Growth Rate Estimation of β <scp>l</scp>-Glutamic Acid from Online Measurements of Multidimensional Particle Size Distributions and Concentration

Ochsenbein, David R.; Schorsch, Stefan; Vetter, Thomas; Mazzotti, Marco; Morari, Manfred

doi:10.1021/ie4031852

Cited by 51 publications

(89 citation statements)

References 45 publications

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“…For the later purpose, shape descriptors need to be calculated.The typical 3D shape structure of a potash alum crystal grown from solution was reconstructed from 2D stereo images obtained from potash alum crystals [69]. Mazzotti and co-workers [48,73] used a flowcell with one camera and two mirrors to generate stereo images for 3D shape reconstruction. The reconstruction ability of this method depends on the developed model and the detection of image features such as lines and corners.…”

Section: Image Analysis and 3d Reconstructionmentioning

confidence: 99%

“…using images not only at the current time but also those before the current moment, the window width can be defined by users [60,70]. Although some advances have been made [45,50,64,65,69,73,139,140], further research is definitely needed to address this issue, and also the effect of secondary nucleation, breakage/aggregation, high-solid concentration, and co-existence of multiple polymorphic forms on accurate estimation of facet crystal growth rates.…”

Section: Growth Rate Estimation Of Crystals Grown In Reactorsmentioning

confidence: 99%

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Measurement, modelling, and closed-loop control of crystal shape distribution: Literature review and future perspectives

2016

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Crystal morphology is known to be of great importance to the end-use properties of the crystal product and affect the down-stream processing such as in filtration and drying, but was previously regarded as too challenging to achieve automatic closed-loop control. As a consequence, previous work has focused on control the crystal size distribution (CSD) where the size of a crystal is often defined as the diameter of a sphere that has the same volume of the crystal. This paper reviews very promising new advances made in recent years in morphological population balance models for modelling and simulation of crystal shape distribution (CShD), measurement and estimation of crystal facet growth kinetics, as well as in 2D and 3D imaging for on-line characterisation of crystal morphology and CShD. A framework is presented integrating various components in order to achieve the ultimate objective of model-based closed-loop control of CShD. The knowledge gaps and challenges that require further research are also identified.

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Section: Image Analysis and 3d Reconstructionmentioning

confidence: 99%

Section: Growth Rate Estimation Of Crystals Grown In Reactorsmentioning

confidence: 99%

Measurement, modelling, and closed-loop control of crystal shape distribution: Literature review and future perspectives

2016

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“…1,8,9 Typically, when modeling crystal formation, a complex number of phenomena need to be included, such as crystal nucleation, growth, agglomeration, and breakage. 1,10 As a result of the agglomeration of particles, clusters with highly irregular structures are often produced. The geometrical features of these clusters cannot be described by means of conventional Euclidean geometry.…”

Section: Introductionmentioning

confidence: 99%

Growth and Aggregation Regulate Clusters Structural Properties and Gel Time

Lazzari

Lattuada

2017

J. Phys. Chem. B

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When particles undergo aggregation, very often they form structures that can be described with fractal geometry concepts. The spatial organization of the particles embedded in these aggregates, quantified by means of their fractal dimension, plays a key role in the clusters' diffusion and aggregation process. Fractal dimensions are typically known for some specific, ideal aggregation scenarios, such as for diluted diffusion limited cluster aggregation (DLCA) or reaction limited cluster aggregation (RLCA). The situation becomes significantly more complicated as soon as the initial particle concentration increases and fractal-dimension changing phenomena, such as particle growth, occur. In this frame, the aim of the present work is twofold: (i) to investigate the clusters' spatial organization in a scenario where growth and aggregation occur simultaneously and (ii) to assess the corresponding aggregation kinetics. To this end, an ad hoc Monte Carlo model has been developed. Both DLCA and RLCA regimes have been explored at several initial primary particle concentrations and for different growth rates. The results were discussed in terms of the characteristic times of growth (τ G ) and aggregation (τ A ), as well as the rate at which the structural properties change, v R . It was then possible to propose empirical correlations in the form d m = d m (v R ) and t gel = t gel (τ A , τ G ) to relate the evolution of the mass mobility exponent d m and the gel times to the simultaneously occurring processes of growth and aggregation.

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“…The latter has seen considerable progress in the last few years, with the advent of an era of new imaging methods, capable of measuring both size and shape of particles in real processes. [21][22][23][24] These tools allow for an unprecedented level of detail regarding the interpretation of images and characterization of systems 21,25,26 and it seems sensible to assume that this progress may bring forth new discoveries in the field of agglomeration.…”

Section: Introductionmentioning

confidence: 99%

Agglomeration of Needle-like Crystals in Suspension: I. Measurements

Ochsenbein

Vetter

Schorsch

et al. 2015

Crystal Growth & Design

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A technique for the detection and measurement of the agglomeration of needle-like particles is presented. A novel image analysis routine, based on a supervised machine learning strategy, is used to identify agglomerates that are subsequently characterized by their volume. Through repeated measurement of a large number of agglomerates, a 1D particle size distribution of agglomerates is reconstructed. Concurrently, established tools are used to characterize needle-like primary crystals, whose shape is described by cylinders and whose population can be described by a separate, two-dimensional

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Growth Rate Estimation of β l-Glutamic Acid from Online Measurements of Multidimensional Particle Size Distributions and Concentration

Cited by 51 publications

References 45 publications

Measurement, modelling, and closed-loop control of crystal shape distribution: Literature review and future perspectives

Measurement, modelling, and closed-loop control of crystal shape distribution: Literature review and future perspectives

Growth and Aggregation Regulate Clusters Structural Properties and Gel Time

Agglomeration of Needle-like Crystals in Suspension: I. Measurements

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