Analytical Sciences最新文献

Pair distribution function (PDF) analysis based on X-ray total scattering is a powerful technique for elucidating local and medium-range structure in crystalline, nanocrystalline, and amorphous materials. Several software packages—such as GudrunX, PDFgetX2, and PDFgetX3—along with facility-specific programs developed at synchrotron sites, are widely used for this purpose. However, these tools typically require installation and environment-dependent configuration, which can introduce compatibility issues across operating systems and create conflicts with pre-installed software. To overcome these limitations, we developed a browser-based PDF analysis application implemented using Pyodide and PyScript, allowing it to run entirely in modern web browsers without additional installation. The software provides key functionalities, including Fourier transformation from S(Q) to G(r), calculation of g(r), back-Fourier transformation with cutoff handling, and sequential data processing. Demonstrations on representative samples confirm consistency with established programs. The software supports both synchrotron data and laboratory-based measurements using Ag radiation sources, underscoring its broad applicability. This tool enables environment-independent and consistent analyses, significantly enhancing the accessibility of X-ray total-scattering and PDF techniques.

Graphical abstract

Poly(dimethylsiloxane) (PDMS) is the most widely used material for microfluidic chips because of its advantageous properties including easy fabrication through soft lithography, which means pattern transfer technique from microfabricated master molds. However, most of the master molds are made of a silicon wafer and a photoresist layer, and have two major disadvantages: (1) the fabrication process is complicated and requires specialized facilities, and (2) the fabricated master molds are fragile. Here, we describe a simple fabrication technique to produce a robust master mold by pattern transfer from an existing PDMS chip to an inexpensive, hobby-use UV-curable resin (UV resin). The process requires no specialized facilities or hazardous chemicals. The test pattern consisted of microchannels with a cross-section of 100 µm × 25 µm and a total area of 30 mm × 30 mm. This pattern was faithfully transferred from the PDMS surface to the UV resin. The inaccuracy of the solidified UV resin was evaluated to be smaller than the measurement error (< 0.2%). The UV resin mold was subsequently tested for the soft lithography of a next-generation PDMS chip. For successful soft lithography, the UV resin mold required heat treatment at 60 °C for at least 48 h prior to use. Without this treatment, substantial damage was observed on both the PDMS and the UV resin surfaces. This problem was probably caused by the inhibition of PDMS curing due to unreacted components of the UV resin remaining on the surface. The technique presented here provides a simple and low-cost route for the repetitive fabrication of identical PDMS microfluidic chips for various research fields.

Graphical abstract

A recurrent neural network (RNN) system based on a Hopfield neural network (HNN) was developed to extract essential spectral patterns from the time-of-flight secondary ion mass spectrometry (ToF–SIMS) spectra of peptide samples. Because ToF–SIMS produces various fragment ions from organic molecules, the interpretation of ToF–SIMS spectra is generally complicated. ToF–SIMS is useful for peptide analysis because it detects specific amino acid fragment ions from peptides that indicate peptide information. However, the ToF–SIMS spectra also contain fragment ions that do not preserve the main structures of the original molecules, which makes them difficult to interpret. Therefore, it is crucial to extract essential spectral patterns from the ToF–SIMS spectra of organic materials. Peptides were selected as the target organic materials for this study due to their systematic chemical structures. A modified HNN was trained on the ToF–SIMS spectra of each peptide, and the trained HNNs were then used to recall patterns for various peptide ToF–SIMS spectra. The results show that the modified HNN recall essential spectra containing specific ions, including the protonated molecular ions and amino acid fragment ions of target peptides. Furthermore, the HNN results revealed differences and similarities between peptides with similar and different amino acid sequences. Thus, this study demonstrates the effectiveness of the HNN in interpreting complex spectra and its potential for preprocessing data for further analysis.

