Microchemical Journal最新文献_第7页

Validated green fluorescent nanosensor for barnidipine determination using lupine-derived multi-doped carbon quantum dots 利用羽扇豆碱衍生的多掺杂碳量子点检测巴尼地平的绿色荧光纳米传感器

IF 4.9 2区化学

Microchemical Journal Pub Date : 2025-09-04 DOI: 10.1016/j.microc.2025.115163

Amal A. El-Masry , Ahmed H. Abdelazim , Islam M. Mostafa , Abdallah M. Zeid

{"title":"Validated green fluorescent nanosensor for barnidipine determination using lupine-derived multi-doped carbon quantum dots","authors":"Amal A. El-Masry , Ahmed H. Abdelazim , Islam M. Mostafa , Abdallah M. Zeid","doi":"10.1016/j.microc.2025.115163","DOIUrl":"10.1016/j.microc.2025.115163","url":null,"abstract":"<div><div>We present a green analytical fluorescence method for the selective determination of barnidipine, an antihypertensive drug, based on nitrogen, sulfur, and phosphorus co-doped carbon quantum dots (NSP-CQDs). The CQDs were synthesized <em>via</em> a rapid microwave-assisted approach using <em>Lupinus albus</em> seeds as a sustainable precursor, yielding highly fluorescent nanoparticles with a quantum yield of 25.2 %. The fluorescence of NSP-CQDs, with an emission maximum at 409 nm (λ<sub>ex</sub> = 320 nm), was efficiently quenched by barnidipine through an inner filter effect. The developed nanosensor enabled quantitative analysis of barnidipine with a linear response in the range of 25.0–250.0 μM, a detection limit of 4.91 μM, and high accuracy, achieving a mean recovery of 99.81 % in pharmaceutical dosage forms. Analytical performance was validated in terms of sensitivity, selectivity, precision, and accuracy, confirmed the reliability of the assay in pharmaceutical preparations. Greenness and practical sustainability of the method were assessed by Complex Modified GAPI and Blue Applicability Grade Index (BAGI) metrics, underscoring its compliance with green analytical chemistry principles. This work demonstrates the integration of eco-friendly nanomaterials into pharmaceutical analysis, providing a novel, reliable, and environmentally sustainable tool for fluorescence-based drug determination.</div></div>","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":"218 ","pages":"Article 115163"},"PeriodicalIF":4.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electrochemiluminescence sensor for specific recognition of melamine: double luminescence cooperative amplification strategy of self-supporting material ZnNi2O2 and Ru(bpy)32+@HNTs 三聚氰胺特异性识别电化学发光传感器：自支撑材料ZnNi2O2和Ru(bpy)32+@HNTs双发光协同放大策略

IF 4.9 2区化学

Microchemical Journal Pub Date : 2025-09-04 DOI: 10.1016/j.microc.2025.115125

Ruidan Li, Li Tian, Yujia Song, Yanjia Guo, Guangping Ma, Pengfei Han, Hanyue Jiang, Wenzhuo Wang, Juan Lu

{"title":"Electrochemiluminescence sensor for specific recognition of melamine: double luminescence cooperative amplification strategy of self-supporting material ZnNi2O2 and Ru(bpy)32+@HNTs","authors":"Ruidan Li, Li Tian, Yujia Song, Yanjia Guo, Guangping Ma, Pengfei Han, Hanyue Jiang, Wenzhuo Wang, Juan Lu","doi":"10.1016/j.microc.2025.115125","DOIUrl":"10.1016/j.microc.2025.115125","url":null,"abstract":"<div><div>A self-supporting material of ZnNi<sub>2</sub>O<sub>2</sub> was synthesized and halloysite nanotubes (HNTs) served as carriers for Ru(bpy)<sub>3</sub><sup>2+</sup>, enhancing stability of the sensor and improving the electrochemiluminescence (ECL) value in this experiment. The ECL sensor for specific recognition of melamine (MEL) was developed based on ZnNi<sub>2</sub>O<sub>2</sub> and Ru(bpy)<sub>3</sub><sup>2+</sup>@HNTs as dual ECL reagents. The maximum initial signal was obtained in the presence of co-reactant tripropylamine (TPrA) through the synergy of ZnNi<sub>2</sub>O<sub>2</sub> and Ru(bpy)<sub>3</sub><sup>2+</sup>@HNTs. A molecularly imprinted polymer (MIP) containing specific recognition sites for MEL was to enable selective recognition, with pyrrole serving as the functional monomer and MEL as the template molecule. The quenching effect was observed as the concentration of MEL increased. Under optimal conditions, the sensor demonstrated the linear correlation between the change of ECL signal and the logarithm of MEL concentration from the range of 1.0 × 10<sup>−12</sup> to 1.0 × 10<sup>−7</sup> mol·L<sup>−1</sup>. Satisfactory results were obtained for the detection of MEL in milk powder.</div></div>","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":"218 ","pages":"Article 115125"},"PeriodicalIF":4.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative evaluation of functionalized magnetic perlite–MWCNT composites for removing azacitidine and pemetrexed from water 功能化磁性珍珠岩- mwcnt复合材料去除水中氮扎胞苷和培美曲塞的比较评价

