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.

Revealing the key antioxidant compounds and potential action mechanisms of Chinese Cabernet Sauvignon red wines by integrating UHPLC-QTOF-MS-based untargeted metabolomics, network pharmacology and molecular docking approaches.

In recent years, red wine drinking has become more popular in China owing to its antioxidant effects. However, the key antioxidant compounds and their action mechanisms of Chinese red wines are still unclear. Herein, the antioxidant activities and chemical compositions of 45 Chinese Cabernet Sauvignon red wine samples were determined using chemical antioxidant assays and an UHPLC-QTOF-MS-based untargeted metabolomics method. The key antioxidant compounds in red wines and potential action mechanisms were revealed by integrating network pharmacology and molecular docking approaches. Results showed that there are 8 key antioxidant compounds in the red wine samples. These compounds are involved in several metabolic pathways in the body, particularly PI3K/AKT. What's more, they bind to the core antioxidant targets through hydrogen bonding and hydrophobic interaction. Among them, myricetin, laricitrin, 2,3,8-tri-O-methylellagic acid and AKT1 have the highest binding energies. This study could provide the theoretical basis for further investigation of physiological activities and functions of Chinese red wines.

Transfer learning across different chemical domains: virtual screening of organic materials with deep learning models pretrained on small molecule and chemical reaction data.

Machine learning is becoming a preferred method for the virtual screening of organic materials due to its cost-effectiveness over traditional computationally demanding techniques. However, the scarcity of labeled data for organic materials poses a significant challenge for training advanced machine learning models. This study showcases the potential of utilizing databases of drug-like small molecules and chemical reactions to pretrain the BERT model, enhancing its performance in the virtual screening of organic materials. By fine-tuning the BERT models with data from five virtual screening tasks, the version pretrained with the USPTO-SMILES dataset achieved R2 scores exceeding 0.94 for three tasks and over 0.81 for two others. This performance surpasses that of models pretrained on the small molecule or organic materials databases and outperforms three traditional machine learning models trained directly on virtual screening data. The success of the USPTO-SMILES pretrained BERT model can be attributed to the diverse array of organic building blocks in the USPTO database, offering a broader exploration of the chemical space. The study further suggests that accessing a reaction database with a wider range of reactions than the USPTO could further enhance model performance. Overall, this research validates the feasibility of applying transfer learning across different chemical domains for the efficient virtual screening of organic materials.Scientific contributionThis study verifies the feasibility of applying transfer learning to large language models in different chemical fields to help organic materials perform virtual screening. Through the comparison of transfer learning from different chemical fields to a variety of organic material molecules, the high precision virtual screening of organic materials is realized.

Mechanistic Insights into Oxidation of Benzaldehyde by Co-Peroxo Complexes.

Transition metal-peroxide complexes play a crucial role as intermediates in oxidation reactions. To unravel the mechanism of benzaldehyde oxidation by the Co-peroxo complex, we conducted density functional theory (DFT) calculations. The identified competing mechanisms include nucleophilic attack and hydrogen atom transfer (HAT). The nucleophilic attack pathway involves Co-O cleavage and nucleophilic attack, leading to the formation of the benzoate product. And the HAT pathway comprises O-O cleavage and HAT, ultimately resulting in the benzoate product. DFT calculations revealed that the formation of the end-on Co-superoxo complex 2 through Co-O cleavage, starting from the side-on Co-peroxo complex 1, is much more favorable than the formation of the two-terminal oxyl-radical intermediate 3 through O-O cleavage. Compared with the nucleophilic attack of benzaldehyde by 2, the abstraction of a hydrogen atom from benzaldehyde by 3 requires higher energy. The nature of the nucleophilicity of 2 and 3 accounts for the reactivity of the reaction.

Acceleration of Photoinduced Electron Transfer by Modulating Electronegativity of Substituents in Stable Zr-Metal-Organic Frameworks to Boost Photocatalytic CO2 Reduction.

