Tam Fortis needs to validate its computational reactor design before finalizing a configuration for its planned zero-power criticality test. The company requires independent analysis to confirm criticality, shutdown margins, temperature feedback, power distribution, neutron leakage, and the interaction of the reactor’s neutronics, heat pipes, and hydride moderator.
BNNT Materials is developing BNNT-based gaskets for molten salt reactor systems, where high temperatures and corrosive salts create significant sealing challenges. The company needs specialized testing to demonstrate that its gaskets can withstand molten fluoride and chloride salts while maintaining sealing performance, chemical stability, and durability under reactor-relevant conditions.
Ur-Energy seeks to improve groundwater restoration following ISR uranium mining, a process that can take years and add significant costs to uranium production. The company is developing an apatite-based treatment method to more efficiently sequester heavy metals and radionuclides, potentially reducing restoration time, costs, and environmental impacts.
Aalo will work with INL to expand EMRALD’s modeling and simulation capabilities so Aalo can optimize reactor design, economics, and operational reliability. INL developed the EMRALD dynamic risk assessment software and has extensive expertise in advanced reactor modeling, reliability analysis, and microreactor development.
OrganiCore will partner with ORNL to leverage its Spallation Neutron Source (SNS), machine-learning-enabled molecular dynamics capabilities, and prior successful TSL validation work for reactor materials to generate and validate the required nuclear data. The project will create critical-path nuclear data needed to support the design, safety analysis, and licensing of organic-cooled small modular reactors (SMRs).
Raven-Flint will work with Idaho National Laboratory (INL) to develop an integrated mass-balance, MC&A, and supporting stream-characterization for the Raven-Flint pilot plant. This will utilize INLs operating-scale UF₆ conversion expertise and advanced radiochemistry and analytical capabilities. INL’s combination of subject-matter expertise, radiological authority, and analytical instrumentation enables the development of NRC-credible MC&A and stream-characterization methodologies essential for commercial licensing.
Srijan will work with Sandia National Laboratories (SNL) to grow thick-film hBN using carbon-free precursors such as boron tribromide and borazine, enabling the material quality needed for neutron detector applications. SNL possesses specialized chemical vapor deposition (CVD) reactor facilities and expertise in carbon-free hBN epitaxial growth that are unavailable commercially and the laboratory’s advanced characterization capabilities, including XRD, SIMS, and Raman spectroscopy, are also essential for validating impurity levels and semiconductor performance.
Constellation proposes to partner with Oak Ridge National Laboratory (ORNL) to apply high-fidelity multiphysics modeling and high-performance computing to improve predictive understanding of MCO phenomena. ORNL will utilize the Virtual Environment for Reactor Applications (VERA) and complementary computational fluid dynamics simulations to analyze historical operating cycles and identify core- and bundle-level mechanisms driving carryover.
NANO proposes to partner with Oak Ridge National Laboratory (ORNL) to apply the SCALE/TSUNAMI code suite to quantify the impact of nuclear data, modeling assumptions, and operational parameters on key reactor physics metrics, including reactivity, power distribution, and temperature coefficients. ORNL’s NRC-recognized analytical tools and expertise will enable development of a validated UQ framework tailored to the KRONOS design.
NuCube proposes to partner with Argonne National Laboratory (ANL) to verify an autonomous control architecture using a Digital Twin of the DeccaCell reactor. ANL will adapt its existing autonomous operation and diagnostics framework to demonstrate automated startup, remote monitoring, islanding-mode transitions, and predictive maintenance within a validated simulation environment. The project will generate a technically defensible basis for reduced staffing models and support future DOE and NRC licensing engagement.