Multichannel Detection Research Articles

Multiwavelength erbium-doped fiber laser using the polarization-hole-burning effect for multichannel acoustic detection.

We propose and demonstrate a novel, to the best of our knowledge, fiber-optic multipoint acoustic detection system based on a multiwavelength erbium-doped fiber (EDF) laser (MWEDFL) using the polarization-hole-burning effect with Fabry-Perot interferometers as the acoustic cavity-loss modulator. A polarization-wavelength-related filter is designed to assign a distinct polarization state to each laser wavelength. By adjusting the polarization state, the polarization-dependent loss and gain of each laser line are tuned to be equal, effectively suppressing the mode competition of EDF and enabling a stable MWEDFL. Each laser line serves as a separate channel for acoustic detection. Theoretical and experimental analyses are conducted to study the transient-response-amplification effect on the acoustic perturbation of the MWEDFL. The results show that the proposed MWEDFL exhibits an amplification effect on the sound-induced cavity-loss modulation, effectively enhancing the sensitivity by 13 dB compared to that obtained using an external-light-source demodulation method. In addition, the MWEDFL based on the PHB effect avoids cross talk between laser channels and can achieve high sensitivity and simultaneous multichannel acoustic detection.

Highly sensitive photoelectrochemical sensors for multichannel detection and uniform bioimaging based on fireworks-like silicon nanowires and its heterojunctions fabricated by MACE and sputtering processes

Photoelectrochemical (PEC) sensors have emerged as a promising candidate for biochemical detection. However, PEC sensors based on bulk semiconductors are limited by sensitivity and detection varieties, though they can provide uniform imaging; PEC sensors based on nanomaterials can meet the requirements of various analytes and sensitivity, but the inhomogeneity of their surface poses a challenge to imaging uniformity. In this work, metal-assisted chemical etching (MACE) and sputtering processes were used to directly fabricated PEC sensors with fireworks-like silicon nanowires (F-SiNWs) and their heterojunctions with excellent performance. Through regulating the etching and sputtering times, the structure and nanomaterials attachment of F-SiNWs can be well controlled. The photoelectric and sensing properties of F-SiNWs with different morphologies were investigated and optimized. Then, the sensor fabricated by optimal F-SiNWs can directly detect H2O2 and indirectly detect glucose under negative bias, while directly detect dopamine (DA) under positive bias. The detection of these three analytes do not interfere with each other, contributing to an excellent multichannel detection system. Subsequently, the multichannel detection of various secretions (H2O2, DA and glucose) of PC-12 cells was achieved by the sensor. Finally, the imaging uniformity of the sensor was demonstrated in different solutions. PEC bioimaging was successfully applied to monitor enzyme activity by bioimaging gradients and cell survival by bioimaging distribution. These results demonstrate the high sensitivity in multichannel detection and excellent stability and homogeneity in bioimaging of the sensor. Therefore, MACE and sputtering process can be a promising tool for constructing PEC sensor.

Fabrication of a 96-electrode array using carbon dioxide laser ablation

The 96 laser-induced multigraphene electrode (96L-MGE) integrated microwell plate (96 L-MGE-MP) is described. Each cell includes separate working, auxiliary, and reference electrodes, and the array sits on a poly-methyl methacrylate (PMMA) well. The 96 electrochemical cells were fabricated by laser ablation of polyimide adhesive tape, which created laser-induced graphene electrodes (L-GE). The microwell was produced using laser ablation of the PMMA sheet as well. The morphology and electrochemical characterization of L-GE were controlled by tuning the laser processing. L-GE fabricated at laser power–laser speed ratios of 0.008–0.02 W s mm–1displayed good electrochemical behaviors. Under the optimal condition of L-GE fabrication, the measured L-GE surface roughness was 475.47 nm. The 96 L-MGE can be fabricated in 24.2 min and is compatible with various analytes. 10 benchmark redox compounds were shown as electrocatalytic examples. The performance of each analyte was investigated by voltammetry. As proof of concept, 96 L-MGE-MP was connected to a 96× connector for multichannel detection. The RSD of the 96 L-MGE-MPwas below 5.3%, which demonstrated good fabrication reproducibility.

Radioactive source localization employing resistive electrode array (REA) detector.

