3D Hotspots Research Articles

Photothermal modulated hotspot for accurate and sensitive SERS detection of pesticides in complicated media

Designing smart surface-enhanced Raman scattering (SERS) nanosensors with superior sensibility, stabilities and repeatability is a challenging and intriguing goal in chemical measurement. Herein, we develop a photothermal modulated SERS platform (PM-SERS) for sensitive and stable analysis of targets by exploiting a stimuli-responsive gold nanoparticles (GNPs) decorated polyvinyl alcohol hydrogel (GPH). Importantly, the proposed GPH facilitates exactly controlling 3D hot-spot regions by modulating surrounding temperature and humidity. The adjustable GPH could not only act as a stable matrix for installing of high-density GNPs, but also as a sorption domain for preconcentration of targeted analyte in hot-spots sites, thus permitting simultaneously modulating 3D nanostructures and seizing targeted analytes in plasmonic regions. Crucially, because of the reversible nanostructures and nanoplasmonic features, GPH can eradicate adsorbates after being exposed to bromide solutions, thereby allowing renewable and reliable on-site SERS detection of complex media. The GPH-based PM-SERS platform exhibits excellent sensitivities and reproducibility for on-demand detection of multiplexed pesticide over a wide linear concentration range (2 × 10-6 to 103 μM), with detection limits as low as hundreds of fM. The GPH-based analytical platform provides tremendous potentials for credible quantification of complicated matrices and on-line process screening.

Machine learning-aided quantitative detection of two mixed antibiotics in a narrow concentration range based on oxygen incorporation-induced 3D SERS substrates

Amoxicillin (AMO) and ciprofloxacin (CIP) as frequently-used antibiotics are often simultaneously taken for anti-infection to protect pig and poultry production, while their effective therapeutic window is narrow. How to quantitatively detect the two antibiotics mixed in a narrow concentration range is essential to ensure their treatment efficacy and food safety. In this study, quantitative detection of AMO and CIP mixed in animal flesh in one order of magnitude concentration range was performed using a triple SERS signal amplification sensor combined with machine learning. The SERS sensor based on oxygen incorporation (Oi)-induced 3D NiO nanoflowers (NFs) coated with Ag nanoparticles included 3D hot spot effect from strong internal electromagnetic couple in NiO NFs, the Oi effect of NiO and synergistic charge transfer effect of between NiO and Ag. Based on triple enhancement effects, sensitive SERS detection of AMO and CIP was made with the limits of detection of 1 nM and 100 nM. Through the use of machine learning techniques like principal component analysis and partial least square regression, qualitative and quantitative detection of AMO and CIP in their mixture from 1.33 μM to 8.69 μM was successfully achieved, where the average proportion of absolute prediction error (p ≤ 0.15) for concentration was 98.06 %.

3D hot spot construction on the hydrophobic interface with SERS tags for quantitative detection of pesticide residues on food surface

The overuse of pesticides results in excessive pesticide residues, posing a potential threat to human health. Herein, this work proposes a SERS substrate for the quantitative analysis of pesticide residues on food surfaces. Au cores are assembled on PS microspheres, followed by the modification of Raman internal standards (1,4-BDT) on the gold core surface and the growth of the Au shell. After incubating the analytes with PS@Au@1,4-BDT@Au particles, the mixture is dropped on the hydrophobic gold film for drying before detection. The SERS substrates exhibited high sensitivity and stability, with a detection limit of 10−12 M and an RSD of less than 7 %. Combined with a portable Raman spectrometer, the SERS detection of pesticide residues on three kinds of food surfaces is carried out, with a sensitivity of 10−11 M, meeting the US MRLs regulations. Therefore, this strategy may possess significant potential for future food safety.

