Tue Dec 8 12:42:16 2015
Approvals Received: 



Approvals Pending:  College/Dean > Provost > Catalog > PeopleSoft Manual Entry  
Effective Status:  Active  
Effective Term:  1173  Spring 2017  
Course:  MATS 3141  
Institution: Campus: 
UMNTC  Twin Cities/Rochester UMNTC  Twin Cities 

Career:  UGRD  
College:  TIOT  College of Science and Engineering  
Department:  11093  Chemical Eng & Mat Sci  
General  
Course Title Short:  Numerical Methods for MatS  
Course Title Long:  Numerical Methods for Material Science  
MaxMin Credits for Course: 
3.0 to 3.0 credit(s)  
Catalog Description: 
Mathematics and numerical/computation methods for Materials Science. Example problems include: Diffusion problems; coupled diffusion/kinetics problems; nucleation, growth and crystallization; quantum mechanics/electrostatic problems relevant to electronic/magnetic/optical devices. The use of MatLab will be emphasized. Prereq: concurrent registration in MATS 3002 recommended, Math 2374, Math 2373, (Chem 4502 or Phys 2303), MatS upper div 

Print in Catalog?:  Yes  
CCE Catalog Description: 
<no text provided>  
Grading Basis:  AF only  
Topics Course:  No  
Honors Course:  No  
Online Course:  No  
Instructor Contact Hours: 
4.0 hours per week  
Course Typically Offered:  Every Spring  
Component 1 : 
LEC (with final exam)  
Component 2 : 
DIS (no final exam) 

AutoEnroll Course: 
Yes  
Graded Component: 
DIS  
Academic Progress Units: 
Not allowed to bypass limits. 3.0 credit(s) 

Financial Aid Progress Units: 
Not allowed to bypass limits. 3.0 credit(s) 

Repetition of Course: 
Repetition not allowed.  
Course Prerequisites for Catalog: 
<no text provided>  
Course Equivalency: 
No course equivalencies  
Add Consent Requirement: 
No required consent  
Drop Consent Requirement: 
No required consent  
Enforced Prerequisites: (coursebased or noncoursebased) 
[Math 2374 or Math 2263 or Math 2573H], [Math 2373 or Math 2243 or Math 2574H], (Chem 4502 or [Phys 2303 or 2503H]), MatS upper div  
Editor Comments:  This is a new course for the MatS major, designed to provide, for the first time, a numerical methods/computational materials science class that is specifically tailored towards materials science. Should this be approved, MatS majors will no longer take CEGE3101 to fulfill a “computer applications” requirement. MATS3141 will be taken instead. LLE 12115.  
Proposal Changes:  <no text provided>  
History Information:  <no text provided>  
Faculty Sponsor Name: 
Chris Leighton  
Faculty Sponsor Email Address: 
leighton@umn.edu  
Student Learning Outcomes  
Student Learning Outcomes: 
* Student in the course:
 Can identify, define, and solve problems
Please explain briefly how this outcome will be addressed in the course. Give brief examples of class work related to the outcome. The whole purpose of this class is to teach MatS students how to solve problems that are not otherwise possible with standard analytical approaches. Such problems are encountered frequently in materials science, particularly in classes in our existing curriculum, such as MATS3012, 3013, 3002, etc. The objective of this class is to teach students the numerical methods needed to implement solutions to these problems using computer applications such as Matlab. The problems will include: oxidation and corrosion problems, nucleation and growth problems, solutions to Schroedingers equation relevant to electronic devices, and electrostatic problems relevant to electronic/optoelectronic devices. More specific examples that will be heavily emphasized include dendritic growth, crystallization more generally, numerical solutions to 1, 2 and 3D wave mechanics problems relevant to electronic devices, etc. How will you assess the students' learning related to this outcome? Give brief examples of how class work related to the outcome will be evaluated. Assessment in this class will be via two midterm exams, a final exam, and weekly assignments. The assignments will be typically based around setting up and solving graphical and numerical problems, and will thus be based directly on the outcomes discussed above. Midterms and finals will test the understanding of the mathematical and numerical methods sections of the class discussed in the syllabus. Conceptual questions on how numerical solutions are implemented will also be given, including analysis and interpretation of results.  
Liberal Education  
Requirement this course fulfills: 
None  
Other requirement this course fulfills: 
None  
Criteria for Core Courses: 
Describe how the course meets the specific bullet points for the proposed core
requirement. Give concrete and detailed examples for the course syllabus, detailed
outline, laboratory material, student projects, or other instructional materials or method.
Core courses must meet the following requirements:
<no text provided> 

