Search or filter publications

Filter by type:

Filter by publication type

Filter by year:



  • Showing results for:
  • Reset all filters

Search results

  • Journal article
    Ruan H, Chen J, Ai W, Wu Bet al., 2022,

    Generalised diagnostic framework for rapid battery degradation quantification with deep learning

    , Energy and AI, Vol: 9, Pages: 1-13, ISSN: 2666-5468

    Diagnosing lithium-ion battery degradation is challenging due to the complex, nonlinear, and path-dependent nature of the problem. Here, we develop a generalised and rapid degradation diagnostic method with a deep learning-convolutional neural network that quantifies degradation modes of batteries aged under various conditions in 0.012 s without feature engineering. Rather than performing extensive aging experiments, synthetic aging datasets for network training are generated. This dramatically lowers training cost/time, with these datasets covering almost all the aging paths, enabling a generalised degradation diagnostic framework. We show that the five thermodynamic degradation modes are correlated, and systematically elucidate their correlations. We thus propose a non-invasive comprehensive evaluation method and find the degradation diagnostic errors to be less than 1.22% for three leading commercial battery chemistries. The comparison with the traditional diagnostic methods confirms the high accuracy and fast nature of the proposed approach. Quantification of degradation modes with the partial discharge/charge data using the proposed diagnostic framework validates the real-world feasibility of this approach. This work, therefore, enables the promise of online identification of battery degradation and efficient analysis of large-data sets, unlocking potential for long lifetime energy storage systems.

  • Journal article
    Zhang C, Amietszajew T, Li S, Marinescu M, Offer G, Wang C, Guo Y, Bhagat Ret al., 2022,

    Real-time estimation of negative electrode potential and state of charge of lithium-ion battery based on a half-cell-level equivalent circuit model

    , JOURNAL OF ENERGY STORAGE, Vol: 51, ISSN: 2352-152X
  • Journal article
    Ai W, Kirkaldy N, Jiang Y, Offer G, Wang H, Wu Bet al., 2022,

    A composite electrode model for lithium-ion batteries with silicon/graphite negative electrodes

    , Journal of Power Sources, Vol: 527, Pages: 231142-231142, ISSN: 0378-7753

    Silicon is a promising negative electrode material with a high specific capacity, which is desirable for com-mercial lithium-ion batteries. It is often blended with graphite to form a composite anode to extend lifetime,however, the electrochemical interactions between silicon and graphite have not been fully investigated. Here,an electrochemical composite electrode model is developed and validated for lithium-ion batteries with asilicon/graphite anode. The continuum-level model can reproduce the voltage hysteresis and demonstratethe interactions between graphite and silicon. At high states-of-charge, graphite provides the majority of thereaction current density, however this rapidly switches to the silicon phase at deep depths-of-discharge due tothe different open circuit voltage curves, mass fractions and exchange current densities. Furthermore, operationat high C-rates leads to heterogeneous current densities in the through-thickness direction, where peak reactioncurrent densities for silicon can be found at the current collector–electrode side as opposed to the separator–electrode side for graphite. Increasing the mass fraction of silicon also highlights the beneficial impacts ofreducing the peak reaction current densities. This work, therefore, gives insights into the effects of siliconadditives, their coupled interactions and provides a platform to test different composite electrodes for betterlithium-ion batteries.

  • Report
    Kallitsis E, Lander L, Edge J, Bravo Diaz L, Brown A, Kelsall G, Offer G, Korre Aet al., 2022,

    Safe and sustainable lithium-ion batteries

    , Safe and Sustainable Lithium-ion Batteries, Publisher: Imperial College London - Energy Futures Lab

    The transition to clean energy and electric mobility is driving unprecedented demand for lithium-ion batteries (LIBs). This paper investigates the safety and sustainability of LIBs, exploring ways of reducing their impact on the environment and ensuring they do not pose a danger to health of workers or users.