Bio‐inspired 3D Sub‐Microstructures Coupling of Au Nanoparticles for SERS Detection of Trace Fentanyl

Abstract3D surface‐enhanced Raman scattering (SERS) platforms with multi‐dimensional hotspots and better tolerance to laser misfocus show great potential for the rapid detection of trace fentanyl. However, the complex fabrication process of 3D fine structures limits the wide‐ranging application of the SERS technique. Herein, a 3D SERS‐active platform is fabricated utilizing a scalable and cost‐effective strategy that involves the electroless deposition of dense Au nanoparticles on natural butterfly wing scales (b‐wings@Au). The resultant b‐wings@Au proves to be sensitive and reliable, with a lower limit of detection of 4× 10−12 m and an enhancement factor (EFexp) of 1.74 × 108 for fentanyl. Furthermore, it exhibits excellent reproducibility, as evidenced by a relative standard deviation of less than 5%, and also demonstrates outstanding stability. The obtained high EFexp is due to the combined effects of the electromagnetic mechanism, involving the enhanced electromagnetic field generated by 3D periodic hotspots, and the chemical mechanism, involving the charge transfer from fentanyl to Au surface. Additionally, the as‐prepared 3D substrate realizes the trace detection of nine fentanyl analogs. This study provides new ideas for the controllable construction of sensitive SERS platforms for drug detection, ultimately advancing the fields of 3D substrates in booming SERS‐based technologies.

3D hotspot engineering and analytes strategy enabled ultrasensitive SERS platform for biosensing of depression biomarker

Nowadays, the diagnose of depression mainly relies on clinical examination while impossible to accurately evaluate the occurrence of depression. Chemical approaches are captivating to analyze stress biomarkers for feedbacking body's endocrine response to stress stimuli. However, it remains challenging in exploring accurate, reliable and sensitive approaches. Herein, we rationally design a newly SERS platform with integrated hotspots engineering and analyte strategy to achieve highly sensitive analysis for estrogen, a typical depression biomarker in adolescent female. On the one hand, the 3D micro/nano plasmonic substrate containing Au–Ag Alloy Nanourchins (AAA-NUs) and arrays-based monolayer films of Au nanoparticles (Au NSs) was constructed to achieve high density and availability of hotspots. On the other hand, the analyte strategy was designed via rapid azotizing reaction to further enhance the scattering cross-section of estrogen in the form of azido compounds. With the synergism of them, the proposed SERS platform displayed high sensitivity for estrogen with a limit of detection down to 10−11 mg/mL. More importantly, the blood estrogen levels of depressed patients were evaluated via the proposed SERS platform and presented high consistence with clinical diagnostic results. This integrated SERS platform paves the way for universal and ultrasensitive biosensing and possess great potential for applying in multi-target detection and disease prediction.

Three-dimensional hotspot structures constructed from nanoporous gold with a V-cavity and gold nanoparticles for surface-enhanced Raman scattering.

The intensity and sensitivity of surface-enhanced Raman scattering (SERS) spectra are highly dependent on the consistency and homogeneity of the nanomaterials. In this study, we developed a large-area three-dimensional (3D) hotspot substrate with good homogeneity and reproducibility in SERS signals. The substrate is based on the synergistic structures of nanoporous gold (NPG) and gold nanoparticles (AuNPs). NPG was combined with a periodic V-shaped nanocavity array to create nanoporous gold with a V-cavity (NPGVC) array featuring uniform hotspots. A nanoporous gold V-shaped resonant cavity (NPGVRC) structure was developed by incorporating AuNPs into the NPGVC array. The coupling action between the AuNPs and NPGVC resulted in a SERS-enhanced electromagnetic field with 3D hotspot distribution. The strategic incorporation of NPG and V-cavity array significantly expanded the surface area available for analyte adsorption and interaction with AuNPs. Using rhodamine 6G (R6G) and malachite green (MG) as probe molecules, the SERS performance was investigated, and the NPGVRC substrate not only showed excellent enhancement with the limit of detection as low as 10-11 M, but also presented good homogeneity. NPGVRC was then used for biological detection of the influenza A virus, where we acquired and examined the characteristic SERS spectra of two spike proteins. It is demonstrated that there is significant potential for our proposed SERS platform to be used in biosensors.

Ag supraparticles with 3D hot spots to actively capture molecules for sensitive detection by surface enhanced Raman spectroscopy.

To achieve highly sensitive detection using surface-enhanced Raman spectroscopy (SERS), it is imperative to fabricate a substrate with a high density of hot spots and facilitate the entry of target molecules into these hot spot regions. However, steric hindrance arising from the presence of surfactants and ligands on the SERS substrate may impede the access of target molecules to the hot spots. Here, we fabricate non-close-packed three-dimensional (3D) supraparticles with high-density hot spots to actively capture molecules. The formation of 3D supraparticles is attributed to the minimization of free energy during the gradual contraction of the droplet. The numerous capillaries present in non-close-packed supraparticles induce the movement of target molecules into the hot spot region through capillary force along with the solution. The results demonstrate that the SERS enhancement effect of 3D supraparticles is at least one order of magnitude higher than that of multi-layered nanoparticle structures formed under natural drying conditions. In addition, the SERS performance of 3D supraparticles is evaluated with diverse target molecules, including antimicrobial agents and drugs. Hence, this work provides a new idea for the preparation of non-close-packed substrates for SERS sensitive detection.

Flexible nanohybrid substrates utilizing gold nanocubes/nano mica platelets with 3D lightning-rod effect for highly efficient bacterial biosensors based on surface-enhanced Raman scattering.

In this study, gold nanocubes (AuNCs) were quickly synthesized using the seed-mediated growth method and reduced onto the surface of two-dimensional (2D) delaminated nano mica platelets (NMPs), enabling the development of AuNCs/NMPs nanohybrids with a 3D lightning-rod effect. First, the growth-solution amount can be changed to easily adjust the AuNCs average-particle size within a range of 30-70 nm. The use of the cationic surfactant cetyltrimethylammonium chloride as a protective agent allowed the surface of AuNCs and nanohybrids to be positively charged. Positively charged nanohybrid surfaces presented a good adsorption effect for detecting molecules with negative charges on the surface. Additionally, the NMP surfaces were rich in ionic charges and provided a large specific surface area for stabilizing the growth of AuNCs. Delaminated AuNCs/NMPs nanohybrids can generate a 3D hotspot effect through self-assembly to enhance the Raman signal. Surface-enhanced Raman scattering (SERS) is highly sensitive in detecting adenine biomolecules. Its limit of detection (LOD) and Raman enhancement factor reached 10-9 M and 3.6 × 108, respectively. Excellent reproducibility was obtained owing to the relatively regular arrangement of AuNC particles, and the relative standard deviation (RSD) was 10.7%. Finally, the surface of NMPs was modified by adding the hydrophilic poly(oxyethylene)-diamine (POE2000) and amphiphilic PIB-POE-PIB copolymer at different weight ratios. The adjustment of the surface hydrophilicity and hydrophobicity of AuNCs/NMPs nanohybrids led to better adsorption and selectivity for bacteria. AuNCs/POE/NMPs and AuNCs/PIB-POE-PIB/NMPs were further applied to the SERS detection of hydrophilic Staphylococcus aureus and hydrophobic Escherichia coli, respectively. The SERS-detection results suggest that the LOD of hydrophilic Staphylococcus aureus and hydrophobic Escherichia coli reached 92 CFU mL-1 and 1.6 × 102 CFU mL-1, respectively. The AuNCs/POE/NMPs and AuNCs/PIB-POE-PIB/NMPs nanohybrids had different hydrophilic-hydrophobic affinities, which greatly improved the selectivity and sensitivity for detecting bacteria with different hydrophilicity and hydrophobicity. Therefore, fast, highly selective, and highly sensitive SERS biological-detection results were obtained.