Criteria for Theme Courses: 
Describe how the course meets the specific bullet points for the proposed theme
requirement. Give concrete and detailed examples for the course syllabus, detailed outline,
laboratory material, student projects, or other instructional materials or methods. Theme courses have the common goal of cultivating in students a number of habits of mind:
<no text provided> 

LE RecertificationReflection Statement: (for LE courses being recertified only) 
<no text provided>  
Statement of Certification: 
This course is certified for a Core,
effective
as of
This course is certified for a Theme, effective as of 

Writing Intensive  
Propose this course as Writing Intensive curriculum: 
No  
Question 1 (see CWB Requirement 1): 
How do writing assignments and writing instruction further the learning objectives
of this course and how is writing integrated into the course? Note that the syllabus must
reflect the critical role that writing plays in the course. <no text provided> 

Question 2 (see CWB Requirement 2): 
What types of writing (e.g., research papers, problem sets, presentations,
technical documents, lab reports, essays, journaling etc.) will be assigned? Explain how these
assignments meet the requirement that writing be a significant part of the course work, including
details about multiauthored assignments, if any. Include the required length for each writing
assignment and demonstrate how the minimum word count (or its equivalent) for finished writing will
be met. <no text provided> 

Question 3 (see CWB Requirement 3): 
How will students' final course grade depend on their writing performance?
What percentage of the course grade will depend on the quality and level of the student's writing
compared to the percentage of the grade that depends on the course content? Note that this information
must also be on the syllabus. <no text provided> 

Question 4 (see CWB Requirement 4): 
Indicate which assignment(s) students will be required to revise and resubmit after
feedback from the instructor. Indicate who will be providing the feedback. Include an example of the
assignment instructions you are likely to use for this assignment or assignments. <no text provided> 

Question 5 (see CWB Requirement 5): 
What types of writing instruction will be experienced by students? How much class
time will be devoted to explicit writing instruction and at what points in the semester? What types of
writing support and resources will be provided to students? <no text provided> 

Question 6 (see CWB Requirement 6): 
If teaching assistants will participate in writing assessment and writing instruction,
explain how will they be trained (e.g. in how to review, grade and respond to student writing) and how will
they be supervised. If the course is taught in multiple sections with multiple faculty (e.g. a capstone
directed studies course), explain how every faculty mentor will ensure that their students will receive
a writing intensive experience. <no text provided> 

Statement of Certification:  This course is certified as Writing Internsive effective as of  
Readme link.
Course Syllabus requirement section begins below


Course Syllabus  
Course Syllabus: 
For new courses and courses in which changes in content and/or description and/or credits
are proposed, please provide a syllabus that includes the following information: course goals
and description; format;structure of the course (proposed number of instructor contact
hours per week, student workload effort per week, etc.); topics to be covered; scope and
nature of assigned readings (text, authors, frequency, amount per week); required course
assignments; nature of any student projects; and how students will be
evaluated. The University "Syllabi Policy" can be
found here
The University policy on credits is found under Section 4A of "Standards for Semester Conversion" found here. Course syllabus information will be retained in this system until new syllabus information is entered with the next major course modification. This course syllabus information may not correspond to the course as offered in a particular semester. (Please limit text to about 12 pages. Text copied and pasted from other sources will not retain formatting and special characters might not copy properly.) University of Minnesota Department of Chemical Engineering and Materials Science MATS3141: Numerical Methods for Material Science (3 credits) Spring Semester 20XX Syllabus Course Description There are a very limited number of important problems in Materials Science that can be completely solved analytically. In this class, students learn how to solve problems that are impossible to solve analytically, but are amenable to numerical solution. To achieve this, students will learn how to set up problems and program them using MatLab, make reasonable numerical approximations, and solve these problems numerically and/or graphically. In all cases the problems discussed will be closely focused on Materials Science examples encountered in other junior and senior year classes. Specific important Materials Science examples that will be covered include:  Oxidation and corrosion problems coupling diffusion and kinetics  Nucleation and growth problems such as dendritic growth and crystallization  Solutions to the Schrodinger equation relevant to semiconductor devices  Solutions to the equations governing electrostatics relevant to electronic devices  Diffusion problems relevant to processing and synthesis of materials and devices To enable a proper numerical analysis of these various problems, a review and extension of some major math concepts is also given at the beginning of the class. This will focus in particular on differential equations of the form commonly encountered in Materials Science, as well as Fourier methods. Note that the class is designed to be taken concurrently with MATS3002, Mass Transport and Kinetics, and a large number of the examples and problems will focus on such topics. The classes will nevertheless be available to be taken separately. The course is organized around the following themes: Course Objectives Students enrolled in this course will: • be given a review and extension of critical mathematical concepts and methods • be given an introduction to basic numerical methods • be given an introduction to programming using MatLab • learn how numerical methods can be applied to solve practical Materials Science problems • develop an understanding of the potential and limitations of numerical methods in Materials Science and Engineering. Prerequisites Math 2373, Linear Algebra and Differential Equations Math 2374, Multivariable Calculus Chem 4502, Quantum Mechanics OR Phys 2303, Physics III Books Required: “Numerical Methods with Applications in Chemical Engineering” by K. Dorfman and P. Daoutidis (currently in press). “Mathematical Physics” by B. Kusse and E.A. Westwig Optional: • Stormy Attaway, MatLab: A Practical Introduction to Programming and Problem Solving • Stephen J. Chapman, MatLab: Programming for Engineers. • Brian H. Hahn and Daniel T. Valentine, Essential MatLab for Engineers and Scientists Course Web Site http://www.moodle.umn.edu/… The course web site will have links to the lecture notes, homework and exam solutions, practice exams and solutions, and other useful educational links. Do not give the solutions to anyone else; the material is for your own use only. Acting to the contrary will be considered unauthorized collaboration. Main Instructor Prof. K. Andre Mkhoyan Office : 34 Amundson Hall Phone : (612) 6252059 Email : mkhoyan@umn.edu Office Hrs.: M 4:005:00 pm and F 4:005:00 pm, or by appointment. Recitation Instructor (TBD) Prof. Office : Phone : Email : Office Hrs.: Teaching Assistants (TAs) (TBD) Ms./Mr. Office : Phone : Email : Office Hrs: Lectures MWF (6070 students anticipated). This will be a required class for Materials Science and Engineering (MSE) majors. Recitations (solving example problems) Th (3035 students per section) Th (3035 students per section) The recitations will focus on example problem solving and will involve work in small groups. There will be no formal lecture. Homework, Exams and Grading Policy 1. The basis of grading will be as follows: Homework 10% Exam 1 (Wednesday, Feb. XXth) 25% Exam 2 (Wednesday, Apr. XXth) 25% Final (XXX, May XXth) 40% Your letter grade will be determined using your overall score, S, in homework and exams. Your overall score will be determined using: , where, HWavg = average of all homework scores Ei = exam score for exam i Efinal = final exam score 2. Homework will be posted on the course web site on Wednesday after class before midnight and will be due on Wednesday at the beginning of the lecture. NO EXCEPTIONS. In the case of properly documented family emergencies or illness, the missed homework assignment will not be used in evaluating the student’s average