Introductory description

Chemical Reaction Engineering and Data Analysis will familiarise students with the science and engineering concepts needed to transfer chemistry reactions from a university lab to an industrial setting. The module focuses on two integrated parts: reactor scale-up (an introduction to chemical reaction engineering) and data processing and analysis (NLLS parametric regression to a specific model with a set of parameters, and Fourier transformations and analysis). Beside the specific scientific concepts, the module will introduce and build the mathematical skills required to be able to comprehend the material. At the same time, we will teach students using Python as a mathematical and coding tool.

This module will be taught over 10 weeks across 30 peer instruction sessions (30 hours). The core material will be supported with worked-out example problem sets. The interactive lecture sessions will enhance more profound learning and develop a thorough understanding of the material. Students will be divided into teams for each session to discuss tasks and contribute to the delivered material using interactive methods, such as Vevox.

Class participation is stimulated by setting weekly homework assignments. These are part of the formative assessment of the module. A 20% summative assessment in the form of a homework problem set is given (1 question per block, provided during the teaching of each block: 5 questions in total to be handed in as one complete set after the module has been taught). The remaining 80% is in the form of a written individual exam.

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

This module consists of 5 parts. Note that underlying mathematical concepts will be taught at the points needed.

Block 1 (4 interactive lectures + 2 workshops): Basic Chemical Reaction Engineering Concepts

(1) Mass balance, the batch, semi-batch, and flow (CSTR, PFR, PBR) reactors.
(2) Extent of reaction/conversion, recap rate laws and reaction stoichiometry (kinetics). Extension of reaction kinetics.
(3) Residence time distributions in flow reactors.
(4) Reactor sizing.
(5) (2 h) Implement what we have learned thus far.

Block 2: (4 interactive lectures + 2 workshops) Isothermal Reactor Design

(1) Examples of reactions in batch, semi-batch, and a CSTR.
(2) Examples of reactions in CSTR and tubular setups.
(3) Extension to multiple reactor systems (series, parallel).
(4) Examples of complex reactions (such as parallel, reversible, autocatalytic).
(5) (2 h) Implement what we have learned thus far.

Block 3. (4 interactive lectures + 2 workshops): Catalysis and Catalytic Reactors

(1) Catalysts and steps in catalytic reactions.
(2) Rate laws, mechanisms, and rate-limiting steps.
(3) Reactor design in heterogeneous catalysis.
(4) Catalyst deactivation and/or diffusion issues.
(5) (2 h) Implement what we have learned thus far.

Block 4. (4 interactive lectures + 2 workshops): Data Processing I

(1) Uncertainty in data, errors, and error space.
(2) How to carry out NLLS regression, part 1 with examples.
(3) How to carry out NLLS regression, part 2 with examples.
(4) Practical examples: kinetic modeling.
(5) (2 h) Implement what we have learned thus far.

Block 5. (4 interactive lectures + 2 workshops): Data Processing II

(1) Signals and noise in real analytical data.
(2) Harmonic inversion and the Fourier Transform.
(3) Fourier deconvolution.
(4) Filtering and smoothing, linear and non-linear curve fitting.
(5) (2 h) Implement what we have learned thus far.

Learning outcomes

By the end of the module, students should be able to:

•  KNOWLEDGE: The module will provide students with a solid understanding of several fundamental and contemporary aspects of chemical reaction engineering (scale-up), and data analysis. We will discuss basic chemical reaction engineering concepts, isothermal reactor design, catalysis, and catalytic reactions. Data processing by NLLS regression, and Fourier analysis of data. Students will develop specialized knowledge in these areas and integrate this across the broader areas of chemistry, chemical engineering, physics and manufacturing.
•  APPLIED LEARNING: This module has active learning activities throughout its delivery and across each block of learning, in which concepts are applied and integrated in an interactive discussion format.
•  DIVERSE PERSPECTIVES: Through interactive learning in groups and individual homework sets, students can evaluate diverse points of view embedded within varying frameworks, which may include technological/scientific context, societal and environmental impact, and temporal and trending contexts.
•  COMPETENCY SKILLS: Students will engage in critical inquiry and develop their skill set to process, understand, communicate/explain and evaluate scientific principles and their impact.
•  COMMUNICATION: Students will be able to communicate effectively in presenting ideas orally (especially in the group-based active learning sessions), and in the format of assessed homework problem sets.
•  ETHICAL REASONING: Students can reason ethically when evaluating the design and use of chemical reaction engineering and formulation science principles in modern society and illustrate their learning through the group active learning discussion sessions and homework sets.

Indicative reading list

Reading lists can be found in Talis

Interdisciplinary

This module combines elements from chemistry, physics, engineering, and mathematics.

Subject specific skills

 KNOWLEDGE
(See learning outcomes for description)

Transferable skills

 APPLIED LEARNING:
 DIVERSE PERSPECTIVES:
 COMPETENCY SKILLS:
 COMMUNICATION:
 ETHICAL REASONING:
(See learning outcomes for descriptions.)