Photoreduction of CO2 with water into chemical feedstocks of fuels provides a green way to help solve both the energy crisis and carbon emission issues. Metal-organic frameworks (MOFs) show great potential for CO2 photoreduction. However, poor water stability and sluggish charge transfer could limit their application. Herein, three water-stable MOFs functionalized with electron-donating methyl groups and/or electron-withdrawing trifluoromethyl groups are obtained for the CO2 photoreduction. Compared with UiO-67-o-CF3-CH3 and UiO-67-o-(CF3)2, UiO-67-o-(CH3)2 achieves excellent performance with an average CO generation rate of 178.0 µmol g-1 h-1 without using any organic solvent or sacrificial reagent. The superior photocatalytic activity of UiO-67-o-(CH3)2 is attributed to the fact that compared with trifluoromethyl groups, methyl groups could not only elevate CO2 adsorption capacity and reduction potential but also promote photoinduced charge separation and migration. These are evidenced by gas physisorption, photoluminescence, time-resolved photoluminescence, electrochemical impedance spectroscopy, transient photocurrent characteristics, and density functional theory calculations. The possible working mechanisms of electron-donating methyl groups are also proposed. Moreover, UiO-67-o-(CH3)2 demonstrates excellent reusability for the CO2 reduction. Based on these results, it could be affirmed that the strategy of modulating substituent electronegativity could provide guidance for designing highly efficient photocatalysts.

AntDAS-GCMS: A New Comprehensive Data Analysis Platform for GC-MS-Based Untargeted Metabolomics with the Advantage of Addressing the Time Shift Problem.

Over the years, a number of state-of-the-art data analysis tools have been developed to provide a comprehensive analysis of data collected from gas chromatography-mass spectrometry (GC-MS). Unfortunately, the time shift problem remains unsolved in these tools. Here, we developed a novel comprehensive data analysis strategy for GC-MS-based untargeted metabolomics (AntDAS-GCMS) to perform total ion chromatogram peak detection, peak resolution, time shift correction, component registration, statistical analysis, and compound identification. Time shift correction was specifically optimized in this work. The information on mass spectra and elution profiles of compounds was used to search for inherent landmarks within analyzed samples to resolve the time shift problem across samples efficiently and accurately. The performance of our AntDAS-GCMS was comprehensively investigated by using four complex GC-MS data sets with various types of time shift problems. Meanwhile, AntDAS-GCMS was compared with advanced GC-MS data analysis tools and classic time shift correction methods. Results indicated that AntDAS-GCMS could achieve the best performance compared to the other methods.

Pt-S Bond-Enabled Temperature-Dependent Phosphorescence in S-Heteroaryl Tetradentate Pt(S

This study presents the rare examples of S-heteroaryl tetradentate Pt(S^C^N^O) luminescent complexes (PtSZ and PtSZtBu) containing a Pt-S bond. The presence of the Pt-S bond allows the novel Pt(S^C^N^O) complexes to exhibit temperature-dependent phosphorescent emission behavior. The PtSZtBu exhibits dual-emission phenomena and biexponential transient decay spectra above 250 K, indicating the presence of two minimal excited states in the potential energy surface (PES) of the T1 state. Through complementary experimental and computational studies, we have identified changes in orbital composition between Pt(dxy)-S(px) and Pt(dyz)-S(pz) in excited states with increasing temperature. This results in two energy minima, enabling the excited states to decay selectively and radiatively at different temperatures. Consequently, this leads to remarkable steady-state and transient emission spectra changes. Our work not only provides valuable insights for the development of novel Pt-S bond-based tetradentate Pt(II) complexes but also enhances our understanding of the distinctive properties governed by the Pt-S bond.

Esters-targeted colorimetric sensor array for the authenticity discrimination of strong-aroma baijiu with different origins.

Baijiu authenticity has been a frequent problem driven by economic interests in recent years, so it is important to discriminate against baijiu with different origins. Herein, we proposed a simple and efficient esters-targeted colorimetric sensor array mediated by hydroxylamine hydrochloride. Esters undergo a nucleophilic addition reaction with hydroxylamine hydrochloride to form hydroxamic acid, which rapidly forms a purplish red ferric hydroxamate under FeCl3·6H2O. Bromophenol blue and rhodamine B enrich the color effects. The array detected 12 esters with a detection limit on the order of 10-5 of most esters and 16 mixed esters with R2 > 0.999 and recoveries close to 100%. Otherwise, for discriminating 34 strong-aroma baijius (SABs), the array has an accuracy of 98% according to the origin, and 95% according to the grades, with a response time of 1 min. This study provides a new strategy for authenticity determination and quality control of baijiu.

Efficient Inhibition of Deep Conversion of Partial Oxidation Products in C-H Bonds' Functionalization Utilizing O2 via Relay Catalysis of Dual Metalloporphyrins on Surface of Hybrid Silica Possessing Capacity for Product Exclusion.

