Rapid determination of rhodium, palladium, and platinum in supported metal catalysts using multivariate analysis of laser induced breakdown spectroscopy data

2018 ◽  
Vol 145 ◽  
pp. 58-63 ◽  
Author(s):  
Jacob E. Jaine ◽  
Michael R. Mucalo
Molecules ◽  
2018 ◽  
Vol 23 (11) ◽  
pp. 2930 ◽  
Author(s):  
Tingting Shen ◽  
Wenwen Kong ◽  
Fei Liu ◽  
Zhenghui Chen ◽  
Jingdong Yao ◽  
...  

Quick access to cadmium (Cd) contamination in lettuce is important to supervise the leafy vegetable growth environment and market. This study aims to apply laser-induced breakdown spectroscopy (LIBS) technology for fast determination of Cd content and diagnosis of the Cd contamination degree in lettuce. Emission lines Cd II 214.44 nm, Cd II 226.50 nm, and Cd I 228.80 nm were selected to establish the univariate analysis model. Multivariate analysis including partial least squares (PLS) regression, was used to establish Cd content calibration models, and PLS model based on 22 variables selected by genetic algorithm (GA) obtained the best performance with correlation coefficient in the prediction set Rp2 = 0.9716, limit of detection (LOD) = 1.7 mg/kg. K-Nearest Neighbors (KNN) and random forest (RF) were used to analyze Cd contamination degree, and RF model obtained the correct classification rate of 100% in prediction set. The preliminary results indicate LIBS coupled with chemometrics could be used as a fast, efficient and low-cost method to assess Cd contamination in the vegetable industry.


2013 ◽  
Vol 39 (1) ◽  
pp. 81-83 ◽  
Author(s):  
A. M. Popov ◽  
M. O. Kozhnov ◽  
T. A. Labutin ◽  
S. M. Zaytsev ◽  
A. N. Drozdova ◽  
...  

2018 ◽  
Vol 10 (40) ◽  
pp. 4879-4885 ◽  
Author(s):  
Song Ye ◽  
Xiao Chen ◽  
Daming Dong ◽  
Jiejun Wang ◽  
Xinqiang Wang ◽  
...  

Chemical oxygen demand (COD) is a water quality indicator that is typically measured by lengthy chemical analysis methods in the laboratory, which indicates that obtaining rapid results is difficult.


2018 ◽  
Vol 61 (3) ◽  
pp. 821-829 ◽  
Author(s):  
Jiyu Peng ◽  
Lanhan Ye ◽  
Tingting Shen ◽  
Fei Liu ◽  
Kunlin Song ◽  
...  

Abstract. Fast and effective measures to determine heavy metals play an important role in ensuring food quality and safety. In this experiment, laser-induced breakdown spectroscopy (LIBS) was used to detect copper content (Cu) in tobacco ( L.) leaves. The experimental parameters for detection, including laser energy, delay time, and camera gate width, were optimized by response surface methodology (RSM). Univariate analysis and multivariate analysis, including partial least squares regression (PLSR) and extreme learning machine (ELM), were used to establish calibration models. In addition, different preprocessing methods were used to eliminate the signal variations and further improve the calibration performance, including baseline correction, background normalization, area normalization, and standard normal variate (SNV) normalization. The results showed that LIBS combined with both univariate and multivariate methods could be used to detect copper content in tobacco leaves. SNV and area normalization were efficient in dealing with signal variations and improving the calibration performance. The ELM model with SNV normalized variables in the spectral region of 324.02 to 325.98 nm achieved the best performance (R2 = 0.9552 and RMSE = 4.8416 mg kg-1 in the testing set). The results provide the first proof-of-principle data for fast determination of copper content in tobacco leaves. Keywords: Copper content, Laser-induced breakdown spectroscopy, Multivariate calibration, Response surface methodology, Tobacco leaves, Univariate calibration.


2015 ◽  
Vol 100 (8-9) ◽  
pp. 1921-1931 ◽  
Author(s):  
Kristen A. Kochelek ◽  
Nancy J. McMillan ◽  
Catherine E. McManus ◽  
David L. Daniel

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