Molybdenum Disulfide-Assisted Spontaneous Formation of Multistacked Gold Nanoparticles for Deep Learning-Integrated Surface-Enhanced Raman Scattering.

Several fabrication methods have been developed for label-free detection in various fields. However, fabricating high-density and highly ordered nanoscale architectures by using soluble processes remains a challenge. Herein, we report a biosensing platform that integrates deep learning with surface-enhanced Raman scattering (SERS), featuring large-area, close-packed three-dimensional (3D) architectures of molybdenum disulfide (MoS2)-assisted gold nanoparticles (AuNPs) for the on-site screening of coronavirus disease (COVID-19) using human tears. Some AuNPs are spontaneously synthesized without a reducing agent because the electrons induced on the semiconductor surface reduce gold ions when the Fermi level of MoS2 and the gold electrolyte reach equilibrium. With the addition of polyvinylpyrrolidone, a two-dimensional large-area MoS2 layer assisted in the formation of close-packed 3D multistacked AuNP structures, resembling electroless plating. This platform, with a convolutional neural network-based deep learning model, achieved outstanding SERS performance at subterascale levels despite the microlevel irradiation power and millisecond-level acquisition time and accurately assessed susceptibility to COVID-19. These results suggest that our platform has the potential for rapid, low-damage, and high-throughput label-free detection of exceedingly low analyte concentrations.

One-Stop Plasmonic Nanocube-Excited SERS Immunoassay Platform of Multiple Cardiac Biomarkers for Rapid Screening and Progressive Tracing of Acute Myocardial Infarction.

Rapid and precise acute myocardial infarction (AMI) diagnosis is essential for preventing patient death. In addition, the complementary roles of creatine kinase muscle brain (CK-MB) and cardiac troponin I (cTnI) cardiac biomarkers in the early and late stages of AMI demand their simultaneous detection, which is difficult to implement using conventional fluorescence and electrochemical technologies. Here, a nanotechnology-based one-stop immuno-surface-enhanced Raman scattering (SERS) detection platform is reported for multiple cardiac indicators for the rapid screening and progressive tracing of AMI events. Optimal SERS is achieved using optical property-based, excitation wavelength-optimized, and high-yield anisotropic plasmonic gold nanocubes. Optimal immunoassay reaction efficiencies are achieved by increasing immobilized antibodies. Multiple simultaneous detection strategies are implemented by incorporating two different Raman reports with narrow wavenumbers corresponding to two indicators and by establishing a computational SERS mapping process to accurately detect their concentrations, irrespective of multiple enzymes in the human serum. The SERS platform precisely estimated AMI onset and progressive timing in human serum and made rapid AMI identification feasible using a portable Raman spectrometer. This integrated platform is hypothesized to significantly contribute to emergency medicine and forensic science by providing timely treatment and observation.

Adiponectin-targeted SERS immunoassay biosensing platform for early detection of gestational diabetes mellitus.

The anisotropic gold nanotriangles (AuNTs) were synthesized by a fast seedless growth process. The high-yield monodispersed AuNT colloids were obtained through a purification process based on depletion-induced interactions. AuNTs were modulated with a localized surface plasmon resonance (LSPR) peak of 638 nm wavelength coherent with the Raman excitation light. However, from finite element computation results, the AuNT clusters showed better performance for the 785 nm laser source due to a red shift in their LSPR properties, hence it was selected for the surface-enhanced Raman scattering (SERS) immunoassay. A self-assembly strategy using a thiol group and ON-OFF strategy in the heat map was performed to ensure the stability of SERS immunoassay platform. The sandwich SERS immunoassay biosensor platform for adiponectin detection demonstrated a wide assay range (10-15-10-6 g/mL), good reliability (R2 = 0.994, clinically relevant range), femto-scale limit of detection (3.0 × 10-16 g/mL), and excellent selectivity without interference from other biomarkers. This showed the possibility of effectively detecting adiponectin levels in the biofluids of pregnant women. Therefore, our technology is the first to quantitatively detect adiponectin based on SERS technology for early detection of gestational diabetes mellitus and has the potential to be used as a clinical biosensor capable of diagnosing various obstetric diseases during early pregnancy.

