Skip to main content Accessibility help
×
Home

nanoHUB.org: A Gateway to Undergraduate Simulation-Based Research in Materials Science and Related Fields

  • Tanya A. Faltens (a1), Peter Bermel (a2), Amanda Buckles (a1), K. Anna Douglas (a3), Alejandro Strachan (a4), Lynn K. Zentner (a1) and Gerhard Klimeck (a1) (a2)...

Abstract

Our future engineers and scientists will likely be required to use advanced simulations to solve many of tomorrow's challenges in nanotechnology. To prepare students to meet this need, the Network for Computational Nanotechnology (NCN) provides simulation-focused research experiences for undergraduates at an early point in their educational path, to increase the likelihood that they will ultimately complete a doctoral program. The NCN summer research program currently serves over 20 undergraduate students per year who are recruited nationwide, and selected by NCN and the faculty for aptitude in their chosen field within STEM, as well as complementary skills such as coding and written communication. Under the guidance of graduate student and faculty mentors, undergraduates modify or build nanoHUB simulation tools for exploring interdisciplinary problems in materials science and engineering, and related fields. While the summer projects exist within an overarching research context, the specific tasks that NCN undergraduate students engage in range from modifying existing tools to building new tools for nanoHUB and using them to conduct original research. Simulation tool development takes place within nanoHUB, using nanoHUB’s workspace, computational clusters, and additional training and educational resources. One objective of the program is for the students to publish their simulation tools on nanoHUB. These tools can be accessed and executed freely from around the world using a standard web-browser, and students can remain engaged with their work beyond the summer and into their careers. In this work, we will describe the NCN model for undergraduate summer research. We believe that our model is one that can be adopted by other universities, and will discuss the potential for others to engage undergraduate students in simulation-based research using free nanoHUB resources.

Copyright

References

Hide All
1. Jain, Anubhav, et al. . “Commentary: The Materials Project: A materials genome approach to accelerating materials innovation.” APL Materials 1.1 (2013): 011002.
2. Roco, Mihail C., Mirkin, Chad A., and Hersam, Mark C.. “Nanotechnology research directions for societal needs in 2020.” J Nanoparticle Res 13.3 (2011): 897919.
3. Patton, Stacey, “Influx of Foreign Students Drives Modest Increase in Graduate-School Enrollments,” Chronicle of Higher Education (September 12, 2013). http://chronicle.com/article/Graduate-School-Enrollments/141577/
4. Klimeck, Gerhard, McLennan, Michael, Brophy, Sean P., Adams, George B. III, and Lundstrom, Mark S.. “nanoHUB.org: Advancing education and research in nanotechnology.” Computing in Science & Engineering 10, no. 5 (2008): 1723.
5. Kellogg Foundation, W.K., “Logic Model Development Guide” (2004) https://www.wkkf.org/resource-directory/resource/2006/02/wk-kellogg-foundation-logic-model-development-guide
6. The 2002 User-Friendly Handbook for Project Evaluation, Directorate for Education and Human Resources, Division of Research and Learning in Formal and Informal Settings, National Science Foundation. http://www.nsf.gov/pubs/2002/nsf02057/start.htm
7. CISE REU Toolkit, UNC Charlotte. http://reu.uncc.edu/cise-reu-toolkit
8. nanoHUB.org Usage Overview (2014). https://nanohub.org/usage
9. McLennan, Michael, and Kennell, Rick. “HUBzero: a platform for dissemination and collaboration in computational science and engineering.” Computing in Science & Engineering 12.2 (2010): 4853.
10. Rappture Bootcamp Course (2014). https://nanohub.org/courses/tools
11. Rappture Bootcamp Lecture videos (2012). https://nanohub.org/resources/14671
12. Madhavan, Krishna, Zentner, Michael, and Klimeck, Gerhard. “Learning and research in the cloud.” Nature Nanotechnology 8.11 (2013): 786789.
13. nanoHUB.org Network for Computational Nanotechnology Summer Undergraduate Research Fellowship. https://nanohub.org/groups/ncnsurf/
14. Strachan, A., “Bayesian Simulation Tool,” (2014). https://nanohub.org/tools/bayes
15. Kang, J., Wang, X., Liu, C., and Bermel, P., “S4: Stanford Stratified Structure Solver,” (2013). https://nanohub.org/tools/s4sim/
16. Liu, V. and Fan, S., “S4 : A free electromagnetic solver for layered periodic structures,” Comput. Phys. Commun. 183, 22332244 (2012).
17. Khan, M. Ryyan, Wang, Xufeng, Bermel, Peter, and Alam, Muhammad A., “Enhanced light trapping in solar cells with a meta-mirror following Generalized Snell's law,” Opt. Express 22, A973A985 (2014).
18. Yablonovitch, E., Miller, O. D., and Kurtz, S. R., “A Great Solar Cell also Needs to be a Great LED: External Fluorescence Leads to New Efficiency Record,” Nobel Symposium 153: Nanoscale Energy Converters, vol. 1519, pp. 911 (2013).
19. Chaffee, Dalton, Wang, Xufeng, and Bermel, Peter. “Simulating Nanoscale Optics in Photovoltaics with the S-Matrix Method.” (2014).
20. Harder, Nils-P., and Green, Martin A.. “Thermophotonics.” Semiconductor Science and Technology 18.5 (2003): S270.
21. Mathur, Anubha, Sakr, Enas Said, and Bermel, Peter. “Modeling Thermophotovoltaic Rare Earth Based Selective Emitters.” (2014).
22. Lent, R. W., Brown, S. D. and Hackett, G., J. Vocational Behavior 45, 79 (1994).
23. Bandura, A., Self-efficacy: The exercise of control. New York: Freeman (1997).
24. nanoHUB.org Simulations and Computational Science Group (2014). https://nanohub.org/groups/simulations

Keywords

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed