Pub Date : 2025-02-18DOI: 10.1016/j.saa.2025.125918
Nafees Ahmad , Ghada Eid , Mohamed M. El-Toony , Asif Mahmood
The design of fluorescent dyes with optimized performance is crucial for advancements in various fields, including bioimaging, diagnostics, and optoelectronics. Traditional approaches to dye design often rely on trial-and-error experimentation, which can be time-consuming and resource-intensive. 42 ML models are tried for each property. One best model is selected for each property. Gradient boosting regressor is best model for the prediction of excitation values while extra trees regressor is best model for the prediction of emission values. A database of 5000 new dyes is generated and analyzed. 30 dyes with higher excitation and emission values are selected. Synthetic accessibility analysis is done for 30 dyes and majority of dyes are easy to synthesized. Our results demonstrate that ML-assisted design can significantly accelerate the discovery process, reduce the need for costly experimental iterations, and lead to the development of dyes with tailored properties for specific applications.
{"title":"Harnessing machine learning for the rational design of high-performance fluorescent dyes","authors":"Nafees Ahmad , Ghada Eid , Mohamed M. El-Toony , Asif Mahmood","doi":"10.1016/j.saa.2025.125918","DOIUrl":"10.1016/j.saa.2025.125918","url":null,"abstract":"<div><div>The design of fluorescent dyes with optimized performance is crucial for advancements in various fields, including bioimaging, diagnostics, and optoelectronics. Traditional approaches to dye design often rely on trial-and-error experimentation, which can be time-consuming and resource-intensive. 42 ML models are tried for each property. One best model is selected for each property. Gradient boosting regressor is best model for the prediction of excitation values while extra trees regressor is best model for the prediction of emission values. A database of 5000 new dyes is generated and analyzed. 30 dyes with higher excitation and emission values are selected. Synthetic accessibility analysis is done for 30 dyes and majority of dyes are easy to synthesized. Our results demonstrate that ML-assisted design can significantly accelerate the discovery process, reduce the need for costly experimental iterations, and lead to the development of dyes with tailored properties for specific applications.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125918"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464559","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}
Pub Date : 2025-02-18DOI: 10.1016/j.saa.2025.125920
Lu Bai , Xue Pan , Zhicheng Liu
The development of electrospun nanomaterials as highly efficient and portable substrates for surface-enhanced Raman scattering (SERS) is of great significance for rapid detection of pollutant molecules. In this work, we prepared sustainable polylactic acid (PLA) electrospun nanofibers decorated with silver nanoparticles (Ag NPs) as a flexible SERS substrate through a combined process of facile electrospinning and green plasma treatment. Using rhodamine 6G (R6G) as probe molecule, the PLA/Ag NPs composite nanofibers show excellent SERS performance and allow the detection of R6G at a low concentration of 10−10 M. In addition, the SERS substrate could be used for trace detection of pesticide thiram, and exhibits high sensitivity with a detection limit of 10−8 M. By taking advantage of the flexibility of the nanofibers, the nanofibrous membrane was pasted on the surface of an apple to sample and detect residual thiram, and the pesticide could be distinctly identified even at a low concentration of 10−7 M. The presence of dense Ag NPs with numerous hot-spots played a crucial role in the substrate’s high sensitivity for SERS detection. This environmentally friendly, self-supporting SERS substrate holds great promise for diverse applications, including environmental monitoring and medical diagnostics.