To inhibit the deep conversion of partial oxidation products (POX-products) in C-H bonds' functionalization utilizing O2, 5-(4-(chloromethyl)phenyl)-10,15,20-tris(perfluorophenyl)porphyrin cobalt(II) and 5-(4-(chloromethyl)phenyl)-10,15,20-tris(perfluorophenyl)porphyrin copper(II) were immobilized on the surface of hybrid silica to conduct relay catalysis on the surface. Fluorocarbons with low polarity and heterogeneous catalysis were devised to decrease the convenient accessibility of polar POX-products to catalytic centers on the lower polar surface. Relay catalysis between Co and Cu was designed to utilize the oxidation intermediates alkyl hydroperoxides to transform more C-H bonds. Systematic characterizations were conducted to investigate the structure of catalytic materials and confirm their successful syntheses. Applied to C-H bond oxidation, not only deep conversion of POX-products was inhibited but also substrate conversion and POX-product selectivity were improved simultaneously. For cyclohexane oxidation, conversion was improved from 3.87% to 5.27% with selectivity from 84.8% to 92.3%, which was mainly attributed to the relay catalysis on the surface excluding products. The effects of the catalytic materials, product exclusion, relay catalysis, kinetic study, substrate scope, and reaction mechanism were also investigated. To our knowledge, a practical and novel strategy was presented to inhibit the deep conversion of POX-products and to achieve efficient and accurate oxidative functionalization of hydrocarbons. Also, a valuable protocol was provided to avoid over-reaction in other chemical transformations requiring high selectivity.

In Situ Construction of CuTCPP/Bi4O5Br2 Hybrids for Improved Photocatalytic CO2 and Cr(VI) Reduction.

Global warming and heavy metal pollution pose tremendous challenges to human development, and photocatalysis is considered to be an effective strategy to solve these problems. Herein, copper(II) tetra (4-carboxyphenyl) porphyrin (CuTCPP) molecules were successfully in situ loaded onto Bi4O5Br2 by a hydrothermal approach. A series of experimental results show that the light absorption capacity and photogenerated carrier separation efficiency were synchronously enhanced after the construction of CuTCPP/Bi4O5Br2 composites. Hence, the as-prepared composites possess significantly improved photocatalytic ability for both CO2 and Cr(VI) reduction. Specifically, CuTCPP/Bi4O5Br2-2 achieves a CO generation rate of 17.14 µmol g-1 under 5 h irradiation, which is twice as high as that of Bi4O5Br2 (8.57 µmol g-1). Besides, the optimized CuTCPP/Bi4O5Br2-2 also exhibits a removal rate of 61.87% for Cr(VI) within 100 min under irradiation. Furthermore, the mechanism of CO2 and Cr(VI) photoreduction was explored by in situ Fourier transform infrared spectroscopy and capture experiments, respectively. This work can be a reference toward the construction of photocatalysts with high activity for solar energy conversion.

An ion synergism fluorescence probe via Cu2+ triggered competition interaction to detect glyphosate.

The widespread use of glyphosate (Gly) poses significant risks to environmental and human health, underscoring the urgent need for its sensitive and rapid detection. In this work, we innovated by developing a novel material, ionic liquids, which formed the ionic probe "[P66614]2[2,3-DHN]-Cu2+ (PDHN-Cu2+)" through coordination with Cu2+. This probe capitalized on the distinctive fluorescence quenching properties of ionic liquids in the presence of Cu2+, driven by synergistic interactions between anions and cations. Glyphosate disrupted the PDHN-Cu2+ coordination structure due to its stronger affinity for Cu2+, triggering a "turn-on" fluorescence response. Impressively, PDHN-Cu2+ enabled the sensitive detection of glyphosate within just one minute, achieving a detection limit as low as 71.4 nM and excellent recovery rates of 97-103% in diverse samples. This groundbreaking approach, utilizing ionic probes, lays a robust foundation for the accurate and real-time monitoring of pesticides, employing a strategy based on synergism and competitive coordination.

A colorimetric sensor based on 4-MPBA Au@AgNPs for accurately identification of EnshiYulu tea grade.

Enshi Yulu green tea (ESYL) is the most representative traditional steamed green tea in Enshi, Hubei. Different ESYL grades exhibit distinct flavors, tastes, and prices. In this study, a visual sensor based on 4-MPBA Au@AgNPs was developed for the rapid and accurate identification of ESYL grades. The recognition mechanism involved the binding of 4-MPBA Au@AgNPs with polyphenolic compounds in ESYL to form borate esters and the conversion of Ag+ to Ag0, with the generated Ag0 depositing on the surface of 4-MPBA Au@AgNPs. The results showed that the sensor can amplify the color differences of different grades of ESYL. The visual results were also validated by the partial least squares discriminant analysis model, demonstrating an enhancement in recognition accuracy from 68.2 % to 95.5 % compared to the original extraction solution. The colorimetric sensor developed in this study is expected to provide a new approach for traceability research of other foods.

