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The development of new methods of identification of active pharmaceutical ingredients (API) is a subject of paramount importance for research centers, the pharmaceutical industry, and law enforcement agencies. Here, a system for identifying and classifying pharmaceutical tablets containing acetaminophen (AAP) by brand has been developed. In total, 15 tablets of 11 brands for a total of 165 samples were analyzed. Mid-infrared vibrational spectroscopy with multivariate analysis was employed. Quantum cascade lasers (QCLs) were used as mid-infrared sources. IR spectra in the spectral range 980-1600 cm-1 were recorded. Five different classification methods were used. First, a spectral search through correlation indices. Second, machine learning algorithms such as principal component analysis (PCA), support vector classification (SVC), decision tree classifier (DTC), and artificial neural network (ANN) were employed to classify tablets by brands. SNV and first derivative were used as preprocessing to improve the spectral information. Precision, recall, specificity, F1-score, and accuracy were used as criteria to evaluate the best SVC, DEE, and ANN classification models obtained. The IR spectra of the tablets show characteristic vibrational signals of AAP and other APIs present. Spectral classification by spectral search and PCA showed limitations in differentiating between brands, particularly for tablets containing AAP as the only API. Machine learning models, specifically SVC, achieved high accuracy in classifying AAP tablets according to their brand, even for brands containing only AAP.
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Acetaminofén , Aprendizaje Automático , Análisis de Componente Principal , Espectrofotometría Infrarroja , Comprimidos , Acetaminofén/química , Acetaminofén/análisis , Comprimidos/química , Espectrofotometría Infrarroja/métodos , Redes Neurales de la Computación , Algoritmos , Máquina de Vectores de SoporteRESUMEN
In the fields of Security and Defense, explosive traces must be analyzed at the sites of the terrorist events. The persistence on surfaces of these traces depends on the sublimation processes and the interactions with the surfaces. This study presents evidence that the sublimation process of these traces on stainless steel (SS) surfaces is very different than in bulk quantities. The enthalpies of sublimation of traces of four highly energetic materials: triacetone triperoxide (TATP), 2,4-dinitrotoluene (DNT), 2,4,6-trinitrotoluene (TNT), and 1,3,5- trinitrohexahydro-s-triazine (RDX) deposited on SS substrates were determined by optical fiber coupled-grazing angle probe Fourier Transform Infrared (FTIR) Spectroscopy. These were compared with enthalpies of sublimation determined by thermal gravimetric analysis for bulk amounts and differences between them were found. The sublimation enthalpy of RDX was very different for traces than for bulk quantities, attributed to two main factors. First, the beta-RDX phase was present at trace levels, unlike the case of bulk amounts which consisted only of the alpha-RDX phase. Second, an interaction between the RDX and SS was found. This interaction energy was determined using grazing angle FTIR microscopy. In the case of DNT and TNT, bulk and traces enthalpies were statistically similar, but it is evidenced that at the level of traces a metastable phase was observed. Finally, for TATP the enthalpies were statistically identical, but a non-linear behavior and a change of heat capacity values different from zero was found for both trace and bulk phases.
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Sustancias Explosivas/química , Modelos Químicos , Algoritmos , Sustancias Explosivas/síntesis química , Espectroscopía Infrarroja por Transformada de Fourier , Termogravimetría , Difracción de Rayos XRESUMEN
Mid-infrared laser spectroscopy was used to investigate common bacteria encountered in biopharmaceutical industries. The study involved the detection of bacteria using quantum cascade laser spectroscopy coupled to a grazing angle probe (QCL-GAP). Substrates similar to surfaces commonly used in biopharmaceutical industries were used as support media for the samples. Reflectance measurements were assisted by Multivariate Analysis (MVA) to assemble a powerful spectroscopic technique with classification and identification resources. The species analyzed, Staphylococcus aureus, Staphylococcus epidermidis, and Micrococcus luteus, were used to challenge the technique's capability to discriminate from microorganisms of the same family. Principal Components Analysis and Partial Least Squares-Discriminant Analysis differentiated between the bacterial species, using QCL-GAP-MVA as the reference. Spectral differences in the bacterial membrane were used to determine if these microorganisms were present in the samples analyzed. Results herein provided effective discrimination for the bacteria under study with high sensitivity and specificity.
