Dielectrophoretic Nanoparticle Aggregation for On-Demand Surface Enhanced Raman Spectroscopy Analysis

An integrated computational pipeline for machine learning-driven diagnosis based on Raman spectra of saliva samples

Raman Spectroscopy promises the ability to encode in spectral data the significant differences between biological samples belonging to patients affected by a disease and samples of healthy patients (controls). However, the decoding and interpretation of the Raman spectral fingerprint is still a difficult and time-consuming procedure even for domain experts. In this work, we test an end-to-end deep-learning diagnostic pipeline able to classify spectral data from saliva samples. The pipeline has been validated against the SARS-COV-2 Infection and for the screening of neurodegenerative diseases such as Parkinson's and Alzheimer's diseases. The proposed system can be used for the fast prototyping of promising non-invasive, cost and time-efficient diagnostic screening tests.

Recent reports on the sensing strategy and the On-site detection of illegal drugs

In this review, works on the on-site detection of illegal drugs in recent years are summarised and discussed, most of which were published within the past five years. The detection methods are categorised as colourimetric, fluorescence, Raman spectrometry, ion mobility spectrometry, electrochemistry, and mass spectrometry. Also, strategies that are possibly suitable for on-site detection and the actual instrumentation to be used in the field are listed.

'When is a hotspot a good nanospot' - review of analytical and hotspot-dominated surface enhanced Raman spectroscopy nanoplatforms

Substrate development in surface-enhanced Raman spectroscopy (SERS) continues to attract research interest. In order to determine performance metrics, researchers in foundational SERS studies use a variety of experimental means to characterize the nature of substrates. However, often this process would appear to be performed indiscriminately without consideration for the physical scale of the enhancement phenomena. Herein, we differentiate between SERS substrates whose primary enhancing structures are on the hundreds of nanometer scale (analytical SERS nanosubstrates) and those whose main mechanism derives from nanometric-sized gaps (hot-spot dominated SERS substrates), assessing the utility of various characterization methods for each substrate class. In this context, characterization approaches in white-light spectroscopy, electron beam methods, and scanning probe spectroscopies are reviewed. Tip-enhanced Raman spectroscopy, wavelength-scanned SERS studies, and the impact of surface hydrophobicity are also discussed. Conclusions are thus drawn on the applicability of each characterization technique regarding amenability for SERS experiments that have features at different length scales. For instance, while white light spectroscopy can provide an indication of the plasmon resonances associated with 10 s-100 s nm-scale structures, it may not reveal information about finer surface texturing on the true nm-scale, critical for SERS' sensitivity, and in need of investigation via scanning probe techniques.

Efficient nanoparticle focusing utilizing cascade AC electroosmotic flow

This study presents on‐chip continuous accumulation and concentration of nanoscale samples using a cascade alternating current electroosmosis (cACEO) flow. ACEO can generate flow motion caused by ion movement due to interactions between the AC electric field and the induced charge layer on the electrode surface, with the potential to accumulate particles, especially in low‐conductive liquid. However, the intrinsic particle diffusive motion, which is sensitive to particle size, is an essential element influencing accumulation efficiency. In this study, an electrode combining chevron and double‐gap geometry embedded in a microfluidic channel was developed to perform efficient three‐dimensional (3D) nanoparticle focusing using ACEO. The chevron electrode pattern was introduced upstream of the focusing zone to overcome particle accumulation in scattering zones near the channel sidewall. To demonstrate the efficiency of the proposed device for particle accumulation, three nanoparticle types were used: latex, metal, and biomaterial. Continuous 3D concentration of 50‐nm polystyrene particles was confirmed. The concentration factor, determined based on image processing, became quite high when 50‐nm gold nanoparticles were used. Moreover, nanoparticles with a 20‐nm diameter were accumulated using cACEO. Finally, we used the concentrator chip to accumulate 50‐nm liposome particles, confirming that the device could also successfully concentrate biomaterials.

