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.

Ingår i Macromolecular materials and engineering, 2026

• DOI för AI-Accelerated Design and Modeling of Organic Electrochemical Energy Materials: From Redox-Active Molecules to Polymer Electrolytes
• Ladda ner fulltext (pdf) av AI-Accelerated Design and Modeling of Organic Electrochemical Energy Materials: From Redox-Active Molecules to Polymer Electrolytes

Unlocking the Chemical Space for Rechargeable Batteries with a Generative Solvent Design System

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

Ingår i ACS Nano, s. 20714-20729, 2026

• DOI för Unlocking the Chemical Space for Rechargeable Batteries with a Generative Solvent Design System
• Ladda ner fulltext (pdf) av 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.

Ingår i Chemistry-Methods, 2026

• DOI för A Two-Stage Machine Learning Framework With Physically Inspired Descriptors for Efficient Prediction of Hydration Free Energies
• Ladda ner fulltext (pdf) av 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

Ingår i Electrochimica Acta, 2026

• DOI för Foundation model distillation with PiNNAcLe: Application to the ZnCl₂ aqueous electrolyte solution
• Ladda ner fulltext (pdf) av 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.

Ingår i Journal of Chemical Theory and Computation, s. 1382-1395, 2025

• DOI för PiNN: equivariant neural network suite for modelling electrochemical systems
• Ladda ner fulltext (pdf) av PiNN: equivariant neural network suite for modelling electrochemical systems

Unlocking the Chemical Space for Rechargeable Batteries with a Generative Solvent Design System

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

Ingår i ACS Nano, s. 20714-20729, 2026

• DOI för Unlocking the Chemical Space for Rechargeable Batteries with a Generative Solvent Design System
• Ladda ner fulltext (pdf) av 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.

Ingår i Chemistry-Methods, 2026

• DOI för A Two-Stage Machine Learning Framework With Physically Inspired Descriptors for Efficient Prediction of Hydration Free Energies
• Ladda ner fulltext (pdf) av 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

Ingår i Electrochimica Acta, 2026

• DOI för Foundation model distillation with PiNNAcLe: Application to the ZnCl₂ aqueous electrolyte solution
• Ladda ner fulltext (pdf) av 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.

Ingår i Journal of Chemical Theory and Computation, s. 1382-1395, 2025

• DOI för PiNN: equivariant neural network suite for modelling electrochemical systems
• Ladda ner fulltext (pdf) av PiNN: equivariant neural network suite for modelling electrochemical systems

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

Ingår i Journal of Physical Chemistry B, s. 7216-7227, 2025

• DOI för 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.

Ingår i Journal of Chemical Theory and Computation, s. 1382-1395, 2025

• DOI för PiNN: Equivariant Neural Network Suite for Modeling Electrochemical Systems
• Ladda ner fulltext (pdf) av 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.

Ingår i Macromolecular materials and engineering, 2026

• DOI för AI-Accelerated Design and Modeling of Organic Electrochemical Energy Materials: From Redox-Active Molecules to Polymer Electrolytes
• Ladda ner fulltext (pdf) av AI-Accelerated Design and Modeling of Organic Electrochemical Energy Materials: From Redox-Active Molecules to Polymer Electrolytes