I. Chemistry
310: Mathematical Methods in Chemistry; 4 cr, hrs.
II. Fall 2001
Instructor: Dr. Stanley Leslie Latesky
Office Phone: 869-6222
Home Phone: 869-0453
e-mail: slatesky@lmunet.edu
web: www.lmunet.edu/faculty/latesky
Office Hours: MWF 8:00-9:00 a.m.
T R:
1:30 - 2:30 p.m.
III. Course
Prerequisite: MATH 131-132 (132 may be taken concurrently)
IV. Course
Description/Goals: An introduction to mathematical and computer
techniques that the student will not have been exposed to in previous
mathematics classes. Goals: 1) Teach students how to intuitively solve
problems. 2) To give students an introduction to finite math, including
operator algebra, matrix algebra, and vector algebra. 3) Give students an
introduction to more complex calculus, such as multi-variable calculus, partial
differential equations, and multiple integration
V. Relationship
of this course to content area knowledge
and skills: Mathematical skills are required for the study
chemistry, environmental science, chemical engineering, medical technology, and
secondary education. This course develops the study habits and skills required
for students in these disciplines. It is a course designed for students that
have a high school background in the sciences and have taken college calculus.
It is intended for those students who wish to pursue a career in the sciences,
and engineering.
VI. Textbook:
Boas, M.L.; Mathematical Methods in the Physical Sciences, Wiley, 1983.
VII.
Course Objectives: 1) To improve problem solving
skills. 2) To relate to students the necessity of understanding mathematics as
an applied tool in the sciences. 3) To study the principles and concepts of advanced
mathematics.
VIII.
Outline of Course Content/Units of Instruction:
1. Infinite
series and power series.
2. Complex numbers and complex geometry.
3. Linear
algebra: vectors, matrices, determinants, Cramer’s rule, linear combinations,
linear operators, and linear functions.
4. Differential
Calculus: differentiation in one variable and multiple variables, chain rule,
implicit differentiation, Lagrange multipliers, boundary value problems, change
of variables, calculus of variations, and Leibniz’ rule.
5. Integral
calculus: single and multiple integrals, techniques of integration, Jacobians,
and surface integrals.
6. Vector
analysis: vector manipulations, gradients, line integrals, Green’s theorem,
divergence theorem, and Stoke’s theorem..
7. Differential
equations: separable equations, linear first order equations, second order
equations, partial differential equations, Laplace’s equation, Poisson’s
equation, and other examples.
8. Tensor
analysis: linear transforms, orthogonal transforms, eigenvalues, and
applications.
9. Acids and
bases: review, advanced concepts, equilibrium, and laboratory methods.
10. Inegral
transforms: Laplace transform, Fourier functions and Fourier transforms,
inverse Laplace transforms, Dirac delta functions, Green functions, and
integral transforms of partial differential equations.
11. Probability:
introductions, sample spaces, probability theorems, random variables, methids
of counting, binomial distributions, Gaussian distributions, and Poisson
distributions.
The material covered in this course will
consist of chapter by chapter coverage of the textbook
The instructor will announce any material
that will not be covered. The student
is responsible for reading each chapter and section therein, even if not
discussed in lecture.
IX. Required
Readings: Textbook and supplementary material distributed by the instructor.
X. Suggested
Reading/Bib1iography: None
XI. Method
of Instruction and Learning Classroom
lecture, problem solving, and homework will be the principle method of instruction.
Homework will be collected on a regular basis. Students will be expected to
read the assignments before coming to class.
XII. Course
requirements/Methods of Assessment/Evaluation/Documentation: All students are
expected to attend classes regularly, to complete assignments on time, to
study, and to work. If you choose not to attend class you are
responsible for obtaining any notes and class material from the instructor. The numerical method of assessment is described below:
|
|
4 Exams Assorted problem assignments |
600 points 400 points |
|
|
Total |
1000 points |
|
|
900
to 1000 pt's 800
to 899 pt's 700
to 799 pt's 600
to 699 pt's below
600 pt's |
A B C D F |
+ grades will be assigned to any student in the upper
20% bracket of any grade group
- grades will be assigned to any student in the bottom
30% bracket of any grade group
XIII Clinical/Laboratory/Field
Experience:
XIV. Date of Last
Revision: August 17, 2001