Construction of Dual-Active Sites by Interfacing with Polyhydroxy Fullerene on Nickel Hydroxide Surfaces to Promote CO2 Deep Photoreduction to CH4.

Due to the complex series of elementary steps involved, achieving deep photoreduction of CO2 to multielectron products such as CH4 remains a challenging task. Therefore, it is crucial to strategically design catalysts that facilitate the controlled formation of the crucial intermediates and provide precise control over the reaction pathway. Herein, we present a pioneering approach by employing polyhydroxy fullerene (PHF) molecules to modify the surface of Ni(OH)2, creating stable and effective synergistic sites to enhance the formation of CH4 from CO2 under light irradiation. As a result, the optimized PHF-modified Ni(OH)2 cocatalyst achieves a CH4 production rate of 455 µmol g-1 h-1, with an electron-based selectivity of approximately 60%. The combination of in situ characterizations and theoretical calculations reveals that the hydroxyl species on the surface of PHF can participate in stabilizing crucial intermediates and facilitating water activation, thereby altering the reaction pathway to form CH4 instead of CO. This study provides a novel approach to regulating the selectivity of photocatalytic CO2 reduction by exploring molecular surface modification through interfacing with functionalized carbon clusters.

One-dimensional nitrogen doped porous carbon nano-array arranged by carbon nanotubes for electrochemical sensing ascorbic acid, dopamine and uric acid simultaneously.

In this work, one-dimensional nitrogen doped porous carbon nano-arrays arranged by carbon nanotube (1D CNTs@NPC) were first constructed, using a coating technology at room temperature and followed by high temperature carbonization. It was expected that the resulting glassy carbon electrodes modified by 1D CNTs@NPC (CNTs@NPC/GCE) could express different electrochemical responses to ascorbic acid (AA), dopamine (DA), uric acid (UA), by virtue of the synergistic-improved effect between CNTs and NPC. Under the optimized conditions, there were excellent analytical parameters for CNTs@NPC/GCE to detect AA, DA and UA, i.e. a wide linear range of 40-2100µM for AA, 0.5-49µM for DA and 3-50µM for AA with low detection limits of 0.36µM, 0.02µmol l-1and 0.57µM respectively. Importantly, the proposed CNTs@NPC/GCE was efficiently applied to determine AA, DA and UA in some real samples with high stability, reproducibility and selectivity. This work will offer an efficient potential for diagnosing ascorbic acid, dopamine or uric acid-related diseases on clinical testing in future.

Highly Efficient and Selective Visible-Light Driven CO2 Reduction by Two Co-Based Catalysts in Aqueous Solution.

Photocatalytic CO2 reduction has been considered as a promising approach to solve energy and environmental problems. Nevertheless, developing inexpensive photocatalysts with high efficiency and selectivity remains a big challenge. In this study, two Co-based complexes [Co2(L1)Cl2] (1-Co) and [Co(L2)Cl] (2-Co) were synthesized by treating two DPA-based (DPA: dipicolylamine) ligands with Co2+, respectively. Under visible-light irradiation, the performance of 1-Co as a homogeneous photocatalyst for CO2 reduction in aqueous media has been explored by using [Ru(phen)3]2+ as a photosensitizer, and triethylolamine (TEOA) as a sacrificial reductant. 1-Co shows high photocatalytic activity for CO2-to-CO conversion, corresponding to the high TONCO of 2600 and TOFCO of 260 h-1 (TONCO = turnover number for CO; TOFCO = turnover frequency for CO). High selectivity of 97% for CO formation is also achieved. The control experiments catalyzed by 2-Co demonstrated that two Co(II) centers in 1-Co may operate independently and activate one CO2 molecule each. Furthermore, the proposed mechanism of 1-Co for photocatalytic CO2 reduction has been investigated via electrochemical analysis, a series of quenching experiments, and density functional theory calculations.

Nitrogen-doped MoS2 quantum dots: Facile synthesis and application for the assay of hematin in human blood.

Nitrogen-doped MoS2 quantum dots (N-MoS2 QDs) were synthesized via a facile hydrothermal approach, and exhibited high fluorescence quantum yield (QY, 14.9%), excellent photostability, biocompatibility and water solubility. A novel method with good selectivity and sensitivity was established to assay hematin using N-MoS2 QDs as a fluorescent probe based on inner filter effect (IFE). Fluorescent quenching of N-MoS2 QDs has a fine linear dependence with the concentration of hematin in the range of 0.5-15 µmol/L and a limit of detection of 0.32 µmol/L (S/N = 3). By the detection method, average concentration of hematin in real health human erythrocytes was measured as 22.5 ± 3.9 µmol/L. And, recoveries range varied from 94 to 108% through standard recovery experiment. The N-MoS2 QDs probe shows excellent photostability, low cytotoxicity and anti-interference ability for hematin assay, which may become a promising method for the test of hematin in human blood.

Highly efficient and selective photocatalytic CO2 to CO conversion in aqueous solution.

Five molecular complexes with different non-noble metal centers were synthesized. The Co-based complex displays the highest photocatalytic performance for CO2 to CO conversion in aqueous media. It achieves high activity (TON = 41 017 and TOF = 3.80 s-1) and selectivity (87%) for the production of CO.

Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology.

This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents' wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident's feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment.