Mathematical modeling, simulation, and optimal design of pharmaceutical crystallizers

Rasche, Michael Lawrence

Permalink

https://hdl.handle.net/2142/78427 Copy

Description

Title

Mathematical modeling, simulation, and optimal design of pharmaceutical crystallizers

Author(s)

Rasche, Michael Lawrence

Issue Date

2015-04-21

Director of Research (if dissertation) or Advisor (if thesis)

Braatz, Richard D.

Doctoral Committee Chair(s)

Braatz, Richard D.

Committee Member(s)

• Kenis, Paul J.A.
• Suslick, Kenneth S.
• Rao, Christopher V.

Department of Study

Chemical & Biomolecular Engr

Discipline

Chemical Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• crystallizer design
• population balance
• sonofragmentation
• slug flow
• simulation

Abstract

Crystallization is the most important purification process in the pharmaceutical industry. In addition to purification, this process can generate solid particles for incorporation with excipients into drug products such as tablets with precisely tunable quantities of active pharmaceutical ingredients. The mathematical modeling and simulation of crystallization processes are useful in systems engineering, with the key conservation equation for the particle size distribution being a partial differential equation known as the population balance equation. This thesis constructs population balance models for three distinct particulate processes: 1) the breakage of crystals due to ultrasonication, 2) a semi-batch anti-solvent crystallization, and 3) continuous slug-flow crystallization, which are solved by three distinct simulation methods: 1) breakage matrix with integer arithmetic, 2) method of characteristics, 3) method of moments combined with the method of lines. The population balance models are also employed for three different engineering purposes: kinetics estimation, steady-state process design, and the design of dynamic feedback control structures. Comparisons to experimental data are made where possible to keep the simulations relevant and grounded in reality. Simulations 1 and 3 are the first to simulate their corresponding processes. Simulation 2 provides a method to substantially reduce experimental costs for the estimation of crystallization kinetics that is contrary to the current literature. All three studies employ mathematical models to advance crystallization technology.

Graduation Semester

2015-5

Type of Resource

text

Permalink

http://hdl.handle.net/2142/78427

Copyright and License Information

Copyright 2015 Michael Rasche

Owning Collections