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Course profile

Chemical Thermodynamics (CHEE2030)

Study period
Sem 2 2024
Location
St Lucia
Attendance mode
In Person

Course overview

Study period
Semester 2, 2024 (22/07/2024 - 18/11/2024)
Study level
Undergraduate
Location
St Lucia
Attendance mode
In Person
Units
2
Administrative campus
St Lucia
Coordinating unit
Chemical Engineering School

1st and 2nd laws of thermodynamics for steady and unsteady systems. Exergy analysis. Equations of state. Gibbs free energy, fugacity and activity. Phase equilibria, electrochemical equilibria. Pure components and solutions. Chemical reaction equilibria.

The main ideas covered in this course are:

1. Energy is conserved (1st Law).ᅠ Keeping track of energy is critically important in many processes and we will apply this to a range of processes.ᅠ

2. Energy always spreads (2nd Law). This imposes limits on what can and cannot be done.ᅠ

3. Phase and chemical equilibrium, regardless of the number of components, phases or reactions, is attained when the free energy of a system is minimised. This point is critical in solving a large number of Chemical Engineering problems and to scoping potential chemical processes.

4. Reliable data and/or equations are required to utilise points 1, 2, and 3 ᅠabove. There is a large amount of data and a large number of property equations (e.g. the various equations of state). The emphasis will be on using the data and equations and critically analysing if the data and/or equations used are suitable for the process you want to investigate.

You will have touched on these points before. This course will help you look at a range of problems to which these principles apply. Naturally this cannot be exhaustive, as Chemical Thermodynamics applies to many areas of engineering and science, but is rather aimed at equipping you with the tools and confidence to tackle unfamiliar problems using these principles.

Course requirements

Assumed background

This course expands upon concepts and knowledge from first year thermodynamics (ENGG1500) and ᅠfirst year ᅠchemistry (CHEM1100). Concepts such as enthalpy, entropy, heat capacity, the ideal gas law and the 1st and 2nd laws of thermodynamics, heats of reaction, and phase equilibrium should already be familiar to students.ᅠ Mathematics to a first year engineering level is required for ᅠthe manipulation of thermodynamic functions (e.g. derivatives, partial derivatives and integration).

Prerequisites

You'll need to complete the following courses before enrolling in this one:

ENGG1500. CHEE2001 to be completed prior to or concurrently with this course.

Companion or co-requisite courses

You'll need to complete the following courses at the same time:

CHEE2001

Incompatible

You can't enrol in this course if you've already completed the following:

CHEE3003

Course contact

Course staff

Timetable

The timetable for this course is available on the UQ Public Timetable.

Additional timetable information

  • There are normally two scheduled activities a week. First is a ᅠworkshop (WKS). There is one of these that everyone attends at the same time. Later in the week there is PBL session.ᅠ
  • There is a computer ICT class in week 1 (only) to cover Python skills used in the course ᅠ(ICT1-01-04). You will need to attend one of the sessions.ᅠ This is a ᅠclass to get students up to speed with what they need to know about solving stuff numerically for this course.ᅠ
  • There will be a Practical ᅠin Week 9. You will need to attend one of the sessions.ᅠ

Aims and outcomes

The aim of this course is to integrate concepts from chemistry and thermodynamics and extend them so students can apply them to realistic, as opposed to idealised, processes. With an understanding of these concepts, students will be able to critically analyse, formulate and solve diverse problems relating to energy and equilibrium.

The main ideas covered in this course are:

1. Energy is conserved (1st Law). Keeping track of energy is critically important in many processes and we will apply this to a range of processes.ᅠ

2. Energy always spreads (2nd Law). This imposes limits on what can and cannot be done.ᅠ

3. Phase and chemical equilibrium, regardless of the number of components, phases or reactions, is attained when the free energy of a system is minimised. This point is critical in solving a large number of Chemical Engineering problems and to scoping potential chemical processes.

4.ᅠReliable data and/or equations are required to utilise points 1, 2, and 3 above. There is a large amount of data and a large number of property equations (e.g. the various equations of state). The emphasis will be on using the data and equations and critically analysing if the data and/or equations used are suitable for the process you want to investigate.

