Meet Dr Ivan Korotkin, a Senior Research Fellow at @unisouthampton! 🎓 He is creating fast and accurate models of Li-ion #batteries 🔋 and seamlessly integrating them into high-performance code. ⚡️ He co-developed DandeLiion, a set of cutting-edge #batterysoftware tools, and BPX, the first physics-based Battery Parameter eXchange standard. DandeLiion: https://www.dandeliion.com/ BPX: https://bpxstandard.com/ LinkedIn (since I don’t have a Twitter account): https://www.linkedin.com/in/ivan-korotkin/
We are thrilled to introduce Dr. Mayur Bonkile, Postdoctoral Research Associate at Imperial College London Mayur is tackling a critical challenge in #battery safety 🔋 - understanding #thermal runaway. In his #research with @Billy Wu and @Gregory Offer, he is developing physics-based models in #PyBaMM to couple thermal runaway behaviour with #degradation modes. 🌡️⚙️ These insights are a valuable tool for both #industry and #academia to build upon. Further links to dive deeper into his research! 📚✨ MSM: https://batterymodel.co.uk/ ESE: https://www.imperial.ac.uk/electrochem-sci-eng PyBaMM: https://pybamm.org/ Mayur: https://www.imperial.ac.uk/people/m.bonkile
Since 2018, the Multiscale Modelling project works to equip industry and academia with new software modelling tools to predict and improve battery lifetime and performance, by connecting the understanding of battery materials at the atomic level all the way up to an assembled battery pack.
Batteries require a range of high value metals and there are valid concerns about where and how we will source these, with environmental impacts from mining and manufacturing, such as habitat destruction, water use and pollutants, at the forefront. Batteries manufactured now will reach their end of life in 8-15 years from now. Given the large quantities of batteries to be output by many gigafactories worldwide, this represents an environmental crisis: a looming mountain of severely degraded batteries in landfills. But the environmental impacts of battery disposal and resource depletion could be prevented, with a little thought and careful planning, looking holistically across the value chain. Sustainability is a highly complex topic and published LCA analyses lack consistency in their approach, assumptions and boundary conditions. There is a need for defining standard tools, methods and even units, to support comparisons between different battery chemistries and applications. This talk will give a broad overview of the topic, defining sustainability in the context of batteries, describing the battery life cycle and identifying the key issues at each stage of the lifecycle, with a particular focus on the trade-offs that can occur between the stages. Where solutions have been proposed, these will be presented. This presentation was part of the Faraday Institution's annual November conference, 2021. For more information on the Multiscale Modelling project visit www.batterymodel.co.uk; Faraday Institution visit www.faraday.ac.uk; Faraday Conference www.faradayconference.org.uk Do not hesistate to get in touch with us via Twitter @batterymodel
The expansion of lithium-ion batteries from consumer electronics to larger-scale transport and energy storage applications has made understanding the many mechanisms responsible for battery degradation increasingly important. The literature in this complex topic has grown considerably; this perspective aims to distil current knowledge into a succinct form, as a reference and a guide to understanding battery degradation. Unlike other reviews, this work emphasises the coupling between the different mechanisms and the different physical and chemical approaches used to trigger, identify and monitor various mechanisms, as well as the various computational models that attempt to simulate these interactions. Degradation is separated into three levels: the actual mechanisms themselves, the observable consequences at cell level called modes, and the operational effects such as capacity or power fade. Five principal and thirteen secondary mechanisms were found that are generally considered to be the cause of degradation during normal operation, which all give rise to five observable modes. A flowchart illustrates the different feedback loops that couple the various forms of degradation, whilst a table is presented to highlight the experimental conditions that are most likely to trigger specific degradation mechanisms. Together, they provide a powerful guide to designing experiments or models for investigating battery degradation. To submit your questions for our Q&A please tweet us at @batterymodel, email us at battery@imperial.ac.uk, contact us on Slack (link provided in presentation e-mail) or simply leave a comment in the field below.
Parameterisation of battery models is crucial to obtain accurate predictions. Lithium transport in the electrodes is a key phenomenon for the behaviour of batteries. This transport is usually modelled by diffusion with a concentration dependent diffusivity. The methods to determine this diffusivity have been used for decades, but they are not specific for porous electrode batteries so this can lead to inaccurate measurements. We present a new approach to characterise the lithium diffusivity systematically derived from the Doyle-Fuller-Newman model. This approach is validated against synthetic data, showing that it is more accurate and robust than the traditional approaches. To submit your questions for our Q&A please tweet us at @batterymodel, email us at battery@imperial.ac.uk, contact us on Slack (link provided in presentation e-mail) or simply leave a comment in the field below.
Battery modelling requires inputs that describe the physical, electrochemical, and thermal properties to be experimentally determined. There is a lack of original data in literature, however quantifying the properties of a battery is essential for predicting battery behaviour. We outline the parameters for a commercial cell and the methodologies we developed to do so. By mapping the temperature and concentration dependency of these parameters we are able to document how properties change during operation. These dependencies are used to make more robust predictions as the dynamic behaviour of the battery is considered. To submit your questions for our Q&A please tweet us at @batterymodel, email us at battery@imperial.ac.uk, contact us on Slack (link provided in presentation e-mail) or simply leave a comment in the field below.
The ONETEP program is based on a linear-scaling reformulation of quantum theory that allows atomistic simulations of orders of magnitude more atoms than conventional approaches, for more realistic models. Within this framework we are developing the first software tools for atomistic electrochemical simulations in industry and academia, enabling major new insights from simulations, such as the prediction of the charge of different electrode materials in batteries under operational conditions. These new software tools are not only capturing the essential chemistry and physics of batteries but can also give us the parameters needed for bridging atomistic with larger scale simulations. To submit your questions for our Q&A please tweet us at @batterymodel, email us at battery@imperial.ac.uk, contact us on Slack (link provided in presentation e-mail) or simply leave a comment in the field below.
Mini-grids are expected to play an important role in achieving universal access to energy. Batteries are a key cost component, but how to choose and operate them is often unclear. This work examines (1) how predictions of semi-empirical degradation models differ from simple linear models often used by energy practitioners, (2) the implications of climatic conditions, and (3) how far battery lifetime can be extended by simple management strategies informed by the degradation models. We found that battery lifetime predictions differ substantially depending on the model and the climatic condition, and that even very simple energy management strategies can be extremely effective, increasing battery lifetime ~45% (or 5-7 years), with minimal impact on system’s reliability. To submit your questions for our Q&A please tweet us at @batterymodel, email us at battery@imperial.ac.uk, contact us on Slack (link provided in presentation e-mail) or simply leave a comment in the field below.
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Meet Dr Ivan Korotkin, a Senior Research Fellow at @unisouthampton! He is creating fast & accurate models of Li-ion #batteries🔋& seamlessly integrating them into high-performance code⚡️He co-developed DandeLiion, a set of cutting-edge #batterysoftware tools, & BPX
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🚀 Exciting News! Thrilled to introduce @MBonkile, Postdoctoral Research Associate at @Imperial College London! 🎓🔬 He is addressing a crucial #battery safety challenge 🔋 - understanding #thermalrunaway 🌡️⚙️ with @ICBillyWu & Greg. #PyBaMM @FaradayInst

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📢👏👏Another new MSM Paper! Check it out:
A Workflow for Identifying Viable Crystal Structures with Partially Occupied Sites Applied to the Solid Electrolyte Cubic Li7La3Zr2O12 | The Journal of Physical Chemistry Letters
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📢New MSM Publication: Effect of thermal gradients on inhomogeneous degradation in lithium-ion batteries🔋🔋. Check out the full paper
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