{'fraction_non_alphanumeric': 0.011320754716981131, 'fraction_numerical': 0.005660377358490566, 'mean_word_length': 5.469512195121951, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Multivariate curve resolution for understanding complex reactions

Chemometrics is applied to in situ infrared spectra collected from a complex reacting mixture to elucidate the reaction mechanism. A series of models beginning with simple peak area progressing to classical least squares then to multivariate curve resolution with nonnegative spectral and concentration profile constraints and finally to multivariate curve resolution with nonnegative constraints and spectral and concentration profile equality constraints are used. The logic used to develop from the simple models to the more complex models is discussed. An intermediate component is estimated, and for each of two of the chemical components, two pure component spectral profiles are required to accurately fit the validation data. The changing polarity of the system is believed to be responsible for the multiple pure spectra required for two single chemical components. A total of 11 components are used to accurately describe the reacting system. Copyright © 2013 John Wiley & Sons, Ltd.