Machine learning in soft matter: from simulations to experiments

K Zhang, X Gong, Y Jiang - Advanced Functional Materials, 2024 - Wiley Online Library
Soft matter with diverse functionalities that are easily designable has fascinated tremendous
research interests in the past several decades. Nevertheless, the inherent confluence of time …

Machine Learning Approaches in Polymer Science: Progress and Fundamental for a New Paradigm

C **e, H Qiu, L Liu, Y You, H Li, Y Li, Z Sun, J Lin… - …, 2025 - Wiley Online Library
Machine learning (ML), material genome, and big data approaches are highly overlapped in
their strategies, algorithms, and models. They can target various definitions, distributions …

Using active learning for the computational design of polymer molecular weight distributions

H Zhou, Y Fang, H Gao - ACS Engineering Au, 2023 - ACS Publications
The design of the reaction conditions is essential for controlling polymerization to synthesize
polymers with desired properties. However, the experimental screening of the reaction …

Ensemble transfer learning assisted soft sensor for distributed output inference in chemical processes

J Zhu, W Zhu, Y Liu - Computers & Chemical Engineering, 2025 - Elsevier
Chemical processes with distributed outputs are characterized by various operating
conditions, and the scarcity of labeled data poses challenges to the prediction of product …

Temporal graph convolutional network soft sensor for molecular weight distribution prediction

W Guo, J Zhu, X Yu, M Jia, Y Liu - Chemometrics and Intelligent Laboratory …, 2024 - Elsevier
In chemical processes with distributed outputs, characteristics of products are influenced by
their distributions and significantly correlated with process variables. It is crucial for an …

Emerging trends in the optimization of organic synthesis through high-throughput tools and machine learning

PQ Velasco, K Hippalgaonkar… - Beilstein Journal of …, 2025 - beilstein-journals.org
The discovery of the optimal conditions for chemical reactions is a labor-intensive, time-
consuming task that requires exploring a high-dimensional parametric space. Historically …

Data‐driven deep learning prediction of full molecular weight distribution in polymerization processes

D Mora‐Mariano, A Flores‐Tlacuahuac… - The Canadian Journal … - Wiley Online Library
The mathematical modelling of the full molecular weight distribution (MWD) results in a large
set of ordinary differential equations (ODEs), which usually requires considerable …