Harnessing GPT-3.5 for text parsing in solid-state synthesis – case study of ternary chalcogenides-Reference-Cited by-同舟云学术

Harnessing GPT-3.5 for text parsing in solid-state synthesis – case study of ternary chalcogenides

Published:2024 Issue:2 Volume:3 Page:328-336
ISSN:2635-098X
Container-title:Digital Discovery
language:en
Short-container-title:Digital Discovery

Author:

Thway Maung¹^ORCID,Low Andre K. Y.¹²^ORCID,Khetan Samyak³,Dai Haiwen¹,Recatala-Gomez Jose¹,Chen Andy Paul¹,Hippalgaonkar Kedar¹²^ORCID

Affiliation:

1. School of Materials Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore

2. Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), Singapore 138634, Singapore

3. Department of Metallurgical Engineering and Materials Science, Indian Institute of Technology Bombay, Maharashtra 400076, India

Abstract

Optimally doped single-phase compounds are necessary to advance state-of-the-art thermoelectric devices which convert heat into electricity and vice versa, requiring solid-state synthesis of bulk materials.

Funder

Institute of Materials Research and Engineering

National Research Foundation Singapore

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/DD/D3DD00202K

Reference42 articles.

1. Machine-Learning Rationalization and Prediction of Solid-State Synthesis Conditions

2. A graph-based network for predicting chemical reaction pathways in solid-state materials synthesis

3. Observing and Modeling the Sequential Pairwise Reactions that Drive Solid‐State Ceramic Synthesis

4. The interplay between thermodynamics and kinetics in the solid-state synthesis of layered oxides

5. Selective metathesis synthesis of MgCr2S4 by control of thermodynamic driving forces

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