Biomimetic Design of a Dynamic M-O-V Pyramid Electron Bridge for Enhanced Nitrogen Electroreduction.

Electrochemical nitrogen reduction reaction (eNRR) offers a sustainable route for ammonia synthesis; however, current electrocatalysts are limited in achieving optimal performance within narrow potential windows. Herein, inspired by the heliotropism of sunflowers, we present a biomimetic design of Ru-VOH electrocatalyst, featuring a dynamic Ru-O-V pyramid electron bridge for eNRR within a wide potential range. In situ spectroscopy and theoretical investigations unravel the fact that the electrons are donated from Ru to V at lower overpotentials and retrieved at higher overpotentials, maintaining a delicate balance between N2 activation and proton hydrogenation. Moreover, N2 adsorption and activation were found to be enhanced by the Ru-O-V moiety. The catalyst showcases an outstanding Faradaic efficiency of 51.48% at -0.2 V (vs RHE) with an NH3 yield rate exceeding 115 µg h-1 mg-1 across the range of -0.2 to -0.4 V (vs RHE), along with impressive durability of over 100 cycles. This dynamic M-O-V pyramid electron bridge is also applicable to other metals (M = Pt, Rh, and Pd).

Simultaneous detection of tyrosine and uric acid in sweat using CoWO4@CNT with a hydrogel modified electrochemical biosensor.

The levels of uric acid (UA) and tyrosine (Tyr) in sweat reflect a person's overall health. However, simultaneously identifying several components in sweat remains challenging. Here, we achieve simultaneous detection of UA and Tyr by synthesizing CoWO4@CNT in a single step using a hydrothermal method. CoWO4's high catalytic efficacy and large CNT reaction area allow the detection of 1-1000 µM UA (LOD = 0.14 µM) and 5-1000 µM Tyr (LOD = 4.2 µM). To increase sweat collection, we developed a polydopamine-polyacrylamide (PDA-PAM) hydrogel with a sweat absorption rate of up to 226%. Finally, by monitoring sweat at various times of day, our sensors can discriminate between UA and Tyr in real sweat, and the results are consistent with the individuals' activity levels. Overall, the effective electrocatalytically active materials and PDA-PAM hydrogel improve the detection of UA and Tyr. The remarkable performance of CoWO4@CNT in real samples shows that it has the potential to improve health detection and real-time sweat analysis.

Rapid, portable, and sensitive detection of CaMV35S by RPA-CRISPR/Cas12a-G4 colorimetric assays with high accuracy deep learning object recognition and classification.

Fast, sensitive, and portable detection of genetic modification contributes to agricultural security and food safety. Here, we developed RPA-CRISPR/Cas12a-G-quadruplex colorimetric assays that can combine with intelligent recognition by deep learning algorithms to achieve sensitive, rapid, and portable detection of the CaMV35S promoter. When the crRNA-Cas12a complex recognizes the RPA amplification product, Cas12 cleaves the G-quadruplex, causing the G4-Hemin complex to lose its peroxide mimetic enzyme function and be unable to catalyze the conversion of ABTS2- to ABTS, allowing CaMV35S concentration to be determined based on ABTS absorbance. By utilizing the RPA-CRISPR/Cas12a-G4 assay, we achieved a CaMV35S limit of detection down to 10 aM and a 0.01 % genetic modification sample in 45 min. Deep learning algorithms are designed for highly accurate classification of color results. Yolov5 objective finding and Resnet classification algorithms have been trained to identify trace (0.01 %) CaMV35S more accurately than naked eye colorimetry. We also coupled deep learning algorithms with a smartphone app to achieve portable and rapid photo identification. Overall, our findings enable low cost ($0.43), high accuracy, and intelligent detection of the CaMV35S promoter.