3D plasmonic hotspot engineering toward ultrasensitive and rapid EC-SERS recognition of plasticizers

Public attention to the health and environmental risks from plasticizer exposure in daily life has led to legal restrictions on the use of plasticizers in products. However, the lack of rapid, sensitive, and reliable analytic methods hinders the effective screening of toxic materials. In the present work, we propose a novel electrochemical surface-enhanced Raman spectroscopy (EC-SERS) technique for the detection of plasticizers such as phthalate esters (PAEs) and bisphenol A. The interior hotspots were realized through the EC deposition onto metal nanopillar (ECOMP) platforms in the presence of analytes within 2.5 min. The tiny molecules surrounded by Au produced sufficient amplification of SERS signals, leading to sub-parts-per-billion (sub-ppb) sensitivity for all the intended specimens. According to the three standard deviation equation, the limit of detection was determined to be 0.002 ppb. The ECOMP platforms with reproducibility (relative standard deviation of <10 %) and linear proportion (R2 ≥ 0.93) were highly suitable for reliable quantitative investigation. A principal component analysis method recognized their slight differences in spectral features. The variability from the first two components was achieved to be 73 %, which separated individual plasticizer groups distinctly. The plasticizer extracted from an actual polyvinyl chloride sample was successfully detected using the proposed technique. The interaction of PAEs with ethanol and the delocalization of PAEs in ECOMP platforms were also discussed. The results demonstrate the feasibility of plasticizer–ECOMP platforms being widely used for onsite testing in industrial fields such as chemical and drug safety.

Dynamic surface-enhanced Raman spectroscopy and positively charged probes for rapid detection and accurate identification of fungal spores in infected apples via deep learning methods

Fungal infections pose a significant threat to apples; therefore, the detection of fungal spores is imperative for controlling infection spread and ensuring food safety. In this study, dynamic surface-enhanced Raman spectroscopy (D-SERS) and positively charged probes were developed to detect and identify the fungal spores via deep learning methods. Firstly, the gold nanorods were modified with cysteamine to develop the positively charged SERS probes, enhancing the capture of fungal spores by promoting interactions with the negatively charged cell wall. Then, the probes and D-SERS were combined to measure the SERS spectra of fungal spores, and the optimal spectral signals were obtained under the metastable state of D-SERS from wet to dry. This was due to capillary forces inducing nanoparticles to form a large number of 3D hot spots, resulting in significant enhancement. Spores of Aspergillus flavus, Rhizopus stolonifer, and Botrytis cinerea can be easily detected with excellent SERS signals from infected apples after simple separation through filtration and centrifugation. Furthermore, the best recognition model was developed by ZFNet, a powerful deep learning method, with the accuracies in the training set, validation set, and prediction set of 100%, 99.44%, and 99.44%, respectively. The proposed method provides a simple, rapid, and accurate approach for the detection and identification of fungal infections in apples, and can be extended to other agricultural products.

Convenient self-assembled PDADMAC/PSS/Au@Ag NRs filter paper for swift SERS evaluate of non-systemic pesticides on fruit and vegetable surfaces.

The goal of food safety supervision is to directly identify the pesticide residues on the surface of fruits and vegetables. This study proposed to develop a facile, non-destructive, and sensitive method based on surface-enhanced Raman scattering (SERS) to detect non-systemic pesticides on the surface of fruits and vegetables. The composite material was prepared by loading CTAB guided Au@Ag NRs with positive charge onto filter paper which was modified with PDADMAC(+) and PSS(-) using electrostatic adsorption. Au@Ag NRs with bimetallic synergies were effectively adsorbed in the fiber grid to generate 3D SERS hotspots within a few microns of depth. The results showed that the 3D composite flexible substrate had a high SERS activity, great repeatability, and sensitivity when the method was utilized to detect 4-MBA, methyl-parathion, thiram and chlorpyrifos. Three kinds of non-systemic pesticides on the peel could be detected directly and quickly owing to the arbitrary bending of the substrate, demonstrating the efficiency of the SERS "paste-reading" method. The acquired findings demonstrated that PDADMAC/PSS/Au@Ag NRs composite filter paper had the potential to provide rapid feedback for in-situ analysis of pesticide residues on the surface of fruit and vegetable.

