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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.00468 |
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| _version_ | 1866913373772316672 |
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| author | van Hees, Alicia Zhang, Zhan-Yun Sudhama, Aishwarya Zhang, Chao |
| author_facet | van Hees, Alicia Zhang, Zhan-Yun Sudhama, Aishwarya Zhang, Chao |
| contents | Aqueous batteries play an increasingly important role for the development of sustainable and safety-prioritised energy storage solutions. Compared to conventional lithium-ion batteries, the cell chemistry in aqueous batteries share many common features with those of electrolyzer and pseudo-capacitor systems because of the involvement of aqueous electrolyte and proton activity. This imposes the needs for a better understanding of the corresponding ion solvation, intercalation and electron transfer processes at atomistic scale. Therefore, this chapter provides an up-to-date overview of molecular modelling techniques and their applications in aqueous batteries. In particular, we emphasize on the dynamical and reactive description of aqueous battery systems brought in by density functional theory-based molecular dynamics simulation (DFTMD) and its machine-learning (ML) accelerated counterpart. Moreover, we also cover the recent advancement of generative artificial intelligence (AI) in molecular and materials design of aqueous batteries. Case studies presented here include popular aqueous battery systems, such as water-in-salt electrolytes, proton-coupled cathode materials, Zn-ion batteries as well as organic redox flow batteries. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_00468 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Molecular Modelling of Aqueous Batteries van Hees, Alicia Zhang, Zhan-Yun Sudhama, Aishwarya Zhang, Chao Materials Science Chemical Physics Aqueous batteries play an increasingly important role for the development of sustainable and safety-prioritised energy storage solutions. Compared to conventional lithium-ion batteries, the cell chemistry in aqueous batteries share many common features with those of electrolyzer and pseudo-capacitor systems because of the involvement of aqueous electrolyte and proton activity. This imposes the needs for a better understanding of the corresponding ion solvation, intercalation and electron transfer processes at atomistic scale. Therefore, this chapter provides an up-to-date overview of molecular modelling techniques and their applications in aqueous batteries. In particular, we emphasize on the dynamical and reactive description of aqueous battery systems brought in by density functional theory-based molecular dynamics simulation (DFTMD) and its machine-learning (ML) accelerated counterpart. Moreover, we also cover the recent advancement of generative artificial intelligence (AI) in molecular and materials design of aqueous batteries. Case studies presented here include popular aqueous battery systems, such as water-in-salt electrolytes, proton-coupled cathode materials, Zn-ion batteries as well as organic redox flow batteries. |
| title | Molecular Modelling of Aqueous Batteries |
| topic | Materials Science Chemical Physics |
| url | https://arxiv.org/abs/2406.00468 |