团簇科学是一门新的交叉科学，对团簇的研究已经成为物理和化学两大学科之间的一个新的生长点。团簇实验往往只能给出谱图或尺寸信息，而确定结构需要结合第一性原理计算。如何预测出团簇真实构型是问题的关键，这是一个典型的NP难题。但该领域全局优化算法的研究者多为数学和计算机背景，缺乏第一性原理计算基础，多针对模型体系。与此同时，第一性原理结构预测计算量需求巨大，却多采用常用但低效的全局优化方法，极其浪费计算资源。因此，基于我们在团簇结构预测算法领域的研究基础和理论化学的研究背景，本项目致力于建立"高效"的第一性原理团簇结构预测方法，以解决该领域目前在方法研究和实际应用方面严重脱节的问题。由于其独特的结构性质，在碳团簇之后，硼团簇又一次引起了广泛关注。硼团簇电子结构具有多样性，对其结构预测极具挑战性。基于所发展的方法，本项目将系统地优化不同尺寸下硼团簇的结构，揭示其规律。

Cluster science is a new inter-discipline, which now is a increasing research field between physics and chemistry. At the most cases, experiments on clusters can give only the information of spectrum or size, and first principle calculations are demanded for determination of the structures. Thus, the key is the prediction of the real structure, which is a typical NP-hard problem. However, developers in structural global optimization method are often in mathematical or computational background without many experiences in first principle calculations, in which what they are interested is just the model system. On the other hand, first principle structural prediction is very time consuming, and many low-efficiency global optimization methods are adopted by the theoretical groups. We have good research backgrounds in both global optimization and first principle calculations, so the main goal of this project is to develop a highly-efficient first principle structure prediction method. Because of its novel bonding features, B clusters become another active research area after C clusters. Structure prediction of boron clusters is a very challenging problem due to its multiple-reference character in electronic structure. We will carry out systematic study on B clusters using the developed method to discover the structural regulation with size.