Cathode Catalyst Layer Design in PEM Water Electrolysis toward Reduced Pt Loading and Hydrogen Crossover

Reducing the use of platinum group metals is crucial for the large-scale deployment of proton exchange membrane (PEM) water electrolysis systems. The optimization of the cathode catalyst layer and decrease of the cathode Pt loading are usually overlooked due to the predominant focus of research on the anode. However, given the close relationship between the rate of hydrogen permeation through the membrane in an operating cell and the local hydrogen concentration near the membrane-cathode interface, the structural design of the cathode catalyst layer is considered to be of pivotal importance for reducing H2 crossover, particularly in combination with the use of thin (≲50 μm) membranes. In this study, we have conducted a detailed investigation on the cathode structural parameters, covering the Pt wt % of the Pt/C electrocatalyst, the type of carbon support (Vulcan and high surface area carbon, HSAC), and the ionomer content, with a goal to reduce Pt loading to 0.025 mgPt/cm2 while minimizing the rate of cell hydrogen crossover. We found that the electrochemical performance is mainly influenced by the changes in the interfacial contact resistance due to variations in the cathode thickness. Both the Pt wt % in Pt/C and the ionomer content showed a positive correlation with the measured H2 in O2% in the anode outlet, whereas the Pt loading exhibited an opposite trend. The rate of hydrogen crossover was analyzed in relation to the calculated local volumetric current density within the cathode catalyst layer. Based on the obtained hydrogen mass transfer coefficient, a cathode catalyst layer comprising 40 wt % Pt on HSAC support with an ionomer-to-carbon (I/C) ratio of 0.35 was found to be an optimum configuration for achieving a low Pt loading of 0.025 mgPt/cm2 and a reduced rate of hydrogen crossover.

Gas Flow Models and Computationally Efficient Methods for Energy Network Optimization

The equations governing gas flow dynamics are computationally challenging for energy network optimization. This paper proposes an efficient solution procedure to enable tractability for an hourly resolved yearly decision horizon. The solution procedure deploys linear and second-order cone gas flow models alternatively based on the length-diameter ratio of pipes, achieving maximum efficiency within accuracy limits. Moreover, it addresses the computational complexity of bidirectional pipe flows by fixing the associated integer variables according to a preceding optimization with a static flow approximation. The procedure also precisely aggregates parallel and serial pipes for increased efficiency. Mathematical derivations and single-pipe analyses substantiate the model selection criterion. Network optimizations validate the accuracy, success rate, and scalability of the procedure, achieving up to 3.1% cost savings compared to static models, enhancing the success rate by a minimum of 96%, and boosting computational efficiency up to 3 orders of magnitude over full dynamic models.

Solvation-Tuned Photoacid as a Stable Light-Driven pH Switch for CO2 Capture and Release

Photoacids are organic molecules that release protons under illumination, providing spatiotemporal control of the pH. Such light-driven pH switches offer the ability to cyclically alter the pH of the medium and are highly attractive for a wide variety of applications, including CO2 capture. Although photoacids such as protonated merocyanine can enable fully reversible pH cycling in water, they have a limited chemical stability against hydrolysis (<24 h). Moreover, these photoacids have low solubility, which limits the pH-switching ability in a buffered solution such as dissolved CO2. In this work, we introduce a simple pathway to dramatically increase stability and solubility of photoacids by tuning their solvation environment in binary solvent mixtures. We show that a preferential solvation of merocyanine by aprotic solvent molecules results in a 60% increase in pH modulation magnitude when compared to the behavior in pure water and can withstand stable cycling for >350 h. Our results suggest that a very high stability of merocyanine photoacids can be achieved in the right solvent mixtures, offering a way to bypass complex structural modifications of photoacid molecules and serving as the key milestone toward their application in a photodriven CO2 capture process.

Influence of Au, Pt, and C Seed Layers on Lithium Nucleation Dynamics for Anode-Free Solid-State Batteries

In the concept of anode-free lithium-ion batteries, cells are manufactured with a bare anode current collector where the lithium metal anode is electrochemically formed from the lithium-containing cathode during the first charge cycle. While this concept has many attractive aspects from a manufacturing and energy density standpoint, stable plating and stripping remain challenging. We have investigated gold, platinum, and amorphous carbon as seed layers placed between the copper current collector and the lithium phosphorus oxynitride thin-film solid electrolyte. These layers guide lithium nucleation and improve the plating and stripping dynamics. All seed layers facilitate reversible lithium plating and stripping even at high current densities up to 8 mA cm-2. Of particular note is the amorphous carbon seed layer, which allowed a significant reduction in plating potential from 300 mV to as low as 50 mV. These results underscore the critical role of seed layers in improving the efficiency of anode-free solid-state batteries and open the door to simplified manufacturing of anode-free battery designs.

