AlloyBERT: Alloy Property Prediction with Large Language Models

arXiv:2403.19783v1 Announce Type: cross
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 …

abstract arxiv challenges cond-mat.mtrl-sci cs.lg encoder importance language language models large language large language models novel parameters prediction predictive processing property requirements researchers study transformer transformer encoder type