Multi-component Detection Research Articles

Multicomponent Gas Detection Method via Dynamic Temperature Modulation Measurements Based on Semiconductor Gas Sensor

Leakage of organic gas in industrial environment can easily cause fire and explosion accidents. Rapid detection of gases type and concentration is the premise for emergency treatment of these situations. Typically, the single semiconductor sensor cannot detect multi-component gas. Here, a new multi-component gas detection method was proposed based on the temperature-response relationship of sensor. This method has low power consumption, low cost and long-term monitoring, which can guide the future exploration of deployable sensors. Firstly, the parameters were optimized according to cosine distance to reflect the maximum difference of temperature-response relationship. Then coordinate system transformation was carried out to further magnify the difference between gases. Finally, the multi-component gas was recognized by using rational taylor function fitting. As a proof-of-concept, we measured the type and concentration of toluene and butanone multi-component gas with mean error of 6.34&#x0025; and 4.32&#x0025; respectively. We analyzed the gas-sensing response mechanism, the theoretical support of the optimized parameters and the causes of local errors. As a universal method, binary component gas detection was <b>explored</b> containing toluene, butanone, acetic anhydride, acetone and diethyl ether.

The fiber ring laser intra-cavity gas sensor for C2H2 and CO2 detection based on photoacoustic spectroscopy

In this paper, a two-component gas sensing system in the resonant cavity of the fiber ring laser based on photoacoustic spectroscopy (PAS) is designed by embedding the PAS cell into the laser resonant cavity. A ring cavity erbium-doped fiber (EDF) laser is built in this system, combined with a longitudinal resonant PAS cell to detect the PAS signal, and a custom-designed wavelength modulator uses the fiber bragg grating (FBG) to paste the piezoelectric transducer (PZT) for scanning and modulating the gas absorption wavelength. The gas concentration is calculated by the second harmonic (2f) PAS signal. Based on time division multiplexing (TDM) technology, the acetylene (C2H2) and carbon dioxide (CO2) is detected respectively by the time-sharing operation of C-band and L-band EDFs for different wavelengths output. The time-sharing operation of the two wavelength laser is realized through optical switches, which effectively avoids the laser power loss and the instability of each wavelength caused by the mode competition phenomenon of multiple wavelengths. The detection performance of C2H2 and CO2 is implemented under normal temperature and pressure. The PAS signal intensity is further improved by optimizing the wavelength modulation amplitude and incident laser power. The linear fit (R2) and minimum detection limit (MDL) of C2H2 and CO2 are 0.99821, 728 ppbv, 0.9994 and 503 ppmv respectively. It shows that the two-component gas sensing system designed in this paper has a good linear response and high sensitivity, and plays an important role on the multi-component gas detection.

Multiplex Surface-Enhanced Raman Scattering: An Emerging Tool for Multicomponent Detection of Food Contaminants.

For survival and quality of human life, the search for better ways to ensure food safety is constant. However, food contaminants still threaten human health throughout the food chain. In particular, food systems are often polluted with multiple contaminants simultaneously, which can cause synergistic effects and greatly increase food toxicity. Therefore, the establishment of multiple food contaminant detection methods is significant in food safety control. The surface-enhanced Raman scattering (SERS) technique has emerged as a potent candidate for the detection of multicomponents simultaneously. The current review focuses on the SERS-based strategies in multicomponent detection, including the combination of chromatography methods, chemometrics, and microfluidic engineering with the SERS technique. Furthermore, recent applications of SERS in the detection of multiple foodborne bacteria, pesticides, veterinary drugs, food adulterants, mycotoxins and polycyclic aromatic hydrocarbons are summarized. Finally, challenges and future prospects for the SERS-based detection of multiple food contaminants are discussed to provide research orientation for further.

