Author
Li Yingchao
Bio: Li Yingchao is an academic researcher from Jilin University. The author has contributed to research in topics: Laser-induced breakdown spectroscopy & Sorting. The author has an hindex of 3, co-authored 3 publications receiving 113 citations.
Papers
More filters
TL;DR: A review of the methods of signal enhancement in laser-induced breakdown spectroscopy (LIBS) is presented in this paper, where the authors show that conventional LIBS suffers from disadvantages of low sensitivity and high limits of detecti...
Abstract: A review of the methods of signal enhancement in laser-induced breakdown spectroscopy (LIBS) is presented. Conventional LIBS suffers from disadvantages of low sensitivity and high limits of detecti...
112 citations
TL;DR: In this article, a review of laser-induced breakdown spectroscopy (LIBS) applications for coal ranks, combustion efficiency, and environmental protection is presented, together with a description of limitations and the potential developing trend for this topic.
Abstract: With massive coal consumption in the industry, the increasing requirements for improving combustion efficiency and environmental protection raise widespread interests. Laser-induced breakdown spectroscopy (LIBS) shows the merits of high-speed, minimally destructive, simple preparation, etc. Combining it with the analytical chemistry methods have become a promising way for coal analysis. In this work, LIBS instruments for collecting coal spectra, pretreatment methods for coal samples, preprocessing of coal data, and analytical chemistry methods for coal analysis were summarized. Moreover, LIBS applications, including coal ranks, combustion efficiency, and environmental protection, are provided. Finally, this review proposes a description of limitations and the potential developing trend for this topic.
47 citations
Patent•
13 Jun 2017
TL;DR: In this paper, a waste ore sorting method and device based on the laser induced breakdown spectroscopy (LIBS) was described, which consists of an ore pulverizer, a filter, a conveying device, a sample shape inspection system, an LIBS detection system, a mechanical sorting and ore collecting system and a measurement and control system.
Abstract: The invention belongs to the field of laser spectroscopy detection and ore sorting, and discloses a waste ore sorting method and device based on the laser induced breakdown spectroscopy (LIBS). The device comprises an ore pulverizer, a filter, a conveying device, a sample shape inspection system, an LIBS detection system, a mechanical sorting and ore collecting system and a measurement and control system. The pulverizer and the filter are used for smashing massive waste ore into small ore blocks of the similar sizes and shapes. The sample shape inspection system is used for obtaining the average heights and boundary dimensions of samples, and further controlling the focusing distance and scanning range of the LIBS detection system. The LIBS detection system is used for detecting material compositions of the ore and determining the ore grade. The mechanical sorting system conveys the ore and the waste ore to different ore collecting tanks separately according to detection results. The measurement and control system is used for performing unified coordination control over all functional units of the device.
3 citations
Cited by
More filters
TL;DR: In this paper, the authors present a comprehensive review of the use of laser-induced breakdown spectroscopy (LIBS) for coal analysis, including fundamentals and key factors, operation modes, data processing and analytical results.
Abstract: Coal is one of the world's most abundant primary energy sources. Real-time coal analysis technology is imperative for coal blending, combustion optimization, pollution reduction, and pricing. Laser-induced breakdown spectroscopy (LIBS) has been a promising candidate for coal analysis because of its uniquely fast, in situ, and online capabilities. Coal is a sedimentary rock with a complex and heterogeneous composition, and therefore, laser–coal interaction exhibits multiple phenomena. A systematic study of the experimental conditions required for stable coal–plasma formation and evolution is a headway for enhancing LIBS results. In coal-fired power plants, LIBS offers three installation sets, namely, inline, at-line, and offline, with minimal space requirements and ease of retrofit. Moreover, LIBS is a safer technique with lower installation and maintenance costs and fits the concern of coal-fired power plants for multielemental detection in fast records. Coal analysis mainly includes calorific heat value determination, proximate analysis, ultimate analysis, and other related analyses. LIBS data is handled with continuously developing mathematical and statistical modeling techniques to provide the smart extraction of the required spectral information for coal analysis. In this tutorial review, we summarize the previous research contributions utilizing LIBS for coal analysis, including fundamentals and key factors, operation modes, data processing, and analytical results. Over and above, LIBS contribution in fly ash analysis and certain literature concerning combustion diagnostics might be included to present a simple guideline for researchers interested in LIBS applications for coal utilization.
117 citations
TL;DR: In the last few years, LIBS has become an established technique for the assessment of elemental concentrations in various sample types as discussed by the authors, since this technique allows to associate the obtained elemental composition information with the spatial coordinates of the investigated sample.
69 citations
TL;DR: Success rates of 76% and higher indicate that ATR-FTIR, NIR reflectance spectroscopy, and LIBS coupled to machine learning classifiers can be used to robustly identify both consumer and environmental plastic samples.
Abstract: To advance our understanding of the environmental fate and transport of macro- and micro-plastic debris, robust and reproducible methods, technologies, and analytical approaches are necessary for in situ plastic-type identification and characterization. This investigation compares four spectroscopic techniques: attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), near-infrared (NIR) reflectance spectroscopy, laser-induced breakdown spectroscopy (LIBS), and X-ray fluorescence (XRF) spectroscopy, coupled to seven classification methods, including machine learning classifiers, to determine accuracy for identifying type of both consumer plastics and marine plastic debris (MPD). With machine learning classifiers, consumer plastic types were identified with 99, 91, 97, and 70% success rates for ATR-FTIR, NIR reflectance spectroscopy, LIBS, and XRF, respectively. The classification of MPD had similar or lower success rates, likely arising from alterations to the plastic from environmental weathering processes with success rates of 99, 81, 76, and 66% for ATR-FTIR, NIR reflectance spectroscopy, LIBS, and XRF, respectively. Success rates indicate that ATR-FTIR, NIR reflectance spectroscopy, and LIBS coupled with machine learning classifiers can be used to identify both consumer and environmental plastic samples.
57 citations
TL;DR: In this article, a review of the development of remote detection based on laser-induced breakdown spectroscopy (LIBS) is presented, where three kinds of techniques are presented.
Abstract: Laser-induced breakdown spectroscopy (LIBS) is well known for its feature of remote detection. In this review, the development of remote detection based on LIBS is presented. Three kinds of...
56 citations
TL;DR: In this paper, the authors present a brief account of laser-induced breakdown spectroscopy (LIBS) equipments, preparation of samples, spectral fusion technology, field-portable and remote LIBS, the machine learning methods in LIBS and the applications of LIBS to analyzing various geological and environmental materials at some specific field sites.
Abstract: Conventional geological and environmental analyses rely heavily on the geologists’ assessments and time-consuming laboratory analyses that are relatively burdensome. Certain features of laser-induced breakdown spectroscopy (LIBS), especially the rapid and without complex sample preparation analysis (e.g., the remote and on-site detections and multi-element analyses), can significantly accelerate the field or remote detection of geological and environmental resources. Moreover, the LIBS technique combined with machine learning becomes an effective means to improve the accuracy of classification and quantitative analysis of the information derived from LIBS spectra data sets. This paper presents a brief account of LIBS equipments, preparation of samples, the spectral fusion technology, field-portable and remote LIBS, the machine learning methods in LIBS, the applications of LIBS to analyzing various geological and environmental materials at some specific field sites during the past six years. Finally, the potential applications of LIBS for some future developments are proposed.
54 citations