Bioprocess in-line monitoring using Raman spectroscopy and Indirect Hard Modeling (IHM): A simple calibration yields a robust model.

To increase the process productivity and product quality of bioprocesses, the in-line monitoring of critical process parameters is highly important. For monitoring substrate, metabolite, and product concentrations, Raman spectroscopy is a commonly used Process Analytical Technology (PAT) tool that can be applied in-situ and non-invasively. However, evaluating bioprocess Raman spectra with a robust state-of-the-art statistical model requires effortful model calibration. In the present study, we in-line monitored a glucose to ethanol fermentation by Saccharomyces cerevisiae (S. cerevisiae) using Raman spectroscopy in combination with the physics-based Indirect Hard Modeling (IHM) and showed successfully that IHM is an alternative to statistical models with significantly lower calibration effort. The IHM prediction model was developed and calibrated with only 16 Raman spectra in total, which did not include any process spectra. Nevertheless, IHM's root mean square errors of prediction (RMSEPs) for glucose (3.68 g/L) and ethanol (1.69 g/L) were comparable to the prediction quality of similar studies that used statistical models calibrated with several calibration batches. Despite our simple calibration, we succeeded in developing a robust model for evaluating bioprocess Raman spectra.

Is the Microgel Collapse a Two-Step Process? Exploiting Cononsolvency to Probe the Collapse Dynamics of Poly-N-isopropylacrylamide (pNIPAM).

Many applications of responsive microgels rely on the fast adaptation of the polymer network. However, the underlying dynamics of the de-/swelling process of the gels have not been fully understood. In the present work, we focus on the collapse kinetics of poly-N-isopropylacrylamide (pNIPAM) microgels due to cononsolvency. Cononsolvency means that either of the pure solvents, e.g., pure water or pure methanol, act as a so-called good solvent, leading to a swollen state of the polymer network. However, in mixtures of water and methanol, the previously swollen network undergoes a drastic volume loss. To further elucidate the cononsolvency transition, pNIPAM microgels with diameters between 20 and 110 µm were synthesized by microfluidics. To follow the dynamics, pure water was suddenly exchanged with an unfavorable mixture of 20 mol% methanol (solvent-jump) within a microfluidic channel. The dynamic response of the microgels was investigated by optical and fluorescence microscopy and Raman microspectroscopy. The experimental data provide unique and detailed insight into the size-dependent kinetics of the volume phase transition due to cononsolvency. The change in the microgel's diameter over time points to a two-step process of the microgel collapse with a biexponential behavior. Furthermore, the dependence between the two time constants from this biexponential behavior and the microgel's diameter in the collapsed state deviates from the square-power law proposed by Tanaka and Fillmore [ J. Chem. Phys. 1979, 70, 1214-1218]. The deviation is discussed considering the adhesion-induced deformation of the gels and the physical processes underlying the collapse.

Enrichment of methanol inside pNIPAM gels in the cononsolvency-induced collapse.

Crosslinked poly-N-isopropylacrylamide (pNIPAM) gels adapt to their environment by a unique transition from a flexible, swollen macromolecular network to a collapsed particle. pNIPAM gels are swollen in both, pure water and pure methanol (MeOH). However, a drastic volume loss is observed in mixtures of water and methanol over a wide composition range. This effect is referred to as cononsolvency. Cononsolvency couples the volume phase transition to the transport of the cosolvent into the polymeric network. So far, the mechanisms underlying cononsolvency have not been fully elucidated. To obtain insights on cononsolvency, Raman microspectroscopy was applied to capture spatially resolved spectra distinguishing between the surroundings and the inside of the gel. Here, we used Indirect Hard Modelling (IHM) for the spectral analysis. Mass balancing allowed the calculation of the solvent composition inside the pNIPAM gel. The results show an increased methanol fraction inside the collapsed gel as compared to its surroundings. Furthermore, the sensitivity of the vibrational bands of methanol to its local hydrogen bonding environment allow to derive information about the molecular interactions. The methanol peak shifts measured inside the gel point towards donor-type hydrogen bonds between methanol and the peptide group of pNIPAM in the cononsolvency-induced collapse. The presented data should enhance our understanding of cononsolvency.

Multicomponent diffusion coefficients from microfluidics using Raman microspectroscopy.

Diffusion is slow. Thus, diffusion experiments are intrinsically time-consuming and laborious. Additionally, the experimental effort is multiplied for multicomponent systems as the determination of multicomponent diffusion coefficients typically requires several experiments. To reduce the experimental effort, we present the first microfluidic diffusion measurement method for multicomponent liquid systems. The measurement setup combines a microfluidic chip with Raman microspectroscopy. Excellent agreement between experimental results and literature data is achieved for the binary system cyclohexane + toluene and the ternary system 1-propanol + 1-chlorobutane + heptane. The Fick diffusion coefficients are obtained from fitting a multicomponent convection-diffusion model to the mole fractions measured in experiments. Ternary diffusion coefficients can be obtained from a single experiment; high accuracy is already obtained from two experiments. Advantages of the presented measurement method are thus short measurement times, reduced sample consumption, and less experiments for the determination of a multicomponent diffusion coefficient.