Latest ArticlesArtificial photocatalytic energy conversion is considered as the most potential strategy for solving the increasingly serious energy crisis and environmental pollution problems by directly capturing solar energy. Therefore, high efficiency photocatalyst has drawn significant research attention in recent years. Due to the excellent electronic, optical, structural, and physicochemical performances, silver-based g-C3N4 have become promising photocatalysts. This review emphasizes the recent progresses and challenges on g-C3N4 decorated with silver for photocatalytic energy conversion. The extensive use of g-C3N4 decorated with silver in diverse photocatalytic reactions, including hydrogen evolution, pollutant degradation and carbon dioxide reduction, is also fully introduced. In addition, we propose the perspectives of g-C3N4 decorated with silver on photocatalytic applications. We hope that this review will shed some light on the photocatalytic energy conversion of g-C3N4 decorated with silver.
Establishing an effective charge transfer mechanism in carbon nitride (g-C3N4) to enhance its photocatalytic activity remains a limiting nuisance. Herein, the combination design of a single Cu atom with hollow g-C3N4 nanospheres (Cu-N3 structure) has been proven to offer significant opportunities for this crucial challenge. Moreover, this structure endows two pathways for charge transfer in the reaction, namely, the N atoms in the three-dimensional planar structure are only bonded with a single Cu atom, and charge transfer occurs between the plane and the layered structure due to the bending of the interlayered g-C3N4 hollow nanospheres. Notably, Cu-N3 and hollow nanosphere structures have been certified to greatly enhance the efficiency of photogenerated carrier separation and transfer between the layers and planes by ultrafast spectral analysis. As a result, this catalyst possesses unparalleled photocatalytic efficiency. Specifically, the hydrogen production rate up to 2040 µmol h−1 g−1, which is 51 times that of pure C3N4 under visible light conditions. The photocatalytic degradation performance of tetracycline and oxidation performance of benzene is also expressed, with a degradation rate of 100%, a conversion of 97.3% and a selectivity of 99.9%. This work focuses on the structure-activity relationship to provide the possibilities for the development of potential photocatalytic materials.
One of the urgent and challenging topics in diversified sustainable energy conversion is the development of high-performance, low-cost, and well durable catalysts. Cu single-atom catalysts (SACs) have become promising catalysts for diversified sustainable energy conversion due to their capability to maximize the utilization efficiency, acquire modulated electronic structure and optimized binding strength with intermediates. In this review, we have provided an interview of the recent progress achieved in the field of electrocatalysis, photocatalysis, and heterogeneous reaction based on Cu SACs. Started by this review, we have summarized some advanced synthetic strategies for the construction of Cu SACs. Subsequently, the performance-improving strategies are discussed in terms of the coordination environments of the reaction center, reaction mechanism and selectivity, based on free energy diagram and electron structure analysis. Finally, the remaining issues, challenges, and opportunities of Cu SACs are also provided, affording a perspective for future studies. This review not only offers us a deep understanding on the catalytic mechanism of Cu SACs for energy conversion, but also encourages more endeavors in prompting their practical application.
Accurate and sensitive strategies for Concanavalin A (Con A) sensing are conducive to the better cognition of various important biological and physiological processes. Here, by designing dextran-functionalized fluorescent microspheres (DxFMs) and boric acid-modified carbon dots (BCDs) as recognition unit and built-in signal reference respectively, a ratiometric fluorescent detection platform was proposed for Con A detection with high reliability. In this protocol, the BCDs/DxFMs precipitation was formed due to the covalent interactions between cis-diol of DxFMs and boronic acid groups of BCDs, thus only fluorescence of BCDs could be detected in the supernatant. When Con A was presented, it could bind to DxFMs through its carbohydrate recognition ability and suppress the subsequent assembly between DxFMs and BCDs, leading to the simultaneous capture of DxFMs and BCDs fluorescence in the supernatant. Since the BCDs content was superfluous, their fluorescence intensities were basically constant in all cases. Based on the unchanged BCDs fluorescence signal and target-dependent DxFMs fluorescence signal in supernatant, the ratiometric detection of Con A was realized. Under optimized conditions, this ratiometric fluorescent platform displayed a linear detection range from 0.125 µg/mL to 12.5 µg/mL with a detection limit of 0.089 µg/mL. Moreover, satisfied analytical outcomes for Con A detection in serum samples were obtained, manifesting huge application potential of this ratiometric fluorescent platform in clinical diagnosis.
We report the photo-mediated 1,2-aryl migration of 2–chloro-1-arylpropanones to 2-arylpropionic acids using HCOONa as an acid scavenger. This pragmatically focused study obviates the multiple-step sequence in the industrially employed, ZnO-promoted rearrangement strategy, and offers rapid access to various 2-arylpropionic acids under environmentally friendly conditions. Furthermore, the successful transfer of this batch photochemistry to a continuous flow platform led to improved scalability and enabled the gram-scale synthesis of loxoprofen.
