SCHEDULED MAINTENANCE - nanoHUB.org will be completely unavailable on Wednesday, December 11, 2013 from 7AM EST (12:00 UTC) to approximately 6PM EST (23:00 UTC) for significant hardware and software upgrades. Please plan accordingly and watch this space for further information. We apologize for any inconvenience.
This web-based course was developed by Purdue University Professor of Materials Engineering Alejandro Strachan to update his courses, lectures, and other materials posted on nanoHUB.org, a nanoscience and nanotechnology resource created by the Network for Computational Nanotechnology.
From Atoms to Materials: Predictive Theory and Simulations is a five-unit online course that develops a unified framework for understanding essential physics that govern materials at atomic scales and relate these processes to the macroscopic world. The course will cover important applications, trends, and directions. The course is taught at the level of a Purdue graduate course for first-year students, but there are no admission requirements and no need to travel to Purdue. The online course can be taken from anywhere in the world.
This short course will teach the basic physics that govern materials at atomic scales and relate these processes to the macroscopic world. Students will use online simulations on nanoHUB.org to enhance the learning of density functional theory and molecular dynamics.
Anyone interested in learning the fundamental science of materials and understanding work on atomic or electronic structure calculations. The course will be useful for advanced undergraduates, beginning graduate students, as well are researchers and practicing engineers and scientists. The goal is to provide a simple, accessible, but sound introduction to the fundamental science of materials.
This course is intended to be broadly accessible to those with a background in the physical sciences or engineering. A background in college-level calculus and algebra is expected. An introductory-level background in physics and chemistry, including classical mechanics, chemistry, and thermodynamics is expected.
From Atoms to Materials: Predictive Theory and Simulations
Register for the new, free self-paced course starting July 1, 2013 at http://nanohub.org/groups/fatmwaitinglist.
Students have the chance to experience a Purdue University-level course and earn the opportunity to purchase a digitally signed proof of completion or CEUs from nanoHUB-U. To qualify, a student must attain an average score of 70% or higher. Depending on the course, a separate exam may be required to qualify.
nanoHUB-U is awarding digital badges to students who successfully complete courses. Digital badges are certifiable icons that represent academic achievements or skills smaller than a college degree. More information about digital badges is available:
Students looking for a more relaxed or self-paced learning experience and who are not interested in receiving a proof of completion can simply watch the lectures and take a few quizzes or exams as their time and interest permit.
Five continuing education units (CEU) will be available for a fee of $225 to students who attain an average score of 70% or higher. A CEU transcript will be provided. Records of continuing education units are maintained permanently in Purdue’s system, and individuals can request a transcript at any time for $6.
ALEJANDRO STRACHAN is professor of materials engineering at Purdue University and the deputy director of NNSA’s Center for the Prediction of Reliability, Integrity and Survivability of Microsystems. Prof. Strachan’s research focuses on the development of predictive atomistic and molecular simulation methodologies to describe materials from first principles, their application to problems of technological importance and quantification of associated uncertainties. Application areas of interest include: coupled electronic, thermal and mechanical processes in nano-electronics, MEMS and energy-conversion devices, thermo-mechanical response and chemistry of polymer composites, molecular solids and active materials including shape memory and high-energy density materials.
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