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Xiao-Yu Ma

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Open access Oct 2026

DNN Surrogate-Assisted Multi-Objective Optimization for Inverse Process Design of SBS-Modified Asphalt Gels

Styrene–butadiene–styrene (SBS)-modified asphalt is a typical physical polymer gel whose macroscopic performance is governed by the coupled effects of processing parameters, material composition, and microstructural characteristics. While machine learning has enabled accurate forward prediction of gel properties, a sys...

Zong-Yuan Wu, Xiao-Yu Ma, Jia-Ming Yang et al. · 0 citations
#explainable ai Open access Sep 2026

From Processing to Performance: A Multi-Scale Machine Learning Framework for SBS-Modified Asphalt Gels with Multi-Target Correlation and Explainable AI

A multi-scale machine learning framework is proposed to establish processing–composition–structure–performance mappings for SBS-modified asphalt gels and enables accurate and interpretable prediction of gel properties and provides a data-driven foundation for material design.

Zong-Yuan Wu, Xiao-Yu Ma, Meng-Xin Qiu et al. · 0 citations

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