2022
DOI: 10.1016/j.polymer.2022.124570
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Exploring polymer precursors for low-cost high performance carbon fiber: A materials genome approach to finding polyacrylonitrile-co-poly(N-vinyl formamide)

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Cited by 10 publications
(4 citation statements)
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“…They found that when compared with the conventional mechanism, incorporating a P­(AN- co -IA) copolymer as a catalyst largely reduced the energy barrier of the initial cyclization to 22.68 kcal/mol, which corresponded to the experimental result . Liu and Zhou et al applied a similar approach to compare the energy barriers for the cyclization reaction using various copolymers. , In addition, other simulation methods such as ab initio molecular dynamics (AIMD) can be a better choice to explore and verify the reaction mechanism, because classical molecular dynamics often ignore the changes in chemical bonds and the charge transfer between reactants. With the method of simulation calculation, we can more conveniently verify the feasibility of the research.…”
Section: Introductionmentioning
confidence: 76%
See 1 more Smart Citation
“…They found that when compared with the conventional mechanism, incorporating a P­(AN- co -IA) copolymer as a catalyst largely reduced the energy barrier of the initial cyclization to 22.68 kcal/mol, which corresponded to the experimental result . Liu and Zhou et al applied a similar approach to compare the energy barriers for the cyclization reaction using various copolymers. , In addition, other simulation methods such as ab initio molecular dynamics (AIMD) can be a better choice to explore and verify the reaction mechanism, because classical molecular dynamics often ignore the changes in chemical bonds and the charge transfer between reactants. With the method of simulation calculation, we can more conveniently verify the feasibility of the research.…”
Section: Introductionmentioning
confidence: 76%
“…22 Liu and Zhou et al applied a similar approach to compare the energy barriers for the cyclization reaction using various copolymers. 23,24 In addition, other simulation methods such as ab initio molecular dynamics (AIMD) can be a better choice to explore and verify the reaction mechanism, because classical molecular dynamics often ignore the changes in chemical bonds and the charge transfer between reactants. 25−27 With the method of simulation calculation, we can more conveniently verify the feasibility of the research.…”
Section: Introductionmentioning
confidence: 99%
“…21 In contrast, P(AN-co-AMPS) copolymers have improved their thermal stability due to the introduction of AMPS, where the cyclization reaction of the copolymers is initiated by both free radical and ionic mechanisms, effectively avoiding the violent exothermic behavior of the cyclization process and forming more ladder-like ring structures during the thermal stabilization process at 200-300 C, which enables them to withstand higher temperature treatments. 31 TGA analysis indicated that the introduction of AMPS was beneficial in improving the thermal stability of the copolymers and that as the AMPS content increased, more heat-resistant ladder-like ring structures were produced and the thermal stability of the copolymers increased accordingly, which facilitated further carbonization. As shown in Figure 8, the P(AN-co-MA) copolymer showed the most severe weight loss, with a carbon residue rate of 41.4% at 800 C. The carbon residue rate of the remaining P(AN-co-MA-co-AMPS) copolymers were all higher, with the best thermal stability of the copolymer achieved when the mass ratio of AN:MA:AMPS is 97.5:1.5:1, the residual carbon rate reached the highest (58.1%).…”
Section: Tga Studiesmentioning
confidence: 99%
“…The establishment of the MGI has become a turning point in data-driven materials science, and the database has gradually evolved into a data center that provides materials data and fundamental analysis services. As the fourth paradigm of data-driven scientific development, materials genetic engineering combines high-throughput computing and design, high-throughput preparation, high-throughput characterization, material databases, and artificial intelligence, significantly shortening the material research and development cycle and reducing the research and development cost to rapidly develop new materials and meet the growing performance requirements [27][28][29][30][31][32][33][34][35][36][37][38]. The objective and purpose of MGI include pioneering a fresh approach to research and development (R&D) and a novel technological framework that seamlessly integrates and fosters collaborative innovation across the spectrum of materials R&D, manufacturing, and application.…”
Section: Introductionmentioning
confidence: 99%