Tailoring of hot spots in plasmonic microgels for dynamic SERS detection of multi-pesticides by suction-release strategy

Tailoring smart surface-enhanced Raman scattering (SERS) substrates with tunable “hot spots” has invoked widely attention due to its unique structures and plasmonic features. Herein, we develop a “suction-release” SERS strategy (SRSS) for dynamic detection of targeted analytes by utilizing a stimulus-responsive three-dimensional (3D) AgNPs-decorated Basil-seeds microgels (ABM). Crucially, this smart ABM enable precisely tailoring 3D hot spots region by regulating the ambient temperature and moisture. The dynamically tunable ABM serves as a stabilized domain for high-density loading of AgNPs, as well as an adsorption matrix for concentration of the analytes in hot spots region, thereby allowing simultaneously regulating 3D structures and capturing target molecules in plasmonic sites. Most importantly, due to the reversible structures and plasmonic properties, the ABM can clean themselves when immersed in iodide solution, thus achieving recyclable and credible SERS analysis of solid samples. The ABM-based SRSS displays superior sensitivity and uniformity for in-field analysis of multiple pesticides over a large range of 2 × 10-6-104 μM. The proposed sensing strategy offers great potential for reliable quantitative SERS detection of complexed media and in-situ process analysis.

Umbrella-frame silicon nanorod arrays decorated with Au nanoparticles as recyclable SERS substrates.

Surface-enhanced Raman scattering (SERS) is a powerful technique for detection and identification of trace amounts of molecules with high specificity. A variety of two- and three-dimensional (3D) SERS substrates have been developed. Among these SERS substrates, to further develop new morphology of 3D SERS-active substrate with robust SERS functionality is still desired and necessary. In this paper, what we believe to be a novel and effective SERS-active substrate based on large-scale 3D Si hierarchical nanoarrays in conjunction with homogeneous Au nanoparticles (AuNPs) was proposed. Its building block shaped like the umbrella-frame structure was fabricated by a simple and cost-effective top-down nanofabrication method. Such umbrella-frame structure achieved excellent SERS performance with high sensitivity and spatial uniformity. For R6G molecules, the detection limit can be as low as 10-14 M, with an enhancement factor of up to 107. The relative standard deviation can reach about 11% above 30 positions across an area of 100×100 μm2. This is mainly attributed to much more active-sites provided by the umbrella-frame structure for adsorption of target molecules and AuNPs, and sufficient 3D hotspots generated by the coupling between the SiNRs guided mode and AuNPs localized surface plasmon resonance (LSPR), as well as that between AuNPs LSPR. Especially by introducing the umbrella-ribs SiNRs and AuNPs, the light field can be greatly confined to the structure surface, creating strongly enhanced and even zero-gap fields in 3D space. Moreover, the proposed SERS-active substrate can be erased and reused multiple times by plasma cleaning and exhibits typically excellent recyclability and stability for robust SERS activity. The experimental results demonstrate the proposed substrate may serve as a promising SERS platform for trace detection of chemical and biological molecules.

Optical response of Au films for reproducible Si nano-structuring and its application for efficient micro-drop SERS with portable Raman system

Si nanostructuring by metal assisted chemical etching is highly sensitive to morphology of thin metal film, here we demonstrate use of plasmon driven optical or dielectric response of Au films for predicting nanopore or nanowire Si prior to etching, ensuring the process reproducibility. By controlling growth temperature, it is shown that same mass thickness of Au films can produce either nanopore, nanowire or hybrid (mix of the two) Si nanostructures, useful for various applications. Ag nanoparticles coated nanostructure Si is shown to be efficient surface enhanced Raman spectroscopy (SERS) substrate for dry state measurements with micro-Raman system. In contrast, by exploiting super-hydrophilicity and strong light coupling of nanostructure Si, a novel micro-drop SERS using portable Raman spectrometer is demonstrated as low-cost, reliable and easy field-deployable technique. With very low sample volume about 50 μL of as prepared Au nanoparticles and analyte, it is capable of producing SERS signal in samples containing 120 pg thiram, 240 pg Rh6G, 455 pg malachite green and 48 pg methylene blue. With advantages of micro-drop SERS, mainly high intensity signal with 3D dynamic hot-spots at high laser power, longer shelf-life colloidal gold, reusable substrates with no prior sample preparation, this method is envisaged to be an inexpensive technique for on-site trace detection applications and importantly quick generation of large experimental SERS data-set for machine learning (ML) driven studies. This is demonstrated by principal component analysis with ML classifier for 100% accurate prediction of trace dyes, pesticide and their binary mixtures.

