Unit information: Complex Disordered Matter in 2026/27

Please note: Programme and unit information may change as the relevant academic field develops. We may also make changes to the structure of programmes and assessments to improve the student experience.

Unit name Complex Disordered Matter
Unit code PHYSM0071
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Professor. Wilding
Open unit status Not open
Units you must take before you take this one (pre-requisite units)

PHYS10012 Core Physics I: Classical, Quantum and Thermal Physics

PHYS20040 From Classical to Modern Physics

PHYS20035 Computational Physics and Data Science OR SCIF20002 Programming and Data Analysis for Scientists.

For students on Chemical Physics, Physics and Philosophy or Mathematics and Physics programmes, completion of PHYS20037 Laboratory Skills and Computing or CHEM20006 Intermediate Practical Chemical Physics will be suitable replacements for the computational physics component.

Units you must take alongside this one (co-requisite units)

-

Units you may not take alongside this one

-

School/department School of Physics
Faculty Faculty of Science

Unit Information

Why is this unit important?

Complex materials, including ferromagnets, glasses, polymers, liquid crystals, and biological membranes, as well as disordered systems like amorphous solids and animal swarms, display behaviours that challenge traditional physics models, revealing new states of matter and exotic phases. Understanding these materials paves the way for technological breakthroughs, such as the development of advanced materials with distinctive mechanical, optical, and electronic properties, and sparks innovations across fields from energy storage to quantum computing. Studying complex and disordered matter is essential for grasping the vast array of real-world phenomena that cannot be captured by idealized, orderly systems. This exploration often demands the creation of novel theoretical frameworks and computational techniques rooted in statistical physics and phenomenological approaches. It not only deepens our fundamental understanding but also delivers practical insights with applications in diverse industries, including materials science, medicine, and nanotechnology.

How does this unit fit into your programme of study?

This unit forms part of the fourth year options portfolio for physics students; a suite of options led by research in the School. Your choice of options will help to shape the physicist you will become.

Your learning on this unit

An overview of content

This course will introduce the physics of exemplars of complex and disordered tter using both traditional modelling based on ideas from statistical and thermal physics, plus a hands-on computational physics approach. Python based exercises (including group work with short presentations) will cover phenomena such as random walks (relevant for diffusion and polymers), self-organisation and phase behaviour, and pattern formation in active matter.

Topics covered will include (inter alia)

  • Theoretical and computational principles
  • Experimental techniques for disordered systems
  • Stability and metastability
  • Broken symmetries and phase behaviour
  • Introduction to criticality and scaling
  • Pattern formation and self-assembly
  • Frustrated systems
  • Active matter

How will students, personally, be different as a result of the unit

By the end of this unit, you will emerge with a strong working knowledge of the physics of many complex and disordered systems of interdisciplinary scientific and industrial interest and a deepened skillset for computational problem solving.

Learning outcomes

By the end of this unit, you should be able to:

  • Demonstrate a broad understanding of the essential qualitative features of a range of complex and disordered systems and the experimental techniques used to study them.
  • Create and solve computational models for disordered systems to predict physical phenomena
  • Demonstrate specialist applied knowledge in the field of computational physics
  • Apply your physics knowledge across topic boundaries and in unrehearsed contexts
  • Demonstrate your ability to formulate and tackle problems in physics
  • Relate your learning to current research in the discipline

How you will learn

The unit is organised through our on-line learning environment (OLE). This is where you will find information about the unit, lecture notes, any pre-recorded videos, recordings of lectures and live sessions, access to online quizzes (where appropriate) and other learning resources.

All teaching activities will be delivered face-to-face (barring intervention from exceptional events), and it is an expectation that you engage with these activities. Learning activities will be split across in-class activities (lectures, problems classes) and those around your own private study (for example online quizzes, videos, textbook references etc.).

The unit will consist of around 30 hours of content delivery with 10 hours of problems support. Along with this time there is an expectation of personal study in line with the University statement on student workloads.

Some sessions may require preparation beforehand (e.g. watching a video, reading a textbook chapter or journal article or similar); where these materials are provided, you should aim to spend around one hour of preparation time for one hour of face-to-face teaching. This will allow you to make the most of class discussions and activities.

How you will be assessed

Tasks which help you learn and prepare you for summative tasks (formative):

There will be regular problems classes, allowing you to ask questions of the facilitator to help you quantify your own understanding and that of others, and to gain verbal feedback on your problem-solving skills.

Tasks which count towards your unit mark (summative):

  • Coursework exercise 1: A problem set solving problems and relating solutions to the physics of disordered matter (20%, ILOs 1, 3, 5)
  • Coursework exercise 2: A computational task to simulate and evaluate systems introduced in the context of the course content (30%, ILOs 2, 3, 5, 6)
  • Examination (50%, all ILOs).

When assessment does not go to plan

If you do not pass the unit, you may have the opportunity to retake any failed components in the next available assessment period *

  • subject to passing a minimum overall number of credits for the year.

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. PHYSM0071).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the University Workload statement relating to this unit for more information.

Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.

The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates within the Regulations and Code of Practice for Taught Programmes.