Identifying chemical factors affecting reaction kinetics in Li-air battery via ab initio calculations and machine learning

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dc.contributor.authorWang, APen_AU
dc.contributor.authorZou, ZYen_AU
dc.contributor.authorWang, Den_AU
dc.contributor.authorLiu, Yen_AU
dc.contributor.authorLi, YJen_AU
dc.contributor.authorWu, JMen_AU
dc.contributor.authorAvdeev, Men_AU
dc.contributor.authorShi, Sen_AU
dc.date.accessioned2021-07-16T04:38:38Zen_AU
dc.date.available2021-07-16T04:38:38Zen_AU
dc.date.issued2021-03-01en_AU
dc.date.statistics2021-07-05en_AU
dc.description.abstractRedox mediators are promised to thermodynamically resolve the cathode irreversibility of Li-air battery. However, the sluggish chemical reaction between mediators and discharge products severely restrains fast charging. Here, we combine ab initio calculations and machine learning method to investigate the reaction kinetics between LiOH and I2, and demonstrate the critical role of the disorder degree of LiOH and the solvent effect. The Li+ desorption is identified as the rate determining step (rds) of the reaction. While LiOH turns from the crystalline to disordered/amorphous structure, the rds energy barrier will be reduced by ∼500 meV. The functional group of the solvent is detected as the key to regulating the solvation effect and phosphate-based solvent is predicted to accelerate the decomposition kinetics most with the strongest solvation capability. These findings indicate that the faster reaction kinetics between mediators and the discharge products can be achieved by rational discharge product structure regulation and appropriate solvent selection. © 2020 Elsevier B.V.en_AU
dc.identifier.citationWang, A., Zou, Z., Wang, D., Liu, Y., Li, Y., Wu, J., Avdeev, M., & Shi, S. (2021). Identifying chemical factors affecting reaction kinetics in Li-air battery via ab initio calculations and machine learning. Energy Storage Materials, 35, 595-601. doi:10.1016/j.ensm.2020.10.022en_AU
dc.identifier.issn2405-8297en_AU
dc.identifier.journaltitleEnergy Storage Materialsen_AU
dc.identifier.pagination595-601en_AU
dc.identifier.urihttps://doi.org/10.1016/j.ensm.2020.10.022en_AU
dc.identifier.urihttps://apo.ansto.gov.au/dspace/handle/10238/11083en_AU
dc.identifier.volume35en_AU
dc.language.isoenen_AU
dc.publisherElsevieren_AU
dc.subjectRedox flow batteriesen_AU
dc.subjectSolvent propertiesen_AU
dc.subjectThermodynamic activityen_AU
dc.subjectElectric dischargesen_AU
dc.subjectReaction kineticsen_AU
dc.subjectMachine learningen_AU
dc.titleIdentifying chemical factors affecting reaction kinetics in Li-air battery via ab initio calculations and machine learningen_AU
dc.typeJournal Articleen_AU
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