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Rayos Láser , Análisis Multivariante , Análisis de Componente Principal , Staphylococcus epidermidis/aislamiento & purificación , Staphylococcus aureus/aislamiento & purificación , Micrococcus luteus/aislamiento & purificación , Microbiología Industrial , Análisis Espectral , Análisis DiscriminanteRESUMEN
Arterial hypertension (AH) is a multifactorial and asymptomatic disease that affects vital organs such as the kidneys and heart. Considering its prevalence and the associated severe health repercussions, hypertension has become a disease of great relevance for public health across the globe. Conventionally, the classification of an individual as hypertensive or non-hypertensive is conducted through ambulatory blood pressure monitoring over a 24-h period. Although this method provides a reliable diagnosis, it has notable limitations, such as additional costs, intolerance experienced by some patients, and interferences derived from physical activities. Moreover, some patients with significant renal impairment may not present proteinuria. Accordingly, alternative methodologies are applied for the classification of individuals as hypertensive or non-hypertensive, such as the detection of metabolites in urine samples through liquid chromatography or mass spectrometry. However, the high cost of these techniques limits their applicability for clinical use. Consequently, an alternative methodology was developed for the detection of molecular patterns in urine collected from hypertension patients. This study generated a direct discrimination model for hypertensive and non-hypertensive individuals through the amplification of Raman signals in urine samples based on gold nanoparticles and supported by chemometric techniques such as partial least squares-discriminant analysis (PLS-DA). Specifically, 162 patient urine samples were used to create a PLS-DA model. These samples included 87 urine samples from patients diagnosed with hypertension and 75 samples from non-hypertensive volunteers. In the AH group, 35 patients were diagnosed with kidney damage and were further classified into a subgroup termed (RAH). The PLS-DA model with 4 latent variables (LV) was used to classify the hypertensive patients with external validation prediction (P) sensitivity of 86.4%, P specificity of 77.8%, and P accuracy of 82.5%. This study demonstrates the ability of surface-enhanced Raman spectroscopy to differentiate between hypertensive and non-hypertensive patients through urine samples, representing a significant advance in the detection and management of AH. Additionally, the same model was then used to discriminate only patients diagnosed with renal damage and controls with a P sensitivity of 100%, P specificity of 77.8%, and P accuracy of 82.5%.
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Hipertensión , Enfermedades Renales , Nanopartículas del Metal , Humanos , Espectrometría Raman/métodos , Oro , Monitoreo Ambulatorio de la Presión Arterial , Nanopartículas del Metal/química , Enfermedades Renales/diagnóstico , Urinálisis/métodos , Hipertensión/orinaRESUMEN
In this study, a mechanism for the uncatalyzed reaction between acetone and hydrogen peroxide is postulated. The reaction leads to the formation of the important homemade explosives collectively known as cyclic acetone peroxides (CAP). The proposed mechanistic scheme is based on Raman, GC-MS, and nuclear magnetic resonance measurements, and it is supported by ab initio density functional theory (DFT) calculations. The results demonstrate that the proposed mechanism for the uncatalyzed formation reaction of CAP occurs in three steps: monomer formation, polymerization of the 2-hydroperoxipropan-2-ol monomer, and cyclization. The temporal decay of the intensities of important assigned-bands is in excellent agreement with the proposed mechanism. Previous reports also confirm that the polymerization step is favored in comparison to other possible pathways.
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During coal mining activities, many compounds are released into the environment that can negatively impact human health. Particulate matter, polycyclic aromatic hydrocarbons (PAHs), metals, and oxides are part of the complex mixture that can affect nearby populations. Therefore, we designed this study to evaluate the potential cytotoxic and genotoxic effects in individuals chronically exposed to coal residues from peripheral blood lymphocytes and buccal cells. We recruited 150 individuals who lived more than 20 years in La Loma-Colombia and 120 control individuals from the city of Barranquilla without a history of exposure to coal mining. In the cytokinesis-block micronucleus cytome (CBMN-Cyt) assay, significant differences in the frequency of micronucleus (MN), nucleoplasmic bridge (NPB), nuclear bud (NBUD), and apoptotic cells (APOP) were observed between the two groups. In the buccal micronucleus cytome (BM-Cyt) assay, a significant formation of NBUD, karyorrhexis (KRX), karyolysis (KRL), condensed chromatin (CC), and binucleated (BN) cells was observed in the exposed group. Considering the characteristics of the study group, a significant correlation for CBMN-Cyt was found between NBUD and vitamin consumption, between MN or APOP and meat consumption, and between MN and age. Moreover, a significant correlation for BM-Cyt was found between KRL and vitamin consumption or age, and BN versus alcohol consumption. Using Raman spectroscopy, a significant increase in the concentration of DNA/RNA bases, creatinine, polysaccharides, and fatty acids was detected in the urine of individuals exposed to coal mining compared to the control group. These results contribute to the discussion on the effects of coal mining on nearby populations and the development of diseases due to chronic exposure to these residues.
