Nano-Device for Energy Harvesting and Sensing
Offered By: Purdue University via edX
Course Description
Overview
This course will introduce students to the field of nanotechnology with a special emphasis on nanomaterials synthesis, characterizations and their applications in civil and environmental engineering. The specific applications will include, but not limited to, tailoring mechanical property, durability, self-cleaning, self-sealing, self-sensing, energy harvesting and other multi-functionality. It integrates the fields of materials science, civil engineering and electrical engineering. The basic concepts will be discussed including nano-scale effect, process-structure-property relationship, nano- and micro-structure property characterizations, multi-functional materials, nano-device fabrication and their applications for energy harvesting, water infiltrations and environmental sensing. lab will be provided to students enrolled in the course to learn nano and micro-structure characterizations skills.
Syllabus
Week 1:
- Introduction to Thermoelectric
- Thermoelectric Materials Properties
- Thermoelectric Device Design
- Thermoelectric Device Fabrication
Week 2:
- Conventional Thermoelectric Generator Applications
- Thermoelectric Generators for IoT Applications
- Thermoelectric Sensors for Biomedical Applications
- Thermoelectric Sensors fro Environmental Applications
Week 3:
- Introduction to Piezoelectricity
- Fundamentals of Piezoelectricity
- Piezoelectric Characterization
Week 4:
- Piezoelectric Device
- Piezoelectric Transducer for Civil Engineering Application
- Piezoelectric Nanogenerator
- Piezoelectric Transducer Fabrication
Week 5:
- Introduction to Machine Learning
- Machine Learning with Materials Science
- Machine Learning Guided Materials Discovery
- Data-Driven Energy Discovery
Taught by
Luna Lu, Guangshuai Han, Yining Feng and Raikhan Tokpatayeva
Tags
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent