Theoretical Investigation on Dialumenes toward Dihydrogen Activation: Mechanism and Ligand Effect.

Herein, we report a computation study based on the density functional theory calculations to understand the mechanism and ligand effect of the base-stabilized dialumenes toward dihydrogen activation. Among all of the examined modes of dihydrogen activation using the base-stabilized dialumene, we found that the concerted 1,2-hydrogenation of the Al═Al double bond is kinetically more preferable. The concerted 1,2-hydrogenation of the Al═Al double bond adopts an electron-transfer model with certain asynchrony. That is, the initial electron donation from the H-H σ bonding orbital to the empty 3p orbital of the Al1 center is followed by the backdonation from the lone pair electron of the Al2 center to the H-H σ antibonding orbital. Combined with the energy decomposition analysis on the transition states of the concerted 1,2-hydrogenation of the Al═Al double bond and the topographic steric mapping analysis on the free dialumenes, we ascribe the higher reactivity of the aryl-substituted dialumene over the silyl-substituted analogue in dihydrogen activation to the stronger electron-withdrawing effect of the aryl group, which not only increases the flexibility of the Al═Al double bond but also enhances the Lewis acidity of the Al═Al core. Consequently, the aryl-substituted dialumene fragment suffers less geometric deformation, and the orbital interactions between the dialumene and dihydrogen moieties are more attractive during the 1,2-hydrogenation process. Moreover, our calculations also predict that the Al═Al double bond has a good tolerance with the stronger electron-withdrawing group (-CF3) and the weaker σ-donating N-heterocyclic carbene (NHC) analogue (e.g., triazol carbene and NHSi). The reactivity of the dialumene in dihydrogen activation can be further improved by introducing these groups as the supporting ligand and the stabilizing base on the Al═Al core, respectively.

Enhancing soil texture classification with multivariate scattering correction and residual neural networks using visible near-infrared spectra.

Soil texture is one of the most important indicators of soil physical properties, which has traditionally been measured through laborious procedures. Approaches utilizing visible near-infrared spectroscopy, with their advantages in efficiency, eco-friendliness and non-destruction, are emerging as potent alternatives. Nevertheless, these approaches often suffer from limitations in classification accuracy, and the substantial impact of spectral preprocessing, model integration, and sample matrix effect is commonly disregarded. Here a novel 11-class soil texture classification strategy that address this challenge by combining Multiplicative Scatter Correction (MSC) with Residual Network (ResNet) models was presented, resulting in exceptional classification accuracy. Utilizing the LUCAS dataset, collected by the Land Use and Cover Area frame Statistical Survey project, we thoroughly evaluated eight spectral preprocessing methods. Our findings underscored the superior performance of MSC in reducing spatial complexity within spectral data, showcasing its crucial role in enhancing model precision. Through comparisons of three 1D CNN models and two ResNet models integrated with MSC, we established the superior performance of the MSC-incorporated ResNet model, achieving an overall accuracy of 98.97 % and five soil textures even reached 100.00 %. The ResNet model demonstrated a marked superiority in classifying datasets with similar features, as observed by the confusion matrix analysis. Moreover, we investigated the potential benefit of pre-categorization based on land cover type of the soil samples in enhancing the accuracy of soil texture classification models, achieving overall classification accuracies exceeding 99.39 % for woodland, grassland, and farmland with the 2-layer ResNet model. The proposed work provides a pioneering and efficient strategy for rapid and precise soil texture identification via visible near-infrared spectroscopy, demonstrating unparalleled accuracy compared to existing methods, thus significantly enhancing the practical application prospects in soil, agricultural and environmental science.

Theoretical Characterization of Catalytically Active Species in Reductive Hydroxymethylation of Styrene with CO2 over a Bisphosphine-Ligated Copper Complex.