{"title":"Fabrication of a flexible nanofiber membrane for SERS detection of pollutants: An efficient and eco-friendly approach","authors":"Lu Bai , Xue Pan , Zhicheng Liu","doi":"10.1016/j.saa.2025.125920","DOIUrl":"10.1016/j.saa.2025.125920","url":null,"abstract":"<div><div>The development of electrospun nanomaterials as highly efficient and portable substrates for surface-enhanced Raman scattering (SERS) is of great significance for rapid detection of pollutant molecules. In this work, we prepared sustainable polylactic acid (PLA) electrospun nanofibers decorated with silver nanoparticles (Ag NPs) as a flexible SERS substrate through a combined process of facile electrospinning and green plasma treatment. Using rhodamine 6G (R6G) as probe molecule, the PLA/Ag NPs composite nanofibers show excellent SERS performance and allow the detection of R6G at a low concentration of 10<sup>−10</sup> M. In addition, the SERS substrate could be used for trace detection of pesticide thiram, and exhibits high sensitivity with a detection limit of 10<sup>−8</sup> M. By taking advantage of the flexibility of the nanofibers, the nanofibrous membrane was pasted on the surface of an apple to sample and detect residual thiram, and the pesticide could be distinctly identified even at a low concentration of 10<sup>−7</sup> M. The presence of dense Ag NPs with numerous hot-spots played a crucial role in the substrate’s high sensitivity for SERS detection. This environmentally friendly, self-supporting SERS substrate holds great promise for diverse applications, including environmental monitoring and medical diagnostics.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125920"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464557","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}
Pub Date : 2025-02-18DOI: 10.1016/j.saa.2025.125930
Marlon Rodrigues , Everson Cezar , Glaucio Leboso Alemparte Abrantes dos Santos , Amanda Silveira Reis , Roney Berti de Oliveira , Leticia de Melo Teixeira , Marcos Rafael Nanni
This study investigated the development and validation of predictive models for estimating foliar nitrogen (N), phosphorus (P), and potassium (K) contents, along with shoot dry mass (SDM) of Brachiaria ruziziensis L. The approach utilized Vis-NIR-SWIR spectroscopy coupled with multivariate statistical techniques (PLS, PCR) and machine learning algorithms (SVM, RF). A triple-factorial, completely randomized design with ten replications per treatment was employed in a greenhouse setting. Treatments included type of input (limestone-mining coproducts), input particle size (filler and powder), and soil class (Arenosol and Ferralsol). Following input incubation, B. ruziziensis was sown. Forty days later, foliar spectra and leaves were collected. Chemical analysis determined NPK content, along with SDM. The study developed predictive models utilizing Vis-NIR-SWIR spectroscopy, Partial Least Squares (PLS), and machine learning algorithms like Support Vector Machine (SVM) and Random Forest (RF) to estimate foliar N, P, K, and biomass. Model adjustments achieved R2p > 0.70 and RPDp > 1.80 for PLS, SVM, and RF models across all variables (SDM, N, P, and K). These results highlight the effectiveness of specific spectral bands for nutrient and biomass discrimination and emphasize the potential of these techniques for rapid, non-destructive nutrient content estimation. The findings support the integration of advanced spectroscopic methods with machine learning algorithms for improved precision agriculture practices, providing a more sustainable alternative for nutrient and biomass analysis in forage crops. This approach optimizes forage production and minimizes atmospheric CO2 emissions.
