Large-scale gold nanoparticle superlattice and its SERS properties for the quantitative detection of toxic carbaryl

Nanoscale ◽  
2013 ◽  
Vol 5 (12) ◽  
pp. 5274 ◽  
Author(s):  
Lina Wu ◽  
Zhijiang Wang ◽  
Baozhong Shen
Keyword(s):  
Gold Nanoparticle ◽  
Large Scale ◽  
Quantitative Detection

scholarly journals Sensitive and Reproducible Gold SERS Sensor Based on Interference Lithography and Electrophoretic Deposition

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4076 ◽  
Author(s):  
June Hwang ◽  
Minyang Yang
Keyword(s):  
Gold Nanoparticle ◽  
Electrophoretic Deposition ◽  
Large Scale ◽  
Surface Enhanced Raman Spectroscopy ◽  
Localized Surface Plasmon ◽  
Interference Lithography ◽  
Metal Nanostructures ◽  
Nanoparticle Array ◽  
Laser Ablation In Liquid ◽  
Label Free Detection

Surface-enhanced Raman spectroscopy (SERS) is a promising analytical tool due to its label-free detection ability and superior sensitivity, which enable the detection of single molecules. Since its sensitivity is highly dependent on localized surface plasmon resonance, various methods have been applied for electric field-enhanced metal nanostructures. Despite the intensive research on practical applications of SERS, fabricating a sensitive and reproducible SERS sensor using a simple and low-cost process remains a challenge. Here, we report a simple strategy to produce a large-scale gold nanoparticle array based on laser interference lithography and the electrophoretic deposition of gold nanoparticles, generated through a pulsed laser ablation in liquid process. The fabricated gold nanoparticle array produced a sensitive, reproducible SERS signal, which allowed Rhodamine 6G to be detected at a concentration as low as 10−8 M, with an enhancement factor of 1.25 × 105. This advantageous fabrication strategy is expected to enable practical SERS applications.

Detection of mycobacterial CFP-10 (Rv3874) protein in tuberculosis patients by gold nanoparticle-based real-time immuno-PCR

2020 ◽  
Vol 15 (8) ◽  
pp. 601-612
Author(s):  
Bhawna Dahiya ◽  
Suman Sharma ◽  
Anish Khan ◽  
Ekta Kamra ◽  
Preeti Mor ◽  
...  
Keyword(s):  
Real Time ◽  
Gold Nanoparticle ◽  
Diagnostic Test ◽  
Clinical Samples ◽  
Quantitative Detection ◽  
Detection Range ◽  
Tuberculosis Patients ◽  
Bodily Fluids ◽  
Diagnostic Potential ◽  
Progression Of Disease

Aim: Timely and reliable diagnostic test for tuberculosis (TB) is immediately required. Attempts were made to improve the technology and diagnostic potential of real-time immuno-PCR (RT-I-PCR). Methods: We designed gold nanoparticle (GNP)-based RT-I-PCR (GNP-RT-I-PCR) assay for the detection of Mycobacterium tuberculosis CFP-10 (Rv3874) protein in clinical samples of TB patients. Results: A wide quantitative detection range of CFP-10 was found to be 0.5–5 × 104 pg/ml in bodily fluids of TB patients, which can evaluate the progression of disease. Moreover, sensitivities of 83.7 and 76.2% were observed in pulmonary (n = 49) and extrapulmonary TB (n = 42) patients, respectively, with specificities of 93.5–93.8% (n = 63). Conclusion: Conjugation of detection antibodies and oligonucleotides to functionalized GNPs of GNP-RT-I-PCR is relatively easier, compared with streptavidin-biotin/succinimidyl-4-( N-maleimidomethyl) cyclohexane-1-carboxylate system employed in RT-I-PCR. Our assay also showed better diagnostic performance than RT-I-PCR, which may provide a viable platform for the development of an efficient TB diagnostic test.

scholarly journals Enhanced Tunability of Gold Nanoparticle Size, Spacing, and Shape for Large-Scale Plasmonic Arrays

2019 ◽  
Vol 2 (7) ◽  
pp. 4395-4401 ◽  
Author(s):  
Nathan J. Ray ◽  
Jae H. Yoo ◽  
Joseph T. McKeown ◽  
Selim Elhadj ◽  
Salmaan H. Baxamusa ◽  
...  
Keyword(s):  
Gold Nanoparticle ◽  
Large Scale ◽  
Nanoparticle Size

scholarly journals Comparison of Nanosized Markers in Lateral Flow Immunoassay of Antibiotic Lincomycin

Proceedings ◽  
2020 ◽  
Vol 60 (1) ◽  
pp. 41
Author(s):  
Olga D. Hendrickson ◽  
Kseniya V. Serebrennikova ◽  
Elena A. Zvereva ◽  
Demid S. Popravko ◽  
Anatoly V. Zherdev ◽  
...  
Keyword(s):  
Quantum Dot ◽  
Gold Nanoparticle ◽  
Limit Of Detection ◽  
Cost Effective ◽  
Lateral Flow ◽  
Lateral Flow Immunoassay ◽  
Quantitative Detection ◽  
Site Testing ◽  
Limits Of Detection ◽  
Chemical Contaminants

Improving the sensitivity of the competitive lateral flow immunoassay (LFIA) is important, given the increasing demands for the monitoring of chemical contaminants in food. The choice of nanosized marker is an essential task for improving the LFIA sensitivity. In this study, a CdSe/ZnS quantum dot (QD)-based LFIA combined with a portable reader was developed for rapid and quantitative detection of an antibiotic lincomycin (LIN). The performance of the proposed fluorescence LFIA was compared to the conventional gold nanoparticle (AuNP)-based LFIA realized with the same immunoreagents. The visual cutoff values were 10 ng/mL for AuNP-based LFIA and 20 ng/mL for QD-based LFIA. Furthermore, the instrumental limits of detection have been shown to be comparable for both nanosized markers and amounted to 0.4 ng/mL for AuNPs and 0.2 ng/mL for QDs, respectively. According to the results obtained, both LFIAs may be used for rapid, cost-effective, on-site testing of antibiotics, in particular LIN. However, the QD-based LFIA exhibits lowest limit of detection with the least immunoreagent consumption, which makes it economically beneficial.

scholarly journals Large-Scale Oil Palm Tree Detection from High-Resolution Satellite Images Using Two-Stage Convolutional Neural Networks

2018 ◽  
Vol 11 (1) ◽  
pp. 11 ◽  
Author(s):  
Weijia Li ◽  
Runmin Dong ◽  
Haohuan Fu ◽  
and Le Yu
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Oil Palm ◽  
Large Scale ◽  
Satellite Images ◽  
Quantitative Detection ◽  
Support Vector ◽  
Palm Tree ◽  
Two Stage ◽  
High Resolution Satellite Images

Being an important economic crop that contributes 35% of the total consumption of vegetable oil, remote sensing-based quantitative detection of oil palm trees has long been a key research direction for both agriculture and environmental purposes. While existing methods already demonstrate satisfactory effectiveness for small regions, performing the detection for a large region with satisfactory accuracy is still challenging. In this study, we proposed a two-stage convolutional neural network (TS-CNN)-based oil palm detection method using high-resolution satellite images (i.e. Quickbird) in a large-scale study area of Malaysia. The TS-CNN consists of one CNN for land cover classification and one CNN for object classification. The two CNNs were trained and optimized independently based on 20,000 samples collected through human interpretation. For the large-scale oil palm detection for an area of 55 km2, we proposed an effective workflow that consists of an overlapping partitioning method for large-scale image division, a multi-scale sliding window method for oil palm coordinate prediction, and a minimum distance filter method for post-processing. Our proposed approach achieves a much higher average F1-score of 94.99% in our study area compared with existing oil palm detection methods (87.95%, 81.80%, 80.61%, and 78.35% for single-stage CNN, Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN), respectively), and much fewer confusions with other vegetation and buildings in the whole image detection results.

Gold Nanoparticle Aggregate Morphology with Controllable Interparticle Spacing Prepared by a Polyelectrolyte Network Template

2008 ◽  
Vol 61 (1) ◽  
pp. 1 ◽  
Author(s):  
Feng Zhao ◽  
Jing Kun Xun ◽  
Shu Feng Liu
Keyword(s):  
Gold Nanoparticle ◽  
Self Assembly ◽  
Large Scale ◽  
Polymer Network ◽  
Resonance Wavelength ◽  
Interparticle Spacing ◽  
Excitation Wavelength ◽  
Mica Surface ◽  
Simple Method ◽  
Nanostructured Gold

Gold nanoparticle self-assembly behaviour on a mica surface was investigated. A large-scale modified partially hydrated polyacrylamide network on a mica surface was successfully fabricated with a simple method. Gold nanoparticles were self-assembled onto a two-dimensional polymer network template by electrostatic interaction, and an interesting nanostructured gold morphology with controllable interparticle spacing was formed on the mica surface. By adjusting the gold aqueous concentrations, the particle distance could be optimized to approach strongest coupling between adjacent particles and match the plasmon resonance wavelength to the laser excitation wavelength. Thus, the spacing between nanoparticles could be controlled for tunable surface-enhanced Raman scattering substrates for optimal signal amplification.

scholarly journals Colorimetric detection of organophosphates with cysteamine capped gold nanoparticle sensors

2020 ◽  
Author(s):  
Muhammad Musaddiq Shah ◽  
Wen Ren ◽  
Bashir Ahmad ◽  
Joseph Irudayaraj
Keyword(s):  
Gold Nanoparticle ◽  
Limit Of Detection ◽  
Colorimetric Detection ◽  
High Sensitivity ◽  
Food Samples ◽  
Quantitative Detection ◽  
Enzyme Mimics ◽  
Nanoparticle Probes ◽  
Site Monitoring ◽  
20 Nm

Nanozyme biosensors have the potential to provide high sensitivity, multiple functionality, and tunable activity. A facile colorimetric biosensor for the detection of organophosphates (OPs) using cysteamine capped gold nanoparticle probes (C-AuNPs) as enzyme mimics is proposed. Parathion ethyl (PE) a class of OPs is a potent insecticide that functions by inhibiting the acetylcholinesterase (AChE) in the nervous system of insects. The inhibition kinetics of AChE using PE enables the development of a PE sensor. C-AuNPs possess the ability to catalyze the oxidization of 3, 3’, 5, 5’-tetramethylbenzidine (TMB) to a blue-colored product without peroxidase. The detection of PE was monitored by the inability of AChE to generate choline. Choline causes the aggregation of C-AuNPs and the aggregated C-AuNPs has decreased ability to catalyze the oxidization of TMB. A calibration was developed in the 40-320 nM range for the quantitative detection of PE. The limit of detection observed was 20 nM and the method had excellent specificity. The proposed sensor provides an excellent platform for on-site monitoring of PE in environmental and food samples with high sensitivity and greater selectivity.

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