Introduction
Would you like to discover the inner soul of the materials and processes through exciting measurement techniques?
Course information
2.5 credits
Start Date: 2020-11-09 - 2020-12-06 (part-time 33%)
Education ordinance: Second cycle
Course code: ERA313
Main area: Energy Engineering
About this course
In this course, you will learn how the spectroscopy techniques can be used to analyse the chemical and structural properties of various materials by interactions with electromagnetic radiation. We will introduce the electromagnetic spectrum and discuss underlying theories behind matter transitions affecting radiation in various spectral ranges and thus enabling the spectroscopic analysis.
You will learn how various spectrometers work and to correctly perform material sampling, preparation, and spectral data acquisition. You will understand how to interpret complex information obtained by various spectroscopic techniques and how to extract information with the help of chemometrics that includes machine learning and artificial intelligence techniques.
The important part of the course will be focused on addressing real industrial and environmental challenges by employing state-of-the-art spectroscopic material characterization methods for process monitoring, control, and optimization.
The course is given over four weeks at a pace of 33%, corresponding to approximately 12 hours of studies per week. The course will be given on 9th November and ends on 6th December 2020.
What you will learn
You will be familiar with the essential principles of near-infrared (NIR), infrared (IR) and Raman spectroscopy.
How to characterize selected biomass and waste materials by using the near-infrared (NIR) spectroscopy, including hyperspectral imaging (HSI), and infrared (IR) and Raman spectroscopy techniques.
How to analyze and interpret data obtained by a given spectroscopy technique or combination of techniques.
How to apply the obtained information in the process and environmental monitoring, control, and optimization.
Entry requirements
120 credits of which 90 credits engineering or natural science and 7,5 credits mathematics.
In addition English course A/English course 6 is required.
You can also apply for the course and get your eligibility evaluated based on knowledge acquired in other ways, such as work experience, other studies, etc.
Course title in Swedish
Tillämpad spektroskopi för framtida energi- och miljösystem
Application information
After submitting your electronic application, the next step is to submit documentation to demonstrate your eligibility for the course you have applied for. In order to document your eligibility, you must provide your high school diploma and university transcript and proof of your English language proficiency.
Entry requirements
To meet the entry requirements for this course you need to have previous academic qualifications (university studies). You will find the specific entry requirements above.
No academic qualifications?
If you do not have the formal academic qualifications needed for a specific course, you can apply for the course and get your eligibility evaluated based on knowledge acquired in other ways, such as work experience, other studies etc. This is also known as a validation of prior learning.
Recognition of prior learning means the mapping out and the assessment of an individual's competence and qualifications, regardless of how, where, or when they were acquired – in the formal education system or in some other way in Sweden or abroad, just recently or a long time ago.
If you think your knowledge and competences will qualify you for this course, you will need to upload the following with your application:
CV with a description of your educational and professional background. Your CV must describe your knowledge and competences in relation to the entry requirements.
If you refer to work experience, you need to upload an employer certificate.
If we need more information, we will contact you.
FutureE
The courses are part of the FutureE project where MDH offers online courses in the areas of AI, Environmental and Energy Engineering, Software and Computer Systems Engineering.
