Li’s Group | School of Materials Science and Engineering

01

Heterogeneous Catalysis

Theory and computation are used to resolve catalytic processes at molecular and atomic scales, supporting the design of active, selective and resilient materials.

Zhong L, Li S*. Unconventional oxygen reduction reaction mechanism and scaling relation on single-atom catalysts. ACS Catalysis (2020).
Tran NV, Liu J, Li S. Dynamic Adaptation of Active Site Driven by Dual-side Adsorption in Single-Atomic Catalysts During CO₂ Electroreduction. Angew. Chem. Int. Ed. (2024).

Reaction network for dynamic active-site adaptation during CO₂ electroreduction on a single-atom catalyst

02

Machine Learning for Material Design

Data-driven accelerate the design of materials, while coordination-environment optimisation identifies high-performance active sites. We connect synthesis, active-site descriptors and performance data to guide material discovery.

Machine-learning workflow for optimising single-atom catalyst coordination and Fenton activity

03

Flexible Electronics & Soft Materials

We combine molecular dynamics, machine learning and charge-transport theory to reveal how cyclic deformation and strain-induced dynamic disorder govern mobility in polymer semiconductors and molecular single crystals, guiding the design of robust flexible electronics.

Machine-learning analysis of electronic coupling and charge mobility in stretched polymer semiconductors

Welcome to Li’s Group.

Three connected directions

Heterogeneous Catalysis

Machine Learning for Material Design

Flexible Electronics & Soft Materials