Ultrasonically assisted synthesis of barium stannate incorporated graphitic carbon nitride nanocomposite and its analytical performance in electrochemical sensing of 4-nitrophenol

We describe the ultrasonic assisted preparation of barium stannate-graphitic carbon nitride nanocomposite (BSO-gCN) by a simple method and its application in electrochemical detection of 4-nitrophenol via electro-oxidation. A bath type ultrasonic cleaner with ultrasonic power and ultrasonic frequency of 100 W and 50 Hz, respectively, was used for the synthesis of BSO-gCN nanocomposite material. The prepared BSO-gCN nanocomposite was characterized by employing several spectroscopic and microscopic techniques such as X-ray diffraction, X-ray photoelectron spectroscopy, fourier transform infra-red, field emission scanning electron microscopy, and high resolution transmission electron microscopy, to unravel the structural and electronic features of the prepared nanocomposite. The BSO-gCN was drop-casted on a pre-treated glassy carbon electrode (GCE), and their sensor electrode was utilized for electrochemical sensing of 4-nitrophenol (4-NP). The BSO-gCN modified GCE exhibited better electrochemical sensing behavior than the bare GCE and other investigated electrodes. The electroanalytical parameters such as charge transfer coefficient (α = 0.5), the rate constant for electron transfer (k_s = 1.16 s⁻¹) and number of electron transferred were calculated. Linear sweep voltammetry (LSV) exhibited increase in peak current linearly with 4-NP concentration in the range between 1.6 and 50 μM. The lowest detection limit (LoD) was calculated to be 1 μM and sensitivity of 0.81 μA μM⁻¹ cm⁻²_. A 100-fold excess of various ions, such as Ca²⁺, Na⁺, K⁺, Cl⁻, I⁻, CO₃²⁻, NO₃, NH₄⁺ and SO₄²⁻ did not able to interfere with the determination of 4-NP and high sensitivity for detecting 4-NP in real samples was achieved. This newly developed BSO-gCN could be a potential candidate for electrochemical sensor applications.     

Machine Learning Algorithm to Predict Acidemia Using Electronic Fetal Monitoring Recording Parameters

Background: Electronic fetal monitoring (EFM) is the universal method for the surveillance of fetal well-being in intrapartum. Our objective was to predict acidemia from fetal heart signal features using machine learning algorithms. Methods: A case–control 1:2 study was carried out compromising 378 infants, born in the Miguel Servet University Hospital, Spain. Neonatal acidemia was defined as pH < 7.10. Using EFM recording logistic regression, random forest and neural networks models were built to predict acidemia. Validation of models was performed by means of discrimination, calibration, and clinical utility. Results: Best performance was attained using a random forest model built with 100 trees. The discrimination ability was good, with an area under the Receiver Operating Characteristic curve (AUC) of 0.865. The calibration showed a slight overestimation of acidemia occurrence for probabilities above 0.4. The clinical utility showed that for 33% cutoff point, missing 5% of acidotic cases, 46% of unnecessary cesarean sections could be prevented. Logistic regression and neural networks showed similar discrimination ability but with worse calibration and clinical utility. Conclusions: The combination of the variables extracted from EFM recording provided a predictive model of acidemia that showed good accuracy and provides a practical tool to prevent unnecessary cesarean sections.     

Dependence of calibration sensitivity of a polysulfone/Ru(II)-tris(4,7-diphenyl-1,10-phenanthroline)-based oxygen optical sensor on its structural parameters

The optimum performance of an optical oxygen sensor based on polysulfone (PSF)/[Ru(II)-Tris(4,7-diphenyl-1,10-phenanthroline)] octylsulfonate (Ru(dpp)OS) was checked by carefully tuning the parameters affecting the membrane preparation. In particular, membranes having thickness ranging between 0.2 and 8.0 μm with various luminophore concentrations were prepared by dip-coating and tested. The membrane thickness was controlled by tuning the solution viscosity, and was measured both by secondary ion mass spectrometry (SIMS) and by visible spectroscopy (Vis). Luminescence-quenching-based calibration was a single value of the Stern-Volmer constant (K^′SV) for membranes containing up to 20 mmol Ru(dpp) g⁻¹ PSF (1.35 μm average thickness). The K^′SV value decreased for larger concentration. The highest sensitivity was obtained with membrane thickness around 1.6 μm, having a response time close to 1 s. Thicker membranes exhibited an emission saturation effect and were characterized by longer response time. The K^′SV behavior was interpreted on the basis of a mathematical approach accounting for the contribution of luminescence lifetime (τ₀), oxygen diffusion coefficient (DO₂) and oxygen solubility inside the membrane (sO₂) establishing the role of all of them and allowing their experimental determination. Moreover, a simple experimental way to estimate K^′SV without needing calibration was proposed. It was based either on the light emission asymmetry or on the percent variation of light emission on passing from pure nitrogen to pure oxygen.     

A Fluorescent Sensor for Dual‐Channel Discrimination between Phosgene and a Nerve‐Gas Mimic

The ability to analyze highly toxic chemical warfare agents (CWAs) and related chemicals in a rapid and precise manner is essential in order to alleviate serious threats to humankind and public security caused by unexpected terrorist attacks and industrial accidents. In this investigation, we designed a o‐phenylenediamine‐pyronin linked dye that is capable of both fluorogenic and colorimetric discrimination between phosgene and the prototypical nerve‐agent mimic, diethyl chlorophosphate (DCP) in the solution or gas phase. Moreover, this dye has been used to construct a portable kit that can be employed for real‐time monitoring of DCP and phosgene in the field, both in a discriminatory manner, and in a simple and safe way.     