Discrimination and prediction of Qingzhuan tea storage year using quantitative chemical profile combined with multivariate analysis: Advantages of MRMHR based targeted quantification metabolomics.

The duration of storage significantly influences the quality and market value of Qingzhuan tea (QZT). Herein, a high-resolution multiple reaction monitoring (MRMHR) quantitative method for markers of QZT storage year was developed. Quantitative data alongside multivariate analysis were employed to discriminate and predict the storage year of QZT. Furthermore, the content of the main biochemical ingredients, catechins and alkaloids, and free amino acids (FAA) were assessed for this purpose. The results show that targeted marker-based models exhibited superior discrimination and prediction performance among four datasets. The R2Xcum, R2Ycum and Q2cum of orthogonal projection to latent structure-discriminant analysis discrimination model were close to 1. The correlation coefficient (R2) and the root mean square error of prediction of the QZT storage year prediction model were 0.9906 and 0.63, respectively. This study provides valuable insights into tea storage quality and highlights the potential application of targeted markers in food quality evaluation.

Perimidocarbene-Based Tetradentate Platinum(II) Complexes with an Unexpectedly Negligible 3MLCT Character.

Two novel six-membered perimidocarbene (PIC)-based tetradentate Pt(II) complexes were designed and successfully synthesized. Systematical experimental and theoretical studies suggest that the PIC moiety greatly affects the frontier orbitals, as well as the photophysical and excited-state properties of the Pt(II) complexes. PtYK2 has a broad emission spectrum peaking at 576 nm with a shoulder band at 620 nm, along with a full width at half-maximum (FWHM) value of 100.0 nm at 77 K in 2-MeTHF; however, the emission spectrum is slightly red-shifted with a dominant peak at 610 nm and a FWHM value of 125.0 nm at room temperature in a poly(methyl methacrylate) (PMMA) film. Time-dependent-density functional theory and natural transition orbital analyses reveal that PtYK2 has a 3LC (3πPIC* → πPIC)-dominated character with an unexpectedly negligible contribution of 3MLCT transition (0.68%) in the T1 state, which results in a broad emission spectrum and a relatively low quantum efficiency of 7.4% in the PMMA film.

A fluorescence ionic probe utilizing Cu2+ assisted competition for detecting glyphosate abused in green tea.

Food fraud caused by the violation of glyphosate use in tea is frequently exposed, posing a potential health risk to consumers and undermining trust in food safety. In the work, an ionic fluorescent probe "[P66614] [4HQCA]-Cu2+ (PHQCA-Cu2+)" was constructed using Cu2+ and ionic liquids coordination through a competitive coordination strategy to detect glyphosate. This probe exhibited a prominent "turn-on" fluorescence response in glyphosate detection. PHQCA-Cu2+was destroyed by glyphosate with its strong coordination capability, and a new complex re-formed simultaneously between glyphosate and the Cu2+ in it, where Cu2+ served as an "invisible indicator" influencing fluorescence changes. Remarkably, PHQCA-Cu2+formed rapidly within 5 s, demonstrated exceptional sensitivity and selectivity, and satisfactory detection performance on paper strips impregnated withPHQCA-Cu2+.Importantly,PHQCA-Cu2+showed excellent recoveries in various green tea, which offered a viable method for identifying contaminated products from the supply chain quickly to enhance overall food safety surveillance.

A novel organic acids-targeted colorimetric sensor array for the rapid discrimination of origins of Baijiu with three main aroma types.

Given the severe problem of Baijiu authenticity, it is essential to discriminate Baijiu from different origins quickly and effectively. As organic acids (OAs) are the most dominant taste-imparting substances in Baijiu, we proposed a simple, fast, and effective OAs-targeted colorimetric sensor array based on the colorimetric reaction of 4-aminophenol (AP)/4-amino-3-chlorophenol (ACP) under oxidation of Cu(NO3)2 for the rapid discrimination of origins of Baijiu with three main aroma types. Hydrogen ions ionized from OAs induced the protonation of the amino group, which blocked the colorimetric reaction, and the different levels of OAs in Baijiu enabled the array to discriminate different origins of Baijiu. The array was implemented to analyze 10 simple OAs and 16 mixed OAs and further for the discrimination of 42 Baijius with an accuracy of 98%. This method provided an efficient research strategy for a basis for rapid quality analysis of Baijiu.