Objective.In this feasibility study, we explore an application of a Resistive Electrode Array (REA) for localization of a radioactive point source. The inverse problem posed by multichannel REA detection is studied from mathematical perspective and involves the questions of the minimal configuration of the conductive leads that can achieve this goal. The basic configuration consists of a circularly shaped REA with four opposite electrical lead-pairs at its perimeter.Approach.A robust mathematical reconstruction method for a 3D radioactive source relative to the REA is presented. The characteristic empirical Green's function for the detector response of the REA is determined by numerically solving Laplace equations with appropriate boundary conditions. Based on this model, Monte Carlo simulations of the inverse problem with Gaussian noise are performed and the overall accuracy of the localization is investigated.Main results.The results show a 3D error distribution of localization which is uniform in the (x,y)-plane of the REA and strongly correlated in the orthogonalz-axis. The overall accuracy decreases with higher distance of the source to the detector which is intuitive due to approximate flux dependence following the inverse square law. Further, a saturation in accuracy regarding the number of electrical leads and a linear dependence of the reconstruction error on the measurement noise level are observed.Significance.A broad range of REA detector configurations and their characteristics are investigated by this study for radioactive source localization allowing diverse practical applications with detector diameters ranging from millimeters to meters.

Collaborative biofluid analysis based multi-channel integrated wearable detection system for the monitoring of wound infection

The infection monitoring of chronic wounds can effectively improve the quality of wound care. However, the widely used single variable intermittent monitoring of wound provides little available information, which leads to inaccurate diagnosis and untimely warnings. In this study, a collaborative biofluid analysis based multi-channel integrated wearable detection system was constructed for the continuous detection of analytes such as pH, uric acid (UA), and C-reactive protein (CRP) in wound exudates with time division multiplexing. Based on the functionally modification with nanomaterials, integrated screen-printed electrodes (iSPE) with three working electrodes were designed for the collaboratively analyzing of wound exudates. Through the development of integrated circuits, the multi-channel wearable detection printed circuit board was constructed. With a self-designed interface, this iSPE was stably connected to the printed circuit board and realized the detection of three targets in the range of pH 3–8, UA concentrations 5–500 μmol/L, and CRP concentrations 1–1000 ng/mL at the same time. Combined with a smartphone, these results were collaborated analyzed and transferred for health management. Therefore, this integrated wearable multi-channel detection system can provide reliable and continuous evaluations for early warning of infection and further treatment of chronic wounds.

High-speed rail defect detection using multi-frequency exciting 3D ACFM

High load wheel-rail friction leads to surface defects on the rail, which requires an accuracy non-destructive testing (NDT) technology to prevent rail fracture and even major safety accidents. Alternating current field measurement (ACFM) has attracted attention due to its high detection precision and low sensitivity of lift-off and velocity effects. The paper proposes a multi-frequency, three-dimensional (3D) ACFM detection system that can obtain abundant detection information for multi-frequency comprehensive evaluation to improve detection accuracy. The system mainly includes an expandable phase-locked amplifier module and an adjustable multi-frequency signal source module, which provides a hardware IQ demodulation acceleration platform for multi-frequency and multi-channel ACFM detection to obtain enough defect signals for analysis. Analysis of the speed effect indicates that increasing the excitation frequency can improve the stability of the detection signal. We design a quantitative evaluation model for defects with a depth of 2–8 mm and surface angle between 30° and 75°.

Mechanistic and Kinetic Measurements of Elementary Surface Reactions Using Temperature-Programmed X-ray Photoelectron Spectroscopy.

