| 1. |
- Andersson, Rasmus, 1990, et al.
(författare)
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CHAMPION: Chalmers hierarchical atomic, molecular, polymeric and ionic analysis toolkit
- 2021
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Ingår i: Journal of Computational Chemistry. - : Wiley. - 0192-8651 .- 1096-987X. ; 42:23, s. 1632-1642
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Tidskriftsartikel (refereegranskat)abstract
- We present CHAMPION (Chalmers hierarchical atomic, molecular, polymeric, and ionic analysis toolkit): a software developed to automatically detect time-dependent bonds between atoms based on their dynamics, classify the local graph topology around them, and analyze the physicochemical properties of these topologies by statistical physics. In stark contrast to methodologies where bonds are detected based on static conditions such as cut-off distances, CHAMPION considers pairs of atoms to be bound only if they move together and act as a bound pair over time. Furthermore, the time-dependent global bond graph is possible to split into dynamically shifting connected components or subgraphs around a certain chemical motif and thereby allow the physicochemical properties of each such topology to be analyzed by statistical physics. Applicable to condensed matter and liquids in general, and electrolytes in particular, this allows both quantitative and qualitative descriptions of local structure, as well as dynamical processes such as speciation and diffusion. We present here a detailed overview of CHAMPION, including its underlying methodology, implementation, and capabilities.
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| 2. |
- Andersson, Rasmus, 1990, et al.
(författare)
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Ion Transport Mechanisms via Time-Dependent Local Structure and Dynamics in Highly Concentrated Electrolytes
- 2020
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Ingår i: Journal of the Electrochemical Society. - : The Electrochemical Society. - 1945-7111 .- 0013-4651. ; 167:14
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Tidskriftsartikel (refereegranskat)abstract
- Highly concentrated electrolytes (HCEs) are attracting interest as safer and more stable alternatives to current lithium-ion battery electrolytes, but their structure, solvation dynamics and ion transport mechanisms are arguably more complex. We here present a novel general method for analyzing both the structure and the dynamics, and ultimately the ion transport mechanism(s), of electrolytes including HCEs. This is based on automated detection of bonds, both covalent and coordination bonds, including how they dynamically change, in molecular dynamics (MD) simulation trajectories. We thereafter classify distinct local structures by their bond topology and characterize their physicochemical properties by statistical mechanics, giving both a qualitative and quantitative description of the structure, solvation and coordination dynamics, and ion transport mechanism(s). We demonstrate the method by in detail analyzing an ab initio MD simulation trajectory of an HCE consisting of the LiTFSI salt dissolved in acetonitrile at a 1:2 molar ratio. We find this electrolyte to form a flexible percolating network which limits vehicular ion transport but enables the Li+ ions to move between different TFSI coordination sites along with their first solvation shells. In contrast, the TFSI anions are immobilized in the network, but often free to rotate which further facilitates the Li+ hopping mechanism.Highly concentrated electrolytes (HCEs) are attracting interest as safer and more stable alternatives to current lithium-ion battery electrolytes, but their structure, solvation dynamics and ion transport mechanisms are arguably more complex. We here present a novel general method for analyzing both the structure and the dynamics, and ultimately the ion transport mechanism(s), of electrolytes including HCEs. This is based on automated detection of bonds, both covalent and coordination bonds, including how they dynamically change, in molecular dynamics (MD) simulation trajectories. We thereafter classify distinct local structures by their bond topology and characterize their physicochemical properties by statistical mechanics, giving both a qualitative and quantitative description of the structure, solvation and coordination dynamics, and ion transport mechanism(s). We demonstrate the method by in detail analyzing an ab initio MD simulation trajectory of an HCE consisting of the LiTFSI salt dissolved in acetonitrile at a 1:2 molar ratio. We find this electrolyte to form a flexible percolating network which limits vehicular ion transport but enables the Li+ ions to move between different TFSI coordination sites along with their first solvation shells. In contrast, the TFSI anions are immobilized in the network, but often free to rotate which further facilitates the Li+ hopping mechanism. Highly concentrated electrolytes (HCEs) are attracting interest as safer and more stable alternatives to current lithium-ion battery electrolytes, but their structure, solvation dynamics and ion transport mechanisms are arguably more complex. We here present a novel general method for analyzing both the structure and the dynamics, and ultimately the ion transport mechanism(s), of electrolytes including HCEs. This is based on automated detection of bonds, both covalent and coordination bonds, including how they dynamically change, in molecular dynamics (MD) simulation trajectories. We thereafter classify distinct local structures by their bond topology and characterize their physicochemical properties by statistical mechanics, giving both a qualitative and quantitative description of the structure, solvation and coordination dynamics, and ion transport mechanism(s). We demonstrate the method by in detail analyzing an ab initio MD simulation trajectory of an HCE consisting of the LiTFSI salt dissolved in acetonitrile at a 1:2 molar ratio. We find this electrolyte to form a flexible percolating network which limits vehicular ion transport but enables the Li+ ions to move between different TFSI coordination sites along with their first solvation shells. In contrast, the TFSI anions are immobilized in the network, but often free to rotate which further facilitates the Li+ hopping mechanism.
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| 3. |
- El-Bousiydy, Hassna, et al.
