As its name implies, the 3.042 Materials Project Laboratory involves working with such operations as investment casting of metals, injection molding of polymers, and sintering of ceramics. After all the abstraction and theory in the lecture part of the DMSE curriculum, many students have found this hands-on experience with materials to be very fun stuff - several have said that 3.042/3.082 was their favorite DMSE subject. The lab is more than operating processing equipment, however. It is intended also to emulate professional practice in materials engineering project management, with aspects of design, analysis, teamwork, literature and patent searching, web creation and oral presentation, and more.

Laws of thermodynamics: general formulation and applications to mechanical, electromagnetic and electrochemical systems, solutions, and phase diagrams. Computation of phase diagrams. Statistical thermodynamics and relation between microscopic and macroscopic properties, including ensembles, gases, crystal lattices, phase transitions. Applications to phase stability and properties of mixtures. Computational modeling. Interfaces.

Introduction to the interactions between cells and surfaces of biomaterials. Surface chemistry and physics of selected metals, polymers, and ceramics. Surface characterization methodology. Modification of biomaterials surfaces. Quantitative assays of cell behavior in culture. Biosensors and microarrays. Bulk properties of implants. Acute and chronic response to implanted biomaterials. Topics in biomimetics, drug delivery, and tissue engineering. Laboratory demonstrations.

Examines the ways in which people in ancient and contemporary societies have selected, evaluated, and used materials of nature, transforming them to objects of material culture. Some examples: glass in ancient Egypt and Rome; powerful metals in the Inka empire; rubber processing in ancient Mexico. Explores ideological and aesthetic criteria often influential in materials development. Laboratory/workshop sessions provide hands-on experience with materials discussed in class. Subject complements 3.091. Enrollment may be limited.

This course provides techniques of effective presentation of mathematical material. Each section of this course is associated with a regular mathematics subject, and uses the material of that subject as a basis for written and oral presentations. The section presented here is on chaotic dynamical systems.

Scientific computing: Fast Fourier Transform, finite differences, finite elements, spectral method, numerical linear algebra. Complex variables and applications. Initial-value problems: stability or chaos in ordinary differential equations, wave equation versus heat equation, conservation laws and shocks, dissipation and dispersion. Optimization: network flows, linear programming. Includes one computational project.

Topics vary from year to year. Topic for Fall: Eigenvalues of random matrices. How many are real? Why are the spacings so important? Subject covers the mathematics and applications in physics, engineering, computation, and computer science. This course covers algebraic approaches to electromagnetism and nano-photonics. Topics include photonic crystals, waveguides, perturbation theory, diffraction, computational methods, applications to integrated optical devices, and fiber-optic systems. Emphasis is placed on abstract algebraic approaches rather than detailed solutions of partial differential equations, the latter being done by computers.

How do populations grow? How do viruses spread? What is the trajectory of a glider?

Many real-life problems can be described and solved by mathematical models. In this course, you will form a team with another student and work in a project to solve a real-life problem.

You will learn to analyze your chosen problem, formulate it as a mathematical model (containing ordinary differential equations), solve the equations in the model, and validate your results. You will learn how to implement Euler’s method in a Python program.

If needed, you can refine or improve your model, based on your first results. Finally, you will learn how to report your findings in a scientific way.

This course is mainly aimed at Bachelor students from Mathematics, Engineering and Science disciplines. However it will suit anyone who would like to learn how mathematical modeling can solve real-world problems.

This course provides students with decision theory, estimation, confidence intervals, and hypothesis testing. It introduces large sample theory, asymptotic efficiency of estimates, exponential families, and sequential analysis.

This resource may be used as a primary source for a general education/quantitative reasoning (QR) math course delivered in the inquiry based learning style. It may also be used to supplement a QR course with occasional in-class active learning activities.

This course covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.

This course covers the mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from the materials science and engineering core courses (3.012 and 3.014) to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, and fourier analysis. Users may find additional or updated materials at Professor Carter's 3.016 course Web site.

This course was originally developed for the Open Course Library project.  The text used is Math in Society, edited by David Lippman, Pierce College Ft Steilacoom.  Development of this book was supported, in part, by the Transition Math Project and the Open Course Library Project. Topics covered in the course include problem solving, voting theory, graph theory, growth models, finance, data collection and description, and probability.

The purpose of this course is to expose you to the wider world of mathematical thinking. There are two reasons for this. First, for you to understand the power of quantitative thinking and the power of numbers in solving and dealing with real world scenarios. Secondly, for you to understand that there is more to mathematics than expressions and equations.

