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2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
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Latest News
Second round of Launch Pad selections includes eight newcomers
The National Reactor Innovation Center at Idaho National Laboratory has announced 13 project selections across 12 companies for the Nuclear Energy Launch Pad, a Department of Energy–led program that integrates reactor and fuel facility authorization, testing, and deployment support for private nuclear developers.
The Launch Pad emerged from the Reactor Pilot Program and Fuel Line Pilot Program.
According to INL, projects selected include reactor development and nuclear fuel cycle advancements, including fabrication, enrichment, and conversion technologies.
Robert Lawrence Ives, Michael Read, Jeffrey Neilson, Thuc Bui, David Marsden, Thuy Le, Hien Tran
Fusion Science and Technology | Volume 82 | Number 3 | April 2026 | Pages 561-571
Research Article | doi.org/10.1080/15361055.2025.2523609
Articles are hosted by Taylor and Francis Online.
Recent advancements in fusion power have led to focused research on cost-effective electricity generation. While plasma physics studies continue, researchers are also working on practical challenges, such as protecting the reactor walls, managing tritium fuel, and improving plasma heating devices. It is anticipated that electron cyclotron heating will be a primary heating mechanism and that improved gyrotrons will be required. Economical fusion power will require gyrotrons that are lower cost and more efficient than currently available. Key requirements will be efficiency higher than 60% and a radio frequency (RF) output power in waveguide. This will also require advanced power supply systems.
The research here is focused on the development of gyrotron systems suitable for fusion power plants. Development of a multistage depressed collector capable of 70% efficiency is described, as well as the development of an improved output coupler that improves efficiency with a significant reduction in gyrotron system cost. This paper also describes the development of machine Learning algorithms to control the power supplies and maximize efficiency under all gyrotron operating conditions.