Xihua University

In the global trend of vigorously developing hydrogen energy, proton-conducting solid oxide electrolysis cells (P-SOECs) have attracted significant attention due to their advantages of high efficiency and not requiring precious metals. However, the application of P-SOECs faces challenges, particularly in developing high-performance anodes possessing both high catalytic activity and ionic conductivity. In this study, La0.9Ba0.1Co0.7Ni0.3O3−δ (LBCN9173) and La0.9Ca0.1Co0.7Ni0.3O3−δ (LCCN9173) oxides are tailored as promising anodes by machine learning model, achieving the synergistic enhancement of water oxidation reaction kinetics and proton conduction, which is confirmed by comprehensively analyzing experiment and density functional theory calculation results. Furthermore, the anodic reaction mechanisms for P-SOECs with these anodes are elucidated by analyzing distribution of relaxation time spectra and Gibbs energy of water oxidation reaction, manifesting that the dissociation of H2O is facilitated on LBCN9173 anode. As a result, P-SOEC with LBCN9173 anode demonstrates a top-rank current density of 2.45 A cm−2 at 1.3 V and an extremely low polarization resistance of 0.05 Ω cm2 at 650 °C. This multi-scale, multi-faceted research approach not only discovered a high-performance anode but also proved the robust framework for the machine learning-assisted design of anodes for P-SOECs.

Excessive use of kanamycin (KAN) in food can lead to ototoxicity, nephrotoxicity, and antibiotic resistance in humans. Therefore, developing a rapid and sensitive detection method to accurately identify KAN is urgent. In this study, we propose a sensitive and convenient detection technique based on an intelligent color-changing hydrogel. This hydrogel incorporates coral-shaped prussian blue (C-PB) nanozymes and Au polyhedra to achieve dual detection of KAN through colorimetric and Raman techniques. We first combined aptamer chains with DNA single strands to construct a "lock" structure within porous metal-organic frameworks, encapsulating numerous 3,3',5,5'-tetramethylbenzidine (TMB) molecules. In the presence of KAN, because of the higher affinity between the aptamer chain and KAN, the "lock" structure is disrupted, releasing a large amount of TMB. Subsequently, TMB is absorbed by the C-PB-based hydrogel and catalyzed into oxidized TMB with the assistance of hydrogen peroxide. Consequently, the hydrogel changes from pink to blue, accompanied by a significant Raman signal. This intelligent hydrogel platform enables ultrasensitive identification of KAN through both colorimetric and Raman modes with a detection limit of 1.58 × 10^-13 mol/L and a linear range from 1.0 × 10^-12 to 1.0 × 10^-3 mol/L. We believe this dual-mode strategy offers a promising pathway for real-time detection and monitoring of actual samples.

Microplastic (MP) pollution has emerged as a significant environmental concern in aquatic ecosystems. Consequently, the development of rapid, sensitive, and efficient methods for microplastic detection is of paramount importance. This study presents a novel Au-Ag alloy nano-sea urchin (AAA-NUs) flexible membrane fabricated via a straightforward vacuum filtration technique. This membrane demonstrates high efficiency in enriching and detecting polyvinyl chloride (PVC) and polyethylene (PE) microplastics in water samples. Initially, an asymmetric seed-mediated growth method was employed to synthesize AAA-NUs with numerous sharp tips and rough surface morphologies, thereby creating abundant nano-interstices that enhance surface-enhanced Raman scattering (SERS) signals effectively. Subsequently, by employing a straightforward vacuum filtration technique, a substantial quantity of AAA-NUs can be rapidly and uniformly deposited onto the polytetrafluoroethylene (PTFE) membrane. This process facilitates the formation of stable surface-enhanced Raman scattering (SERS) "hotspots," thereby significantly improving the sensitivity of the sensor. When water containing PE and PVC microplastics passes through the AAA-NUs membrane, these microplastics are captured efficiently. Leveraging the outstanding SERS enhancement of the AAA-NUs flexible membrane, this method achieves a low limit of detection (LOD) of 0.269 μg/mL and 0.373 μg/mL for PE and PVC, which was reduced by 1-2 orders of magnitude compared to conventional SERS substrates. With the growing prevalence of portable Raman spectrometers, this technology holds substantial promise for water quality assessment.