  • Journal article
    Diaz LB, Hales A, Marzook MW, Patel Y, Offer Get al., 2022,

    Measuring Irreversible Heat Generation in Lithium-Ion Batteries: An Experimental Methodology

  • Journal article
    Roe C, Feng X, White G, Li R, Wang H, Rui X, Li C, Zhang F, Null V, Parkes M, Patel Y, Wang Y, Wang H, Ouyang M, Offer G, Wu Bet al., 2022,

    Immersion cooling for lithium-ion batteries – a review

    , Journal of Power Sources, Vol: 525, Pages: 231094-231094, ISSN: 0378-7753

    Battery thermal management systems are critical for high performance electric vehicles, where the ability to remove heat and homogenise temperature distributions in single cells and packs are key considerations. Immersion cooling, which submerges the battery in a dielectric fluid, has the potential of increasing the rate of heat transfer by 10,000 times relative to passive air cooling. In 2-phase systems, this performance increase is achieved through the latent heat of evaporation of the liquid-to-gas phase transition and the resulting turbulent 2-phase fluid flow. However, 2-phase systems require additional system complexity, and single-phase direct contact immersion cooling can still offer up to 1,000 times improvements in heat transfer over air cooled systems. Fluids which have been considered include: hydrofluoroethers, mineral oils, esters and water-glycol mixtures. This review therefore presents the current state-of-the-art in immersion cooling of lithium-ion batteries, discussing the performance implications of immersion cooling but also identifying gaps in the literature which include a lack of studies considering the lifetime, fluid stability, material compatibility, understanding around sustainability and use of immersion for battery safety. Insights from this review will therefore help researchers and developers, from academia and industry, towards creating higher power, safer and more durable electric vehicles.

  • Journal article
    Jiang Y, Niu Z, Offer G, Xuan J, Wang Het al., 2022,

    Insights into the role of silicon and graphite in the electrochemical performance of silicon/graphite blended electrodes with a multi-material porous electrode model

    , Journal of The Electrochemical Society, Vol: 169, Pages: 020568-020568, ISSN: 0013-4651

    Silicon/graphite blended electrodes are promising candidates to replace graphite in lithium ion batteries, benefiting from the high capacity of silicon and the good structural stability of carbon. Models have proven essential to understand and optimise batteries with new materials. However, most previous models treat silicon/graphite blends as a single “lumped” material, offering limited understanding of the behaviors of the individual materials and thus limited design capability. Here, we present a multi-material model for silicon/graphite electrodes with detailed descriptions of the contributions of the individual active materials. The model shows that silicon introduces voltage hysteresis to silicon/graphite electrodes and consequently a “plateau shift” during delithiation of the electrodes. There will also be competition between the silicon and graphite lithiation reactions depending on silicon/graphite ratio. A dimensionless competing factor is derived to quantify the competition between the two active materials. This is demonstrated to be a useful indicator for active operating regions for each material and we demonstrate how it can be used to design cycling protocols for mitigating electrode degradation. The multi-material electrode model can be readily implemented into full-cell models and coupled with other physics to guide further development of lithium ion batteries with silicon-based electrodes.

  • Journal article
    Steinhardt M, Barreras JV, Ruan H, Wu B, Offer GJ, Jossen Aet al., 2022,

    Meta-analysis of experimental results for heat capacity and thermal conductivity in lithium-ion batteries: A critical review

    , Journal of Power Sources, Vol: 522, Pages: 1-25, ISSN: 0378-7753

    Scenarios with rapid energy conversion for lithium-ion batteries are increasingly relevant, due to the desire for more powerful electric tools or faster charging electric vehicles. However, higher power means higher cooling requirements, affecting the battery temperature and its thermal gradients. In turn, temperature is a key quantity influencing battery performance, safety and lifetime. Therefore, thermal models are increasingly important for the design and operation of battery systems. Key parameters are specific heat capacity and thermal conductivity. For these parameters, this paper presents a comprehensive review of the experimental results in the literature, where the median values and corresponding uncertainties are summarized. Whenever available, data is analyzed from component to cell level with the discussion of dependencies on temperature, state of charge (SOC) and state of health (SOH). This meta-analysis reveals gaps in knowledge and research needs. For instance, we uncover inconsistencies between the specific heat capacity of electrode-separator stacks and full-cells. For the thermal conductivity, we found that thermal contact resistance and dependencies on battery states have been poorly studied. There is also a lack of measurements at high temperatures, which are required for safety studies. Overall, this study serves as a valuable reference material for both modellers and experimenters.

