# Advances in Toughening Modification Methods for Epoxy Resins: A Comprehensive Review
## 7 Computational and Intelligent Method-Driven Development of Epoxy Resins
### Computational Modeling Techniques  
Current advancements in the development and optimization of enhanced epoxy resin systems are increasingly benefiting from computational modeling techniques. Molecular dynamics (MD) simulations and finite-element-based multi-scale approaches have provided critical insights into phase behavior [120; 121], curing kinetics [122; 123], and fracture mechanics across multiple length and time scales [124; 125; 126].  
[PERSON] et al. [127] conducted a comprehensive investigation into the thermodynamic and mechanical properties of various epoxy-amine resins (as illustrated in Figure 8) using molecular dynamics (MD) simulations with the CHARMM force field. A multi-step crosslinking algorithm was first developed to simulate the resin curing process, followed by calculations of key material properties, including density and glass transition temperature. The results demonstrated that the simulation methodology effectively predicted these properties, with mean absolute deviations ranging from 2% to 12%. Furthermore, systematic analysis revealed the influence of molecular weight and crosslinking density on resin performance: increasing molecular weight and crosslinking ensured material density, while inversely affecting glass transition temperature and Young's modulus. These findings not only validate the robustness of the adopted computational framework but also provide critical theoretical guidance for the rational design of high-performance epoxy-amine resin systems.  
[PERSON] et al. [128] investigated the effects of uniform dispersion versus agglomeration of carbon nanotubes (CNTs) on the tensile mechanical properties of CNT-reinforced epoxy resin (EP) nanocomposites through finite element simulation analysis. The results demonstrated that, for composites with low CNT mass fractions (0.5 wt%), simulations assuming uniform filler distribution accurately predicted tensile strength and elastic modulus. Conversely, for composites with higher CNT mass fractions (1.5 wt%), the modified analysis method incorporating CNT agglomeration effects achieved superior precision in mechanical property predictions, exhibiting enhanced accuracy and reliability.  
[PERSON] et al. [129] employed molecular dynamics (MD) simulations to investigate the thermodynamic and mechanical properties of epoxy networks derived from the reaction of DGEBA with two curing agents, TETA and DETDA, at varying crosslinking densities. The study revealed that, for the DGEBA/TETA system, a crosslinking density of 62.5% yielded the closest agreement between the glass transition temperature (Tg) calculated from density-temperature curves and experimental values, with Tg ranging from 385-395 \({}^{\circ}\)C. Furthermore, systematic analyses were conducted on the temperature-dependent variations in the coefficient of thermal expansion (CTE), elastic modulus, Pois  
Figure 8: Molecular representation of the epoxy resins (**a**–**e**) and of the hardeners (**f**–**m**). Carbon, oxygen, nitrogen, and hydrogen atoms are shown in gray, red, blue, and white, respectively. (**n**,**o**) Snapshots of crosslinked systems, where orange and gray phases represent respectively the epoxy resins and hardeners [127].  
son's ratio, and density across different crosslinking levels. Comparative evaluation of the DGEBA/TETA and DGEBA/DETDA systems demonstrated that increasing crosslinking density enhanced Tg and mechanical performance, though these improvements plateaued at higher crosslinking densities. Overall, the DGEBA/TETA system exhibited superior mechanical properties, while the DGEBA/DETDA system consistently achieved higher Tg values under all tested conditions.