Two-step machine learning-assisted label-free surface-enhanced Raman spectroscopy for reliable prediction of dissolved furfural in transformer oil.

Accurate detection of dissolved furfural in transformer oil is crucial for real-time monitoring of the aging state of transformer oil-paper insulation. While label-free surface-enhanced Raman spectroscopy (SERS) has demonstrated high sensitivity for dissolved furfural in transformer oil, challenges persist due to poor substrate consistency and low quantitative reliability. Herein, machine learning (ML) algorithms were employed in both substrate fabrication and spectral analysis of label-free SERS. Initially, a high-consistency Ag@Au substrate was prepared through a combination of experiments, particle swarm optimization-neural network (PSO-NN), and a hybrid strategy of particle swarm optimization and genetic algorithm (Hybrid PSO-GA). Notably, a two-step ML framework was proposed, whose operational mechanism is classification followed by quantification. The framework adopts a hierarchical modeling strategy, incorporating simple algorithms such as kernel support vector machine (Kernel-SVM), k-nearest neighbors (KNN), etc., to independently establish lightweight regression models on each cluster, which allows each model to focus more effectively on fitting the data within its cluster. The classification model achieved an accuracy of 100%, while the regression models exhibited an average correlation coefficient (R2) of 0.9953 and the root mean square errors (RMSE) consistently below 10-2. Thus, this ML framework emerges as a rapid and reliable method for detecting dissolved furfural in transformer oil, even in the presence of different interfering substances, which may also have potentiality for other complex mixture monitoring systems.

Ice-template-induced highly ionic conductive PVA/PEG-SiO2 gel polymer electrolyte for zinc-ion batteries.

In this work, a SiO2 doped polyvinyl alcohol/polyethylene glycol (PVA/PEG) gel polymer electrolyte (PVA/PEG-SiO2) was constructed via an ice-crystal template for zinc-ion batteries. The SiO2 and the three-dimensional porous skeleton make it have excellent ionic conductivity and mechanical strength, and inhibit the growth of dendrites. The assembled ZIBs exhibit excellent rate performance and cycle stability, making it a promising electrolyte membrane candidate for flexible wearable electronics.

Simultaneous detection of multiple aging characteristic components in oil-paper insulation using sensitive Raman technology and microfluidics.

The aging characteristic components of oil-paper insulation reflect the aging status of the power equipment. In this study, we designed a novel microfluidic chip capable of automatic and rapid extraction of aging components from insulating oil. Combined with Raman spectroscopy technology, it enables simultaneous detection of various aging components. By optimizing the microfluidic chip structural and adopting an optical window encapsulation, it eliminates interference from the Polydimethylsiloxane (PDMS). Measurements and analyses were carried out on multiple oil samples containing three aging products (furfural, acetone, and methanol). The results indicate that this novel microfluidic chip facilitates simultaneous detection of multiple components, significantly improving the detection sensitivity of complex oil. The detection limits for furfural, acetone, and methanol in insulating oil are 0.43 mg/L, 1.04 mg/L, and 2.31 mg/L, respectively. This provides a new approach for the online detection of oil-paper insulation equipment.

Phase-Modified Strongly Coupled δ/ε-MnO2 Homojunction Cathode for Kinetics-Enhanced Zinc-Ion Batteries.