homework grade. Homework solutions will be posted on the web site within 24 hours after students have turned in the homework. Students are encouraged to discuss the material and study together in the interest of learning. However, each student is expected to complete their problem sets independently. Students may work on problems together if in the interest of learning. However, problem set solutions must be submitted in the student’s own handwriting and reflect the student’s own reasoning, words and calculations. Remember that your success in the exams will depend on how well you understand the material and the individual effort you put in the problem sets. 3. Questions and complaints regarding homework or exam grading should be directed to Professor Mkhoyan within a week after the graded work is returned to you. If you ask for a regrade we will regrade all parts of the homework and exam in question. 4. The examination and homework due dates are firm. Make up final exams are possible in the case of properly documented family emergencies or illness. Make up final exams will be given after the regularly scheduled exam and will be different than that given in class. While every effort will be made to make exams that are of equal “fairness” and difficulty, students requesting a make up exam acknowledge that they are taking a different exam and agree not to question its difficulty as compared to the inclass exam. 5. There will not be make up midterms. In the case of properly documented family emergencies or illness the missed exam will not be used in evaluating the student’s grade; missed exams will be equally distributed between the remaining exams and the Final. 6. Exams are closed book. You may bring an ordinary scientific calculator to the exams. 7. When answering homework and exam questions write neatly and use complete and clear sentences that are your own. Show all your work with a reasonable number of logical steps that leads to the final answer. Numerical answers must have units unless the value is dimensionless. Write your name and last name on the upper right hand corner of your homework and staple all pages together. Please use graph paper or software to produce all graphs in the homework. Label all axis and give units. The instructors and TAs may give no credit when units are omitted from the graphs or numerical answers. Email Policy In compliance with FERPA and the Minnesota Privacy Act, Students must use their U of M email account for conducting official business with the University of Minnesota. Messages originating from other email accounts will be disregarded. Student Academic Integrity and Scholastic Dishonesty “Academic integrity is essential to a positive teaching and learning environment. All students enrolled in University courses are expected to complete coursework responsibilities with fairness and honesty. Failure to do so by seeking unfair advantage over others or misrepresenting someone else’s work as your own, can result in disciplinary action. The University Student Conduct Code defines scholastic dishonesty as follows: Scholastic Dishonesty: Scholastic dishonesty means plagiarizing; cheating on assignments or examinations; engaging in unauthorized collaboration on academic work; taking, acquiring, or using test materials without faculty permission; submitting false or incomplete records of academic achievement; acting alone or in cooperation with another to falsify records or to obtain dishonestly grades, honors, awards, or professional endorsement; altering forging, or misusing a University academic record; or fabricating or falsifying data, research procedures, or data analysis. Within this course, a student responsible for scholastic dishonesty can be assigned a penalty up to and including an "F" or "N" for the course. If you have any questions regarding the expectations for a specific assignment or exam, ask.” Copying homework solution from others, from solutions to problems posted during previous years and from instructor solution manuals is considered a breach of the above honesty code. Students who breach this code will be reported to the appropriate University authorities, will be given zero on all the homework assignments and may be assigned an “F” in the class. Software Usage The primary application used in the class will be MatLab, which students have access to via the UofM / CSE site license. You will be provided with details of how to access this application.   Outline/Schedule Week Topic Assignment 1 Mathematical Models HW #1 2 Review of Mathematics: Linear Algebra; Review of Mathematics: Norms and Conditioning HW #2 3 Review of Mathematics: Ordinary Differential Equations (ODEs), Partial Differential Equations (PDEs), with applications in MSE HW #3 4 Fourier Series, Fourier Transforms, with applications in MSE HW #4 5 Computer Math/Elements of Computer Algorithms; Elements of Computer Algorithms HW #5 6 Gauss Elimination, Pivoting and Banded Matrices, Iterative Methods MidTerm #1 7 Newton’s Method, NewtonRaphson Method, Examples of Materials Science problems HW #6 8 Linear Interpolation, Gauss Quadrature, Examples of Materials Science problems HW #7 9 Explicit and Implicit Euler Methods, Examples of Materials Science problems HW #8 10 Higher Order Methods, Systems of ODEs and HigherOrder ODEs, Examples of Materials Science problems HW #9 11 FiniteDifference Method, Examples of Materials Science problems HW #10 12 Boundary Value Problems (BVPs), Examples of Materials Science problems MidTerm #2 13 Method of Lines, Examples of Materials Science problems HW #11 14 Twodimensional PDEs, Examples of Materials Science problems HW #12 15 Numerical Fast Fourier Transforms, Examples of Materials Science problems 

