Application Process of Coating Agent and the Coating Effect Evaluation Based on Molecular Dynamics

涂层 分子动力学 相容性(地球化学) 材料科学 聚合物 聚四氟乙烯 化学工程 双层 吸附 分子 复合材料 化学 物理化学 有机化学 计算化学 生物化学 工程类
作者
Dihua Ouyang,Langlang Zhang,Ruijin Mao,Xiaowen Qin,Weiqiang Pang
出处
期刊:Langmuir [American Chemical Society]
卷期号:39 (9): 3411-3419 被引量:7
标识
DOI:10.1021/acs.langmuir.2c02954
摘要

In the field of energy-containing materials, the modification of nanoaluminum powders has been widely studied. However, in modified experimental design, the lack of theoretical prediction usually leads to long experimental cycles and high resource consumption. To this end, this study evaluated the process and effect of dopamine (PDA)- and polytetrafluoroethylene (PTFE)-modified nanoaluminum powders based on molecular dynamics (MD). Through the calculation of the coating stability, compatibility, and oxygen barrier performance of the modified material, the modification process and effect were explored from a microscopic point of view. The results showed that the adsorption of PDA on the nanoaluminum was the most stable, and the binding energy was 463.03 kcal·mol-1. PDA and PTFE with different ratios are compatible systems at 350 K, and the best compatibility ratio is 10 wt % PTFE/90 wt % PDA. The 90 wt % PTFE/10 wt % PDA bilayer model has the best barrier performance for oxygen molecules in a wide temperature range. The calculated results of the coating stability agree with the experiments, and it is pointed out that it is feasible to evaluate the modification effect in advance by MD simulation. In addition, the simulation results concluded that the double-layered PDA and PTFE have better oxygen barrier properties. Compatibility can be used only to determine whether phase separation occurs between mixtures and is not directly related to the dense mixing of polymers and the barrier properties of small gas molecules. The simulation provided in this article can predict the experimental results and provide theoretical guidance for coating modification experiments in order to reduce unnecessary experiments, shorten the experimental cycle, and reduce costs.
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