Rechargeable Zn-MnO2 batteries using mild water electrolytes have garnered significant interest owing to their impressive theoretical energy density and eco-friendly characteristics. However, MnO2 suffers from huge structural changes during the cycles, resulting in very poor stability at high charge-discharge depths. Briefly, the above problems are caused by slow kinetic processes and the dissolution of Mn atoms in the cycles. In this paper, a 2D homojunction electrode material (δ/ε-MnO2) based on δ-MnO2 and ε-MnO2 has been prepared by a two-step electrochemical deposition method. According to the DFT calculations, the charge transfer and bonding between interfaces result in the generation of electronic states near the Fermi surface, giving δ/ε-MnO2 a more continuous distribution of electron states and better conductivity, which is conducive to the rapid insertion/extraction of Zn2+ and H+. Moreover, the strongly coupled Mn-O-Mn interfacial bond can effectively impede dissolution of Mn atoms and thus maintain the structural integrity of δ/ε-MnO2 during the cycles. Accordingly, the δ/ε-MnO2 cathode exhibits high capacity (383 mAh g-1 at 0.1 A g-1), superior rate performance (150 mAh g-1 at 5 A g-1), and excellent cycling stability over 2000 cycles (91.3% at 3 A g-1). Profoundly, this unique homojunction provides a novel paradigm for reasonable selection of different components.

Optical feedback frequency locking: impact of directly reflected field and responding strategies.

The challenges presented by the directly reflected field in optical feedback cavity-enhanced spectroscopy systems serve as substantial obstacles, introducing additional complexity to existing systems and compromising their sensitivity, as the underlying mechanisms of its adverse effects remain not fully understood. This study aims to address this issue by introducing a comprehensive analytical model. Additionally, frequency locking can be achieved by decreasing the feedback rate, the laser's linewidth enhancement factor, and the directly reflected field, and by increasing the refractive index of the gain medium, the length of the laser's resonant cavity, the electric field reflectivity of the laser's output facet, and the resonant field. These parameters can affect the feedback coupling rate pre-factor, and for a resonant cavity with a length of 0.394 m, optical feedback can only be established when the feedback coupling rate pre-factor is less than 1.05 × 109. Through experimental validation, we successfully confirm the effectiveness of the proposed solution in eliminating the detrimental effects of the directly reflected field. Importantly, this suppression is achieved without compromising other aspects of the system's performance. The research findings not only offer the potential to optimize various cavity-enhanced spectroscopy systems that rely on optical feedback but also show promising applications in advancing the development of high-purity spectrum diode lasers utilizing optical feedback from an external high-finesse cavity.

Characterization of Temperature and Strain Changes in Lithium-Ion Batteries Based on a Hinged Differential Lever Sensitization Fiber Bragg Grating Strain-Temperature Simultaneous-Measurement Sensor.

Li-ion batteries are expected to become the mainstream devices for green energy storage or power supply in the future due to their advantages of high energy and power density and long cycle life. Monitoring the temperature and strain change characteristics of Li-ion batteries during operation is conducive to judging their safety performance. The hinged differential lever sensitization structure was used for strain sensitization in the design of an FBG sensor, which also allowed the simultaneous measurement of strain and temperature. The temperature and strain variation characteristics on the surface of a Li-ion soft-packed battery were measured using the des.igned sensor. This report found that the charging and discharging processes of Li-ion batteries are both exothermic processes, and exothermic heat release is greater when discharging than when charging. The strain on the surface of Li-ion batteries depends on electrochemical changes and thermal expansion effects during the charge and discharge processes. The charging process showed an increasing strain, and the discharging process showed a decreasing strain. Thermal expansion was found to be the primary cause of strain at high rates.

Research on Transformer Omnidirectional Partial Discharge Ultrasound Sensing Method Combining F-P Cavity and FBG.

To achieve omnidirectional sensitive detection of partial discharge (PD) in transformers and to avoid missing PD signals, a fiber optic omnidirectional sensing method for PD in transformers combined with the fiber Bragg grating (FBG) and Fabry-Perot (F-P) cavity is proposed. The fiber optic omnidirectional sensor for PD as a triangular prism was developed. The hollow structure of the probe was used to insert a single-mode fiber to form an F-P cavity. In addition, the three sides of the probe were used to form a diaphragm-type FBG sensing structure. The ultrasound sensitization diaphragm was designed based on the frequency characteristics of PD in the transformer and the vibration model of the diaphragm in the liquid environment. The fiber optic sensing system for PD was built and the performance test was conducted. The results show that the resonant frequency of the FBG acoustic diaphragm is around 20 kHz and that of the F-P cavity acoustic diaphragm is 94 kHz. The sensitivity of the developed fiber optic sensor is higher than that of the piezoelectric transducer (PZT). The lower limit of PD detection is 68.72 pC for the FBG sensing part and 47.97 pC for the F-P cavity sensing part. The directional testing of the sensor and its testing within a transformer simulation model indicate that the proposed sensor achieves higher detection sensitivity of PD in all directions. The omnidirectional partial discharge ultrasound sensing method proposed in this paper is expected to reduce the missed detection rate of PD.