{"title":"Unveiling the potential of Brachiaria ruziziensis: Comparative analysis of multivariate and machine learning models for biomass and NPK prediction using Vis-NIR-SWIR spectroscopy","authors":"Marlon Rodrigues , Everson Cezar , Glaucio Leboso Alemparte Abrantes dos Santos , Amanda Silveira Reis , Roney Berti de Oliveira , Leticia de Melo Teixeira , Marcos Rafael Nanni","doi":"10.1016/j.saa.2025.125930","DOIUrl":"10.1016/j.saa.2025.125930","url":null,"abstract":"<div><div>This study investigated the development and validation of predictive models for estimating foliar nitrogen (N), phosphorus (P), and potassium (K) contents, along with shoot dry mass (SDM) of <em>Brachiaria ruziziensis</em> L. The approach utilized Vis-NIR-SWIR spectroscopy coupled with multivariate statistical techniques (PLS, PCR) and machine learning algorithms (SVM, RF). A triple-factorial, completely randomized design with ten replications per treatment was employed in a greenhouse setting. Treatments included type of input (limestone-mining coproducts), input particle size (filler and powder), and soil class (Arenosol and Ferralsol). Following input incubation, <em>B. ruziziensis</em> was sown. Forty days later, foliar spectra and leaves were collected. Chemical analysis determined NPK content, along with SDM. The study developed predictive models utilizing Vis-NIR-SWIR spectroscopy, Partial Least Squares (PLS), and machine learning algorithms like Support Vector Machine (SVM) and Random Forest (RF) to estimate foliar N, P, K, and biomass. Model adjustments achieved R<sup>2</sup><sub>p</sub> > 0.70 and RPD<sub>p</sub> > 1.80 for PLS, SVM, and RF models across all variables (SDM, N, P, and K). These results highlight the effectiveness of specific spectral bands for nutrient and biomass discrimination and emphasize the potential of these techniques for rapid, non-destructive nutrient content estimation. The findings support the integration of advanced spectroscopic methods with machine learning algorithms for improved precision agriculture practices, providing a more sustainable alternative for nutrient and biomass analysis in forage crops. This approach optimizes forage production and minimizes atmospheric CO<sub>2</sub> emissions.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125930"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464560","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}
Accurate assessment of soluble solid content (SSC) in blueberries is crucial for quality evaluation. However, in real production lines, blueberries are usually in random placement and the biological heterogeneity of blueberry parts can lead to spectral distortion, which affects the accuracy of SSC prediction models in various placement situations. Therefore, it is crucial to investigate an appropriate modeling method to minimize these negative effects. In this paper, we propose an approach that combines hyperspectral imaging (HSI) technique, residual multilayer perceptron, and transfer learning to build a universal model capable of detecting blueberry SSC in various placement situations. The study acquired SSC values of 1150 blueberry samples and hyperspectral data at different surfaces (stem end, calyx end, and two parts of the equatorial plane), used a residual multilayer perceptron to build a local model, and fine-tuned the model by transfer learning to improve its generalization ability. The results show that the optimized model has significantly improved prediction accuracy on different surfaces, especially the model based on equatorial surface data (enhanced-equator-1) performs well. In the external validation set, the model achieved correlation coefficients of prediction (rp) of 0.941, 0.924, 0.933, and 0.943; root mean square errors of prediction (RMSEP) of 0.539 %, 0.612 %, 0.571 %, and 0.542 %; and residual predictive deviations (RPD) of 2.91, 2.57, 2.75, and 2.90 on the four surfaces, respectively. This suggests that building a local model by residual multilayer perceptron and fine-tuning the model using the transfer learning method can eliminate the effect of the heterogeneity of blueberry parts on the model to a certain extent, enhance the robustness of the model to biological heterogeneity, and improve the accuracy of the detection of blueberry SSC under different placement situations.
{"title":"Exploring a universal model for predicting blueberry soluble solids content based on hyperspectral imaging and transfer learning to address spatial heterogeneity challenge","authors":"Guoliang Chen, Mianqing Yang, Guozheng Wang, Jingyuan Dai, Saiwei Yu, Baichao Chen, Dayang Liu","doi":"10.1016/j.saa.2025.125921","DOIUrl":"10.1016/j.saa.2025.125921","url":null,"abstract":"<div><div>Accurate assessment of soluble solid content (SSC) in blueberries is crucial for quality evaluation. However, in real production lines, blueberries are usually in random placement and the biological heterogeneity of blueberry parts can lead to spectral distortion, which affects the accuracy of SSC prediction models in various placement situations. Therefore, it is crucial to investigate an appropriate modeling method to minimize these negative effects. In this paper, we propose an approach that combines hyperspectral imaging (HSI) technique, residual multilayer perceptron, and transfer learning to build a universal model capable of detecting blueberry SSC in various placement situations. The study acquired SSC values of 1150 blueberry samples and hyperspectral data at different surfaces (stem end, calyx end, and two parts of the equatorial plane), used a residual multilayer perceptron to build a local model, and fine-tuned the model by transfer learning to improve its generalization ability. The results show that the optimized model has significantly improved prediction accuracy on different surfaces, especially the model based on equatorial surface data (enhanced-equator-1) performs well. In the external validation set, the model achieved correlation coefficients of prediction (<em>r<sub>p</sub></em>) of 0.941, 0.924, 0.933, and 0.943; root mean square errors of prediction (RMSEP) of 0.539 %, 0.612 %, 0.571 %, and 0.542 %; and residual predictive deviations (RPD) of 2.91, 2.57, 2.75, and 2.90 on the four surfaces, respectively. This suggests that building a local model by residual multilayer perceptron and fine-tuning the model using the transfer learning method can eliminate the effect of the heterogeneity of blueberry parts on the model to a certain extent, enhance the robustness of the model to biological heterogeneity, and improve the accuracy of the detection of blueberry SSC under different placement situations.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125921"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464556","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}
Pub Date : 2025-02-18DOI: 10.1016/j.saa.2025.125923
Xiaoli Zhang , Zhaoguang Wang , Jing Yang , Yingying Li , Cheng Lu , Yanqiang Hao , Guanbo He , Yongjian Zhang , Qifang Song , Jun Long , Jiajie Liang , Yong Tang
Currently, producing NPSH after HPV infection of cells has been confirmed. These NPSH-containing substances accumulate around the urethral opening and are subsequently washed out with urine. Therefore, indirect detection of HPV infection by assessing NPSH levels in urine is feasible, but it has not been reported in detail so far. Here, an assay using phosphotungstic acid to oxidise and produce colour changes by NPSH in urine was developed. This assay enabled the rapid, non-invasive identification of HPV infection by detecting the metabolic byproduct NPSH produced by HPV-infected cells. Employing a smartphone-based device, developed using an ambient light sensor, reduces the cost and simplifies the operation associated with the colourimetric assay. The colourimetric assay was used to detect L-cysteine and L-ascorbic acid standard substance (as NPSH mimics), the limited of detection were 0.12 mM and 31.25 μM, respectively, with high reproducibility and stability. When this colourimetric assay was used to evaluate urine samples from individuals suspected of HPV infection, along with other at-home self-screening methods for HPV nucleic acid detection in urine, showed comparable sensitivity and specificity. Compared with nucleic acid detection in urine, this colourimetric assay is cost-effective, user-friendly, amenable to self-sampling, and enables testing at one’s convenience and location of choice, which is more suitable for home self-testing or population self-screening.
{"title":"Smartphone-based urine colourimetric assay for home self-screening of HPV infection","authors":"Xiaoli Zhang , Zhaoguang Wang , Jing Yang , Yingying Li , Cheng Lu , Yanqiang Hao , Guanbo He , Yongjian Zhang , Qifang Song , Jun Long , Jiajie Liang , Yong Tang","doi":"10.1016/j.saa.2025.125923","DOIUrl":"10.1016/j.saa.2025.125923","url":null,"abstract":"<div><div>Currently, producing NPSH after HPV infection of cells has been confirmed. These NPSH-containing substances accumulate around the urethral opening and are subsequently washed out with urine. Therefore, indirect detection of HPV infection by assessing NPSH levels in urine is feasible, but it has not been reported in detail so far. Here, an assay using phosphotungstic acid to oxidise and produce colour changes by NPSH in urine was developed. This assay enabled the rapid, non-invasive identification of HPV infection by detecting the metabolic byproduct NPSH produced by HPV-infected cells. Employing a smartphone-based device, developed using an ambient light sensor, reduces the cost and simplifies the operation associated with the colourimetric assay. The colourimetric assay was used to detect L-cysteine and L-ascorbic acid standard substance (as NPSH mimics), the limited of detection were 0.12 mM and 31.25 μM, respectively, with high reproducibility and stability. When this colourimetric assay was used to evaluate urine samples from individuals suspected of HPV infection, along with other at-home self-screening methods for HPV nucleic acid detection in urine, showed comparable sensitivity and specificity. Compared with nucleic acid detection in urine, this colourimetric assay is cost-effective, user-friendly, amenable to self-sampling, and enables testing at one’s convenience and location of choice, which is more suitable for home self-testing or population self-screening.