摘要
软物质科学是物理、化学和材料科学领域的重要分支.但软物质系统因其多尺度结构和丰富的动态行为,给研究带来了巨大挑战.而场论模拟方法在应对这些挑战中显示出独特优势,其通过引入连续的场变量,为描述和处理软物质系统中的复杂相互作用提供了一个更加高效和宏观的视角.本文首先介绍了场论模拟方法的基本原理并阐述了它们在软物质物理上的应用,如蛋白质的HP模型结构预测、高分子链的静态拓扑缠结、化学反应或光反应驱动微观相分离等,接着探讨了深度学习等现代计算技术在软物质研究中的应用.最后展望了软物质研究领域的未来发展趋势,指出场论方法在软物质物理研究领域仍具有巨大优势.
Abstract
Soft matter science is an important branch in the fields of physics,chemistry,and material science.However,the complexity of soft matter systems,especially their multi-scale structures and rich dynamic behaviors,poses significant challenges to researchers.To address these challenges,simulation methods based on field theory demonstrate unique advantages in simulation techniques.By introducing continuous field variables,they provide a more efficient and macroscopic perspective for describing and handling complex interactions in soft matter systems.This article first introduces the basic principles of polymer field theory and elaborates on their appli-cations in soft matter physics,such as the structure prediction of protein HP models,the static topological entanglement problems of polymer chains,chemical reaction/light induced microphase separation,etc.It then explores the application of modern computational technologies like deep learning in soft matter research,and finally looks forward to the future research trends and developments in the field of soft matter,pointing out that field theory remains a powerful tool for soft matter study.
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