Prediction of Diblock Copolymer Morphology via Machine Learning

no code implementations • 31 Aug 2023 • Hyun Park, Boyuan Yu, Juhae Park, Ge Sun, Emad Tajkhorshid, Juan J. de Pablo, Ludwig Schneider

A machine learning approach is presented to accelerate the computation of block polymer morphology evolution for large domains over long timescales.

Data Augmentation Explainable artificial intelligence

A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture

1 code implementation • 14 Jun 2023 • Hyun Park, Xiaoli Yan, Ruijie Zhu, E. A. Huerta, Santanu Chaudhuri, Donny Cooper, Ian Foster, Emad Tajkhorshid

Metal-organic frameworks (MOFs) exhibit great promise for CO2 capture.

End-to-end AI framework for interpretable prediction of molecular and crystal properties

1 code implementation • 21 Dec 2022 • Hyun Park, Ruijie Zhu, E. A. Huerta, Santanu Chaudhuri, Emad Tajkhorshid, Donny Cooper

We introduce an end-to-end computational framework that allows for hyperparameter optimization using the DeepHyper library, accelerated model training, and interpretable AI inference.

Hyperparameter Optimization