Effect and mechanism of green and aldehyde aroma compounds from sweet orange on sucrose sweetness perception.

At present, there are relatively few studies on the influence of green aroma and aldehyde aroma compounds on the sweetness perception of sucrose. This study examined the effects of 11 aroma compounds from sweet orange, characterized by green and aldehyde flavors, on the sweetness of a 5 % sucrose solution. Using artificial sensory analysis and electronic tongue technology, it was found that most aromatic compounds can inhibit sweetness perception, and the inhibitory effect of trans-2-decenoaldehyde is the most significant.

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.

Efficient Inhibition of Deep Conversion of Partial Oxidation Products in C-H Bonds' Functionalization Utilizing O 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 O, 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.

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.

Double boron-oxygen-fused polycyclic aromatic hydrocarbons: skeletal editing and applications as organic optoelectronic materials.

An efficient one-pot strategy for the facile synthesis of double boron-oxygen-fused polycyclic aromatic hydrocarbons (dBO-PAHs) with high regioselectivity and efficient skeletal editing is developed. The boron-oxygen-fused rings exhibit low aromaticity, endowing the polycyclic aromatic hydrocarbons with high chemical and thermal stabilities. The incorporation of the boron-oxygen units enables the polycyclic aromatic hydrocarbons to show single-component, low-temperature ultralong afterglow of up to 20 s.

Predicting band gaps of MOFs on small data by deep transfer learning with data augmentation strategies.

Porphyrin-based MOFs combine the unique photophysical and electrochemical properties of metalloporphyrins with the catalytic efficiency of MOF materials, making them an important candidate for light energy harvesting and conversion. However, accurate prediction of the band gap of porphyrin-based MOFs is hampered by their complex structure-function relationships. Although machine learning (ML) has performed well in predicting the properties of MOFs with large training datasets, such ML applications become challenging when the training data size of the materials is small.

Deep transfer learning for predicting frontier orbital energies of organic materials using small data and its application to porphyrin photocatalysts.

Machine learning (ML) models have received increasing attention as a new approach for the virtual screening of organic materials. Although some ML models trained on large databases have achieved high prediction accuracy, the application of ML to certain types of organic materials is limited by the small amount of available data. On the other hand, metalloporphyrins and porphyrins (MpPs) have received increasing attention as potential photocatalysts, and recent studies have found that both HOMO/LUMO energy levels and energy gaps are important factors controlling the MpP photocatalysts.

Computational Exploration of Dirhodium Complex-Catalyzed Selective Intermolecular Amination of Tertiary vs. Benzylic C-H Bonds.

The mechanism and origins of site-selectivity of Rh(-tfpttl)-catalyzed C()-H bond aminations were studied using density functional theory (DFT) calculations. The synergistic combination of the dirhodium complex Rh(-tfpttl) with -butylphenol sulfamate TBPhsNH composes a pocket that can access both tertiary and benzylic C-H bonds. The nonactivated tertiary C-H bond was selectively aminated in the presence of an electronically activated benzylic C-H bond.

Mechanistic Study of Chemoselectivity for Carbon Radical Hydroxylation versus Chlorination with Fe (OH)(Cl) Complexes.

The Fe (OH)(Cl) complex resembles the key intermediate proposed for the non-heme iron halogenases. Goldberg and co-workers reported that the Fe (OH)(Cl) RC reacts with triphenylmethyl radical 1 to give an exclusive hydroxylation product. To understand the chemoselectivity of the reaction of RC with 1, density functional theory (DFT) calculations have been conducted.

A theoretical study of the ligand-controlled palladium-catalysed regiodivergent synthesis of dibenzosilepin derivatives.

Palladium-catalysed ligand-controlled 1,-palladium migration of silicon-tethering substrates provides a regiodivergent synthesis strategy for constructing silicon-bridged π-conjugated compounds possessing a 6,6-fused or a 5,7-fused scaffold. Density functional theory (DFT) calculations were carried out to elucidate the detailed mechanism of this 1,-palladium migration involving - or -carbopalladation. The computational results suggest that alkyne insertion is the regioselectivity-determining step.

A chemometric strategy to automatically screen selected ion monitoring ions for gas chromatography-mass spectrometry-based pseudotargeted metabolomics.

The pseudotargeted metabolomics based on gas chromatography-mass spectrometry (GC-MS) has the advantage of filtering out artifacts originating from sample treatment and accurately quantifying underlying compounds in the analyzed samples. However, this technique faces the problem of selecting high-quality selective ions for performing selected ion monitoring (SIM) on instruments. In this work, we proposed AntDAS-SIMOpt, an automatic untargeted strategy for SIM ion optimization that was accomplished on the basis of an experimental design combined with advanced chemometric algorithms.

Mechanistic Investigation of Palladium-Catalyzed -C-H Bond Activation of Arenes with a Carboxyl Directing Group.

The mechanism of Pd(II)-catalyzed -C-H bond olefination of arenes with a carboxyl directing group (DG)-containing template has been investigated with density functional theory. The reaction includes three major steps: C-H bond activation, alkene insertion, and β-hydride elimination. The C-H activation step, which proceeds via a concerted metalation-deprotonation pathway, is found to be the rate- and regioselectivity-determining step.

Microwave-assisted Natural Deep Eutectic Solvents Pretreatment Followed by Hydrodistillation Coupled with GC-MS for Analysis of Essential Oil from Turmeric (Curcuma longa L.).

