Thermal Investigations of Electrochemical Devices

Electrochemical devices are amongst the most promising systems for renewable and clean energy; despite this there are a number of challenges which have both hindered widespread commercialisation and resulted in safety concerns. Common amongst all electrochemical devices is the importance of temperature and thermal management. Here, the thermal properties of components and devices are examined using infrared thermal imaging, and complimentary techniques, to improve both the fundamental understanding and safety of a number of electrochemical systems, with a focus on fuel cells and batteries. A study investigating the stress distribution in solid oxide fuel cell anodes under imposed non-uniform temperature conditions is described, highlighting the potential for combining infrared imaging with complimentary techniques; in this instance, X-ray diffraction. This study is expanded to show the potential impact of the results on finite element analysis. Thermal imaging is combined with X-ray microtomography in order to describe the surface temperature effects associated with discharging a cylindrical Li-ion battery. Here the internal structure of the cell is seen to have a major impact on the temperature variation observed. Advanced thermal imaging techniques are described with a diagnostic entitled electro-thermal impedance spectroscopy, in addition to the first reported use of lock-in thermography on a Li-ion battery. The impact of the work is highlighted, where appropriate detailing the potential incorporation of the diagnostic and experimental techniques in novel areas, whilst also considering the relevance to existing methodologies and mechanisms

Thermal Runaway of a Li-Ion Battery Studied by Combined ARC and Multi-Length Scale X-ray CT

Lithium ion battery failure occurs across multiple length scales. In this work, the properties of thermal failure and its effects on electrode materials were investigated in a commercial battery using a combination of accelerating rate calorimetry (ARC) and multi-length scale X-ray computed tomography (CT). ARC measured the heat dissipated from the cell during thermal runaway and enabled the identification of key thermal failure characteristics such as onset temperature and the rate of heat generation during the failure. Analysis before and after failure using scanning electron microscopy (SEM) and X-ray CT were performed to reveal the effects of failure on the architecture of the whole cell and microstructure of the cathode material. Mechanical deformations to the cell architecture were revealed due to gas generation at elevated temperatures (>200 °C). The extreme conditions during thermal runaway caused the cathode particles to reduce in size by a factor of two. Electrode surface analysis revealed surface deposits on both the anode and cathode materials. The link between electrode microstructure and heat generation within a cell during failure is analysed and compared to commercially available lithium ion cells of varying cathode chemistries. The optimisation of electrode designs for safer battery materials is discussed

Investigating the effect of thermal gradients on stress in solid oxide fuel cell anodes using combined synchrotron radiation and thermal imaging

Thermal gradients can arise within solid oxide fuel cells (SOFCs) due to start-up and shut-down, non-uniform gas distribution, fast cycling and operation under internal reforming conditions. Here, the effects of operationally relevant thermal gradients on Ni/YSZ SOFC anode half cells are investigated using combined synchrotron X-ray diffraction and thermal imaging. The combination of these techniques has identified significant deviation from linear thermal expansion behaviour in a sample exposed to a one dimensional thermal gradient. Stress gradients are identified along isothermal regions due to the presence of a proximate thermal gradient, with tensile stress deviations of up to 75Â MPa being observed across the sample at a constant temperature. Significant strain is also observed due to the presence of thermal gradients when compared to work carried out at isothermal conditions

Battery state-of-charge estimation using machine learning analysis of ultrasonic signatures

The potential of acoustic signatures to be used for State-of-Charge (SoC) estimation is demonstrated using artificial neural network regression models. This approach represents a streamlined method of processing the entire acoustic waveform instead of performing manual, and often arbitrary, waveform peak selection. For applications where computational economy is prioritised, simple metrics of statistical significance are used to formally identify the most informative waveform features. These alone can be exploited for SoC inference. It is further shown that signal portions representing both early and late interfacial reflections can correlate highly with the SoC and be of predictive value, challenging the more common peak selection methods which focus on the latter. Although later echoes represent greater through-thickness coverage, and are intuitively more information-rich, their presence is not guaranteed. Holistic waveform treatment offers a more robust approach to correlating acoustic signatures to electrochemical states. It is further demonstrated that transformation into the frequency domain can reduce the dimensionality of the problem significantly, while also improving the estimation accuracy. Most importantly, it is shown that acoustic signatures can be used as sole model inputs to produce highly accurate SoC estimates, without any complementary voltage information. This makes the method suitable for applications where redundancy and diversification of SoC estimation approaches is needed. Data is obtained experimentally from a 210 mAh LiCoO2/graphite pouch cell. Mean estimation errors as low as 0.75% are achieved on a SoC scale of 0–100%

Development of a tool to predict outcome of Autologous Chondrocyte Implantation

Objective. The study had 2 objectives: first, to evaluate the success of autologous chondrocyte implantation (ACI) in terms of incidence of surgical re-intervention, including arthroplasty, and investigate predictors of successful treatment outcome. The second objective was to derive a tool predicting a patient’s arthroplasty risk following ACI. Design. In this Level II, prognostic study, 170 ACI-treated patients (110 males [aged 36.8 ± 9.4 years]; 60 females [aged 38.1 ± 10.2 years]) completed a questionnaire about further surgery on their knee treated with ACI 10.9 ± 3.5 years previously. Factors commonly assessed preoperatively (age, gender, defect location and number, previous surgery at this site, and the preoperative Lysholm score) were used as independent factors in regression analyses. Results. At final follow-up (maximum of 19 years post-ACI), 40 patients (23.5%) had undergone surgical re-intervention following ACI. Twenty-six patients (15.3%) underwent arthroplasty, more commonly females (25%) than males (10%; P = 0.001). Cox regression analyses identified 4 factors associated with re-intervention: age at ACI, multiple operations before ACI, patellar defects, and lower pretreatment Lysholm scores (Nagelkerke’s R2 = 0.20). Six predictive items associated with risk of arthroplasty following ACI (Nagelkerke’s R2 = 0.34) were used to develop the Oswestry Risk of Knee Arthroplasty index with internal crossvalidation. Conclusion. In a single-center study, we have identified 6 factors (age, gender, location and number of defects, number of previous operations, and Lysholm score before ACI) that appear to influence the likelihood of ACI patients progressing to arthroplasty. We have used this information to propose a formula or “tool” that could aid treatment decisions and improve patient selection for ACI