An excitation wavelength-optimized, stable SERS biosensing nanoplatform for analyzing adenoviral and AstraZeneca COVID-19 vaccination efficacy status using tear samples of vaccinated individuals.

We introduce a label-free surface-enhanced Raman scattering (SERS) biosensing platform equipped with metallic nanostructures that can identify the efficacy of Oxford-AstraZeneca (AZD1222) vaccine in vaccinated individuals using non-invasive tear samples. We confirmed the hypothesis that the tears of people who receive the AZD1222 vaccine may be similar to those of adenovirus epidemic keratoconjunctivitis patients since the Oxford-AstraZeneca vaccine is derived from a replication-deficient ChAdOx1 vector of chimpanzee adenovirus. Additionally, we confirmed the potential of the three markers for estimating the vaccination status via analyzing the signals emanating from antibodies or immunoglobulin G by-product using our label-free, SERS biosensing technique with a high reproducibility (<3% relative standard deviation), femtomole-scale limit of detection (1 × 10-14 M), and high SERS response of >108. Therefore, our label-free SERS biosensing nanoplatforms with long-term storage and robust stability will enable rapid and robust monitoring of the vaccine presence in vaccinated individuals.

A digital SERS sensing platform using 3D nanolaminate plasmonic crystals coupled with Au nanoparticles for accurate quantitative detection of dopamine.

We report a digital surface-enhanced Raman spectroscopy (SERS) sensing platform using the arrays of 3D nanolaminate plasmonic crystals (NLPC) coupled with Au nanoparticles and digital (on/off) SERS signal analysis for the accurate quantitative detection of dopamine (DA) at ultralow concentrations. 3D NLPC SERS substrates were fabricated to support the optically dense arrays of vertically-stacked multi-nanogap hotspots and combined with Raman tag-conjugated Au nanoparticles for NLPC-based dual-recognition structures. We demonstrate that the 3D NLPC-based dual-recognition structures including Au nanoparticle-induced additional hotspots can enable more effective SERS enhancement through the molecular recognition of DA. For the accurate quantification of DA at ultralow concentrations, we conducted digital SERS analysis to reduce stochastic signal variation due to various microscopic effects, including molecular orientation/position variation and the spatial distribution of nanoparticle-coupled hotspots. The digital SERS analysis allowed the SERS mapping results from the DA-specific dual-recognition structures to be converted into binary "On/Off" states; the number of "On" events was directly correlated with low-abundance DA molecules down to 1 pM. Therefore, the digital SERS platform using the 3D NLPC-based dual-recognition structures coupled with Au nanoparticles and digital SERS signal analysis can be used not only for the ultrasensitive, accurate, and quantitative determination of DA, but also for the practical and rapid analysis of various molecules on nanostructured surfaces.

Label-free breast cancer detection using fiber probe-based Raman spectrochemical biomarker-dominated profiles extracted from a mixture analysis algorithm.

We report the development of a label-free, simple, and high efficiency breast cancer detection platform with multimodal biomarker analytic algorithms on a portable 785 nm Raman setup with an endoscopic Raman-lensed fiber optic probe. We propose a multimodal biomarker extraction algorithm (PCMA) implemented by combining a multivariate statistics principal component analysis (PCA) algorithm and a multivariate curve resolution-alternating least squares (MCR-ALS) computational model for extraction of the biomarker information hidden in Raman spectrochemical data. We show that the six Raman spectrochemical peaks at 1009, 1270, 1305/1443, 1658, and 1750 cm-1 assigned to phenylalanine, amide III in proteins, CH2 deformation in lipids, amide I in proteins, and carbonyl, respectively, can be used as a biomarker for breast cancer diagnosis using the biomarker-dominated PCMA spectrochemical spectra of breast tissues. From 20 human breast tissues, the PCMA-linear discriminant analysis (PCMA-LDA) identification method achieved high classification performance with a sensitivity and specificity >99% along with an improvement of approximately 4.5% compared to the performance without the PCMA mixture analysis algorithm. Our label-free breast cancer detection method has the potential for clinical application to diagnose breast cancer in real-time during surgery.

