X-ray Tomography Applied to Electrochemical Devices and Electrocatalysis

Comprehensive Analysis of Wettability in Waterproofed Gas Diffusion Layers for Polymer Electrolyte Fuel Cells

In polymer electrolyte fuel cells (PEFCs), the gas diffusion layer (GDL) is crucial for managing the flooding tolerance, which is the ability to remove the water produced during power generation from the assembled cell. However, an improved understanding of the properties of GDLs is required to develop effective waterproofing strategies. This study investigated the influence of the polytetrafluoroethylene (PTFE) content on the pore diameter, porosity, wettability, water saturation, and flooding tolerance of waterproofed carbon papers as cathode GDLs in PEFCs. The addition of minimal PTFE (∼6 wt %) to carbon paper provided external waterproofing, whereas internal waterproofing was achieved at a higher PTFE content (∼13 wt %). However, excessive PTFE (∼37 wt %) led to macropore collapse within the carbon paper, reducing fuel cell performance. Although PTFE addition was expected to improve the flooding tolerance, operando synchrotron X-ray radiography revealed that the water saturation level in carbon paper increased with increasing PTFE content. These findings provide a benchmark for assessing whether GDLs meet the flooding tolerance requirements of PEFCs and may be applicable to waterproofed GDLs in electrochemical devices for water and CO2 electrolysis.

Generative Artificial Intelligence for Designing Multi-Scale Hydrogen Fuel Cell Catalyst Layer Nanostructures

Multiscale design of catalyst layers (CLs) is important to advancing hydrogen electrochemical conversion devices toward commercialized deployment, which has nevertheless been greatly hampered by the complex interplay among multiscale CL components, high synthesis cost and vast design space. We lack rational design and optimization techniques that can accurately reflect the nanostructure-performance relationship and cost-effectively search the design space. Here, we fill this gap with a deep generative artificial intelligence (AI) framework, GLIDER, that integrates recent generative AI, data-driven surrogate techniques and collective intelligence to efficiently search the optimal CL nanostructures driven by their electrochemical performance. GLIDER achieves realistic multiscale CL digital generation by leveraging the dimensionality-reduction ability of quantized vector-variational autoencoder. The powerful generative capability of GLIDER allows the efficient search of the optimal design parameters for the Pt-carbon-ionomer nanostructures of CLs. We also demonstrate that GLIDER is transferable to other fuel cell electrode microstructure generation, e.g., fibrous gas diffusion layers and solid oxide fuel cell anode. GLIDER is of potential as a digital tool for the design and optimization of broad electrochemical energy devices.

Recent development and applications of differential electrochemical mass spectrometry in emerging energy conversion and storage solutions

Electrochemical energy conversion and storage are playing an increasingly important role in shaping the sustainable future. Differential electrochemical mass spectrometry (DEMS) offers an operando and cost-effective tool to monitor the evolution of gaseous/volatile intermediates and products during these processes. It can deliver potential-, time-, mass- and space-resolved signals which facilitate the understanding of reaction kinetics. In this review, we show the latest developments and applications of DEMS in various energy-related electrochemical reactions from three distinct perspectives. (I) What is DEMS addresses the working principles and key components of DEMS, highlighting the new and distinct instrumental configurations for different applications. (II) How to use DEMS tackles practical matters including the electrochemical test protocols, quantification of both potential and mass signals, and error analysis. (III) Where to apply DEMS is the focus of this review, dealing with concrete examples and unique values of DEMS studies in both energy conversion applications (CO2 reduction, water electrolysis, carbon corrosion, N-related catalysis, electrosynthesis, fuel cells, photo-electrocatalysis and beyond) and energy storage applications (Li-ion batteries and beyond, metal-air batteries, supercapacitors and flow batteries). The recent development of DEMS-hyphenated techniques and the outlook of the DEMS technique are discussed at the end. As DEMS celebrates its 40th anniversary in 2024, we hope this review can offer electrochemistry researchers a comprehensive understanding of the latest developments of DEMS and will inspire them to tackle emerging scientific questions using DEMS.