IF 4.9 2区化学

Microchemical Journal Pub Date : 2025-09-04 DOI: 10.1016/j.microc.2025.115142

Reyhaneh Kaveh , Kaveh Yasrebi

{"title":"Comparative evaluation of functionalized magnetic perlite–MWCNT composites for removing azacitidine and pemetrexed from water","authors":"Reyhaneh Kaveh , Kaveh Yasrebi","doi":"10.1016/j.microc.2025.115142","DOIUrl":"10.1016/j.microc.2025.115142","url":null,"abstract":"<div><div>This study evaluates the adsorption capacities and removal efficiencies of four adsorbents, magnetic perlite–Fe₂O₃, perlite–MWCNT, perlite–MWCNT–COOH, and perlite–MWCNT–melamine, for removing pharmaceutical contaminants azacitidine (AZA) and pemetrexed (PMX) from aqueous solutions. The magnetic perlite–MWCNT composite was synthesized via chemical vapor deposition, and the functionalized MWCNTs were prepared by controlled acid oxidation. Perlite–MWCNT–melamine demonstrated the maximum adsorption capacities (Q<sub>m</sub>), achieving 570 mg·g<sup>−1</sup> for AZA and 630 mg·g<sup>−1</sup> for PMX. Using Box–Behnken response surface methodology (RSM), we optimized contact time, adsorbent dosage, and pH to maximize removal efficiency. The adsorption process followed the Langmuir isotherm and pseudo-second-order kinetics, indicating monolayer chemisorption. Thermodynamic analysis confirmed that adsorption was spontaneous and endothermic. Additionally, all adsorbents demonstrated excellent reusability over six cycles, with minimal loss in removal efficiency. These findings suggest that melamine-functionalized perlite–MWCNT composites are highly effective and durable adsorbents for practical pharmaceutical contaminant removal in water treatment applications.</div></div>","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":"218 ","pages":"Article 115142"},"PeriodicalIF":4.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning assisted wearable antifouling sensor for reliable sweat analysis under dynamic conditions 机器学习辅助可穿戴防污传感器在动态条件下进行可靠的汗液分析

IF 4.9 2区化学

Microchemical Journal Pub Date : 2025-09-04 DOI: 10.1016/j.microc.2025.115182

Mingrui Lv , Xianghua Zeng , Xinjin Zhang , Wenpeng Sun , Xiujuan Qiao

{"title":"Machine learning assisted wearable antifouling sensor for reliable sweat analysis under dynamic conditions","authors":"Mingrui Lv , Xianghua Zeng , Xinjin Zhang , Wenpeng Sun , Xiujuan Qiao","doi":"10.1016/j.microc.2025.115182","DOIUrl":"10.1016/j.microc.2025.115182","url":null,"abstract":"<div><div>Wearable sweat sensors face persistent reliability challenges from biofouling and dynamic physiological variations during real-world use. To overcome these dual limitations, we introduce a paradigm-shifting co-design strategy integrating an antifouling catalytic hydrogel with machine learning-driven dynamic compensation. Our platform features: (1) A peptide composite hydrogel incorporating Au-PdNPs/rGO nanohybrids and engineered hydrophilic peptides, achieving exceptional antifouling performance (8.3 % signal loss in undiluted sweat) while providing specific catalytic activity toward uric acid (UA); (2) An artificial neural network (ANN) trained on 1217 experimental datasets spanning simultaneously varying physiological conditions. This synergistic approach enables three critical advances: First, the hydrogel's extreme hydrophilicity (9.01° contact angle) prevents surface fouling by sweat, maintaining electrode activity. Second, the ANN dynamically decouples environmental interference from target signals, overcoming the “single-variable optimization” limitation of conventional sensors. Third, the real sweat validation demonstrates accurate UA prediction, significantly outperforming static calibration methods and matching ELISA accuracy. By unifying antifouling material engineering with adaptive machine learning, this work establishes a new framework for reliable wearable biosensing, achieving prediction accuracy (R<sup>2</sup> = 0.9989) under real-world dynamic conditions.</div></div>","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":"218 ","pages":"Article 115182"},"PeriodicalIF":4.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sustainable electrochemical sensor from CO2 laser pyrolyzed green leaves for carbendazim detection 基于CO2激光热解绿叶的多菌灵可持续电化学传感器

