Smart Materials Design Research Group

Representative Publications

[1] Wenhui Duan and Gang Zhang, Thermal Transport in Nanomaterials, Science Press, 2017.
[2] Gang Zhang and Wenhui Duan, “Novel Physical Effects in Thermal Transport of Nanomaterials,” Physics, 49(10), 668–678 (2020).
[3] “Size-Dependent Phononic Thermal Transport in Low-dimensional Nanomaterials,” Physics Reports, 860, 1–26 (2020).
[4] “Anomalous strain effect on the thermal conductivity of low-buckled two-dimensional silicene,” National Science Review, 8(9), nwaa220.
[5] “Phononic Weyl pair, phononic Weyl complex, phononic real Chern insulator state, and phononic corner modes in 2D Kekulé-order graphene,” Applied Physics Reviews, 10, 031416 (2023).

2. Dynamically Reversible Thermal Regulation under Multiphysics Coupling

Reversible dynamic thermal regulation has broad application prospects in integrated-circuit thermal management, the new energy industry, aerospace, and related fields. The group has systematically investigated the mechanisms and performance of thermal switches based on a wide range of solid materials, including ferroelectric materials, ferromagnetic materials, nanomaterials and nanostructures, polymers, and phase-change materials. Multiple control strategies and potential mechanisms for enhancing thermal-switch performance have also been explored.

[1] “Actively and reversibly controlling thermal conductivity in solid materials,” Physics Reports, 1058, 1–32 (2024).
[2] “Spin-gapless semiconductors for future spintronics and electronics,” Physics Reports, 888, 1–57 (2020).
[3] “Giant Thermal Switching in Ferromagnetic VSe2 with Programmable Switching Temperature,” Nanoscale Horizons, 8, 202–210 (2023).
[4] “Manipulating interfacial thermal conduction of 2D Janus heterostructure via a thermo-mechanical coupling,” Advanced Functional Materials, 32(18), 2110846 (2022).
[5] “Thermo-mechanical correlation in two-dimensional materials,” Nanoscale, 13, 1425 (2021).

3. Artificial Intelligence-Accelerated Materials Design and Development

Thermoelectric materials provide important solid-state solutions for waste-heat recovery and cooling. Over the past decades, improving thermoelectric performance has remained a central challenge in the field, typically requiring the coordinated optimization of multiple interrelated physical parameters. In recent years, the group has introduced artificial intelligence into thermoelectric materials research and improved thermoelectric conversion efficiency through the optimization of key physical parameters across multiple material systems.

In 2022, the group initiated and hosted the International Conference on Intelligent Materials Design, centered on the application of artificial intelligence and deep learning to the prediction of new materials and material properties. Three editions of the conference series have been successfully held to date, bringing together hundreds of experts and scholars from China and abroad and continuously promoting international academic exchange and collaboration in this frontier interdisciplinary field.

[1] “Machine Learning Approaches for Thermoelectric Materials Research,” Advanced Functional Materials, 30, 1906041 (2020).
[2] “Material Platforms for Defect Qubits and Single Photon Emitters,” Applied Physics Reviews, 7, 031308 (2020).
[3] Artificial Intelligence for Materials Science, Tian Wang, Yuan Cheng, Gang Zhang, Springer, 2021.

Patents and Intellectual Property

[1] Preparation Method of Surface-State Nano Silver Oxide for Low-Temperature Solid-State Interconnection Technology, ZL 2022 1 0806826.1 (Invention Patent)
[2] Interconnection Method and Interconnection Structure of Copper/Silver-Based Solid-Solution Composite Bumps, ZL 2024 1 1188988.9 (Invention Patent)
[3] Micro-Interconnection System Based on an Ultrasonic-Laser Coupling Mechanism, ZL 2024 1 1536676.2 (Invention Patent)