The core course is a complete, ready to run, fully online course, featuring 9 topics: Problem solving, voting theory, graph theory, growth models, consumer finance, collecting data, describing data, probability, and historical counting. Additional optional topics are provided. The course materials can easily be used with a face-to-face course.

Each topic features:

Readings from a complete textbook, available in printed form for ~$15, or online for free. A playlist of videos, corresponding to the examples in the text. Exercises available in the book, or algorithmically generated online homework and quizzes are available on WAMAP.org (for Washington faculty) or MyOpenMath.com (for everyone else). Writing assignments, requiring the students to think beyond calculations. For many topics, some in-class activities and paper quizzes are available.

The purpose of this course is to expose you to the wider world of mathematical thinking. There are two reasons for this. First, for you to understand the power of quantitative thinking and the power of numbers in solving and dealing with real world scenarios. Secondly, for you to understand that there is more to mathematics then expressions and equations. The core course is a complete, ready to run, fully online course, featuring 9 topics: Problem solving, voting theory, graph theory, growth models, consumer finance, collecting data, describing data, probability, and historical counting. Additional optional topics are provided. The course materials can easily be used with a face-to-face course.

Lebesgue's integration theory with applications to analysis, including an introduction to convolution and the Fourier transform.

This course is an introduction to measurement technology and describes the theoretical foundations and practical examples of measurement systems. The analyzing of measurements problems and specifying of measurements systems are the main subjects that are treated in this course, where the main focus will be on the different kind of measurement errors and the concept of uncertainty in measurement results. Electronic measurement instrumentation will be introduced; a number of conventional sensors for the measurement of non-electronic variables will be described, as well as electronic circuits for the reading of the sensors.-Analyzing of measurement problems-Describing of measurement problems -Analyzing the measurement quantity-Analyzing the measurement boundaries for a quantity to be measured in different circumstances-Professional use of the measurement system-Describing the operating principle of conventional instruments for electronic measurements.-Comparing the available measurement instruments on the basis of quality and accuracy.-Realization of simple measurement setups.-Using the electronic sensor for the measurement of non-electronic variables.-Using a simple signal processing circuits for the reading of the sensors.-Analyzing, presenting and interpreting of measurement results;-Recognizing and describing of error sources.

This course, Measurements for Water is in Dutch, but the following parts are in English:Lectures: Waterbalans Water balance)ReadingsDit vak gaat in op het hoe te doen van typische metingen op het vakgebied van gezondheidstechniek (waterkwaliteit), hydrologie, waterbeheer, waterbouw en vloeistofmechanica (waterkwantiteit).Onderdelen hierin zijn: het herkennen van de relevante parameters, leren over meetmethodes, meetapparatuur, nauwkeurigheid, opstellen van een meetplan, veiligheid, het zelf doen van metingen (laboratorium e/o in het veld) en bewerken en verwerken van gegevens.In een workshop wordt er geleerd met beschikbare electronica componenten een eigen meetsensor te bouwen.Leerdoelen- In staat zijn aan te geven welke parameters van belang zijn bij een bepaald proces- In staat zijn aan te geven hoe de parameters gemeten kunnen worden- Geschikte meetapparatuur kunnen kiezen- Een meetplan kunnen maken (uitvoering, tijd, duur, kosten, veiligheid)- Basis principes electronica in de meettechniek begrijpen en kunnen toepassen

Introduces mechanical and economic models of assemblies and assembly automation on two levels. "Assembly in the small" comprises basic engineering models of rigid and compliant part mating and explains the operation of the Remote Center Compliance. "Assembly in the large" takes a system view of assembly, including the notion of product architecture, feature-based design and computer models of assemblies, analysis of mechanical constraint, assembly sequence analysis, tolerances, system-level design for assembly and JIT methods, and economics of assembly automation. Case studies and current research included. Class exercises and homework include analyses of real assemblies, the mechanics of part mating, and a semester long project.

Here we will learn about the mechanical behavior of structures and materials, from the continuum description of properties to the atomistic and molecular mechanisms that confer those properties to all materials. We will cover elastic and plastic deformation, creep, fracture and fatigue of materials including crystalline and amorphous metals, semiconductors, ceramics, and (bio)polymers, and will focus on the design and processing of materials from the atomic to the macroscale to achieve desired mechanical behavior. We will cover special topics in mechanical behavior for material systems of your choice, with reference to current research and publications.