Genesis Mission Projects

Accelerating American Innovation

AI-driven projects for national scientific challenges

ORNL is taking a central role in the Genesis Mission, leading nine projects and contributing to 32 more that apply AI and advanced computing to some of the nation’s most complex scientific challenges. From fusion energy and critical minerals to water forecasting, advanced materials and autonomous science, these efforts are designed to move promising ideas into practical scientific capabilities with broad national impact.

ORNL leadership and DOE Secretary standing in front of the Frontier supercomputer

Participants prepare posters for a session at the Spallation Neutron Source during a computing-focused event at Oak Ridge National Laboratory.

ORNL-led projects

Phase I

infographic for FADO: Fusion Agentic Design Orchestrator

AI-assisted fusion power plant designs

Developing an AI platform that will integrate high-performance computing tools and robotic system design.

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A spiking attention mechanism, above, acts as the most critical part of a spiking transformer, which ORNL scientists seek to develop for energy-efficient AI. These spiking neural networks mimic the neurons in the human brain and could accelerate scientific discovery while consuming much less power than current systems.

Low-energy AI for scientific discovery

Analyzing scientific data at unprecedented rates and scales with lower costs and higher speeds than conventional AI while maintaining equivalent accuracy.

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Pipit, an AI-based “foundation model factory,” will create custom foundation AI models that U.S. industry can employ in advanced manufacturing such as designed microstructures in 3D printed alloys, above.

AI-accelerated materials development and advanced manufacturing applications

AI-based “foundation model factory” that will create custom foundation AI models that U.S. industry can leverage

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Analyzing the potential for heavy rare earth element resources in granitic terrains across the southeastern U.S. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

AI-enabled discovery of rare earth elements

Improving predictions of underground deposits of materials essential for energy technologies, advanced manufacturing and national supply chain security.

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SciNet, a science-aware autonomous platform for research network operations, will coordinate network traffic among agentic and scientific workflows across institutional boundaries. This image was created with the assistance of AI.

AI-powered operations for self-driving science research

Analyzing scientific data at unprecedented rates and scales with lower costs and higher speeds than conventional AI while maintaining equivalent accuracy.

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HydroORBIT, a multimodal AI foundation model trained on ORNL’s Frontier supercomputer, will improve prediction of surface and groundwater systems across the continental U.S. This image was created with the assistance of AI.

AI foundation model development for water forecasting

Improving prediction of surface and groundwater systems across the continental U.S.

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AI-enabled predictive modeling of the subsurface critical zone across variable U.S. landscapes. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

AI-enabled subsurface biogeochemical modeling

Increasing understanding of underground biogeochemical cycles that affect the availability of resources such as critical minerals.

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Water-for-energy prediction across the Tennessee Valley Authority service region. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

AI for long-range water prediction

Forecasting water availability, streamflow and river temperature weeks to years in advance, supporting hydropower and thermoelectric operations in the Tennessee Valley Authority region.

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ORNL’s Ying Yang leads the SMART-AI project to advance structural materials for fusion energy. AI will make decisions about processing and operating conditions to speed industrial designs. Image credit: Renee Manning, ORNL

AI for next-generation fusion materials development

Linking processing, microstructure and performance that will accelerate deployment of next-generation structural alloys for reliable operation in nuclear fusion power plants.

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Phase II

AI-empowered design of functional quantum magnets

Physics‑informed AI framework for the inverse design of quantum magnets with targeted properties

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Collaborations

Phase I

AI Predictions for Safer, Higher-Performance Nuclear Reactor Control

Reactor Exhaust And Core Twin — Multi-fidelity AI Predictions for Safe, Integrated, and High-Performance Control

Fuel Cladding and Core Internals

Physics Informed Transformer Foundation Model with Uncertainty Quantification for Coupled Eulerian and Lagrangian Flow Physics (PIT-FM)

AI Forecasting of Seasonal and Long-Term Water Conditions

An Agentic AI Framework for Seasonal-to-Interannual U.S. Water Prediction: Coupling Large AI-based Prediction Models and Wavelet Diffusion with E3SM

