Fabrication of Non-woven Fabric-Based SERS Substrate for Direct Detection of Pesticide Residues in Fruits

Modified paper-based substrates fabricated via electrostatic attraction of gold nanospheres for non-destructive detection of pesticides based on surface-enhanced Raman spectroscopy

BACKGROUND

Flexible surface-enhanced Raman spectroscopy (SERS) substrates such as paper-based substrates show great potential for rapid detection of residual chemicals on food surfaces. However, controlling the density and distribution of metallic nanoparticles adsorbed on the paper is still challenging.

RESULTS

The amount of gold (Au) nanospheres (51 ± 4 nm) attached on the filter paper modified with 3-aminopropyltriethoxysilane (APTES) was tunable, increasing as the level of APTES (2.5-15.0 g kg-1 ) applied for paper modification increased. Moreover, the Au nanospheres were relative evenly distributed on the filter paper modified with 2.5-10.0 g kg-1 of APTES, which resulted in excellent intra- and inter-reproducibility of SERS signals for pesticides including thiram, diquat dibromide, and paraquat dichloride (relative standard deviation = 2.2-10.1%). The modified paper-based substrate could be used to detect as low as 0.05-0.2 mg L-1 of pesticides in standard solutions, and as low as 5-20 ng cm-2 of residual pesticides on apple skins with minimum sample pretreatment.

CONCLUSION

This paper-based substrate with tunable feature for the density and distribution of nanoparticles is applicable for rapid SERS detection of residual pesticides in fruits and vegetables. © 2023 Society of Chemical Industry.

Silver nanostar films for surface-enhanced Raman spectroscopy (SERS) of the pesticide imidacloprid

Strategies for synthetic control of anisotropic metal nanostructures have grown in recent years in part due to their great potential for application as surface-enhanced Raman scattering (SERS) sensing substrates. It has been shown that SERS using silver substrates is a powerful tool for identification and qualification of trace chemical analysis on the basis of their unique molecular vibrations. In this work, we synthesized star-shaped silver nanostructures and fabricated SERS substrates to use the SERS enhancement of the Raman signal to detect neonicotinoid pesticides. These silver nanostar substrates were prepared by assembling the nanostar particles on a glass substrate surface using a self-assembly technique with various layers of silver nanostars film. The silver nanostar distribution on the solid substrate surface was found to have good reproducibility, reusability and were a stable SERS substrate giving SERS enhancements for pesticide detection at concentrations as low as 10⁻⁶ mg/ml. The distribution of these silver nanostars on the surface allowed excellent reproducibility of the detection with a low relative standard derivation (RSD) of SERS intensity of 8%. This work potentially builds a platform for an ultrasensitive detector where samples can be probed with little to no pre-processing and a range of pollutants can be detected at very low levels.

Fabrication and evaluation of chitosan modified filter paper for chlorpyrifos detection in wheat by surface-enhanced Raman spectroscopy

BACKGROUND

Chlorpyrifos is a commonly used organophosphorus pesticide in agriculture. However, its neurotoxicity poses a huge threat to human health. In the present study, a chitosan-modified filter paper-based surface enhanced Raman scattering active substrate (Ch/AgNPs/paper) was fabricated and used to detect trace amounts of chlorpyrifos in 120 treated wheat samples.

RESULTS

Results showed that the Ch/AgNPs/paper substrate could be used to enhance the chlorpyrifos spectral fingerprint only up to a concentration of 0.000558 mg L^-1 . Following Raman spectra acquisition, three pre-processing methods, including Savitzky-Golay (Savitsky-Golay filter with a second order polynomial) smoothing with first derivative and second derivative and normalization, were used to reduce baseline variation and increase resolutions of spectral peak features of the original spectra dataset. Then, prediction models based on partial least squares were established for detecting chlorpyrifos pesticide residue in wheat. The partial least squares model with normalization yielded optimal result, with a correlation coefficient of 0.9764, root mean square error of prediction of 1.22 mg L^-1 in the prediction, and relative analysis deviation of 4.12. Five unknown samples were prepared to verify the accuracy of the prediction model. The predicted recoveries were calculated to be between 97.25% and 119.38% with an absolute t value of 0.598. The value of a t-test shows that the prediction model is accurate and reliable.

CONCLUSION

The present study demonstrates that the proposed method can achieve rapid detection of chlorpyrifos in wheat. © 2022 Society of Chemical Industry.

A SERS pH sensor for highly alkaline conditions and its application for pH sensing in aerosol droplets

Surface-Enhanced Raman Scattering (SERS) has been widely used in pH sensing. However, SERS sensors capable of stably analysing pH under highly alkaline conditions are still scarce. In this work, a SERS pH sensor employing Alizarin Yellow R as the molecular probe was carefully developed for strong alkaline solutions. The results showed that the probe presented excellent sensing performance in the pH range of 10.04-14.04, including desirable stability and reversibility. Raman band assignments of the probe molecules with the protonated and deprotonated forms were calculated using Gaussian 09. To demonstrate the application, we measured the centroid pH of the phosphate buffer (PB) droplet and compared it to the value obtained with 4-mercaptobenzoic acid (4-MBA) as a probe.

Advances in Optical Sensors for Persistent Organic Pollutant Environmental Monitoring

Optical chemical sensors are widely applied in many fields of modern analytical practice, due to their simplicity in preparation and signal acquisition, low costs, and fast response time. Moreover, the construction of most modern optical sensors requires neither wire connections with the detector nor sophisticated and energy-consuming hardware, enabling wireless sensor development for a fast, in-field and online analysis. In this review, the last five years of progress (from 2017 to 2021) in the field of optical chemical sensors development for persistent organic pollutants (POPs) is provided. The operating mechanisms, the transduction principles and the types of sensing materials employed in single selective optical sensors and in multisensory systems are reviewed. The selected examples of optical sensors applications are reported to demonstrate the benefits and drawbacks of optical chemical sensor use for POPs assessment.

A wearable screen-printed SERS array sensor on fire-retardant fibre gloves for on-site environmental emergency monitoring

Glove-based wearable sensors can offer the potential ability to a fast and on-site environmental threat assessment, which is crucial for timely and informed incident management. In this study, an on-demand surface-enhanced Raman scattering (SERS) array sensor has been patterned on fire-retardant fibre gloves via the screen-printing technique in large batches. The screen-printed ink contains one-pot synthesized silver nanoparticle and molybdenum disulfide nanocomposite (Ag/MoS₂), and polyanionic cellulose (PAC) as a new adhesive agent. Rhodamine 6G (R6G) was employed as an initial probe molecule to systematically evaluate the performance of the resulting sensor. The results suggest that the fabricated fire-retardant screen-printed SERS array sensor displays high reproducibility and stability at 250 °C, with the lower detection limit of 10^-13 M for R6G. The spot-to-spot SERS signals show that the intensity variation was less than 10%. Besides, the SERS signals can be maintained over 7 weeks. Further investigation was then successfully carried out to detect polycyclic aromatic hydrocarbons (PAHs), which are commonly used as flammable chemicals. In our perception, this wearable fire-retardant screen-printed SERS array sensor would be an ideal candidate for practical on-site environmental emergency monitoring due to its fire-retardant capability and timely measurement on a portable carrier.

Strategies for SERS Detection of Organochlorine Pesticides

Organochlorine pesticides (OCPs) embody highly lipophilic hazardous chemicals that are being phased out globally. Due to their persistent nature, they are still contaminating the environment, being classified as persistent organic pollutants (POPs). They bioaccumulate through bioconcentration and biomagnification, leading to elevated concentrations at higher trophic levels. Studies show that human long-term exposure to OCPs is correlated with a large panel of common chronic diseases. Due to toxicity concerns, most OCPs are listed as persistent organic pollutants (POPs). Conventionally, separation techniques such as gas chromatography are used to analyze OCPs (e.g., gas chromatography coupled with mass spectrometry (GC/MS)) or electron capture detection (GC/ECD). These are accurate, but expensive and time-consuming methods, which can only be performed in centralized lab environments after extensive pretreatment of the collected samples. Thus, researchers are continuously fueling the need to pursue new faster and less expensive alternatives for their detection and quantification that can be used in the field, possibly in miniaturized lab-on-a-chip systems. In this context, surface enhanced Raman spectroscopy (SERS) represents an exceptional analytical tool for the trace detection of pollutants, offering molecular fingerprint-type data and high sensitivity. For maximum signal amplification, two conditions are imposed: an efficient substrate and a high affinity toward the analyte. Unfortunately, due to the highly hydrophobic nature of these pollutants (OCPs,) they usually have a low affinity toward SERS substrates, increasing the challenge in their SERS detection. In order to overcome this limitation and take advantage of on-site Raman analysis of pollutants, researchers are devising ingenious strategies that are synthetically discussed in this review paper. Aiming to maximize the weak Raman signal of organochlorine pesticides, current practices of increasing the substrate's performance, along with efforts in improving the selectivity by SERS substrate functionalization meant to adsorb the OCPs in close proximity (via covalent, electrostatic or hydrophobic bonds), are both discussed. Moreover, the prospects of multiplex analysis are also approached. Finally, other perspectives for capturing such hydrophobic molecules (MIPs-molecularly imprinted polymers, immunoassays) and SERS coupled techniques (microfluidics-SERS, electrochemistry-SERS) to overcome some of the restraints are presented.

Detection of Aflatoxin B1 Based on a Porous Anodized Aluminum Membrane Combined with Surface-Enhanced Raman Scattering Spectroscopy

An Aflatoxin B₁ (AFB₁) biosensor was fabricated via an Ag nanoparticles assembly on the surface of a porous anodized aluminum (PAA) membrane. First, the Raman reporter 4-Aminothiophenol (4-ATP) and DNA (partially complementary to AFB₁ aptamer) were attached to the surface of Ag nanoparticles (AgNPs) by chemical bonding to form a 4-ATP-AgNPs-DNA complex. Similarly, the surface of a PAA membrane was functionalized with an AFB₁ aptamer. Then, the PAA surface was functionalized with 4-ATP-AgNPs-DNA through base complementary pairing to form AgNPs-PAA sensor with a strong Raman signal. When AFB₁ was added, AgNPs would be detached from the PAA surface because of the specific binding between AFB₁ and the aptamer, resulting in a reduction in Raman signals. The detection limit of the proposed biosensor is 0.009 ng/mL in actual walnut and the linear range is 0.01-10 ng/mL. The sensor has good selectivity and repeatability; it can be applied to the rapid qualitative and quantitative detection of AFB₁.

Fabrication of sensitive silver-decorated cotton swabs for SERS quantitative detection of mixed pesticide residues in bitter gourds

This study developed a simple, efficient and environmentally friendly fabrication method for surface-enhanced Raman spectroscopy (SERS) wipers for the rapid detection of individual and mixed pesticide residues in actual samples.

A review of developments and applications of thin-film microextraction coupled to surface-enhanced Raman scattering

Surface-enhanced Raman scattering (SERS) greatly expands the applications of Raman spectroscopy and is a promising technique for food safety, environmental analysis, and public safety. Thin-film microextraction (TFME) provides an efficient sample preparation method for SERS to improve its selectivity and detection efficiency. This review comprehensively describes the development and applications of SERS and TFME, including the history, mechanisim, and active substrate of SERS and the theory, device, forms, and practical applications of TFME. The applications of TFME-SERS in food safety and environment monitoring are discussed, which could improve their advantages. TFME extracts and enriches the target analytes to eliminate the interfering substance, providing a facial way for SERS to analyze the target analytes in complex matrices. The development of TFME-SERS technology not only expands the application range of TFME, but greatly improves the anti-interference ability and detection sensitivity of SERS. Thus, the established methods are fast, convenient, and highly sensitive. This technology is potential to be applied in the on-site and real-time detection.

Silver-based surface enhanced Raman spectroscopy devices for detection of organophosphorus pesticides traces

The detection of traces of substances by surface-sensitive techniques such as surface enhanced Raman spectroscopy (SERS) explores the interaction of adsorbed molecules on plasmonic surfaces to improve the limit of detection of analytes. This article is an overview about recent development in SERS substrates applied in the detection of organophosphorus pesticides on plasmonic surfaces (arrays of metal nanoparticles). The morphology, roughness, chemical functionalization degree, and aggregation level of plasmonic centers are some of the critical parameters to be controlled in the optimization of SERS signal from specific analytes.