IF 4.9 2区化学

Microchemical Journal Pub Date : 2025-09-04 DOI: 10.1016/j.microc.2025.115136

Beatriz F. Germinare , Jéssica R. Camargo , Wilson S. Fernandes-Junior , Bruno C. Janegitz

{"title":"Sustainable electrochemical sensor from CO2 laser pyrolyzed green leaves for carbendazim detection","authors":"Beatriz F. Germinare , Jéssica R. Camargo , Wilson S. Fernandes-Junior , Bruno C. Janegitz","doi":"10.1016/j.microc.2025.115136","DOIUrl":"10.1016/j.microc.2025.115136","url":null,"abstract":"<div><div>The use of green leaves as a substrate for electrochemical sensor production is a sustainable and innovative alternative to conventional materials. Also, CO<sub>2</sub> laser pyrolysis facilitates electrode fabrication on various substrates, promoting high-performance, eco-friendly, and cost-effective sensors. In this work, we used the green leaf as a substrate for sensors from <em>S. macrophylla</em>, a tree species that is abundant and easily accessible in Brazil. For this purpose, we adjusted the laser cutting parameters such as distance, power, and speed to improve the analytical signal. For the electrochemical measurements, the leaves were treated with 0.3 mol L<sup>−1</sup> sodium citrate to improve performance and stability. This electrochemical sensor was characterized through electrochemical and morphological analysis. The proposed sensor was applied for Carbendazim (CBZ), a fungicide that protects plants from fungal diseases and poses health risks, including carcinoma, in humans. For this analyte, the sensor presented a linear range of 0.5 to 10 μmol L<sup>−1</sup>, with a detection limit of 0.1 μmol L<sup>−1</sup>. CBZ was detected by using addition and recovery tests in tap water, orange juice, and honey, and the values varied from 90.6 % to 101.1 %. This study demonstrates that electrochemical sensors made from dehydrated green leaves exhibit effective analytical performance, high repeatability, and reproducibility, highlighting their potential as sustainable alternatives to traditional sensor substrates.</div></div>","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":"218 ","pages":"Article 115136"},"PeriodicalIF":4.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Isothermal one-pot RPA-CRISPR/Cas12b assay for rapid and highly sensitive detection of Brucella spp 一锅等温RPA-CRISPR/Cas12b快速高灵敏度检测布鲁氏菌

IF 4.9 2区化学

Microchemical Journal Pub Date : 2025-09-04 DOI: 10.1016/j.microc.2025.115139

Yongfu Chen , Xinggui Yang , Yue Wang , Fengming Chen , Xiaoyu Wei , Hai Jiang , Yong Hu , Shijun Li