Overview of Status of Medical Device Registration and Quality Evaluation Requirements for Clinical Mass Spectrometry

Mass spectrometry technology is becoming an important tool for clinical analysis due to its high specificity, high sensitivity and high multi-component detection capability. The current applications of this technology are mainly in liquid chromatography-tandem mass spectrometry (LC-MS/MS), matrix-assisted laser desorptionionization time-of-flight mass spectrometry (MALDI-TOF-MS), inductively coupled plasma mass spectrometry (ICP-MS), gas chromatography-mass spectrometry (GC-MS) and the related in vitro diagnostic kits. At present, the number of medical device (MD) based on mass spectrometry technology is growing rapidly, especially the number of LC-MS/MS and MALDI-TOF-MS registered MD products, and the standardization of relevant product quality requirements is also being effectively carried out. In general, clinical mass spectrometry equipment is still mainly imported, and the equipment price is relatively high. The development of mass spectrometry kits is mainly based on imported platforms, and domestic equipment is still in its infancy; the further promotion of clinical application of mass spectrometry also depends on the progress of the automation and standardization of the analysis procedure. To investigate the detection performance of mass spectrometry systems, it is necessary to fully consider the characteristics of mass spectrometry technology itself.

Feature Extraction and Analysis of Speech Signal Based on Fractional Fourier Transform

The extraction of speech features is the basis of speech signal processing, and the extraction of speech features is to obtain the parameters representing speech signals through the analysis of speech signals. The shape information of the signal can be extracted and processed by selecting appropriate structural elements and adopting mathematical morphological transformation. Selecting different structural elements will result in different shape transformation results, thus extracting the shape information of different components. In this paper, the feature extraction and analysis of speech signals are further studied based on FRFT (fractional fourier transform). The simulation results show that in different noise environments, such as when the speech is bathed with signal-to-noise ratio of 0dB and 10dB respectively, the recognition rate of this method is higher than that of the traditional parametric method. In this paper, based on the strength of FRFT signal components, the component signals are detected one by one in order, and then according to the detection results, the strongest component signals are removed from the observed signals in order to reduce their influence on the weak component signals, thus improving the effectiveness and reliability of multi-component signal detection and parameter estimation.

Research Progress of Wide Tunable Bragg Grating External Cavity Semiconductor Lasers.

In this paper, we review the progress of wide tunable Bragg grating external cavity semiconductor lasers (BG-ECSLs). We concentrate on BG-ECSLs based on the wide tunable range for multicomponent detection. Wide tunable BG-ECSLs have many important applications, such as wavelength-division multiplexing (WDM) systems, coherent optical communications, gas detection and atom cooling. Wide tunability, narrow linewidth and a high side-mode suppression ratio BG-ECSLs have attracted much attention for their merits. In this paper, three main structures for achieving widely tunable, narrow linewidth, high side-mode suppression ratio BG-ECSLs are reviewed and compared in detail, such as the volume Bragg grating (VBG) structure, fiber Bragg grating (FBG) structure and waveguide Bragg grating (WBG) structure of ECSLs. The advantages and disadvantages of different structures of BG-ECSLs are analyzed. The results show that WBG-ECSLs are a potential way to realize the integration, small size, wide tuning range, stable spectral output and high side-mode suppression ratio laser output. Therefore, the use of WBG as optical feedback elements is still the mainstream direction of BG-ECSLs, and BG-ECSLs offer a further new option for multicomponent detection and multi-atoms cooling.

Research on Mid-Infrared External Cavity Quantum Cascade Lasers and Applications

In this paper, we review the progress of the development and application of external cavity quantum cascade lasers (ECQCLs). We concentrated on ECQCLs based on the wide tunable range for multi-component detection and applications. ECQCLs in the mid-infrared band have a series of unique spectral properties, which can be widely used in spectroscopy, gas detection, protein detection, medical diagnosis, free space optical communication, and so on, especially wide tuning range, the tuning range up to hundreds of wavenumbers; therefore, ECQCLs show great applications potential in many fields. In this paper, the main external cavity structures of ECQCLs are reviewed and compared, such as the Littrow structure, the Littman structure, and some new structures. Some new structures include the intra-cavity out-coupling structure, multimode interference (MMI) structure, and acousto-optic modulator (AOM) control structure. At the same time, the application research of ECQCLs in gas detection, protein detection, and industry detection are introduced in detail. The results show that the use of diffraction gratings as optical feedback elements can not only achieve wide tuning, but it also has low cost, which is beneficial to reduce the complexity of the laser structure. Therefore, the use of diffraction gratings as optical feedback elements is still the mainstream direction of ECQCLs, and ECQCLs offer a further new option for multi-component detection.

A miniaturized electrochemical device based on the nitrogen, carbon-codoped bimetal for real-time monitoring of acetaminophen and dopamine in urine

In-situ real-time detection of drug metabolites and biomolecules in hospitalized patients’ urine helps the doctors to monitor their physiological indicators and regulate the use of drug doses. In this work, nitrogen-doped carbon-supported bimetal was prepared into the screen-printed electrodes (SPEs) and applied for real-time monitoring of acetaminophen (AC) and dopamine (DA) in urine. Via one-step pyrolysis of the core-shell cubic precursor (Cu3[Co(CN)6]2@Co3[Co(CN)6]2, CuCo@CoCo), the nitrogen-doped carbon-supported bimetal (CuCo-NC) was formed. The bimetal composites presented twice higher catalytic activity than the counterparts with single metal. In addition, the nanocomposites exhibited strong conductivity after pyrolysis, promoting electron transport efficiency as indicated by impedance measurements. Accordingly, the CuCo-NC based sensor offered excellent sensitivity with the detection limits down to 50 nM and 30 nM at the detection range of 0.1–400 μM and 0.2–200 μM for detection of AC and DA, respectively. Finally, in combination with a miniaturized electrochemical device, the sensor was applied for in-situ real-time monitoring of AC and DA in the urinary bag for up to 12h. As compared with other techniques such as high-performance liquid chromatography, UV-spectrophotometry and fluorescence spectrometer, the biosensor demonstrated the advantages of real-time monitoring, easy operation and excellent portability. However, the multi-component detection and self-calibration function need to be further developed. This method paves a way for the continuous monitoring of drug metabolites and biomolecules of hospitalized patients.

Optimizing Evanescent Efficiency of Chalcogenide Tapered Fiber.

Evanescent wave absorption-based mid-infrared chalcogenide fiber sensors have prominent advantages in multicomponent liquid and gas detection. In this work, a new approach of tapered-fiber geometry optimization was proposed, and the evanescent efficiency was also theoretically calculated to evaluate sensing performance. The influence of fiber geometry (waist radius (Rw), taper length (Lt), waist deformation) on the mode distribution, light transmittance (T), evanescent proportion (TO) and evanescent efficiency (τ) is discussed. Remarkably, the calculated results show that the evanescent efficiency can be over 10% via optimizing the waist radius and taper length. Generally, a better sensing performance based on tapered fiber can be achieved if the proportion of the LP11-like mode becomes higher or Rw becomes smaller. Furthermore, the radius of the waist boundary (RL) was introduced to analyze the waist deformation. Mode proportion is almost unchanged as the RL increases, while τ is halved. In addition, the larger the micro taper is, the easier the taper process is. Herein, a longer waist can be obtained, resulting in larger sensing area which increases sensitivity greatly.

Component level signal segmentation method for multi-component fault detection in a wind turbine gearbox

Condition monitoring of a modern wind turbine gearbox is quite challenging as it comes with multiple stages which operate at different frequencies. A gearbox is made up of multiple components and fault diagnosis (single or multi-component) could be challenging owing to the interaction between the mating parts and the damaged component. In this investigation, a simplified signal segmentation technique that segments the non-stationary vibration signals to match a specific speed stage and component within a multi-stage gearbox is proposed. This technique improves the features within the dataset and allow even simpler algorithms to be more effective while performing fault diagnosis. The segmentation approach is also evaluated for its robustness with three different machine-learning algorithms, namely Decision tree, Support Vector Machine and Deep Neural Network. The overall classification accuracy of the datasets prepared with the proposed approach is found to be 97%, which is higher when compared to the conventional approach.

Multicomponent trace gas detection with hollow-core fiber photothermal interferometry and time-division multiplexing

We report a multicomponent photothermal gas sensor with a conjoined-tube hollow-core optical fiber gas cell. With a common Fabry-Perot probe interferometer and a common gas cell, simultaneous detection of methane, acetylene and ammonia can be achieved by time-division multiplexing. Experiments with a 15-cm-long hollow-core fiber demonstrated noise-equivalent concentration of 24.2 parts-per-billion (ppb) for methane, 11.6 ppb for acetylene, and 46.1 ppb for ammonia. The dynamic range is measured to be around 5 orders of magnitude. The crosstalk issue is addressed by spectrum fitting. Assisted with an air pump and a compact gas chamber, the response time of less than 10 s is achieved.

From Passive Signal Output to Intelligent Response: "On-Demand" Precise Imaging Controlled by Near-Infrared Light.

"On-demand" accurate imaging of multiple intracellular miRNAs will significantly improve the detection reliability and accuracy. However, the "always-active" design of traditional multicomponent detection probes enables them to passively recognize and output signals as soon as they encounter targets, which will inevitably impair the detection accuracy and, inevitably, result in false-positive signals. To address this scientific problem, in this work, we developed a near-infrared (NIR) light-activated multicomponent detection intelligent nanoprobe for spatially and temporally controlled on-demand accurate imaging of multiple intracellular miRNAs. The proposed intelligent nanoprobe is composed of a rationally designed UV light-responsive triangular DNA nano sucker (TDS) and upconversion nanoparticles (UCNPs), named UCNPs@TDS (UTDS), which can enter cells autonomously through endocytosis and enable remote regulation of on-demand accurate imaging for multiple intracellular miRNAs using NIR light illumination at a chosen time and place. It is worth noting that the most important highlight of the UTDS we designed in this work is that it can resist nonspecific activation as well as effectively avoid false-positive signals and improve the accuracy of imaging of multiple intracellular miRNAs. Moreover, distinguishing different kinds of cell lines with different miRNA expressions levels can be also achieved through this NIR light-activated intelligent UTDS, showing feasible prospects in precise imaging and disease diagnosis.

A click-induced fluorescence-quenching sensor based on gold nanoparticles for detection of copper(Ⅱ) ion and ascorbic acid

Gold nanoparticles (AuNPs), as one of the major tools of fluorescence-quenching sensors, have been widely used in biochemical analysis through fluorescence resonance energy transfer (FRET) effect. With the development of chemistry and biochemistry, reaction-based fluorescent sensors have attracted increasing attention because of their unique selectivity, high sensitivity and rapid detection. Here we report a click-induced fluorescence-quenching sensor based on AuNPs for detection of copper ion (Cu2+) and ascorbic acid (AA). A fluorescent dye Rhodamine B-(CH2CH2O)4-azide (RB-PEG4-N3) is conjugated to the surface of AuNPs via Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) in the presence of Cu2+ and AA, leading to the fluorescence quenching of Rhodamine B. The sensor responds quickly (within less than 3 min). The fluorescent intensity linearly correlates with the concentration of Cu2+ in the range of 0–108 μM. The limit of detection (LOD) for Cu2+ is 5.8 μM. The concentration range for detection of AA is 0–3 mM. The LOD for AA is 0.13 mM. In addition, the application of the sensor is verified by performing detection in real samples such as fresh orange, juice, VC tablet, and lake water. This work expands the application of AuNPs-based fluorescence-quenching sensors for multi-component detection.

An Improved LC-MS/MS Method for the Analysis of Thirteen Cytostatics on Workplace Surfaces.