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125923"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464563","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}
Pub Date : 2025-02-18DOI: 10.1016/j.saa.2025.125914
Chao Zhou , Yi Yao , Xue Guo, Bo Yang
Fe3+ is an essential element for the human body, and its regulation in cells is associated with serious diseases. Therefore, the ability to detect Fe3+ in living cells is highly valuable. In this study, we successfully developed a novel supramolecular fluorescent probe (ACB-TPE), based on an acyclic cucurbituril and tetraphenylethylene derivatives. The ACB-TPE probe retains the aggregation-induced emission property of TPE, and it can achieve highly specific recognition of Fe3+ ions without interference from other metal ions, anions, or amino acids. The binding constant between ACB-TPE and Fe3+ is 1.42 × 105, and the detection limit is 8.36 × 10−8 M. Additionally, the probe displayed a high response speed to Fe3+. Importantly, the ACB-TPE probe exhibited strong fluorescence emission in living cells, enabling the detection of Fe3+ through bioimaging. These make it a valuable tool for studying the role of Fe3+ regulation in cellular processes and disease pathogenesis. A significant contribution to the field of cellular metal ion detection and regulation is made by the probe’s unique properties and applications.
{"title":"Nano fluorescent probe based on acyclic cucurbituril for Fe3+ detection in cells","authors":"Chao Zhou , Yi Yao , Xue Guo, Bo Yang","doi":"10.1016/j.saa.2025.125914","DOIUrl":"10.1016/j.saa.2025.125914","url":null,"abstract":"<div><div>Fe<sup>3+</sup> is an essential element for the human body, and its regulation in cells is associated with serious diseases. Therefore, the ability to detect Fe<sup>3+</sup> in living cells is highly valuable. In this study, we successfully developed a novel supramolecular fluorescent probe (ACB-TPE), based on an acyclic cucurbituril and tetraphenylethylene derivatives. The ACB-TPE probe retains the aggregation-induced emission property of TPE, and it can achieve highly specific recognition of Fe<sup>3+</sup> ions without interference from other metal ions, anions, or amino acids. The binding constant between ACB-TPE and Fe<sup>3+</sup> is 1.42 × 10<sup>5</sup>, and the detection limit is 8.36 × 10<sup>−8</sup> M. Additionally, the probe displayed a high response speed to Fe<sup>3+</sup>. Importantly, the ACB-TPE probe exhibited strong fluorescence emission in living cells, enabling the detection of Fe<sup>3+</sup> through bioimaging. These make it a valuable tool for studying the role of Fe<sup>3+</sup> regulation in cellular processes and disease pathogenesis. A significant contribution to the field of cellular metal ion detection and regulation is made by the probe’s unique properties and applications.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125914"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464564","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}
Pub Date : 2025-02-18DOI: 10.1016/j.saa.2025.125899
Hua-Ying Chen , Yue He , Chao Chen , Jing Wang , Kai Ge , Bin-Bin Chen , Da-Wei Li
A surface-enhanced Raman spectroscopy (SERS) nanosensor with dual-reactivity is developed for the simultaneous imaging of hypochlorite (ClO−) and nitric oxide (NO) in living cells. Utilizing the specific reactions between functional molecules and ClO− and NO, respectively, the 2-mercapto-4-methoxy-phenol (2-MP) and o-phenylenediamine (OPD) molecules are synchronously assembled on the surface of gold nanoparticles to fabricate the dual-function nanosensors. The advantages of SERS technology, narrow peaks for spectral multiplexing and fingerprint information, further facilitate the simultaneous detection of ClO− and NO. The prepared nanosensors achieve a highly sensitive and selective measurement of ClO− and NO with a limit of detection of 0.054 μM and 0.46 μM, respectively. Furthermore, the SERS nanosensors enable the simultaneous visualization of ClO− and NO in the single living cell, which opens up the prospects to investigate the ClO−- and NO-involved physiological and pathological events.
