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Rechargeable zinc-air batteries (ZABs) are regarded as a remarkably promising alternative to current lithium-ion batteries, addressing the requirements for large-scale high-energy storage. Nevertheless, the sluggish kinetics involving oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) hamper the widespread application of ZABs, necessitating the development of high-efficiency and durable bifunctional electrocatalysts. Here, we report oxygen atom-bridged Fe, Co dual-metal dimers (FeOCo-SAD), in which the active site Fe-O-Co-N6 moiety boosts exceptional reversible activity toward ORR and OER in alkaline electrolytes. Specifically, FeOCo-SAD achieves a half-wave potential (E1/2) of 0.87 V for ORR and an overpotential of 310 mV at a current density of 10 mA cm-2 for OER, with a potential gap (ΔE) of only 0.67 V Meanwhile, FeOCo-SAD manifests high performance with a peak power density of 241.24 mW cm-2 in realistic rechargeable ZABs. Theoretical calculations demonstrate that the introduction of an oxygen bridge in the Fe, Co dimer induced charge spatial redistribution around Fe and Co atoms. This enhances the activation of oxygen and optimizes the adsorption/desorption dynamics of reaction intermediates. Consequently, energy barriers are effectively reduced, leading to a strong promotion of intrinsic activity toward ORR and OER. This work suggests that oxygen-bridging dual-metal dimers offer promising prospects for significantly enhancing the performance of reversible oxygen electrocatalysis and for creating innovative catalysts that exhibit synergistic effects and electronic states. [ABSTRACT FROM AUTHOR]

Hydrogen peroxide (H2O2) is an important green oxidant in the field of sewage treatment, and how to improve its activation efficiency and generate free radicals with stronger oxidation performance is a key issue in current research. Herein, we synthesized a Cu-doped α-Fe2O3 catalyst (7% Cu-Fe2O3) for activation of H2O2 under visible light for degradation of organic pollutants. The introduction of a Cu dopant changed the d-band center of Fe closer to the Fermi level, which enhanced the adsorption and activation of the Fe site for H2O2, and the cleavage pathway of H2O2 changed from heterolytic cleavage to homolytic cleavage, thereby improving the selectivity of ⋅OH generation. In addition, Cu doping also promoted the light absorption ability of α-Fe2O3 and the separation of hole-electron pairs, which enhanced its photocatalytic activities. Benefiting from the high selectivity of ⋅OH, 7% Cu-Fe2O3 exhibited efficient degradation activities against ciprofloxacin, the degradation rate was 3.6 times as much as that of α-Fe2O3, and it had good degradation efficiency for a variety of organic pollutants. [ABSTRACT FROM AUTHOR]

The performance optimization of isolated atomically dispersed metal active sites is critical but challenging. Here, TiO2@Fe species-N-C catalysts with Fe atomic clusters (ACs) and satellite Fe-N4 active sites were fabricated to initiate peroxymonosulfate (PMS) oxidation reaction. The AC-induced charge redistribution of single atoms (SAs) was verified, thus strengthening the interaction between SAs and PMS. In detail, the incorporation of ACs optimized the HSO5 -oxidation and SO5 ·-desorption steps, accelerating the reaction progress. As a result, the Vis/TiFeAS/PMS system rapidly eliminated 90.81% of 45 mg/L tetracycline (TC) in 10 min. The reaction process characterization suggested that PMS as an electron donor would transfer electron to Fe species in TiFeAS, generating 1O2. Subsequently, the hVB + can induce the generation of electron-deficient Fe species, promoting the reaction circulation. This work provides a strategy to construct catalysts with multiple atom assembly-enabled composite active sites for high-efficiency PMS-based advanced oxidation processes (AOPs). [ABSTRACT FROM AUTHOR]

Protein corona formation is critical for the design of ideal and safe nanoparticles (NPs) for nanomedicine, biosensing, organ targeting, and other applications, but methods to quantitatively predict the formation of the protein corona, especially for functional compositions, remain unavailable. The traditional linear regression model performs poorly for the protein corona, as measured by R2 (less than 0.40). Here, the performance with R2 over 0.75 in the prediction of the protein corona was achieved by integrating a machine learning model and meta-analysis. NPs without modification and surface modification were identified as the two most important factors determining protein corona formation. According to experimental verification, the functional protein compositions (e.g., immune proteins, complement proteins, and apolipoproteins) in complex coronas were precisely predicted with good R² (most over 0.80). Moreover, the method successfully predicted the cellular recognition (e.g., cellular uptake by macrophages and cytokine release) mediated by functional corona proteins. This workflow provides a method to accurately and quantitatively predict the functional composition of the protein corona that determines cellular recognition and nanotoxicity to guide the synthesis and applications of a wide range of NPs by overcoming limitations and uncertainty. [ABSTRACT FROM AUTHOR]