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Antineoplásicos , Minas de Carbón , Exposición Profesional , Humanos , Exposición Profesional/análisis , Mucosa Bucal , Pruebas de Micronúcleos/métodos , Daño del ADN , Linfocitos , Antineoplásicos/farmacologíaRESUMEN
Plants growing in the Caribbean, Rubia tinctorum, Lippia dulcis and Spermacoce remota, were used in vitro to remove TNT from culture media. Plants were found to be resistant to high TNT levels. S. remota was able to remove TNT in less than 48 h. Part of the TNT was physically removed from the culture media by evaporation.
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Sustancias Explosivas/metabolismo , Lippia/metabolismo , Rubiaceae/metabolismo , Contaminantes del Suelo/metabolismo , Trinitrotolueno/metabolismo , Biodegradación Ambiental , Región del Caribe , Sustancias Explosivas/análisis , Lippia/crecimiento & desarrollo , Rubia/crecimiento & desarrollo , Rubia/metabolismo , Rubiaceae/crecimiento & desarrollo , Contaminantes del Suelo/análisis , Trinitrotolueno/análisisRESUMEN
Silver, gold, copper and platinum nanoparticles (NPs) were grown on surfaces in the form of patterns by the exposure of laser radiation onto droplets of metal ion solutions and the aid of a reducing agent. The generation of patterns from metallic NPs was achieved by combining induced growth of NPs and nanostructures by laser incidence directly on surfaces and optical image formation techniques for transferring the patterns. Near-UV (363.8 nm) and visible (532 nm) laser wavelengths were used for the laser-induced growth of NPs into microstructures on glass, quartz, stainless steel, silicon, and gold-on-silicon substrates. The sizes of the patterns formed were on the micrometer scale and the sizes of the transferred patterns were on the millimeter scale. The patterns formed were generated by optical transference of image and interference of laser beams. Ag and Au substrates were highly active in surface enhanced Raman spectroscopy (SERS). The enhanced Raman activity was measured for SERS probe molecules: 9H-purin-6-amine (adenine) and 1,2-bis (4-pyridyl)-ethane analytes on Ag and Au substrates, respectively. The enhancement factors obtained were 1.8×10(5) and 6.2×10(6), respectively.
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The process analytical technology (PAT) initiative proposed by the US Food and Drug Administration (FDA) suggests innovative methods to better understand pharmaceutical processes. The development of analytical methods that quantify active pharmaceutical ingredients (APIs) in powders and tablets is fundamental to monitoring and controlling a drug product's quality. Analytical methods based on vibrational spectroscopy do not require sample preparation and can be implemented during in-line manufacturing to maintain quality at each stage of operations. In this study, a mid-infrared (MIR) quantum cascade laser (QCL) spectroscopy-based protocol was performed to quantify ibuprofen in formulations of powder blends and tablets. Fourteen blends were prepared with varying concentrations from 0.0% to 21.0% (w/w) API. MIR laser spectra were collected in the spectral range of 990 to 1600 cm-1. Partial least squares (PLS) models were developed to correlate the intensities of vibrational signals with API concentrations in powder blends and tablets. PLS models were evaluated based on the following figures of merit: correlation coefficient (R2), root mean square error of calibration, root mean square error of prediction, root mean square error of cross-validation, and relative standard error of prediction. QCL assisted by multivariate analysis was demonstrated to be accurate and robust for analysis of the content and blend uniformity of pharmaceutical compounds.