{"title":"A dual-reactivity-based surface-enhanced Raman spectroscopy nanosensor for the simultaneous imaging of hypochlorite and nitric oxide in living cells","authors":"Hua-Ying Chen , Yue He , Chao Chen , Jing Wang , Kai Ge , Bin-Bin Chen , Da-Wei Li","doi":"10.1016/j.saa.2025.125899","DOIUrl":"10.1016/j.saa.2025.125899","url":null,"abstract":"<div><div>A surface-enhanced Raman spectroscopy (SERS) nanosensor with dual-reactivity is developed for the simultaneous imaging of hypochlorite (ClO<sup>−</sup>) and nitric oxide (NO) in living cells. Utilizing the specific reactions between functional molecules and ClO<sup>−</sup> and NO, respectively, the 2-mercapto-4-methoxy-phenol (2-MP) and o-phenylenediamine (OPD) molecules are synchronously assembled on the surface of gold nanoparticles to fabricate the dual-function nanosensors. The advantages of SERS technology, narrow peaks for spectral multiplexing and fingerprint information, further facilitate the simultaneous detection of ClO<sup>−</sup> and NO. The prepared nanosensors achieve a highly sensitive and selective measurement of ClO<sup>−</sup> and NO with a limit of detection of 0.054 μM and 0.46 μM, respectively. Furthermore, the SERS nanosensors enable the simultaneous visualization of ClO<sup>−</sup> and NO in the single living cell, which opens up the prospects to investigate the ClO<sup>−</sup>- and NO-involved physiological and pathological events.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125899"},"PeriodicalIF":4.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464681","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}
Pub Date : 2025-02-17DOI: 10.1016/j.saa.2025.125912
Yansheng Liu , Mengqi Wang , Guofu Wang , Xiaobo Jia , Jin Zhou , Hongqi Li , Haixin Chang , Zhaoxu Li
This work reported a surface-enhanced Raman spectroscopy (SERS)-based microfluidic chip that detects mercury ions (Hg2+) in water with high sensitivity and good reproducibility. Silver nanoparticles (AgNPs) are easily fabricated on a Si substrate using a thin, thermally treated Ag film. Cy3 functionalized single-stranded DNA (Cy3-ssDNA) serves as the probe, which is immobilized on the AgNPs (Cy3-ssDNA/AgNPs), generating a SERS-based sensing surface. Due to the strong interaction between thymine (T) bases and Hg2+, in the presence of these ions, the ssDNA forms a T-Hg2+-T hairpin structure, which enhances the SERS signal. This method exhibits a limit of detection (LOD) of 1 × 10−13 M. Furthermore, the proposed SERS chip demonstrates exceptional selectivity for mercury ions, as well as good reusability. The reusability of the SERS microfluidic chip was evaluated using the L-cysteine, which has a stronger affinity than T for Hg2+. By applying L-cysteine, the chip can be reused 10 times for the detection of Hg2+ at concentrations as low as 1 × 10−8 M. The method proposed in this study shows good sensitivity and holds good potential for application in the detection of Hg2+.
