Over the past decades, advances in science and technology have greatly benefitted the society. However, the exploitation of fossil fuels and excessive emissions of polluting gases have disturbed the balance of the normal carbon cycle, causing serious environmental issues and energy crises. Global warming caused by heavy CO2 emissions is driving new attempts to mitigate the increase in the concentration of atmospheric CO2. Significant efforts have been devoted for CO2 conversion. To date, the electroreduction of CO2, which is highly efficient and offers a promising strategy for both storing energy and managing the global carbon balance, has attracted great attention. In addition, the electrosynthesis of value-added C2+ products from CO2 addresses the need for the long-term storage of renewable energy. Therefore, developing catalysts that function under ambient conditions to produce C2 selectively over C1 products will increase the utility of renewable feedstocks in industrial chemistry applications. Recently, great progress has been made in the development of materials for electrocatalytic CO2 reduction (ECR) toward C2+ products; however, some issues (e.g., low selectivity, low current efficiency, and poor durability) remain to be addressed. In addition, the elementary reaction mechanism of each C2+ product remains unclear, contributing to the blindness of catalyst design. In this regard, the development of proposed mechanisms of ECR toward C2+ products is summarized herein. The key to generating C2+ products is improving the chances of C-C coupling. Test conditions significantly influence the reaction path of the catalyst. Thus, three different paths that that are most likely to occur during ECR to C2+ products are proposed, including the CO, CO-COH, and CO-CO paths. In addition, typical material regulatory strategies and technical designs for ECR toward C2+ products (e.g. crystal facet modulation, defect engineering, size effect, confinement effects, electrolyzer design, and electrolyte pH) are introduced, focusing on their effects on the selectivity, current efficiency, and durability. The four strategies for catalyst design (crystal facet modulation, defect engineering, size effect, and confinement effect) primarily affect the selectivity of the ECR via adjustment of the adsorption of reaction intermediates. The last two strategies for technique design (electrolyzer design and electrolyte pH) contributing greatly toward improving the current efficiency than selectivity. Finally, the challenges and perspectives for ECR toward C2+ products and their future prospects are discussed herein. Therefore, breakthroughs in the promising field of ECR toward the generation of C2+ products are possible when these catalyst design strategies and mechanisms are applied and novel designs are developed.

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To develop a highly efficient visible light-induced and conveniently recyclable photocatalyst, in this study, a ternary magnetic ZnO/Fe 3 O 4 /g-C 3 N 4 composite photocatalyst was synthesized for the photodegradation of Monas dye. The structure and optical performance of the composite photocatalyst were characterized using X-ray diffraction (XRD), transmission electron microscopye (TEM), energy dispersive spectroscopy (EDS), photoluminescence (PL) spectra, ultraviolet–visible diffuse reflection, and photo-electrochemistry. The photocatalytic activities of the prepared ZnO/Fe 3 O 4 /g-C 3 N 4 nanocomposites were notably improved, and they were significantly higher than those of pure g-C 3 N 4 and ZnO. Given the presence of the heterojunction between the interfaces of g-C 3 N 4 and ZnO, the higher response to visible light and separation efficiency of the photo-induced electrons and holes enhanced the photocatalytic activities of the ZnO/Fe 3 O 4 /g-C 3 N 4 nanocomposites. The stability experiment revealed that ZnO/Fe 3 O 4 /g-C 3 N 4 -50% demonstrates a relatively higher photocatalytic activity after 5 recycles. The degradation efficiency of MO, AYR, and OG over ZnO/Fe 3 O 4 /g-C 3 N 4 -50% were 97.87%, 98.05%, and 83.35%, respectively, which was due to the number of dye molecules adsorbed on the photocatalyst and the structure of the azo dye molecule. Azo dyes could be effectively and rapidly photodegraded by the obtained photocatalyst. Therefore, the environment-friendly photocatalyst could be widely applied to the treatment of dye contaminated wastewater.

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Motivation Cancer is a heterogeneous group of diseases. Cancer subtyping is a crucial and critical step to diagnosis, prognosis and treatment. Since high-throughput sequencing technologies provide an unprecedented opportunity to rapidly collect multi-omics data for the same individuals, an urgent need in current is how to effectively represent and integrate these multi-omics data to achieve clinically meaningful cancer subtyping. Results We propose a novel deep learning model, called Deep Structure Integrative Representation (DSIR), for cancer subtypes dentification by integrating representation and clustering multi-omics data. DSIR simultaneously captures the global structures in sparse subspace and local structures in manifold subspace from multi-omics data and constructs a consensus similarity matrix by utilizing deep neural networks. Extensive tests are performed in 12 different cancers on three levels of omics data from The Cancer Genome Atlas. The results demonstrate that DSIR obtains more significant performances than the state-of-the-art integrative methods. Availability and implementation https://github.com/Polytech-bioinf/Deep-structure-integrative-representation.git Supplementary information Supplementary data are available at Bioinformatics online.