The crystal growth kinetics of a proprietary active pharmaceutical ingredient (API) was investigated by isothermal seeded batch de-supersaturation experiments in solvent mixtures using the "true" thermodynamic representation of the supersaturation driving force, which considers the activities of the saturated and supersaturated states. Three approaches to approximate the experimentally inaccessible activity coefficients of the supersaturated state were assessed, as well as the most common approximation, which omits the activity coefficients altogether. Subsequently, the supersaturation data from the different expressions were fed into a population balance model to estimate kinetic parameters for the empirical, Burton− Cabrera−Frank, and birth-and-spread growth models. The results demonstrate that the approach used to compute the supersaturation alters the estimated kinetic parameters significantly, having potentially serious implications for their physical interpretation and for extracting the physical properties they represent in lumped form. Moreover, including the chemical activities in the supersaturation leads to kinetic parameters with a tighter joint confidence interval and weaker parameter correlation that can better explain the experimental observation of the API growing appreciably only under higher antisolvent amounts. Finally, the simultaneous occurrence of multiple crystal growth mechanisms is investigated, concluding that the additive contribution of B+S and BCF best explains the supersaturation decay observed in the experiments for this API.

This document contains the post-print pdf-version of the refereed paper: "Optimal experiment design under parametric uncertainty: a comparison of a sensitivities based approach versus a polynomial chaos based stochastic approach" by Philippe Nimmegeers, Satyajeet Bhonsale, Dries Telen, and Jan Van Impe which has been archived on the university repository Lirias (https://lirias.kuleuven.be/) of the KU Leuven.The content is identical to the content of the published paper, but without the final typesetting by the publisher.

Second-generation biomass is an underexploited resource, which can lead to valuable products in a circular economy. Available locally as food waste, gardening and pruning waste or agricultural waste, second-generation biomass can be processed into high-valued products through a flexi-feed small-scale biorefinery. The flexi-feed and the use of local biomass ensure the continuous availability of feedstock at low logistic costs. However, the viability and sustainability of the biorefinery must be ensured by the design and optimal operation. While the design depends on the available feedstock and the desired products, the optimisation requires the availability of a mathematical model of the biorefinery. This paper details the design and modelling of a small-scale biorefinery in view of its optimisation at a later stage. The proposed biorefinery comprises the following processes: steam refining, anaerobic digestion, ammonia stripping and composting. The models’ integration and the overall biorefinery operation are emphasised. The simulation results assess the potential of the real biowaste collected in a commune in Flanders (Belgium) to produce oligosaccharides, lignin, fibres, biogas, fertiliser and compost. This represents a baseline scenario, which can be subsequently employed in the evaluation of optimised solutions. The outlined approach leads to better feedstocks utilisation and product diversification, raising awareness on the impact and importance of small-scale biorefineries at a commune level.