Enhanced stretchability of metal/interlayer/metal hybrid electrode.

Despite the excellent electrical conductivity of metal thin film electrodes, their poor mechanical stretchability makes it extremely difficult to apply them as stretchable interconnect electrodes. Thus, we propose a novel stretchable hybrid electrode (SHE) by adopting two strategies to overcome the metal thin film electrode limitations: grain size engineering and hybridization with conductive interlayers. The grain size engineering technique improves the inherent metal thin film stretchability according to the Hall-Petch theory, and the hybridization of the conductive interlayer materials, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) and carbon nanotube (CNT), suppresses crack propagation. Especially, the CNT-inserted SHE exhibits a decreased resistance change of approximately 32% in tensile test and 75% in a 10 000 cycle fatigue test because of the rough surface of the designed electrode, which relieves maximum stress by redistributing it more evenly to prevent penetrating crack propagation.

Wavelength-dependent label-free identification of isolated nontuberculous mycobacteria using surface-enhanced Raman spectroscopy.

We investigated the effect of Raman excitation wavelengths on the surface-enhanced Raman spectroscopy (SERS)-based identification of isolated nontuberculous mycobacteria (NTM). The SERS spectra with 3 commonly used excitation wavelengths, 532, 638, and 785 nm, were compared across 6 representative NTM species that primarily cause human NTM infections in Korea and the United States; these species were identified. The statistical differences among NTM SERS spectra at each Raman excitation wavelength were verified using 1-way analysis of variance, and the 6 NTM species were identified using principal components-linear discriminant analysis with leave-one-out cross validation. The identification accuracies with aromatic amino acid biomarkers were 99.3%, 91.3%, and 90.7% for 532, 638, and 785 nm, respectively. We believe that the proposed SERS protocol with aromatic amino acid biomarkers at the 532-nm Raman excitation wavelength will enable fast and accurate identification of NTM compared to previous identification methods.

Label-Free Surface-Enhanced Raman Spectroscopy Biosensor for On-Site Breast Cancer Detection Using Human Tears.

Surface-enhanced Raman scattering (SERS) is an ultrasensitive molecular screening technique with greatly enhanced Raman scattering signals from trace amounts of analytes near plasmonic nanostructures. However, research on the development of a sensor that balances signal enhancement, reproducibility, and uniformity has not yet been proposed for practical applications. In this study, we demonstrate the potential of the practical application for detecting or predicting asymptomatic breast cancer from human tears using a portable Raman spectrometer with an identification algorithm based on multivariate statistics. This potentiality was realized through the fabrication of a plasmonic SERS substrate equipped with a well-aligned, gold-decorated, hexagonal-close-packed polystyrene (Au/HCP-PS) nanosphere monolayer that provided femtomole-scale detection, giga-scale enhancement, and <5% relative standard deviation for reliability and reproducibility, regardless of the measuring site. Our results can provide a first step toward developing a noninvasive, real-time screening technology for detecting asymptomatic tumors and preventing tumor recurrence.

Effects of scleral collagen crosslinking with different carbohydrate on chemical bond and ultrastructure of rabbit sclera: Future treatment for myopia progression.