Centrifugal Extraction-Assisted Fiber-Enhanced Raman Spectroscopy for Online Detection of Trace Furfural in Oil Power Equipment.

Oil-paper insulated equipment is integral in power conversion and supports low-loss electricity transport. As a characteristic byproduct of the oil-paper insulation system, the realization of efficient detection of furfural in oil is crucial to the safe operation of the power grid. We proposed a novel approach using dual-enhanced Raman spectroscopy for sensing trace liquid components. This method employs a centrifugal extractor to separate and enrich the targeted components, achieving selective enhancement. The optimal phase ratio was determined to be 30:1. A liquid-core fiber was used to optimize the laser transmission efficiency and Raman signal collection efficiency, resulting in a nonselective signal enhancement of 44.86. It also investigated the impact of intermolecular interactions on the shift of Raman spectra, identifying the reasons for the differences in Raman signals between pure furfural, furfural in oil, and furfural in water. A batch of samples with furfural dissolved in insulation oil was measured using this system and achieved a limit of detection of 0.091 mg/L. The stability of the dual-enhanced Raman platform was experimentally verified with a spectral intensity fluctuation of 0.68%. This method is fast, stable, adaptable, and suitable for the detection of a wide range of liquid ingredients.

4-ATP-modified CNTs@NiO-Fe2O3-Ag SERS filter membrane for rapid in-situ detection of furfural in mineral oil.

Evaluating the transformer aging state and detecting multi-aging characteristics in transformer oil with high sensitivity and fast speed has become a key challenge. This study introduces a P-N heterojunction (CNTs@NiO-α-Fe2O3) fabricated through electroless nickel plating and a one-step hydrothermal method. Additionally, silver nanoparticles (AgNPs) with adjustable particle sizes are grown on the surface using a chemical reduction method. To obtain high sensitivity and rapid SERS signal, CNTs@NiO-α-Fe2O3-Ag gel is adsorbed on a disposable needle filter (220 nm) surface, and 4-aminothiophene (4-ATP) is grafted onto the surface of SERS substrate. The minimum detection limit was 0.025 mg/L (EF = 5.22 × 104), and the response time of SERS best signal could be shortened to 3 min. Density functional theory (DFT) calculations reveal that by constructing a P-N heterostructure of NiO-Fe2O3 and assessing the adsorption energies of furfural, acetone, and methanol on the surface of the P-N heterojunction. This SERS strategy has a huge application prospect in the aging diagnosis of oil-paper insulation systems in a transformer.

Fluorescence Noise Eliminating Fiber-Enhanced Raman Spectroscopy for Simultaneous and Multiprocess Analysis of Intermediate Compositions for C2H2 and H2 Production.

