High-sensitivity and rapid detection of heavy metal elements in water is in great demand. Traditional laboratory analysis methods limited to long cycles, complex processing, and risk of secondary pollution, which made it impossible to achieve on-site detection. Laser-induced breakdown spectroscopy (LIBS) has the characteristics of rapid and minimal damage and has been applied to the detection of solids, liquids and even gases. However, it is difficult to directly detect with LIBS due to the low content of heavy metals in water and the matrix effect of samples. We propose a rapid detection method of heavy metal elements in water by laser-induced breakdown spectroscopy combined with sample morphology constrained positioning. Using Pb as a representative element, analyze the enhancement effect and mechanism of the above sample processing method on the LIBS signal, and establish a calibration curve with a concentration range of 100-1000 ug/L. The correlation coefficient R2 is 0.97, and the detection limit reaches 86.6 ug/L., which meets the requirements of surface water quality testing. The study combined with portable LIBS equipment can provide a low-cost and rapid screening method for heavy metal pollution in surface water.
Nitrate is widely distributed in various water environments, and its potential toxicity poses a great threat to human health and environment. It is of great significance to realize rapid detection of nitrate in water. Raman spectroscopy, as a molecular spectrum, has been widely used in the detection of ionic concentration in liquid samples. However, fluorescence background interference and spectral peak overlap are still a challenge for the detection of trace targets in practical applications. In this study, we proposed a rapid detection method for nitrate at low concentration in drinking water based on Raman spectra combined with adsorption materials., The difference between characteristic spectrum of nitrate adsorption at low concentration and background spectrum of adsorption material was emphatically analyzed after verifying the effectiveness of nitrate adsorbent. The peak decomposition method of nitrate characteristic spectrum was established to achieve highly sensitive detection of nitrate concentration of 5-10 mg/L. The calibration curve of NO3 - -N concentration in 5-100 mg/L was established according to the normalized spectral intensity. The correlation coefficient R2 of the established regression model reached 0.98. The root mean square error (RMSE) was 3.56 mg/L. This study provides a rapid detection method for nitrate in water, which can provide a low-cost assessment method for daily household drinking water quality and water quality purification combined with portable Raman spectrometer. At the same time, this method is also expected to achieve fast on-site detection for early warning response of surface water pollution.
Infrared spectroscopy can provide fingerprints of most molecular compounds, which is widely used for detection of solid, liquid, and gas components with the advantages of fast response, high sensitivity, and specificity. However, Fourier transform infrared spectroscopy (FTIR) system has a large size and is heavy in quality, which limits its potential for onsite detection applications. With the development of materials and technology, quantum cascade laser (QCL), as a kind of infrared coherent light source, has gradually appeared on the market, which provides the possibility to design a portable infrared spectroscopy system with the features of light weight and low cost. Therefore, based on the miniaturized QCL and infrared detector, we designed a portable infrared spectroscopy detection system with a bandwidth of 200 cm-1 (1168- 952 cm-1) in this paper. We successfully detected the infrared absorption characteristic peak of ethanol gas at 1060 cm-1 with this system, which verified its feasibility for detecting infrared spectroscopy of molecular compounds.
Many volatile organic compounds (VOCs) will be released in the process of food deterioration. These VOCs are closely related to the physical and chemical properties of the food. Its rapid detection is important to the assessment of food quality and safety. Traditional analytical methods based on chromatography-mass spectrometry have excellent detection limits and accuracy, but their sampling and pretreatment lead to time-consuming, and cannot quickly detect food VOCs. This article uses tunable diode laser absorption spectroscopy (TDLAS) technology to explore a rapid detection method for fo od spoilage based on VOCs. In this paper, a spectral absorption peak caused by ammonia gas released from spoiled beef is successfully detected, and its amplitude increases with the deterioration of beef. This study demonstrates that food spoilage can be identified using VOCs based on laser spectroscopy.
Animal body surface temperature abnormality is highly correlated with animal physiological abnormalities and epidemic diseases. In animal groups, the conventional local thermometry is always stuck in limitations like large workload and large temperature error induced by animal restraint stress reaction, etc. A fast surface temperature measurement system carrying a smartphone-based miniature non-refrigeration IR thermal imaging temperature sensor for animal groups was developed in this research. A thermostat-based internal calibration method was established to tackle the temperature drift of the thermal core, and implement the real-time calibration of the temperature measuring errors caused by the temperature response drift of the detector.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.