IEEE SENSORS JOURNAL
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2024
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IF 4.3
Zhikang Rao,Boyu Guo,Jixiang Zu,Weiqiang Zheng,Ying Xu,Yuting Yang
In clinical diagnosis, the detection of dopamine (DA) is often interfered by epinephrine (EP), a neurotransmitter drug that shares a similar structure with DA, which affects the accurate prediction of DA concentration. In this study, an electrochemiluminescence (ECL) and differential pulse voltammetry (DPV) dual model biosensor combined with machine learning algorithm was proposed for improving the selective detection of DA under EP interference. First, reduced graphene and gold nanoparticles were applied to enhance the sensitivity and stability of the sensor in ECL and DPV measurement. Compared with single model sensing, the dual model sensor could combine the superiority of ECL and DPV while improving the accuracy and reliability of experimental data. Then, nine graphic features related to concentration prediction were extracted from the ECL and DPV response curves, and Pearson’s correlation coefficient (PCC), as well as random forest (RF) algorithm, was adopted for feature importance analysis. To achieve accurate signal decoupling, an intelligent biologically inspired algorithm, particle swarm optimization (PSO) algorithm, was introduced to optimize initial weights and thresholds of the traditional artificial neural network (ANN) for further model training based on multi-feature fusion, which greatly increased the prediction accuracy of DA in the presence of EP. The results demonstrated that DA could be accurately predicted in the concentration range of 9– 200 μM , and the R2 between the true and predicted values of DA concentration reached 0.99. The root-mean-square error (RMSE) and mean absolute error (MAE) of the test dataset were 5.77 and 4.32 μM , respectively. In addition, the PSO-ANN-assisted ECL-DPV dual model detection scheme has been successfully applied for the determination of DA in real samples, such as goat serum and artificial urine.
研究领域:
生物医学工程
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临床诊断
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电化学传感
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DOI
高影响因子
JOURNAL OF COLLOID AND INTERFACE SCIENCE
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2025
·
IF 9.7
Yunna Chen,Chao Song,Lizheng Chen,Longlong Lei,Junhui Wang,Tanghe Xu,Chong He,Wenbin Li
SiO 2 aerogel fibers are widely regarded as one of the lightest solid materials, exhibiting exceptional thermal insulation properties. However, achieving both high elasticity and spinnability remains a significant challenge in the fabrication process. A scalable and efficient vortex-assisted multi-stage spinning strategy has been employed to fabricate Silica Nanofiber Aerogel Fibers@Polysiloxane/Aramid Aerogel Fibers (SiNAFs@PSO/Aramid). These fibers are characterized by a hierarchical architecture, consisting of an interwoven SiO₂ nanowire aerogel network as the core and a robust PSO/Aramid composite shell. SiNAFs@PSO/Aramid demonstrate ultralow density (<0.15 g/cm 3 ), exceptional mechanical resilience (tensile strength >4 MPa), and an ultra-low thermal conductivity of 0.033 W/m·K, outperforming conventional thermal insulation materials. Mechanical integrity remains stable under extreme thermal ranging from −196 °C to 500 °C, ensuring durability in harsh environments. Superior weaveability enables the fabrication of highly adaptable, three-dimensional foldable textiles with tunable geometric configurations. Upon exposure to high temperatures, an in-situ transformation into SiOC ceramic composites occurs, significantly enhancing thermal shock resistance and mechanical stability. Flexibility and geometric adaptability of these aerogel fabrics make SiNAFs@PSO/Aramid well-suited for applications requiring diverse shape configurations, as well as high-temperature thermal insulation.
