This work reports an economical and environmentally friendly, external hydrogen-free method for the selective cleavage of lignin and lignin model compounds into value-added chemicals.

Lignins isolated from representative hardwood, softwood, and grass materials were effectively hydrocracked to aromatics catalyzed by tungsten carbide over activated carbon (W C/AC). The effects of botanical species and fractionation methods on lignin structure and the activity of W C/AC were studied in detail. Gas permeation chromatography (GPC), FTIR, elemental analysis, and 2 D HSQC NMR showed that all the extracted samples shared the basic skeleton of lignin, whereas the fractionation method significantly affected the structure. The organosolv process provided lignin with a structure more similar to the native lignin, which was labile to be depolymerized by W C/AC. Softwood lignins (i.e., spruce and pine) possessed higher molecular weights than hardwood lignins (i.e., poplar and basswood); whereas corn stalk lignin that has noncanonical subunits and exhibited the lowest molecular weight owing to its shorter growth period. β-O-4 bonds were the major linkages in all lignin samples, whereas softwood lignins contained more resistant linkages of β-5 and less β-β than corn stalk and hardwood lignins; as a result, lowest hydrocracking efficiency was obtained in softwood lignins, followed by corn stalk and hardwood lignins. 2 D HSQC NMR spectra of lignin and the liquid oil as well as the solid residue showed that W C/AC exhibited high activity not only in β-O-4 cleavage, but also in deconstruction of other ether linkages between aromatic units, so that high yield of liquid oil was obtained from lignin.

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To enhance the catalytic activity and temper the reaction conditions in the hydrodeoxygenation (HDO) of lignin-derived phenols to arenes, a Co–MoS2–x catalyst was proposed and prepared via a facile strategy. Co oxide was synthesized via a solvothermal method, adsorbed at the edge of MoS2–x , and finally reduced to metallic Co via an in situ spontaneous interfacial redox reaction to form Co–MoS2–x . In the HDO of 4-methylphenol, a 97.4% conversion with toluene selectivity up to 99.6% is obtained at the hitherto lowest reaction temperature of 120 °C. This catalyst also exhibits good versatility in catalyzing HDO of different lignin monomers and even lignin bio-oil into arenes. Notably, Co–MoS2–x is very stable in the HDO reusability study: no deactivation was observed after recycling eight times. The high HDO activity of Co–MoS2–x is attributed to the formation of a metal–vacancy interface and electronic transfer from Co to MoS2–x according to the characterization results and theoretical analysis.

Constructing heterostructured photocatalysts is an efficient method to improve photocatalytic carbon dioxide (CO 2 ) reduction. Herein, holey g-C 3 N 4 (HGN) with rich amino groups (−NH x ) was hybridized with NH 2 -UiO-66 (NUZ) via a facile in situ growth method. NUZ nanocrystals were anchored on HGN via NHx−Zr−O chemical bonding, leading to the uniform dispersion and avoiding the leaching of NUZ, thus showing excellent stability in photocatalysis. The chemically bonded interfacial charge transfer effect originated from the NHx−Zr−O formation efficiently accelerated the separation and migration of charge carriers, improving the photoactivity. Benefiting from the NHx−Zr−O formation, the optimized NUZ/HGN-35% heterojunctions exhibited outstanding activity in the photoreduction of CO 2 to CO (31.6 μmol g −1 h −1 ), which was about 2 and 3 times higher than that of pure NUZ and HGN under visible-light irradiation. This study is expected to provide useful insights for constructing composites with strong interaction for CO 2 reduction, H 2 production, and N 2 reduction.

been described as a key metric for understanding the effects of global warming due to its direct impact on climate change. [2] Extensive modeling with energy-economyenvironment scenarios or projections to keep the global temperature from rising above 1.5 °C by the year 2100 shows that such a positive outlook is only possible if the global energy system is completely decarbonized (i.e., net-zero global CO 2 emissions) by mid-century, followed by active CO 2 removal (i.e., carbon-negative) in the second half of the century. [3] The catalytic conversion of CO 2 to valuable energy-related products (e.g., syngas, CH 4 , CH 3 OH, and longer-chain hydrocarbons) [4] by thermal reforming and hydrogenation, [5][6][7][8][9][10][11] electrocatalysis, [12][13][14] or photocatalysis [15] could occupy an important position in a future carbon-negative economy by directly replacing nonrenewable sources of these molecules, provided that the energy inputs to these processes are themselves derived from renewable sources. [16,17] In this regard, photocatalytic strategies stand out by not requiring a secondary medium of energy storage, and being able to realize the CO 2 conversion into high value-added fuels directly via renewable solar energy without external energy input. [18] Indeed, photocatalytic CO 2 reduction has been considered to be a "kill two birds with one stone" approach for sustainable energy production and greenhouse gas reduction. [19] In contrast, thermocatalytic approachesThe solar-energy-driven photoreduction of CO 2 has recently emerged as a promising approach to directly transform CO 2 into valuable energy sources under mild conditions. As a clean-burning fuel and drop-in replacement for natural gas, CH 4 is an ideal product of CO 2 photoreduction, but the development of highly active and selective semiconductor-based photocatalysts for this important transformation remains challenging. Hence, significant efforts have been made in the search for active, selective, stable, and sustainable photocatalysts. In this review, recent applications of cutting-edge experimental and computational materials design strategies toward the discovery of novel catalysts for CO 2 photocatalytic conversion to CH 4 are systematically summarized. First, insights into effective experimental catalyst engineering strategies, including heterojunctions, defect engineering, cocatalysts, surface modification, facet engineering, and single atoms, are presented. Then, datadriven photocatalyst design spanning density functional theory (DFT) simulations, high-throughput computational screening, and machine learning (ML) is presented through a step-by-step introduction. The combination of DFT, ML, and experiments is emphasized as a powerful solution for accelerating the discovery of novel catalysts for photocatalytic reduction of CO 2 . Last, challenges and perspectives concerning the interplay between experiments and data-driven rational design strategies for the industrialization of large-scale CO 2 photoreduction technologies are described.

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