In this work, a density functional theory (DFT) study was performed to identify the catalytically active species in the copper-catalyzed three-component reductive hydroxymethylation of styrene with CO2 and hydrosilane. The calculations reveal that the dimeric copper(I) hydride species, formed in a mixture of the bisphosphine ligand, Cu(OAc)2, and hydrosilane, probably acts as the catalyst precursor. In the beginning, this species is catalytically competent to trigger the hydrocupration of styrene, along with the formation of the dimeric copper(I) alkyl intermediate. Subsequently, CO2 insertion into the dimeric copper(I) alkyl intermediate occurs, which is accompanied by the cleavage of the Cu-Cu bond and the generation of the monomeric copper(I) carboxylate intermediate. In the end, the sequential reduction of the monomeric copper(I) carboxylate intermediate with the hydrosilane produces the monomeric copper(I) hydride species as the actual catalyst and turns on the catalytic cycle. On the other hand, the monomeric copper(II) hydride species, yielded as the kinetic product in the initial reaction of the bisphosphine ligand, Cu(OAc)2, and hydrosilane, is also reactive for the hydrocupration of styrene. However, the resulting monomeric copper(II) alkyl intermediate is found to be the catalyst resting state, because of the much higher energy barrier demanded for the subsequent nucleophilic attack toward CO2. On the basis of the results of an activation-strain model (ASM) analysis and charge decomposition analysis (CDA), the low activity of the monomeric copper(II) alkyl intermediate can be ascribed to the more crowded environment around the central copper(II) ion and the weaker nucleophilicity of the alkyl moiety. Furthermore, all of the possible CuH species generated in the system are competent to promote the two-component hydrosilylation of CO2 with hydrosilane, which is an inevitable side reaction along with the reductive hydroxymethylation of styrene with CO2 and hydrosilane.

Simple field-based automated dispersive liquid-liquid microextraction of trace level phthalate esters in natural waters with gas chromatography and mass spectrometric analysis.

A small, simple, and field-based automated dispersive liquid-liquid microextraction method followed by gas chromatography mass spectrometric analysis was developed for trace level phthalate esters analysis in natural waters. With a single syringe pump that is coupled with a multiposition valve, the whole extraction procedure including cleaning, sampling, mixing of extractant and disperser solvents, extraction, phase separation, and analytes collection was carried out in a totally automated way with a sample throughput of 21 h(-1) . Key factors, such as type and ratio of the extractant and disperser solvent, aspiration flow rate, extraction time, and matrix effect, were thoroughly investigated. Under the optimum conditions, linearity was found in the range from 0.03 to 60 µg/L. Limits of detection ranged from 0.0015 to 0.003 µg/L. Enrichment factors were in a range of 106-141. Reproducibility and recoveries were assessed by testing a series of three natural water samples that were spiked with different concentration levels. Finally, the proposed method was successfully applied in analysis of real surface waters. The developed system is inexpensive, light (2.6 kg), simple to use, applicable in the field, with high sample throughput, and sensitive enough for trace level phthalate esters analysis in natural waters.

Speciation analysis of mercury in sediments using ionic-liquid-based vortex-assisted liquid-liquid microextraction combined with high-performance liquid chromatography and cold vapor atomic fluorescence spectrometry.

An improved novel method based on ionic liquid vortex-assisted liquid-liquid microextraction has been developed for the extraction of methylmercury, ethylmercury and inorganic mercury in sediment samples prior to analysis by high-performance liquid chromatography with cold vapor atomic fluorescence spectrometry. In this work, mercury species were firstly complexed with dithizone, and the complexes were extracted into 1-hexyl-3-methylimidazolium hexafluorophosphate. Key factors that affect the extraction efficiency of mercury species, such as type and amount of ionic liquid and chelatants, extraction time, sample pH, salt effect and matrix effect were investigated. Under the optimum conditions, linearity was found in the concentration range from 0.1-70 ng/g. Limits of detection ranged from 0.037-0.061 ng/g. Reproducibility and recoveries were assessed by extracting a series of six independent sediment samples that were spiked with different concentration levels. Finally, the proposed method was successfully applied in analysis of real sediment samples. In this work, ionic liquids vortex-assisted liquid-liquid microextraction was for the first time used for the extraction of mercury species in sediment samples. The proposed method was proved to be much simpler and more rapid, as well as more environmentally friendly and efficient compared with the previous methods.

Determination of phthalate esters in liquor samples by vortex-assisted surfactant-enhanced-emulsification liquid-liquid microextraction followed by GC-MS.