{"title":"Detection of Hg2+ in environmental water conditions by using a reusable SERS-based microfluidic chip with a high specificity and sensitivity","authors":"Yansheng Liu , Mengqi Wang , Guofu Wang , Xiaobo Jia , Jin Zhou , Hongqi Li , Haixin Chang , Zhaoxu Li","doi":"10.1016/j.saa.2025.125912","DOIUrl":"10.1016/j.saa.2025.125912","url":null,"abstract":"<div><div>This work reported a surface-enhanced Raman spectroscopy (SERS)-based microfluidic chip that detects mercury ions (Hg<sup>2+</sup>) in water with high sensitivity and good reproducibility. Silver nanoparticles (AgNPs) are easily fabricated on a Si substrate using a thin, thermally treated Ag film. Cy3 functionalized single-stranded DNA (Cy3-ssDNA) serves as the probe, which is immobilized on the AgNPs (Cy3-ssDNA/AgNPs), generating a SERS-based sensing surface. Due to the strong interaction between thymine (T) bases and Hg<sup>2+</sup>, in the presence of these ions, the ssDNA forms a T-Hg<sup>2+</sup>-T hairpin structure, which enhances the SERS signal. This method exhibits a limit of detection (LOD) of 1 × 10<sup>−13</sup> M. Furthermore, the proposed SERS chip demonstrates exceptional selectivity for mercury ions, as well as good reusability. The reusability of the SERS microfluidic chip was evaluated using the L-cysteine, which has a stronger affinity than T for Hg<sup>2+</sup>. By applying L-cysteine, the chip can be reused 10 times for the detection of Hg<sup>2+</sup> at concentrations as low as 1 × 10<sup>−8</sup> M. The method proposed in this study shows good sensitivity and holds good potential for application in the detection of Hg<sup>2+</sup>.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"333 ","pages":"Article 125912"},"PeriodicalIF":4.3,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445312","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}
Pub Date : 2025-02-17DOI: 10.1016/j.saa.2025.125919
Yuanjie Teng , Yi Zhong , Pei Xu , Jie Li , Zaifa Pan , Tianyu Hu , Haibing Ji , Xingchen Zhang , Yantao Lou
Gold, silver, and copper nanoparticles (CuNPs) exhibit strong localized surface plasmon resonance (LSPR) effects at specific sizes, which can amplify the Raman signals of adsorbed molecules. However, despite the cost-effectiveness of CuNPs, their applications in surface-enhanced Raman spectroscopy (SERS) are limited due to their susceptibility to surface oxidation and particle aggregation. In this study, three distinct capping agents—pillararenes, polyvinylpyrrolidone, and sodium citrate—were employed to enhance particle dispersion, improve stability, and protect the CuNPs from oxidation and degradation. The synthesized CuNPs were thoroughly characterized using UV–Vis absorption spectroscopy, transmission electron microscopy, energy-dispersive X-ray spectroscopy and Raman spectroscopy. Results revealed that CuNPs capped with pillararenes demonstrated superior SERS enhancement effects when using 4-aminothiophenol as the probe molecule, achieving an enhancement factor of 3.7 × 105. Furthermore, pillararene-capped CuNPs exhibited a broader linear range in SERS quantitative detection applications. This proposed method offers a versatile and cost-effective SERS substrate compared to commercial gold and silver nanocolloids, positioning it as a promising candidate for a wide range of SERS applications.
{"title":"Utilizing pillararenes as capping agents to stabilize copper nanoparticles for cost-effective and high-performance SERS application","authors":"Yuanjie Teng , Yi Zhong , Pei Xu , Jie Li , Zaifa Pan , Tianyu Hu , Haibing Ji , Xingchen Zhang , Yantao Lou","doi":"10.1016/j.saa.2025.125919","DOIUrl":"10.1016/j.saa.2025.125919","url":null,"abstract":"<div><div>Gold, silver, and copper nanoparticles (CuNPs) exhibit strong localized surface plasmon resonance (LSPR) effects at specific sizes, which can amplify the Raman signals of adsorbed molecules. However, despite the cost-effectiveness of CuNPs, their applications in surface-enhanced Raman spectroscopy (SERS) are limited due to their susceptibility to surface oxidation and particle aggregation. In this study, three distinct capping agents—pillararenes, polyvinylpyrrolidone, and sodium citrate—were employed to enhance particle dispersion, improve stability, and protect the