C2H2 and H2, as important chemical and energy raw materials, can be produced effectively and environmentally friendly by the partial oxidation (POX) of CH4. Simultaneous analysis of intermediate gas compositions in the multiprocess (cracking, recovery, degassing, etc) of POX can regulate product generation and improve production efficiency. To overcome the disadvantage of common gas chromatography, we propose a fluorescence noise eliminating fiber-enhanced Raman spectroscopy (FNEFERS) technique for simultaneous and multiprocess analysis of the POX process, in which the fluorescence noise eliminating (FNE) method can effectively eliminate the horizontal and vertical spatial noise to ensure ppm level limits of detection (LOD). The vibration modes of gas compositions related to each POX process such as cracked gas, synthesis gas, and product acetylene are analyzed. Meanwhile, the composition of three-process intermediate sample gases from Sinopec Chongqing SVW Chemical Co., Ltd is quantitatively and qualitatively analyzed simultaneously, along with the ppm level LODs (H2: 11.2 ppm, C2H2: 3.1 ppm, CO2: 9.4 ppm, C2H4: 4.8 ppm, CH4: 1.5 ppm, CO: 17.9 ppm, allene: 1.5 ppm, methyl acetylene: 2.6 ppm, 1,3-butadiene: 2.8 ppm) with a laser power of 180 mW, exposure time of 30 s, and accuracy of higher than 95.2%. This study fully demonstrates the ability of FNEFERS to replace gas chromatography to achieve simultaneous and multiprocess analysis of intermediate compositions for C2H2 and H2 production and to monitor other chemical and energy production processes.

Cavity-Enhanced Raman Spectroscopy for Detection of Trace Gaseous Impurities in Hydrogen for Fuel Cells.

Gaseous impurities contained in hydrogen (H2) profoundly affect the performance of hydrogen proton-exchange membrane fuel cells. We demonstrate the utility of cavity-enhanced Raman spectroscopy as a unique approach for detection of gaseous impurities. A dense-pattern multipass cavity which is composed of four spherical mirrors placed in a Z-shaped configuration is used to enhance the Raman signal by extending the laser-gas interaction length. A total of 85 spots are identified on the 2-inch-diameter front (or rear) mirror, which indicates that 510 beams exist in the cavity. Detection limits of the impurity gases, including oxygen (O2), nitrogen (N2), carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), ammonia (NH3), and hydrogen sulfide (H2S), reach sub-ppm- and ppb-levels at a total pressure of 0.1 and 2.5 MPa, respectively. This satisfies the detection requirements according to the maximum allowable concentration for these gases. Our cavity-enhanced Raman spectroscopy (CERS) apparatus can simultaneously measure multiple gases with high sensitivity and selectivity with no sample destruction. It has excellent application prospects in gaseous impurity analysis for the quality assessment of gaseous energy.

Simple technique of coupling a diode laser into a linear power buildup cavity for Raman gas sensing.

We report a novel, to the best of our knowledge, and simple technique to lock a 642 nm multi-quantum well diode laser to an external linear power buildup cavity by directly feeding the cavity reflected light back to the diode laser for enhancement of gas Raman signals. The dominance of the resonant light field in the locking process is achieved by reducing the reflectivity of the cavity input mirror and thus making the intensity of the directly reflected light weaker than that of the resonant light. Compared with traditional techniques, stable power buildup in the fundamental transverse mode TEM00 is guaranteed without any additional optical elements or complex optical arrangements. An intracavity exciting light of 160 W is generated with a 40 mW diode laser. Using a backward Raman light collection geometry, detection limits at the ppm level are achieved for ambient gases (N2, O2) with an exposure time of 60 s.

Quantitative Analysis of Acetone in Transformer Oil Based on ZnO NPs@Ag NWs SERS Substrates Combined with a Stoichiometric Model.

Acetone is an essential indicator for determining the aging of transformer insulation. Rapid, sensitive, and accurate quantification of acetone in transformer oil is highly significant in assessing the aging of oil-paper insulation systems. In this study, silver nanowires modified with small zinc oxide nanoparticles (ZnO NPs@Ag NWs) were excellent surface-enhanced Raman scattering (SERS) substrates and efficiently and sensitively detected acetone in transformer oil. Stoichiometric models such as multiple linear regression (MLR) models and partial least square regressions (PLS) were investigated to quantify acetone in transformer oil and compared with commonly used univariate linear regressions (ULR). PLS combined with a preprocessing algorithm provided the best prediction model, with a correlation coefficient of 0.998251 for the calibration set, 0.997678 for the predictive set, a root mean square error in the calibration set (RMSECV = 0.12596 mg/g), and a prediction set (RMSEP = 0.11408 mg/g). For an acetone solution of 0.003 mg/g, the mean absolute percentage error (MAPE) was the lowest among the three quantitative models. For a concentration of 7.29 mg/g, the MAPE was 1.60%. This method achieved limits of quantification and detections of 0.003 mg/g and 1 µg/g, respectively. In general, these results suggested that ZnO NPs@Ag NWs as SERS substrates coupled with PLS simply and accurately quantified trace acetone concentrations in transformer oil.