Electro-thermal impedance spectroscopy applied to an open-cathode polymer electrolyte fuel cell

The development of in-situ diagnostic techniques is critical to ensure safe and effective operation of polymer electrolyte fuel cell systems. Infrared thermal imaging is an established technique which has been extensively applied to fuel cells; however, the technique is limited to measuring surface temperatures and is prone to errors arising from emissivity variations and reflections. Here we demonstrate that electro-thermal impedance spectroscopy can be applied to enhance infrared thermal imaging and mitigate its limitations. An open-cathode polymer electrolyte fuel cell is used as a case study. The technique operates by imposing a periodic electrical stimulus to the fuel cell and measuring the consequent surface temperature response (phase and amplitude). In this way, the location of heat generation from within the component can be determined and the thermal conduction properties of the materials and structure between the point of heat generation and the point of measurement can be determined. By selectively ‘locking-in’ to a suitable modulation frequency, spatially resolved images of the relative amplitude between the current stimulus and temperature can be generated that provide complementary information to conventional temporal domain thermograms

Investigating lithium-ion battery materials during overcharge-induced thermal runaway: an operando and multi-scale X-ray CT study

Catastrophic failure of lithium-ion batteries occurs across multiple length scales and over very short time periods. A combination of high-speed operando tomography, thermal imaging and electrochemical measurements is used to probe the degradation mechanisms leading up to overcharge-induced thermal runaway of a LiCoO2 pouch cell, through its interrelated dynamic structural, thermal and electrical responses. Failure mechanisms across multiple length scales are explored using a post-mortem multi-scale tomography approach, revealing significant morphological and phase changes in the LiCoO2 electrode microstructure and location dependent degradation. This combined operando and multi-scale X-ray computed tomography (CT) technique is demonstrated as a comprehensive approach to understanding battery degradation and failure

In Situ Ultrasound Acoustic Measurement of the Lithium-Ion Battery Electrode Drying Process

The electrode drying process is a crucial step in the manufacturing of lithium-ion batteries and can significantly affect the performance of an electrode once stacked in a cell. High drying rates may induce binder migration, which is largely governed by the temperature. Additionally, elevated drying rates will result in a heterogeneous distribution of the soluble and dispersed binder throughout the electrode, potentially accumulating at the surface. The optimized drying rate during the electrode manufacturing process will promote balanced homogeneous binder distribution throughout the electrode film; however, there is a need to develop more informative in situ metrologies to better understand the dynamics of the drying process. Here, ultrasound acoustic-based techniques were developed as an in situ tool to study the electrode drying process using NMC622-based cathodes and graphite-based anodes. The drying dynamic evolution for cathodes dried at 40 and 60 °C and anodes dried at 60 °C were investigated, with the attenuation of the reflective acoustic signals used to indicate the evolution of the physical properties of the electrode-coating film. The drying-induced acoustic signal shifts were discussed critically and correlated to the reported three-stage drying mechanism, offering a new mode for investigating the dynamic drying process. Ultrasound acoustic-based measurements have been successfully shown to be a novel in situ metrology to acquire dynamic drying profiles of lithium-ion battery electrodes. The findings would potentially fulfil the research gaps between acquiring dynamic data continuously for a drying mechanism study and the existing research metrology, as most of the published drying mechanism research studies are based on simulated drying processes. It shows great potential for further development and understanding of the drying process to achieve a more controllable electrode manufacturing process

Correlative electrochemical acoustic time-of-flight spectroscopy and X-ray imaging to monitor the performance of single-crystal and polycrystalline NMC811/Gr lithium-ion batteries

LiNixMnyCozO2 (NMC) electrodes typically consist of anisotropic single-crystal primary particles aggregated to form polycrystalline secondary particles. Electrodes composed of polycrystalline NMC particles have a comparatively high gravimetric capacity and good rate capabilities but do not perform as well as single crystal equivalents in terms of volumetric energy density and cycling stability. This has prompted research into well-dispersed single-crystalline NMC products as an alternative solution for high-energy-density batteries. Here, for the first time known to the authors, electrochemical acoustic time-of-flight (EA-ToF) spectroscopy has been shown to be effective in distinguishing between Li-ion batteries composed of either single-crystal NMC811 (SC-NMC811) or polycrystalline NMC811 (PC-NMC811) electrodes. Cells composed of PC-NMC811 electrodes had a higher degree of gas evolution compared to cells containing SC-NMC811 electrodes. Cells composed of PC-NMC811 electrodes also underwent larger changes in the acoustic signal's time-of-flight (ToF) during constant current cycling at a range of C-rates indicating expansion, fracture or dislocation of the reflective interfaces inside the cell. In addition, X-ray computed tomography (X-ray CT) has been used to confirm significant morphological differences between SC-NMC811 electrodes and PC-NMC811 electrodes including the electrode's particle size distribution (PSD) that is suggested to have an effect on acoustic signal interaction with these electrode interfaces