AlloyBERT: Alloy Property Prediction with Large Language Models

TL;DR

AlloyBERT leverages large language models to predict alloy properties from textual descriptions, outperforming traditional models and demonstrating the potential of NLP techniques in materials science.

Contribution

This paper introduces AlloyBERT, a novel transformer-based model that predicts alloy properties from textual data, combining pre-trained language models with domain-specific fine-tuning.

Findings

Achieved low MSE scores on alloy property datasets.

Outperformed shallow models in property prediction accuracy.

Established a text-based framework for alloy property prediction.

Abstract

The pursuit of novel alloys tailored to specific requirements poses significant challenges for researchers in the field. This underscores the importance of developing predictive techniques for essential physical properties of alloys based on their chemical composition and processing parameters. This study introduces AlloyBERT, a transformer encoder-based model designed to predict properties such as elastic modulus and yield strength of alloys using textual inputs. Leveraging the pre-trained RoBERTa encoder model as its foundation, AlloyBERT employs self-attention mechanisms to establish meaningful relationships between words, enabling it to interpret human-readable input and predict target alloy properties. By combining a tokenizer trained on our textual data and a RoBERTa encoder pre-trained and fine-tuned for this specific task, we achieved a mean squared error (MSE) of 0.00015 on the Multi Principal Elemental Alloys (MPEA) data set and 0.00611 on the Refractory Alloy Yield Strength (RAYS) dataset. This surpasses the performance of shallow models, which achieved a best-case MSE of 0.00025 and 0.0076 on the MPEA and RAYS datasets respectively. Our results highlight the potential of language models in material science and establish a foundational framework for text-based prediction of alloy properties that does not rely on complex underlying representations, calculations, or simulations.