研究领域:
材料科学
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纳米技术
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气凝胶材料
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隔热工程
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复合纤维制备
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高温材料工程
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PubMed
高影响因子
Journal of Environmental Sciences
·
2025
·
IF 6.3
Jia-Wei Song,Ju-Xiang Chen,Wen-Hai Chu,Yu-Qiong Gao,Nai-Yun Gao
Conventional treatment methods struggle to effectively eliminate sulfamethoxazole (SMX) from wastewater due to its persistent aromatic structure and sulfonamide moiety, while existing advanced oxidation processes often suffer from high energy consumption and inadequate degradation pathway control. This study demonstrates an advanced approach for SMX degradation in aqueous systems through dielectric barrier discharge (DBD) plasma technology synergistically integrated with COMSOL multiphysics simulation and particle swarm optimization-support vector machine (PSO-SVM) modeling. Computational simulations revealed that the DBD plasma generates a diffuse arc (D-A) mode electric field with Penning ionization effects, where primary reactive species formation predominantly occurs within the sheath layer. Under optimized operational parameters (input power: 50 W, pH 7, conductivity: 3.16 μS/cm, initial concentration: 10 mg/L, the carrier gas: air), the system achieved an exceptional SMX removal efficiency of 99.82 %, corresponding to a constant reaction rate of 0.3087 min −1 . The machine learning-optimized process simultaneously enhanced energy yield by 18.11 mg/kW·h and improved energy utilization efficiency by 15.11%. Notably, the system maintained robust performance (>75% SMX removal) in the presence of competing inorganic anions (NO 3 − , HCO 3 − and Cl − ). Mechanistic investigations combining DFT, EPR and UPLC-MS/MS elucidated that •OH, O 2 •− , 1 O 2 , •NO 2 and ONOOH preferentially attack the electrophilic N(4), N(7), and N(17) sites, initiating sequential diazotization and nitration pathways. Practical validation using hospital wastewater demonstrated significant removal of COD (56.17 %) and TOC (40.16 %), while effectively suppressing antimicrobial resistance genes. This work establishes PSO-SVM optimized DBD plasma as a sustainable and intelligent solution for pharmaceutical wastewater remediation.
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SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
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2022
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IF 4.831
Shan Tu,Zhigang Wang,Wentao Zhang,Yuanpeng Li,Yulai She,Hao Du,Cancan Yi,Bo Qin,Zhiqiang Liu
This study investigated the feasibility of using terahertz (THz) technology for the rapid identification of isomers. The time-domain spectra of 2-hydroxybenzoic acid (2-HA), 3-hydroxybenzoic acid (3-HA), and 4-hydroxybenzoic acid (4-HA) were measured by a THz time-domain spectroscopy system (THz-TDS) in the range of 0.3–1.8 THz. Aiming at the isomer classification problem, a THz spectral data classification model based on a variational mode decomposition–particle swarm optimization–support vector machine (VMD-PSO-SVM) method was proposed. Empirical mode decomposition (EMD) and variational mode decomposition (VMD) were used to extract the first eight intrinsic mode functions (IMFs) of the time-domain signal. Principal component analysis (PCA) was used to extract the first 80 principal components of each modal component as the classification feature vector. The particle swarm optimization (PSO) and support vector machine (SVM) algorithms were used to construct 2-, 3-, and 4-HA classification models. We found that the prediction accuracy of the VMD-PSO-SVM model was significantly higher than that of EMD-PSO-SVM model regardless of the modal components. For both EMD and VMD, with the increase in the IMF number, the corresponding classification recognition accuracy tended to decrease. The results showed that the rapid identification model of hydroxybenzoic acid isomers based on THz spectroscopy and SVM was effective and feasible, providing an accurate and rapid method for the chemical synthesis and quality monitoring of biomedicine.
研究领域:
分析化学
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生物医学工程
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PubMed
高影响因子
ACS Applied Electronic Materials
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2026
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IF 4.7
Mingzhi Jiao,Liangsong Duan,Jiade Zhang,Wei Peng,Chenyu Wen
To address the demands for efficient detection of combustible gas, such as hydrogen (H2), ethylene (C2H4), and acetylene (C2H2), in complex gas environments relevant to environmental monitoring, industrial safety, and smart homes, we developed zinc oxide (ZnO) gas sensors featuring bimetallic surface decoration with palladium (Pd) and gold (Au). Electron microscopy reveals the surface morphology of the sensing film and Pd/Au codecoration conformation, while X-ray photoelectron spectroscopy supports that codecoration modulates the distribution of surface oxygen species on ZnO. Gas sensing measurements demonstrate that Pd/Au decoration enhances both sensitivity and selectivity toward H2, C2H4, and C2H2. Specifically, a sensor decorated with 0.6 nm Pd and 2.3 nm Au exhibits a 178-fold increase in response to 160 ppm H2. Furthermore, by combining particle swarm optimization algorithm for feature selection with a support vector machine classifier, a recognition accuracy of 96.07% is achieved across seven different pure and mixture gas samples. This study presents a high-accuracy ZnO-based gas sensing platform optimized through both material engineering and machine learning algorithm, providing a reliable solution for real-world applications in industrial safety and environmental monitoring.
