A model of Near Infrared Diffuse Reflectance Spectroscopy (NIR-DRS) was established for the first time to determine the content of Shengmaxinside I in the honey-fried processing of Rhizoma Cimicifugae. Shengmaxinside I content was determined by high-performance liquid chromatography (HPLC), and the data of the honey-fried processing of Rhizoma Cimicifugae samples from different batches of different origins by NIR-DRS were collected by TQ Analyst 8.0. Partial Least Squares (PLS) analysis was used to establish a near-infrared quantitative model. The determination coefficient R² was 0.9878. The Cross-Validation Root Mean Square Error (RMSECV) was 0.0193%, validating the model with a validation set. The Root Mean Square Error of Prediction (RMSEP) was 0.1064%. The ratio of the standard deviation for the validation samples to the standard error of prediction (RPD) was 5.5130. This method is convenient and efficient, and the experimentally established model has good prediction ability, and can be used for the rapid determination of Shengmaxinside I content in the honey-fried processing of Rhizoma Cimicifugae.

Proton exchange membrane fuel cells (PEMFCs) are leading candidates to decarbonize the transport sector, but widespread deployment will require improvements in lifetime, fuel economy and cost. Here we present the grooved electrode, an alternative electrode structure that enhances PEMFC performance and durability by coupling high ionomer (ion-conducting binder) content for improved H+ transport with grooves for rapid O2 transport. Grooved electrodes provide up to 50% higher performance than state-of-the-art conventional electrodes under standard operating conditions. Fuel cell diagnostics combined with multiphysics modelling demonstrate that grooved electrodes provide facile O2 transport despite their high ionomer content, enabling improved reaction rate uniformity. Grooved electrodes also provide improved durability, with less performance loss after carbon corrosion compared with baseline electrodes. Machine learning analysis demonstrates the potential to further optimize grooved structures for next-generation PEMFCs with enhanced performance and durability, enabling smaller and cheaper fuel cell stacks with higher fuel efficiency.

Correction to: Nature Energy. Published online 25 May 2023. This paper was originally published under a standard Springer Nature license (© The Author(s), under exclusive licence to Springer Nature Limited). It is now available as an open-access paper under a Creative Commons Attribution 4.0 International license, © The Author(s). The error has been corrected in the online version of the article.

Proton exchange membrane fuel cells (PEMFCs) are expected to play a pivotal role in decarbonizing the transportation sector, and particularly heavy-duty vehicles (HDVs). However, improvements in durability are needed for PEMFCs to compete with state-of-the-art power sources for HDVs. Here, we examine how catalyst layer (CL) cracks that are engineered affect the CL durability by using patterned silicon templates to control the CL crack density at the micrometer scale. Electrochemical analyses show that the initial PEMFC performance is relatively unaffected by crack density, but the performance after durability testing was strongly affected. Specifically, CLs with high crack density showed higher performance relative to CLs without cracks after application of a carbon corrosion accelerated stress test. Electrochemical analyses coupled with X-ray computed tomography and scanning transmission electron microscopy with energy dispersive X-ray spectroscopy showed that the cracks provide shorter oxygen diffusion pathways to reaction sites, leading to decreased oxygen transport resistance. Additionally, we observed that the catalyst durability is unaffected by cracks. Our results provide a mechanistic explanation of the role of cracks in CL durability.

The degradation of polymer electrolyte membrane fuel cells (PEMFCs) catalyst layers used for heavy-duty vehicles was examined using a catalyst-specific accelerated stress test (AST). High surface area carbon supported dispersed Pt (Pt/ HSC), annealed Pt (a-Pt/ HSC) and PtCo (PtCo/ HSC) alloy catalysts were examined over the course of 90,000 cycles by measuring changes in mass activity, O2 transport resistance, electrochemical active surface area ( ECSA), catalyst accessibility and ionomer-electrocatalyst interactions. Compared to a-Pt/HSC and Pt/HSC catalyst, the PtCo/HSC showed better initial mass activity, a larger initial mass transport loss, and faster degradation after the first 30k AST cycles, as a large portion of Co leached out during potential cycling. Pt/HSC showed higher initial performance relative to a-Pt/HSC but had faster degradation. STEM characterizations show that the ECSA losses are largely related to Pt dissolution resulting in either catalyst particle growth via the Ostwald ripening mechanism or redeposition in the membrane. Catalyst accessibility measurements showed decreased RH sensitivity for all three samples, while CO impedance measurements revealed a decrease in both Pt-water and carbon-water interactions. This implies that, Pt is either preferentially redepositing on the exterior of the carbon support, or that the ionomer is undergoing morphological changes enabling the enhanced intrusion of mesopores.

Nanoparticles are an important class of materials that exhibit special properties arising from their high surface area-to-volume ratio. Scanning transmission electron microscopy (STEM) has played an important role in nanoparticle characterization, owing to its high spatial resolution, which allows direct visualization of composition and morphology with atomic precision. This typically comes at the cost of sample size, potentially limiting the accuracy and relevance of STEM results, as well as the ability to meaningfully track changes in properties that vary spatially. In this work, automated STEM data acquisition and analysis techniques are employed that enable physical and compositional properties of nanoparticles to be obtained at high resolution over length scales on the order of microns. This is demonstrated by studying the localized effects of potential cycling on electrocatalyst degradation across proton exchange membrane fuel cell cathodes. In contrast to conventional, manual STEM measurements, which produce particle size distributions representing hundreds of particles, these high-throughput automated methods capture tens of thousands of particles and enable nanoparticle size, number density, and composition to be measured as a function of position within the cathode. Comparing the properties of pristine and degraded fuel cells provides statistically robust evidence for the inhomogeneous nature of catalyst degradation across electrodes. These results demonstrate how high-throughput automated STEM techniques can be utilized to investigate local phenomena occurring in nanoparticle systems employed in practical devices.

Memory devices with high speed and high density are highly desired to address the 'memory wall' issue. Here we demonstrated a highly scalable, three-dimensional stackable ferroelectric diode, with its rectifying polarity modulated by the polarization reversal of Hf_0.5Zr_0.5O₂ films. By visualizing the hafnium/zirconium lattice order and oxygen lattice order with atomic-resolution spherical aberration-corrected STEM, we revealed the correlation between the spontaneous polarization of Hf_0.5Zr_0.5O₂ film and the displacement of oxygen atom, thus unambiguously identified the non-centrosymmetric Pca2₁ orthorhombic phase in Hf_0.5Zr_0.5O₂ film. We further implemented this ferroelectric diode in an 8 layers 3D array. Operation speed as high as 20 ns and robust endurance of more than 10⁹ were demonstrated. The built-in nonlinearity of more than 100 guarantees its self-selective property that eliminates the need for external selectors to suppress the leakage current in large array. This work opens up new opportunities for future memory hierarchy evolution.