Energy Technologies

Abstract: In-situ two-dimensional X-ray absorption spectroscopy (XAS) imaging was employed to analyze cerium ion (Ce3+) migration in the through-plane direction in proton exchange membrane fuel cells (PEMFCs), offering fundamental insights supporting improvement of their power density and membrane durability. The transport of Ce3+ was visualized in both unreinforced thick Nafion membranes (Nafion 115, 127 µm) and reinforced thin (12 µm) perfluorosulfonic acid (PFSA) membranes under either an electrical potential gradient or a water activity gradient. The diffusion coefficients of Ce3+ were ascertained based on its behavior after removal of these gradients in both membrane types. Additionally, using a one-dimensional cation transport model, the mobility and electroosmotic drag coefficients of Ce3+ were derived from experimentally obtained data of the thick Nafion membrane. Our measurements also demonstrate that the migration of Ce3+ in the thick membranes was notably impeded by the presence of ferrous ion (Fe2+) impurities. Because Fe2+ is known to accelerate membrane degradation by promoting hydroxyl radical formation, this effect might further exacerbate membrane degradation. It therefore warrants careful consideration.

Microadditive manufacturing has revolutionized the production of complex, nano- to microscale components across various fields. This work investigates two-photon (2P) and three-photon (3P) fluorescence imaging, as well as third-harmonic generation (THG) microscopy, to examine periodic microarchitected lattice structures fabricated using multiphoton lithography (MPL). By immersing the structures in refractive index matching fluids, we demonstrate high-fidelity 3D reconstructions of both fluorescent structures using 2P and 3P microscopy as well as low-fluorescence structures using THG microscopy. These results show that multiphoton fluorescence (MPF) imaging offers reduced signal decay with respect to depth compared to single-photon techniques in the examined structures. We further demonstrate the ability to nondestructively identify intentional internal modifications of the structure that are not immediately visible with scanning electron microscope (SEM) images and compression-induced fractures, highlighting the potential of these techniques for quality control and defect detection in microadditively manufactured components.

Gold nanoparticles (AuNPs) are widely used functional nanomaterials that exhibit adjustable properties depending on their shapes and sizes. Creating a comprehensive dataset of AuNP syntheses is useful for understanding how to control their morphology and size. Here, we employed search-based algorithms and fine-tuned the Llama-2 large language model to extract 492 multi-sourced seed-mediated AuNP synthesis recipes from the literature. With this dataset which we share online, we verified that the type of seed capping agent such as CTAB or citrate plays a crucial role in determining the morphology of the AuNPs, aligning with established findings in the field. We also observe a weak correlation between the final AuNR aspect ratio and silver concentration, although a large variance reduces the significance of this relationship. Overall, our work demonstrates the value of literature-based datasets in advancing knowledge in the field of nanomaterial synthesis for further exploration and better reproducibility.

Light-driven reduction of CO₂ into chemicals using a photoelectrochemical (PEC) approach is considered as a promising way to meet the carbon neutral target. The very top surface of the photoelectrode and semiconductor/electrolyte interface plays a pivotal role in defining the performance for PEC CO₂ reduction. However, such impact remains poorly understood. Here, we report an electrodeposition-annealing route for tailoring surface composition of ZnTe photocathodes. Our work demonstrates that a Zn-rich surface on the ZnTe photocathode is essential to impact the CO₂ reduction activity and selectivity. In particular, the Zn-rich surface not only facilitated the interfacial charge carrier transfer, but also acted as electrocatalyst for boosting carbon product selectivity and suppressing the hydrogen evolution reaction. This work provides a new avenue to optimize the photocathode, as well as improvement of the CO₂RR performance.

Further improvements to lithium-ion and emerging battery technologies can be enabled by an improved understanding of the chemistry and working mechanisms of interphases that form at electrochemically active battery interfaces. However, it is difficult to collect and interpret spectra of interphases for several reasons, including the presence of a variety of compounds. To address this challenge, we herein present a vibrational spectroscopy and X-ray diffraction data library of ten compounds that have been identified as interphase constituents in lithium-ion or emerging battery chemistries. The data library includes attenuated total reflectance Fourier transform infrared spectroscopy, Raman spectroscopy, and X-ray diffraction data, collected in inert atmospheres provided by custom sample chambers. The data library presented in this work (and online repository) simplifies access to reference data that is otherwise either diffusely spread throughout the literature or non-existent, and provides energy storage researchers streamlined access to vital interphase-relevant data that can accelerate battery research efforts.

Solar modules in utility-scale systems are expected to maintain decades of lifetime to rival conventional energy sources. However, cyclic thermomechanical loading often degrades their long-term performance, highlighting the importance of effective design to mitigate thermal expansion mismatches between module materials. Given the complex composition of solar modules, isolating the impact of individual components on overall durability remains a challenging task. In this work, we analyze a comprehensive data set that comprises bill-of-materials (BOM) and thermal cycling power loss from 251 distinct module designs to identify the predominant design factors and their impacts on the thermomechanical durability of modules. The methodology of our analysis combines machine learning modeling (random forest) and Shapley additive explanation (SHAP) to correlate design factors with power loss and interpret the model's decision-making. The interpretation reveals that silicon type (monocrystalline or polycrystalline), encapsulant thickness, busbar numbers, and wafer thickness predominantly influence the degradation. With lower power loss of around 0.6% on average in the SHAP analysis, monocrystalline cells present better durability than polycrystalline cells. This finding is further substantiated by statistical testing on our raw data set. The SHAP analysis also demonstrates that while thicker encapsulants lead to reduced power loss, further increasing their thickness over around 0.6 to 0.7 mm does not yield additional benefits, particularly for the front side one. In addition, other important BOM features such as the number of busbars are analyzed. This study provides a blueprint for utilizing explainable machine learning techniques in a complex material system and can potentially guide future research on optimizing the design of solar modules.

Electrochemical conversion of CO2 to CO is demonstrated with symmetric-structured metal supported solid oxide cells (MS-SOC). Perovskite Pr0.5Sr0.4Mn0.2Fe0.8O3−δ (PSMF) and Pr6O11 catalysts were infiltrated into the MS-SOC cathode and anode, using 3 cycles with firing at 850 °C and 8 cycles with firing at 800 °C, respectively. Upon reduction during operation, the perovskite PSMF was transformed to Ruddlesden-Popper structure with a highly efficient electrocatalytic activity. The impact of operating temperature (600-800 °C) and overpotential (0-1.8 V) on the CO2 conversion was investigated. The highest CO2 conversion of 57.2% was achieved at 750 °C and 1.8 V. During extended operation for 150 h at 750 °C and 1.2 V, a cell demonstrated relatively stable performance, with initial current density of 535 mA cm−2 and CO2 conversion of 23%. Degradation mechanisms were studied by posttest characterization.