In this study, the baseline separations of xylene isomers and phthalate acid esters on a homemade DUT-67(Zr) packed column were achieved, respectively. The high selectivity for xylene isomers and phthalate acid esters was obtained with the increase in temperature and decrease in the retention time. The hydrophobicity of xylene isomers and phthalate acid esters resulted in the different separation time on the DUT-67(Zr) packed column. The relative standard deviation values of retention time, peak area, peak height, and half peak width for five repeat separation of the xylene isomers were 0.26-0.35, 2.11-2.26, 1.51-2.03, and 0.29-0.77%, and the values of the phthalate acid esters on DUT-67(Zr) column were 0.1-0.4, 4.4-5.2, 3.9-6.3, and 0.6-2.1%, respectively. The thermodynamic properties indicated that the separation of xylene isomers was controlled by ΔH and ΔS, but the separation of phthalate acid esters was mainly controlled by ΔS.
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http://dx.doi.org/10.1002/jssc.201800119 | DOI Listing |
Int J Mol Sci
November 2024
Department of Medicinal and Life Sciences, Hanyang University, Sangnok-gu, Ansan 15588, Gyeonggi-do, Republic of Korea.
Environmental pollutants, particularly volatile organic compounds (VOCs), are associated with various diseases, including atopic dermatitis (AD). However, despite numerous studies on AD, there is a lack of research on the impact of various environmental exposures on mothers and infants. This study, therefore, investigated the effects of maternal exposure to specific VOCs (toluene, xylene, and benzene) on the expression of AD-related genes in mothers and their infants.
View Article and Find Full Text PDFRapid Commun Mass Spectrom
March 2025
School of Life and Environmental Sciences, GuiLin University of Electronic Technology, GuiLin, China.
With the increasing application scenarios and detection needs of high-field asymmetric waveform ion mobility spectrometry (FAIMS) analysis, deep learning-assisted spectral analysis has become an important method to improve the analytical effect and work efficiency. However, a single model has limitations in generalizing to different types of tasks, and a model trained from one batch of spectral data is difficult to achieve good results on another task with large differences. To address this problem, this study proposes an adaptive multicore dual-path fusion multimodel extraction of heterogeneous features for FAIMS spectral analysis model in conjunction with FAIMS small-sample data analysis scenarios.
View Article and Find Full Text PDFAdv Mater
December 2024
Key Laboratory of Biomass Chemical Engineering of Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
The separation of xylene isomers, especially para-xylene, is a crucial but challenging process in the chemical industry due to their similar molecular dimensions. Here, a flexible metal-organic framework, Ni(ina), (ina = isonicotinic acid) is employed to effectively discriminate xylene isomers. The adsorbent with adaptive deformation accommodates the shapes of isomer molecules, thereby translating their subtle shape differences into characteristic framework deformation energies.
View Article and Find Full Text PDFCrit Rev Toxicol
November 2024
Chemical Regulation & Food Safety, Exponent Incorporated, Menlo Park, California, USA.
Xylene is a high production volume chemical that is widely used as a solvent and polymer precursor, and is currently undergoing substance evaluation under Registration, Evaluation, Authorization and Restriction of Chemicals (REACH). Xylenes recently received testing decisions on one-generation reproductive toxicity (EOGRT) studies with additional developmental neurotoxicity (DNT) cohorts for each of the three isomers. Xylene presents a unique opportunity to investigate the need for additional animal DNT toxicology testing because it is a legacy industrial chemical for which a significant amount of animal and human data already exists on its toxicity profile, including central nervous system effects.
View Article and Find Full Text PDFACS Sens
November 2024
Department of Electrical and Computer Engineering, Marquette University, Milwaukee, Wisconsin 53201-1881, United States.
This work presents an adaptive sensor signal-processing approach to enable quantification, using a single gas sensor or a small sensor array, of multianalyte mixtures of aromatic hydrocarbons in the presence of various interferents and humidity for environmental-monitoring applications. Dynamic sensor responses are analyzed by extracting multivariable sensing parameters to provide necessary sensitivity and selectivity. This is achieved by integrating the Levenberg-Marquardt-modified, exponentially weighted, recursive-least-squares-estimation (LM-modified EW-RLSE) algorithm and principal-component analysis (PCA).
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