BACKGROUND: Myopia is the most common ocular disorder and is mainly caused by axial elongation of the sclera. If the stiffness of sclera increased, it can inhibit myopia progression. The aim of this study is to compare the effect of the collagen crosslinking with different types and concentrations of carbohydrates on chemical bond and ultrastructural change of rabbit sclera. METHODS: Nine New Zealand white rabbits were treated with five, sequential sub-Tenon injections of 0.15 mL solutions of ribose, sucrose, and glycogen of 0.1, 0.2 and 0.4 M concentration at the right eye over 14 days. Ten weeks after the last injection, the rabbits were sacrificed and chemical bond and ultrastructural changes were compared with those of the untreated left sclera using Raman spectroscopy, atomic force microscopy (AFM), and histology. RESULTS: Raman spectroscopy of the control and cross-linked rabbit sclera tissue revealed different types of collagen interactions. Raman shift of 919 cm-1 (C-C stretching and vibration of the proline ring in collagen) was the highest in ribose, followed by sucrose and glycogen. Total energy intensity was also highest in ribose, followed by sucrose and glycogen, and showed a tendency to increase at higher concentrations. AFM revealed interlocking arrangements of collagen fibrils. The collagen fibril diameter was 105.6 ± 21.2 nm, 109.4 ± 28.8 nm, 113.1 ± 30.8 nm and 137.6 ± 25.3 nm for control group, 0.4 M glycogen, sucrose, and ribose, respectively. Histology indicated increased density of the collagen bundle and no increase in inflammatory cell recruitment compared to control at high concentrations of ribose. CONCLUSIONS: Scleral crosslinking using glycation increased the scleral biomechanical rigidity and these results were particularly pronounced in ribose. Scleral crosslinking using glycation may be a promising method for inhibiting high myopia progression.

Direct Visualization of Cross-Sectional Strain Distribution in Flexible Devices.

For flexible devices that inevitably undergo repetitive deformations, it is important to evaluate and control the mechanical strain imposed on the flexible systems for enhancing the reliability. In this paper, a novel experimental method to directly visualize cross-sectional strain distribution in the thin flexible devices is proposed. Digital image correlation (DIC) is effectively adapted by using microscopic images of the cross section for accurate analysis of the microscale deformations. To conduct the DIC strain analysis, speckle patterning is accomplished by using microparticles from diamond-abrasive suspensions with optimized fabrication conditions. First, the cross-sectional micro-DIC analysis is performed successfully for 100 µm-thick substrates. Full-field strain quantification and easy inspection of a neutral plane are demonstrated and compared with results of finite element analysis simulation. Using the presented method, generation of multiple neutral planes is clearly visualized for a trilayer structure with a very soft adhesive midlayer, where strain decoupling occurs by severe shear deformation of the soft adhesive layer. Furthermore, bending strain distribution in a flexible fabric-reinforced polymer (FRP) substrate is also investigated to analyze and predict fatigue fracture in the complex inner structure under repetitive bending loading.

Paper-Based Surface-Enhanced Raman Spectroscopy for Diagnosing Prenatal Diseases in Women.

We report the development of a surface-enhanced Raman spectroscopy sensor chip by decorating gold nanoparticles (AuNPs) on ZnO nanorod (ZnO NR) arrays vertically grown on cellulose paper (C). We show that these chips can enhance the Raman signal by 1.25 × 107 with an excellent reproducibility of <6%. We show that we can measure trace amounts of human amniotic fluids of patients with subclinical intra-amniotic infection (IAI) and preterm delivery (PTD) using the chip in combination with a multivariate statistics-derived machine-learning-trained bioclassification method. We can detect the presence of prenatal diseases and identify the types of diseases from amniotic fluids with >92% clinical sensitivity and specificity. Our technology has the potential to be used for the early detection of prenatal diseases and can be adapted for point-of-care applications.

A label-free cellulose SERS biosensor chip with improvement of nanoparticle-enhanced LSPR effects for early diagnosis of subarachnoid hemorrhage-induced complications.