Multi-Sensor Vibration Signal Based Three-Stage Fault Prediction for Rotating Mechanical Equipment

In order to reduce maintenance costs and avoid safety accidents, it is of great significance to carry out fault prediction to reasonably arrange maintenance plans for rotating mechanical equipment. At present, the relevant research mainly focuses on fault diagnosis and remaining useful life (RUL) predictions, which cannot provide information on the specific health condition and fault types of rotating mechanical equipment in advance. In this paper, a novel three-stage fault prediction method is presented to realize the identification of the degradation period and the type of failure simultaneously. Firstly, based on the vibration signals from multiple sensors, a convolutional neural network (CNN) and long short-term memory (LSTM) network are combined to extract the spatiotemporal features of the degradation period and fault type by means of the cross-entropy loss function. Then, to predict the degradation trend and the type of failure, the attention-bidirectional (Bi)-LSTM network is used as the regression model to predict the future trend of features. Furthermore, the predicted features are given to the support vector classification (SVC) model to identify the specific degradation period and fault type, which can eventually realize a comprehensive fault prediction. Finally, the NSF I/UCR Center for Intelligent Maintenance Systems (IMS) dataset is used to verify the feasibility and efficiency of the proposed fault prediction method.     

互相关法在光纤液滴指纹图分析中的应用

为了实现光纤液滴指纹图的实时分析,引进了互相关分析法.在对乙醇溶液测量的过程中,将50％浓度的乙醇溶液对应的光纤液滴指纹图作为参考指纹图,然后将测得的光纤液滴指纹图与参考指纹图进行互相关,得到光纤液滴指纹图的相关曲线,从中提取与液体参量有关的各种信息.利用互相关分析法对各种浓度的乙醇溶液进行了处理,得出了相关峰高度与浓度的单调关系,验证了互相关法的可行性.     

Electrochemical Impedance Spectroscopy in the Characterisation and Application of Modified Electrodes for Electrochemical Sensors and Biosensors

Electrochemical impedance spectroscopy is finding increasing use in electrochemical sensors and biosensors, both in their characterisation, including during successive phases of sensor construction, and in application as a quantitative determination technique. Much of the published work continues to make little use of all the information that can be furnished by full physical modelling and analysis of the impedance spectra, and thus does not throw more than a superficial light on the processes occurring. Analysis is often restricted to estimating values of charge transfer resistances without interpretation and ignoring other electrical equivalent circuit components. In this article, the important basics of electrochemical impedance for electrochemical sensors and biosensors are presented, focussing on the necessary electrical circuit elements. This is followed by examples of its use in characterisation and in electroanalytical applications, at the same time demonstrating how fuller use can be made of the information obtained from complete modelling and analysis of the data in the spectra, the values of the circuit components and their physical meaning. The future outlook for electrochemical impedance in the sensing field is discussed.     

Graphene-Oxide-Based Fluoro- and Chromo-Genic Materials and Their Applications

Composite materials and their applications constitute a hot field of research nowadays due to the fact that they comprise a combination of the unique properties of each component of which they consist. Very often, they exhibit better performance and properties compared to their combined building blocks. Graphene oxide (GO), as the most widely used derivative of graphene, has attracted widespread attention because of its excellent properties. Abundant oxygen-containing functional groups on GO can provide various reactive sites for chemical modification or functionalization of GO, which in turn can be used to develop novel GO-based composites. This review outlines the most recent advances in the field of novel dyes and pigments encompassing GO as a key ingredient or as an important cofactor. The interactions of graphene with other materials/compounds are highlighted. The special structure and unique properties of GO have a great effect on the performance of fabricated hybrid dyes and pigments by enhancing the color performance of dyes, the anticorrosion properties of pigments, the viscosity and rheology of inks, etc., which further expands the applications of dyes and pigments in dyeing, optical elements, solar-thermal energy storage, sensing, coatings, and microelectronics devices. Finally, challenges in the current development as well as the future prospects of GO-based dyes and pigments are also discussed. This review provides a reference for the further exploration of novel dyes and pigments.     

Photoluminescence linewidth broadening due to alloy/thickness fluctuation of CdxZn1 − xSe/ZnSe triple quantum wells

Photoluminescence (PL) linewidth broadening of Cd_xZn_{1 − x}Se/ZnSe triple quantum wells, grown on GaAs substrates by molecular beam epitaxy (MBE), has been investigated. Various quantum well (QW) samples have been prepared with different QW thickness and composition (Cd-composition). Measured and calculated PL linewidth are compared. Both composition and thickness fluctuations are considered for the calculation with the parameters such as the volume of exciton, nominal thickness and composition of QWs. Surface roughness measured by atomic force microscopy (AFM) is used to estimate the interface roughness. Results show that when Cd-composition increases additional linewidth broadening due to Zn/Cd interdiffusion is enhanced.     

Luminescence properties of Y3Al5O12:Ce nanoceramics

Comparative analysis of the luminescent properties of Y₃Al₅O₁₂:Ce (YAG:Ce) transparent optical ceramics (OС) with those of single crystal (SC) and single crystalline film (SCF) analogues has been performed under excitation by pulsed synchrotron radiation in the fundamental absorption range of YAG host. It has been shown that the properties of YAG:Ce OC are closer to the properties of the SCF counterpart, where Y_Al antisite defects are completely absent, rather than to the properties of SC of this garnet with large concentration of Y_Al antisite defects. At the same time, the luminescence spectra of YAG:Ce OC show weak emission bands in the 200-470 nm range related to Y_Al antisite defects and charged oxygen vacancies (F⁺ and F centers). YAG:Ce ОС also possesses significantly larger contribution of slow components in the Ce³⁺ luminescence decay under high-energy excitation in comparison with SC and SCF of this garnet due to the involvement of antisite defects, charged oxygen vacancies as well as boundaries of grains in the energy transfer processes from the host to the Ce³⁺ ions.