Chemistry methods : new approaches to solving problems in chemistry最新文献

Polylactide (PLA), a biobased, biodegradable polyester derived from lactic acid, is recognized as an alternative to conventional plastics due to properties such as mechanical strength and compostability. Despite widespread use in applications from medical devices to packaging, PLA degradation in the environment, particularly its breakdown into microplastics, raises concerns. Conventional analytical methods are inadequate for quantifying PLA degradation in environments. To address this, radio tracking techniques using carbon-14 have emerged as a reliable method for PLA decomposition studies. The first step is producing labeled polymers from suitable monomers. Ring-opening polymerization (ROP) of lactide is widely used for synthesizing PLA, but this approach faces challenges due to the limited availability and high cost of ¹⁴C-labeled precursors. We report the first use of a biocompatible zinc bisguanidine catalyst for the synthesis of ¹⁴C-lactide from ¹⁴C-lactic acid, enabling the production of ¹⁴C-PLA. The process involves dehydration and oligomer formation, followed by catalytic depolymerization to yield ¹⁴C-lactide, which is polymerized through ROP. Lactide production was optimized by comparing the toxic industrial catalyst tin(II) octanoate [Sn(Oct)₂] with our catalyst, the latter ultimately used for ¹⁴C-lactide and ¹⁴C-PLA production. The resulting micro-¹⁴C-labeled PLA can be used to quantify degradation, assess environmental impact.

Cerebrospinal fluid (CSF) is an important human biofluid studied within neurological implications. The objective of this literature review is to explore the potential of quantitative nuclear magnetic resonance (NMR) spectroscopy for a precise and reproducible measurement of metabolites in CSF. A two-source-based literature search is conducted among entries from a Web of Science Core Collection (owned by Clarivate) and the PubMed library, with the objective of researching NMR-based investigations of human CSF. The query results are then rerouted toward key summaries pertaining to NMR experiments, sample preparation, and identified metabolites. 94 papers focusing on sample preparation and NMR methods and 49 papers that reported about CSF metabolite concentrations with an overall total of 114 different metabolites that can be detected by NMR are identified. The findings are summarized in comprehensive tables to facilitate future research and use of harmonized protocols regarding sample preparation and measurement. While a large set of metabolites can be measured in CSF, many different sample preparation protocols and analytical settings are used. This is a major drawback for the translation of CSF NMR spectroscopy to a clinical setting, so future studies should try to harmonize preanalytical and analytical conditions and apply absolute quantitation.

Ternary mixtures based on ionic liquids (IL), water, and alkali halides (MX) are emerging as greener alternatives to lithium-ion electrolytes. Consequently, a question arises about the possible influence of M⁺ cations on the structural heterogeneities in the IL solvent network, formed in the presence of water. This study employs nuclear magnetic resonance methodologies, such as high-gradient diffusion measurements, to provide an in-depth understanding of the nearest environment of Na⁺ in the EMIM-BF₄-H₂O-NaCl pilot solution. The results reveal a strong dependence between the number of water molecules in the first solvation shell of sodium and the formation of the polar nanodomains in the IL. The EMIM-BF₄:H₂O molecular ratio, previously reported as the most significant parameter governing the structural arrangement of binary IL-water systems, becomes of lower importance in the presence of small concentrations of sodium halides. Thus, even minor changes in the IL solutions may lead to significant modifications in their behavior, potentially expanding the range of applications.

Mass spectrometry imaging (MSI) is a powerful tool for spatial metabolomics and biomarker discovery, but molecular identification remains challenging, particularly for low-abundance analytes with poor signal-to-noise ratios. Herein, a novel approach that utilizes a deuterated analog of the reactive matrix FMP-10 to enhance molecular identification is introduced. This isotopically labeled matrix enables precise determination of derivatization patterns, allowing the number and sequence of reactive functional groups in small molecules to be deduced. By observing specific mass shifts, the method provides additional structural information beyond high-resolution MS and MS/MS, addressing key limitations in MSI-based biomarker discovery. This innovative labeling strategy improves identification confidence for neurotransmitters and metabolites, making it a powerful addition to the MSI toolbox for complex tissue analysis. The findings represent a significant advance for spatial metabolomics, with particular advantages for neurochemical mapping in the study of neurodegenerative diseases.

Automated electrochemical platforms are attracting attention for their potential in streamlining reaction preparation, electrolysis, and analysis to generate large datasets in a fast and efficient manner. Moreover, the recent implementation of on-line analytics together with closed-loop workflows has enabled the emergence of electrochemical self-driving laboratories. In this review, the common guidelines for the development of these platforms are presented, covering the main modules to assemble these systems. Furthermore, a comprehensive survey of all the platforms applied in synthetic organic electrochemistry is reported, where each example is described in terms of elements and applications and classified by category. Finally, an outlook including a perspective on the topic is presented, proposing potential future directions of the field.