Cytostatics are drugs used in cancer treatment, which pose serious risks to healthcare workers. Dermal absorption via surface contamination is the key exposure route; thus, rapid, reliable, and validated analytical methods for multicomponent detection are crucial to identify the exposure risk. A surface-wipe-sampling technique compatible with hospitals’ safety requirements (gauze, 1 mL isopropanol) and a fast and simple extraction method (1 mL acetonitrile, 20 min ultrasonic bath, evaporation, reconstitution in 200 µL acetonitrile), coupled with liquid chromatography–tandem mass spectrometry analysis, were developed. It allowed identification and quantification of 13 cytostatics on surfaces: cyclophosphamide, doxorubicin, etoposide, ifosfamide, paclitaxel, bicalutamide, capecitabine, cyproterone, flutamide, imatinib, megestrol, mycophenolate mofetil, prednisone. Good linearity, sensitivity, and precision were achieved (R2 > 0.997, IDLs < 4.0 pg/cm2, average CV 16%, respectively). Accuracy for four model surfaces (melamine-coated wood, phenolic compact, steel 304, steel 316) was acceptable (80 ± 12%), except for capecitabine and doxorubicin. Global uncertainty is below 35% for concentrations above 100 pg/cm2 (except for capecitabine and doxorubicin)—a guidance value for relevant contamination. Method application in a Portuguese university hospital (28 samples) identified the presence of seven cytostatics, at concentrations below 100 pg/cm2, except for three samples. The widespread presence of cyclophosphamide evinces the necessity to review implemented procedures.

Integrated hand-held electrochemical sensor for multicomponent detection in urine

Electrochemical sensors have shown great advantage and application potential in point-of-care testing (POCT) related scenarios. However, some fatal problems plague its widespread utilization, which include the susceptibility of sensors to interference in real samples (e.g. pH), the contradiction between the limited objects detectable for most sensors and the requirement of multi-target analysis in most cases, and the complicated procedures in sensor preparation as well as in routine use. This paper contributed a tip-like electrochemical sensor prototype. By integrated with a commercial pipettor, it fulfilled semi-automatic assay procedure of sampling, detection and rinsing, thus saving operational time and manual work. The tip sensor owns the property of simple fabrication and is free from any modification of extra bio/chem materials. Moreover, built on multiple electrochemical signal outputs including open circuit potential, peak current and potential of specific electrochemical reaction, this work established a novel multi-component sensing strategy, wherein detection of uric acid (UA), urea and pH in urine samples was realized by using one single working electrode. The detection range for the above targets is 5.0~600 μM for UA, 4.0~8.0 for pH and 0.5~7.0 mM for urea with the detection limits (S/N = 3) of 0.05 μM for UA and 5.4 μM for urea, and the sensitivity of pH assay is 73 mV/pH. Notably, as variation of sample pH has impact on electrochemical analysis, the pH-related parameter was introduced for calibration to diminish such interference. The developed tip sensor and the novel sensing strategy may open a new window for electrochemical technology and broaden its application in POCT.

Simple and Sensitive Multi-components Detection Using Synthetic Nitrogen-doped Carbon Dots Based on Soluble Starch.

Although carbon dots (CDs) as fluorescent sensors have been widely exploited, multi-component detection using CDs without tedious surface modification is always a challenging task. Here, two kinds of nitrogen-doped CDs (NCD-m and NCD-o) based on soluble starch (SS) as carbon source were prepared through one-pot hydrothermal process using m-phenylenediamine and o-phenylenediamine as nitrogenous dopant respectively. Through fluorescence "on-off" mechanism of CDs, NCD-m and NCD-o could be used as a fluorescence sensor for detection of Fe 3+ and Ag + with LOD of 0.25 and 0.51μM, respectively. Additionally, NCD-m could be used for indirect detection of ascorbic acid (AA) with LOD of 5.02μM. Moreover, fluorescence intensity of NCD-m also exhibited the sensitivity to pH change from 2 to 13. More importantly, Both NCD-m and NCD-o had potential application for analysis of complicated real samples such as tap water, Vitamin C tablets and orange juice. Ultimately, the small size of NCD-m could contribute to reinforcing intracellular endocytosis, which allowed them to be used for bacteria imaging. Obviously, these easily obtainable nitrogen-doped CDs were able to be used for multi-components detection. Strategy for synthesis of nitrogen-doped carbon dots (NCDs) and a schematic for fabrication of as-prepared NCDs for detection of Fe 3+, Ag + and ascorbic acid (AA).