This paper describes a method by which surface-reaction kinetics can be measured by slowly and precisely ramping up the surface temperature at a constant rate while simultaneously collecting X-ray photoelectron spectra (XPS). This approach results in the collection of a large amount of data over relatively small temperature steps to produce quasi-continuous kinetic data. The method is illustrated for the desorption and reaction of diethyl disulfide (DEDS) on a Au(111) substrate in ultrahigh vacuum, where the results can be compared with previous conventional temperature-programmed desorption (TPD) data from Au(111). Experiments were carried out using a double-pass cylindrical-mirror analyzer with a channeltron detector to demonstrate how this approach can be implemented in a routine, multitechnique vacuum chamber. The approach will be even more effective in a more modern, specialized XPS apparatus with high-transmission hemispherical analyzers with multichannel array detectors, which will enable the spectra of several elements to be measured simultaneously. The results yielded an activation energy for multilayer desorption of DEDS of 41 ± 1 kJ/mol, with a pre-exponential factor of 8 ± 7 × 1012 s-1, an activation energy of 53 ± 6 kJ/mol and pre-exponential factor of 9 ± 8 × 1013 s-1 for monolayer desorption and an activation energy of 90 ± 6 kJ/mol with a prefactor of 1.0 ± 0.3 × 1015 s-1 for the reaction of adsorbed ethyl thiolate species to adsorbed DEDS. While these results were collected for a system for which the kinetic data could have been obtained using conventional TPD, this method can be more usefully applied to those surface reaction processes that do not rely on the formation of desorption products. This system, having been previously studied by TPD, facilitates a comparison with results obtained by conventional methods.

Simultaneous detection of dynamic calcium signaling and ERK activity in living cells.

Calcium (Ca2+) is a universal second messenger in eukaryotic cells, and extracellular regulated protein kinases (ERK) are the core component of the mitogen-activated protein kinase (MAPK) signaling cascade. Both are involved in numerous physiological and pathological processes, such as organogenesis, tumorigenesis, proliferation, migration and apoptosis. Over the past decade, it has been found that calcium signaling can regulate the ERK activity through multiple mechanisms, and conversely, ERK signaling transduction can also affect the triggering and intensity of calcium signaling. However, there are few reports on how to perform real-time synchronous detection of these two signals. Here we described a method for dynamically and synchronously recording calcium signals and ERK activity in living cells, utilizing stable expression of multiple genetically-encoded probes and multi-channel synchronous detection technology using confocal microscopy. The protocol can be useful to address the spatiotemporal encoding dynamic mechanism of calcium signaling and ERK activity in single or multiple cells, and to reveal the interaction and causal characteristics of these two signals.

Engineering a universal and fully automatic analyzer for multichannel and on-site biochemical detection in body fluids.

Rising concerns over wellness and aging have heightened the demand for convenient and efficient on-site health monitoring and disease screening. Current research, focused on specific biomarker detection, often neglects the complexities of sample matrix interference and the absence of a comprehensive, automated platform. To address these issues, we have developed a universal, fully automated analyzer for multifaceted, on-site biochemical analysis of body fluids. This analyzer integrates automated sample pretreatment, automatic dilution, detection, and self-cleaning functionalities seamlessly. It is designed to detect a wide range of analytes, from small molecules to macromolecules, including ions and proteins, utilizing spectrophotometric sensing. After optimization, the analyzer achieves performance comparable to traditional Enzyme-Linked Immunosorbent Assay (ELISA), while significantly expanding its detection range through automated dilution. Demonstrations of small molecule detection include the simultaneous assessment of citric acid (CA) and oxalic acid (OA) in urine, achieving recovery rates between 96.65%-106.42% and 93.13%-112.50%, respectively. For protein detection, the analyzer successfully identified Cyfra21-1 in saliva with a recovery rate of 104.93%-111.31%. The pre-treatment process requires only 8.8 minutes, showing enhanced recovery rates for CA and OA at 97.8% and 97.6% respectively, which are superior and more rapid than manual methods. The exemplary pretreatment and detection performance of the analyzer underlines its effectiveness in multifaceted, on-site biomarker detection, establishing it as a promising and versatile tool for disease screening and health monitoring. This analyzer offers a powerful technological solution for on-site fluid testing, advancing community health care by facilitating more reliable and rapid diagnostics.

Ultrafast dynamics of fluorene initiated by highly intense laser fields.