{"title":"Isothermal one-pot RPA-CRISPR/Cas12b assay for rapid and highly sensitive detection of Brucella spp","authors":"Yongfu Chen , Xinggui Yang , Yue Wang , Fengming Chen , Xiaoyu Wei , Hai Jiang , Yong Hu , Shijun Li","doi":"10.1016/j.microc.2025.115139","DOIUrl":"10.1016/j.microc.2025.115139","url":null,"abstract":"<div><div>As a zoonotic disease caused by <em>Brucella</em> species, brucellosis requires rapid, sensitive, and precise diagnostic approaches to effectively curb its epidemiological spread. Herein, we developed a novel isothermal one-pot recombinase polymerase amplification (RPA)-CRISPR/Cas12b (IOPR-Cas12b) assay targeting the conserved region of the <em>Brucella</em> spp.-specific <em>BCSP31</em> gene sequence. This assay is integrated with real-time fluorescence detection and lateral flow biosensor (LFB), recognized as promising tools for Point-of-care testing (POCT) molecular diagnostics. A <em>BCSP31</em>-targeted IOPR-Cas12b assay was developed through systematic design and screening of RPA primers and guide RNA (gRNA), and optimization of reaction conditions. The IOPR-Cas12b achieved maximum efficiency at 43 °C for 40 min with real-time fluorescence and LFB readout methods. The system exhibited remarkable sensitivity with limits of detection (LOD) of 3.65 × 10<sup>1</sup> copies/reaction (real-time fluorescence) and 3.65 × 10<sup>2</sup> copies/reaction (LFB), while maintaining strict specificity by showing no cross-reactivity with 19 non-target bacterial species. Clinical validation using 61 samples demonstrated 100 % concordance between the IOPR-Cas12b assay and reference methods (culture and conventional PCR). The entire detection workflow was accomplished within 40 min through real-time fluorescence monitoring. Furthermore, the incorporation of visual LFB detection eliminated the reliance on sophisticated instrumentation, enhancing its suitability for field-deployable POCT applications. The developed one-pot platform combining IOPR-Cas12b with dual-mode detection (real-time fluorescence/LFB) offers a rapid, sensitive, and highly specific solution, providing a highly competitive technical means for brucellosis screening and prevention.</div></div>","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":"218 ","pages":"Article 115139"},"PeriodicalIF":4.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of Machine Learning Models for Classifying Wood Surface Defects Using Near-Infrared Spectroscopy 机器学习模型在近红外光谱木材表面缺陷分类中的应用

IF 4.9 2区化学

Microchemical Journal Pub Date : 2025-09-04 DOI: 10.1016/j.microc.2025.115180

Jiawei Zhang, Wenlan Huang, Zhengfan Shang, Jiawen Shi, Bin Na

{"title":"Application of Machine Learning Models for Classifying Wood Surface Defects Using Near-Infrared Spectroscopy","authors":"Jiawei Zhang, Wenlan Huang, Zhengfan Shang, Jiawen Shi, Bin Na","doi":"10.1016/j.microc.2025.115180","DOIUrl":"10.1016/j.microc.2025.115180","url":null,"abstract":"<div><div>Accurate identification of wood surface defects is crucial for improving the quality and utilization of wood products. To address the low efficiency and accuracy of traditional manual inspection methods, this study collected near-infrared spectroscopy (NIRS) data from Brich and Fir surfaces, including defect-free samples and three typical defect types. The effectiveness of machine learning models in classifying wood surface defects was systematically investigated. Two feature dimensionality reduction methods, principal component analysis (PCA) and recursive feature elimination (RFE), were selected for comparison to screen out representative feature variables. Four classification models, namely, partial least squares discriminant analysis (PLS-DA), random forest (RF), support vector machine (SVM) and fully connected neural network (FCNN), were used to model and classify the wood defect samples. The results indicate that PCA outperforms RFE in enhancing model classification performance. Among the models, the FCNN achieved the best performance, with a highest classification accuracy of 98.85 %, and both recall and F1-score reaching 0.989. These findings demonstrate the superiority of deep learning methods in wood defect recognition tasks. This study systematically evaluated machine learning models based on near-infrared spectroscopy for the classification of wood surface defects, providing valuable insights for model selection and optimization in future research.</div></div>","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":"218 ","pages":"Article 115180"},"PeriodicalIF":4.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A cucurbituril-based N-doped carbon nanomaterial for efficient detection and removal of Fe(CN)63− 一种有效检测和去除Fe(CN)63−的瓜脲基n掺杂碳纳米材料

IF 4.9 2区化学

Microchemical Journal Pub Date : 2025-09-04 DOI: 10.1016/j.microc.2025.115141

Li Liu , Bo Xiao , Ran Cen , Zi-Yun Li , Shang-Wei Yuan , Xin Xiao

引用次数: 0

A novel smartphone-based electrochemical hydroquinone sensor using renewable electrocatalyst of carboxyl-functionalized carbon nanofiber derived from white seabass scale collagen 一种基于智能手机的新型对苯二酚电化学传感器，使用可再生电催化剂的羧基功能化碳纳米纤维来源于白鲈鱼鳞片胶原蛋白

IF 4.9 2区化学

Microchemical Journal Pub Date : 2025-09-04 DOI: 10.1016/j.microc.2025.115186

Thanawath Tuntiwongmetee , Suntisak Khumngern , Kwansuda Kongthong , Kaewta Kaewtatip , Supapich Romportong , Natha Nontipichet , Panote Thavarungkul , Apon Numnuam