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Standoff infrared and Raman spectroscopy (SIRS and SRS) detection systems were designed from commercial instrumentation and successfully tested in remote detection of high explosives (HE). The SIRS system was configured by coupling a Fourier-transform infrared interferometer to a gold mirror and detector. The SRS instrument was built by fiber coupling a spectrograph to a reflective telescope. HE samples were detected on stainless steel surfaces as thin films (2-30 microg/cm(2)) for SIRS experiments and as particles (3-85 mg) for SRS measurements. Nitroaromatic HEs: TNT, DNT, RDX, C4, and Semtex-H and TATP cyclic peroxide homemade explosive were used as targets. For the SIRS experiments, samples were placed at increasing distances and an infrared beam was reflected from the stainless steel surfaces coated with the target chemicals at an angle of approximately 180 degrees from surface normal. Stainless steel plates containing TNT and RDX were first characterized for coverage distribution and surface concentration by reflection-absorption infrared spectroscopy. Targets were then placed at the standoff distance and SIRS spectra were collected in active reflectance mode. Limits of detection (LOD) were determined for all distances measured for the target HE. LOD values of 18 and 20 microg/cm(2) were obtained for TNT and RDX, respectively, for the SIR longest standoff distance measured. For SRS experiments, as low as 3 mg of TNT and RDX were detected at 7 m source-target distance employing 488 and 514.5 nm excitation wavelengths. The first detection and quantification study of the important formulation C4 is reported. Detection limits as function of laser powers and acquisition times and at a standoff distance of 7 m were obtained.
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Mid-infrared (MIR) laser spectroscopy was used to detect the presence of residues of high explosives (HEs) on fabrics. The discrimination of the vibrational signals of HEs from a highly MIR-absorbing substrate was achieved by a simple and fast spectral evaluation without preparation of standards using the classical least squares (CLS) algorithm. Classical least squares focuses on minimizing the differences between the spectral features of the actual spectra acquired using MIR spectroscopy and the spectral features of calculated spectra modeled from linear combinations of the spectra of neat components: HEs, fabrics, and bias. Samples in several combinations of cotton fabrics/HEs were used to validate the methodology. Several experiments were performed focusing on binary, ternary, and quaternary mixtures of TNT, RDX, PETN, and fabrics. The parameters obtained from linear combinations of the calculated spectra were used to perform discrimination analyses and to determine the sensitivity and selectivity of HEs with respect to the substrates and to each other. However, discrimination analysis was not necessary to achieve successful detection of HEs on cotton fabric substrates. The RDX signals ( mRDX > 0.02 mg) on cotton were used to calculate the limit of detection (LOD). The signal-to-noise ratios (S/N) calculated from the spectra of cotton dosed with decreasing masses of RDX until S/N ≈ 3 resulted in a LOD of 15-33 µg, depending on the vibrational band used. Linear fits generated by comparing the mass dosed RDX with the fraction predicted were also used to calculate the LOD based on the uncertainty of the blank and the slope. This procedure resulted in a LOD of 58 µg. Probably the most representative value of the method LOD was calculated using an interpolation of a threshold determined using the predicted average value for the blank plus 3.28 times the standard deviations ( p-value threshold) for low surface dosages of RDX (LOD = 40 µg). The contribution demonstrates that to achieve HE detection on fabrics using the proposed algorithm, i.e., determining the presence/absence of HEs on the substrates, the library must contain the spectra of HEs, substrates, and potential interferents or that these spectra be added to the models in the field. If the model does not contain the spectra of the fabric components, there is a high probability of finding false positives for clean samples (no HEs) and a low probability for failed detection in samples with HEs. More work will be required to demonstrate that these new approaches to HE detection work on real-world samples and when contaminating materials are present in the samples.
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The optical properties for crystalline films of the highly energetic material (HEM) hexahydro-1,3,5-trinitro-s-triazine, which is also known as RDX, deposited on gold (Au) and stainless steel (SS) substrates are presented. RDX has two important stable conformational polymorphs at room temperature: α-RDX and ß-RDX. The optical properties obtained in the present work correspond to thin film samples of predominantly ß-RDX polymorph. The infrared spectroscopic intensities measured showed significant differences in the ß-RDX crystalline films deposited on the two substrates with respect to the calculated real part of refractive index. The ß-RDX/Au crystalline films have a high dynamic response, which is characterized by the asymmetric stretching mode of the axial nitro groups, whereas for the ß-RDX/SS crystalline films, the dynamic response was mediated by the -N-NO2 symmetric stretch mode. This result provides an idea of how the electric field vector propagates through the ß-RDX crystalline films deposited on the two substrates.
