Explore
For Enterprise
Join for Free
Log In

Navegar
Pesquisar
For Enterprise
Entrar
Inscreva-se gratuitamente

Introduction to the Arrhenius Relationship

Loading...

Materials Science: 10 Things Every Engineer Should Know

Universidade da Califórnia, Davis

4.6 (1,089 classificações) | 33K alunos inscritos

We explore “10 things” that range from the menu of materials available to engineers in their profession to the many mechanical and electrical properties of materials important to their use in various engineering fields. We also discuss the principles behind the manufacturing of those materials. By the end of the course, you will be able to: * Recognize the important aspects of the materials used in modern engineering applications, * Explain the underlying principle of materials science: “structure leads to properties,” * Identify the role of thermally activated processes in many of these important “things” – as illustrated by the Arrhenius relationship. * Relate each of these topics to issues that have arisen (or potentially could arise) in your life and work. If you would like to explore the topic in more depth you may purchase Dr. Shackelford's Textbook: J.F. Shackelford, Introduction to Materials Science for Engineers, Eighth Edition, Pearson Prentice-Hall, Upper Saddle River, NJ, 2015

Visualizar o programa do curso

Habilidades que você aprenderá

Materials, Mechanical Engineering, Engineering Design, Electrical Engineering

Avaliações

4.6 (1,089 classificações)

5 stars
755 ratings
4 stars
279 ratings
3 stars
44 ratings
2 stars
9 ratings
1 star
2 ratings

SS

Jul 25, 2017

It helped me a lot to have a basic idea about different types of materials, processing and properties. I earned basic knowledge about materials and I can teach these relevant topics to students

AP

Jun 24, 2018

Beautiful course. Helped me a lot in the selection of materials for our rocketry team. I'll be sure to suggest this course to my fellow teammates. A big thumbs-up to UCDAVIS for this course.

Na lição

Course Overview / The Menu of Materials / Point Defects Explain Solid State Diffusion

Welcome to week 1! In lesson one, you will learn to recognize the six categories of engineering materials through examples from everyday life, and we’ll discuss how the structure of those materials leads to their properties. Lesson two explores how point defects explain solid state diffusion. We will illustrate crystallography – the atomic-scale arrangement of atoms that we can see with the electron microscope. We will also describe the Arrhenius Relationship, and apply it to the number of vacancies in a crystal. We’ll finish by discussing how point defects facilitate solid state diffusion, and applying the Arrhenius Relationship to solid state diffusion.

Crystallography and the Electron Microscope6:39

Introduction to the Arrhenius Relationship5:33

The Arrhenius Relationship Applied to the Number of Vacancies in a Crystal4:13

Point Defects and Solid State Diffusion3:15

The Arrhenius Relationship Applied to Solid State Diffusion2:38

Ministrado por

James Shackelford
Distinguished Professor Emeritus

Transcrição

So now let's go to the short video lecture, in which we introduce the great Swedish chemist Svante Arrhenius, who quantified for us the important observation that chemical reactions happen more rapidly as we go to higher temperatures. And in fact, they happen more rapidly at an exponentially faster rate. That concept is one that we're going to see helpful in understanding solid state diffusion, but also in a number of other similar applications throughout the remainder of this course. And now we'll have a lesson on diffusion, the transport of atoms within a solid material. And to begin. Let's acknowledge a very important relationship, temperature relationship of chemical reaction rates, originally identified in that regard in the late 19th century. So, what this equation is telling us is at the rate at which chemical reactions occur, increase exponentially with temperature. We see temperature over here on the right side of the equation. It's important to appreciate that that temperature is in the denominator of this exponential term, but it is also in an exponential term that is negative. So if we think that through that means that ultimately as the temperature increases, The rate will increase also, and we'll see very specific examples shortly. We call this the Arrhenius equation, because we're indebted to Svante Arrhenius, a great Swedish chemist from the 19th century. One of the great scientists of the 19th century, he very appropriately won the second Nobel prize in chemistry for this work. In spite of the fact that he was a personal friend of Alfred Nobel, the benefactor for the Nobel prizes, he richly deserved this honor because again, this equation is of tremendous utility and understanding of the nature of chemical reactions in general across a wide temperature range. And very broadly gives us an expression that allows us to appreciate that exponential dependence on temperature for any thermally activated process and again, we'll see in this chapter that diffusion is an excellent example. And we begin to see how this somewhat complex looking small equation becomes elegantly simply if we simply take the logarithm of both sides of the previous form. So we have the logarithm of the rate is equal to the logarithm of that exponential term. And of course the natural logarithm of the base e, is the argument of that exponential and so that is -Q over RT. And the logarithm of a product is the sum of the logarithms, and so the right side of the equation becomes the logarithm of the pre-exponential constant, and the argument of the exponent. So Q over R now becomes the slope of a linear plot. This is basically y is equal to mx plus b, in the usual form, y is we think of y as mx plus b. We have our mx over here and our b over here. So we can look at a plot of this equation, this now nicely linear equation. So, we see as we look at a set of data points with a typical experimental scatter along a wide temperature range, that the best fit through that is a straight line slope. And again, that slope is the minus q over r. Also, because we're plotting this against 1 over temperature and the 0 on that scale is going to correspond to the hypothetical case of 1 over infinite temperature, then we can simply extend this experimental spot to the intercept and get the value then of the logarithm, natural logarithm of the pre-exponential constant. So we have the ability now to be very quantitative about monitoring the rate of chemical reactions.

Explore nosso catálogo

Registre-se gratuitamente e obtenha recomendações, atualizações e ofertas personalizadas.

O Coursera proporciona acesso universal à melhor educação do mundo fazendo parcerias com as melhores universidades e organizações para oferecer cursos on-line.

Coursera

Sobre
Liderança
Carreiras
Lista de cursos
Certificados
Certificados MasterTrack™
Notas
For Enterprise
For Government

Comunidade

Aprendizes
Parceiros
Desenvolvedores
Testadores beta
Tradutores
Blog
Tech Blog

Mais

Termos
Privacidade
Ajuda
Acessibilidade
Imprensa
Contato
Diretório
Afiliados

© 2019 Coursera Inc. Todos os direitos reservados.