A novel method using vortex-assisted surfactant-enhanced-emulsification liquid-liquid microextraction has been developed for the extraction of phthalate esters (PAEs) in Chinese liquor samples prior to analysis by GC-MS. In the proposed method, a high-density extraction solvent (carbon tetrachloride) was dispersed into samples with the aid of a surfactant (Triton X-100) and vortex agitation, resulting in a short extraction equilibrium (30 s). After centrifugation, a single microdrop of solvent was easily collected for GC-MS analysis. Key factors that affected the extraction efficiency were optimized. Under the optimum conditions, linearity was found in the range from 0.05 to 50 µg/L. Coefficients of determination varied from 0.9938 to 0.9971. LODs, based on an S/N of 3, ranged from 4.9 to 13 ng/L. Enrichment factors varied from 140 to 184. Reproducibility and recoveries were assessed by testing a series of three liquor samples that were spiked with different concentration levels. Finally, the proposed method was successfully applied to the determination of PAEs in 16 Chinese liquor samples. In this work, high-density-solvent vortex-assisted surfactant-enhanced-emulsification liquid-liquid microextraction was applied for the first time for the extraction of PAEs in Chinese liquor samples and was proved to be simple, rapid, and sensitive.

Enhancing soil nitrogen measurement via visible-near infrared spectroscopy: Integrating soil particle size distribution with long short-term memory models.

Good quality of soil nitrogen data, which is essential for the advancement of both enhanced agricultural management and ecological environment, traditionally depends on labor intensive chemical procedures. Visible near-infrared (Vis-NIR) spectroscopy, acknowledged for its efficiency, environmental compatibility and rapidity, merges as a promising alternative. However, the effectiveness of Vis-NIR measurement models are significantly compromised by soil particle size distribution (PSD), presenting a substantial challenge in improving the measurement accuracy and reliability. Here an innovative deep learning methodology that integrates PSD with Vis-NIR spectroscopy was proposed for the measurement of nitrogen content in soil samples. By leveraging the LUCAS dataset, different strategies for integrating PSD with Vis-NIR spectral data in deep learning models were explored, revealing that our proposed InSGraL framework, which incorporated mixed features of PSD and spectra as LSTM inputs achieves superior performance. Compared to models utilizing solely Vis-NIR data, InSGraL exhibits a 39.47 % reduction in RMSE and a 42.55 % decrease in MAE, and demonstrates robust performance across various land cover types, achieving an R2 of 0.94 on grassland samples. Moreover, Shapley Additive exPlanations (SHAP) analysis revealed that incorporating PSD modifies the spectral input importance distribution, effectively mitigating spectral interference from particle size while highlighting critical wavelengths previously obscured. This study provides an innovative modeling strategy to mitigate the influence of PSD by integrating it within deep learning framework using Vis-NIR, contributing a deeper understanding of the relationship between PSD and Vis-NIR spectra for the measurement of nitrogen content and offering an effective means to attain soil nitrogen data.

Vortex-assisted extraction combined with dispersive liquid-liquid microextraction for the determination of polycyclic aromatic hydrocarbons in sediment by high performance liquid chromatography.

A simple, rapid, and efficient method, vortex-assisted extraction followed by dispersive liquid-liquid microextraction (DLLME) has been developed for the extraction of polycyclic aromatic hydrocarbons (PAHs) in sediment samples prior to analysis by high performance liquid chromatography fluorescence detection. Acetonitrile was used as collecting solvent for the extraction of PAHs from sediment by vortex-assisted extraction. In DLLME, PAHs were rapidly transferred from acetonitrile to dichloromethane. Under the optimum conditions, the method yields a linear calibration curve in the concentration range from 10 to 2100 ng g(-1) for fluorene, anthracene, chrysene, benzo[k]fluoranthene, and benzo[a]pyrene, and 20 to 2100 ng g(-1) for other target analytes. Coefficients of determinations ranged from 0.9986 to 0.9994. The limits of detection, based on signal-to-noise ratio of three, ranged from 2.3 to 6.8 ng g(-1) . Reproducibility and recoveries was assessed by extracting a series of six independent sediment samples, which were spiked with different concentration levels. Finally, the proposed method was successfully applied in analyses of real nature sediment samples. The proposed method extended and improved the application of DLLME to solid samples, which greatly shorten the extraction time and simplified the extraction process.

[Determination of trace amounts of mercury in sediments by sequential injection cold vapor atomic fluorescence spectrometry coupled with microwave-assisted digestion].