Nanoplasmonic hybrid hotspot in graphene transistor

A field effect transistor based on graphene was introduced to generate a hybrid plasmonic mode. The main reasons to consider graphene in this study are the achievement of high field confinement and the graphene two carrier transport channel near its charge neutrality point. We have observed a nonlinear behavior of the hybrid plasmonic mode near the graphene charge neutrality point because of the existence of the two carrier model. This nonlinear behavior reflects the intrinsic nanoelectronic characteristics of graphene. The proposed nanoelectronic device presents an ultraconfined tunable hybrid hotspot, the mode area of which is ${10}^{5}$ times smaller than the diffraction limited spot area. Moreover, this area is three orders of magnitude smaller than the modal area of the similar metal-based hybrid nanostructure. Such a nanoscale 3D hotspot with plasmonic-photonic character has been reported here. Furthermore, a hybrid structure based on bilayer twisted graphene was numerically investigated which renders ultrahigh confinement and ultralong propagation distance. The proposed nanodevice can be applied to design compact integrated circuits, optical neural networks, and high resolution sensors.

Fabrication of core shell Au@Ag supraparticles with 3D hotspots via evaporation self-assembly for sensitive surface enhanced Raman scattering detection

Three-dimensional (3D) plasmonic nanostructures exhibit excellent surface-enhanced Raman scattering (SERS) performance for detecting trace analytes. Nevertheless, fabrication of 3D plasmonic SERS substrates with non-close packed structures via simple evaporation assembly still remains a challenge. Here, we successfully prepared 3D supraparticles in millimeter scale via a simple evaporation assembly of highly concentrated core-shell Au@Ag nanoparticles (NPs) on hydrophobic surface. The formation of supraparticles could account for hydrophobic condensation effect, the huge numbers of spherical NPs, and unique core shell structure of Au@Ag NPs. Such supraparticle was consisting of more than 104 of Au@Ag NPs where nanogaps among NPs created plenty of 3D “hotspots”. The supraparticles with non-close packed structure is benefit for the diffusion of more targets into the hotspots, leading to enhanced interactions that contribute to a higher sensitivity. It was demonstrated that supraparticles could provide great enhancement for SERS behavior, which was eight folds higher than that of Au@Ag NPs assembled 3D multilayered structures. In addition, supraparticles with excellent sensitivity and high reproducibility were successfully applied in the detection of pesticide and antibiotics both in organic and aqueous solvents. This work provides a new way for the fabrication of 3D plasmonic nanostructures with highly sensitive and reproducible SERS performance.

Highly sensitive and selective SERS substrates with 3D hot spot buildings for rapid mercury ion detection.

Heavy metal ions, which are over-emitted from industrial production, pose a major threat to the ecological environment and human beings. Among the present detection technologies, achieving rapid and on-site detection of contaminants remains a challenge. Herein, capillaries with three-dimensional (3D) hot spot constructures are fabricated to achieve repaid and ultrasensitive mercury ion (Hg2+) detection in water based on surface-enhanced Raman scattering (SERS). The 4-mercapto pyridine (4-Mpy) serves as the Raman reporter with high selectivity, enabling the detection of Hg2+ by changes in adsorption configuration at the trace level. Under optimized conditions, the SERS response of 4-Mpy for Hg2+ exhibits good linearity, ranging from 1 pM to 0.1 μM in a few minutes, and the detection limit of 0.2 pM is much lower than the maximum Hg2+ concentration of 10 nM allowed in drinking water, as defined by the US Environmental Protection Agency (EPA). Simultaneously, combined with the theoretical simulation and experimental results, the above results indicate that the SERS substrates possess outstanding performances in specificity, recovery rate and stability, which may hold great potential for achieving rapid and on-site environmental pollutant detection using a portable Raman spectrometer.

