摘要： 【目的/意义】自分层涂料可破解传统多涂层涂装体系的诸多难题，是涂料领域绿色智能化转型的关键方向。梯度分布是其结构和功能的核心，建立自分层涂料梯度分布与性能的科学评价体系，对研发及工程应用至关重要。【分析/评论/进展】本文在梳理梯度分布形成机制及影响因素的基础上，分析了涵盖静态（如扫描电镜-能谱联用、纳米压痕）与动态（如原位 X射线衍射、电化学阻抗谱）检测的表征体系，阐明了各方法特性，探讨了深度剖析及表征-模拟联用思路，分析了当前表征与模拟手段的瓶颈并提出发展方向。【结论/展望】系统构建自分层涂料梯度分布表征及性能评价体系，对自分层涂料精准研发、质量管控及工程化转化具有重要意义，未来可依托高分辨率原位监测与智能技术提升体系精准性。
关键词:
自分层涂料,
梯度分布,
表征方法,
原位监测,
计算机模拟
Abstract: [Objective/Significance] Self-stratifying coatings can solve many problems of traditional multi-coating systems and they are the key direction for the green and intelligenttransformation in the coating field. Gradient distribution is the core of its structure and function, andaccurate characterization and systematic evaluation are crucial for research and development as well asengineering applications. This paper aims to establish a scientific evaluation system for the gradientdistribution and performance of self-stratifying coatings, providing support for technical research anddevelopment, quality control and scenario adaptation. [Analysis/Discussion/Progress] Based on sortingout the formation mechanism and influencing factors of gradient distribution, a characterization systemcovering static detection (e. g., SEM-EDS, nanoindentation) and dynamic detection (e. g., in-situ XRD,electrochemical impedance spectroscopy) was analyzed. The characteristics of each method were clarified,the ideas of in-depth analysis and characterization-simulation combination were discussed, and the current characterization and simulation bottlenecks were analyzed and the development directions wereproposed. [Conclusion/Prospect] The evaluation system constructed in this study provides a scientificbasis for the precise research and development and quality control of self-stratifying coatings, and hasimportant practical significance for promoting the engineering transformation of this technology. In thefuture, the accuracy of the system can be further improved by relying on high-resolution in-situ monitoring and intelligent technologies.
Key words:
self-stratifying coatings,
gradient distribution,
characterization methods,
in-situ monitoring,
computer simulation
中图分类号:
姜立萍, 牛腾, 魏惠荣, 王欣怡, 杨皓丞. 自分层涂料梯度分布表征方法与性能评价体系研究进展[J]. 涂料工业, 2026, 56(10): 83-90.
Jiang Liping, Niu Teng, Wei Huirong, Wang Xinyi, Yang Haocheng. Research on gradient distribution characterization and performance evaluation system for self-stratifying coatings[J]. Paint & Coatings Industry, 2026, 56(10): 83-90.