New insights for integration of nano particle with microfluidic systems for sensor applications

A biosensor is a compact device, which utilizes biological derived recognition component, immobilized on a transducer to analyze an analyte. Nanoparticles with their unique chemical and physical properties are versatile in their applications to develop as sensors. Different nanoparticles play different roles in the sensing systems like metal and metal oxide nanoparticles. The application of Gold, Silver and Copper nanoparticles will be discussed in brief. The nanoparticles typically function as substrates for immobilization of biomolecules, as catalytic agent, electron transfer agent between electrode surface and the biomolecules, and as reactants. Microfluidic deals with manipulating very small volumes of fluids (micro and nanoliters). This miniaturized platform enhances control of flow conditions and mixing rate of fluids. The microfluidics improves the sensitivity of the analysis, and reduces the volumes of sample and reagent in the analysis. The review specifically aims at representing microfluidics-based sensors and nanoparticle based sensors. This review will also focus on probable merger of these two fields to take advantage of both the fields and this will help in pushing the boundaries of these fields further more.

Microscale modelling of dielectrophoresis assembly processes

This work presents a microscale approach for simulating the dielectrophoresis assembly of polarizable particles under an external electric field. The model is shown to capture interesting dynamical and topological features, such as the formation of chains of particles and their incipient aggregation into hierarchical structures. A quantitative characterization in terms of the number and size of these structures is also discussed. This computational model could represent a viable numerical tool to study the mechanical properties of particle-based hierarchical materials and suggest new strategies for enhancing their design and manufacture. This article is part of the theme issue 'Progress in mesoscale methods for fluid dynamics simulation'.

Recent advances in developing optical and electrochemical sensors for analysis of methamphetamine: A review

Recognition of misused stimulant drugs has always been a hot topic from a medical and judicial perspective. Methamphetamine (MAMP) is an addictive and illegal drug that profoundly affects the central nervous system. Like other illicit drugs, the detection of MAMP in biological and street samples is vital for several organizations such as forensic medicine, anti-drug headquarters and diagnostic clinics. By emerging nanotechnology and exploiting nanomaterials in sensing applications, a great deal of attention has been given to the design of analytical sensors in MAMP tracing. For the first time, this study has briefly reviewed all the optical and electrochemical sensors in MAMP detection from earlier so far. How various receptors with engineering nanomaterials allow developing novel approaches to measure MAMP have been studied. Fundamental concepts related to optical and electrochemical recognition assays in which nanomaterials have been used and relevant MAMP sensing applications have been comprehensively covered. Challenges, opportunities and future outlooks of this field have also been discussed at the end.

Development of Crime Scene Intelligence Using a Hand-Held Raman Spectrometer and Transfer Learning

The classification of ignitable liquids, such as gasoline, is critical crime scene intelligence to assist arson investigations. Rapid field gasoline classification is challenging because the current forensic testing standard requires gas chromatography-mass spectrometry analysis of evidence in an accredited laboratory. In this work, we reported a new intelligent analytical platform for field identification and classification of gasoline evidence. A hand-held Raman spectrometer was utilized to collect Raman spectra of reference gasoline samples with various octane numbers. The Raman spectrum pattern was converted into image presentations by continuous wavelet transformation (CWT) to facilitate artificial intelligence development using the transfer learning technique. GoogLeNet, a pretrained convolutional neural network (CNN), was adapted to train the classification model. Six different classification models were also developed from the same data set using conventional machine learning algorithms to evaluate the performance of our new approach. The experimental results indicated that the pretrained CNN model developed by our new data workflow outperformed other models in several performance benchmarks, such as accuracy, precision, recall, F1, Cohen's Kappa, and Matthews correlation coefficient. When the transfer learning model was challenged with the data collected from weathered gasoline samples, the classifier could still offer 73 and 53% accuracy for 50 and 25% weathered gasoline samples, respectively. In conclusion, wavelet transforms combined with transfer learning successfully processed and classified complex Raman spectral data without feature engineering. We envision that this nondestructive, automated, and accurate platform will accelerate crime scene intelligence development based on evidence's chemical signatures detected by hand-held Raman spectrometers.