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Quantum cascade laser spectroscopy was used to quantify active pharmaceutical ingredient content in a model formulation. The analyses were conducted in non-contact mode by mid-infrared diffuse reflectance. Measurements were carried out at a distance of 15 cm, covering the spectral range 1000-1600 cm(-1) Calibrations were generated by applying multivariate analysis using partial least squares models. Among the figures of merit of the proposed methodology are the high analytical sensitivity equivalent to 0.05% active pharmaceutical ingredient in the formulation, high repeatability (2.7%), high reproducibility (5.4%), and low limit of detection (1%). The relatively high power of the quantum-cascade-laser-based spectroscopic system resulted in the design of detection and quantification methodologies for pharmaceutical applications with high accuracy and precision that are comparable to those of methodologies based on near-infrared spectroscopy, attenuated total reflection mid-infrared Fourier transform infrared spectroscopy, and Raman spectroscopy.
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Láseres de Semiconductores , Preparaciones Farmacéuticas/análisis , Espectroscopía Infrarroja Corta/métodos , Calibración , Análisis de los Mínimos Cuadrados , Límite de Detección , Preparaciones Farmacéuticas/química , Reproducibilidad de los ResultadosRESUMEN
The fabrication of high-performance plasmonic nanomaterials for bio-sensing and trace chemical detection is a field of intense theoretical and experimental research. The use of metal-silicon nanopillar arrays as analytical sensors has been reported with reasonable results in recent years. The use of bio-inspired nanocomposite structures that follow the Fibonacci numerical architecture offers the opportunity to develop nanostructures with theoretically higher and more reproducible plasmonic fields over extended areas. The work presented here describes the nanofabrication process for a series of 40 µm × 40 µm bio-inspired arrays classified as asymmetric fractals (sunflower seeds and romanesco broccoli), bilaterally symmetric (acacia leaves and honeycombs), and radially symmetric (such as orchids and lily flowers) using electron beam lithography. In addition, analytical capabilities were evaluated using surface-enhanced Raman scattering (SERS). The substrate characterization and SERS performance of the developed substrates as the strategies to assess the design performance are presented and discussed.
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A quantum cascade laser spectrometer was used to obtain the reflection spectra of highly energetic materials (HEMs) deposited on nonideal, low-reflectivity substrates, such as travel-bag fabric (polyester), cardboard, and wood. Various deposition methods were used to prepare the standards and samples in the study. The HEMs used were the nitroaromatic explosive 2,4,6-trinitrotoluene (TNT), the aliphatic nitrate ester pentaerythritol tetranitrate (PETN), and the aliphatic nitramine 1,3,5-trinitroperhydro-1,3,5-triazine (RDX). Chemometrics algorithms were applied to analyze the recorded spectra. Partial least squares (PLS) regression analysis was used to find the best correlation between the infrared signals and the surface concentrations of the samples, and PLS combined with discriminant analysis (PLS-DA) was used to discriminate, classify, and identity similarities in the spectral datasets. Several preprocessing steps were applied to prepare the mid-infrared spectra of HEMs deposited on the target substrates. The results demonstrate that the infrared vibrational method described in this study is well suited for the rapid screening analysis of HEMs on low-reflectivity substrates when a supervised model has been previously constructed or when a reference spectrum of the clean substrate can be acquired to be subtracted from the HEM-substrate spectrum.
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A laser-mediated methodology for standoff infrared detection of threat chemicals is described in this article. Laser-induced thermal emissions (LITE) from vibrationally excited residue of highly energetic material (HEM) deposited on substrates were detected remotely. Telescope-based Fourier transform infrared (FT-IR) spectroscopy measurements were carried out on substrates containing small amounts of HEM at surface concentrations of 5-200 µg/cm(2). Target substrates of various thicknesses were heated remotely using a carbon dioxide laser, and their mid-infrared (mid-IR), thermally stimulated emission spectra were recorded after heating. The telescope was configured from reflective optical elements to minimize emission losses in the mid-IR frequencies. Spectral replicas were acquired at distances from 4 to 64 m using an FT-IR interferometer at 4 cm(-1) resolution. The laser power, laser exposure times, and acquisition time of the FT-IR interferometer were adjusted to improve the detection and identification of samples. The advantages of increasing the thermal emission were easily observed in the results. The signal intensities were proportional to the thickness of the coated surface (a function of the surface concentration) as well as the laser power and laser exposure time. The limits of detection obtained for the HEM studied were 140-21 µg/cm(2) at 4 m. Detection was achieved at 64 m for a surface concentration of 200 µg/cm(2).
