Introductory description

Chemical Reaction Engineering and Data Analysis will familiarise students with the scientific and engineering concepts needed to transfer chemical reactions from a university lab to an industrial setting. The module concentrates on two interconnected parts: reactor scale-up (an introduction to chemical reaction engineering) and data processing and analysis (including numerical root finding and integration, ODE solving, kinetic model development and discrimination illustrated with heterogeneous catalytic reactions, determination of rate coefficients using NLLS, EVM/ODR, and Bayesian MCMC approaches, and Fourier transformations and analyses for signal processing). In addition to the scientific concepts, the module will introduce and develop the mathematical skills necessary to understand the material. Simultaneously, we will teach students to use Python as both a tool for mathematics and a coding language.

This module will be delivered over 10 weeks, comprising 30 peer instruction sessions (30 hours). The core content will be supported by worked examples and problem sets. The interactive lecture sessions aim to promote deeper learning and foster a comprehensive understanding of the subject. Students will be encouraged to organise into teams for each session to discuss tasks and engage with the material through interactive methods.

Class participation is encouraged through weekly homework assignments, which count toward the module's formative assessment. A 20% individual summative assessment is conducted via short weekly homework multiple-choice quizzes (2 questions per week, 20 questions in total over 10 weeks); the answers must be submitted weekly (e.g., via an assessed Moodle online quiz). The remaining 80% is assessed through 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 4 parts. Note that the underlying mathematical and coding concepts will be taught as needed.

Block 1 (6 lectures with active participation): Basic Chemical Reaction Engineering Concepts
(1) Mass/mole balance, the batch, semi-batch, and flow (e.g. CSTR, PFR, PBR) reactors.
(2) Conversion, recap rate laws and reaction stoichiometry (kinetics). Extension of reaction kinetics.
(3) Reactor sizing and Levenspiel Plots.
(4) Space time and Space Velocity

Block 2: (12 Lectures with active participation) Isothermal Reactor Design
(1) Reactors in parallel, series, and potpourri arrangements.
(2) Volume Changes in reactions
(3) Multiple Reactions
(4) Data-Processing I: Numerical root finding and integration, ODE solving.

Block 3. (6 lectures with active participation): Catalysis and Catalytic Reactors
(1) Heterogeneous catalysis and reactor design
(2) Data processing II: Kinetic model development:/discrimination rate laws, mechanisms, and rate-limiting steps.
(3) Data processing III: Determination of experimental parameters through NLLS, EVM/ODR and Bayesian MCMC methods.

Block 4 (6 lectures with active participation). Data Processing IV
(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.

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, EVM/ODR and Bayesian MCMC methods, and Fourier analysis of data for signal processing. 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 the formative assessed homework problem sets.
•  ETHICAL REASONING: Students can reason ethically when evaluating the design and use of chemical reaction engineering principles in modern society and illustrate their learning through the group active learning discussion sessions and formative homework sets.

Indicative reading list

Reading lists can be found in Talis

Specific reading list for the module

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.)