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The rapid and reliable in-situ detection of trace elements relevant to nuclear materials and metal elements in environmental matrices is a major challenge in the fields of environmental monitoring, nuclear safety, and resource assessment. Element identification in Laser-induced Plasma Spectroscopy (LIPS, synonymous with Laser-induced Breakdown Spectroscopy or LIBS) can be achieved by analyzing the corresponding peak information emitted by the plasma. However, due to differences in spectral databases (e.g., wavelength shift), making quick judgments remains challenging. To tackle this issue, we developed a novel data analysis strategy that explicitly accounts for spectral peak shifts. This method was evaluated using both the Akaike and Bayesian Information Criteria (AIC/ BIC) and correlation coefficients to enhance the reliability of LIPS for aerosol analysis. This approach statistically models inevitable spectral peak shifts to establish a probabilistic identification framework, offering clear evaluative criteria for detecting key elements in complex environmental samples. Experimental results demonstrate that this method substantially lowers misidentification risks and offers a robust analytical tool for field deployment and real-time environmental screening.

Graphical abstract

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The water content of organic solvents was determined by the ligand dissociation of a tris(2-methyl-8-quinolinolato)indium(III) complex. Water in the organic solvent reacts with the indium complex to induce a ligand-exchange reaction. The fluorescence of deprotonated 2-methyl-8-quinolinol disappears when the ligand-exchange reaction forms a neutral molecule; thus, the complex can serve as a turn-off water-detection sensor. We measured the water content of various organic solvents, including ethyl acetate, 1-octanol, and ethanol. The indium complex was dissolved in a water-containing organic solvent, the fluorescence of the 8-quinolonolate ion was measured, and determination curves were constructed based on the decrease in fluorescence intensity. To demonstrate the versatility of the present method, we measured the water content of alcoholic drinks. These results are consistent with the data obtained by Karl Fischer (KF) titration. Although the limits of detection and quantification were not as low as those of the KF titration, the simple experimental setup and procedure of this method are favorable for its application.

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We propose a sensitive method for discriminating fluorinated from non-fluorinated ions using ion-transfer voltammetry. This approach employed supported liquid membranes (SLMs) impregnated with either a fluorous solvent, 1H,1H,5H-octafluoropentyl-1,1,2,2-tetrafluoroethyl ether (OFE), or an organic solvent, 1,6-dichlorohexane (DCH). Ion-transfer reactions of the fluorinated ion perfluorooctanoate (PFOA⁻) and various non-fluorinated anions were measured at both the SLM(OFE)|water (W) and SLM(DCH)|W interfaces. Fluorinated ions exhibit fluorophilicity, while non-fluorinated ions show fluorophobicity toward fluorous solvents. Consequently, the shifts in the recorded ion-transfer potentials for PFOA⁻ and non-fluorinated ions between the SLM(OFE)|W and SLM(DCH)|W interfaces exhibited opposite trends, indicating that fluorinated ions can be readily discriminated through voltammetric measurements. Furthermore, electrochemical preconcentration of PFOA⁻ into the SLM proved feasible, enabling sensitive determination of PFOA⁻ by subsequent voltammetric measurement. The proposed method is simple and cost-effective, making it a promising approach for the analysis of problematic per- and polyfluoroalkyl substances.

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The Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method is widely used as a pretreatment technique to extract a broad range of drugs and toxicants into the acetonitrile layer. However, the aqueous layer generated during the extraction process has a high-salt content and has not been analytically explored. This study focused on the unused aqueous layer and established a method for detecting the highly polar compounds glyphosate (Gly) and glufosinate (Glu) through derivatization with 9-fluorenylmethoxycarbonyl chloride, followed by liquid chromatography–tandem mass spectrometry. Under optimized conditions, both analytes were effectively separated and detected with favorable peak shapes from 50 µL of whole blood. Calibration curves exhibited good linearity over the range of 0.1–10 µg/mL, with correlation coefficients of 0.993 for Gly and 0.994 for Glu. The lower limit of quantification for both compounds was 0.1 µg/mL. The method also demonstrated acceptable precision, accuracy, process efficiency, and stability. Herein, we demonstrate that the aqueous layer generated during the QuEChERS extraction process can serve as a valuable analytical matrix for determining Gly and Glu in blood. This method can be employed by directly adding the derivatization reagent to the aqueous layer without modifying the conventional QuEChERS extraction process. This method has the ability to reduce sample consumption by employing multiple extraction layers with distinct physicochemical characteristics. This is particularly important when only a limited number of sample volumes is available such as in fatal cases or poisoning incidents.

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