Gaseous CO2 is transformed photochemically and thermochemically in the presence of H2 to CH4 at millimole per hour per gram of catalyst conversion rates, using visible and near‐infrared photons. The catalyst used to drive this reaction comprises black silicon nanowire supported ruthenium. These results represent a step towards engineering broadband solar fuels tandem photothermal reactors that enable a three‐step process involving i) CO2 capture, ii) gaseous water splitting into H2, and iii) reduction of gaseous CO2 by H2.

The field of solar fuels seeks to harness abundant solar energy by driving useful molecular transformations. Of particular interest is the photodriven conversion of greenhouse gas CO2 into carbon-based fuels and chemical feedstocks, with the ultimate goal of providing a sustainable alternative to traditional fossil fuels. Nonstoichiometric, hydroxylated indium oxide nanoparticles, denoted In2O3-x(OH)y, have been shown to function as active photocatalysts for CO2 reduction to CO via the reverse water gas shift reaction under simulated solar irradiation. However, the relatively wide band gap (2.9 eV) of indium oxide restricts the portion of the solar irradiance that can be utilized to ∼9%, and the elevated reaction temperatures required (150-190 °C) reduce the overall energy efficiency of the process. Herein we report a hybrid catalyst consisting of a vertically aligned silicon nanowire (SiNW) support evenly coated by In2O3-x(OH)y nanoparticles that utilizes the vast majority of the solar irradiance to simultaneously produce both the photogenerated charge carriers and heat required to reduce CO2 to CO at a rate of 22.0 μmol·gcat(-1)·h(-1). Further, improved light harvesting efficiency of the In2O3-x(OH)y/SiNW films due to minimized reflection losses and enhanced light trapping within the SiNW support results in a ∼6-fold increase in photocatalytic conversion rates over identical In2O3-x(OH)y films prepared on roughened glass substrates. The ability of this In2O3-x(OH)y/SiNW hybrid catalyst to perform the dual function of utilizing both light and heat energy provided by the broad-band solar irradiance to drive CO2 reduction reactions represents a general advance that is applicable to a wide range of catalysts in the field of solar fuels.

The development of strategies for increasing the lifetime of photoexcited charge carriers in nanostructured metal oxide semiconductors is important for enhancing their photocatalytic activity. Intensive efforts have been made in tailoring the properties of the nanostructured photocatalysts through different ways, mainly including band-structure engineering, doping, catalyst-support interaction, and loading cocatalysts. In liquid-phase photocatalytic dye degradation and water splitting, it was recently found that nanocrystal superstructure based semiconductors exhibited improved spatial separation of photoexcited charge carriers and enhanced photocatalytic performance. Nevertheless, it remains unknown whether this strategy is applicable in gas-phase photocatalysis. Using porous indium oxide nanorods in catalyzing the reverse water-gas shift reaction as a model system, we demonstrate here that assembling semiconductor nanocrystals into superstructures can also promote gas-phase photocatalytic processes. Transient absorption studies prove that the improved activity is a result of prolonged photoexcited charge carrier lifetimes due to the charge transfer within the nanocrystal network comprising the nanorods. Our study reveals that the spatial charge separation within the nanocrystal networks could also benefit gas-phase photocatalysis and sheds light on the design principles of efficient nanocrystal superstructure based photocatalysts.

Gaseous CO2 is transformed to CH4 at ambient temperature at high rates under intense solar-simulated radiation over sputtered Ru supported on Si-based photonic crystals.

Sunlight‐driven catalytic hydrogenation of CO2 is an important reaction that generates useful chemicals and fuels and if operated at industrial scales can decrease greenhouse gas CO2 emissions into the atmosphere. In this work, the photomethanation of CO2 over highly dispersed nanostructured RuO2 catalysts on 3D silicon photonic crystal supports, achieving impressive conversion rates as high as 4.4 mmol gcat−1 h−1 at ambient temperatures under high‐intensity solar simulated irradiation, is reported. This performance is an order of magnitude greater than photomethanation rates achieved over control samples made of nanostructured RuO2 on silicon wafers. The high absorption and unique light‐harvesting properties of the silicon photonic crystal across the entire solar spectral wavelength range coupled with its large surface area are proposed to be responsible for the high methanation rates of the RuO2 photocatalyst. A density functional theory study on the reaction of CO2 with H2 revealed that H2 splits on the surface of the RuO2 to form hydroxyl groups that participate in the overall photomethanation process.

In article number https://doi.org/10.1002/aenm.201702277, Geoffrey A. Ozin and co‐workers report that the photomethanation of CO2 over highly dispersed nanostructured RuO2 catalysts on 3D silicon photonic crystal supports achieves impressive conversion rates as high as 4.4 mmol gcat−1 h−1 at ambient temperatures under high‐intensity solar simulated irradiation. This performance is an order of magnitude greater than photomethanation rates achieved over control samples made of nanostructured RuO2 on silicon wafers.

With the emergence of a new pandemic worldwide, a novel strategy to approach it has emerged. Several initiatives under the umbrella of "open science" are contributing to tackle this unprecedented situation. In particular, the "R Language and Environment for Statistical Computing" [1, 2] offers an excellent tool and ecosystem for approaches focusing on open science and reproducible results. Hence it is not surprising that with the onset of the pandemic, a large number of R packages and resources were made available for researches working in the pandemic. In this paper, we present an R package that allows users to access and analyze worldwide data from resources publicly available. We will introduce the covid19.analytics package [3], focusing in its capabilities and presenting a particular study case where we describe how to deploy the COVID19.ANALYTICS Dashboard Explorer.