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Group Introduction

We are a group engaged in theoretical modelling and design of organic semiconducting and low-dimensional materials using state-of-the-art computational methods, including first-principles electronic structure calculations, density functional perturbation theory, molecular dynamics, as well as machine learning. 

Our recent work focuses on four primary directions

Prediction of thermoelectric properties of organic materials, and strategies to improve thermoelectric conversion efficiency by band engineering, optimal doping, as well as tailoring molecular weight and crystallinity of polymeric materials.

Design of covalent organic frameworks and metal organic frameworks for electronic, spintronic, magnetic, and photocatalytic applications. 

Novel van der Waals layered materials for ferroelectric and structural phase change memories.

Collaborations with experimentalists to understand the structure, self-assembly, and chemical activities of low-dimensional systems.

Recent Publications
  • Tianhao Tan, Lian Duan, Dong Wang*Interpretable Machine Learning for Solvent-Dependent Carrier Mobility in Solution-Processed Organic Thin Films.
    Adv. Intell. Discov.0 (2025), e2500078.
  • Mianzhi Pan†, Tianhao Tan†, Yawen Ouyang†, Qian Jin, Yougang Chu, Wei-Ying Ma, Jianbing Zhang, Lian Duan*, Dong Wang*, Hao Zhou*,Generative AI-powered inverse design for tailored narrowband molecular emitters.
    Digit. Discov.4, (2025)2942-2953.
  • Qian Jin, Lu Wang, Lian Duan, and Dong Wang*.Boosting Exciton Utilization Rate in Organic Electroluminescence Devices with BN-Embedded Triangulenes and Triplet Fluorescence Emission.
    J. Phys. Chem. Lett.16 (2025),4893-4899.
  • Chunlin Xu and Dong Wang*Theoretical Perspective of Enhancing Order in n-Doped Thermoelectric Polymers through Side Chain Engineering: The Interplay of Counterion–Backbone Interaction and Side Chain Steric Hindrance.
    Nano Lett.24(2024),1776–1783.
Copyright © Dong Wang's group, Department of Chemistry, Tsinghua University

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