(författare)
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LIBAC: An Annotated Corpus for Automated “Reading” of the Lithium-Ion Battery Research Literature
- 2023
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Ingår i: Chemistry of Materials. - : American Chemical Society (ACS). - 1520-5002 .- 0897-4756. ; 35:5, s. 1849-1857
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Tidskriftsartikel (refereegranskat)abstract
- The lithium-ion battery (LIB) research literature has increased very rapidly of late. While this is an immense source of valuable knowledge and facts for the community, these are also partly “buried” in the literature. To truly make the most possible use of the information available and automate “reading”, special tools are required. Named entity recognition (NER) is one such tool, which uses supervised machine learning for information extraction. To enable efficient NER, however, a large and high-quality annotated corpus is crucial. Here, we report on our generated, semi-automatically annotated lithium-ion battery annotated corpus, “LIBAC”, for 28 different entities of LIBs, which was used for training and evaluating Tok2vec and Transformer-based models, resulting in high general accuracies for these with F1-scores of 81 and 83%, respectively. LIBAC itself was created from 6985 paragraphs randomly chosen from ca. 11,000 LIB research papers and contains 73,300 annotated spans (627,428 tokens). This is the prime stepping-stone needed to develop a large-scale information extraction system designed for the LIB research literature.
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| 4. |
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| 5. |
- Franco, Alejandro A., et al.
(författare)
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Boosting Rechargeable Batteries R&D by Multiscale Modeling: Myth or Reality?
- 2019
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Ingår i: Chemical Reviews. - : American Chemical Society (ACS). - 0009-2665 .- 1520-6890. ; 119:7, s. 4569-4627
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Tidskriftsartikel (refereegranskat)abstract
- This review addresses concepts, approaches, tools, and outcomes of multiscale modeling used to design and optimize the current and next generation rechargeable battery cells. Different kinds of multiscale models are discussed and demystified with a particular emphasis on methodological aspects. The outcome is compared both to results of other modeling strategies as well as to the vast pool of experimental data available. Finally, the main challenges remaining and future developments are discussed.
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| 6. |
- Lombardo, Teo, et al.
(författare)
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Artificial Intelligence Applied to Battery Research: Hype or Reality?
- 2022
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Ingår i: Chemical Reviews. - : American Chemical Society (ACS). - 0009-2665 .- 1520-6890. ; 122:12, s. 10899 -10969
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Forskningsöversikt (refereegranskat)abstract
- This is a critical review of artificial intelligence/machine learning (AI/ML) methods applied to battery research. It aims at providing a comprehensive, authoritative, and critical, yet easily understandable, review of general interest to the battery community. It addresses the concepts, approaches, tools, outcomes, and challenges of using AI/ML as an accelerator for the design and optimization of the next generation of batteries - a current hot topic. It intends to create both accessibility of these tools to the chemistry and electrochemical energy sciences communities and completeness in terms of the different battery RD aspects covered.
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| 7. |
- Thangavel, Vigneshwaran, et al.
(författare)
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A microstructurally resolved model for Li-S batteries assessing the impact of the cathode design on the discharge performance
- 2016
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Ingår i: Journal of the Electrochemical Society. - : The Electrochemical Society. - 1945-7111 .- 0013-4651. ; 163:13, s. A2817-A2829
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Tidskriftsartikel (refereegranskat)abstract
- This paper reports a discharge model for lithium sulfur (Li-S) battery cells, supported by a multi-scale description of the composite C/S cathode microstructure. The cathode is assumed to be composed of mesoporous carbon particles with inter-particular pores in-between and the sulfur impregnated into both types of pores. The electrolyte solutes such as sulfur, polysulfides and lithium ions, produced during the discharge, are allowed to exchange between the pores. Furthermore, the model describes the Li2S(solid) precipitation and its effects on transport and reduction reaction kinetics. Hereby it provides fundamental insights on the impact on the Li-S discharge curve of practically modifiable manufacturing parameters and operation designs, such as current density, carbon porosity, C/S ratio and sizes of carbon particles and pores.
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| 8. |
- Årén, Fabian, 1994, et al.
(författare)
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Global and Local Structure of Lithium Battery Electrolytes: Origin and Onset of Highly Concentrated Electrolyte Behavior
- 2023
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Ingår i: Journal of the Electrochemical Society. - 1945-7111 .- 0013-4651. ; 170:6
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Tidskriftsartikel (refereegranskat)abstract
- Highly concentrated electrolytes (HCEs), created simply by increasing the lithium salt concentration from the conventional 1 M to 3-5 M, have been suggested as a path towards safer and more stable lithium batteries. Their higher thermal and electrochemical stabilities and lower volatilities are usually attributed to the unique solvation structure of HCEs with not enough solvent available to fully solvate the Li+ ions—but much remains to be understood. Here the structural features that characterize the behavior of electrolytes in general and HCEs in particular, and especially the transition from conventional to highly concentrated behavior, are reported for lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in acetonitrile (ACN), a common HCE system. We analyze four different salt concentrations using ab initio molecular dynamics (AIMD) and the CHAMPION software, to obtain trends in global and local structure, as well as configurational entropy, to elucidate what truly sets apart the highly concentrated regime.
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