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EAS Doctoral Proposal Defense by Md Shovon Hossain

Monday, November 09, 2026 at 11:00am to 1:00pm

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SENG 214
Dr. Caiwei Shen, Department of Mechanical Engineering
cshen2@umassd.edu

Topic: Entropy-Driven Design and Physics-Enforced Neural Network Modeling of Multi-Polymer Solid Electrolytes for Structural Energy Storage

Abstract:

Structural energy storage requires electrolytes that can both conduct ions and carry mechanical loads, yet in solid polymer electrolytes (SPEs) ionic conductivity and mechanical properties are often traded against each other. This proposal examines configurational entropy, introduced by blending chemically distinct polymers, as a design variable to ease this trade-off. Dual-polymer electrolytes of poly(lactic acid) (PLA) and poly(methyl methacrylate) (PMMA) with LiTFSI formed miscible, single-phase matrices with higher ionic conductivity than single-polymer electrolytes, and tuning polymer chain length balanced ionic transport against mechanical integrity. Adding poly(vinylidene fluoride) (PVDF) to form ternary blends produced more diverse Li+ coordination environments in experiments and molecular dynamics simulations, but only two of seven ternary compositions outperformed all single- and dual-polymer electrolytes, indicating that compositional balance governs multifunctional performance. Preliminary five-polymer blends also show promising ionic conductivity, but the composition space is too large to explore experimentally. The proposed work will develop physics-guided machine learning models, trained on a consistently measured dataset and informed by molecular simulations, to predict ionic conductivity and mechanical properties and to guide composition selection. Together, this work aims to establish how entropy and compositional balance can guide the design of SPEs for structural energy storage.

ADVISOR(s):  Dr. Caiwei Shen, Department of Mechanical Engineering, (cshen2@umassd.edu)

COMMITTEE MEMBERS:

  • Dr. Maricris Mayes, Department of Chemistry and Biochemistry
  • Dr. Ruolin Zhou, Department of Electrical and Computer Engineering                                                         

NOTE:  All EAS Students are ENCOURAGED to attend.