Courses

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ME 423 Intro to Dynamics of Microsystems

The course aims to introduce the students to the principles of MEMS and Microsystem dynamics and their modeling techniques. The course is multi-disciplinary in nature and will tackle several multi-physics problems, which include vibrations, dynamics, fluid mechanics, heat, electronics and electricity, etc. It will emphasize analytical and some numerical modeling techniques. The topics will include topics such as Sensing and Actuation in MEMS (electrostatic, electrothermal, piezoelectric, electromagnetic, etc.), Elements of Lumped-Parameter Modeling in MEMS (stiffness, damping, inertia), case studies of accelerometers, gyroscopes, filters, switches, mirrors, and basic principles of stability and nonlinear analysis of microsystems. (Technical elective.)

Prerequisite: ME 421.

Offered in the fall semester. 3 credits

ME 473 Micro/Nanomaterials Processing      

"This course will explore how micro and nano-scale materials and devices are produced. Covered topics include the 1) fundamentals of micro and nano-materials processing in material science and transport phenomena, 2) micro and nano-fabrication processes for Micro-Electro-Mechanical Systems (MEMS) and Nano-Electro-Mechanical Systems (NEMS), 3) existing and emerging manufacturing processes for industrial scale production of micro- and nano-scale materials, and 4) Metrology and characterization tools for conducting research in micro and nano-materials processing.

Prerequisites: ME 302 or approval of instructor.

Term varies. 3 credits

ME  531 Applied Machine Learning fr ME

"This course covers machine learning fundamentals, some popular and advanced machine learning models. Major topics include supervised learning (logistics regression, support vector machine, artificial neural networks, Gaussian process), unsupervised learning (clustering, dimensionality reduction), convolutional neural networks, generative adversarial networks, physics-constrained/informed neural networks, and optimization algorithms (stochastic gradient descent, Bayesian optimization). This course also covers the applications of machine learning models in mechanical engineering. Students should be familiar with Python basic commands and programming.

Prerequisites: ME 303 or equivalent.  

Offered in the fall semester. 3 credits

ME 573X Micro/Nanomaterials Processing

This course will explore how micro and nano-scale materials and devices are produced. Covered topics include the 1) fundamentals of micro and nano-materials processing in material science and transport phenomena, 2) micro and nano-fabrication processes for Micro-Electro-Mechanical Systems (MEMS) and Nano-Electro-Mechanical Systems (NEMS), 3) existing and emerging manufacturing processes for industrial scale production of micro- and nano-scale materials, and 4) Metrology and characterization tools for conducting research in micro and nano-materials processing. This course is cross-listed as a graduate-level course. Completion of additional assignments is required for graduate credits.

Prerequisites: ME 302 or approval of instructor.

Term varies. 3 credits