Dr. G.H. Chen　　　陳冠華博士

B.Sc., Fudan;
Ph.D. Caltech

Room 601
Chong Yuet Ming Chemistry Building
The University of Hong Kong
Pokfulam Road
Hong Kong

Localized-density-matrix (LDM) method is developed to calculate electronic dynamics of very large molecular systems containing up to tens of thousand atoms. It has been implemented at semiempirical and first-principles levels. Electronic structures of nanostructures and proteins are under investigation. Inclusion of nuclei is expected to yield important information of these systems.

Quantum Chemistry Simulation of Open Systems and Application to Nanoelectronics

Traditionally Quantum Chemistry deals the closed systems where energy and number of particles are fixed. With the development of materials science, nanotechnology and quantum computing, the needs for the accurate calculations of open systems are increasingly acute. A new formalism based on the dynamics of reduced single-electron density matrix is being developed to simulate open systems where energy and matter are exchanged with the environments. The new formalism is applied to examine the relaxation of complex molecular systems and evaluate the electric responses of molecular devices.

Combining Artificial Intelligence and Quantum Chemistry

We have combined Neural Networks and density functional theory, and greatly improved the accuracy of first-principles calculations. Neural Networks has been employed to construct a new type of exchange-correlation functional for density functional theory. Introduction of artificial intelligence to quantum mechanical calculations is expected to have profound impact on computational science.

Computer-Aided Drug Design

We have developed a computational procedure to optimize the existing drug leads. A neural network method is used to determine QSAR of the existing drug leads, from which new leads are predicted. The new leads are further selected via conventional docking procedure. The resulting leads are subsequently tested and confirmed via quantum chemistry method, QM/MM.

1. L.H. Hu, G.H. Chen, R.M.W. Chau, “A neural networks-based drug discovery approach and its application for designing aldose reductase inhibitors”, Journal of Molecular Graphics and Modelling, 2006, 24, 244.
2. C.C. Ma, Y. Zhao, J.C.Y. Yam, G.H. Chen, Q. Jiang, “A tribological study of double-walled and triple-walled carbon nanotube oscillators”, Nanotechnology, 2005, 16, 1253.
3. Q. Wang, T. Hu, G.H. Chen, Q. Jiang, “Bending Instability Characteristics of Double-Walled Carbon Nanotubes”, Phys. Rev. B, 2005, 71, 045403.
4. J.C.Y. Yam, C.C. Ma, X.J. Wang, G.H. Chen “Electronic Structure and Charge Distribution of Potassium-Iodide-Intercalated Single-Walled Carbon Nanotubes”, Appl. Phys. Lett., 2004, 85, 4484.
5. X. Zheng, G.H. Chen, Z.B. Li, S.Z. Deng, N.S. Xu, “Quantum mechanical investigation of field emission mechanism of a micrometer-long single-walled carbon nanotube”, Phys. Rev. Lett., 2004, 92, 106803.
6. L.H. Hu, X.J. Wang, L.H. Wong, G.H. Chen, “Combined first-principles calculation and neural-network correction approach for heat of formation”, J. Chem. Phys.(Commun.), 2003, 119, 11501.
7. J.C.Y. Yam, S. Yokojima. G.H. Chen, “Linear-scaling time-dependent density functional theory”, Phys. Rev. B, 2003, 68, 153105.
8. Y. Zhao, C.C. Ma, G.H. Chen, Q. Jiang, “Energy dissipation mechanisms in carbon nanotube oscillators”, Phys. Rev. Lett., 2003, 91, 175504.