Nuclear Energy Innovation Summit at ANS Student Conference

By Will Boyd

A first-time event at this year’s American Nuclear Society Student Conference was the Nuclear Energy Innovation Summit, held at the Massachusetts Institute of Technology. The premiere event for the summit was a Pitch Contest that challenged students to effectively communicate their ideas in 90 seconds by using only a single slide per team, followed by 90 seconds of questions from a diverse panel of judges.

Pitch Contest

Twelve teams representing eight universities presented their ideas for how to change the world through nuclear energy—ranging from re-purposed submarine cores for powering remote communities, to an online hub for reactor design collaboration, to co-generation of nuclear power for electricity and process heat for shale oil production.

Sponsoring three cash awards for the summit’s competitions was The MIT Clean Energy Prize,  which engages young entrepreneurs to tackle the world’s most critical energy challenges. The three sponsored awards were the Most Innovative Pitch ($125), the Most Practical Pitch ($125), and the Best Pitch ($250).

The Best Pitch Prize was awarded to Cadet John Asbach and Cadet Branden Passons of the U.S. Military Academy for their pitch titled One in Eight: A Novel Approach to Improving Computer Aided Detection in Mammography Screenings.

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Cadet Branden Passons, Mac MacFarland (CEO of Luminant), and Cadet John Asbach

Click here to see all the Pitch slides

Idea storm

The Innovation Summit also included an Idea Storm, a fast-paced, high-energy brainstorming session that was well received by the students attending the conference. The Idea Storm opened with inspirational talks by Eugene Kuznetsov and Michael Short, both successful pro-nuclear entrepreneurs, about how the start-up model for innovation that has proven so successful in the software industry may be applied to the nuclear industry. Following the talks, the students split into groups to dream up the next great ideas in nuclear energy. The areas for discussion were Small Modular Reactors, Space Reactors, Waste Management, and Generation-V Reactors. The students found the discussions to be an excellent integration of the technology, policy, and economic issues surrounding these key areas.

The Small Modular Reactors discussion group highlighted the opportunities for SMRs to be used for power generation in isolated communities and for resource extraction in remote parts of the world. The Space Reactors discussion group focused on many areas, including the potential for nuclear energy to power space vehicles to mine asteroids for rare earth metals, a vibrant space for start-ups in the private space industry. The Waste Management discussion group focused on the challenges to making deep borehole disposal a reality in the United States today. Finally, the Generation-V Reactors discussion group defined the standards for a “Market-Driven Reactor Design” as a successor to the technological basis behind Generation-IV designs.

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Sam Telleen, Sloan School MBA candidate, at Idea Storm

Owing to the summit’s success, plans are already under discussion for a 2014 summit and for online “tech challenges” that will encourage open collaboration and ideas on key, self-contained industry challenges. Next year’s Innovation Summit at MIT will incorporate an even more vibrant schedule of events for nuclear engineering students to convene to network and present their ideas. Those interested in participating and/or sponsoring the 2014 Innovation Summit or upcoming “tech challenges” should contact the chair, Will Boyd, at Information regarding the event will be trending on Twitter under the handle @NukeInnovators.




Will Boyd is a PhD student in MIT’s Nuclear Science & Engineering Department and a research assistant for the Computational Reactor Physics Group. He is currently developing OpenMOC—a C++/CUDA code implementing the method of characteristics algorithm to solve for the 2D flux distribution in a nuclear reactor core. His current work is on exploring massively parallel algorithms for MOC on machines with one or more GPU accelerators.