Engineering topics
Zenyuk, Iryna V. (ORCID:0000000216120475)
Publications and source records attributed to Zenyuk, Iryna V. (ORCID:0000000216120475).
Tailoring the Mass Transport to Achieve High-Performing Unitized Regenerative Fuel Cells Considering Practical Operating Conditions
Unitized regenerative fuel cells (URFCs) convert electrical energy to chemical bonds in hydrogen during charge and convert chemical energy to output electricity during discharge, offering a promising solution to long-term energy storage. Recent studies indicate that the round-trip-voltaic efficiency (RTE) and longevity of URFCs are limited by complex mass transport during charging and discharging. Here, we first investigate how different porous transport layer (PTL) structures can impact URFC performance. The preferred PTL has a low tortuosity and high porosity, leading to a high RTE above 50% at 1 A cm −2 using Nafion 212. Moreover, thicker membranes, such as Solvay 90, are required to ensure mechanical stability and minimize H 2 crossover when operating under high differential pressure. Although this assembly inevitably leads to a higher ohmic loss, the RTE can be improved by further tailoring the electrode structures to facilitate mass transport by using supported catalyst, which still achieves over 50% RTEs at 1 A cm −2 . Optimization of porous structure to mitigate mass transport resistance with appropriate materials down selection considering practical application requirements can be a key design principle for achieving high-performing URFCs.
Elucidating electrochemical nitrate and nitrite reduction over atomically-dispersed transition metal sites
Abstract Electrocatalytic reduction of waste nitrates (NO 3 − ) enables the synthesis of ammonia (NH 3 ) in a carbon neutral and decentralized manner. Atomically dispersed metal-nitrogen-carbon (M-N-C) catalysts demonstrate a high catalytic activity and uniquely favor mono-nitrogen products. However, the reaction fundamentals remain largely underexplored. Herein, we report a set of 14; 3 d -, 4 d -, 5 d - and f -block M-N-C catalysts. The selectivity and activity of NO 3 − reduction to NH 3 in neutral media, with a specific focus on deciphering the role of the NO 2 − intermediate in the reaction cascade, reveals strong correlations (R=0.9) between the NO 2 − reduction activity and NO 3 − reduction selectivity for NH 3 . Moreover, theoretical computations reveal the associative/dissociative adsorption pathways for NO 2 − evolution, over the normal M-N 4 sites and their oxo-form (O-M-N 4 ) for oxyphilic metals. This work provides a platform for designing multi-element NO 3 RR cascades with single-atom sites or their hybridization with extended catalytic surfaces.
Lithium Metal Battery Quality Control via Transformer–CNN Segmentation
Lithium metal battery (LMB) has the potential to be the next-generation battery system because of its high theoretical energy density. However, defects known as dendrites are formed by heterogeneous lithium (Li) plating, which hinders the development and utilization of LMBs. Non-destructive techniques to observe the dendrite morphology often use X-ray computed tomography (XCT) to provide cross-sectional views. To retrieve three-dimensional structures inside a battery, image segmentation becomes essential to quantitatively analyze XCT images. This work proposes a new semantic segmentation approach using a transformer-based neural network called TransforCNN that is capable of segmenting out dendrites from XCT data. In addition, we compare the performance of the proposed TransforCNN with three other algorithms, U-Net, Y-Net, and E-Net, consisting of an ensemble network model for XCT analysis. Our results show the advantages of using TransforCNN when evaluating over-segmentation metrics, such as mean intersection over union (mIoU) and mean Dice similarity coefficient (mDSC), as well as through several qualitatively comparative visualizations.
Understanding Platinum Ionomer Interface Properties of Polymer Electrolyte Fuel Cells
A well-designed cathode catalyst layer with optimal ionomer distribution is critical to minimizing amount of Platinum (Pt) content in polymer electrolyte fuel cells (PEFCs). The impact of Pt loading, ionomer content and carbon support types on the catalyst/ionomer interface were also investigated at dry and wet conditions. Higher Pt loadings resulted in higher double layer capacity (C dl ) and similar electrochemical surface area (ECSA) due to well dispersed ionic phase material. Higher ionomer content resulted in higher ionic conductivity but also showed similar SO 3 − group coverage. High surface area (HSA) carbon support had larger ECSA and C dl at both dry and wet conditions, as less agglomerated Pt was well dispersed in the meso-pores of the support. Lower SO 3 − group coverages were observed for HSA carbon than for Vulcan carbon due to Pt particles being buried within the porous HSA carbon support. The effect of cell conditioning and voltage recovery on the PEFC cathode catalyst layer was shown to have minimal impact on SO 3 − group coverage despite a decrease in C dl and ECSA due to the size increase of Pt particles. At dry condition, a significant increases in SO 3 − group coverage were observed for all MEAs due to higher adsorptivity of ionomer in dry conditions.
Observation of Preferential Pathways for Oxygen Removal through Porous Transport Layers of Polymer Electrolyte Water Electrolyzers
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Development of low temperature fuel cell holders for Operando x-ray micro and nano computed tomography to visualize water distribution
Abstract Synchrotron x-ray imaging techniques, like x-ray computed tomography (CT) and radiography have proven instrumental in expanding the communities knowledge of complex transport and reaction kinetics in electrochemical devices such as fuel cells and electrolyzers. This work presents the development of novel x-ray CT imaging techniques for operando visualization of water within low temperature fuel cells at spatial resolutions spanning the micro and nano scales. The design of operando sample holders, for both micro x-ray CT and nano CT experiments is described in depth, and prototypes of these sample holders were evaluated across a set of requirements, the most important of which are x-ray transmissibility, electrical conductivity and mechanical stability. Water segmentation from micro x-ray CT data was enabled by an image subtraction method, where the image without water is subtracted from the one with water. Through iterative experimentations, the operando nano CT cell was developed to optimize mechanical compression, electric conductivity and gas flow. While three-dimensional fuel cell reconstructions were shown possible, there remain challenges to overcome at typical lower energies (8 keV) due to beam damage, whereas it is not as significant for higher energies (>17.5 keV).