Vapour – liquid equilibria of acetic acid + water and propanoic acid + water: experimental measurement and thermodynamic modelling

Vapour – liquid equilibria were measured for the acetic acid + water and the propanoic acid + water systems, in the temperature range of 412.6 to 483.2 K and pressures of 1.87 to 19.38 bar, over the entire range of concentrations. An experimental apparatus based on the static-analytical method with sampling of both phases was used with quantitative analysis by GC. A new experimental technique comprising positron emission particle tracking (PEPT) was developed and applied for the determination phase compositions and molar volumes for the acetic acid + water system at 412.6 K. The Peng-Robinson (PR), the Cubic Plus Association (CPA), the Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT) and the PC-polar-SAFT (PCP-SAFT) equations modelled the data. The 1A and 2B association schemes for propanoic acid and the 2B, 3B and 4C for water, were evaluated. In CPA, the ECR and CR1 combining rules were also tested. A single binary interaction parameter was used in all models. PCP-SAFT presented higher predictive and correlative capabilities when the organic acid was modelled as 1A and water as 2B. The best association combination among CPA and PC-SAFT was 2B and 4C for the acid and water, respectively. CR1 accounted for lower errors in predictive mode while ECR in correlative mode. CPA performance was intermediate between the PC-SAFT and PCP-SAFT models and the PR equation. PR predictions were rather poor but correlations were better than those of CPA, at the expense of a larger binary interaction parameter

Data mining for quality prediction of battery in manufacturing process : Cathode coating process

A data mining approach is proposed for evaluating the effects of battery production factors in cathode coating stage on both battery capacity and internal resistance for the first time. Specifically, an effective neural network model is built based on real data form designed experiments for obtaining reference cathode coating for coin cells. The purpose is to analyze and predict how the battery quality in both charge and discharge scenarios changes with respect to the key factors of coating including its weight and thickness. The results highlight the correlation between mentioned factors and battery quality indices, which could guide manufacturer to identify efficient ways for producing high-quality batteries

Effect of coating operating parameters on electrode physical characteristics and final electrochemical performance of lithium‑ion batteries

The effect of coating parameters of NMC622 cathodes and graphite anodes on their physical structure and half-cell electrochemical performance is evaluated by design of experiments. Coating parameters include the coater comma bar gap, coating ratio and web speed. The electrochemical properties studied are gravimetric and volumetric capacity, rate performance, areal specific impedance (ASI) and C-rate. Differences in the manufacturing effects on the electrode physical structure and electrochemical performance are observed between the electrodes and are modelled by linear regression. The effect of cell coating weight and porosity on half-coin cell electrochemical performance is also evaluated by linear regression. The cathode performance at high gravimetric and volumetric C-rates is mainly influenced by coating weight, whereas porosity is the only explanatory variable for volumetric C-rates of 1C and below. For anode, correlations are only found for the C/20 and 5C gravimetric and volumetric capacities and are related to coating weight. An inverse relationship between ASI and coating weight is observed for cathode, but in general the cell physical characteristics cannot completely explain the observed ASI for both electrodes. The obtained models are useful for the design and robust manufacturing of electrodes since present a quantitative relationship between the coating parameters, cell characteristics and final cell electrochemical performance

Study of the cathode coating-drying manufacturing process by design of experiments

The understanding of traditional battery manufacturing operating conditions on electrode structure and final electrochemical performance is currently limited. In this study, the design of experiments methodology (DoE) is applied for the identification of the main operating variables (factors) of the coating-drying process in the manufacturing of cathodes at the pilot-scale. The experimental design is a saturated design that considers only two settings (levels) for each of the factors. The factors studied are: comma bar gap (80 and 140 µm), coating ratio (110 and 150%), web speed (0.5 and 1.5 m/min), drying temperature of the first oven zone (85 and 110 °C) and drying air speed (5 and 15 m/s). The output variables (responses) include precalendered and calendered physical electrode properties (mass loading, thickness and porosity) as well as gravimetric and volumetric energy capacities. Analysis of variance and multiple linear regression determines the relationship between factors and responses and their statistical significance with a confidence level of 90% (p-value =0.1). Empirical models for the responses are obtained in terms of the statistically significant factors. Results show that comma bar gap and coating ratio are critical parameters since have a direct impact on battery electrochemical performance. The drying temperature is not statistically significant at the conditions studied and therefore is a non-critical parameter. The correlations show a good agreement between the experimental data and the models, resulting in correlation coefficients (R2) as high as 0.99 in some cases. The work demonstrates the applicability of DoE to the manufacturing process of Li-ion batteries at a pilot-scale for the identification of important operating variables and their effect on battery performance. The obtained models are useful in the determination of operating parameters settings to achieve a robust manufacturing process, therefore reducing time and cost

Multiple Gastrointestinal Vascular Variations in a Male Cadaver: A Case Report and Literature Review of Embryonic, Genetic, and Clinicosurgical Implications of Pathogenicity

BACKGROUND: To be acquainted with gastrointestinal vasculature variations is of utmost importance for establishing proper surgical management, improving safety, and decreasing the frequency of iatrogenic errors or complications arising in operational and post-operational settings. CASE REPORT: The subject of the present publication involves a unique case of an 80-year-old Caucasian male who presented with various vascular variations during routine cadaveric dissection. Key variations presented in this report include unique findings such as an abnormal trifurcation of the celiac trunk, a bifurcation of the superior mesenteric artery, and its associated branches; an unusual portocaval system communication; and various renal variations. These variations are examined in an anatomical and clinical context. We further discuss the possible embryologic and genetic mechanisms which may lead to such vascular abnormalities. CONCLUSION: Furthermore, with this report, we aim to demonstrate the strong need for adequate knowledge of vascular variations as well as the important role of pre-operative imaging in the identification of vascular variations and the elimination of iatrogenic errors during surgical procedures

Impact of formulation and slurry properties on lithium-ion electrode manufacturing

The characteristics and performance of lithium-ion batteries typically rely on the precise combination of materials in their component electrodes. Understanding the impact of this formulation and the interdependencies between each component is critical in optimising cell performance. Such optimisation is difficult as the cost and effort for the myriad of possible combinations is too high. This problem is addressed by combining a design of experiments (DoE) and advanced statistical machine learning approach with comprehensive experimental characterisation of electrode slurries and coatings. An industry relevant graphite anode system is used, and with the aid of DoE, less than 30 experiments are defined to map impact of different weight fractions of active material (80–96 wt%), conductive additive (Carbon Black at 1–10 wt%) and a two-component binder system (Carboxymethyl Cellulose (CMC) at 1–3 wt% and Styrene Butadiene Rubber (SBR), at 1–7 wt%). Using Explainable Machine Learning (XML) methods, correlations between the formulation, slurry weight percentage (30–50 wt% in water) and coating speed (1–15 m/min) are quantified. Slurry viscosity, while known to depend on the CMC concentration, is also heavily influenced by carbon black and SBR when at high concentration, as is common in research. Viscosity increasing components also improve adhesion, by improving dispersion and hindering binder migration. Conductivity of the coating on current collector is sensitive to the current collector-coating interface, which makes it a highly useful probe. Improvements in cell capacity are observed with higher viscosity formulations (High weight percentage, CMC content), attributed to reduction in migration and slumping of the slurry on the current collector. SBR had a negative impact at any concentration due to its insulating nature, and carbon black reduces gravimetric capacity when included at high concentrations. The insights from this study facilitate the formulation optimisation of electrodes providing improved slurry design rules for future high performance electrode manufacturing