  • Journal article
    Morgan LM, Islam MM, Yang H, O'Regan K, Patel AN, Ghosh A, Kendrick E, Marinescu M, Offer GJ, Morgan BJ, Islam MS, Edge J, Walsh Aet al., 2022,

    From Atoms to Cells: Multiscale Modeling of a LiNi<i><sub>x</sub></i>Mn<i><sub>y</sub></i>Co<i><sub>z</sub></i>O<sub>2</sub> Cathodes for Li-Ion Batteries

    , ACS ENERGY LETTERS, Vol: 7, Pages: 108-122, ISSN: 2380-8195
  • Journal article
    Morgan LM, Mercer MP, Bhandari A, Peng C, Islam MM, Yang H, Holland J, Coles SW, Sharpe R, Walsh A, Morgan BJ, Kramer D, Saiful Islam M, Hoster HE, Edge JS, Skylaris CKet al., 2022,

    Pushing the boundaries of lithium battery research with atomistic modelling on different scales

    , Progress in Energy, Vol: 4

    Computational modelling is a vital tool in the research of batteries and their component materials. Atomistic models are key to building truly physics-based models of batteries and form the foundation of the multiscale modelling chain, leading to more robust and predictive models. These models can be applied to fundamental research questions with high predictive accuracy. For example, they can be used to predict new behaviour not currently accessible by experiment, for reasons of cost, safety, or throughput. Atomistic models are useful for quantifying and evaluating trends in experimental data, explaining structure-property relationships, and informing materials design strategies and libraries. In this review, we showcase the most prominent atomistic modelling methods and their application to electrode materials, liquid and solid electrolyte materials, and their interfaces, highlighting the diverse range of battery properties that can be investigated. Furthermore, we link atomistic modelling to experimental data and higher scale models such as continuum and control models. We also provide a critical discussion on the outlook of these materials and the main challenges for future battery research.

  • Journal article
    Gopalakrishnan K, Offer GJ, 2022,

    A Composite Single Particle Lithium-Ion Battery Model Through System Identification

  • Journal article
    Pang M-C, Marinescu M, Wang H, Offer Get al., 2021,

    Mechanical behaviour of inorganic solid-state batteries: can we model the ionic mobility in the electrolyte with Nernst-Einstein's relation?

    , PHYSICAL CHEMISTRY CHEMICAL PHYSICS, Vol: 23, Pages: 27159-27170, ISSN: 1463-9076
  • Journal article
    O'Kane SEJ, Campbell ID, Marzook WWJ, Offer GJ, Marinescu Met al., 2021,

    Physical Origin of the Differential Voltage Minimum Associated With Lithium Plating in Li-Ion Batteries

    , ECS Meeting Abstracts, Vol: MA2021-02, Pages: 466-466
  • Journal article
    Hales A, Prosser R, Bravo Diaz L, White G, Patel Y, Offer GJ, Marzook WWJet al., 2021,

    The Cell Cooling Coefficient As a Design Tool to Optimize Thermal Management of Lithium-Ion Cells in Battery Packs

    , ECS Meeting Abstracts, Vol: MA2021-02, Pages: 422-422
  • Journal article
    Lander L, Kallitsis E, Hales A, Edge J, Korre A, Offer GJet al., 2021,

    Cost and Carbon Footprint Reduction of Electric Vehicle Lithium-Ion Batteries through Efficient Thermal Management

    , ECS Meeting Abstracts, Vol: MA2021-02, Pages: 743-743
  • Journal article
    Pang M-C, Yang K, Brugge R, Zhang T, Liu X, Pan F, Yang S, Aguadero A, Wu B, Marinescu M, Wang H, Offer GJet al., 2021,