Plasmonic Split-Trench Resonator for Trapping and Sensing

On-chip integration of plasmonics and electronics can benefit a broad range of applications in biosensing, signal processing, and optoelectronics. A key requirement is a chip-scale manufacturing method. Here, we demonstrate a split-trench resonator platform that combines a high-quality-factor resonant plasmonic biosensor with radio frequency (RF) nanogap tweezers. The split-trench resonator can simultaneously serve as a dielectrophoretic trap and a nanoplasmonic sensor. Trapping is accomplished by applying an RF electrical bias across a 10 nm gap, thereby either attracting or repelling analytes. Trapped analytes are detected in a label-free manner using refractive-index sensing, enabled by interference between surface-plasmon standing waves in the trench and light transmitted through the gap. This active sample concentration mechanism enables detection of nanoparticles and proteins at a concentration as low as 10 pM. We can manufacture centimeter-long split-trench cavity resonators with high throughput via photolithography and atomic layer deposition, toward practical applications in biosensing, spectroscopy, and optoelectronics.

Continuous-Flow Nanoparticle Trapping Driven by Hybrid Electrokinetics in Microfluidics

We introduce herein an efficient microfluidic approach for continuous transport and localized collection of nanoparticles via hybrid electrokinetics, which delicately combines linear and nonlinear electrokinetics driven by a composite DC-biased AC voltage signal. The proposed technique utilizes a simple geometrical structure, in which one or a series of metal strips serving as floating electrode (FE) are attached to the substrate surface and arranged in parallel between a pair of coplanar driving electrodes (DE) in a straight microchannel. On application of a DC-biased AC electric field across the channel, nanoparticles can be transported continuously by DC bulk electroosmotic flow, and then trapped selectively onto the metal strips due to AC-field induced-charge electrokinetic (ICEK) phenomenon, which behaves as counter-rotating micro-vortices around the ideally polarizable surfaces of FE. Finite-element simulation is carried out by coupling the dual-frequency electric field, flow field and sample mass transfer in sequence, for guiding a practical design of the microfluidic nanoparticle concentrator. With the optimal device geometry, the actual performance of the technique is investigated with respect to DC bias, AC voltage amplitude, and field frequency by using both latex nanospheres (∼500 nm) and BSA molecules (∼10 nm). Our experimental observation indicates nanoparticles are always enriched into a narrow bright band on the surface of each FE, and a horizontal concentration gradient even emerges in the presence of multiple metal strips, which therefore permits localized analyte enrichment. The proposed trapping method is supposed to guide an elaborate design of flexible electrokinetic frameworks embedding FE for continuous-flow analyte manipulation in modern microfluidic systems.

Recent progress of microfluidics in surface-enhanced Raman spectroscopic analysis

Surface-enhanced Raman spectroscopy is a significant analytical tool capable of fingerprint identification of molecule in a rapid and ultrasensitive manner. However, it is still hard to meet the requirements of practical sample analysis. The introduction of microfluidics can effectively enhance the performance of surface-enhanced Raman spectroscopy in complex sample analysis including reproducibility, selectivity, sensitivity, and speed. This review summarizes the recent progress of microfluidics in surface-enhanced Raman spectroscopic analysis through four combination approaches. First, microfluidic synthetic techniques offer uniform nano-/microparticle fabrication approaches for reproductive surface-enhanced Raman spectroscopic analysis. Second, the integration of microchip and surface-enhanced Raman spectroscopic substrate provides advanced devices for sensitive and efficient detection. Third, microfluidic sample preparations enable rapid separation and preconcentration of analyte prior to surface-enhanced Raman spectroscopic detection. Fourth, highly integrated microfluidic devices can be employed to realize multistep surface-enhanced Raman spectroscopic analysis containing material fabrication, sample preparation, and detection processes. Furthermore, the challenges and outlooks of the application of microfluidics in surface-enhanced Raman spectroscopic analysis are discussed.

Self-Concentrated Surface-Enhanced Raman Scattering-Active Droplet Sensor with Three-Dimensional Hot Spots for Highly Sensitive Molecular Detection in Complex Liquid Environments

In this work, a surface-enhanced Raman scattering (SERS)-active droplet with three-dimensional (3D) hot spots prepared from a superhydrophobic SERS substrate, which is inspired by the nut wizard strategy, was developed for ultrasensitive detection in complex liquid environments. The SERS substrate was composed of silver-capped parylene C-coated carbon nanoparticles (Ag-PC@CNPs). Such a SERS substrate was prepared by candle-soot deposition to provide a porous carbon nanoparticle layer followed by deposition of a parylene C film to protect the CNPs and then sputtering of silver nanoparticles. Similar to a nut wizard, a droplet rolling on the Ag-PC@CNP-coated substrate picked up the Ag-PC@CNPs. In this way, a self-concentrated and extremely sensitive SERS-active droplet sensor with 3D hot spots was formed. The sensor did not require precise laser focusing and showed relatively high repeatability and much higher sensitivity than those of a corresponding SERS substrate with two-dimensional hot spots. The sensor also achieved high sensitivity and specificity in complex liquid environments; in addition, bovine serum albumin with a concentration as low as 1 pM can be achieved. Consequently, an extremely simple, flexible, and highly sensitive SERS detection technique applicable to liquid biopsy analysis is anticipated.

Theory for hierarchical assembly with dielectrophoresis and the role of particle anisotropy

Nonuniform electric fields cause polarizable particles to move through an effect known as dielectrophoresis (DEP). Additionally, the particles themselves create nonuniform fields due to their induced dipoles. When the nonuniform field of one particle causes another to move, it represents a path to hierarchical assembly termed mutual DEP (mDEP). Anisotropic particles potentially provide further opportunities for assembly through intense and intricate local field profiles. Here, we construct a theoretical framework for describing anisotropic particles as templates for assembly through mDEP by considering the motion of small nanoparticles near larger anisotropic nanoparticles. Using finite element analysis, we study eight particle shapes and compute their field enhancement and polarizability in an orientation-specific manner. Strikingly, we find a more than tenfold enhancement in the field near certain particle shapes, potentially promoting mDEP. To more directly relate the field intensity to the anticipated assembly outcome, we compute the volume experiencing each field enhancement versus particle shape and orientation. Finally, we provide a framework for predicting how mixtures of two distinct particle species will begin to assemble in a manner that allows for the identification of conditions that kinetically bias assembly toward specific hierarchical outcomes.

Carbene modification and reversible crosslinking of silver nanoparticles for controlled antibacterial activity

Silver nanoparticles (Ag NPs) system capable of exhibiting different particle size at different temperature was developed, which depended on the extent of Diels-Alder (DA) reaction of bismaleimide with furan. Thus, Ag NPs were functionalized on the surface by a furyl-substituted carbene through an insertion reaction. Subsequent reversible DA crosslinking achieved a controlled aggregation with different particle size, which gives a series of different antibacterial activity. These Ag NPs were characterized by Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), X-ray Photoelectron Spectroscopy (XPS), and Nanoparticle Size Analyzer. The aggregation of the Ag NPs could be reliably adjusted by varying the temperature of DA/reverse-DA reaction. The antibacterial activity was assessed using the inhibition zone method against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), which decreased first and then increased in agreement with the size evolution of Ag NPs. This approach opens a new horizon for the carbene chemistry to modify silver nanoparticles with variable size and give controlled antibacterial activity.

A Numerical Investigation of Enhancing Microfluidic Heterogeneous Immunoassay on Bipolar Electrodes Driven by Induced-Charge Electroosmosis in Rotating Electric Fields

A unique approach is proposed to boost on-chip immuno-sensors, for instance, immunoassays, wherein an antibody immobilized on the walls of a microfluidic channel binds specifically to an antigen suspended freely within a working fluid. The performance of these sensors can be limited in both susceptibility and response speed by the slow diffusive mass transfer of the analyte to the binding surface. Under appropriate conditions, the binding reaction of these heterogeneous immuno-assays may be enhanced by electroconvective stirring driven by external AC electric fields to accelerate the translating motion of antigens towards immobilized antibodies. To be specific, the phenomenon of induced-charge electroosmosis in a rotating electric field (ROT-ICEO) is fully utilized to stir analyte in the vicinity of the functionalized surface of an ideally polarizable floating electrode in all directions inside a tri-dimensional space. ROT-ICEO appears as a consequence of the action of a circularly-polarized traveling wave signal on its own induced rotary Debye screening charge within a bipolar induced double layer formed on the central floating electrode, and thereby the pertinent electrokinetic streamlines exhibit a radially converging pattern that greatly facilitates the convective transport of receptor towards the ligand. Numerical simulations indicate that ROT-ICEO can enhance the antigen–antibody binding reaction more effectively than convectional nonlinear electroosmosis driven by standing wave AC signals. The effectiveness of ROT-ICEO micro-stirring is strongly dependent on the Damkohler number as well as the Peclet number if the antigens are carried by a continuous base flow. Our results provide a promising way for achieving a highly efficient heterogeneous immunoassay in modern micro-total-analytical systems.

