Outline

Overview

As the power of computers increases, so does their capacity to provide new tools for scientific analysis. Where once computational chemistry was the domain of specialists, computational methods are now commonly used across all areas of chemistry, both in chemical research and in the application of chemical knowledge in industry and society. For example, techniques of computational chemistry are today used for drug discovery, materials prediction, and the modelling of complex environmental systems. The object of this unit is to introduce students to the goals, methods and critical assessment of computer modelling in chemistry. The unit will address the four goals of modelling: explanation, prediction, interpretation and discovery. In exploring how computational methods meet these goals, you will cover topics in biomolecular modelling, molecular electronic structure, chemical kinetics, and experimental data interpretation. You will learn how to design and carry out computations for a range of chemical problems and engage in hands-on calculations. No prior knowledge of computers or programming is required. By doing this unit, you will develop an understanding of the variety of ways computers can be used and how to use sound criteria for judging the quality of computational results and the reliability of conclusions based on those results.Advanced students attend in addition an advanced seminar series to gain more in-depth disciplinary knowledge where they actively engage with a diverse range of contemporary chemical research problems and case studies. They gain additional opportunities to develop skills in collaborative work and enhance their written and oral communication skills.

Unit details and rules

Academic unit	Chemistry Academic Operations
Credit points	6
Prerequisites ?	A mark of 65 or greater in [(CHEM2401 or CHEM2911 or CHEM2915) and (CHEM2402 or CHEM2524 or CHEM2912 or CHEM2916 or CHEM2924)] or a mark of 65 or greater in (CHEM2521 or CHEM2921 or CHEM2991)
Corequisites ?	None
Prohibitions ?	CHEM3117 or CHEM3123 or CHEM3917
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Brendan Kennedy, brendan.kennedy@sydney.edu.au
Laboratory supervisor(s)	Asaph Widmer-Cooper, asaph.widmer-cooper@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Record+)	Final exam Canvas online examination - This assessment item is compulsory	38%	Formal exam period	2 hours
Outcomes assessed:
Small continuous assessment	Lab report/presentation multiple individual lab reports and group presentation (each less than 10%)	33%	Multiple weeks	Variable
Outcomes assessed:
Assignment	Advanced assignments Presentation and written reports. See canvas for details.	7%	Multiple weeks	Variable
Outcomes assessed:
Assignment	Written assignment Written assignment. See canvas for details.	12%	Week 06 Due date: 11 Sep 2022 at 23:59	Variable
Outcomes assessed:
Small test	In-semester test Canvas online test	10%	Week 08	25 minutes
Outcomes assessed:
= hurdle task ? = group assignment ? = Type B final exam ?

Assessment summary

Theory: The theory component represents 67% of the unit mark. The theory component of the course must be passed for the unit for the unit to be passed. This component comprises of an in-semester test, a written assignment, advanced assignments and a final examination. The final examination covers the whole of the lecture course and is made up of short answer questions. Questions from past exam papers will be available on the Canvas site for this unit.
Laboratory: The laboratory course represents 33% of the unit mark. It is assessed through lab reports and presentation. The laboratory course must be passed for the unit to be passed.
Final exam: If a second replacement exam is required, this exam may be delivered via an alternative assessment method, such as a viva voce (oral exam). The alternative assessment will meet the same learning outcomes as the original exam. The format of the alternative assessment will be determined by the unit coordinator.
Compulsory Assessment: Failure to submit or attend compulsory assessment tasks or to attend classes to the required level will result in an Absent Fail (AF) for the unit.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	At HD level, a student demonstrates a flair for the subject as well as a detailed and comprehensive understanding of the unit material. A ‘High Distinction’ reflects exceptional achievement and is awarded to a student who demonstrates the ability to apply their subject knowledge and understanding to produce original solutions for novel or highly complex problems and/or comprehensive critical discussions of theoretical concepts.
Distinction	75 - 84	At DI level, a student demonstrates an aptitude for the subject and a well-developed understanding of the unit material. A ‘Distinction’ reflects excellent achievement and is awarded to a student who demonstrates an ability to apply their subject knowledge and understanding of the subject to produce good solutions for challenging problems and/or a reasonably well-developed critical analysis of theoretical concepts.
Credit	65 - 74	At CR level, a student demonstrates a good command and knowledge of the unit material. A ‘Credit’ reflects solid achievement and is awarded to a student who has a broad general understanding of the unit material and can solve routine problems and/or identify and superficially discuss theoretical concepts.
Pass	50 - 64	At PS level, a student demonstrates proficiency in the unit material. A ‘Pass’ reflects satisfactory achievement and is awarded to a student who has threshold knowledge.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date: Deduction of 5% of the maximum mark for each calendar day after the due date. After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Multiple weeks	Goals and methods of computational science, including explanation, prediction, interpretation and discovery. Introduction to programming.	Lecture (4 hr)
	Time-dependent simulation of chemical kinetics models	Lecture (4 hr)
	Introduction to molecular computational chemistry, relationship between molecular mechanics and electronic structure, molecular mechanics models, and methods for integrating the equations of motions.	Lecture (4 hr)
	Geometry optimisation, solvent and continuum models, and biomolecular applications, docking, etc.	Lecture (4 hr)
	Electronic structure of atoms, LCAO-MO, many-electron states, Hartree-Fock and mean-field theory, wavefunction methods beyond Hartree-Fock, density functional theory and applications of electronic structure	Lecture (8 hr)
	13 x 4 hr laboratory classes	Science laboratory (52 hr)
Week 09	Overview of place of electronic structure within computational chemistry, properties computable by electronic structure techniques	Lecture (2 hr)
Weekly	12 x advance seminars	Seminar (12 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

See canvas for details

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. Explain how to design and carry out computations for a range of chemical problems .
LO2. Apply a range of computational methods and techniques for hands-on calculations
LO3. Interpret computational results and critically assess their quality and realiability in context to methods used and approximations made while carrying out the calculations.
LO4. Design computational methods to solve chemical problems in topics of biomolecular modelling, molecular electronic structure, chemical kinetics, and experimental data interpretation
LO5. Carry out experimental work safely and competently in a chemical laboratory
LO6. Develop skills to work collaboratively in responsible data collection, analysis and communication and advance chemical enquiry.
LO7. Evaluate and interpret scientific information and experimental data and judge their reliability and significance.
LO8. Communicate scientific information and laboratory findings appropriately both orally and through written work and engage in discussions on contemporary topics in chemistry.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered.

Additional information

Work, health and safety

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.

General Laboratory Safety Rules

No eating or drinking is allowed in any laboratory under any circumstances
A laboratory coat and closed-toe shoes are mandatory
Follow safety instructions in your manual and posted in laboratories
In case of fire, follow instructions posted outside the laboratory door
First aid kits, eye wash and fire extinguishers are located in or immediately outside each laboratory
As a precautionary measure, it is recommended that you have a current tetanus immunisation. This can be obtained from University Health Service: unihealth.usyd.edu.au/

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

CHEM3923: Computational Chemistry (Advanced)

Semester 2, 2022 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect