What question did this study set out to answer?

The aim is to optimize 2D halide perovskites using large language model (LLM) techniques.

April 1, 2026Digital Discovery2 citationsOpen Access

POLARIS: perovskite optimization using LLM-assisted refinement and intelligent screening

JMJordan M. MarshallIndiana University – Purdue University Fort Wayne SSSheryl L. SanchezKnoxville College RDRushik DesaiPurdue University West Lafayette

Key Points

The aim is to optimize 2D halide perovskites using large language model (LLM) techniques.
Utilized LLM-assisted mining to convert literature into a spacer-cation dataset.
Applied GNN-GP models to predict structural and optoelectronic properties with uncertainty.
Implemented clustering methods to categorize chemical spacer families.
Identified significant patterns in the structural and optoelectronic properties of perovskites.
Generated a comprehensive dataset from 200 studies that facilitates further materials research.

Abstract

LLM-assisted mining converts 200 studies on 2D halide perovskites into a spacer-cation dataset. GNN-GP models predict structural and optoelectronic targets with uncertainty, and clustering reveals chemical spacer families.

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Cite This Study

Marshall et al. (Thu,) studied this question.

synapsesocial.com/papers/69ccb6ce16edfba7beb888e4 https://doi.org/https://doi.org/10.1039/d5dd00378d

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