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Abstract

A method for designing polymers includes translating polymer representations of a training dataset and a test dataset into a format comprehensible by a generative pretraining transformer (GPT)-based model, training the GPT-based model with the translated polymer representations, generating new polymer representations, in a predefined format, using the trained GPT-based model, predicting at least one property of the generated new polymer representations using a machine learning (ML) property predictive model and selecting a first subset of the generated new polymer representations as a function of the at least one predicted property, and calculating the at least one property of the first subset of the generated new polymer representations using a molecular dynamics (MD) module.

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First Claim