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MSE593 : Special Topics in MSE

MSE/Macro 593, Special Topics

Instructor: Katsuyo Thornton
Instructor: Wenhao Sun
Instructor: Brian Love

Course Outcomes:

There are two different offerings of this course.


Engagement in the Research Process 


Preamble:  The class is organized to aid in the development of independent writing examples as features of a portfolio.  Countless examples exist where students are required to produce comprehensive documents relating to literature reviews for dissertations, project reports for academic progress, and independent research ideas worthy of further exploration.  You are also likely expected to write papers as part of your graduate experience and into later phases of your career.  The goal is to help organize thought processes such that one can write more efficiently and with more of a purpose. We will not write your dissertation for you as part of this class. 


To accomplish this, students need to be equipped with goals and targets for writing.  Examples include elements of literature reviews for one’s dissertation, the candidacy background document, Federal graduate fellowship application personal statements, exploratory write-ups for SBIR type grants, and directed and independent explorations fur future research ideas.  Please note that you should not be thinking that this class will be a complete critique for your literature review for your candidacy exam.  Rather, the class could help you frame how to accomplish the review, and pieces of your lit review might be appropriate.  The individual writing assignments here will be shorter than what might be expected for a complete lit review. 


Background and pre-requisites:  Graduate or near graduate standing in engineering or a relevant science oriented discipline. 


Time and Location:  1:30-3PM MW  3150 HH Dow


Data-Driven Materials Design and Genomics


The Materials Genome Initiative (MGI) is an ongoing U.S. initiative to discover, manufacture, and deploy advanced materials twice as fast, at a fraction of the cost. Many MGI efforts are enabled by large-scale materials informatics—employing methods such as high-throughput computing, data-driven materials optimization, and knowledge discovery in materials databases. In this course, students will learn how to use Python to access big-data from existing materials databases, and how to design and execute a data-driven research project in MSE. State-of-the-art methods in statistical analysis, supervised and unsupervised machine-learning, and data visualization will be covered, with computational labs to teach proficiency in these techniques. We will review examples of MGI efforts in the design of lithium ion batteries and structural alloys. A capstone project will provide an opportunity for students to design and propose new MGI initiatives.

Tuesday, Thursday
DOW 3150 
8:30-10 AM


Prof. Wenhao Sun, Materials Science and Engineering,
Prof. Katsuyo Thornton, Materials Science and Engineering,