基于基团贡献法和分子动力学预测聚间苯二甲酰对苯二胺的玻璃化转变温度

doi:10.7503/cjcu20180344

摘要/Abstract

摘要：

采用基团贡献法(GC)和分子动力学法(MD)模拟了聚间苯二甲酰间苯二胺纤维(MPDI)和聚对苯二甲酰对苯二胺(PPTA)的玻璃化转变温度, 并与实验值进行了对比. 结果表明, 使用基团贡献法和分子动力学法测得的MPDI和PPTA的玻璃化转变温度与实验值接近, 说明基团贡献法和分子动力学法可以用来预测芳香族聚酰胺的玻璃化转变温度. 在此基础上, 采用GC和MD预测了聚间苯二甲酰对苯二胺(PPIA)的玻璃化转变温度. 在MD模拟中, 对密度、比体积、回转半径和非键相互作用随温度的变化规律进行了分析. 结果表明, 自由体积理论能较好地解释PPIA的玻璃化转变现象, 其中非键相互作用随温度的变化是玻璃化转变的本质原因. PPIA的玻璃化转变温度介于MPDI和PPTA之间, 有望成为综合性能介于两者之间的另一种高性能聚酰胺.

关键词: 基团贡献法, 分子动力学模拟, 玻璃化转变温度, 聚间苯二甲酰对苯二胺

Abstract:

Aramid fibers mainly include wholly aromatic polyamide and heterocyclic aromatic polyamide, while the wholly aromatic polyamides(aramids) are considered to be high-performance organic materials due to their outstanding thermal and mechanical properties. Their high-performances arise from their aromatic structure and amide linkages. The better known commercial aramids, poly(p-phenylene terephthalamide)(PPTA) and poly(m-phenylene isophthalamide)(MPDI), are used in advanced technologies and have been transformed into high-strength and flame-retardant fibers and coatings, with applications in the aerospace and armament industry. Poly(p-phenylene isophthalamide)(PPIA), a new aromatic polyamide, has not yet been commercialized and there are few reports about its comprehensive performance until nowadays. In this paper, Group Contribution(GC) method and molecular dynamics(MD) simulation were used to simulate the glass transition temperatures(T_g) of MPDI and PPTA. Then analysis and comparisons of the glass transition temperatures by GC method and MD simulation with their experimental values are presented. The results show that the glass transition temperature measured by GC method and MD simulation is very close to the experimental value, and that the change of the density, specific volume, radius of gyration and energy along with temperature can cha-racterize the glass transition temperature. Then these two methods were exploited to simulate the T_g of PPIA. The change of the density, specific volume, radius of gyration and energy interactions along with temperature were analyzed in the MD simulation. The results show that the free volume theory can explain the glass transition phenomenon of PPIA, and the change of the non-bond energy interactions with temperature is the essential reason. These results indicates that PPIA has the potential to become another high performance polyamide with its T_g lying between those of both MPDI and PPTA. It is of great significance to emphasize on the synthesis of PPIA with sufficiently high molecular weight. In general, the group contribution method and molecular dynamics simulation can predict the T_g of aromatic polyamide sucessfully, and they can contribute to a deeper understanding on the glass transition phenomenon of aromatic polyamides and the molecular motion behind.

Key words: Group contribution method, Molecular dynamics simulation, Glass transition temperature, Poly(p-phenylene isophthalamide)

中图分类号:

O631

TrendMD:

吴红枚, 李惠婷, 李永成, 王宏青, 王孟. 基于基团贡献法和分子动力学预测聚间苯二甲酰对苯二胺的玻璃化转变温度. 高等学校化学学报, 2019, 40(1): 180.

WU Hongmei,LI Huiting,LI Yongcheng,WANG Hongqing,WANG Meng. Using Group Contribution Method and Molecular Dynamics to Predict the Glass Transition Temperature of Poly(p-phenylene isophthalamide)^†. Chem. J. Chinese Universities, 2019, 40(1): 180.

图/表 10

Fig.1 Chemical structures of MPDI and PPTA

Fig.2 Amorphous cell construction for a MPDI

Table 1 Tg of MPDI and PPTA from different methods

Method	T_g(MPDI)/K	T_g(PPTA)/K
Experiment value	545.2—548.2	600—618.2
GC	524.5	583.8
MD(Density-Temperature)	565.2	616.5
MD(Specific volume-Temperature)	566.9	616.3
MD(Radius of gyration-Temperature)	571.3	615.8
MD(Non-bond energy-Temperature)	567.4	617.4

Fig.3 Tg vs. degree of polymerization(DP) chart for PPIA at 300 K

Fig.4 Temperature(A) and energy fluctuation properties(B) vs. simulation time of PPIA(500 K, 200 ps NPT)

Fig.5 Density vs. temperature chart for an MD simulation of PPIA

Fig.6 Specific volume vs. temperature chart for an MD simulation of PPIA

Fig.7 Radius of gyration vs. temperature chart for an MD simulation of PPIA

Fig.8 Plots of energy components vs. temperature chart for an MD simulation of PPIA

Table 2 Tg of PPIA from different methods

Method	T_g/K
GC	554.4
MD(Density-Temperature)	593.6
MD(Specific volume-Temperature)	594.1
MD(Radius of gyration-Temperature)	592.2
MD(Non-bond energy-Temperature)	594.3

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