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Gold and silver nanoparticles (NPs) were prepared in water, acetonitrile and isopropanol by laser ablation methodologies. The average characteristic (longer) size of the NPs obtained ranged from 3 to 70 nm. 4-Aminobenzebethiol (4-ABT) was chosen as the surface enhanced Raman scattering (SERS) probe molecule to determine the optimum irradiation time and the pH of aqueous synthesis of the laser ablation-based synthesis of metallic NPs. The synthesized NPs were used to evaluate their capacity as substrates for developing more analytical applications based on SERS measurements. A highly energetic material, TNT, was used as the target compound in the SERS experiments. The Raman spectra were measured with a Raman microspectrometer. The results demonstrate that gold and silver NP substrates fabricated by the methods developed show promising results for SERS-based studies and could lead to the development of micro sensors.
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A standoff detection system was assembled by coupling a reflecting telescope to a Fourier transform infrared spectrometer equipped with a cryo-cooled mercury cadmium telluride detector and used for detection of solid-phase samples deposited on substrates. Samples of highly energetic materials were deposited on aluminum substrates and detected at several collector-target distances by performing passive-mode, remote, infrared detection measurements on the heated analytes. Aluminum plates were used as support material, and 2,4,6-Trinitrotoluene (TNT) was used as the target. For standoff detection experiments, the samples were placed at different distances (4 to 55 m). Several target surface temperatures were investigated. Partial least squares regression analysis was applied to the analysis of the intensities of the spectra obtained. Overall, standoff detection in passive mode was useful for quantifying TNT deposited on the aluminum plates with high confidence up to target-collector distances of 55 m.
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Aluminio/química , Espectroscopía Infrarroja por Transformada de Fourier/métodos , Trinitrotolueno/química , Análisis de los Mínimos Cuadrados , Reproducibilidad de los ResultadosRESUMEN
Advances in nanofabrication have allowed the production of new and more reproducible substrates for the Raman detection of trace antimicrobials in water. The superior substrate uniformity combined with the ability to control surface morphology represents a significant step forward in the design of substrates with improved enhancement factors and trace-detection capabilities. The work presented herein successfully combines electron-beam lithography (EBL) and reactive ion-etching (RIE) protocols for the construction, testing, and validation of plasmonic hybrid morphology nanoarrays for the detection of arsenic antimicrobials in water. The fabricated substrates consist of 2500 µm(2) Ag-coated silicon dioxide (SiO2)/Si pillar nanoarrays of alternating hexagonal and elliptical features. Control of simple fabrication parameters such as inter-particle spacing (gap) and its orientation relative to the laser polarization vector (parallel or orthogonal) result in over a tenfold improvement in the apparent Raman response under optimized conditions. At a 633 nm excitation frequency, the best substrate performance was observed on parallel-oriented features with a 200 nm gap, with over one order of magnitude increase in the apparent surface-enhanced Raman scattering (SERS) signal relative to standard silver-polydimethylsiloxane (Ag-PDMS) nanocomposites. Monitoring of the characteristic As-C stretching band at 594 cm(-1) allowed the detection of arsenic antimicrobials in water well within the parts per million range. Calculated surface-enhancement factors (SEF) for this substrate, employing 532, 785, and 633 nm excitation wavelengths, was within five, six, and seven orders of magnitude, respectively. The effect of substrate morphology and nanofabrication process on the Raman enhancement factor is presented.
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Antiinfecciosos/análisis , Nanoestructuras/química , Nanotecnología/instrumentación , Espectrometría Raman/instrumentación , Ácido Arsanílico/análisis , Nanoestructuras/ultraestructura , Nanotecnología/métodos , Reproducibilidad de los Resultados , Dióxido de Silicio/química , Plata/química , Espectrometría Raman/métodosRESUMEN
This work focused on establishing the parameters for enhancing the Raman signals of DNA and RNA constituents: nitrogenous bases, nucleosides and nucleotides, using metallic nanoparticles as surface enhanced Raman scattering substrates. Silver nanospheres were synthesized using sodium borohydride as a reducing agent and sodium citrate as a capping agent. The prepared nanoparticles had a surface plasmon band at â¼384nm and an average size of 12±3nm. The nanoparticles' surface charge was manipulated by changing the pH of the Ag colloidal suspensions in the range of 1-13. Low concentrations as 0.7µM were detected under the experimental conditions. The optimum pH values were: 7 for adenine, 9 for AMP, 5 for adenosine, 7 for dAMP and 11 for deoxyadenosine.