCOPUS:85181840401
SN - 0897-4756
VL - 36
SP - 772
EP - 785
JO - Chemistry of Materials
JF - Chemistry of Materials
IS - 2
ER -