It is very difficult to predict some complications after subarachnoid hemorrhage (SAH), despite rapid advances in medical science. Herein, we introduce a label-free cellulose surface-enhanced Raman spectroscopy (SERS) biosensor chip with pH-functionalized, gold nanoparticle (AuNP)-enhanced localized surface plasmon resonance (LSPR) effects for identification of SAH-induced cerebral vasospasm and hydrocephalus caused by cerebrospinal fluid (CSF). The SERS biosensor chip was implemented by the synthesis reaction of the AuNPs, which were charged positively through pH level adjustment, onto a negatively-charged cellulose substrate with ξ = -30.7 mV. The zeta potential, nanostructural properties, nanocrystallinity, and computational calculation-based electric field distributions of the cellulose-originated AuNPs were optimized to maximize LSPR phenomena and then characterized. Additionally, the performance of the SERS biosensor was compared under two representative excitation laser sources in the visible region (532 nm) and near-infrared region (785 nm). The Raman activities of our SERS biosensor chip were evaluated by trace small molecules (crystal violet, 2 µL), and the biosensor achieved an enhancement factor of 3.29 × 109 for the analytic concept with an excellent reproducibility of 8.5% relative standard deviation and a detection limit of 0.74 pM. Furthermore, the experimental results revealed that the five proposed SERS-based biomarkers could provide important information for identifying and predicting SAH-induced cerebral vasospasm and hydrocephalus complications (91.1% reliability and 19.3% reproducibility). Therefore, this facile and effective principle of our SERS biosensor chip may inspire the basis and strategies for the development of sensing platforms to predict critical complications in various neurosurgical diagnoses.

Low-Cost Label-Free Biosensing Bimetallic Cellulose Strip with SILAR-Synthesized Silver Core-Gold Shell Nanoparticle Structures.

We introduce a label-free biosensing cellulose strip sensor with surface-enhanced Raman spectroscopy (SERS)-encoded bimetallic core@shell nanoparticles. Bimetallic nanoparticles consisting of a synthesis of core Ag nanoparticles (AgNP) and a synthesis of shell gold nanoparticles (AuNPs) were fabricated on a cellulose substrate by two-stage successive ionic layer absorption and reaction (SILAR) techniques. The bimetallic nanoparticle-enhanced localized surface plasmon resonance (LSPR) effects were theoretically verified by computational calculations with finite element models of optimized bimetallic nanoparticles interacting with an incident laser source. Well-dispersed raspberry-like bimetallic nanoparticles with highly polycrystalline structure were confirmed through X-ray and electron analyses despite ionic reaction synthesis. The stability against silver oxidation and high sensitivity with superior SERS enhancement factor (EF) of the low-cost SERS-encoded cellulose strip, which achieved 3.98 × 108 SERS-EF, 6.1%-RSD reproducibility, and <10%-degraded sustainability, implicated the possibility of practical applications in high analytical screening methods, such as single-molecule detection. The remarkable sensitivity and selectivity of this bimetallic biosensing strip in determining aquatic toxicities for prohibited drugs, such as aniline, sodium azide, and malachite green, as well as monitoring the breast cancer progression for urine, confirmed its potential as a low-cost label-free point-of-care test chip for the early diagnosis of human diseases.

Controlled multiple neutral planes by low elastic modulus adhesive for flexible organic photovoltaics.

To protect brittle layers in organic photovoltaic devices, the mechanical neutral plane strategy can be adopted through placing the brittle functional materials close to the neutral plane where stress and strain are zero during bending. However, previous research has been significantly limited in the location and number of materials to protect through using a single neutral plane. In this study, multiple neutral planes are generated using low elastic modulus adhesives and are controlled through quantitative analyses in order to protect the multiple brittle materials at various locations. Moreover, the protection of multiple brittle layers at various locations under both concave and convex bending directions is demonstrated. Multilayer structures that have soft adhesives are further analyzed using the finite element method analysis in order to propose guidelines for structural design when employing multiple neutral planes.

Highly Reproducible Au-Decorated ZnO Nanorod Array on a Graphite Sensor for Classification of Human Aqueous Humors.

