The detection of molecules by surface-enhanced Raman spectroscopy (SERS) is dependent on the nanomaterial used to induce the enhancement effect. This depends on a variety of parameters of the substrate such as the metal used for their creation, their shape, size and size distribution, concentration, as well as the parameters of the solution, such as packing of the nanoparticles, the complexity of the sample, the solvent, etc. It is most crucial, that the parameters are kept constant to provide uniformity of the enhancement. this is crucial for the development of SERS as a reliable and quantitative technique for bioanalysis. Here, we have developed the silver-core and gold-shell nanoparticles, to serve as the enhancement material. The fabrication phase involved constant concentrations of chemicals stability of the solution physical parameters like stirring and heating, and differed only in the perturbation of the reagents addition kinetics. These nanoparticles were investigated further with their ability to measure the solutions of 2-naphtalenethiol in DMSO, as model for testing the variability of the signal due to the enhancement and the kinetics of the nanoparticle-sample solution during a routine Raman measurement procedure. The results indicate vast difference in the preference of the 2-naphthalenethiol to come into contact with the nanoparticles and the partial enhancement of DMSO in most cases, with an almost complete by-pass of the solvent and direct detection of the 2-naphthalenethiol in one case. Moreover, the kinetics of the measurement solution, or its stability during measurement, is provided.
KEYWORDS: Raman spectroscopy, Interference (communication), Signal processing, Principal component analysis, Denoising, Spectroscopy, Molecular spectroscopy, Signal to noise ratio, Light scattering, Chemical compounds, Modulation, Signal detection, Electronics
We present an overview of noise sources deteriorating the quality of the recorded biological Raman spectra and the ability to determine the specimen composition. The acquired Raman spectra exhibit intense additive noise components or drifts because of low intensity of the scattered light. Therefore we have to apply expensive or bulky measurement setups to limit their inherent noise or to apply additional signal processing to reduce random components after recording the spectra (e.g., Savitzky-Golay filtering, polynomial approximation, denoising by empirical mode decomposition). We present noise sources generated in detectors of Raman scattered photon stream. We consider the methods of background noise reduction by increasing averaging time when the background noise comprises of white noise and 1/f noise components. We consider how the background noise reduces the accuracy of chemical compounds estimation using Raman spectra and prediction model based on linear (e.g., Principal Component Analysis) or nonlinear (e.g., Support Vector Machine) methods. Finally, we give some remarks about synchronous detection and background noise reduction.
We present an surface-enhanced Raman spectroscopy (SERS) approach for detection of drugs of abuse in whole human blood. We utilize a near infrared laser with 830 nm excitation wavelength in order to reduce the influence of fluorescence on the spectra of blood. However, regular plasmon resonance peak of plasmonic nanoparticles, such as silver or gold fall in a much lower wavelength regime about 400 nm. Therefore, we have shifted the plasmon resonance of nanoparticles to match that of an excitation laser wavelength, by fabrication of the silver-core gold-shell nanoparticles. By combining the laser and plasmon resonance shift towards longer wavelengths we have achieved a great reduction in background fluorescence of blood. Great enhancement of Raman signal coming solely from drugs was achieved without any prominent lines coming from the erythrocytes. We have applied chemometric processing methods, such as Principal Component Analysis (PCA), to detect the elusive differences in the Raman bands which are specific for the investigated drugs. We have achieved good classification for the samples containing particular drugs (e.g., butalbital, α-hydroxyalprazolam). Furthermore, a quantitative analysis was carried out to assess the limit of detection (LOD) using Partial Least Squares (PLS) regression method. In conclusion, our LOD values obtained for each class of drugs was competitive with the gold standard GC/MS method.
KEYWORDS: Sensors, Molecules, Gas sensors, Diffusion, Biological and chemical sensing, Resistance, Stochastic processes, Statistical analysis, Thermometry, Chemical analysis
We present a short survey on fluctuation-enhanced gas sensing. We compare some of its main characteristics with those
of classical sensing. We address the problem of linear response, information channel capacity, missed alarms and false
alarms.
In this paper it is discussed the efficiency of harmonics detection in the precence of Gaussian noise by applying bispectrum function (higher-order spectrum). The proposed method is compared with the effectiveness obtained by the classical method that implements power spectrum density. The main results reported in this paper are, first, confirmation that the bispectrum function can reveal the harmonics overwelmed by Gaussian noise and, second, how this method is limited in practice. The details of the applied procedure are presented and discussed due to the random error of the bispectrum estimator and its method of calculation. The principles of the higher-order spectrum analysis are also pointed out.
Electrochemical noise (EN) has been intensively investigated for the last few decades. There are practical applications of EN measurements for corrosion recognition but the phenomenon needs still further research. The experimental results of correlation between the surface damages of the metal electrodes and the intensity of voltage fluctuations observed between two nominally identically prepared electrodes are presented. The sets of carbon steel electrodes were applied. Only the metal surfaces were exposed to the electrolyte. The low-frequency voltage noise was continuously registered and the pictures of the electrode surfaces were taken every 30 minutes. The pits, which were created on the metal surface, were detected by Matlab software and compared with the statistical parameters of the observed voltage noise. The acts of the individual pits creation were strictly related to the presence and intensity of transients, characteristic for meta-stable pitting processes in carbon steel.
The experimental setup is described. Some detailed remarks according to the applied detection algorithms of the metal damage are also included.
Nanoparticle films of PdxWO3, with x being 0.01 or 0.12, were made by dual-beam gas deposition. Resistance noise as well as dc resistance were measured during exposure to ethanol and hydrogen gas. For ethanol concentrations exceeding 50 ppm, changes in the resistance noise gave 300 times larger detection sensitivity than changes in the dc resistance. This sensitivity reached a maximum at 250 °C and was very reproducible for ethanol sensing.
The resistance fluctuations of sensors can give improved selectivity and sensibility and the analysis is limited to power spectrum density only. Non-Gaussian low frequency noise components can be observed in nanoparticle gas sensors especially if some of the characteristics length scales is in the submicron range. These components can be characterized by higher-order spectra (HOS). In this paper, bispectra and trispectra are used. The modulus and phase characteristics of the higher-order spectra of the observed resistance fluctuations are analyzed separately. The explored sensors consist of WO3 films, with Pd nanoparticles uniformly distributed in the oxide structure.
Corrosion in concrete can cause disastrous destructions of bridges and other constructions. Different methods of corrosion monitoring can be applied including electrochemical noise despite its disadvantageous limitations. Noise measurements enable continuous monitoring of corrosive conditions inside concrete and recognition when corrosion starts to make trouble there.
Results of electrochemical noise measurements in concrete are presented. Polarization resistance of carbon steel is estimated by current and voltage noise measurements. Changes of factor 2-4 of the estimated polarization resistance are recognized during time of noise registration. The observed changes in uniform corrosion rate can be identified by electrochemical noise analysis. Limitations of the applied method of polarization resistance evaluation are considered and presented.
KEYWORDS: Sensors, Molecules, Gases, Biological and chemical sensing, Chemical analysis, Gas sensors, Diffusion, Calibration, Stochastic processes, Resistance
Both selectivity and sensitivity of chemical sensors can be significantly improved by exploiting the information contained in microfluctuations present in the sensor system. We call our collection of methods to extract information from these microfluctuations Fluctuation-Enhanced Chemical Sensing. In this review paper we summarize our recent experimental and theoretical results using commercial Taguchi sensors, Surface Acoustic Wave (SAW) Devices and MOS-FET based sensors.
The stochastic component of chemical sensor signal contains valuable information that can be visualized not only by spectral analysis but also by using nonlinear characteristic components. The analysis of nonlinear stochastic components enables the extraction of physically interesting and useful features and may lead to significant improvements in selectivity and sensitivity. Various measures of nonlinearity are presented and estimated for sample sensor data obtained from commercial chemical sensors. Particular attention was paid to the bispectrum function that detects nonlinear and non-stationary components in the analyzed noise. The results suggest that bispectrum measurements provide valuable information about the nature of noise generation in chemical sensors. Moreover, we have found, by analyzing skewness and kurtosis distributions, that the measured time series were stationary.
Electrochemical corrosion processes can be investigated by observation of the charge flow between electrolyte and the corroding metal. Usually, the charge flow is observed as spontaneous current and voltage fluctuations (electrochemical noise) in a three-electrode setup. Different types of corrosion processes can be recognized by electrochemical noise analysis. Uniform corrosion rate can be evaluated by estimation of polarization resistance between metal and electrolyte. Local corrosion events (breakdowns of the passive layer) that produce characteristic transients observed in noise can be detected. The different methods of electrochemical noise analysis are presented. The limitations and advantages of the method for corrosion monitoring and research are underlined. The experimental results are also discussed.
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