You will have touched on these points before. This course will help you look at a range of problems to which these principles apply. Naturally this cannot be exhaustive, as Chemical Thermodynamics applies to many areas of engineering and science, but is rather aimed at equipping you with the tools and confidence to tackle unfamiliar problems using these principles.

Learning outcomes

After successfully completing this course you should be able to:

LO1.

Identify and explain the underlying thermodynamic principles of real processes: the first law, second law, and free energy minimisation.

LO2.

Source, and use, a wide range of thermodynamic data and charts.

LO3.

Explain the basis of ideal and non-ideal models for fluid and solution thermodynamic properties and apply them to process calculations.

LO4.

Identify and solve complex thermodynamic problems involving mass and energy balances, phase, and reaction equilibria.

LO5.

Use Matlab, Excel, and specialist thermodynamic software to perform complex thermodynamic calculations.

Assessment

Assessment summary

Category Assessment task Weight Due date
Tutorial/ Problem Set Problem Sets
  • Hurdle
26% Problem Set (Hurdle)

Every second Monday at 4pm Weeks 3, 5, 6, 7, 9, 13, week 11 Tue 2pm.

Examination Exam – In-Semester Outside Scheduled Class
  • Identity Verified
  • In-person
20% In-Semester Examination

9/09/2024

18:00-20:00

Practical/ Demonstration Practical Phase Diagram 4%

18/09/2024 - 20/09/2024

Attend your signed-on session.


Examination Exam – during Exam Period (Central)
  • Hurdle
  • Identity Verified
  • In-person
50% Final Examination (Hurdle)

End of Semester Exam Period

2/11/2024 - 16/11/2024

A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.

Assessment details

Problem Sets

  • Hurdle
Mode
Written
Category
Tutorial/ Problem Set
Weight
26% Problem Set (Hurdle)
Due date

Every second Monday at 4pm Weeks 3, 5, 6, 7, 9, 13, week 11 Tue 2pm.

Task description

Weekly problem sets will be worked on through the semester and submitted every second week.

They can be completed in self-formed pairs. No peer assessment will be applied. It is expected pairs will make an equal contribution. If your partner is not pulling their weight, form another pair! If this causes issues, discuss with coordinator. Individual submissions are allowed if you want or cannot find a partner that week.

The practice of the ICT - Python skills (Computer Exercise) class will be marked as one of problem sets.

The problem sets are evenly weighted. Your best 11 of 13 weekly problem sets (incl. ICT practice) will count towards determining your average mark for the problem sets.  

The due dates for problem sets are every second Mon 4pm weeks 3, 5, 6, 7, 9, 13, week 11 Tue 2pm.

This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.

Hurdle requirements

To pass the course you have to achieve a minimum of 45% in problem sets.

Submission guidelines

Submit online through Blackboard.

Deferral or extension

You may be able to apply for an extension.

Late submission

Assessments must be submitted on or before the due date. Late submissions of assessment items will only be accepted if approval for late submission has been obtained prior to the due date.

Penalties Apply for Late Submission

Refer PPL Assessment Procedure Section 3 Part C (48)

Problem sets

Max Extension Period

24 hrs

Late Penalty (Submitted after due date without an approved extension)

100% Late penalty

Rationale

This policy is so we can return graded problem sets within days of submission and make solutions available so you get frequent feedback throughout the semester.

How assessment will be modified for a student with a valid reason for an extension longer than the Maximum Extension Period but less than or equal to 4 weeks

An approved extension for a problem set will result in an exemption (not an extension) and a reduction in your "best of" count for your problem sets.

Exam – In-Semester Outside Scheduled Class

  • Identity Verified
  • In-person
Mode
Activity/ Performance, Written
Category
Examination
Weight
20% In-Semester Examination
Due date

9/09/2024

18:00-20:00

Task description

Closed book invigilated In-Semester Exam will cover materials of weeks 1 to 6. This exam may cover any material covered in those weeks except for calculations using Python/Excel/Factsage which are not part of the exam.

This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.