{"title":"A novel smartphone-based electrochemical hydroquinone sensor using renewable electrocatalyst of carboxyl-functionalized carbon nanofiber derived from white seabass scale collagen","authors":"Thanawath Tuntiwongmetee , Suntisak Khumngern , Kwansuda Kongthong , Kaewta Kaewtatip , Supapich Romportong , Natha Nontipichet , Panote Thavarungkul , Apon Numnuam","doi":"10.1016/j.microc.2025.115186","DOIUrl":"10.1016/j.microc.2025.115186","url":null,"abstract":"<div><div>A smartphone-assisted square wave voltametric hydroquinone (HQ) sensor was developed based on novel functionalized carbon nanofiber (f-CNF) derived from a sustainable precursor of white seabass (<em>Lates calcarifer</em>) scale collagen via slow pyrolysis carbonization. The as-prepared f-CNF exhibited a consistent fibrous structure with a large surface area, high graphitic content, high crystallinity, abundant carboxyl groups, and excellent dispersibility. The f-CNF was drop-cast on a screen-printed carbon electrode (f-CNF/SPCE). The proposed sensor exhibited high electrical conductivity, rapid electron transfer, a large electroactive surface area, a high number of adsorption sites, and outstanding electrocatalytic activity. The portable HQ sensor demonstrated a wide linear detection range from 1.0 to 150 μM (R<sup>2</sup> = 0.9959) with a limit of detection (LOD) at 0.54 μM. Reproducibility and selectivity were excellent. The highlights of this electrochemical sensor are reusability for up to 18 cycles (90 individual measurements) and high stability for 8 weeks in use and 12 weeks in storage. The f-CNF/SPCE successfully detected HQ in pharmaceutical samples, achieving acceptable recoveries from 96.1 to 102.9 %. The results were consistent with those obtained using UV–Vis spectrophotometry and with product label information. Additionally, the square wave voltametric sensing application allows for the simultaneous detection of HQ, catechol (CC), and resorcinol (RS).</div></div>","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":"218 ","pages":"Article 115186"},"PeriodicalIF":4.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From agro-waste to advanced electrochemical interface: Selective detection of hydroquinone and catechol using sunflower-derived carbon 从农业废弃物到先进的电化学界面：利用向日葵衍生碳选择性检测对苯二酚和儿茶酚

IF 4.9 2区化学

Microchemical Journal Pub Date : 2025-09-04 DOI: 10.1016/j.microc.2025.115184

Jingwen Yin , Hongteng Zhang , Yue Wang

{"title":"From agro-waste to advanced electrochemical interface: Selective detection of hydroquinone and catechol using sunflower-derived carbon","authors":"Jingwen Yin , Hongteng Zhang , Yue Wang","doi":"10.1016/j.microc.2025.115184","DOIUrl":"10.1016/j.microc.2025.115184","url":null,"abstract":"<div><div>In this study, an ultrasensitive, cost-effective, and environmentally sustainable electrochemical sensor was developed using porous carbon derived from sunflower seed shells for the simultaneous detection of hydroquinone (HQ) and catechol (CC), two toxic phenolic pollutants frequently present in industrial effluents. The carbon material was synthesized through a direct, single-step pyrolysis process that required no chemical activation or metal additives, aligning with the principles of green chemistry and resource valorization. The structural and surface chemical properties of the carbon were comprehensively characterized using SEM, EDS, XRD, FTIR, and Raman spectroscopy. The presence of abundant oxygen-containing functional groups and naturally retained KCl contributed to the enhanced surface reactivity and electrical conductivity of the resulting carbons. The fabricated electrode exhibited excellent performance in simultaneously detecting HQ and CC, with distinct redox peak separation, high sensitivity, rapid response, and strong anti-interference capability. Under optimized conditions, the sensor achieved wide linear detection range of 0.5–400 μM for both analytes and ultralow detection limits of 3.24 nM for HQ and 1.95 nM for CC. The practical applicability of the sensor was validated using river and tap water samples, yielding recovery rates between 97.25 % and 106.42 %, which were in excellent agreement with high-performance liquid chromatography (HPLC) results. This work underscores the feasibility of converting agricultural waste into high-performance carbon-based sensing platforms for real-time environmental pollutant monitoring</div></div>","PeriodicalId":391,"journal":{"name":"Microchemical Journal","volume":"218 ","pages":"Article 115184"},"PeriodicalIF":4.9,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0