Readme link.
Strategic Objectives & Consultation section begins below


Strategic Objectives & Consultation  
Name of Department Chair Approver: 
C. Daniel Frisbie  
Strategic Objectives  Curricular Objectives: 
How does adding this course improve the overall curricular objectives ofthe unit? Fulfilling a computer applications requirement for MatS majors currently involves taking CEGE3101, a Computer Applications class for CEGE. This course understandably focuses on applications in Civil Engineering, and does not provide any materials science specific examples. It is also not integrated into the rest of the materials science curriculum, and does not cover any mathematics topics not covered in the standard preparatory math classes but required for materials science. As such, a numerical methods and computer applications class specifically geared to our majors would be a substantial improvement to our curriculum. This class will allow us to first fill some gaps in the math education of our majors with specific topics that our students need to understand but are not currently taught, followed by numerical methods, followed by numerous example applied directly to materials science problems. The latter will be the main focus of the class, emphasizing the overlap with other MatS classes such as MatS3002, 3012 and 3013, and greatly improving the understanding of our majors in computational materials science. It should be noted that our program is rare among the top ones in the nation in not currently having some form of computational materials science class. 

Strategic Objectives  Core Curriculum: 
Does the unit consider this course to be part of its core curriculum? Yes. See above. CEGE3101 is currently required. In the future, MATS3141 will be required instead. 

Strategic Objectives  Consultation with Other Units: 
In order to prevent course overlap and to inform other departments of new
curriculum, circulate proposal to chairs in relevant units and followup with direct
consultation. Please summarize response from units consulted and include correspondence. By
consultation with other units, the information about a new course is more widely disseminated
and can have a positive impact on enrollments. The consultation can be as simple as an
email to the department chair informing them of the course and asking for any feedback
from the faculty. Consultation with CHEN, CEGE, and Biochem (CBS) shown below, edited for length. D. Bernlohr, Head, Biochem. I have looked at MATS 3141 with an eye to duplication and emphasis. A course in problem solving using numerical solutions that builds on existing courses should be met with broad interest. To my knowledge, the topic listings do not duplicate existing offerings, and have merit and uniqueness. I do not believe that courses such as this are present in the bio arena; for students that double major in a bio major and MATS, problem solving courses are welcome. I think it will be an interesting experiment to see how a problemsolving course works that does not have a lecture but only recitations. Overall, looks like a very practical, solid course that adds to the exceptional repertoire of courses offered by CEMS. S. Kumar, DUGS, CHEN. As ChEn DUGS, I strongly support this course because it will greatly strengthen the math abilities of MatS undergrads. We have long had a similar course in ChEn (3201) that has served our students very well. Courses like this bridge the gap between theory concepts learned in sophomorelevel math and applications encountered in engineering courses. The programming aspects also teach students to think systematically and carefully, and to critically evaluate output provided by computer packages. I predict that the MatS students will enjoy and benefit from this course as much as ChEn students have! R. Barnes, DUGS, CEGE. Although I will miss the energy and insights that MATS students bring to class, I understand your decision to create a course specifically for your students. I am a great believer in the importance of engagement  and, the first and best method to ensure engagement is immediate and obvious relevance; context matters. I recall talking with L. Francis about such a course some years ago. Given your increased enrollments, this addition is inevitable and  in my opinion  a good idea. 