Exam details

Planning time 10 minutes
Duration 90 minutes
Calculator options

(In person) Casio FX82 series or UQ approved , labelled calculator only

Open/closed book Closed Book examination - no written materials permitted
Exam platform Paper based
Invigilation

Invigilated in person

Submission guidelines

Deferral or extension

You may be able to defer this exam.

Practical Phase Diagram

Mode
Activity/ Performance
Category
Practical/ Demonstration
Weight
4%
Due date

18/09/2024 - 20/09/2024

Attend your signed-on session.


Task description

Lab session where students work in groups to construct a ternary phase diagram for a liquid-liquid equlibrium system from experimental observation.

This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.

Lab sessions 46-542 Wet Lab.

18/9 Wed - PRA1 - 01 8am-10am; PRA 1 - 02 12pm-2pm; PRA 1 - 03 2pm-4pm; PRA 1 - 04 4pm-6pm;

19/9 Thu - PRA 1 - 05 12pm-2pm; PRA 1 - 06 2pm-4pm; PRA 1 - 07 4pm-6pm;

20/9 Fri - PRA 1 - 08 8am-10am; PRA 1 - 09 10am-12pm; PRA 1 -10 12pm-2pm;

Submission guidelines

Calculations and diagram submitted at the end of class (one set per group).

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.

Late submission

Assessments must be submitted on or before the due date. Late submissions of assessment items will only be accepted if approval for late submission has been obtained prior to the due date.

Penalties Apply for Late Submission

Refer PPL Assessment Procedure Section 3 Part C (48)

Exam – during Exam Period (Central)

  • Hurdle
  • Identity Verified
  • In-person
Mode
Written
Category
Examination
Weight
50% Final Examination (Hurdle)
Due date

End of Semester Exam Period

2/11/2024 - 16/11/2024

Task description

Exam is closed book. Material from all weeks will be covered. 

Students will be provided with a copy of the equation and data booklet. 

This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.

Hurdle requirements

To pass the course you have to achieve a minimum of 40% of the final examination assessment

Exam details

Planning time 10 minutes
Duration 180 minutes
Calculator options

(In person) Casio FX82 series or UQ approved , labelled calculator only

Open/closed book Closed Book examination - no written materials permitted
Exam platform Paper based
Invigilation

Invigilated in person

Submission guidelines

Deferral or extension

You may be able to defer this exam.

Course grading

Full criteria for each grade is available in the Assessment Procedure.

Grade Description
1 (Low Fail)

Absence of evidence of achievement of course learning outcomes.

Course grade description: Typically 0 - 19.9% overall Fail: Essentially no evidence of effort or understanding.

2 (Fail)

Minimal evidence of achievement of course learning outcomes.

Course grade description: Typically 20 - 44.9% overall OR with >=45% overall with with < 35% in problem sets and < 20% of the final examination assessment Fail: Demonstrates little understanding of the key concepts of the course. Will often start solutions on the wrong track and/or using methods/ calculations/ assumptions that contradict each other. May also fail to identify obvious sign and magnitude errors in erroneous calculations.

3 (Marginal Fail)

Demonstrated evidence of developing achievement of course learning outcomes

Course grade description: Typically 45 - 49.9% overall with >= 35 % in problem sets and >= 25% examination assessment OR with >=50% overall with < 45% in problem sets and < 40% of the final examination assessment Fail: Demonstrates a poor understanding of some key concepts. Starts some solutions on the wrong track and/or using methods/calculations/assumptions that contradict each other. May also fail to identify obvious sign and magnitude errors.

4 (Pass)

Demonstrated evidence of functional achievement of course learning outcomes.

Course grade description: Typically >= 50% overall with >= 45 % in problem sets and >= 40% of the final examination assessment Pass: Demonstrates a functional understanding of all concepts. Able to use these concepts to solve straight forward problems. Can start most complex problems with the correct concept and assumptions, but may not be able to complete the majority of these problems. Some contradictions are evident but should not be common. Able to identify most magnitude and sign errors.

5 (Credit)

Demonstrated evidence of proficient achievement of course learning outcomes.

