Increasing demand on workforce for nanotechnology implementation has resulted in an exponential increase of demand on educational material and methods to qualify this workforce. However, nanotechnology is a field that integrates many areas of science and engineering requiring a significant amount of background knowledge in both theory and application to build upon. This challenge is significantly magnified when trying to teach nanotechnology concepts and applications at the undergraduate engineering level. A considerable amount of time is needed for an undergraduate engineering student to be able to design and build a useful device applying nanotechnology concepts, within one course time.
This paper presents an actual experience in teaching hands-on applications in nanotechnology to undergraduate engineering students through an optimized model, within a normal course time. The model significantly reduces the time needed by undergraduate students to learn the necessary manufacturing techniques and apply them to produce useful products at the micro and nano levels, by ensuring that infrastructure and legwork related to the educational process are partially completed and verified, before the course starts. The model also provides improved outcomes as all its pre-course work is also tested with students working under different arrangements of professors’ supervision. The result is an optimized infrastructure setup for micro and nanotechnology design and manufacturing education, built with students in mind, to be completed within the frame of one semester course.
The model was implemented at GVSU-SOE as the core hands-on part of a senior undergraduate course titled (EGR 457 nano/micro systems engineering). Students in the course were able to go through the design and build steps of different MEMS and NEMS products, while learning and utilizing cleanroom equipment and procedures. This was based on infrastructural arrangements by students preceding this class by a semester and working closely with the professors. Assessment was conducted on both sides of the model and results were collected for evaluation and improvement of the model.