A Robust Framework for Generating Adsorption Isotherms to Screen Materials for Carbon Capture

To rank the performance of materials for a given carbon capture process, we rely on pure component isotherms from which we predict the mixture isotherms. For screening a large number of materials, we also increasingly rely on isotherms predicted from molecular simulations. In particular, for such screening studies, it is important that the procedures to generate the data are accurate, reliable, and robust. In this work, we develop an efficient and automated workflow for a meticulous sampling of pure component isotherms. The workflow was tested on a set of metal-organic frameworks (MOFs) and proved to be reliable given different guest molecules. We show that the coupling of our workflow with the Clausius-Clapeyron relation saves CPU time, yet enables us to accurately predict pure component isotherms at the temperatures of interest, starting from a reference isotherm at a given temperature. We also show that one can accurately predict the CO₂ and N₂ mixture isotherms using ideal adsorbed solution theory (IAST). In particular, we show that IAST is a more reliable numerical tool to predict binary adsorption uptakes for a range of pressures, temperatures, and compositions, as it does not rely on the fitting of experimental data, which typically needs to be done with analytical models such as dual-site Langmuir (DSL). This makes IAST a more suitable and general technique to bridge the gap between adsorption (raw) data and process modeling. To demonstrate this point, we show that the ranking of materials, for a standard three-step temperature swing adsorption (TSA) process, can be significantly different depending on the thermodynamic method used to predict binary adsorption data. We show that, for the design of processes that capture CO₂ from low concentration (0.4%) streams, the commonly used methodology to predict mixture isotherms incorrectly assigns up to 33% of the materials as top-performing.

An Ecosystem for Digital Reticular Chemistry

The vastness of the materials design space makes it impractical to explore using traditional brute-force methods, particularly in reticular chemistry. However, machine learning has shown promise in expediting and guiding materials design. Despite numerous successful applications of machine learning to reticular materials, progress in the field has stagnated, possibly because digital chemistry is more an art than a science and its limited accessibility to inexperienced researchers. To address this issue, we present mofdscribe, a software ecosystem tailored to novice and seasoned digital chemists that streamlines the ideation, modeling, and publication process. Though optimized for reticular chemistry, our tools are versatile and can be used in nonreticular materials research. We believe that mofdscribe will enable a more reliable, efficient, and comparable field of digital chemistry.

Characterization of Chemisorbed Species and Active Adsorption Sites in Mg-Al Mixed Metal Oxides for High-Temperature CO2 Capture

Mg-Al mixed metal oxides (MMOs), derived from the decomposition of layered double hydroxides (LDHs), have been purposed as adsorbents for CO₂ capture of industrial plant emissions. To aid in the design and optimization of these materials for CO₂ capture at 200 °C, we have used a combination of solid-state nuclear magnetic resonance (ssNMR) and density functional theory (DFT) to characterize the CO₂ gas sorption products and determine the various sorption sites in Mg-Al MMOs. A comparison of the DFT cluster calculations with the observed ¹³C chemical shifts of the chemisorbed products indicates that mono- and bidentate carbonates are formed at the Mg-O sites with adjacent Al substitution of an Mg atom, while the bicarbonates are formed at Mg-OH sites without adjacent Al substitution. Quantitative ¹³C NMR shows an increase in the relative amount of strongly basic sites, where the monodentate carbonate product is formed, with increasing Al/Mg molar ratios in the MMOs. This detailed understanding of the various basic Mg-O sites presented in MMOs and the formation of the carbonate, bidentate carbonate, and bicarbonate chemisorbed species yields new insights into the mechanism of CO₂ adsorption at 200 °C, which can further aid in the design and capture capacity optimization of the materials.

In Situ Reflectometry and Diffraction Investigation of the Multiscale Structure of p-Type Polysilicon Passivating Contacts for c-Si Solar Cells

The integration of passivating contacts based on a highly doped polycrystalline silicon (poly-Si) layer on top of a thin silicon oxide (SiO_x) layer has been identified as the next step to further increase the conversion efficiency of current mainstream crystalline silicon (c-Si) solar cells. However, the interrelation between the final properties of poly-Si/SiO_x contacts and their fabrication process has not yet been fully unraveled, which is mostly due to the challenge of characterizing thin-film stacks with features in the nanometric range. Here, we apply in situ X-ray reflectometry and diffraction to investigate the multiscale (1 Å-100 nm) structural evolution of poly-Si contacts during annealing up to 900 °C. This allows us to quantify the densification and thinning of the poly-Si layer during annealing as well as to monitor the disruption of the thin SiO_x layer at high temperature >800 °C. Moreover, results obtained on a broader range of thermal profiles, including firing with dwell times of a few seconds, emphasize the impact of high thermal budgets on poly-Si contacts' final properties and thus the importance of ensuring a good control of such high-temperature processes when fabricating c-Si solar cells integrating such passivating contacts. Overall, this study demonstrates the robustness of combining different X-ray elastic scattering techniques (here XRR and GIXRD), which present the unique advantage of being rapid, nondestructive, and applicable on a large sample area, to unravel the multiscale structural evolution of poly-Si contacts in situ during high-temperature processes.

Multimodal Microscale Imaging of Textured Perovskite-Silicon Tandem Solar Cells

Halide perovskite/crystalline silicon (c-Si) tandem solar cells promise power conversion efficiencies beyond the limits of single-junction cells. However, the local light-matter interactions of the perovskite material embedded in this pyramidal multijunction configuration, and the effect on device performance, are not well understood. Here, we characterize the microscale optoelectronic properties of the perovskite semiconductor deposited on different c-Si texturing schemes. We find a strong spatial and spectral dependence of the photoluminescence (PL) on the geometrical surface constructs, which dominates the underlying grain-to-grain PL variation found in halide perovskite films. The PL response is dependent upon the texturing design, with larger pyramids inducing distinct PL spectra for valleys and pyramids, an effect which is mitigated with small pyramids. Further, optimized quasi-Fermi level splittings and PL quantum efficiencies occur when the c-Si large pyramids have had a secondary smoothing etch. Our results suggest that a holistic optimization of the texturing is required to maximize light in- and out-coupling of both absorber layers and there is a fine balance between the optimal geometrical configuration and optoelectronic performance that will guide future device designs.