Soft matter is a general term for condensed matter which is neither a simple liquid nor a crystal. Typical soft matter include colloidal solutions, aerosols, polymers, emulsions, glass, gels, liquid crystals, biopolymers and so on. The physical properties of soft matter are very sensitive to its molecular structure and microscopic interaction details. Generally, analytical methods such as continuous medium hypothesis or mean field approximation are limited to study soft matter theory, while molecular simulation methods which can accurately describe molecular structure and interaction are particularly important. In many cases, soft matter usually has mesoscopic time and space characteristic scale, which often exceeds the space-time range of conventional molecular simulation, so it is necessary to improve and expand conventional molecular simulation methods. Our research group has carried out a series of research on molecular simulation theory, algorithm and data analysis method. The specific research directions are as follows 
1.Trajectory Mapping  
2.Re-weighted ensemble dynamics
3.Generalized Canonical Ensemble
 

Biophysics is an interdisciplinary research field of physics and life science. Its ultimate goal is to explain all kinds of life phenomena from the physical level. From the physical point of view, life is the most complex and exquisite non-equilibrium open system. Through the complex internal mechanism, it continuously exchanges material, energy and information with the environment, and thus achieves the purpose of self maintenance and self replication. The basic material units that constitute these internal mechanisms are DNA, RNA and protein, which are biological macromolecules in cells. Through the complex and specific interaction, they complete the fine recognition, so as to carry out specific regulation on various physical and chemical processes in the cell, and make the cell display subtle and changeable life activities (such as cell division, movement, expression of genetic information). Studying these molecular machines and their interactions is an important part of biophysics. With the rapid development of single molecule Biophysical Technology in the past 20 years, people have been able to directly study single molecular machines, and basic physical problems closely related to life processes have been proposed. For example, what is the physical mechanism of self-assembly or self-organization of molecular machines? How do they work stably in the environment of thermal fluctuations? How to use chemical energy to generate mechanical motion or information? What is the energy efficiency? What are the structural design and optimization principles of molecular machines? In addition, how can various chemical reaction modules (such as gene regulatory modules) work together in a thermal fluctuation environment? , etc. These questions all point to a core, that is, how can a large number of unreliable components (including severe thermal noise) form a generally stable and orderly life system? This poses a great challenge to theoretical physics, especially statistical physics. At present, there are no answers to these problems, and long-term close cooperation among biology, physics, chemistry, mathematics, computer science, engineering and other disciplines is needed. Our group has carried out theoretical research around the above problems, combined with stochastic process theory and molecular dynamics and other computational simulation methods, focusing on the structure, motion mechanism and energetics of biological molecular machines such as DNA and protein, and also related non-equilibrium statistical physics.
 1.Kinesin
 2.DNA
 3.DNA Polymerase
 

Ice formation is the most common phenomenon in nature. In many fields such as climate change, life science, aviation industry and so on, ice water phase transition is an important research topic. In the real freezing process of nature, there are few bulk pure water systems freezing. Pure water can keep liquid at minus 40 ℃ without freezing. Most of the freezing phenomena occur when there are other impurities in the water or contact with the interface, which is called heterogeneous nucleation process. Many factors have great influence on nucleation mechanism and nucleation rate, such as surface morphology, hydrophilic and hydrophobic properties, local electric field, surface roughness, ion adsorption, hydrogen bond and so on. These factors are often interwoven, so far, people can not fully explain the mechanism of water ice formation or control the formation of ice. Even the most advanced experimental techniques such as cryo TEM, X-ray laser spectroscopy and so on, their temporal and spatial resolution is not enough to detect the atomic scale details in the process of liquid-solid phase transition. Due to the development of molecular dynamics simulation technology in recent years, more and more people begin to use molecular dynamics simulation to study liquid-solid phase transition. In recent years, our research group has been devoted to the study of water icing mechanism by using molecular dynamics simulation method, and to explore the means to control ice formation.
The representative works in recent years are as follows:
1. Guoying Bai, Dong Gao, Zhang Liu, Xin Zhou*, Jianjun Wang*, Probing the critical nucleus size for ice formation with graphene oxide nanosheets, Nature 576.7787(2019):437-441.
2. Mingzhe Shao, Chuanbiao Zhang, Chonghai Qi, Chunlei Wang, Jianjun Wang, Fangfu Ye and Xin Zhou*, Hydrogen polarity of interfacial water regulates heterogeneous ice nucleation, Phys. Chem. Chem. Phys. 22，258-264 (2020).
3. Han Xue, Youhua Lu, Hongya Geng, Bin Dong, Shuwang Wu, Qingrui Fan, Zhen Zhang, Xiaojun Li, Xin Zhou*, Jianjun Wang*, Hydroxyl Groups on the Graphene Surfaces Facilitate Ice Nucleation, J Phys. Chem. Lett., 10, 2458-2462 (2019).
4. Qi Cheng, Shenglin Jin*, Kai Liu, Han Xue, Bingchen Huo, Xin Zhou*, and Jianjun Wang*, Modifying Surfaces with the Primary and Secondary Faces of Cyclodextrins To Achieve a Distinct Anti-icing Capability,Langmuir,  35 (15), 5176–5182 (2019).
5. Zhen Dong, Jianjun Wang, and Xin Zhou*, Effect of antifreeze protein on heterogeneous ice nucleation based on a 2D random field Ising model, Phys. Rev. E 95，052140 (2017).