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dc.contributor.author
Rajagopalan, Ashwin Kumar
dc.contributor.supervisor
Mazzotti, Marco
dc.contributor.supervisor
Morari, Manfred
dc.contributor.supervisor
Myerson, Allan S.
dc.date.accessioned
2019-10-21T14:20:49Z
dc.date.available
2019-10-11T09:58:48Z
dc.date.available
2019-10-21T08:41:28Z
dc.date.available
2019-10-21T14:20:49Z
dc.date.issued
2019
dc.identifier.uri
http://hdl.handle.net/20.500.11850/369948
dc.identifier.doi
10.3929/ethz-b-000369948
dc.description.abstract
Crystallization is a separation process that has been practised and applied widely in fine chemical and pharmaceutical industries. In the majority of applications, it is used to obtain a high purity solid form, which often exhibits a distribution of sizes and shapes. Crystallization involves a number of fundamental phenomena -- often poorly understood -- like nucleation, growth, dissolution, agglomeration, to name a few. The lack of reliable monitoring tools and techniques inhibits attaining deeper insights into the mechanisms involved, which naturally affects the robust and optimal operation of these crystallization processes. Poor understanding coupled with stringent targets on the product quality for drugs in terms of purity, stability, and bioavailability, has attracted significant attention from both the academia and the industry. The work presented in this thesis led to improvements in the state-of-the-art imaging techniques for size and shape characterization of the solid phase in batch solution crystallization processes. Based on these improvements, studies making use of the shape information obtained from the imaging device were undertaken for several interesting and previously unexplored applications. The former point led to providing better characterization and understanding of the process from a macroscopic scale. While the latter point with the aid of the former led to several automated and controlled approaches to manipulate the size and shape of undesirable needle-like crystals to equant crystals. The key accomplishments of this thesis were • enhancements to the hardware of a stereoscopic imaging device and to the imaging analysis routines to classify crystals observed by the imaging device into five different shape classes and to obtain a three-dimensional reconstruction of these crystals. • assessing the reliability of commercial spectroscopic techniques to estimate solute concentration in batch crystallization processes and proposing a new approach based on volumetric reconstruction of crystals observed by the stereoscopic imaging device, to estimate the solute concentration. • transformation of needle-like crystals to more equant crystals in a multistage cyclic process consisting of wet milling, dissolution, and growth stages, exploiting the online monitoring capabilities of the imaging device and simple feedback control laws for the individual stages. To summarize, the results obtained certainly reinforce the potential and the competence of imaging tools to tackle a wide array of challenges faced by the crystallization community. Irrespective of the promising outcome, their potential pitfalls are definitely not overlooked and plausible proposals to overcome these are discussed diligently to assist future research on monitoring, on modeling and on control of crystallization processes.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
ETH Zurich
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
Crystallization
en_US
dc.subject
Particle size and shape distribution
en_US
dc.subject
Process Analytical Technology (PAT)
en_US
dc.subject
Feedback control
en_US
dc.subject
Particle size measurement
en_US
dc.subject
Process Control
en_US
dc.subject
population balance equations
en_US
dc.subject
Size and shape manipulation
en_US
dc.title
A Dual Projection Imaging System to Characterize Crystallization Processes: Design and Applications
en_US
dc.type
Doctoral Thesis
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2019-10-21
ethz.size
306 p.
en_US
ethz.code.ddc
DDC - DDC::6 - Technology, medicine and applied sciences::660 - Chemical engineering
ethz.grant
Crystallization: Optimal control and advanced monitoring 2.0 (CrystOCAM 2.0)
en_US
ethz.identifier.diss
26190
en_US
ethz.publication.place
Zurich
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02668 - Inst. f. Energie- und Verfahrenstechnik / Inst. Energy and Process Engineering::03484 - Mazzotti, Marco / Mazzotti, Marco
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02668 - Inst. f. Energie- und Verfahrenstechnik / Inst. Energy and Process Engineering::03484 - Mazzotti, Marco / Mazzotti, Marco
en_US
ethz.grant.agreementno
155971
ethz.grant.fundername
SNF
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.program
Projekte MINT
ethz.relation.references
https://doi.org/10.1016/j.powtec.2017.08.044
ethz.relation.references
https://doi.org/10.1021/acs.cgd.8b00473
ethz.relation.references
https://doi.org/10.1021/acs.jpclett.8b01998
ethz.relation.references
https://doi.org/10.1021/acs.cgd.8b01048
ethz.relation.references
https://doi.org/10.1021/acs.cgd.9b00080
ethz.relation.references
https://doi.org/10.1021/acs.cgd.9b00445
ethz.relation.references
https://doi.org/10.1016/j.compchemeng.2019.106581
ethz.date.deposited
2019-10-11T09:58:57Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2019-10-21T14:21:39Z
ethz.rosetta.lastUpdated
2022-03-28T23:55:16Z
ethz.rosetta.versionExported
true
ethz.COinS
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