Course grade description: Typically >= 65% overall with >= 60% in problem sets and >= 55% of the final examination assessment Credit: Demonstrates a good understanding of all concepts in the course with perhaps a very good understanding of some. Simple problems are (essentially) correctly solved with more complex problems solved (or more progress in these problems) than for a 4 but with some significant errors still. Essentially no contradictions in concepts/ calculations/ assumptions are evident. Able to identify essentially all magnitude and sign errors in erroneous calculations (i.e. unrealistic solutions).

6 (Distinction)

Demonstrated evidence of advanced achievement of course learning outcomes.

Course grade description: Typically >= 75% overall with >= 70% in problem sets and >= 65% of the final examination assessment Distinction: Demonstrates a very good understanding of concepts in the course that is unwavering when faced with unfamiliar problems. Simple problems are (essentially) correctly solved with most complex problems solved or with small errors. Errors (or incomplete solutions) are due to lack of attention to detail, not accounting for a subtlety of a problem or not being able to integrate several concepts in the one problem. Essentially no contradictions in concepts/ calculations/ assumptions are evident. Able to identify essentially all magnitude and sign errors in erroneous calculations (i.e. unrealistic solutions).

7 (High Distinction)

Demonstrated evidence of exceptional achievement of course learning outcomes.

Course grade description: Typically >= 85% overall with >= 80% in problem sets and >= 75% of the final examination assessment High Distinction: Demonstrates a deep and robust understanding of all concepts in the course and an ability to transfer and use these concepts in a variety of contexts. Simple and complex problems are solved with the correct concepts/ calculations/ assumptions with only minor errors. Able to identify essentially all magnitude and sign errors in erroneous calculations (i.e. unrealistic solutions).

Additional course grading information

The assessment is split into two parts: problem setsᅠ and examination assessment.

There are % requirements in both problem set ᅠand examination ᅠassessment for each grade band. ᅠ

The examination ᅠassessment % is calculated based on the weighted average of all examination ᅠassessment.

Supplementary assessment

Supplementary assessment is available for this course.

Additional assessment information

Marks for a piece of assessment can only be changed within 4 weeks of assessment being returned to students (as opposed to when you check your assessment). Marks will not be changed after 4 weeks has elapsed. It is your responsibility to check that your mark on Grade Centre in Blackboard is correct.


Learning resources

You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.

Library resources

Find the required and recommended resources for this course on the UQ Library website.

Additional learning resources information

Course Blackboard site: https://learn.uq.edu.au. The Blackboard site will contain a variety of information related to the course including lecture and assessment material. Information will be sent to students through Blackboard.

Learning activities

The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.

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Learning period Activity type Topic
Multiple weeks
Lecture

Online lectures and readings

Students are required to review the week's material before and complete the related online quizzes before the Workshop.

Workshop

Workshop (WKS)

Active learning workshop targeting key concepts and skills for the week. This will help address common misconceptions and give you a head start for the Problem Sets that week. A combination of concept and clicker questions will be used.

Problem-based learning

Problem Based Learning (PBL)

Class where students work on problem sets. This is a classroom learning environment where students get to ask questions related to how they are going. It is highly recommended that problem sets are started BEFORE the PBL. You will get a lot more out of the PBL if you do this and you will finish problem sets faster.

Information technology session

ICT - Python skills

This will cover the functions and capabilities of Python that you will be required to use to solve some problems in this course.

Learning outcomes: L05

Practical

Practical

Practical based on key concepts of the course

Learning outcomes: L02, L03, L04

Policies and procedures

University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:

Learn more about UQ policies on my.UQ and the Policy and Procedure Library.

School guidelines

Your school has additional guidelines you'll need to follow for this course:

  • Safety Induction for Practicals

Course guidelines

Safety Induction for Practicals

Anyone undertaking courses with a practical component must complete the UQ Undergraduate Student Laboratory Safety Induction and pass the associated assessment.

Specific instructions, usage guidelines and rules for each of the undergraduate laboratories will be delivered as part of each course.

In some cases, students may be required to attend a specific face-to-face laboratory induction/training session.