We present an investigation of the ultrafast dynamics of the polycyclic aromatic hydrocarbon fluorene initiated by an intense femtosecond near-infrared laser pulse (810 nm) and probed by a weak visible pulse (405 nm). Using a multichannel detection scheme (mass spectra, electron and ion velocity-map imaging), we provide a full disentanglement of the complex dynamics of the vibronically excited parent molecule, its excited ionic states, and fragments. We observed various channels resulting from the strong-field ionization regime. In particular, we observed the formation of the unstable tetracation of fluorene, above-threshold ionization features in the photoelectron spectra, and evidence of ubiquitous secondary fragmentation. We produced a global fit of all observed time-dependent photoelectron and photoion channels. This global fit includes four parent ions extracted from the mass spectra, 15 kinetic-energy-resolved ionic fragments extracted from ion velocity map imaging, and five photoelectron channels obtained from electron velocity map imaging. The fit allowed for the extraction of 60 lifetimes of various metastable photoinduced intermediates.

A multi-channel electrochemical biosensor based on polyadenine tetrahedra for the detection of multiple drug resistance genes.

Antimicrobial resistance poses a serious threat to human health due to the high morbidity and mortality caused by drug-resistant microbial infections. Therefore, the development of rapid, sensitive and selective identification methods is key to improving the survival rate of patients. In this paper, a sandwich-type electrochemical DNA biosensor based on a polyadenine-DNA tetrahedron probe was constructed. The key experimental conditions were optimized, including the length of polyadenine, the concentration of the polyadenine DNA tetrahedron, the concentration of the signal probe and the hybridization time. At the same time, poly-avidin-HRP80 was used to enhance the electrochemical detection signal. Finally, excellent biosensor performance was achieved, and the detection limit for the synthetic DNA target was as low as 1 fM. In addition, we verified the practicability of the system by analyzing E. coli with the MCR-1 plasmid and realized multi-channel detection of the drug resistance genes MCR-1, blaNDM, blaKPC and blaOXA. With the ideal electrochemical interface, the polyA-based biosensor exhibits excellent stability, which provides powerful technical support for the rapid detection of antibiotic-resistant strains in the field.

Noninvasive health monitoring of fish using optical ventilation signals

Fish health monitoring systems in land-based aquaculture must be noninvasive, with no sensors on the surface or inside the fish, in order to minimize stress. This study developed a method for monitoring optical ventilation signals from the operculum movement of olive flounders (Paralichthys olivaceus) and combined it with decision trees, a type of machine learning, to achieve continuous and long-term monitoring. The optical ventilation signal monitoring system was realized using a tank with an interpolated multichannel optical detection probe. The proposed system acquires channel signals using a four-channel optical detection probe situated around the gills of the flounder and processes the channel signals every 10 s in mini-batches to classify and select the optical ventilation signal that best reflects the operculum movement, thereby improving robustness. The opercular beats, which represent ventilation frequency, were calculated from the optical ventilation signal to enable continuous monitoring. To further demonstrate the usefulness of this system, the stress response to high water temperature exposure was monitored and compared to the opercular beats and the variability in plasma glucose concentration, which is used as a stress indicator in fish. The results suggest that the opercular beats respond sensitively to stress application, and the system is useful for fish health monitoring.

GOL-SFSTS based few-shot learning mechanical anomaly detection using multi-channel audio signal

Anomaly detection has become an essential component of mechanical equipment preventive maintenance. When encountered in complicated industrial and military applications, audio signals can be captured in a non-contact manner, preserving significant engineering potential. Common systems that operate on single-channel raw sound inputs have limited anti-noise capabilities and few-shot learning (FSL) robustness. This study proposed a competitive FSL multi-channel anomaly detection framework that uses the global optimization layer-based spallation few-shot training strategy (GOL-SFSTS) on audio Mel-spectrogram samples. The transform on 8-channel audio Mel Spectrogram increases the model's feature capture ability for multi-channel signals greatly. A 'hot-plug' discrepancy distance operator GOL is used to improve the model's anti-noise capacity when dealing with real-world operating situations. SFSTS is a growable learning approach designed to make the model more suitable for later classes and to increase FSL compatibility. We conduct ablation comparisons with other cutting-edge techniques, and FSL classification results on MIMII datasets show that our framework outperforms ResNet34 in full, 30-shot, 15-shot, and 5-shot by 9.6 %, 10.4 %, 9.8 %, and 5 %, respectively. The results of four trials indicate that the designed GOL-SFSTS framework is effective for anomaly detection applications. This paper's impressive achievements have opened up new opportunities for FSL multi-channel audio mechanical anomaly detection.

