Abstract

Ash content, as a crucial indicator of coal quality, its rapid and accurate determination is pivotal to improve the energy utilization of coal and reduce environmental pollution. Traditional spectroscopic methods face significant challenges in acquiring accurate information from coal samples due to the notorious matrix effects arising from their complex composition, vast molecular structure, and diverse coal types. In this study, the feasibility of total reflection X-ray fluorescence (TXRF) combined with partial least squares (PLS) for the determination of coal ash was firstly investigated based on the TXRF being unaffected by matrix effects. Firstly, coal samples were prepared as suspensions, and the effects of sample particle size and different dispersants on the results of TXRF analyses were evaluated. The accuracy and applicability of the chosen sample preparation strategies were further validated using inductively coupled plasma mass spectrometry (ICP-MS) and two certified reference materials (CRMs). Subsequently, based on the analysis of 19 coal samples, the impact of three different predictive variables on the performance of the PLS model was investigated: (a) TXRF full spectrum normalized by the net intensity of the internal standard; (b) net intensity of characteristic peaks for 12 elements (Al, Si, K, Ca, Ti, Fe, Cr, Mn, Cu, Ni, and Sr) normalized by the net intensity of the internal standard; (c) concentrations of the aforementioned 12 elements. The results demonstrate that the PLS model constructed usingthe TXRF full spectrum normalized by the net intensity of the internal standard exhibits the best predictive capabilities, with the determination coefficient of calibration set (R2) and mean square error (MSE) of the prediction set reaching 0.9736 and 0.99 %, respectively. Moreover, the measurement accuracy of this model was six times greater than that obtained with traditional X-ray fluorescence (XRF). Presented analytical results display the possibilities of combining TXRF with PLS for coal quality evaluation.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.