Portable surface-enhanced Raman scattering analysis performed with microelectrode-templated silver nanodendrites

Using a handheld Raman spectrometer, we demonstrate how silver nanodendritic substrates formed on microelectrode platforms can be used for ultrasensitive detection of target analytes, such as cocaine and melamine. The nanostructured substrates are formed through the electrochemical deposition of silver on electrically insulated silicon substrates with the aid of an alternating current (AC) signal applied to the microelectrodes. A nanostructure lateral growth rate of 8.90 ± 0.19 μm min^-1 was achieved by implementing a semi-batch process that kept the reactant concentrations high during silver deposition. This facile process can be used with different microelectrode designs, thus allowing for customizable SERS substrates. Compared with a commercially available benchmark, our surface-enhanced Raman scattering (SERS) substrates were found to be at least twice more sensitive. Moreover, by applying multivariate analysis, specifically principal component analysis and linear classification models, the pesticide thiram was identified at 1 ppm with 100% accuracy in spiked apple juice without sample pre-processing. Our technique provides the means for combining microelectrode platforms with SERS for portable, point-of-care sensing applications.

Microfluidic analysis of fentanyl-laced heroin samples by surface-enhanced Raman spectroscopy in a hydrophobic medium

Opioid overdose deaths resulting from heroin contaminated with the potent opioid agonist fentanyl, are currently a serious public health issue. A rapid and reliable method for identifying fentanyl-laced heroin could lead to reduced opioid overdose. Herein, we describe a strategy for detecting fentanyl at low concentrations in the presence of heroin, based on the significant hydrophobicity of fentanyl compared to heroin hydrochloride, by preferentially extracting trace concentrations of fentanyl using ultrasound-assisted emulsification microextraction using octanol as the extracting phase. Surface-enhanced Raman spectroscopy (SERS), is enabled by exposing the analyte to silver nanoparticle-coated SiO₂ nanoparticles, designed to be stable in mixtures of octanol and ethanol. The sample is then loaded into an SU8/glass microfluidic device that is compatible with non-aqueous solutions. The SERS-active nanoparticles are aggregated by dielectrophoresis using microelectrodes embedded in the microfluidic channels, and the nanoparticle aggregates are interrogated using Raman spectroscopy. Using this method, we were able to reliably detect fentanyl from samples with as low as 1 : 10 000 (mol/mol) fentanyl-to-heroin ratio, improving the limits of detection of fentanyl-laced heroin samples by two orders of magnitude over current techniques. The described system could also be useful in chemical detection where rapid and robust preconcentration of trace hydrophobic analytes, and rapid SERS detection in non-aqueous solvents is indicated.

Quantitative surface-enhanced Raman spectroscopy chemical analysis using citrate as an in situ calibrant

Direct detection, or inferring the presence of illicit substances, is of great forensic and toxicological value. Surface-enhanced Raman spectroscopy (SERS) has been shown capable of detecting such molecules in a quick and sensitive manner. Herein we describe an analysis strategy for quantitation of low concentrations of three analytes (methamphetamine, cocaine, and papaverine) by SERS analysis using the citrate capping agent that initially saturates the silver nanoparticles' surface as an in situ standard. The citrate is subsequently displaced by the analyte to an extent dependent on the analyte's concentration in the analyte solution. A general model for the competitive adsorption of citrate and a target analyte was developed and used to determine the relative concentrations of the two species coexisting on the surface of the silver nanoparticles. To apply this model, classical least squares (CLS) was used to extract the relative SERS contribution of each of the two species in a given SERS spectrum, thereby accurately determining the analyte concentration in the sample solution. This approach, in essence, transforms citrate into a local standard against which the concentration of an analyte can be reliably determined.