Rapid screening of critical process parameters based on near infrared spectroscopy: a case study of the ethanol precipitation process

2015 ◽  
Vol 7 (11) ◽  
pp. 4616-4620 ◽  
Author(s):  
Binjun Yan ◽  
Haibin Qu
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Process Parameters ◽  
Near Infrared ◽  
Rapid Screening ◽  
Precipitation Process ◽  
Ethanol Precipitation ◽  
Critical Process Parameters ◽  
Critical Process

Rapid screening of critical process parameters based on NIRS.

scholarly journals The relevance study of effective information between near infrared spectroscopy and chondroitin sulfate in ethanol precipitation process

2014 ◽  
Vol 07 (06) ◽  
pp. 1450022 ◽  
Author(s):  
Lian Li ◽  
Baoyang Ding ◽  
Qi Yang ◽  
Shang Chen ◽  
Huaying Ren ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Chondroitin Sulfate ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
Process Analytical Technology ◽  
Precipitation Process ◽  
Calibration Model ◽  
Optical Cell ◽  
Ethanol Precipitation

Near infrared spectroscopy (NIRS) is based on molecular overtone and combination vibrations. It is difficult to assign specific features under complicated system. So it is necessary to find the relevance between NIRS and target compound. For this purpose, the chondroitin sulfate (CS) ethanol precipitation process was selected as the research model, and 90 samples of 5 different batches were collected and the content of CS was determined by modified carbazole method. The relevance between NIRS and CS was studied throughout optical pathlength, pretreatment methods and variables selection methods. In conclusion, the first derivative with Savitzky–Golay (SG) smoothing was selected as the best pretreatment, and the best spectral region was selected using interval partial least squares (iPLS) method under 1 mm optical cell. A multivariate calibration model was established using PLS algorithm for determining the content of CS, and the root mean square error of prediction (RMSEP) is 3.934 g⋅L-1. This method will have great potential in process analytical technology in the future.

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