There is considerable interest in making use of solar energy through photosynthesis to create alternative forms of fuel. Here, we show that photosystem I from a thermophilic bacterium and cytochrome-c(6) can, in combination with a platinum catalyst, generate a stable supply of hydrogen in vitro upon illumination. The self-organized platinization of the photosystem I nanoparticles allows electron transport from sodium ascorbate to photosystem I via cytochrome-c(6) and finally to the platinum catalyst, where hydrogen gas is formed. Our system produces hydrogen at temperatures up to 55 degrees C and is temporally stable for >85 days with no decrease in hydrogen yield when tested intermittently. The maximum yield is approximately 5.5 micromol H(2) h(-1) mg(-1) chlorophyll and is estimated to be approximately 25-fold greater than current biomass-to-fuel strategies. Future work will further improve this yield by increasing the kinetics of electron transfer, extending the spectral response and replacing the platinum catalyst with a renewable hydrogenase.

The eighteenth data release (DR18) of the Sloan Digital Sky Survey (SDSS) is the first one for SDSS-V, the fifth generation of the survey. SDSS-V comprises three primary scientific programs or “Mappers”: the Milky Way Mapper (MWM), the Black Hole Mapper (BHM), and the Local Volume Mapper. This data release contains extensive targeting information for the two multiobject spectroscopy programs (MWM and BHM), including input catalogs and selection functions for their numerous scientific objectives. We describe the production of the targeting databases and their calibration and scientifically focused components. DR18 also includes ∼25,000 new SDSS spectra and supplemental information for X-ray sources identified by eROSITA in its eFEDS field. We present updates to some of the SDSS software pipelines and preview changes anticipated for DR19. We also describe three value-added catalogs (VACs) based on SDSS-IV data that have been published since DR17, and one VAC based on the SDSS-V data in the eFEDS field.

The functionality of modern cities relies heavily on interdependent infrastructure systems such as those for water, power, and transportation. Disruptions often propagate within and across physical infrastructure networks and result in catastrophic consequences. The reaction of communities to disasters (e.g., seeking alternative resource sources) may further transfer and aggravate the burden on surviving infrastructures, which may facilitate cascading secondary disruptions. Hence, a holistic analysis framework that integrates infrastructure interdependencies and human community behaviors is needed to evaluate a city's vulnerability to disruptions and to assess the impact of a disaster. To this end, we develop a game‐theoretical equilibrium model in a multilayer infrastructure network to systematically investigate the mutual influence between the infrastructures and the communities. Two types of infrastructure failure patterns are formulated to capture general network interdependencies; network equilibrium is extended into infrastructure and community systems to address redistribution of demand for life‐supporting resources; the societal impact of disasters is estimated based on communities’ resource demand loss, cost increase, as well as total infrastructure failures. A real‐world case study based on Maiduguri, Nigeria, is implemented to demonstrate the proposed model and algorithm, and to reveal insights.

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