CuNPs from oxidation and degradation. The synthesized CuNPs were thoroughly characterized using UV–Vis absorption spectroscopy, transmission electron microscopy, energy-dispersive X-ray spectroscopy and Raman spectroscopy. Results revealed that CuNPs capped with pillararenes demonstrated superior SERS enhancement effects when using 4-aminothiophenol as the probe molecule, achieving an enhancement factor of 3.7 × 10<sup>5</sup>. Furthermore, pillararene-capped CuNPs exhibited a broader linear range in SERS quantitative detection applications. This proposed method offers a versatile and cost-effective SERS substrate compared to commercial gold and silver nanocolloids, positioning it as a promising candidate for a wide range of SERS applications.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"334 ","pages":"Article 125919"},"PeriodicalIF":4.3,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464683","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}
Pub Date : 2025-02-17DOI: 10.1016/j.saa.2025.125915
Yihan Cheng , Linlong Deng , Lei Xue , Shuai Fu , Yunke Gao , Haibin Wang
In this study, a new versatile fluorescent probe, YH (N, N-((1E, 1′E)-((phenylazanediyl)bis(4, 1-phenylene))bis(methanylylidene))di(picolinohydrazide)), was created and synthesized. YH demonstrated the capability to continuously detect Cu2+ and PO43− in EtOH/HEPES solutions (95/5, V/V, HEPES = 10 mmol, pH = 7.4). Additionally, YH could function as a ratiometric fluorescent probe for identifying Zn2+. The interaction mechanisms among YH and Cu2+ as well as Zn2+ were elucidated through 1H NMR titration, mass spectrometry, and FT-IR spectroscopy. Moreover, YH displayed aggregation-induced luminescence in methanol and water. Furthermore, the solid form of YH exhibited notable mechanochromism characteristics, transitioning from blue to green after grinding, and this process was reversible by ethanol vapor fumigation. Due to YH’s high sensitivity to mechanical stimuli, a starch @ YH composite was successfully developed for detecting latent fingerprints. Meanwhile, YH was utilized for detecting Cu2+ and Zn2+ in environmental water samples and was effectively employed with test papers for ion detection, demonstrating broad application prospect.
{"title":"A triphenylamine-based multifunctional fluorescent probe for Cu2+ and Zn2+ as well as mechanochromism and application in latent fingerprints","authors":"Yihan Cheng , Linlong Deng , Lei Xue , Shuai Fu , Yunke Gao , Haibin Wang","doi":"10.1016/j.saa.2025.125915","DOIUrl":"10.1016/j.saa.2025.125915","url":null,"abstract":"<div><div>In this study, a new versatile fluorescent probe, <strong>YH</strong> (N, N-((1E, 1′E)-((phenylazanediyl)bis(4, 1-phenylene))bis(methanylylidene))di(picolinohydrazide)), was created and synthesized. <strong>YH</strong> demonstrated the capability to continuously detect Cu<sup>2+</sup> and PO<sub>4</sub><sup>3−</sup> in EtOH/HEPES solutions (95/5, V/V, HEPES = 10 mmol, pH = 7.4). Additionally, <strong>YH</strong> could function as a ratiometric fluorescent probe for identifying Zn<sup>2+</sup>. The interaction mechanisms among <strong>YH</strong> and Cu<sup>2+</sup> as well as Zn<sup>2+</sup> were elucidated through <sup>1</sup>H NMR titration, mass spectrometry, and FT-IR spectroscopy. Moreover, <strong>YH</strong> displayed aggregation-induced luminescence in methanol and water. Furthermore, the solid form of <strong>YH</strong> exhibited notable mechanochromism characteristics, transitioning from blue to green after grinding, and this process was reversible by ethanol vapor fumigation. Due to <strong>YH</strong>’s high sensitivity to mechanical stimuli, a starch @ <strong>YH</strong> composite was successfully developed for detecting latent fingerprints. Meanwhile, <strong>YH</strong> was utilized for detecting Cu<sup>2+</sup> and Zn<sup>2+</sup> in environmental water samples and was effectively employed with test papers for ion detection, demonstrating broad application prospect.</div></div>","PeriodicalId":433,"journal":{"name":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","volume":"333 ","pages":"Article 125915"},"PeriodicalIF":4.3,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445313","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号