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Register a new userZinc Electrode Shape-Change in Secondary Air Batteries: A 2D Modeling Approach
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Zinc-air batteries offer large specific energy densities, while relying on abundant and non-toxic materials. In this paper, we present the first multi-dimensional simulations of zinc-air batteries. We refine our existing theory-based model of secondary zinc-air systems. The model comprises thermodynamically consistent multi-species transport in alkaline electrolytes, formation and dissolution of metallic zinc and passivating zinc oxide, as well as multi-phase coexistence in gas diffusion electrodes. For the first time, we simulate zinc shape-change during battery cycling by modeling convection of zinc solids. We validate our model with in-situ tomography of commercial button cells. Two-dimensional volume-averaged simulations of cell voltage and zinc electrode morphology during discharge agree with these measurements. Thus, we can study how electrolyte carbonation limits shelf-life and how zinc shape-change limits cycle-life. The charging current is found to be the major contributor to cycle-life limitations. Finally, we optimize initial anode structure and charge-discharge protocols for improved performance and cycle-ability.
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This paper presents a combined theoretical and experimental investigation of aqueous near-neutral electrolytes based on chloride salts for rechargeable zinc-air batteries (ZABs). The resilience of near-neutral chloride electrolytes in air could extend ZAB lifetime, but theory-based simulations predict that such electrolytes are vulnerable to other challenges including pH instability and the unwanted precipitation of mixed zinc hydroxide chloride products. In this work, we combine theory-based simulations with experimental methods such as full cell cycling, operando pH measurements, ex-situ XRD, SEM, and EDS characterization to investigate the performance of ZABs with aqueous chloride electrolytes. The experimental characterization of near-neutral ZAB cells observes the predicted pH instability and confirms the composition of the final discharge products. Steps to promote greater pH stability and control the precipitation of discharge products are proposed.
Aqueous zinc-air batteries (ZABs) are a low-cost, safe, and sustainable technology for stationary energy storage. ZABs with pH-buffered near-neutral electrolytes have the potential for longer lifetime compared to traditional alkaline ZABs due to the slower absorption of carbonates at non-alkaline pH values. However, existing near-neutral electrolytes often contain halide salts, which are corrosive and threaten the precipitation of ZnO as the dominant discharge product. This paper presents a method for designing halide-free aqueous ZAB electrolytes using thermodynamic descriptors to computationally screen components. The dynamic performance of a ZAB with one possible halide-free aqueous electrolyte based on organic salts is simulated using an advanced method of continuum modeling, and the results are validated by experiments. XRD, SEM, and EDS measurements of Zn electrodes show that ZnO is the dominant discharge product, and operando pH measurements confirm the stability of the electrolyte pH during cell cycling. Long-term full cell cycling tests are performed, and RRDE measurements elucidate the mechanism of ORR and OER. Our analysis shows that aqueous electrolytes containing organic salts could be a promising field of research for zinc-based batteries, due to their Zn$^{2+}$ chelating and pH buffering properties. We discuss the remaining challenges including the electrochemical stability of the electrolyte components.
A thick electrode with high areal capacity has been developed as a strategy for high-energy-density lithium-ion batteries, but thick electrodes have difficulties in manufacturing and limitations in ion transport. Here, we reported a new manufacturing approach for ultra-thick electrode with aligned structure, called structure electrode additive manufacturing or SEAM, which aligns active materials to the through-thicknesses direction of electrodes using shear flow and a designed printing path. The ultra-thick electrodes with high loading of active materials, low tortuous structure, and good structure stability resulting from a simple and scalable SEAM lead to rapid ion transport and fast electrolyte infusion, delivering a higher areal capacity than slurry-casted thick electrodes. SEAM shows strengths in design flexibility and scalability, which allows the production of practical high energy/power density structure electrodes.
In this work, we develop a combined convolutional neural networks (CNNs) and finite element method (FEM) to examine the effective thermal properties of composite phase change materials (CPCMs) consisting of paraffin and copper foam. In this approach, first the CPCM microstructures are modeled using FEM and next the image dataset with corresponding thermal properties is created. The image dataset is subsequently used to train and test the CNN performance, which is then compared with the performance of a popular network architecture for image classification tasks. The predicted thermal properties are employed to define the properties of the CPCM material of a battery pack. The heat generation and electrochemical response of a Li-ion cell during the charging/discharging is simulated by applying Newman battery model. Thermal management is achieved by the latent heat of paraffin, with copper foam for enhancing the thermal conductivity. The multiscale model is finally developed using FEM to investigate the effectiveness of the thermal management of the battery pack. In these models the thermal properties estimated by the FEM and the CNN are employed to define the CPCM materials properties of a battery pack. Our results confirm that the model developed on the basis of a CNN can evaluate the effectiveness of the battery packs thermal management system with an excellent accuracy in comparison with the original FEM models.
In the lithium-ion battery literature, discharges followed by a relaxation to equilibrium are frequently used to validate models and their parametrizations. Good agreement with experiment during discharge is easily attained with a pseudo-two-dimensional model such as the Doyle-Fuller-Newman (DFN) model. The relaxation portion, however, is typically not well-reproduced, with the relaxation in experiments occurring much more slowly than in models. In this study, using a model that includes a size distribution of the active material particles, we give a physical explanation for the slow relaxation phenomenon. This model, the Many-Particle-DFN (MP-DFN), is compared against discharge and relaxation data from the literature, and optimal fits of the size distribution parameters (mean and variance), as well as solid-state diffusivities, are found using numerical optimization. The voltage after relaxation is captured by careful choice of the current cut-off time, allowing a single set of physical parameters to be used for all C-rates, in contrast to previous studies. We find that the MP-DFN can accurately reproduce the slow relaxation, across a range of C-rates, whereas the DFN cannot. Size distributions allow for greater internal heterogeneities, giving a natural origin of slower relaxation timescales that may be relevant in other, as yet explained, battery behavior.
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