NANOFABRICATION AND CHARACTERISATION - 2023/4

Module code: EEEM050

Module Overview

Expected prior learning: Students should have an interest in practical aspects of experimental methods in nanotechnology applications.

Module purpose:

This module provides students with an introduction to some of the most widely used experimental techniques and skills in engineering applications that leverage phenomena on the nanoscale, from characterising new solar cells to measuring the morphology and properties of thin layers down to single-sheet 2D materials. The module introduces students to key transferrable research skills, building confidence and competence in how to use statistical analytical tools to design experiments and significantly reduce the number of redundant experiments in quality assurance of manufacturing processes, improving their resilience and sustainability. EEEM050 complements fundamental aspects of nanoengineering taught in parallel in EEE3037 and provides essential learning for experimental project dissertations in EEEM004.

Module provider

Computer Science and Electronic Eng

Module Leader

STOLOJAN Vlad (CS & EE)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Overall student workload

Independent Learning Hours: 110

Lecture Hours: 17

Seminar Hours: 3

Tutorial Hours: 10

Guided Learning: 8

Captured Content: 2

Module Availability

Semester 1

Prerequisites / Co-requisites

None.

Module content

Indicative content includes the following:

1. Data and image processing and analysis


  • Experimental and statistical errors.

  • Image and data processing and analysis.

  • Automated particle analysis.

  • Paper/article search skills and referencing software.




2. Design of Experiments


  • Principles of experimental design.

  • Factorial design.

  • Taguchi method.

  • ANOVA (analysis of variance).




3. Optical Microscopy and Spectroscopy


  • Optical and 3D optical microscopies.

  • UV-Vis-NIR, FTIR and luminescence spectroscopies.

  • Raman spectroscopy.




4. Nanostructure growth and deposition 


  • Chemical Vapour Deposition growth of nanostructures.

  • Solution processing of nanostructures.

  • Models for the growth of nanostructures.




5. Surface characterisation and electrical properties 


  • Atomic Force Microscopy and related surface analysis techniques.

  • X-ray photoelectron spectroscopy.

  • Electrical measurements at the nanoscale.




6. Surface characterisation with Ion Beams 


  • Introduction to ion implantation in electronics.

  • Ion Beam analysis.

  • Thin film characterisation.




7. Micro and Nano -Electromechanical Systems: Principles and Fabrication


  • Fundamentals of MEMS and NEMS design and processing, use in sensors, microsystems technology and applications.

  • Applications and technology generated based on scaling and implementation of NEMS/MEMS.

  • Key drivers associated with developing new technologies and the development of next generation NEMS devices.



 

 

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Coursework 20
Examination Online 4HR Online (open book) EXAM 80

Alternative Assessment

N/A

Assessment Strategy

The assessment strategy for this module is designed to provide students with the opportunity to demonstrate the following:

· The practical analysis of data, including specifically error estimation and derivation.

· Application of design of experiments concepts to planning research strategies.

· The understanding of the wider scope of a specific piece of research, through literature review

· The graphical representation of results and analysis, including the understanding the role of figure captions.

· The ability to understand the fundamental theory behind major experimental techniques used in nanotechnology and fabrication and apply it to case studies and examples.

· A general understanding of the achievements and challenges facing the next generation of nanoscale devices.

 

Thus, the summative assessment for this module consists of the following:

EXAM 80% and Coursework 20%

Any deadline given here is indicative. For confirmation of exact dates and times, please check the Departmental assessment calendar issued to you.

 

Formative assessment and feedback

For the module, students will receive formative assessment/feedback in the following ways.

· During lectures, by question and answer sessions

· During tutorials/tutorial classes

· By means of unassessed tutorial problem sheets (with answers/model solutions)

 

Module aims

  • Introduce students to common analytical experimental techniques used in nanoelectronics and nanotechnology, such as: 1) optical microscopy (eg. confocal) and spectroscopies (eg. Raman); 2) scanning probe microscopy (Atomic Force Microscopy and its variants); 3) ion, X-ray and electron beam spectroscopies (eg. Rutherford Backscattering, Energy-dispersive X-ray); 4) electrical measurements on the nanoscale.
  • Provide practical experience in analysing data and measurement errors. Provide practical experience in Design of Experiments approaches.
  • Provide some of the soft skills used in communicating research results, such as literature searching, use of referencing database, producing journal-quality figures and presenting results.
  • Introduction to electronics and electro-mechanical fabrication techniques (lithography, printing).
  • Introduction to nanomaterials fabrication techniques (eg. growth of graphene, nanotubes and nanowires, deposition of thin films)
  • The module also aims to provide opportunities for students to learn about the Surrey Pillars listed below.

Learning outcomes

Attributes Developed
Ref
001 To apply the fundamental theory of basic experimental characterisation to examples and case studies in nanoelectronics and nanotechnology KC M1, M2
002 To critically analyse experimental data and present to an audience, in publication-quality format CPT M4, M16, M17
003 To critically analyse and interpret information gained from scientific journals CPT M4

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to achieve the following aims.

The course covers some of the fundamentals behind nanotechnology and moves on to discuss their practical implementation in nanoscience and quantum engineering, nanomaterials and nanotechnology, before discussing future trends and applications. Coupled with this, the course teaches some of the basics of scientific communication, from literature review to the design and planning of publication-quality images and figures, to the presentation of data. It also strengthens the some of the basic mathematical skills necessary for data analysis and introduces design of experiment approaches.

 

Learning and teaching methods include the following.

• Online taught material and class discussions

• Tutorials and formative feedback sessions

• Dedicated revision sessions

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: EEEM050

Other information

The module provides the students the opportunity to demonstrate their mastery of advanced calculations, which will aid their employability and digital competence.

Critical thinking and exercising engineering judgment will be developed via carefully chosen practical examples, working with missing data and critically assessing published peer-reviewed articles (R&R)

The student’s digital capabilities will be enhanced via the student’s use of advanced experimental software to extract and interpret results from experimental data.

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2023/4 academic year.