Highly selective photocatalytic CO2 reduction into C2H4 enabled by metal-organic framework-derived catalysts with high Cu+ content.

The highly selective conversion of CO2 into valuable C2H4 is a highly important but particularly challenging reaction. Herein, the metal-organic frameworks MOF-74(Cu) with infinite Cu(II)-O chains and Cu-BTC (BTC=benzene-1,3,5-tricarboxylate) with paddle-wheel binuclear Cu(II) clusters are used as precursors. These MOFs are reduced by NaBH4 to obtain Cu0/Cuδ+-based photocatalysts denoted as R-MOF-74(Cu) and R-Cu-BTC, respectively. Significantly, R-MOF-74(Cu) achieves a high selectivity of 90.2 % for C2H4 with a yield rate of 6.5 µmol g-1 within 5 h due to its high Cu+ content. To the best of our knowledge, this C2H4 product selectivity is a record high among all the photocatalysts reported so far for photocatalytic CO2 reduction. In contrast, R-Cu-BTC only forms CO as a product with a cumulative yield of 0.7 µmol g-1 within 5 h. Photoelectrochemical characterization and electron paramagnetic resonance results show that R-MOF-74(Cu) has low interfacial transfer resistance, high photogenerated electron separation efficiency, and excellent CO2 activation and water oxidation performance. In addition, in situ Fourier transform infrared spectroscopy is used to determine the possible reaction pathway from CO2 to C2H4 over R-MOF-74(Cu). This work demonstrates the great potential of MOF-derived photocatalysts for the conversion of CO2 into C2H4 and provides guidance for future photocatalyst development.

[Application of ion chromatographic fingerprint analysis for quality evaluation of tobacco flavors].

Tobacco flavor, an important tobacco additive, is an essential raw material in cigarette production that can effectively improve the quality of tobacco products, add aroma and taste, and increase the suction flavor. The quality consistency of tobacco flavors affects the quality stability of branded cigarettes. Therefore, the quality control of tobacco flavors is a major concern for cigarette and flavor manufacturers. Physical and chemical indices, odor similarity, and sensory efficacy are employed to evaluate the quality of tobacco flavors, and the analysis of chemical components in tobacco flavors is usually conducted using gas chromatography (GC) and high performance liquid chromatography (HPLC). However, because the composition of tobacco flavors is complex, their quality cannot be fully reflected using a single component or combination of components. Therefore, establishing an objective analytical method for the quality control of tobacco flavors is of extreme importance. Chromatographic fingerprint analysis is routinely used for the discriminative analysis of tobacco flavors. Chromatographic fingerprints refer to the general characteristics of the concentration profiles of different chemical compounds. In the daily procurement process, fingerprints established by GC and HPLC are effective for the evaluation and identification of tobacco flavors. However, given continuous improvements in aroma-imitation technology, some flavors with high similarity cannot be directly distinguished using existing methods. In this study, a method for the determination of organic acids and inorganic anions in tobacco flavors based on ion chromatography (IC) was developed to ensure the quality consistency of tobacco flavors. A 1.0 g sample of tobacco flavors and 10 mL of deionized water were mixed and vibrated for 30 min. The aqueous sample solution was passed through a 0.45 µm membrane filter and RP pretreatment column in succession to eliminate interferences and then subjected to IC. Standard solutions containing nine organic acids and seven inorganic anions were used to identify the anions in the tobacco flavors, and satisfactory reproducibility was obtained. The relative standard deviations (RSDs) for retention times and peak areas were <0.71% and <6.02%, respectively. The chromatographic fingerprints of four types of tobacco flavors (samples A-D) from five different batches were obtained. Nine tobacco flavor samples from different manufacturers (samples AY1-AY3, BY1-BY2, CY1-CY2, DY1-DY2) were also analyzed to obtain their chromatographic fingerprints. Hierarchical cluster and similarity analyses were used to evaluate the quality of tobacco flavors from different manufacturers. Hierarchical clustering refers to the process of subdividing a group of samples into clusters that exhibit a high degree of intracluster similarity and intercluster dissimilarity. The dendrograms obtained using SPSS 12.0 indicated good quality consistency among the samples in different batches. Samples AY3, BY2, CY2, and DY1 clustered with the batches of standard tobacco flavors. Therefore, hierarchical cluster analysis can effectively distinguish the quality of products from different manufacturers. The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (version 2.0) was used to evaluate the similarity between the standard tobacco flavors and products from different manufacturers. Among the samples analyzed, samples AY3, BY2, CY2, and DY1 showed the highest similarity values (>97.7%), which was consistent with the results of the hierarchical cluster analysis. This finding indicates that IC combined with chromatographic fingerprint analysis could accurately determine the quality of tobacco flavors. GC combined with ultrasonic-assisted liquid-liquid extraction was also used to analyze the tobacco flavors and verify the accuracy of the proposed method. Compared with GC coupled with ultrasonic-assisted liquid-liquid extraction, IC demonstrated more significant quality differences among certain tobacco flavors.

Synchronous Switching Strategy to Enhance the Real-Time Powering and Charging Performance of Triboelectric Nanogenerator.

