TR 11:00–12:30 in 206 Transportation
Students will be able to
Dallas R. Trinkle (dtrinkle@illinois.edu; 308 MSEB in the west stairwell).
An “active learning” approach where we focus on the course objectives: applying knowledge to answer scientific questions about materials and data and critically engaging with the scientific literature. You will:
First off: Teams are not easy.
As you will find out, group work is not always easy. Team members sometimes cannot prepare for or attend group sessions because of other responsibilities, and conflicts often result from differing skill levels and work ethics. When teams work and communicate well, however, the benefits more than compensate for the difficulties. Chances of success are greatly improved if there is an agreement beforehand on what everyone on team expects from everyone else: Team expectations.
In addition, the real world, for the most part, requires people to work together and interface skills, etc. Teamwork is a highly valued skill, but like all skills, requires practice.
One primary activity of our class is engaging actively with scientific literature. This is a primary activity for scientists, and is a skill. It requires
The focus will be on current scientific literature in the emerging materials and data area.
From time to time, we will conclude with a minute paper which helps to synthesize your understanding of the lecture, think about your questions, and prime discussion for the next class period. This will be done electronically using the link: forms.illinois.edu/sec/4555495. There, you will have three questions:
Following class, I will compile the questions, organize them, and answer some of them online (on the course website). Your responses also help me to adjust the course as needed.
Breakdown to be determined.
I am committed to assisting students requiring special accommodations for circumstances that are registered with the DRES Student Services Department. These formal accommodations should be discussed with me as early as possible in the semester or as soon after DRES approval as possible.
If you are not formally registered with DRES and have anxiety, depression, learning disabilities, or other issues that affect your ability to fully participate and learn in this class, you are encouraged to check-in with me so we can determine together the kind of support you need to thrive in this class. Please set up a meeting with me via email.
I value all students regardless of their background, race, religion (creed), ethnicity, gender, gender expression, age, country of origin, disability status, marital status, sexual orientation, or military status, etc., and am committed to providing a climate of excellence and inclusiveness within all aspects of the course. If there are aspects of your culture or identity that you would like to share with me as they relate to your success in this class, I am happy to meet to discuss. Likewise, if you have any concerns in this area of facing any special issues or challenges, you are encouraged to discuss the matter with me (set up a meeting via email) with an assurance of full confidentiality (only exception being mandatory reporting of academic integrity / code violation and sexual harassment). Harassment or discrimination of any kind will not be tolerated.
You are bound by the University Honor Code in this course. Any violation of the Honor Code will result in disciplinary action.
Students are responsible for producing their own code, reports, and projects. Collaborative interaction is encouraged, but each student must do their own implementation, perform all calculations themselves, and write their own reports. Plagiarism will not be tolerated, and verified incidents will result in all parties receiving a zero and formal academic sanctions. Students are responsible for familiarizing themselves with the definition of and penalties for plagiarism in Section I-401 of the UIUC Student Code. Note that plagiarism includes “copying another student’s paper or working with another person when both submit similar papers without authorization to satisfy an individual assignment.”
May occur as deemed necessary by the professor; they will be announced and the updated syllabus posted on the course website.
The Univ. Illinois library has access to a huge variety of electronic resources; this plus additional online resources will be our references. Many can be accessed from the library’s website, or via the campus VPN. Alternatively, you can take advantage of the library proxy. This is done by appending proxy2.library.illinois.edu to the web address; when reloaded, you will be asked for Univ. Illinois authentication, and then will be able to access the resource as if you were on campus. In general, this authentication is required only once per session. So, the website
http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.113.025504would become
http://journals.aps.org.proxy2.library.illinois.edu/prl/abstract/10.1103/PhysRevLett.113.025504Alternatively, install the Proxy Bookmarklet which makes it extremely easy to use the proxy. I highly recommend this method.
In addition, we will use Google Drive to share files. You should have an “infinite” amount of free storage on Google Drive, and you can set up Google Drive so that files are automatically synced to your computer. You may want to upload PDFs from the pre-lecture reading there; if you place these PDFs in the shared folder, please name them FirstAuthorLastName-Journal-Year.pdf so that they remain organized. The team slides will be made available using Google Apps.
This means that you will need to either:
Your campus Google account will be separate from an existing Google account, should you have one.
| Tuesday | Thursday | notes |
|---|---|---|
| 1/21 | 1/23 | introduction; Python review |
| 1/28 | 1/30 | Querying data and Linear regression |
| 2/4 | 2/6 | Querying data (edits) and Linear regression (edits) / Materials selection |
| 2/11 | 2/13 | Density functional theory and high-throughput computation Materials Project |
| 2/18 | 2/20 | Materials selection with Materials Project: Topic 1, pdf and Band Alignment |
| 2/25 | 2/27 | Generalized Linear Models and Hierarchical Bayesian Modeling |
| 3/3 | 3/5 | Linear modeling: Topic 2 |
| 3/10 | 3/12 | |
| no class (spring break) | ||
| 3/24 | 3/26 | Uncertainty Quantification in Multiscale Modeling (chapter 4 on transport modeling) ; slides |
| 3/31 | 4/2 | Uncertainty quantification: Topic 3 |
| 4/7 | 4/9 | nanoMFG |
| 4/14 | 4/16 | nanoMFG |
| 4/21 | 4/23 | 4CEED |
| 4/28 | 4/30 | 4CEED |
| 5/5 | ||
| 5/12 | 5/14 | finals week |