Gold-decorated, vertically grown ZnO nanorods (NRs) on a flexible graphite sheet (Au/ZnONRs/G) were developed for surface-enhanced Raman scattering (SERS)-based biosensing to identify trace amounts of human aqueous humors. This Au/ZnONRs/G SERS-functionalized sensor was fabricated via two steps: hydrothermal synthesis-induced growth of ZnO NRs on graphite sheets for nanostructure fabrication, followed by e-beam evaporator-induced gold metallization on ZnONRs/G for SERS functionalization. The thickness of the Au layer and the height of the ZnO NRs for enhancing SERS performance were adjusted to maximize Raman intensity, and the optimized Au/ZnONRs/G nanostructures were verified by the electric finite element computational models to maximize the electric fields. The proposed Au/ZnONRs/G SERS sensor showed an enhancement factor of 2.3 × 106 via rhodamine 6G Raman probe and excellent reproducibility (relative standard deviation of <10%) via Raman mapping of a SERS active area with a square of 100 × 100 µm2. To evaluate the actual bioapplicability of point-of-care-testing (POCT) analysis in clinics, SERS data acquisition was performed with an integration time of 1 s from a 1 µL analytic droplet of the sample. The performance of this Au/ZnONRs/G sensor was evaluated using human aqueous humors with cataract and two oxidative stress-induced eye diseases, age-related macular degeneration, and diabetic macular edema. These three eye diseases could be identified without any labeling or modification using the Au/ZnONRs/G SERS sensor and the computational algorithm incorporating a support vector machine and multivariate statistical prediction. Therefore, these findings indicate that our label-free, highly reproducible and flexible Au/ZnONRs/G SERS-functionalized sensor supported by a multivariate statistics-derived bioclassification method has great potential in POCT applications for identifying eye diseases.

Controlling successive ionic layer absorption and reaction cycles to optimize silver nanoparticle-induced localized surface plasmon resonance effects on the paper strip.

This study investigates why a silver nanoparticle (SNP)-induced surface-enhanced Raman scattering (SERS) paper chip fabricated at low successive ionic layer absorption and reaction (SILAR) cycles leads to a high SERS enhancement factor (7×108) with an inferior nanostructure and without generating a hot spot effect. The multi-layered structure of SNPs on cellulose fibers, verified by magnified scanning electron microscopy (SEM) and analyzed by a computational simulation method, was hypothesized as the reason. The pattern of simulated local electric field distribution with respect to the number of SILAR cycles showed good agreement with the experimental Raman intensity, regardless of the wavelength of the excitation laser sources. The simulated enhancement factor at the 785-nm excitation laser source (2.8×109) was 2.5 times greater than the experimental enhancement factor (1.1×109). A 532-nm excitation laser source exhibited the highest maximum local electric field intensity (1.9×1011), particularly at the interparticle gap called a hot spot. The short wavelength led to a strong electric field intensity caused by strong electromagnetic coupling arising from the SNP-induced local surface plasmon resonance (LSPR) effects through high excitation energy. These findings suggest that our paper-based SILAR-fabricated SNP-induced LSPR model is valid for understanding SNP-induced LSPR effects.

Label-free optical detection of age-related and diabetic oxidative damage in human aqueous humors.

In this study, we investigate the biochemical characteristics of oxidative stress in age-related macular degeneration (AMD) and diabetic retinopathy (DR) by analyzing aqueous humors. Nondiabetic cataract aqueous humor was used as the control. The level of oxidative damage was evaluated based on changes in Raman spectral intensity. Seven prominent peaks were detected at 1002, 1043, 1062, 1352, 1419, 1454, and 1656 cm-1 . We proposed four multimodal biomarkers to distinguish these peaks based on the ratios of Raman intensities in two wavelengths, including CHO (C-O stretching or C-O-H bending modes), AG (adenine and guanine), PRO-AG (protein and AG), and PHEα (phenylalanine symmetric ring breath and amide I α-helix) markers. The presence of oxidative damage was detected by CHO and AG markers associated with C-O stretching, C-O-H bending modes in carbohydrates (1043 cm-1 ), and the nucleic acids adenine and guanine (1352 cm-1 ), respectively. DR-related oxidative damage was identified by PRO-AG and PHEα markers associated with adenine, guanine, and protein components (1419 and 1454 cm-1 ) and amide I α-helix protein structure (1656 cm-1 ), respectively. AMD-related oxidative damage was identified by four biomarkers. Four multimodal biomarkers with simple linear threshold values achieved high sensitivity of 100% and high specificity of 100% for classifying oxidative stress-induced AMD and DR diseases. Therefore, Raman-based label-free optical detection is effective for detecting the presence of age-related or diabetic oxidative damage in aqueous humor.

