Open AccessStudy on the Processing Technology of Calamine Calcination by Near-Infrared Spectroscopy
Author(s) -
Xiaodong Zhang,
Long Chen,
Yu Shu Bai,
Keli Chen
Publication year - 2019
Publication title -
journal of spectroscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.323
H-Index - 21
eISSN - 2314-4920
pISSN - 2314-4939
DOI - 10.1155/2019/9326789
Subject(s) - calcination , spectroscopy , infrared spectroscopy , zinc , infrared , analytical chemistry (journal) , materials science , process analytical technology , mineralogy , chemistry , environmental chemistry , chemical engineering , metallurgy , physics , engineering , catalysis , optics , biochemistry , organic chemistry , quantum mechanics , bioprocess
Near-infrared spectroscopy has been widely used in qualitative and quantitative analysis and online monitoring in the production process of traditional Chinese medicines. The aim was to establish a fast determination model of zinc oxide (ZnO) content in calcined calamine and to explore methods through judging the end point of calamine calcination. Eight batches of calamine samples sourced from hydrozincite with different sizes and textures were calcined at different temperatures. During the calcination process, ZnO contents, X-ray diffraction (XRD) patterns, and near-infrared spectra of the samples were used to analyze their changes rules. The model of determining ZnO content of calcined calamine was established to use near-infrared spectroscopy based on the partial least squares (PLS) regression algorithm. In addition, this paper summarized the change rules of calamine in calcination according to XRD patterns, using the “ K value” quantitative method to define the characteristic T value. When the T value was equal to 1.00 (100%), that is to say, the calamine sample was completely calcined. Then, matching the near-infrared spectroscopy data with the T value and establishing the T value analysis model using the PLS algorithm were performed. Through cross and independent validation and evaluation, it was proved that the two models were very effective and had strong predictive abilities. Finally, the purpose of the online monitoring of the calcination process and controlling the quality of the calcined calamine was achieved.