探索計算化學的最新發展： 應用軟體 Q-Chem 新功能訓練課程
Expanding the frontier: a workshop on the use and new features for Q-Chem
Computational chemistry has becoming increasingly important in chemistry in chemistry. Given the number of computational chemists in Taiwan, and the increasing number of experimental groups that start doing computation along with their experimental works, it will become more and more important to connect users and developers in order to perform cutting-edge work. Q-Chem is a quantum chemistry software package that has two developer groups in Taiwan. Therefore, we feel it is important to hold a Q-Chem workshop, hoping to increase the communication or even collaboration between developers and users in the area of quantum chemistry computation, and eventually benefit our chemistry research community.
The workshop will highlight some of the features in the new Q-Chem 4.0 software package. Professors Wanzhen Liang (Department of Chemical Physics, University of Science and Technology of China), Jeng-Da Chai (Department of Physics, National Taiwan University) and Chao-Ping Hsu (Institute of Chemistry, Academia Sinica) will give short lectures on the unique functionalities they have developed followed by application examples. Dr. Jing Kong (CEO, Q-Chem Inc.) and Prof. Jianguo Yu (College of Chemistry, Beijing Normal University) will lead a hand-on workshop that allows uses to run and test for the new functions.
Q-Chem 4.0 新增功能，請見下方
Q-Chem 4.0’s significant new functionalities includes
* TD-DFT analytic gradient and Hessian for excited-state structure
* IRC searches for mapping complicated potential energy surfaces;
* Range-separated and dispersion-corrected DFT functionals;
* Faster algorithms for DFT, HF and coupled-cluster calculations;
* More choices for excited-state, solvation and charge-transfer calculations;
* Effective Fragment Potential and QM/MM for treating large systems;
* Maximum Overlap Method for excited-state calculations of large systems;
* Intracules for analysis of two-electron properties;
* Shared-memory for multicore systems and implementations for GPUs;
as well as many other areas.