Photoinduced loading of electron-rich Cu single atoms by moderate coordination for hydrogen evolution.

Single-atom catalysts offer maximal atom utilization efficiencies and high-electronegativity heteroatoms play a crucial role in coordinating reactive single metal atoms to prevent agglomeration. However, these strong coordination bonds withdraw electron density for coordinated metal atoms and consequently affect their catalytic activity. Herein we reveal the high loading (11.3 wt%) and stabilization of moderately coordinated Cu-P3 structure on black phosphorus support by a photochemical strategy with auxiliary hydrogen. Single-atom Cu sites with an exceptional electron-rich feature show the [Formula: see text] close to zero to favor catalysis. Neighboring Cu atoms work in synergy to lower the energy of key water adsorption and dissociation intermediates. The reported catalyst shows a low overpotential of only 41 mV at 10 mA cm-2 and Tafel slope of 53.4 mV dec-1 for the alkaline hydrogen evolution reaction, surpassing both isolated Cu single atoms and Cu nanoclusters. The promising materials design strategy sheds light on the design and fabrication of high-loading single metal atoms and the role of neighboring single atoms for enhanced reaction kinetics.

Dense-pattern multi-pass cavity based on spherical mirrors in a Z-shaped configuration for Raman gas sensing.

We report a dense-pattern multi-pass cavity (MPC) based on four spherical mirrors placed in a Z-shaped cavity configuration for improving the Raman signals from gases. The folding structure of the cavity causes dense patterns of spots, and at least 420 beams are reflected in the cavity. Raman spectra of ambient air, methane, and ethylene are recorded to demonstrate the performance of our apparatus. At atmospheric pressure, ppm-level detection limits of the gases are achieved with 10 s of exposure time. The Raman signal intensities of the gases show excellent linearity with the gases' partial pressures, which means that high-accuracy detection is also feasible.

Highly sensitive and reproducible CNTs@Ag modified Flower-Like silver nanoparticles for SERS situ detection of transformer Oil-dissolved furfural.

Accurately evaluating the aging state of oil paper insulation in electrical equipment is a key to ensure the safe operation of the power transformer. For achieving highly sensitive in-situ detection of dissolved furfural in transformer oil with good reproducibility, flower-like silver nanoparticles modified with carbon nanotubes (CNTs@Ag-F-AgNPs) was synthesized by a combination of electroless silver plating and redox method. The large specific surface area and strong adsorption capacity of CNTs@Ag promoted the formation of more "hot spots". CNTs@Ag-F-AgNPs were adsorbed on Si-Au substrate via mercapto groups on the coupling agent 1'4 phenyldimercaptan molecule (BDT). Using rhodamine 6G (R6G) as probe molecule, the enhanced factor reached 6.96 × 109. Then, the substrate was used for in-situ SERS detection of transformer oil-dissolved furfural at different concentrations and the detection limit was 2.25 mg/L at 1703 cm-1 (Stretching vibration of C = O in furfural molecule), fulfilling requirements of furfural content detection after severe aging of transformer (4 mg/L). Besides, the relative standard deviation (RSD) of characteristic peak intensity at ten different positions was only 1.74%. These results exhibite that three-dimensional nanostructure with high sensitivity and good reproducibility exhibited a wide application range for in situ detection of dissolved trace furfural in transformer oil.