    Interactions are important: Linking multi-physics mechanisms to the performance and degradation of solid-state batteries

    , MATERIALS TODAY, Vol: 49, Pages: 145-183, ISSN: 1369-7021
  • Journal article
    Lander L, Cleaver T, Rajaeifar MA, Viet N-T, Elliott RJR, Heidrich O, Kendrick E, Edge JS, Offer Get al., 2021,

    Financial viability of electric vehicle lithium-ion battery recycling

    , ISCIENCE, Vol: 24
  • Journal article
    Schimpe M, Varela Barreras J, Wu B, Offer GJet al., 2021,

    Battery degradation-aware current derating: an effective method to prolong lifetime and ease thermal management

    , Journal of The Electrochemical Society, Vol: 168, Pages: 1-13, ISSN: 0013-4651

    To ensure the safe and stable operation of lithium-ion batteries in battery energy storage systems (BESS), the power/current is de-rated to prevent the battery from going outside the safe operating range. Most derating strategies use static limits for battery current, voltage, temperature and state-of-charge, and do not account for the complexity of battery degradation. Progress has been made with models of lithium plating for fast charging. However, this is a partial solution, does not consider other degradation mechanisms, and still requires complex optimization work, limiting widespread adoption. In this work, the calendar and cycle degradation model is analysed offline to predetermine the degradation rates. The results are integrated into the current-derating strategy. This framework can be adapted to any degradation model and allows flexible tuning. The framework is evaluated in simulations of an outdoors-installed BESS with passive thermal management, which operates in a residential photovoltaic application. In comparison to standard derating, the degradation-aware derating achieves: (1) increase of battery lifetime by 65%; (2) increase in energy throughput over lifetime by 49%, while III) energy throughput per year is reduced by only 9.5%. These results suggest that the derating framework can become a new standard in current derating.

  • Journal article
    Lander L, Kallitsis E, Hales A, Edge JS, Korre A, Offer Get al., 2021,

    Cost and carbon footprint reduction of electric vehicle lithium-ion batteries through efficient thermal management

    , Applied Energy, Vol: 289, Pages: 1-10, ISSN: 0306-2619

    Electric vehicles using lithium-ion batteries are currently the most promising technology to decarbonise the transport sector from fossil-fuels. It is thus imperative to reduce battery life cycle costs and greenhouse gas emissions to make this transition both economically and environmentally beneficial. In this study, it is shown that battery lifetime extension through effective thermal management significantly decreases the battery life cycle cost and carbon footprint. The battery lifetime simulated for each thermal management system is implemented in techno-economic and life cycle assessment models to calculate the life cycle costs and carbon footprint for the production and use phase of an electric vehicles. It is demonstrated that by optimising the battery thermal management system, the battery life cycle cost and carbon footprint can be reduced by 27% (from 0.22 $·km−1 for air cooling to 0.16 $·km−1 for surface cooling) and 25% (from 0.141 kg CO2 eq·km−1 to 0.104 kg CO2 eq·km−1), respectively. Moreover, the importance of cell design for cost and environmental impact are revealed and an improved cell design is proposed, which reduces the carbon footprint and life cycle cost by 35% to 0.0913 kg CO2 eq·km−1 and 40% to 0.133 $·km−1, respectively, compared with conventional cell designs combined with air cooling systems.

  • Journal article
    Li S, Kirkaldy N, Zhang C, Gopalakrishnan K, Amietszajew T, Bravo Diaz L, Varela Barreras J, Shams M, Hua X, Patel Y, Offer G, Marinescu Met al., 2021,

    Optimal cell tab design and cooling strategy for cylindrical lithium-ion batteries