The delayed reactant labeling (DRL) technique can extract kinetic information from ESI-MS spectra by using isotopic labeling during reaction monitoring. Despite being powerful, the necessity for laborious kinetic modeling made DRL inaccessible. Here, we address this issue by introducing a Python program, DRL-Fit. DRL-Fit is capable of modeling reactions and comparing the predictions with the DRL data to find a set of rate constants that accurately describe the reaction system. Several built-in functions test the robustness of each model, providing further insight into the workings of both the reaction and the model. We demonstrate the capabilities of connecting DRL with the DRL-Fit program for the nitro-Mannich reaction, determining the rate constants for all reaction steps. Varying experimental conditions are logically reflected in the rate changes of individual reaction steps. The model also explains the decreased conversion in the presence of scandium triflate.

Mass spectrometry-based natural products (NPs) targeted discovery often relies on a complicated decision-making process involving tedious comparison of exact masses data and tandem mass spectra-based annotation tools output against various spectral reference libraries. To address this bottleneck, tandem mass spectrum to decision (MS2DECIDE) is presented which leverages decision theory and expert knowledge to aggregate the outputs of three widely used annotation tools (GNPS, Sirius, and ISDB-LOTUS) and computes a recommendation for targeting NPs with regard to their potential novelty. We demonstrate, through two case studies, that MS2DECIDE reliably captures the novelty of natural products from their tandem mass spectra. MS2DECIDE is freely accessible on GitHub.

Photoswitchable molecular systems are nowadays very popular and promising for development of molecular electronics in the future. Their physico-chemical properties, such as activation wavelength, quantum yields, or stability of metastable forms are usually compared with the already published data, with the aim to demonstrate their improvement. An investigation of chemical kinetics is not always straightforward and requests careful data analysis and their processing. Importantly, stability of metastable forms is quantified by half-life values τ_1/2, which can be determined in several ways, leading to incomparable results. In this comparative study, it is demonstrated that processing the same data set by different approaches used in literature leads to a wide range of the half-life values. As model compounds, we prepared azopyrazole derivatives 1 and 2 with the most stable Z isomers published (τ_1/2 46 years and 1000 days at room temperature, respectively). Depending on the processing method the half-life values of 1 in a range of 41.9–57.4 years were determined, with 16% of deviation. And for 2 in a range of 492–826 days (25% deviation). The results let us recommend a comprehensive methodology of how to process and evaluate the kinetic data with the aim of producing comparable results among laboratories all over the world.

Replacement of the ubiquitous lead titanate zirconate piezoceramics is still a challenge involving sustainable materials and processes. An extended effort has been paid for the optimization of the properties of (K_0.5Na_0.5)NbO₃ (KNN) lead-free piezoceramics at the expenses of high-energetic budget. A sustainable solid-state processing with potential for industrial scaling (knowledge-based, sustainable, reproducible, and cost-effective) is still lacking. In this work, an efficient solution is proposed using the well-known and noncontaminant attrition-ball-milling of the mixture of reagents for only 3 h, prior to the synthesis tests at increasing temperatures. After calcination at only 450 °C/2 h, 60 wt% KNN is achieved. Moreover, after 850 °C/2 h the calcined powder becomes a pure KNN. A second ball-milling of powder calcined at 700850 °C gives place to populations of nanostructured particles (380–40 nm, respectively). The milled powder calcined at 700 °C is pressureless sintered in air for 2 h at 1050 and 1100 °C, leading to coarse grained ceramics. Milled powder calcined at 750 and 850 °C, sintered at the same conditions, produces fine grain homogeneous microstructures. Ceramics show an orthorhombic Amm2 pure KNN perovskite phase, as seen by x-ray diffraction and Rietveld analysis. The piezoelectric values (d₃₃ = 115 pC/N, d₃₁ = ₋22 pC/N, k_p = 20%, k_t = 40%) are exceptional when derived from such a straightforward solid-state route.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a key spatial omics technology for spatially resolved visualization and direct on-tissue identification of multiple lipid and metabolite classes. Recently, many on-tissue chemical derivatization (OTCD) reagents targeting defined functional groups have been introduced to improve sensitivity and/or molecular specificity for compound annotation. Some act as reactive matrices that introduce permanent charges and no longer require (de)protonation for ionization. However, OTCD side reactions are understudied, and it is presently unknown what pseudo metabolites can be generated as OTCD-derived artifacts. These are compounds that, in principle, exist as bona fide metabolites in tissues but that can also be products of OTCD side reactions. Here, it is demonstrated that besides expected reaction products, the reactive matrix 4-(anthracen-9-yl)-2-fluoro-1-methylpyridin-1-ium iodide (FMP)-10 can also cause unexpected N- and O-lactoylation and even apparent poly-lactoylation of multiple amino acids through Mukaiyama esterification. Side reactions are unrelated to MALDI laser photochemistry, as they happen in solution and can be readily observed by liquid chromatography–MS/MS. Since N-lactoylated amino acids have recently received much attention in sports physiology and obesity research, much care needs to be taken to distinguish true endogenous N-lactoylated amino acids from those that are formed by Mukaiyama side reactions.