The Focused Beam Reflectance Measurement (FBRM) technique provides on‐line and in‐situ information about the chord length distribution of a population of particles in dispersion. This is rather promising for applications such as crystal size distribution control in crystallization processes. The objective of this study is to deepen the understanding of the characteristics of the FBRM measurement. On the one hand, a model is presented, which allows in principle to transform particle size distributions (PSD) into chord length distributions (CLD). On the other hand, measurements with particles in suspension show the critical dependence of the measurement on the optical properties of the system. A special technique has been developed to measure CLDs of single particles. These measurements clarify some of the above effects, detect possible over‐ and underestimations of particle size and give indications about how to interpret and exploit on‐line CLD spectra.

The control objectives of batch crystallization processes are often defined in terms of particle size distribution (PSD), or properties related to the PSD, viz. average particle size, product filterability, dry solids flow properties, etc. To achieve these control objectives, a constrained nonlinear model-based optimization strategy has been adopted. This involves the detailed modeling of batch crystallization including model validation and parameter estimation, on-line monitoring of supersaturation and PSD, and the application of optimization strategies. A deterministic population balance model accounting for solution thermodynamics, crystal growth, and nucleation has been developed. State estimation is achieved by the on-line monitoring of temperature, concentrations in the liquid phase, particle density, and PSD. For this purpose, the focused beam reflectance measurement (FBRM) provides an on-line, in-situ information of crystal size and particle concentration in the form of a chord length distribution (CLD). A method using a three-dimensional geometrical CLD model and an inverse technique based on projections onto convex sets (POCS) has been introduced to calculate PSDs from CLD raw data. These concepts are applied to the batch cooling crystallization of paracetamol in ethanol.

16Given the increasing penetration of renewable energy technologies as distributed generation 17 embedded in the consumption centres, there is growing interest in energy storage systems 18 located very close to consumers. These systems allow to increase the amount of renewable 19 energy generation consumed locally, they provide opportunities for demand-side 20 management and help to decarbonise the electricity, heating and transport sectors. 21In this paper, the authors present an interdisciplinary review of community energy storage 22 (CES) with a focus on its potential role and challenges as a key element within the wider 23 energy system. The discussion includes: the whole spectrum of applications and 24 technologies with a strong emphasis on end user applications; techno-economic, 25 environmental and social assessments of CES; and an outlook on CES from the customer, 26 utility company and policy-maker perspectives. Currently, in general only traditional thermal 27 storage with water tanks is economically viable. However, CES is expected to offer new 28 opportunities for the energy transition since the community scale introduces several 29 advantages for electrochemical technologies such as batteries. Technical and economic 30 benefits over energy storage in single dwellings are driven by enhanced performance due to 31 less spiky community demand profile and economies of scale respectively. In addition, CES 32 brings new opportunities for citizen participation within communities and helps to increase 33 awareness of energy consumption and environmental impacts. 34

Crystallization at production scale is typically a poorly understood unit operation, with little implementation of the first principles aspect of crystallization in its design, optimization, and control. Problems with production crystallizers include the following: (1) inconsistencies of batch-to-batch in terms of the size and number of crystals produced and (2) the purity profile (residual impurities in crystals, or wrong polymorph or chiral purity). This can have a significant impact both on product quality and downstream process unit operations including filtration, drying, milling, and product formulation. This contribution reviews typical problems encountered in production crystallization, with case studies, advice, and strategies to understand and avoid these problems through the use of in situ crystallization characterization tools.