Triboelectric nanogenerators (TENGs) are of great significance as sustainable power sources that harvest energy from the human body and environment. Nevertheless, due to TENG's impedance-dependent output voltage characteristics, in traditional strategy (TS), real-timely powering a sensor with TENG has a poor sensing on/off ratio (or response), and directly charging a capacitor with TENG shows a low charging efficiency. This degraded real-time powering and charging performance of TENG compared to a commercial constant voltage source is a huge challenge of the TENG field for a long time. This work proposes a synchronous switching strategy (SSS) for TENG to real-timely power sensors or charge capacitors without degrading its performance. Compared with TS, this new strategy enables sensors to have 5-7 times sensing on/off ratio enhancement when using TENG as a power source, reaching the powering ability of a commercial constant voltage source, it makes the powering performance of TENG stable under different driving frequency, improving the powering robustness of TENG. In addition, compared with TS, SSS can also enhance the charging efficiency of TENG in every charging cycle by up to 2.4 times when charging capacitors. This work contributes to real-timely powering or charging the distributed, mobile and wireless electronics using TENG.

Electrocatalytic reduction of nitrite to ammonia on undercoordinated Cu.

Electrocatalytic NO2--to-NH3 reduction (NO2RR) has emerged as an intriguing route for simultaneous mitigation of harmful nitrites and production of valuable NH3. Herein, we design for the first time undercoordinated Cu nanowires (u-Cu) as an efficient and selective NO2RR electrocatalyst, delivering the maximum NO2--to-NH3 faradaic efficiency of 94.7% and an ammonia production rate of 494.5 µmol h-1 cm-2 at -0.7 V vs. RHE. Theoretical calculations reveal that the created undercoordinated Cu sites on u-Cu can enhance NO2- adsorption, boost NO2--to-NH3 energetics and restrict competitive hydrogen evolution, thereby enabling the active and selective NO2RR.

Intelligent Method to Optimize the Frequency Modulation for Beam Pumping System Based on Deep Reinforcement Learning.

A mathematical simulation model of a beam pumping system with frequency conversion control is established, considering the influence of the real-time frequency variation on the motion law of a pumping unit, the longitudinal vibration of a sucker rod string, the crankshaft torque, and the motor power. On this basis, the key links such as state space, action space, and reward function are defined by using deep reinforcement learning theory, and an intelligent model to optimize the frequency modulation for a beam pumping system based on deep reinforcement learning is constructed. The simulation and field application results show that the frequency optimization model can significantly reduce the fluctuation amplitude of the polished rod load, crankshaft torque, motor power, and input power of the system, making the operation of the pumping system more stable and energy-saving. More importantly, the model can realize the independent learning and control of the corresponding parameters without manual intervention to ensure the normal operation of the system and improve the level of information and intelligent management of oil wells.

Enhancing the filtration efficiency and wearing time of disposable surgical masks using TENG technology.

The COVID-19 pandemic has caused an unprecedented human and health crisis. And the shortage of protective equipment, especially the personal protective disposable surgical masks, has been a great challenge. Here, we developed an effective and simple scheme to prolong the lifetime of disposable surgical masks without changing their current structure, which is beneficial to solve the shortage of personal masks. After electrifying the meltblown PP filter by the new-developed single-electrode-based sliding triboelectric nanogenerator (TENG) charge replenishment (NGCR) technology, the processed filter is bipolar charged and has a filtration efficiency beyond 95% for the particulate matter (PM) ranging from PM0.3 to PM10.0. Further, we demonstrate the 80 °C dry heating is an effective decontamination method. This method is compatible with single-electrode-based sliding TENG charge replenishment technology. The 80 °C dry heating and the NGCR technology can make up an effective regeneration procedure for the mask. Even after ten cycles of simulated 4 h wearing process and such regeneration procedure, the filtration efficiency of the disposable surgical masks PM0.3 is still higher than 95%.

Direct monitoring changes of salbutamol concentration in serum by chemiluminescent imaging.

We report in this manuscript, the use of direct ammonium persulfate-enhanced chemiluminescence (CL) imaging, to monitor changes to measure serum salbutamol concentration in subjects of different haptoglobin (Hp) phenotypes at different dosing time. It was noted that CL generated from Hp was decreased due to salbutamol's reducibility, which was used for monitoring salbutamol concentration in serum. The serum from the subjects treated by oral administration of salbutamol, was collected at different dosing time and was separated by polyacrylamide gel electrophoresis (PAGE) prior to the CL detection. According to CL images, samples were separated into three groups based on the Hp phenotypes. The curves of CL signal intensity versus time were obtained for each group, and we demonstrated that there were more significant variables on binding ability between groups. The maximum salbutamol concentration in the serum appeared after 4h, which was in agreement with the literature. In addition, the binding constants of salbutamol to Hp were determined by a fluorescence-based method, whose results were in agreement with the phenomenon of the greater salbutamol metabolism rate for Group Hp 1-1 than Group Hp 2-2. The presented method can monitor changes of salbutamol concentration in serum directly, making the procedures much simple, convenient, rapid and has the property of lower cost. It provided us with excellent reference information for the individual dosage regimen of different Hp groups, which hopefully could become a potential method for further pharmaceutical research.