    , Journal of Power Sources, Vol: 492, Pages: 1-16, ISSN: 0378-7753

    The ability to correctly predict the behavior of lithium ion batteries is critical for safety, performance, cost and lifetime. Particularly important for this purpose is the prediction of the internal temperature of cells, because of the positive feedback between heat generation and current distribution. In this work, a comprehensive electro-thermal model is developed for a cylindrical lithium-ion cell. The model is comprehensively parameterized and validated with experimental data for 2170 cylindrical cells (LG M50T, NMC811), including direct core temperature measurements. The validated model is used to study different cell designs and cooling approaches and their effects on the internal temperature of the cell. Increasing the number of tabs connecting the jellyroll to the base of the cylindrical-can reduces the internal thermal gradient by up to 25.41%. On its own, side cooling is more effective than base cooling at removing heat, yet both result in thermal gradients within the cell of a similar magnitude, irrespective of the number of cell tabs. The results are of immediate interest to both cell manufacturers and battery pack designers, while the modelling and parameterization framework created is an essential tool for energy storage system design.

  • Journal article
    Hales A, Brouillet E, Wang Z, Edwards B, Samieian MA, Kay J, Mores S, Auger D, Patel Y, Offer Get al., 2021,

    Isothermal temperature control for battery testing and battery model parameterization

    , SAE International Journal of Electrified Vehicles, Vol: 10, Pages: 105-122, ISSN: 2691-3747

    The hybrid/electric vehicle (H/EV) market is very dependent on battery models. Battery models inform cell and battery pack design, critical in online battery management systems (BMSs), and can be used as predictive tools to maximize the lifetime of a battery pack. Battery models require parameterization, through experimentation. Temperature affects every aspect of a battery’s operation and must therefore be closely controlled throughout all battery experiments. Today, the private sector prefers climate chambers for experimental thermal control. However, evidence suggests that climate chambers are unable to adequately control the surface temperature of a battery under test. In this study, laboratory apparatus is introduced that controls the temperature of any exposed surface of a battery through conduction. Pulse discharge tests, temperature step-change tests, and driving cycle tests are used to compare the performance of this conductive thermal control apparatus (CTCA) against a climate chamber across a range of scenarios. The CTCA outperforms the climate chamber in all tests. In CTCA testing, the rate of heat removal from the cell is increased by two orders of magnitude. The CTCA eliminates error due to cell surface temperature rise, which is inherent to climate chamber testing due to insufficient heat removal rates from a cell under test. The CTCA can reduce the time taken to conduct entropic parameterization of a cell by almost 10 days, a 70% reduction in the presented case. Presently, the H/EV industry’s reliance on climate chambers is impacting the accuracy of all battery models. The industry must move away from the flawed concept of convective cooling during battery parameterization.

  • Journal article
    Robinson J, Xi K, Kumar RV, Ferrari AC, Au H, Titirici M-M, Parra Puerto A, Kucernak A, Fitch SDS, Garcia-Araez N, Brown Z, Pasta M, Furness L, Kibler A, Walsh D, Johnson L, Holc C, Newton G, Champness NR, Markoulidis F, Crean C, Slade R, Andritsos E, Cai Q, Babar S, Zhang T, Lekakou CT, Rettie A, Kulkarni NN, Jervis R, Cornish M, Marinescu M, Offer G, Li Z, Bird L, Grey C, Chhowhalla M, Di Lecce D, Miller T, Brett D, Owen R, Liatard S, Ainsworth D, Shearing Pet al., 2021,

    2021 roadmap on lithium sulfur batteries

    , Journal of Physics: Energy, Vol: 3, ISSN: 2515-7655

    Batteries that extend performance beyond the intrinsic limits of Li-ion batteries are among the most important developments required to continue the revolution promised by electrochemical devices. Of these next-generation batteries, lithium sulfur (Li–S) chemistry is among the most commercially mature, with cells offering a substantial increase in gravimetric energy density, reduced costs and improved safety prospects. However, there remain outstanding issues to advance the commercial prospects of the technology and benefit from the economies of scale felt by Li-ion cells, including improving both the rate performance and longevity of cells. To address these challenges, the Faraday Institution, the UK's independent institute for electrochemical energy storage science and technology, launched the Lithium Sulfur Technology Accelerator (LiSTAR) programme in October 2019. This Roadmap, authored by researchers and partners of the LiSTAR programme, is intended to highlight the outstanding issues that must be addressed and provide an insight into the pathways towards solving them adopted by the LiSTAR consortium. In compiling this Roadmap we hope to aid the development of the wider Li–S research community, providing a guide for academia, industry, government and funding agencies in this important and rapidly developing research space.

  • Journal article
    Edge JS, O'Kane S, Prosser R, Kirkaldy ND, Patel AN, Hales A, Ghosh A, Ai W, Chen J, Yang J, Li S, Pang M-C, Bravo Diaz L, Tomaszewska A, Marzook MW, Radhakrishnan KN, Wang H, Patel Y, Wu B, Offer GJet al., 2021,

    Lithium ion battery degradation: what you need to know

    , Physical Chemistry Chemical Physics, Vol: 23, Pages: 8200-8221, ISSN: 1463-9076

    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.

  • Journal article
    Prosser R, Offer G, Patel Y, 2021,

    Lithium-Ion Diagnostics: The First Quantitative In-Operando Technique for Diagnosing Lithium Ion Battery Degradation Modes under Load with Realistic Thermal Boundary Conditions

  • Journal article
    Hua X, Zhang C, Offer G, 2021,

    Finding a better fit for lithium ion batteries: A simple, novel, load dependent, modified equivalent circuit model and parameterization method

    , JOURNAL OF POWER SOURCES, Vol: 484, ISSN: 0378-7753
  • Journal article
    Ghosh A, Foster JM, Offer G, Marinescu Met al., 2021,

    A Shrinking-Core Model for the Degradation of High-Nickel Cathodes (NMC811) in Li-Ion Batteries: Passivation Layer Growth and Oxygen Evolution

  • Journal article
    Hua X, Heckel C, Modrow N, Zhang C, Hales A, Holloway J, Jnawali A, Li S, Yu Y, Loveridge M, Shearing P, Patel Y, Marinescu M, Tao L, Offer Get al., 2021,

    The prismatic surface cell cooling coefficient: A novel cell design optimisation tool & thermal parameterization method for a 3D discretised electro-thermal equivalent-circuit model

    , eTransportation, Vol: 7, Pages: 1-15, ISSN: 2590-1168

    Thermal management of large format prismatic lithium ion batteries is challenging due to significant heat generation rates, long thermal ‘distances’ from the core to the surfaces and subsequent thermal gradients across the cell. The cell cooling coefficient (CCC) has been previously introduced to quantify how easy or hard it is to thermally manage a cell. Here we introduce its application to prismatic cells with a 90 Ah prismatic lithium iron phosphate cell with aluminium alloy casing. Further, a parameterised and discretised three-dimensional electro-thermal equivalent circuit model is developed in a commercially available software environment. The model is thermally and electrically validated experimentally against data including drive cycle noisy load and constant current CCC square wave load, with particular attention paid to the thermal boundary conditions. A quantitative study of the trade-off between cell energy density and surface CCC, and into casing material selection has been conducted here. The CCC enables comparison between cells, and the model enables a cell manufacturer to optimise the cell design and a systems developer to optimise the pack design. We recommend this is operated together holistically. This paper offers a cost-effective, time-efficient, convenient and quantitative way to achieve better and safer battery designs for multiple applications.

  • Journal article
    Chowdhury R, Banerjee A, Zhao Y, Liu X, Brandon Net al., 2021,

    Simulation of bi-layer cathode materials with experimentally validated parameters to improve ion diffusion and discharge capacity