AI Coordination of Advanced Manufacturing Simulations

Agentic HPC Pipeline Initiative: AI-Driven Orchestration of DOE Lab Codes for Advanced Manufacturing

Optimizing Nuclear Waste Treatment Through Salt Chemistry Predictions

Salt Chemistry Optimization and Prediction Engine for Nuclear Waste Treatment Planning

AI Discovery and Recovery of Geothermal Critical Minerals

AI-Enabled Geobiological Critical Minerals Characterization and Recovery in Geothermal Systems

AI Predictions for Scaling Nuclear Waste Vitrification

Vitrification AI for Scale-Bridging Prediction and Process Translation

Faster AI Modeling of Complex Fluid Flows

ROBIN-NET: RObust BIdirectional PINNs for Accelerated Complex Flow Modeling and Discovery

Digital Modeling of Fusion Fuel Production and Recovery

Developing a Digital Replica of a Deuterium-Tritium Process Loop for Fusion Fuel Cycle Optimization

Machine Learning for Engineering Microbial Gene Transfer

Machine-learning Optimization of Biological Interfaces for Lateral gene Exchange PATHways

AI Predictions of Material Fatigue and Structural Lifespan

A Material Agnostic Physics-Aware, Interpretable AI Framework for Fatigue Life Prediction in TPMS Structures

Real-Time AI Control of Fusion Energy Systems

Weak-Form Agentic Digital Twins for Real-Time Control of Magnetically Confined Fusion Systems Under Sparse Observation

Faster Nuclear Data Analysis Using AI

Accelerating Nuclear Data Delivery Using AI/ML approaches in High Complexity Data Sets

Adaptive AI for Automated Chemical Manufacturing

Closed-Loop, Efficient, Adaptive, and Robust AI for Agentic Chemical Manufacturing

Physics-Enhanced AI Discovery of Unconventional Superconductors

Physics-Enhanced AI Framework for Discovering New Classes of Unconventional Superconductors

AI Management of Distributed Electric Grid Systems

Scalable Agentic Grid Engine for Distribution Systems

Tracing Scientific Data and Model Results to Sources

A Composable Provenance Module for Scientific Foundation Models

AI Modeling of Connected Surface and Groundwater Systems

Rigorous AI and Information Network for Surface-Subsurface Water System Coupling

Tracing Cybersecurity Threats Across Scientific AI Workflows

Scientific Provenance-Oriented Threat Tracing and Attribution for Genesis Workflows

AI Modeling of Subsurface and Reservoir Systems

Molecular-to-Reservoir Integrated AI for Coupled Landscape and Earth-system Subsurface Intelligence

AI Modeling of Reservoir and Groundwater Interactions

Reservoir-Groundwater Interactions for River Flow Variability, Energy, and Resilience with AI

AI-Accelerated Nuclear Astrophysics Simulations

Enabling Nuclear Astrophysics Computational Transformation with AI

AI Discovery of Advanced Semiconductor Materials and Interfaces

From Edisonian Optimization to Predictive Molecular Design: AI-Driven Discovery and Engineering of Advanced Semiconductor Interfaces

AI Platforms for Accelerating 2D Materials Development

AI-Orchestrated Multimodal Platforms for Accelerated Discovery, Scale-Up, and Deployment of 2D Materials

AI Modeling of Complex Turbulent Energy Flows

Differentiable Physics-Integrated Generative Modeling for Complex Turbulent Flows in DOE Energy Systems

AI Optimization of High-Performance Computing Applications

An End-to-End AI Framework for Performance Prediction and Optimization in HPC Applications

Recovering Rare Earth Elements with Magnetic Sorbents

Selective Recovery of Light and Heavy Rare-Earth Element Pairs via Functionalized Magnetic Sorbents with Induction-Assisted Regeneration

AI Tools for Improving Supercomputing Workloads

Using AI to Standardize and Systematically Advance HPC Workloads

AI Discovery of Rare Scientific Events

Enabling Rare Event Discovery with Surrogate Modeling and Simulation AI Agents