Zhan-Yun Zhang

AI-Accelerated Design and Modeling of Organic Electrochemical Energy Materials: From Redox-Active Molecules to Polymer Electrolytes

Zhang, Zhan-Yun; Savvas, Giannis; Li, Jichen; Zhou, Yue et al.

Part of Macromolecular materials and engineering, 2026

• DOI for AI-Accelerated Design and Modeling of Organic Electrochemical Energy Materials: From Redox-Active Molecules to Polymer Electrolytes
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Unlocking the Chemical Space for Rechargeable Batteries with a Generative Solvent Design System

Zhang, Zhan-Yun; Mercado, Rocio; Le, Thanh Trung; Zhang, Chao

Part of ACS Nano, p. 20714-20729, 2026

• DOI for Unlocking the Chemical Space for Rechargeable Batteries with a Generative Solvent Design System
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A Two-Stage Machine Learning Framework With Physically Inspired Descriptors for Efficient Prediction of Hydration Free Energies

Jia, Luyang; Zhang, Zhan-Yun; Xie, Bin-Bin; Shen, Lin et al.

Part of Chemistry-Methods, 2026

• DOI for A Two-Stage Machine Learning Framework With Physically Inspired Descriptors for Efficient Prediction of Hydration Free Energies
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Foundation model distillation with PiNNAcLe: Application to the ZnCl₂ aqueous electrolyte solution

Sudhama, Aishwarya; Zhang, Zhan-Yun; Zhang, Chao

Part of Electrochimica Acta, 2026

• DOI for Foundation model distillation with PiNNAcLe: Application to the ZnCl₂ aqueous electrolyte solution
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PiNN: equivariant neural network suite for modelling electrochemical systems

Li, Jichen; Knijff, Lisanne; Zhang, Zhan-Yun; Andersson, Linnéa et al.

Part of Journal of Chemical Theory and Computation, p. 1382-1395, 2025

• DOI for PiNN: equivariant neural network suite for modelling electrochemical systems
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Unlocking the Chemical Space for Rechargeable Batteries with a Generative Solvent Design System

Zhang, Zhan-Yun; Mercado, Rocio; Le, Thanh Trung; Zhang, Chao

Part of ACS Nano, p. 20714-20729, 2026

• DOI for Unlocking the Chemical Space for Rechargeable Batteries with a Generative Solvent Design System
• Download full text (pdf) of Unlocking the Chemical Space for Rechargeable Batteries with a Generative Solvent Design System

A Two-Stage Machine Learning Framework With Physically Inspired Descriptors for Efficient Prediction of Hydration Free Energies

Jia, Luyang; Zhang, Zhan-Yun; Xie, Bin-Bin; Shen, Lin et al.

Part of Chemistry-Methods, 2026

• DOI for A Two-Stage Machine Learning Framework With Physically Inspired Descriptors for Efficient Prediction of Hydration Free Energies
• Download full text (pdf) of A Two-Stage Machine Learning Framework With Physically Inspired Descriptors for Efficient Prediction of Hydration Free Energies

Foundation model distillation with PiNNAcLe: Application to the ZnCl₂ aqueous electrolyte solution

Sudhama, Aishwarya; Zhang, Zhan-Yun; Zhang, Chao

Part of Electrochimica Acta, 2026

• DOI for Foundation model distillation with PiNNAcLe: Application to the ZnCl₂ aqueous electrolyte solution
• Download full text (pdf) of Foundation model distillation with PiNNAcLe: Application to the ZnCl₂ aqueous electrolyte solution

PiNN: equivariant neural network suite for modelling electrochemical systems

Li, Jichen; Knijff, Lisanne; Zhang, Zhan-Yun; Andersson, Linnéa et al.

Part of Journal of Chemical Theory and Computation, p. 1382-1395, 2025

• DOI for PiNN: equivariant neural network suite for modelling electrochemical systems
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Machine Learning with Physically Inspired Descriptors to Predict Solvation Free Energies of Neutral and Ionic Solutes in Aqueous and Nonaqueous Solvents

Jia, Luyang; Zhang, Zhan-Yun; Shen, Lin; Fang, Wei-Hai

Part of Journal of Physical Chemistry B, p. 7216-7227, 2025

• DOI for Machine Learning with Physically Inspired Descriptors to Predict Solvation Free Energies of Neutral and Ionic Solutes in Aqueous and Nonaqueous Solvents

PiNN: Equivariant Neural Network Suite for Modeling Electrochemical Systems

Li, Jichen; Knijff, Lisanne; Zhang, Zhan-Yun; Andersson, Linnéa et al.

Part of Journal of Chemical Theory and Computation, p. 1382-1395, 2025

• DOI for PiNN: Equivariant Neural Network Suite for Modeling Electrochemical Systems
• Download full text (pdf) of PiNN: Equivariant Neural Network Suite for Modeling Electrochemical Systems

AI-Accelerated Design and Modeling of Organic Electrochemical Energy Materials: From Redox-Active Molecules to Polymer Electrolytes

Zhang, Zhan-Yun; Savvas, Giannis; Li, Jichen; Zhou, Yue et al.

Part of Macromolecular materials and engineering, 2026

• DOI for AI-Accelerated Design and Modeling of Organic Electrochemical Energy Materials: From Redox-Active Molecules to Polymer Electrolytes
• Download full text (pdf) of AI-Accelerated Design and Modeling of Organic Electrochemical Energy Materials: From Redox-Active Molecules to Polymer Electrolytes