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首页> 外文期刊>Materials and Manufacturing Processes >Genetic Algorithms Applied to Li~+ Ions Contained in Carbon Nanotubes: An Investigation Using Particle Swarm Optimization and Differential Evolution Along with Molecular Dynamics
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Genetic Algorithms Applied to Li~+ Ions Contained in Carbon Nanotubes: An Investigation Using Particle Swarm Optimization and Differential Evolution Along with Molecular Dynamics

机译：遗传算法应用于碳纳米管中所含的Li〜+离子：使用粒子群算法和差分演化以及分子动力学的研究

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摘要

Empirical potentials based upon two and three body interactions were applied to the Li~+-C system, assuming the Li~+ ions to be distributed inside high-symmetry, single walled carbon nanotubes of different chirality. Structural optimizations for various assemblages were conducted using evolutionary and genetic algorithms, where differential evolution and particle swarm optimization techniques worked satisfactorily. The results were compared with the outcome of some rigorous molecular dynamics simulations. The potential for using the carbon nanotubes in the negative electrode of lithium ion batteries was also critically examined.
机译：假设Li〜+离子分布在具有不同手性的高对称，单壁碳纳米管内，则将基于两种和三种体相互作用的经验电势应用于Li〜+ -C系统。使用进化和遗传算法对各种组合进行结构优化，其中差分进化和粒子群优化技术可以令人满意地工作。将结果与一些严格的分子动力学模拟的结果进行了比较。还严格检查了在锂离子电池负极中使用碳纳米管的潜力。

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