Multi-channel detection of dopamine and glucose utilizing graphene field effect transistor electrochemical sensor and efficient data fusion algorithm

Schizophrenia, a severe neurological disorder, is linked to aberrations in dopamine (DA) and glucose levels. While numerous methods have been developed for the sensitive and selective detection of either DA or glucose individually, there remains a challenge in achieving simultaneous detection of both with a single platform. To address this, we designed a graphene field effect transistor (GFET) based electrochemical sensor, augmented with 11-mercaptoundecanoic acid-gold nanoclusters (MUA-AuNCs) and pyrene-1-boronic acid (PBA) for enhanced DA and glucose detection. MUA-AuNCs and PBA improved selectivity and sensitivity towards DA and glucose respectively. Moreover, we incorporated a unique data fusion algorithm based on a least squares method. Utilizing a dual-channel sensor setup, this algorithm corrects interference by leveraging accurate DA readings from one channel to compute precise glucose concentrations in mixed solutions, thus ensuring high detection accuracy. This sensor displayed exceptional performance in simultaneous DA and glucose detection, addressing prevalent issues in current methods. Our approach not only has potential to improve schizophrenia monitoring but also provides insights for electrochemical sensor design and optimization.

Portable multichannel detection instrument based on time-resolved fluorescence immunochromatographic test strip for on-site detecting pesticide residues in vegetables

In this work, a portable multichannel detection instrument based on time-resolved fluorescence immunochromatographic test strip (TRFIS) was proposed for on-site detecting pesticide residues in vegetables. Its hardware consisted of a silicon photodiode and excitation light source array, a mainboard of the lower machine with STMicroelectronics 32 (STM32) and a linear stepping motor. While detecting, cardboard with 6-channel TRFIS was pulled into the cassette by the stepping motor. The peak area of the test (T) line and control (C) line of each TRFIS was sampled and calculated by software, then the concentration of the detected pesticide was obtained according to the ratio of the T to C value. This instrument could sample 6-channel TRFIS within 30 s simultaneously, and it exhibited excellent accuracy with a 2.5% average coefficient of variation for each channel (n = 12). In addition, the TRFIS was constructed by using europium oxide time-resolved fluorescent microspheres to label the monoclonal antibody against acetamiprid and form a fluorescent probe, which was fixed on the binding pad. The TRFIS was used for the detection of acetamiprid in celery cabbage, cauliflower and baby cabbage. This instrument was used to complete the qualitative and quantitative analysis of the TRFIS, so as to enhance the practical application of the detection method. This TRFIS possessed excellent linearity ranging from 0.25 mg kg−1 to 1.75 mg kg−1 for the detection of acetamiprid, and the limit of detection were 0.056–0.074 mg kg−1 in the different vegetable matrix. The platform combines the accuracy and portability of traditional test strips with the highly sensitive and efficient fluorescence intensity recognition function of detection equipment, which shows a great application prospect of multi-channel rapid detection of small molecule pollutants in the field.

Rapid scan white light pump–probe spectroscopy with 100 kHz shot-to-shot detection

We demonstrate a femtosecond pump–probe spectrometer that utilizes a white light supercontinuum as input and relies on mutual synchronization of the laser repetition rate, acousto-optical chopper, pump–probe delay stage, and the CCD camera to record shot-to-shot pump–probe spectra while the pump–probe delay is scanned synchronously with the laser repetition rate. The unique combination of technologies implemented here allows for electronically controllable and repetition-rate scalable detection throughput that is only limited by the camera frame rate. Despite high probe RMS fluctuations due to sample scatter (from ∼1.8% with solvent to 7.9% with sample scatter), a combination of fast and slow averaging with a fine sampling of pump–probe delay leads to reduction of RMS noise without multichannel referencing down to ∼0.4 mOD for a scattering nanotube sample. Throughput and limitations of the rapid versus stepwise scanning approaches are analyzed. Experimental comparison with stepwise scan shows ∼1.9x noise reduction in a significantly faster experiment, suggesting an additional suppression of 1/f noise enabled by rapid scan data collection. The particular combination of technologies implemented here makes our approach especially suitable for high throughput impulsive pump–probe micro-spectroscopy of highly scattering samples, without added cost and complexity of light sources, multichannel detection, or long sample exposure.

Design and calibration of an elliptical crystal spectrometer for the diagnosis of proton-induced x-ray emission (PIXE)

Laser-driven proton-induced x-ray emission (laser-PIXE) is a nuclear analysis method based on the compact laser ion accelerator. Due to the transient process of ion acceleration, the laser-PIXE signals are usually spurted within nanoseconds and accompanied by strong electromagnetic pulses (EMP), so traditional multi-channel detectors are no longer applicable. In this work, we designed a reflective elliptical crystal spectrometer for the diagnosis of laser-PIXE. The device can detect the energy range of 1 keV–11 keV with a high resolution. A calibration experiment was completed on the electrostatic accelerator of Peking University using samples of Al, Ti, Cu, and ceramic artifacts. The detection efficiency of the elliptical crystal spectrometer was obtained in the order of 10−9.

Development of a multi-needle fiberoptic Raman spectroscopy technique for simultaneous multi-site deep tissue Raman measurements in the brain.

We report on the development of a multi-needle fiberoptic Raman spectroscopy (MNF-RS) technique for simultaneous multi-site deep Raman measurements in brain tissue. The multi-needle fiberoptic Raman probe is designed and fabricated using a number of 100 µm core diameter, aluminum-coated fibers under a coaxial laser excitation and Raman collection scheme, enabling simultaneous collection of deep tissue Raman spectra from a number of tissue sites. We have also developed a Raman retrieval algorithm based on the transformation matrix of each individual needle fiber probe projected to different pixels of a charge-coupled device (CCD) for recovering the tissue Raman spectra collected by each needle fiber probe, allowing simultaneous multi-channel detection by a single Raman spectrometer. High-quality tissue Raman spectra of different tissue types (e.g., muscle, fat, gray matter, and white matter in porcine brain) can be acquired in both the fingerprint (900-1800 cm-1) and high-wavenumber (2800-3300 cm-1) regions within sub-second times using the MNF-RS technique. We also demonstrate that by advancing the multi-needle fiberoptic Raman probe into deep porcine brain, tissue Raman spectra can be acquired simultaneously from different brain regions (e.g., cortex, thalamus, midbrain, and cerebellum). The significant biochemical differences across different brain tissues can also be distinguished, suggesting the promising potential of the MNF-RS technique for label-free neuroscience study at the molecular level.

Surface and Underwater Acoustic Source Recognition Using Multi-Channel Joint Detection Method Based on Machine Learning

Sound source recognition is a very important application of passive sonar. How to distinguish between surface and underwater acoustic sources has always been a challenge. Due to the mixing of underwater target radiated noise and marine environmental noise, especially in shallow water environments where multipath effects exist, it is difficult to distinguish them. To solve the surface and underwater acoustic source recognition problem, this paper proposes a multi-channel joint detection method based on machine learning. First, the simulation data are generated using the normal model KRAKEN setting in the same environment as the SACLANT 1993 experiment, which uses a vertical linear array of 48 hydrophones. Secondly, the GBDT classifier and LightGBM classifier are trained separately, and then the model is evaluated using precision, recall, F1, and accuracy. Finally, four ML models (kNN, random subspace kNN, GBDT, and LightGBM) are used to analyze all 48 channels of hydrophone data. For each model, two kinds of feature extraction methods (module features, real and imaginary features) are applied. Generally, the results show that both GBDT and LightGBM models have better performance than both kNN and random subspace kNN ones. For both GBDT and LightGBM models, the results using module features have better performance than using real and imaginary features.

Broadband dispersion spectroscopy using interferometric phase modulation under background light suppression.

This Letter presents a dispersion spectroscopy method that achieves simultaneous detection of molecular vibrational dispersion over a broad spectral range. The method is implemented with an infrared mode-locked laser, a dispersion-compensated Michelson interferometer, and a multichannel detector. Synchronous detection under interferometric phase modulation near the destructive interference condition is employed to achieve a high signal-to-noise ratio. We successfully demonstrate the method by measuring the dispersion of carbon monoxide gas, achieving a noise-equivalent dispersion of 1.3 × 10-8 cm and a corresponding noise-equivalent absorbance of 6.5 × 10-4 with a measurement time of 2.2 s.