Investigation of the Single-Particle Scale Structure-Activity Relationship Providing New Insights for the Development of High-Performance Batteries

As electric vehicles, portable electronic devices, and tools have increasingly high requirements for battery energy density and power density, constantly improving battery performance is a research focus. Accurate measurement of the structure-activity relationship of active materials is key to advancing the research of high-performance batteries. However, conventional performance tests of active materials are based on the electrochemical measurement of porous composite electrodes containing active materials, polymer binders, and conductive carbon additives, which cannot establish an accurate structure-activity relationship with the physical characterization of microregions. In this review, in order to promote the accurate measurement and understanding of the structure-activity relationship of materials, the electrochemical measurement and physical characterization of energy storage materials at single-particle scale are reviewed. The potential problems and possible improvement schemes of the single particle electrochemical measurement and physical characterization are proposed. Their potential applications in single particle electrochemical simulation and machine learning are prospected. This review aims to promote the further application of single particle electrochemical measurement and physical characterization in energy storage materials, hoping to achieve 3D unified evaluation of physical characterization, electrochemical measurement, and theoretical simulation at the single particle scale to provide new inspiration for the development of high-performance batteries.

Cathode|Electrolyte Interface Engineering by a Hydrogel Polymer Electrolyte for a 3D Porous High-Voltage Cathode Material in a Quasi-Solid-State Zinc Metal Battery by In Situ Polymerization

This work highlights the development of a superior cathode|electrolyte interface for the quasi solid-state rechargeable zinc metal battery (QSS-RZMB) by a novel hydrogel polymer electrolyte using an ultraviolet (UV) light-assisted in situ polymerization strategy. By integrating the cathode with a thin layer of the hydrogel polymer electrolyte, this technique produces an integrated interface that ensures quick Zn2+ ion conduction. The coexistence of nanowires for direct electron routes and the enhanced electrolyte ion infiltration and diffusion by the 3D porous flower structure with a wide open surface of the Zn-MnO electrode complements the interface formation during the in situ polymerization process. The QSS-RZMB configured with an integrated cathode (i-Zn-MnO) and the hydrogel polymer electrolyte (PHPZ-30) as the separator yields a comparable specific energy density of 214.14 Wh kg-1 with that of its liquid counterpart (240.38 Wh kg-1, 0.5 M Zn(CF3SO3)2 aqueous electrolyte). Other noteworthy features of the presented QSS-RZMB system include its superior cycle life of over 1000 charge-discharge cycles and 85% capacity retention with 99% coulombic efficiency at the current density of 1.0 A g-1, compared to only 60% capacity retention over 500 charge-discharge cycles displayed by the liquid-state system under the same operating conditions.

Fully Integrated Multiplexed Wristwatch for Real-Time Monitoring of Electrolyte Ions in Sweat

Considerable progress has already been made in sweat sensors based on electrochemical methods to realize real-time monitoring of biomarkers. However, realizing long-term monitoring of multiple targets at the atomic level remains extremely challenging, in terms of designing stable solid contact (SC) interfaces and fully integrating multiple modules for large-scale applications of sweat sensors. Herein, a fully integrated wristwatch was designed using mass-manufactured sensor arrays based on hierarchical multilayer-pore cross-linked N-doped porous carbon coated by reduced graphene oxide (NPCs@rGO-950) microspheres with high hydrophobicity as core SC, and highly selective monitoring simultaneously for K+, Na+, and Ca2+ ions in human sweat was achieved, exhibiting near-Nernst responses almost without forming an interfacial water layer. Combined with computed tomography, solid-solid interface potential diffusion simulation results reveal extremely low interface diffusion potential and high interface capacitance (598 μF), ensuring the excellent potential stability, reversibility, repeatability, and selectivity of sensor arrays. The developed highly integrated-multiplexed wristwatch with multiple modules, including SC, sensor array, microfluidic chip, signal transduction, signal processing, and data visualization, achieved reliable real-time monitoring for K+, Na+, and Ca2+ ion concentrations in sweat. Ingenious material design, scalable sensor fabrication, and electrical integration of multimodule wearables lay the foundation for developing reliable sweat-sensing systems for health monitoring.

Unveiling the Inner Structure of Micrometric Hollow Polymeric Fibers Using Synchrotron X-Ray Nanotomography

In this study, a novel application of synchrotron X-ray nanotomography based on high-resolution full-field transmission X-ray microscopy for characterizing the structure and morphology of micrometric hollow polymeric fibers is presented. By employing postimage analysis using an open-source software such as Tomviz and ImageJ, various key parameters in fiber morphology, including diameter, wall thickness, wall thickness distribution, pore size, porosity, and surface roughness, were assessed. Electrospun polycaprolactone fibers with micrometric diameters and submicrometric features with induced porosity via gas dissolution foaming were used to this aim. The acquired synchrotron X-ray nanotomography data were analyzed using two approaches: 3D tomographic reconstruction and 2D radiographic projection-based analysis. The results of the combination of both approaches demonstrate unique capabilities of this technique, not achievable by other available techniques, allowing for a full characterization of the internal and external morphology and structure of the fibers as well as to obtain valuable qualitative insights into the overall fiber structure.