Local Charge Transfer Unveils Antideactivation of Ru at High Potentials for the Alkaline Hydrogen Oxidation Reaction.

The activity of Ru-based alkaline hydrogen oxidation reaction (HOR) electrocatalysts usually decreases rapidly at potentials higher than 0.1 V (vs a reversible hydrogen electrode (RHE)), which significantly limits the lifetime of fuel cells. It is found that this phenomenon is caused by the overadsorption of the O species due to the overcharging of Ru nanoparticles at high potentials. Here, Mn1Ox(OH)y clusters-modified Ru nanoparticles (Mn1Ox(OH)y@Ru/C) were prepared to promote charge transfer from overcharged Ru nanoparticles to Mn1Ox(OH)y clusters. Mn1Ox(OH)y@Ru/C exhibits high HOR activity and stability over a wide potential range of 0-1.0 V. Moreover, a hydroxide exchange membrane fuel cell with a Mn1Ox(OH)y@Ru/C anode delivers a high peak power density of 1.731 W cm-2, much superior to that of a Pt/C anode. In situ X-ray absorption fine structure (XAFS) analysis and density functional theory (DFT) calculations reveal that Mn in Mn1Ox(OH)y clusters could receive more electrons from overcharged Ru at higher potentials and significantly decrease the overadsorption of the O species on Ru, thus permitting the HOR on Ru to proceed at high potentials. This study provides guidance for the design of alkaline HOR catalysts without activity decay at high potentials.

Ultralow-Loading Ruthenium-Iridium Fuel Cell Catalysts Dispersed on Zn-N Species-Doped Carbon.

Developing low-loading platinum-group-metal (PGM) catalysts is one of the key challenges in commercializing anion-exchange-membrane-fuel-cells (AEMFCs), especially for hydrogen oxidation reaction (HOR). Here, ruthenium-iridium nanoparticles being deposited on a Zn-N species-doped carbon carrier (Ru6Ir/Zn-N-C) are synthesized and used as an anodic catalyst for AEMFCs. Ru6Ir/Zn-N-C shows extremely high mass activity (5.87 A mgPGM -1) and exchange current density (0.92 mA cm-2), which is 15.1 and 3.9 times that of commercial Pt/C, respectively. Based on the Ru6Ir/Zn-N-C AEMFCs achieve a peak power density of 1.50 W cm-2, surpassing the state-of-the-art commercial PtRu catalysts and the power ratio of the normalized loading is 14.01 W mgPGM anode -1 or 5.89 W mgPGM -1 after decreasing the anode loading (87.49 µg cm-2) or the total PGM loading (0.111 mg cm-2), satisfying the US Department of Energy's PGM loading target. Moreover, the solvent and solute isotope separation method is used for the first time to reveal the kinetic process of HOR, which shows the reaction is influenced by the adsorption of H2O and OH-. The improvement of the hydrogen bond network connectivity of the electric double layer by adjusting the interfacial H2O structure together with the optimized HBE and OHBE is proposed to be responsible for the high HOR activity of Ru6Ir/Zn-N-C.

A 10-m national-scale map of ground-mounted photovoltaic power stations in China of 2020.

We provide a remote sensing derived dataset for large-scale ground-mounted photovoltaic (PV) power stations in China of 2020, which has high spatial resolution of 10 meters. The dataset is based on the Google Earth Engine (GEE) cloud computing platform via random forest classifier and active learning strategy. Specifically, ground samples are carefully collected across China via both field survey and visual interpretation. Afterwards, spectral and texture features are calculated from publicly available Sentinel-2 imagery. Meanwhile, topographic features consisting of slope and aspect that are sensitive to PV locations are also included, aiming to construct a multi-dimensional and discriminative feature space. Finally, the trained random forest model is adopted to predict PV power stations of China parallelly on GEE. Technical validation has been carefully performed across China which achieved a satisfactory accuracy over 89%. Above all, as the first publicly released 10-m national-scale distribution dataset of China's ground-mounted PV power stations, it can provide data references for relevant researchers in fields such as energy, land, remote sensing and environmental sciences.

V-O Species-Doped Carbon Frameworks Loaded with Ru Nanoparticles as Highly Efficient and CO-Tolerant Catalysts for Alkaline Hydrogen Oxidation.

Efficient and CO-tolerant catalysts for alkaline hydrogen oxidation (HOR) are vital to the commercial application of anion exchange membrane fuel cells (AEMFCs). Herein, a robust Ru-based catalyst (Ru/VOC) with ultrasmall Ru nanoparticles supported on carbon frameworks with atomically dispersed V-O species is prepared elaborately. The catalyst exhibits a remarkable mass activity of 3.44 mA µgPGM, which is 31.3 times that of Ru/C and even 4.7 times higher than that of Pt/C. Moreover, the Ru/VOC anode can achieve a peak power density (PPD) of 1.194 W cm-2, much superior to that of Ru/C anode and even better than that of Pt/C anode. In addition, the catalyst also exhibits superior stability and exceptional CO tolerance. Experimental results and density functional theory (DFT) calculations demonstrate that V-O species are ideal OH- adsorption sites, which allow Ru to release more sites for hydrogen adsorption. Furthermore, the electron transfer from Ru nanoparticles to the carbon substrate regulates the electronic structure of Ru, reducing the hydrogen binding energy (HBE) and the CO adsorption energy on Ru, thus boosting the alkaline HOR performance and CO tolerance of the catalyst. This is the first report that oxophilic single atoms distributed on carbon frameworks serve as OH- adsorption sites for efficient hydrogen oxidation, opening up new guidance for the elaborate design of high-activity catalysts for the alkaline HOR.

Weak ergodicity breaking and anomalous diffusion in collective motion of active particles under spatiotemporal disorder.

The effects of spatiotemporal disorder, i.e., both the noise and quenched disorder, on the dynamics of active particles in two dimensions are investigated. We demonstrate that within the tailored parameter regime, nonergodic superdiffusion and nonergodic subdiffusion occur in the system, identified by the observable quantities (the mean squared displacement and ergodicity-breaking parameter) averaged over both the noise and realizations of quenched disorder. Their origins are attributed to the competition effects between the neighbor alignment and spatiotemporal disorder on the collective motion of active particles. These results may be helpful for further understanding the nonequilibrium transport process of active particles, as well as for detection of the transport of self-propelled particles in complex and crowded environments.