Research on LPI radar signal detection and parameter estimation technology

Modern radar signals mostly use low probability of intercept (LPI) waveforms, which have short pulses in the time domain, multicomponent properties, frequency hopping, combined modulation waveforms and other characteristics, making the detection and estimation of LPI radar signals extremely difficult, and leading to highly required significant research on perception technology in the battlefield environment. This paper proposes a visibility graphs (VG)-based multicomponent signals detection method and a modulation waveforms parameter estimation algorithm based on the time-frequency representation (TFR). On the one hand, the frequency domain VG is used to set the dynamic threshold for detecting the multicomponent LPI radar waveforms. On the other hand, the signal is projected into the time and frequency domains by the TFR method for estimating its symbol width and instantaneous frequency (IF). Simulation performance shows that, compared with the most advanced methods, the algorithm proposed in this paper has a valuable advantage. Meanwhile, the calculation cost of the algorithm is quite low, and it is achievable in the future battlefield.

Cavity Enhanced Multi-Channels Gases Raman Spectrometer.

Raman spectroscopy has the advantages of multi-component detection, with a simple device and wide concentration ranges, and it has been applied in environmental monitoring and gas logging. However, its low sensitivity has limited its further applications. In fact, the Raman signal is not weak, but the utilization efficiency of the Raman signal is low, and most of the signal is wasted. Given this, in this paper we report a cavity-enhanced multi-channel gas Raman spectrometer with an eight-sided cuvette. First, we simulated the Raman scattering intensity at angles from 30 degrees to 150 degrees. The simulation results showed that the signal intensity at an angle of 45° is 1.4 times that observed at 90°. Based on the simulation results, we designed a three-channel sample cell for higher sensitivity. The results of these experiments showed that the sensitivity could be increased by adding all signal together, and the limit of detection (LOD) for CO2 was 75 ppm, which is better than that of each channel. This paper thus presents a new method to enhance the Raman signal, which can be used in field applications.

High-Sensitivity Raman Gas Probe for In Situ Multi-Component Gas Detection.

Multiple reflection has been proven to be an effective method to enhance the gas detection sensitivity of Raman spectroscopy, while Raman gas probes based on the multiple reflection principle have been rarely reported on. In this paper, a multi-reflection, cavity enhanced Raman spectroscopy (CERS) probe was developed and used for in situ multi-component gas detection. Owing to signal transmission through optical fibers and the miniaturization of multi-reflection cavity, the CERS probe exhibited the advantages of in situ detection and higher detection sensitivity. Compared with the conventional, backscattering Raman layout, the CERS probe showed a better performance for the detection of weak signals with a relatively lower background. According to the 3σ criteria, the detection limits of this CERS probe for methane, hydrogen, carbon dioxide and water vapor are calculated to be 44.5 ppm, 192.9 ppm, 317.5 ppm and 0.67%, respectively. The results presented the development of this CERS probe as having great potential to provide a new method for industrial, multi-component online gas detection.

Simple and eco-friendly synthesis of crude orange-peel-derived carbon nanoparticles for detection of Fe3+ and ascorbic acid.

Although fluorescence sensors based on carbon dots (CDs) have been developed widely, multicomponent detection using CDs without extra and tedious surface modification remains a challenge. Here, the crude carbon nanoparticles (CPs) as a fluorescence sensor were prepared through one-pot hydrothermal process using orange peel as the precursor. The method was simple, rapid, economical, and eco-friendly given that such extra steps as dialysis and lyophilization were not required. By adding ethanol into the reaction solvent, the fluorescence properties of orange-peel-derived CPs as well as their sensitivity of detecting Fe3+ with a limit of detection of 0.25 μM were improved. Additionally, orange-peel-derived CPs could be used as a fluorescence sensor for detection of ascorbic acid (AA) with a LOD of 5 μM. More importantly, the proposed fluorescence methods were successfully used to qualitatively and quantitatively analyze Fe3+ and AA in real samples. Recovery of Fe3+ from tap water was within the range 97.2-105.4%. Conversely, recovery of AA from vitamin C tablets and orange juices laid within the ranges 97.7-99.3% and 93.2-97.6%, respectively.