Inclusion complexes of ß-cyclodextrin with isomeric ester aroma compounds: Preparation, characterization, mechanism study, and controlled release.

Cyclodextrins (CDs) have been discovered to provide an efficient solution to the limited application of ester aroma molecules used in food, tobacco, and medication due to their strong smell and unstable storage. This work combined molecular modeling and experimental to analyze the conformation and controlled release of isomeric ester aroma compounds/ß-CD inclusion complexes (ICs). The investigation revealed that ester aroma compounds could be effectively encapsulated within the ß-CD cavity, forming ICs with low binding affinity. Furthermore, the key driving forces in ICs were identified as hydrogen bonds and van der Waals interactions through theoretical simulation. Results from the Fourier transform infrared (FTIR), nuclear magnetic resonance (NMR) and Isothermal titration calorimetry (ITC) experiments confirmed the intermolecular interaction predicted by the molecular model. Notably, the release rate of aroma compounds from L-menthyl acetate/ß-CD (LMA/ß-CD) IC exceeded that of terpinyl acetate/ß-CD (TA/ß-CD) IC. This difference is attributed to the length of the chain of aroma molecules and the variation in the position of functional groups, influencing the stable formation of ICs with ß-CD. These findings hold potential implications for refining the application of ICs across diverse industries.

Rapid visual detection of sulfur dioxide residues in food using acid-sensitive CdTe quantum dots-loaded alginate hydrogel beads.

Acid-sensitive CdTe quantum dots-loaded alginate hydrogel (CdTe QDs-AH) beads were designed for the visual detection of SO2 residues. As proof of concept, two types of CdTe QDs were selected as model probes and embedded in AH beads. The entire test was performed within 25 min in a modified double-layer test tube with one bead fixed above the sample solution. Adding citric acid and heating at 70 ℃ for 20 min transformed the sulfites in the solution into SO2 gas, which then quenched the fluorescence of the CdTe QDs-AH beads. Using this assay, qualitative, naked-eye detection of SO2 residues was achieved in the concentration range of 25-300 ppm, as well as precise quantification was possible based on the difference in the average fluorescence brightness of the beads before and after the reaction. Five food types were successfully analysed using this method, which is simpler and more economical than existing methods, and does not require complex pretreatment.

UHPLC-QTOF-MS-based untargeted metabolomic authentication of Chinese red wines according to their grape varieties.

Wine is a very popular alcoholic drink owing to its health benefits of antioxidant effects. However, profits-driven frauds of wine especially false declarations of variety frequently occurred in markets. In this work, an UHPLC-QTOF-MS-based untargeted metabolomics method was developed for metabolite profiling of 119 bottles of Chinese red wines from four varieties (Cabernet Sauvignon, Merlot, Cabernet Gernischt, and Pinot Noir). The metabolites of red wines from different varieties were assessed using orthogonal partial least-squares discriminant analysis (OPLS-DA) and analyzed using KEGG metabolic pathway analysis. Results showed that the differential compounds among different varieties of red wines are mainly flavonoids, phenols, indoles and amino acids. The KEGG metabolic pathway analysis showed that indoles metabolism and flavonoids metabolism are closely related to wine varieties. Based on the differential compounds, OPLS-DA models could identify external validation wine samples with a total correct rate of 90.9 % in positive ionization mode and 100 % in negative ionization mode. This study indicated that the developed untargeted metabolomics method based on UHPLC-QTOF-MS is a potential tool to identify the varieties of Chinese red wines.

An artificial intelligence platform for automated PFAS subgroup classification: A discovery tool for PFAS screening.

Since structural analyses and toxicity assessments have not been able to keep up with the discovery of unknown per- and polyfluoroalkyl substances (PFAS), there is an urgent need for effective categorization and grouping of PFAS. In this study, we presented PFAS-Atlas, an artificial intelligence-based platform containing a rule-based automatic classification system and a machine learning-based grouping model. Compared with previously developed classification software, the platform's classification system follows the latest Organization for Economic Co-operation and Development (OECD) definition of PFAS and reduces the number of uncategorized PFAS. In addition, the platform incorporates deep unsupervised learning models to visualize the chemical space of PFAS by clustering similar structures and linking related classes. Through real-world use cases, we demonstrate that PFAS-Atlas can rapidly screen for relationships between chemical structure and persistence, bioaccumulation, or toxicity data for PFAS. The platform can also guide the planning of the PFAS testing strategy by showing which PFAS classes urgently require further attention. Ultimately, the release of PFAS-Atlas will benefit both the PFAS research and regulation communities.