Metaheuristic ab initio optimum search for doping effects in nanocarbons

Kenji Tsuruta, Keiichi Mitani, Md Abdullah Al Asad, Yuta Nishina, Kazuma Gotoh, Atsushi Ishikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We have developed a combined approach of metaheuristic optimization algorithms (MOA), such as the genetic algorithm, with an ab-initio materials simulation engine. Concurrent run of the ab-initio calculations with each different parameter set selected by the MOA searches the optimum condition within a given input-parameter space. Using this methodology, the optimum dopant and its position/structure at a graphene edge are found to be a multiple N-atoms doping at graphitic sites, which predicts to lead to better charging/discharging performance when it is used as an anode material of Li-ion battery.

Original languageEnglish
Title of host publicationTHERMEC 2018
EditorsR. Shabadi, Tara Chandra, M. Jeandin, Mihail Ionescu, C. Richard
PublisherTrans Tech Publications Ltd
Pages2356-2359
Number of pages4
ISBN (Print)9783035712087
DOIs
Publication statusPublished - Jan 1 2018
Event10th International Conference on Processing and Manufacturing of Advanced Materials, 2018 - Paris, France
Duration: Jul 9 2018Jul 13 2018

Publication series

NameMaterials Science Forum
Volume941 MSF
ISSN (Print)0255-5476

Conference

Conference10th International Conference on Processing and Manufacturing of Advanced Materials, 2018
CountryFrance
CityParis
Period7/9/187/13/18

Fingerprint

Doping (additives)
optimization
Graphite
Set theory
genetic algorithms
Graphene
charging
electric batteries
engines
graphene
Anodes
anodes
Genetic algorithms
methodology
Engines
Atoms
atoms
ions
simulation
Lithium-ion batteries

Keywords

  • Ab-initio simulation
  • Doping effect
  • Genetic algorithm
  • Lithium-ion battery
  • Nano-carbon

ASJC Scopus subject areas

  • Materials Science(all)
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering

Cite this

Tsuruta, K., Mitani, K., Asad, M. A. A., Nishina, Y., Gotoh, K., & Ishikawa, A. (2018). Metaheuristic ab initio optimum search for doping effects in nanocarbons. In R. Shabadi, T. Chandra, M. Jeandin, M. Ionescu, & C. Richard (Eds.), THERMEC 2018 (pp. 2356-2359). (Materials Science Forum; Vol. 941 MSF). Trans Tech Publications Ltd. https://doi.org/10.4028/www.scientific.net/MSF.941.2356

Metaheuristic ab initio optimum search for doping effects in nanocarbons. / Tsuruta, Kenji; Mitani, Keiichi; Asad, Md Abdullah Al; Nishina, Yuta; Gotoh, Kazuma; Ishikawa, Atsushi.

THERMEC 2018. ed. / R. Shabadi; Tara Chandra; M. Jeandin; Mihail Ionescu; C. Richard. Trans Tech Publications Ltd, 2018. p. 2356-2359 (Materials Science Forum; Vol. 941 MSF).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Tsuruta, K, Mitani, K, Asad, MAA, Nishina, Y, Gotoh, K & Ishikawa, A 2018, Metaheuristic ab initio optimum search for doping effects in nanocarbons. in R Shabadi, T Chandra, M Jeandin, M Ionescu & C Richard (eds), THERMEC 2018. Materials Science Forum, vol. 941 MSF, Trans Tech Publications Ltd, pp. 2356-2359, 10th International Conference on Processing and Manufacturing of Advanced Materials, 2018, Paris, France, 7/9/18. https://doi.org/10.4028/www.scientific.net/MSF.941.2356
Tsuruta K, Mitani K, Asad MAA, Nishina Y, Gotoh K, Ishikawa A. Metaheuristic ab initio optimum search for doping effects in nanocarbons. In Shabadi R, Chandra T, Jeandin M, Ionescu M, Richard C, editors, THERMEC 2018. Trans Tech Publications Ltd. 2018. p. 2356-2359. (Materials Science Forum). https://doi.org/10.4028/www.scientific.net/MSF.941.2356
Tsuruta, Kenji ; Mitani, Keiichi ; Asad, Md Abdullah Al ; Nishina, Yuta ; Gotoh, Kazuma ; Ishikawa, Atsushi. / Metaheuristic ab initio optimum search for doping effects in nanocarbons. THERMEC 2018. editor / R. Shabadi ; Tara Chandra ; M. Jeandin ; Mihail Ionescu ; C. Richard. Trans Tech Publications Ltd, 2018. pp. 2356-2359 (Materials Science Forum).
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