A novel method for the determination of trace amounts of mercury in sediments by sequential injection cold vapor atomic fluorescence spectrometry coupled with microwave assisted digestion was developed in this paper. Satisfactory results were found when the digestion was carried out at 140 degrees C for 5 min by using 10% HCl-50% HNO3- 40% H2O or 30% HCl-20% HNO3- 50% H2O media. The linear range was 0.02-30 ng x mL(-1) with detection limit of 0.5 ng x g(-1). Relative standard deviation for the complete procedure of the analysis of 10 digested sediment samples was 3.7%. Recoveries of the spiked samples were between (91.2 +/- 4.3)% and (96.5 +/- 4.6)%. The analytical results for three certified reference materials GSD-2, GSD-9 and GSD-10 were consistent with the certified values. The method has been successfully applied to six natural sediment samples. The results indicated that the method was rapid, highly sensitive and precision, and suitable for the determination of trace amounts of mercury in sediment samples.

Automated, high frequency, on-line dimethyl sulfide measurements in natural waters using a novel "microslug" gas-liquid segmented flow method with chemiluminescence detection.

Dimethyl sulfide (DMS) is the major biogenic volatile sulfur compound in surface seawater. Good quality DMS data with high temporal and spatial resolution are desirable for understanding reduced sulfur biogeochemistry. Here we present a fully automated and novel "microslug" gas-liquid segmented flow-chemiluminescence (MSSF-CL) based method for the continuous in-situ measurement of DMS in natural waters. Samples were collected into a flow tank and DMS transferred from the aqueous phase to the gas phase using a vario-directional coiled flow, in which microvolume liquid and gas slugs were interspersed. The separated DMS was reacted with ozone in a reaction cell for CL detection. The analytical process was automated, with a sample throughput of 6.6 h-1. Using MSSF for DMS separation was more effective and easily integrated with CL detection compared with the commonly used bubbling approach. Key parameters of the proposed method were investigated. The linear range for the method was 0.05-500 nM (R2 = 0.9984) and the limit of detection (3 x S/N) was 0.015 nM, which is comparable to the commonly used gas chromatography (GC) method and sensitive enough for direct DMS measurement in typical aquatic environments. Reproducibility and recovery were assessed by spiking natural water samples (river, lake, reservoir and pond) with different concentrations of DMS (10, 20 and 50 nM), giving relative standard deviations (RSDs) ≤1.75% (n = 5) and recoveries of 94.4-107.8%. This fully automated system is reagent free, easy to assemble, simple to use, portable (weight ~5.1 kg) and can be left in the field for several hours of unattended operation. The instrumentation can provide high quality DMS data for natural waters with an environmentally relevant temporal resolution of ~9 min.

Theoretical design and experimental investigation on highly selective Pd particles decorated C3N4 for safe photocatalytic NO purification.

Rational design of highly active and selective photocatalyst for NO removal is significant for the commercial application of photocatalytic technology because the secondary byproduct caused by insufficient and non-selective pollutant oxidation process is a major challenge. In this work, Pd nanoparticles decorated C3N4 (PdCN) is designed by density functional theory (DFT) at first. The PdCN exhibits superiority to CN in terms of both kinetics and thermodynamics performances, as reflected in the lower activation barrier of rate-determining step and higher selectivity for the final product (nitrate) instead of toxic intermediate (NO2). The as-designed highly selective and efficient photocatalyst is then fabricated by a facile method with an extremely low content of Pd particles supported on C3N4. Compared to bare CN, the synthesized PdCN exhibits highly enhanced purification of NO in air and strong inhibition of toxic NO2 by-product as supported by in-situ DRIFTS investigation, which is consistent with the theoretical prediction. This work is a typical demonstration of setting up a bridge between theory and experiment to give a promising way to the rational design of advanced photocatalysts and atomic understanding of the reaction mechanism.

A simple field method for the determination of sulfite in natural waters: Based on automated dispersive liquid-liquid microextraction coupled with ultraviolet-visible spectrophotometry.

