Frontiers in Chemistry最新文献

We report on an in situ FTIR study of the thermo-oxidative degradation of a flexible epoxy resin. Different and complementary approaches to the analysis of the spectral data were employed, providing a detailed description of the process in terms of kinetics and mechanisms. A preliminary normal coordinate analysis, based on the DFT method, allowed for a reliable interpretation of the observed spectrum, increasing the amount of available structural information. Two-dimensional correlation spectroscopy provided details on the evolution of the reacting network structure. The relative stability of the various functional groups was ranked, and the most likely sites of initiation were identified. Oxygen fixation on the network chains produced amide and ketone groups, with the latter developing at a higher rate. The kinetic profiles of various functional groups were accurately simulated by a first-order, biexponential model, which allowed a quantitative comparison among their relative stabilities. The spectroscopic analysis allowed us to propose likely mechanisms and to identify those that occur preferentially.

Effective removal of organic and inorganic impurities by adsorption technique requires the preparation of new materials characterized by low production costs, significant sorption capacity, and reduced toxicity, derived from natural and renewable sources. To address these challenges, new adsorbents have been developed in the form of polymer microspheres based on ethylene glycol dimethacrylate (EGDMA) and vinyl acetate (VA) (EGDMA/VA) containing starch (St) modified with boric acid (B) and dodecyl-S-thiuronium dodecylthioacetate (DiTDTA) for the removal of dyes: C.I. Basic Blue 3 (BB3) and C.I. Acid Green 16 (AG16) and heavy metal ions (M(II)): Cu(II), Ni(II), and Zn(II) from water and wastewater. The adsorbents were characterized by ATR/FT-IR, DSC, SEM, BET, EDS, and pH_PZC methods. These analyses demonstrated the successful modification of microspheres and the increased thermal resistance resulting from the addition of the modified starch. The point of zero charge for EGDMA/VA was 7.75, and this value decreased with the addition of modified starch (pH_PZC = 6.62 for EGDMA/VA-St/B and pH_PZC = 5.42 for EGDMA/VA-St/DiTDTA). The largest specific surface areas (S_BET) were observed for the EGDMA/VA microspheres (207 m²/g), and S_BET value slightly decreases with the modified starch addition (184 and 169 m²/g) as a consquence of the pores stopping by the big starch molecules. The total pore volumes (V_tot) were found to be in the range from 0.227 to 0.233 cm³/g. These materials can be classified as mesoporous, with an average pore diameter (W) of approximately 55 Å (5.35-6.10 nm). The SEM and EDS analyses indicated that the EGDMA/VA microspheres are globular in shape with well-defined edges and contain 73.06% of carbon and 26.94% of oxygen. The microspheres containing modified starch exhibited a loss of smoothness with more irregular shape. The adsorption efficiency of dyes and heavy metal ions depends on the phases contact time, initial adsorbate concentration and the presence of competing electrolytes and surfactants. The equilibrium data were better fitted by the Freundlich isotherm model than by the Langmuir, Temkin, and Dubinin-Radushkevich models. The highest experimental adsorption capacities were observed for the BB3 dye which were equal to 193 mg/g, 190 mg/g, and 194 mg/g for EGDMA/VA, EGDMA/VA-St/B, EGDMA/VA-St/DiTDTA, respectively. The dyes and heavy metal ions were removed very rapidly and the time required to reach system equilibrium was below 20 min for M(II), 40 min for BB3, and 120 min for AG16. 50% v/v methanol and its mixture with 1 M HCl and NaCl for dyes and 1 M HCl for M(II) desorbed these impurities efficiently.

Introduction: Untargeted metabolomics is often used in studies that aim to trace the metabolic profile in a broad context, with the data-dependent acquisition (DDA) mode being the most commonly used method. However, this approach has the limitation that not all detected ions are fragmented in the data acquisition process, in addition to the lack of specificity regarding the process of fragmentation of biological signals. The present work aims to extend the detection of biological signals and contribute to overcoming the fragmentation limits of the DDA mode with a dynamic procedure that combines experimental and in silico approaches.

Methods: Metabolomic analysis was performed on three different species of actinomycetes using liquid chromatography coupled with mass spectrometry. The data obtained were preprocessed by the MZmine software and processed by the custom package RegFilter.

Results and discussion: RegFilter allowed the coverage of the entire chromatographic run and the selection of precursor ions for fragmentation that were previously missed in DDA mode. Most of the ions selected by the tool could be annotated through three levels of annotation, presenting biologically relevant candidates. In addition, the tool offers the possibility of creating local spectral libraries curated according to the user's interests. Thus, the adoption of a dynamic analysis flow using RegFilter allowed for detection optimization and curation of potential biological signals, previously absent in the DDA mode, being a good complementary approach to the current mode of data acquisition. In addition, this workflow enables the creation and search of in-house tailored custom libraries.