Instrument-Free Synthesizable Fabrication of Label-Free Optical Biosensing Paper Strips for the Early Detection of Infectious Keratoconjunctivitides.

We introduce a surface-enhanced Raman scattering (SERS)-functionalized, gold nanoparticle (GNP)-deposited paper strip capable of label-free biofluid sensing for the early detection of infectious eye diseases. The GNP biosensing paper strip was fabricated by the direct synthesis and deposition of GNPs on wax-divided hydrophilic areas of a permeable porous substrate through a facile, power-free synthesizable, and highly reproducible successive ionic layer absorption and reaction (SILAR) technique. To maximize localized surface plasmon resonance-generated SERS activity, the concentration of the reactive solution and number of SILAR cycles were optimized by controlling the size and gap distance of GNPs and verified by computational modeling with geometrical hypotheses of Gaussian-estimated metallic nanoparticles. The responses of our SERS-functionalized GNP paper strip to Raman intensities exhibited an enhancement factor of 7.8 × 10(8), high reproducibility (relative standard deviation of 7.5%), and 1 pM 2-naphthalenethiol highly sensitive detection limit with a correlation coefficient of 0.99, achieved by optimized SILAR conditions including a 10/10 mM/mM HAuCl4/NaBH4 concentration and six SILAR cycles. The SERS-functionalized GNP paper is supported by a multivariate statistics-preprocessed machine learning-judged bioclassification system to provide excellent label-free chemical structure sensitivity for identifying infectious keratoconjunctivitis. The power-free synthesizable fabrication, label-free, rapid analysis, and high sensitivity feature of the SILAR-fabricated SERS-functionalized GNP biosensing paper strip makes it an excellent alternative in point-of-care applications for the early detection of various infectious diseases.

Facile Fabrication of a Silver Nanoparticle Immersed, Surface-Enhanced Raman Scattering Imposed Paper Platform through Successive Ionic Layer Absorption and Reaction for On-Site Bioassays.

We introduce a novel, facile, rapid, low-cost, highly reproducible, and power-free synthesizable fabrication method of paper-based silver nanoparticle (AgNP) immersed surface-enhanced Raman scattering (SERS) platform, known as the successive ionic layer absorption and reaction (SILAR) method. The rough and porous properties of the paper led to direct synthesis of AgNPs on the surface as well as in the paper due to capillary effects, resulting in improved plasmon coupling with interparticles and interlayers. The proposed SERS platform showed an enhancement factor of 1.1 × 10(9), high reproducibility (relative standard deviation of 4.2%), and 10(-12) M rhodamine B highly sensitive detection limit by optimizing the SILAR conditions including the concentration of the reactive solution (20/20 mM/mM AgNO3/NaBH4) and the number of SILAR cycles (six). The applicability of the SERS platform was evaluated using two samples including human cervical fluid for clinical diagnosis of human papillomavirus (HPV) infection, associated with cervical cancer, and a malachite green (MG) solution for fungicide and parasiticide in aquaculture, associated with human carcinogenesis. The AgNP-immersed SERS-functionalized platform using the SILAR technique allowed for high chemical structure sensitivity without additional tagging or chemical modification, making it a good alternative for early clinical diagnosis of HPV infection and detection of MG-activated human carcinogenesis.