Rapid analysis of metal ions and organic compounds in strong acidic solutions is of sustainable interest in multiple disciplines. However, complicated and time-consuming pretreatments are always required for MS analysis of the compounds in strong acidic solutions. Otherwise, it will result in a weak signal and cause serious damage to the mass spectrometer. Herein, a simple method inherited from nano-ESI MS was developed for rapid analysis of strong acidic solutions. Nanoliter (nL) strong acidic solution was first loaded in the nano-ESI emitter, followed by evaporation to remove the H+ and leave the analytes on the wall of the nano-ESI emitter. The evaporation process can be completed within 1 min because of the extremely tiny volume (≤1 nL) of the loaded solution. Then, the dried analytes on the wall of the nano-ESI emitter were redissolved by loading a new solvent, followed by nano-ESI MS analysis. By using this method, metal ions and organic compounds in the strong acidic solution can be detected with low sample consumption (1 nL), high speed (< 2 min/sample), high sensitivity (limit of detection = 0.2 µg/L), and high accuracy (> 90%). Proof-of-concept applications of the present method have been successfully achieved for the analysis of gastric juice (pH of the sample = 1), monitoring reaction catalyzed by strong acid (pH of the system = 0), and micro-area analysis of ores (pH of the extraction solvent = 0), showing great application potential in multiple fields.
Biomass pyrolysis oil can be improved effectively by electrocatalytic hydrogenation (ECH). However, the unclear interactions among different components lead to low bio-oil upgrading efficiency in the conversion process. Herein, benzaldehyde and phenol, as common compounds in bio-oil, were chosen as model compounds. The interactions between the two components were explored in the ECH process by combining experiments and theoretical calculations. Results showed that phenol could accelerate the conversion of benzaldehyde in the ECH. The selectivity of benzyl alcohol was increased from 60.9% of unadded phenol to 99.1% with 30 mmol/L phenol concentration at 5 h. Benzaldehyde inhibited the ECH of phenol. In the presence of benzaldehyde, the conversion rate of phenol was below 10.0% with no cyclohexanone and cyclohexanol formation at 5 h. The density functional theory (DFT) calculations revealed that the phenol could promote the adsorption of benzaldehyde and facilitate the targeted conversion of benzaldehyde on the active site by lowering the reaction energy barrier. The research on the interaction between phenol and benzaldehyde in the ECH provides a theoretical basis for the application of ECH in practical bio-oil upgrading.
Interface engineering is of great importance to improve the photocatalytic performance. Herein, in-situ formation plasmon Bi/BiOCl nanosheets assembled heterojunction microspheres are fabricated via facile reductive solvothermal approach. The aldehyde group in the DMF structure is used to exert the weak reducing property of the solvent and thus strip out the metal Bi in BiOCl. The metal Bi is anchored on surface of BiOCl firmly due to in-situ formation engineered interface, which could realize efficient charge transfer channel. The resultant Bi/BiOCl heterojunctions assemblies with narrow bandgap of 3.05 eV and mesoporous structure extend the photoresponse to visible light region and could provide sufficient surface active sites. The visible-light-driven photocatalytic degradation of high-toxic norfloxacin for Bi/BiOCl heterojunctions is up to 95.5% within 20 min, representing several times that of pristine BiOCl nanosheets and the physical mixture. It is attributed to the in-situ formation of Bi/BiOCl heterojunctions and surface plasmon resonance (SPR) effect of plasmon Bi promoting charge transfer, and the obvious photothermal effect promoting the photocatalytic reaction, which are verified by experimental and density functional theory (DFT) calculations. This strategy provides ideal perspectives for fabricating metal/semiconductor heterojunctions photocatalysts with high-performance.
Predictive modeling of photocatalytic NO removal is highly desirable for efficient air pollution abatement. However, great challenges remain in precisely predicting photocatalytic performance and understanding interactions of diverse features in the catalytic systems. Herein, a dataset of g-C3N4-based catalysts with 255 data points was collected from peer-reviewed publications and machine learning (ML) model was proposed to predict the NO removal rate. The result shows that the Gradient Boosting Decision Tree (GBDT) demonstrated the greatest prediction accuracy with R2 of 0.999 and 0.907 on the training and test data, respectively. The SHAP value and feature importance analysis revealed that the empirical categories for NO removal rate, in the order of importance, were catalyst characteristics > reaction process > preparation conditions. Moreover, the partial dependence plots broke the ML black box to further quantify the marginal contributions of the input features (e.g., doping ratio, flow rate, and pore volume) to the model output outcomes. This ML approach presents a pure data-driven, interpretable framework, which provides new insights into the influence of catalyst characteristics, reaction process, and preparation conditions on NO removal.
DNA nanomaterials hold great promise in biomedical fields due to its excellent sequence programmability, molecular recognition ability and biocompatibility. Hybridization chain reaction (HCR) is a simple and efficient isothermal enzyme-free amplification strategy of DNA, generating nicked double helices with repeated units. Through the design of HCR hairpins, multiple nanomaterials with desired functions are assembled by DNA, exhibiting great potential in biomedical applications. Herein, the recent progress of HCR-based DNA nanomaterials for biosensing, bioimaging and therapeutics are summarized. Representative works are exemplified to demonstrate how HCR-based DNA nanomaterials are designed and constructed. The challenges and prospects of the development of HCR-based DNA nanomaterials are discussed. We envision that rationally designing HCR-based DNA nanomaterials will facilitate the development of biomedical applications.
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