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高影响因子
International Journal of Nanomedicine
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2023
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IF 8
Chang Li,Chunmeng Sun,Shasha Li,Peng Han,Huimin Sun,Ammar Ouahab,Yan Shen,Yourui Xu,Yerong Xiong,Jiasheng Tu
In order to limit the adverse reactions caused by polysorbate 80 in Taxotere®, a widely used formulation of docetaxel, a safe and effective nanocarrier for this drug has been developed based on micelles formed by a new class of well-defined polyoxyethylene sorbitol oleate (PSO) with sorbitol as the matrix in aqueous solution. The physicochemical properties of the amphiphilic surfactant and the resulting micelles can be easily fine-tuned by the homogeneous sorbitol matrix and pure oleic acid. Composition, critical micelle concentration, and entrapment efficiency were investigated by ultraviolet visible spectroscopy, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, fluorospectrophotometry, and high-performance liquid chromatography. In vitro and in vivo evaluation revealed that PSO had exceptionally low hemolysis and histamine release rates compared with commercial polysorbate 80. Moreover, the tumor targeting delivery of PSO was investigated by in vivo imaging in S180 tumor-bearing mice. The results suggest that this novel delivery system, PSO, provides an acceptable alternative to polysorbate 80 for delivery of docetaxel. Further, due to the hypoallergenic nature of PSO, the mechanism of pseudoallergy caused by the polyoxyethylene nonionic surfactant was investigated. Based on in vitro cell analysis, it was assumed that the initial contact of polyoxyethylene nonionic surfactant with mast cells provoked pseudoallergy via polyamine receptor-mediated endocytosis.
研究领域:
药剂学
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生物医学工程
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肿瘤学
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PubMed
高影响因子
Journal of Functional Foods
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2024
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IF 3.8
Shengchen Ding,Jun Chen,Guangming Chen,Weiyi Tian,Junping Zheng,Haiming Hu,Lu Cao,Xiaowei Yao,Baifei Hu,Hongtao Liu
This study aimed to isolate oligosaccharides from P. sibiricum , analyze its structure, and elucidate the pharmacological mechanism for colitis improvement. First, a homogeneous oligosaccharide PSO-A was isolated and its structure was characterized. Then, the colitis model was induced with 3 % dextran sulfate sodium (DSS) and intervened with PSO-A. The results show that PSO-A was an agavin-type acetylated fructooligosaccharide with a molecular weight of 2.12 kDa. PSO-A consisted of (2 → 6)-β-D-Fru f residue backbone with an internal α-D-Glc p residue and (2 → 1)-β-D-Fru f residue side chains. Further, PSO-A increased mucin content, protected intestinal barrier integrity of colitis mice, and significantly inhibited the levels of inflammatory factors. Moreover, the protein expressions of NLRP3, ASC, and Caspase-1 in colitis mice was statistically inhibited by PSO-A. In summary, PSO-A could alleviate colitis by inhibiting NLRP3 inflammasome pathway, which provides a basis for the development and application of P. sibiricum oligosaccharides as drug or functional food to relieve colitis.
