NANS1004 Computational Nanosciences (2–4 cr)

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Study level:
Advanced studies
Grading scale:
0-5
Language:
English
Responsible organisation:
Department of Biological and Environmental Science, Department of Physics, Faculty of Mathematics and Science, Department of Chemistry
Curriculum periods:
2024-2025, 2025-2026, 2026-2027, 2027-2028

Description

  • Viewpoints to computational research (material systems, methods, analysis, processes, computational infrastructure, practical aspects)

  • Overview of various computational methods (many-body methods, density-functional theory, tight-binding model, classical force fields, discretized continuum)

  • Suitability of different methods to investigate nanomaterial properties

  • Computational research at NanoScience Center of Jyväskylä

Extended version includes in addition
  • Solving a computational nanoscience problem in practice
  • Using one computational nanoscience method and a related software in a suitable computational environment
  • Visualizing and summarizing results
  • Preparing and presenting a report

Learning outcomes

At the end of this course, students are able to

  • relate computational research to purely experimental and theoretical research,

  • name the most common computational methods of nanoscience research,

  • describe the basic principles behind the methods,

  • differentiate and classify different methods of computational nanoscience with respect to their central approximations, quantum-mechanical characters, computational efficiencies and use,

  • give a presentation about one topic related to computational nanoscience,

  • justifiably choose the most appropriate computational methods once given the material system and the properties under investigation,

  • in future independently deepen their methodological knowledge on computational nanoscience.

In the extended version, students are in addition to previous able to
  • solve a computational nanoscience problem in practice,
  • use one computational method with a related software in a suitable computational environment/infrastructure,
  • make a report about the results and explain the results.

Study materials

Material produced by other students and material given at the lectures. 

Completion methods

Method 1

Description:
Completion method 1 includes only the lecture part of the course. Mandatory part.
Evaluation criteria:
Activity on lectures, researcher interview and presentation, criteria based self-assessment (possibly other smaller written tasks).
Time of teaching:
Period 4
Select all marked parts

Method 2

Description:
This completion method includes both lecture part and a computational project.
Evaluation criteria:
Lecture part: activity on lectures, researcher interview and presentation, criteria based self-assessment (possibly other smaller written tasks). Computational project: report, presenting results and discussion.
Time of teaching:
Period 4
Select all marked parts
Parts of the completion methods
x
x

Lecture part (2 cr)

Type:
Participation in teaching
Grading scale:
0-5
Evaluation criteria:
<p>Attendance and activity on the lectures, presentation and its material, self-assessment</p>
Language:
English
Study methods:

Active participation to the lectures, interview of a specialist, preparing and giving a presentation, writing a self-assessment, other tasks during lectures

Teaching

x

Independent computational project (2 cr)

Type:
Independent study
Grading scale:
0-5
Evaluation criteria:
<p>Report and presenting the results, discussion<br></p>
Language:
English
Study methods:

Participation to the guided sessions, independent working with the given computational project, preparing a report about results and presenting them

Teaching