Vibrational Spectra and Molecular Vibrational Behaviors of Dibenzyl Disulfide, Dibenzyl Sulphide and Bibenzyl.

The vibration spectroscopy (Raman and infrared) of widely concerned molecules in sulfur corrosion phenomenon (Dibenzyl Disulfide, Dibenzyl Sulphide, and Bibenzyl) is detailedly analyzed based on density functional theory and experimental measurement. The dominant conformations of these molecules are determined according to Boltzmann distribution in relative Gibbs free energy. Additionally, noncovalent interaction analysis is conducted to indicate intramolecular interaction. Vibration normal mode is assigned based on potential energy distribution, which comprehensively reveals the molecular vibrational behaviors. Conformations weighted spectra are obtained and compared with experimentally measured spectra. We found that experimental spectra are in good agreement with the theoretical spectra in B3LYP-D3(BJ)/6-311G** level with a frequency correction factor. Furthermore, the divergence among these molecules is discussed. The vibrational behavior of the methylene group in the molecule shows a trend with the presence of the sulfur atom.

Degree of polymerization mapping Raman feature extraction of oil-paper insulation aging based on quadratic mutual information.

To assess the aging of oil-paper insulation, an accelerated aging experiment is executed. Raman spectroscopy, a nondestructive detection method with access to component identification and fault diagnosis, is used to analyze the aging of oil-paper insulation. Raman feature of oil-paper insulation aging with a close relationship with the degree of polymerization is obtained based on the concept of quadratic mutual information. By analyzing the relationship between the extracted feature and the degree of polymerization of samples at different aging degrees, the feasibility of reflecting the aging degree of oil-paper insulation is determined. By load analysis, the chemical correlation between the extracted feature and oil-paper insulation aging is clarified. For eight test samples, the prediction error of degree of polymerization based on Raman features is less than 50. These results show that the features extracted in this paper are helpful to realizing the Raman spectrum diagnosis of oil-paper insulation aging.

Hazardous Gas Detection by Cavity-Enhanced Raman Spectroscopy for Environmental Safety Monitoring.

We demonstrate the practicability of cavity-enhanced Raman spectroscopy (CERS) with a folded multipass cavity as a unique tool for the detection of hazardous gases in the atmosphere. A four-mirror Z-sharped multipass cavity results in a greatly extended laser-gas interaction length to improve the Raman signal intensity of gases. For Raman intensity maximization, the optimal number of intracavity beams of a single reflection cycle is calculated and then the cavity parameters are designed. A total of 360 intracavity beams are realized, which are circulated four times in the cavity based on the polarization. ppb-Level Raman gas sensing at atmospheric pressure for several typical explosive gases and toxic gases in ambient air, including hydrogen (H2), methane (CH4), carbon monoxide (CO), hydrogen sulfide (H2S), and chlorine (Cl2), is achieved at 300 s exposure time. Our CERS apparatus, which can detect multiple gases simultaneously with ultrahigh sensitivity and high selectivity, is powerful for detecting hazardous gases in the atmosphere, and it has excellent potential for environmental safety monitoring.

Fiber-enhanced Raman spectroscopy for highly sensitive H2 and SO2 sensing with a hollow-core anti-resonant fiber.

An innovative fiber-enhanced Raman gas sensing system with a hollow-core anti-resonant fiber is introduced. Two iris diaphragms are implemented for spatial filtering, and a reflecting mirror is attached to one fiber end that provides a highly improved Raman signal enhancement over 2.9 times than the typical bare fiber system. The analytical performance for multigas compositions is thoroughly demonstrated by recording the Raman spectra of carbon dioxide (CO2), oxygen (O2), nitrogen (N2), hydrogen (H2), and sulfur dioxide (SO2) with limits of detection down to low-ppm levels as well as a long-term instability < 1.05%. The excellent linear relationship between Raman signal intensity (peak height) and gas concentrations indicates a promising potential for accurate quantification.