研究领域:
药理学
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生物化学
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分子生物学
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免疫学
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胃肠病学
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高影响因子
APPLIED CATALYSIS A-GENERAL
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2026
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IF 4.8
Xiaofei Ma,Shijiao Hao,Hui Jiang,Weiqian Qi,Hefang Wang
La 2 O 2 CO 3 -Cu-Al mixed oxides (CL X A-LDO) were fabricated via the calcination of lanthanum carbonate-doped Cu-Al layered double hydroxides (LDHs) with unique wool-scale-like lamellar structures. CL X A-LDO were employed for the synthesis of dimethyl carbonate (DMC) via the transesterification of methanol with propylene carbonate (PC). Characterization via XRD, FT-IR, TG, and SEM confirmed that lanthanum carbonate-doped Cu-Al LDHs with unique wool-scale-like lamellar structures were successfully prepared. After calcination, these precursors transformed into La 2 O 2 CO 3 -CuO-Al 2 O 3 composites. CO 2 -TPD and XPS results indicate that CL 1.0 A-LDO-600 possesses abundant medium/strong basic sites and a favorable O II /O I ratio. Consequently, CL 1.0 A-LDO-600 exhibited a PC conversion of 68.44% and a DMC yield of 67.84% under mild conditions (80 °C, 2 h, catalyst loading 2.0 wt%, methanol/PC molar ratio = 10). Moreover, CL 1.0 A-LDO-600 demonstrated high stability, with only a modest activity loss (Δ PC = 6.2%) after six consecutive cycles. The kinetic analysis indicated a complex reaction mechanism. However, this behavior was effectively simplified to a pseudo-first-order reaction model, providing activation energies of Ea(k + ) = 47.17 kJ·mol -1 (forward) and Ea(k - ) = 44.46 kJ·mol -1 (reverse). The experimental data were systematically validated using a particle swarm optimization-backpropagation artificial neural network (PSO-BP) model. The hybrid model demonstrated superior predictive accuracy, achieving R 2 values of 0.9956 and 0.9916 for the training and testing sets, respectively, thereby outperforming the conventional BP model. This work provides fundamental insights into the rational design of LDHs-derived mixed oxide catalysts for sustainable DMC synthesis.
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JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS
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2026
·Vol. 37
·期 7
·517
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IF 3.2
Zhu Guosong,Li Xiaoyuan,Pan Wenqian,Zhou Wei,Luo Heng,Hu Yue,Fan Xiaomeng,Li Yang
As electromagnetic environments become more complex, the design of novel electromagnetic wave absorbers (EWMs) that combine low-frequency absorption with multi-frequency response remains a significant challenge. Experimental validation demonstrates that controlling the crystallinity and morphology of the ZnO coating layer through process temperature can significantly influence the electromagnetic properties of YCo composite materials. Nevertheless, the establishment and description of the intricate relationship between process temperature and electromagnetic response remains a formidable challenge. In order to address this issue, a data-driven modeling and inverse design framework (SSA-GRNN-PSO) integrating sparrow search algorithm (SSA), generalized regression neural network (GRNN), and particle swarm optimization (PSO) is proposed based on limited experimental data. This framework facilitates precise prediction of the complex electromagnetic parameters of ZnO@YCo composites at varying processing temperatures. When combined with a multilayer structural design concept, it achieves multi-band inverse design. The final composite material, with a thickness of 19.1 mm, exhibited strong multi-band absorption characteristics, with a bandwidth of 7.452 GHz, and a reflection loss of − 25.47 dB in the 2–18 GHz range. Moreover, an optimized design with a thickness of 5.4 mm was achieved, which features a bandwidth of 7.416 GHz and a reflection loss of − 15.72 dB.
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MICROCHEMICAL JOURNAL
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2025
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IF 5.1
Shengxin Li,Ziyan Zhang,Zhiran Zhang,Sen Zhou,Mengkai Liu,Xichao Li,Zheng Zheng,Jie Sun
The moisture, oil, protein, and nervonic acid contents are crucial criteria for assessing the nutritional value and processing quality of Xanthoceras sorbifolia Bunge seed kernels (XSKs). Near-infrared spectroscopy (NIRS) offers a viable alternative to conventional chemical methods for rapid and non-destructive sample analysis. This study employed a highly adaptive method known as competitive adaptive reweighted sampling (CARS), which facilitates variable selection for different components and streamlines the feature-variable screening process. Using this method, various algorithms were applied to establish NIRS detection models for the four components of XSKs, and accuracy evaluations were conducted using the prediction set determination coefficient ( R P 2 ), root-mean-square error (RMSEP), and other parameters. The results indicated that CARS effectively extracted key information on various components in NIRS. Based on the feature variables selected by CARS, the partial least squares regression (PLSR) model exhibited optimal performance regarding moisture ( R P 2 = 0.978, RMSEP = 0.117 %) and nervonic acid content ( R P 2 = 0.988, RMSEP = 0.072 %). Meanwhile, the particle swarm optimization-enhanced support vector regression (PSO-SVR) model and back-propagation neural networks (BPNN) achieved superior performance for protein ( R P 2 = 0.989, RMSEP = 0.243 %) and oil content ( R P 2 = 0.978, RMSEP = 0.467 %), respectively. These models enable rapid and non-destructive detection of multi-component content, thereby facilitating the expeditious identification and selection of XSKs with high nutritional value and superior quality.