Sulfite is known to be harmful to human health and associated to sulfur related environmental effects and ideally should be analyzed onsite owing to its instability. Here we describe an automated, miniaturized, and highly efficient dispersive liquid-liquid microextraction (DLLME) system that seamlessly coupled to a UV-vis spectrophotometer for the trace analysis of sulfite in natural waters. The automated DLLME system was constructed by a single syringe pump that is coupled with a multiposition valve. Nanomolar levels of sulfite could be extracted from natural water samples and injected into the hyphenated spectrophotometer for quantification. The whole analytical procedures, including chromogenic reactions, DLLME, collecting and transferring of microvolume of extracts, and spectrophotometric quantification, were automatically carried out. Key parameters that affect the performance of the method were investigated. The method allows the determination of trace levels of sulfite in the range of 15-1500 nM with a detection limit of 1.2 nM. Good reproducibility and recoveries were obtained by analyzing a series of natural water samples that were spiked with different concentration levels. The method was successfully applied to real natural water samples with satisfactory results. The proposed analytical system is light (3.9 kg), simple to use, able to be applied in the field, and sensitive enough for fresh and saline waters analysis.

Automated dispersive liquid-liquid microextraction coupled to high performance liquid chromatography - cold vapour atomic fluorescence spectroscopy for the determination of mercury species in natural water samples.

An automated, home-constructed, and low cost dispersive liquid-liquid microextraction (DLLME) device that directly coupled to a high performance liquid chromatography (HPLC) - cold vapour atomic fluorescence spectroscopy (CVAFS) system was designed and developed for the determination of trace concentrations of methylmercury (MeHg+), ethylmercury (EtHg+) and inorganic mercury (Hg2+) in natural waters. With a simple, miniaturized and efficient automated DLLME system, nanogram amounts of these mercury species were extracted from natural water samples and injected into a hyphenated HPLC-CVAFS for quantification. The complete analytical procedure, including chelation, extraction, phase separation, collection and injection of the extracts, as well as HPLC-CVAFS quantification, was automated. Key parameters, such as the type and volume of the chelation, extraction and dispersive solvent, aspiration speed, sample pH, salt effect and matrix effect, were thoroughly investigated. Under the optimum conditions, linear range was 10-1200ngL-1 for EtHg+ and 5-450ngL-1 for MeHg+ and Hg2+. Limits of detection were 3.0ngL-1 for EtHg+ and 1.5ngL-1 for MeHg+ and Hg2+. Reproducibility and recoveries were assessed by spiking three natural water samples with different Hg concentrations, giving recoveries from 88.4-96.1%, and relative standard deviations <5.1%.

Speciation analysis of mercury in sediments using vortex-assisted liquid-liquid microextraction coupled to high-performance liquid chromatography-cold vapor atomic fluorescence spectrometry.

A simple and fast solvent microextraction method termed vortex-assisted liquid-liquid microextraction (VALLME) coupled with high-performance liquid chromatography-vapor generation atomic fluorescence spectrometry (HPLC-CVAFS) has been developed for the trace analysis of methylmercury (MeHg(+)), ethylmercury (EtHg(+)) and inorganic mercury (Hg(2+)) in sediment samples. Carbon tetrachloride was used as collecting solvent for the extraction of mercury species from sediment by a vortex-assisted extraction. In VALLME, 100 µL 1% (m/v) l-Cysteine were used as extraction solvent and were injected into 4 mL carbon tetrachloride. The extraction solvent dispersed into carbon tetrachloride under vigorously shaking by a vortex agitator. The fine droplets could extract mercury species within few minutes because of the shorter diffusion distance and larger specific surface area. After centrifugation, the floating extractant phase restored its initial single microdrop shape and was used for HPLC-CVAFS analysis. The parameters affecting the extraction efficiency of the proposed VALLME such as extraction solvent, vortex time, volumes of extraction solvent and salt addition etc. were investigated. Under the optimum conditions, linearity was found in the concentration range from 0.1 to 25 ng g(-1) for MeHg(+), 0.2 to 65 ng g(-1) for EtHg(+), and 0.1 to 30 ng g(-1) for Hg(2+). Coefficients of determination (R(2)) ranged from 0.9938 to 0.9972. The limits of detection (LODs, signal-to-noise ratio (S/N)=3) were 0.028 ng g(-1) for MeHg(+), 0.057 ng g(-1) for EtHg(+), and 0.029 ng g(-1) for Hg(2+). Reproducibility and recoveries were assessed by testing a series of 6 sediment samples, which were spiked with different concentration levels. Finally, the proposed method was successfully applied in analyses of real nature sediment samples. In this work, VALLME was applied to the extraction of mercury species in sediment samples for the first time. Using l-Cys as extraction solvent, the extraction process is sensitive and environmentally friendly and could be achieved within 3 min.