Temperature Correction
of Spectra to Improve Solute
Concentration Monitoring by In Situ Ultraviolet and Mid-Infrared Spectrometries
toward Isothermal Local Model Performance
posted on 2022-11-04, 14:36authored byMagdalene
W. S. Chong, Thomas McGlone, Ching Yee Chai, Naomi E. B. Briggs, Cameron J. Brown, Francesca Perciballi, Jaclyn Dunn, Andrew J. Parrott, Paul Dallin, John Andrews, Alison Nordon, Alastair J. Florence
Changes in temperature can significantly affect spectroscopic-based
methods for in situ monitoring of processes. As varying temperature
is inherent to many processes, associated temperature effects on spectra
are unavoidable, which can hinder solute concentration determination.
Ultraviolet (UV) and mid-infrared (IR) data were acquired for l-ascorbic acid (LAA) in MeCN/H2O (80:20 w/w) at
different concentrations and temperatures. For both techniques, global
partial least squares (PLS) models for prediction of LAA concentration
constructed without preprocessing of the spectra required a high number
of latent variables to account for the effects of temperature on the
spectra (root mean square error of cross validation (RMSECV) of 0.18
and 0.16 g/100 g solvent, for UV and IR datasets, respectively). The
PLS models constructed on the first derivative spectra required fewer
latent variables, yielding variable results in accuracy (RMSECV of
0.23 and 0.06 g/100 g solvent, respectively). Corresponding isothermal
local models constructed indicated improved model performance that
required fewer latent variables in the absence of temperature effects
(RMSECV of 0.01 and 0.04 g/100 g solvent, respectively). Temperature
correction of the spectral data via loading space standardization
(LSS) enabled the construction of global models using the same number
of latent variables as the corresponding local model, which exhibited
comparable model performance (RMSECV of 0.06 and 0.04 g/100 g solvent,
respectively). The additional chemometric effort required for LSS
is justified if prediction of solute concentration is required for
in situ monitoring and control of cooling crystallization with an
accuracy and precision approaching that attainable using an isothermal
local model. However, the model performance with minimal preprocessing
may be sufficient, for example, in the early phase development of
a cooling crystallization process, where high accuracy is not always
required. UV and IR spectrometries were used to determine solubility
diagrams for LAA in MeCN/H2O (80:20 w/w), which were found
to be accurate compared to those obtained using the traditional techniques
of transmittance and gravimetric measurement. For both UV and IR spectrometries,
solubility values obtained from models with LSS temperature correction
were in better agreement with those determined gravimetrically. In
this first example of the application of LSS to UV spectra, significant
improvement in the predicted solute concentration is achieved with
the additional chemometric effort. There is no extra experimental
burden associated with the use of LSS if a structured approach is
employed to acquire calibration data that account for both temperature
and concentration.