In this study a Machine Learning model was employed to predict the lipid profile from supercritical fluid extraction (SFE) of microalgae Galdieria sp. USBA-GBX-832 under different temperature (40, 50, 60°C), pressure (150, 250 bar), and ethanol flow (0.6, 0.9 mL min^-1) conditions. Six machine learning regression models were trained using 33 independent variables: 29 from RD-Kit molecular descriptors, three from the extraction conditions, and the infinite dilution activity coefficient (IDAC). The lipidomic characterization analysis identified 139 features, annotating 89 lipids used as the entries of the model, primarily glycerophospholipids and glycerolipids. It was proposed a methodology for selecting the representative lipids from the lipidomic analysis using an unsupervised learning method, these results were compared with Tanimoto scores and IDAC calculations using COSMO-SAC-HB2 model. The models based on decision trees, particularly XGBoost, outperformed others (RMSE: 0.035, 0.095, 0.065 and coefficient of determination (R²): 0.971, 0.933, 0.946 for train, test and experimental validation, respectively), accurately predicting lipid profiles for unseen conditions. Machine Learning methods provide a cost-effective way to optimize SFE conditions and are applicable to other biological samples.

Introduction: Deep eutectic solvents (DESs) have emerged as green solvents with versatile applications, demonstrating significant potential in biocatalysis. They often increase the solubility of poorly water-soluble substrates, serve as smart co-substrates, modulate enzyme stereoselectivity, and potentially improve enzyme activity and stability. Despite these advantages, screening for an optimal DES and determining the appropriate water content for a given biocatalytic reaction remains a complex and time-consuming process, posing a significant challenge.

Methods: This paper discusses the rational design of DES tailored to a given biocatalytic system through a combination of experimental screening and computational tools, guided by performance targets defined by solvent properties and process constraints. The efficacy of this approach is demonstrated by the reduction of CO₂ to formate catalyzed by NADH-dependent formate dehydrogenase (FDH). By systematically analyzing FDH activity and stability, NADH stability (both long-term and short-term stability after solvent saturation with CO₂), and CO₂ solubility in initially selected glycerol-based DESs, we were able to skillfully guide the DES screening process.

Results and discussion: Considering trade-offs between experimentally determined performance metrics of DESs, 20% solution of choline chloride:glycerol in phosphate buffer (ChCl:Gly_80%B) was identified as the most promising solvent system for a given reaction. Using ChCl:Gly as a co-solvent resulted in an almost 15-fold increase in FDH half-life compared to the reference buffer and stabilized the coenzyme after the addition of CO₂. Moreover, the 20% addition of ChCl:Gly to the buffer improved the volumetric productivity of FDH-catalyzed CO₂ reduction in a batch system compared to the reference buffer. The exceptional stability of the enzyme in this co-solvent system shows great potential for application in continuous operation, which can significantly improve process productivity. Additionally, based on easily measurable physicochemical solvent properties and molecular descriptors derived from COSMO-RS, QSAR models were developed, which successfully predicted enzyme activity and stability, as well as coenzyme stability in selected solvent systems with DESs.

Development of simple solid-phase electrochemiluminescence (ECL) immunosensor with convenient fabrication for high-performance detection of tumor biomarkers is crucial. Herein, a solid-phase ECL immunoassay was constructed based on a bipolar silica nanochannel film (bp-SNA) modified electrode for highly sensitive detection of carbohydrate antigen 125 (CA 125). Inexpensive and readily available indium tin oxide (ITO) electrode was used as the supporting electrode for the growth of bp-SNA. bp-SNA consists of a bilayer SNA film with different functional groups and charge properties, including negatively charged inner layer SNA (n-SNA) and positively charged outer layer SNA (p-SNA). The nanochannels of bp-SNA were used for the immobilization of ECL emitter tris(bipyridine)ruthenium(II), while the outer surface was utilized for constructing the immunorecognition interface. Due to the dual electrostatic interaction composed of electrostatic attraction from n-SNA and electrostatic repulsion from p-SNA, ECL emitter could be stably confined within bp-SNA, providing stable and high ECL signals to the modified electrode. After amino groups on the outer surface of bp-SNA were derivatized with aldehyde groups, recognition antibodies could be covalently immobilized, and an immunosensor was obtained after blocking nonspecific sites. When CA 125 binds to the antibodies on the recognition interface, the formed complex reduces the diffusion of the co-reactant tripropylamine (TPrA) to the supporting electrode, decreasing the ECL signal. Based on this mechanism, the constructed immunosensor can achieve sensitive ECL detection of CA 125. The linear detection range is from 0.01 to 100 U/mL, with a detection limit of 4.7 mU/mL. CA 125 detection in serum is also achieved. The construction immunosensor has advantages including simple and convenient fabrication, high stability of the immobilized emitter, and high selectivity, making it suitable for CA 125 detection.

Two-dimensional materials have excellent electronic and optical properties, suggesting absolute advantages in nanodevices. In this work, a new two-dimensional material with a puckered structure, a C₂B₆ monolayer, is proposed. The material presents dynamic and thermal stability calculated by first-principle simulations. Interestingly, the C₂B₆ monolayer possesses semiconductor behavior with an ultra-narrow bandgap of approximately 0.671 eV by HSE06 functional. Meanwhile, the hole in the C₂B₆ monolayer shows ultrahigh mobility at approximately 6,342 cm²⋅V^-1⋅s^-1 in decent transport directions, which is larger than traditional transition metal dichalcogenides materials. More importantly, the pronounced anisotropy of mobility of the electrons and holes can separate the photogenerated charges, suggesting the applications for photocatalytic, photovoltaic and optical and cold chain electronic devices. Then, the novel properties of the light absorption characteristic are obtained, and the anisotropic photocurrent implies the C₂B₆ monolayer can be used as a potential photoelectric device. Our results provide theoretical guidance for the design and application of two-dimensional materials.