    , Sustainable Energy and Fuels, Vol: 5, Pages: 1103-1119, ISSN: 2398-4902

    The prospect of thick graded electrodes for both higher energy and higher-power densities in lithium-ion batteries is investigated. The simulation results discussed in previous reports on next-generation graded electrodes do not recognize the effect of material processing conditions on microstructural, transport and kinetic parameters. Hence, in this work, we focus on the effect of material processing conditions on particle morphology and its subsequent influence on microstructure (porosity and tortuosity), along with the resultant transport (solid-phase diffusivity) and kinetic (reaction rate constant) properties of synthesized single-layer cathodes. These experimental insights are employed to simulate the benefits of 400 μm thick bi-layer graded cathodes with two different particle sizes and porosities in each layer. The microstructural, transport, and kinetic information are obtained through 3D imaging and electrochemical impedance spectroscopy (EIS) techniques. These parameters are used to develop bi-layer numerical models to understand transport phenomena and to predict cell performance with such graded structures. Simulation results highlight that bi-layer cathodes display higher electrode utilization (solid phase lithiation) next to the current-collector compared to conventional monolayer cathodes with an increase of 39.2% in first discharge capacity at 2C. Additionally, the simulations indicate that an improvement of 47.7% in energy density, alongside a marginal increase of 0.6% in power density, can be achieved at 4C by structuring the porosity in the layer next to the separator to be higher than the porosity in the layer next to the current-collector.

  • Journal article
    Pang M-C, Wei Y, Wang H, Marinescu M, Yan Y, Offer GJet al., 2021,

    Large-format bipolar and parallel solid-state lithium-metal cell stacks: a thermally coupled model-based comparative study

    , Journal of The Electrochemical Society, Vol: 167, Pages: 1-23, ISSN: 0013-4651

    Despite the potential of solid electrolytes in replacing liquid electrolytes, solid-state lithium-metal batteries have not been commercialised for large-scale applications due to manufacturing constraints. In this study, we demonstrate that the desired energy and power output for large-format solid-state lithium-metal batteries can be achieved by scaling and stacking unit cells. Two stack configurations, a bipolar and a parallel stack are modelled and compared. With 63 cells stacked in series, we show that a bipolar stack could reach a stack voltage up to 265 V. In contrast, a parallel stack with 32 double-coated cells could achieve a nominal capacity of 4 Ah. We also demonstrate that the choice of current collectors is critical in determining the gravimetric power and energy density of both stacks. By coupling the electrochemical stack model thermally, we show that the Joule heating effects are negligible for bipolar stacks but become dominant for parallel stacks. Bipolar stacks are better due to their higher power and energy densities and lower heat generation, but a lower Coulombic stack capacity limits their performance. In contrast, parallel stacks generate more heat and require more advanced thermal management. These thermally-coupled stack models can be used as prototypes to aid the future development of large-format solid-state batteries.

  • Journal article
    Chen B, Xuan J, Offer GJ, Wang Het al., 2020,

    Multiplex measurement of diffusion in zinc battery electrolytes from microfluidics using Raman microspectroscopy

    , Applied Energy, Vol: 279, Pages: 1-6, ISSN: 0306-2619

    Rechargeable zinc batteries have emerged as an inexpensive and safe post-lithium-ion battery technology and have received increasing research interest. Developing suitable electrolytes and understanding their transport properties lie at the heart of successful zinc battery technologies as the battery behaviour is a strong function of ion transport in the electrolytes. To accelerate the research and development process, herein we demonstrate a low-cost and high-throughput approach to measure the diffusion in zinc electrolytes at different concentrations simultaneously. The new approach combines Raman microspectroscopy and a multiplexed microfluidic chip with integrated micromixers, concentration gradient generators and a Y-sensor array. Aqueous-based zinc sulphate electrolytes, widely used in zinc batteries, were used for a proof-of-concept. The measured diffusion coefficients for different electrolyte concentrations show good agreement with literature values. With four electrolyte samples in this study, the developed approach requires minimum 0.5 mL of the electrolyte solutions and 30 mins, which is over ten times faster than a typical diffusion measurement with the conventional electrochemical approach in restricted-diffusion cells. The microfluidic chip is readily scalable to further increase the throughput, and can be extended to for use of measuring different (i.e. organic and aqueous) and even mixtures of electrolytes (i.e. ethylene carbonate and dimethyl carbonate) as well as salts (Li+, Na+, Mg2+, etc.).

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: Request URI: /respub/WEB-INF/jsp/search-t4-html.jsp Query String: id=1134&limit=30&page=1&respub-action=search.html Current Millis: 1718367484527 Current Time: Fri Jun 14 13:18:04 BST 2024