Flexible PDMS-Based SERS Substrates Replicated from Beetle Wings for Water Pollutant Detection

The flexible surface-enhanced Raman scattering (SERS) sensor, which has the bionic 3D nanoarray structure of a beetle-wing substrate (BWS), was successfully prepared by replicated technology and thermal evaporation. The bionic structure was replicated with polydimethylsiloxane (PDMS) and then silver (Ag) nanoisland thin films were deposited by thermal evaporation. The deposition times and thicknesses (25-40 nm) of the Ag thin films were manipulated to find the optimal SERS detection capability. The Ag nanoisland arrays on the surface of the bionic replicated PDMS were observed by scanning electron microscope (SEM), X-ray diffraction (XRD), and contact angle, which can generate strong and reproducible three-dimensional hotspots (3D hotspots) to enhance Raman signals. The water pollutant, rhodamine 6G (R6G), was used as a model molecule for SERS detection. The results show that 35 nm Ag deposited on a PDMS-BWS SERS substrate displays the strongest SERS intensity, which is 10 times higher than that of the pristine BWS with 35 nm Ag coating, due to the excellent 3D bionic structure. Our results demonstrate that bionic 3D SERS sensors have the potential to be applied in wearable devices and sensors to detect biomolecules and environmental pollutants, such as industrial wastewater, in the future.

3D Hot Spots Droplets on the MoS2/Al Hydrophobic Array Interface for SERS Quantitative and Multiplex Detection of Pesticide Residues

AbstractThe practical application of surface‐enhanced Raman spectroscopy (SERS) technology for quantitative analysis still confronts the hinder of controlling the uniformity of signal and anchoring target molecules in a designed space. Herein, a facile method of devising the shrinkage of three‐dimension (3D) hot spots droplets on a hydrophobic array substrate is demonstrated for the quantitative and multiplex detection of pesticide residues by using a portable Raman spectrometer. The shrunk droplet which is consisted of the analyte solution and AgNPs sol can induce simultaneously increasing density of plasmonic hot spots and immobilizing target molecules in hot spots. Besides, the closely packed Ag nanoparticles (AgNPs) are anchored in the gaps of the MoS2 nanosheet array, generating uniform hotspots distribution with relative standard deviation (RSD) of about 8 %. In addition, the synergetic effects between MoS2 and AgNPs further enhance the SERS sensitivity, and thereby target molecules of 10−9 m are readily detected. Besides, the proposed strategy exhibits excellent SERS sensitivity for the analysis of pesticides down to 10−8 m. Importantly, quantitative analysis and multi‐components detection of pesticide residues on honeysuckle surface are achieved. Therefore, it is expected to be used for quantitative analysis of complex pesticide systems on real samples.

Three-Dimensional Surface-Enhanced Raman Scattering Platform with Hotspots Built by a Nano-mower for Rapid Detection of MRSA.

Methicillin-resistant Staphylococcus aureus (MRSA) has become one of the greatest threats to human health due to its strong drug resistance, wide distribution range, and high infection rate. Rapid identification of MRSA strains is very important for accurate diagnosis and early treatment of MRSA infections. Here, we introduced an Exo III-assisted nanomotor mower to build 3D hotspots for rapid detection of MRSA by surface-enhanced Raman scattering (SERS). As the bacteria bound to the aptamer, two trigger chains were released from the double-stranded structure, and the nano-mowers were activated by opening a hairpin probe on gold nanoparticles (AuNPs). With the continued cleavage of Exo III and cyclic release of the trigger chain, multiple hairpin DNAs on the AuNPs were cleaved to increase the motor power. The resulting nano-mower continued slicing protective DNA from larger AuNPs, exposing the AuNPs. Without the protection of DNA, Mg2+ in the buffer induced spontaneous aggregation of the AuNPs, and a large number of hotspots were formed for SERS measurements. Under optimal conditions, MRSA can be detected within 40 min, and the concentration of MRSA showed a good linear relationship with the SERS intensity at 1342 cm-1, with a limit of detection as low as 1 CFU/mL and a wide linear range (100 to 107 CFU/mL). This strategy creates a rapid bacterial detection method that performs well on actual samples utilizing portable Raman spectroscopy instruments, with potential applications in food detection, water detection, clinical treatment, and diagnosis.