The electrochemical reduction of CO₂ has been recognized as a promising strategy to convert ambient atmospheric CO₂ into valuable products. Bismuth-based catalysts have garnered the widespread attention of researchers due to their cost-effectiveness, low toxicity, and high natural abundance. Significant progress has been made toward enhancing the reactivity of catalyst structureons through innovative synthesis techniques and engineering. Advances include the use of flow cells and membrane electrode assembly (MEA) cells to attain high cathodic current densities of over 200 mA cm^-2 with superior selectivity that approaches over 90%.

Though technologies for the highly selective reduction of CO₂ to formate have been realized for bismuth-based catalysts, several challenges remain that hinder their commercialization. Further advancements are essential for improving the stability of Bi-based catalysts for industrial applications. The development of in situ characterization techniques is required to be compatible with high current densities, which would provide insights into the kinetics of the CO₂ reduction reaction (CO₂RR) to facilitate the identification of key intermediates for real-world applications. Economic evaluations are vital for assessing the CO₂RR in terms of the cost and efficacy of the CO₂ reduction process. A research team has highlighted recent developments and proposed viable future directions, with their work being published in the journal Industrial Chemistry & Materials recently. The main goal of this feature article is to provide readers with the latest research progress and current challenges of CO₂RR using Bi-based catalysts.

A recent study published in the Journal of Geo-information Science introduces a stratified sampling method based on remote sensing complexity for interpretation. Led by researchers Lianfa Li and Xiaomei Yang from the Chinese Academy of Sciences, the study integrates surface morphology, spectral characteristics, and spatial heterogeneity metrics, alongside multi-scale morphological transformations. This method enhances sample representativeness and reduces classification errors. Experimental validation demonstrated its superiority over traditional techniques, particularly in complex terrains. The findings significantly advance applications in land-use classification, environmental monitoring, and disaster assessment, offering a solid foundation for intelligent remote sensing analysis.

A new study unveils an innovative strategy to combat Pseudomonas aeruginosa, a major culprit behind food spoilage and foodborne illnesses. With antimicrobial resistance on the rise, conventional treatments are losing their effectiveness, creating an urgent need for alternative solutions. This research focuses on quorum sensing inhibitors (QSIs), which disrupt bacterial communication, reducing virulence and combating drug resistance. Unlike traditional antibiotics, QSIs do not kill bacteria, thus minimizing the risk of resistance development. The study evaluates a variety of QSIs, from natural compounds to enzymes, offering a fresh perspective on controlling this harmful pathogen.

A new study has revealed that ferulic acid, a natural compound found in various plant-based foods, can significantly inhibit the growth and migration of colon cancer cells at different stages of progression. The research, which offers valuable insights into how ferulic acid induces cell cycle arrest and apoptosis, suggests that this compound could serve as an effective dietary intervention for preventing colon cancer. These findings open new avenues for dietary strategies aimed at reducing the burden of this widespread disease.

In a bid to explore MAX phases with experimental significance across a significantly broader combinatorial space, the researchers of this study pioneered the development of a machine-learning model for predicting MAX phase stability. This model is based on elemental features and can swiftly forecast the stability of MAX phases by simply leveraging the basic parameters of elements. Notably, the model successfully identified 150 MAX phases that met the stability criteria but had not been synthesized previously. It also guided the first-ever experimental synthesis of Ti₂SnN. Ti₂SnN showcases a low elastic modulus, high damage tolerance, and self-extrusion characteristics. This accomplishment not only enhances the screening efficiency by a factor of tens but also uncovers the crucial role of valence electrons. As a result, it provides novel insights into the fundamental principles governing MAX phase formation.