In the past decade, natural deep eutectic solvents (NADESs) as green and sustainable extraction solvents with great potential for the efficient extraction of bioactive compounds from the plants are emerging. In this study, a microwave-assisted technology is used to prepare natural deep eutectic solvents. And natural deep eutectic solvents as pretreatment solvents coupled with microwave-assisted hydrodistillation (MAHD) for isolating essential oil (EO) derived from turmeric (Curcuma longa L.

Computational Studies on the Mechanism and Origin of the Different Regioselectivities of Manganese Porphyrin-Catalyzed C-H Bond Hydroxylation and Amidation of Equilenin Acetate.

The manganese porphyrin-catalyzed C-H bond hydroxylation and amidation of equilenin acetate developed by Breslow and his co-worker have been investigated with density functional theory (DFT) calculations. The hydroxylation of C(sp)-H bond of equilenin acetate leading to the 6-hydroxylated product is more favorable than the hydroxylation of C(sp)-H bond of equilenin acetate, leading to the 11β-hydroxylation product. The computational results suggest that the C(sp)-H bond hydroxylation of equilenin acetate undergoes an oxygen-atom-transfer mechanism, which is more favorable than the C(sp)-H bond hydroxylation undergoing the hydrogen-atom-abstraction/oxygen-rebound (HAA/OR) mechanism by 1.

Rh(iii)-catalyzed, hydrazine-directed C-H functionalization with 1-alkynylcyclobutanols: a new strategy for 1H-indazoles.

Rh(iii)-catalyzed coupling of phenylhydrazines with 1-alkynylcyclobutanols was realized through a hydrazine-directed C-H functionalization pathway. This [4+1] annulation, based on the cleavage of a Csp-Csp triple bond in alkynylcyclobutanol, provides a new pathway to prepare diverse 1H-indazoles under mild reaction conditions.

Understanding the structures and aromaticity of heteroporphyrins with computations.

Heteroporphyrins are porphyrin derivatives with replacement of the pyrrolic NH moiety by other heteroatom-containing groups, such as PH, AsH, SiH2, O, S, etc. For all studied heteroporphyrins, the macrocycle structure is distorted due to the presence of large heteroatoms. The HOMO-LUMO gap of heteroporphyrins is generally decreased compared to regular porphyrins.

Mechanism and stereoselectivity of benzylic C-H hydroxylation by Ru-porphyrin: a computational study.

The mechanism and origin of the stereoselectivity of asymmetric benzylic C-H hydroxylation by Ru-porphyrin were elucidated with density functional theory calculations. The reaction proceeds via a hydrogen-atom abstraction/oxygen-rebound pathway, wherein a high-valent ruthenium-oxo species abstracts a hydrogen atom from ethylbenzene to generate a radical pair intermediate, followed by the oxygen-rebound process to form 1-phenylethanol. The hydrogen-atom abstraction step is the rate- and stereoselectivity-determining step.

Computational Exploration of Chiral Iron Porphyrin-Catalyzed Asymmetric Hydroxylation of Ethylbenzene Where Stereoselectivity Arises from π-π Stacking Interaction.

The mechanism and origins of stereoselectivity of chiral iron porphyrin-catalyzed asymmetric hydroxylation of ethylbenzene were explored with density functional theory. The hydrogen atom abstraction is the rate- and stereoselectivity-determining step. In good agreement with experimental results, the formation of the ()-1-phenylethanol product is found to be the most favorable pathway.

ZnCdSe-CdTe quantum dots: A "turn-off" fluorescent probe for the detection of multiple adulterants in an herbal honey.

To enhance the power of untargeted detection, a "turn-off" fluorescent probe with double quantum dots (QDs) was developed and coupled with chemometrics for rapid detection of multiple adulterants in an herbal (Rhus chinensis Mill., RCM) honey. The double water-soluble ZnCdSe-CdTe QDs have two separate and strong fluorescent peaks, which can be quenched by honey and extraneous adulterants with varying degrees.

Characterization of Aroma-Active Components and Antioxidant Activity Analysis of E-jiao (Colla Corii Asini) from Different Geographical Origins.

E-jiao (Colla Corii Asini, CCA) has been widely used as a healthy food and Chinese medicine. Although authentic CCA is characterized by its typical sweet and neutral fragrance, its aroma components have been rarely investigated. This work investigated the aroma-active components and antioxidant activity of 19 CCAs from different geographical origins.

Automatic untargeted metabolic profiling analysis coupled with Chemometrics for improving metabolite identification quality to enhance geographical origin discrimination capability.

Untargeted metabolic profiling analysis is employed to screen metabolites for specific purposes, such as geographical origin discrimination. However, the data analysis remains a challenging task. In this work, a new automatic untargeted metabolic profiling analysis coupled with a chemometric strategy was developed to improve the metabolite identification results and to enhance the geographical origin discrimination capability.

Detection of unexpected frauds: Screening and quantification of maleic acid in cassava starch by Fourier transform near-infrared spectroscopy.

Fourier transform near-infrared (FT-NIR) spectroscopy and chemometrics were adopted for the rapid analysis of a toxic additive, maleic acid (MA), which has emerged as a new extraneous adulterant in cassava starch (CS). After developing an untargeted screening method for MA detection in CS using one-class partial least squares (OCPLS), multivariate calibration models were subsequently developed using least squares support vector machine (LS-SVM) to quantitatively analyze MA. As a result, the OCPLS model using the second-order derivative (D2) spectra detected 0.

Simple automatic strategy for background drift correction in chromatographic data analysis.

Chromatographic background drift correction, which influences peak detection and time shift alignment results, is a critical stage in chromatographic data analysis. In this study, an automatic background drift correction methodology was developed. Local minimum values in a chromatogram were initially detected and organized as a new baseline vector.