How do different curing agents affect the glass transition temperature (Tg) of the epoxy resin? Recently, the Institute of Polymer Research, School of Chemistry and Chemical Engineering, Hunan University proposed a molecular dynamics simulation method to study the glass transition temperature (Tg) of epoxy resin as a function of curing agent structure. They first established some simple molecular models of the cured epoxy resin, and then a molecular dynamics simulation (MD) was performed repeatedly. The data obtained from the simulation was used as the VT curve, and the Tg value was determined using the turning point on the curve. The simulated value is in good agreement with the calculated value. Although there is a large deviation from the experimental value, the influence of the curing agent on Tg can be obtained qualitatively by MD simulation. The proposed method has potential significance for the development of a curing agent with an enhanced curing effect.
Glass transition temperature (Tg) determines the temperature range for handling and applying epoxy-based thermosetting resin materials. It is helpful for understanding mechanical properties and other properties and is one of the important properties of these materials. Therefore, it is very useful to predict Tg before designing and synthesizing new materials with desired properties. There are many prediction methods for the glass transition temperature of cured epoxy resins. To sum up, there are empirical equations proposed by LENielsen and DiMarzio, and Porter's group contribution modeling method, Bicerano's connection index method, and other semi-empirical methods. The method of simulation is also an alternative method. Compared to the several methods mentioned above, detailed atomic simulations can provide information on mechanism or principle; it is very attractive in the long run. However, these simulations usually require expensive machine hours in order to obtain practical and useful results; they are not suitable for the study of cured epoxy systems.
The aim of this subject at Hunan University is to propose a simple and feasible method for predicting the glass transition temperature of epoxy resins cured by different curing agents. The method consists of two steps: building a molecular model and operating a molecular simulation. The method was tested by comparing the simulation results with the calculations or experimental results. The effect of the curing agent on the thermosetting resin of the corresponding cured epoxy resin was then examined. Practical epoxy systems typically include the following major components: epoxy resins, curing agents, pigments, solvents, and other additives. However, in this study, the epoxy system was limited to the resin component and the curing agent component, both of which are indispensable in practical applications. The selected resin component is a single bisphenol A diglycidyl ester (DGEBA), and the hardener components are di(4-aminophenyl)sulfone (DDS) and meta-diphenylamine (PDA), respectively. Commonly used materials in epoxy systems, and the corresponding cured epoxy resin experimental data available. Therefore, this work represents a preliminary study, and further studies will include more realistic models of other major components.
After establishing a molecular model of the curing epoxy system and molecular dynamics simulation of the glass transition temperature, the VT curve is simulated for the data set simulated by the two epoxy systems. The data points above and below the Tg are approximately linear, and the glass transition temperature The inflection point of the curve is determined, and the volume of the system changes drastically at the temperature corresponding to the point. The results are quite obvious from the calculated values ​​and the experimental values. The results of molecular dynamics simulations agree well with the QSPR predictions, but there is a large deviation from the experimental values. The results obtained by these two methods are quite different from the experimental results, which may be due to the fact that the cross-linking effect of the chemical structure cannot be ignored. A simple model using MD to simulate cured epoxy resin predicts its glass transition temperature. Some knowledge of the mechanism that causes glass transition is obtained in the simulation. This method can be used to predict the effect of different structural curing agents on Tg. When developing new epoxy curing agents, QSAR predictions can save time before simulation. In order to predict the absolute value of Tg, further study is needed.
Glass transition temperature (Tg) determines the temperature range for handling and applying epoxy-based thermosetting resin materials. It is helpful for understanding mechanical properties and other properties and is one of the important properties of these materials. Therefore, it is very useful to predict Tg before designing and synthesizing new materials with desired properties. There are many prediction methods for the glass transition temperature of cured epoxy resins. To sum up, there are empirical equations proposed by LENielsen and DiMarzio, and Porter's group contribution modeling method, Bicerano's connection index method, and other semi-empirical methods. The method of simulation is also an alternative method. Compared to the several methods mentioned above, detailed atomic simulations can provide information on mechanism or principle; it is very attractive in the long run. However, these simulations usually require expensive machine hours in order to obtain practical and useful results; they are not suitable for the study of cured epoxy systems.
The aim of this subject at Hunan University is to propose a simple and feasible method for predicting the glass transition temperature of epoxy resins cured by different curing agents. The method consists of two steps: building a molecular model and operating a molecular simulation. The method was tested by comparing the simulation results with the calculations or experimental results. The effect of the curing agent on the thermosetting resin of the corresponding cured epoxy resin was then examined. Practical epoxy systems typically include the following major components: epoxy resins, curing agents, pigments, solvents, and other additives. However, in this study, the epoxy system was limited to the resin component and the curing agent component, both of which are indispensable in practical applications. The selected resin component is a single bisphenol A diglycidyl ester (DGEBA), and the hardener components are di(4-aminophenyl)sulfone (DDS) and meta-diphenylamine (PDA), respectively. Commonly used materials in epoxy systems, and the corresponding cured epoxy resin experimental data available. Therefore, this work represents a preliminary study, and further studies will include more realistic models of other major components.
After establishing a molecular model of the curing epoxy system and molecular dynamics simulation of the glass transition temperature, the VT curve is simulated for the data set simulated by the two epoxy systems. The data points above and below the Tg are approximately linear, and the glass transition temperature The inflection point of the curve is determined, and the volume of the system changes drastically at the temperature corresponding to the point. The results are quite obvious from the calculated values ​​and the experimental values. The results of molecular dynamics simulations agree well with the QSPR predictions, but there is a large deviation from the experimental values. The results obtained by these two methods are quite different from the experimental results, which may be due to the fact that the cross-linking effect of the chemical structure cannot be ignored. A simple model using MD to simulate cured epoxy resin predicts its glass transition temperature. Some knowledge of the mechanism that causes glass transition is obtained in the simulation. This method can be used to predict the effect of different structural curing agents on Tg. When developing new epoxy curing agents, QSAR predictions can save time before simulation. In order to predict the absolute value of Tg, further study is needed.
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