Using photoelectrocatalytic CO₂ reduction reaction (CO₂RR) to produce valuable fuels is a fascinating way to alleviate environmental issues and energy crises. Bismuth-based (Bi-based) catalysts have attracted widespread attention for CO₂RR due to their high catalytic activity, selectivity, excellent stability, and low cost. However, they still need to be further improved to meet the needs of industrial applications. This review article comprehensively summarizes the recent advances in regulation strategies of Bi-based catalysts and can be divided into six categories: (1) defect engineering, (2) atomic doping engineering, (3) organic framework engineering, (4) inorganic heterojunction engineering, (5) crystal face engineering, and (6) alloying and polarization engineering. Meanwhile, the corresponding catalytic mechanisms of each regulation strategy will also be discussed in detail, aiming to enable researchers to understand the structure–property relationship of the improved Bi-based catalysts fundamentally. Finally, the challenges and future opportunities of the Bi-based catalysts in the photoelectrocatalytic CO₂RR application field will also be featured from the perspectives of the (1) combination or synergy of multiple regulatory strategies, (2) revealing formation mechanism and realizing controllable synthesis, and (3) in situ multiscale investigation of activation pathways and uncovering the catalytic mechanisms. On the one hand, through the comparative analysis and mechanism explanation of the six major regulatory strategies, a multidimensional knowledge framework of the structure–activity relationship of Bi-based catalysts can be constructed for researchers, which not only deepens the atomic-level understanding of catalytic active sites, charge transport paths, and the adsorption behavior of intermediate products, but also provides theoretical guiding principles for the controllable design of new catalysts; on the other hand, the promising collaborative regulation strategies, controllable synthetic paths, and the in situ multiscale characterization techniques presented in this work provides a paradigm reference for shortening the research and development cycle of high-performance catalysts, conducive to facilitating the transition of photoelectrocatalytic CO₂RR technology from the laboratory routes to industrial application.

Continuous monitoring of biosignals is essential for advancing early disease detection, personalized treatment, and health management. Flexible electronics, capable of accurately monitoring biosignals in daily life, have garnered considerable attention due to their softness, conformability, and biocompatibility. However, several challenges remain, including imperfect skin-device interfaces, limited breathability, and insufficient mechanoelectrical stability. On-skin epidermal electronics, distinguished by their excellent conformability, breathability, and mechanoelectrical robustness, offer a promising solution for high-fidelity, long-term health monitoring. These devices can seamlessly integrate with the human body, leading to transformative advancements in future personalized healthcare. This review provides a systematic examination of recent advancements in on-skin epidermal electronics, with particular emphasis on critical aspects including material science, structural design, desired properties, and practical applications. We explore various materials, considering their properties and the corresponding structural designs developed to construct high-performance epidermal electronics. We then discuss different approaches for achieving the desired device properties necessary for long-term health monitoring, including adhesiveness, breathability, and mechanoelectrical stability. Additionally, we summarize the diverse applications of these devices in monitoring biophysical and physiological signals. Finally, we address the challenges facing these devices and outline future prospects, offering insights into the ongoing development of on-skin epidermal electronics for long-term health monitoring.

- Development of an AI method that enables efficient large-scale model training while protecting personal information with only a single model transmission

- Overcomes previous limitations of computational cost and overfitting… expected to be applied in medical image analysis