研究领域:
植物学
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食品科学
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分析化学
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高影响因子
CHEMICAL ENGINEERING JOURNAL
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2023
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IF 15.1
Weisen Yang,Yifei Liu,Yaqin Zhu,Wenlong Jiang,Fengshuo Shi,Jiapeng Hu,Shaohua Jiang,Shaoju Jian
Aquatic ecosystem contaminated by organic dyes is one of the most crucial issues plaguing people worldwide, while water remediation through adsorption technology is the most sustainable option. Herein, two chitosan-based adsorbents were successfully fabricated by a facile one-step method under alkaline condition via electrospraying technology, then the above two materials were cross-linked with epichlorohydrin and grafted triethylenetetramine to prepare two kinds magnetic Fe 3 O 4 /CS-ET-1 and Fe 3 O 4 /CS-ET-2 microspheres for remediation of anion dyes namely Congo red (CR) in wastewater respectively. The morphology features, structure, composition, thermal stability, and pore diameter of the two adsorbents were acquired by SEM coupled with EDX, XRD, FTIR, TGA, and BET. The adsorption behavior of Fe 3 O 4 /CS-ET-1 and Fe 3 O 4 /CS-ET-2 microspheres towards CR from water was systematically evaluated. The determined isoelectric points (pHpzc) of Fe 3 O 4 /CS-ET-1 and Fe 3 O 4 /CS-ET-2 are orderly 7.4 and 7.8. The results confirmed that the CR remediation process can be simulated by PSO kinetic model ( R 2 > 0.995) along with Langmuir isotherm ( R 2 > 0.998) with maximal CR adsorption amounts by Fe 3 O 4 /CS-ET-1 and Fe 3 O 4 /CS-ET-2 microspheres of 1145.42 and 617.28 mg g −1 at pH = 7 and T = 25 °C, respectively. The negative Δ G 0 , positive Δ H 0 (28.65 and 8.02 kJ mol −1 ), and positive Δ S 0 (112.29 and 62.71 J mol −1 K −1 ) signified that the adsorption of CR onto Fe 3 O 4 /CS-ET-1 and Fe 3 O 4 /CS-ET-2 microspheres surface was spontaneous and endothermic in nature. After four consecutive cycles, both magnetic microspheres remained a superior CR removal performance, indicative of the stability and recyclability of the adsorbents.
研究领域:
环境科学
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材料科学
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化学工程
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水处理
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高影响因子
Journal of Environmental Chemical Engineering
·
2024
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IF 7.4
Xinyu Liu,Bowen Xu,Jianlong Wang
In this study, sponge-like chitosan capsules (CTS-S) were successfully prepared as efficient adsorbent through a facile and green method. The cross-linked porous structure and abundant adsorption sites of CTS-S led to stable and remarkable adsorption efficacy for the purification of wastewater containing anionic dyes in a wide pH range. The highest maximum adsorption capacity for Congo red (CR), Reactive brilliant blue KN-R (KNR), and Methyl blue (MB) were 1372.49, 881.75, and 169.04 mg/g, respectively. Kinetics study suggested that KN-R and CR adsorption processes were best depicted by the PSO model, while PFO model was applicable for MB. Adsorption isotherms of CR, KNR, MB conformed to the Sips model, demonstrating that the adsorption of CR, KNR, MB onto CTS-S was monolayer and heterogeneous. Adsorption mechanism insights further verified that electrostatic forces, hydrogen bonds, and n-π stacking worked for efficient removal of CR, KNR, MB by CTS-S, which was supported by characterization results and DFT calculation. Overall, CTS-S provided a useful and promising option as low-cost and eco-friendly absorbents for the adsorption of synthetic dyes.
研究领域:
环境科学
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化学工程
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材料科学
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高影响因子
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