Current Research Project
SPARC research projects span multiple disciplines, united by the use of advanced computation, modeling, and AI to address scientific and engineering challenges.
List of current research projects:
- Materials: Computational Materials Science
- Neural Representations for Advanced Radiographic Reconstructions
- Organic Scintillator Based System for Plutonium Assay in Separation Processes
- Artificial Intelligence: Analysis tools for LANL’s CMF simulation workflows
- Artificial Intelligence: Applications to Laser Plasma Interaction
- Advance Algorithms: Neutron Transport
- Materials: Prototype Machining and Delivery
- Advance Algorithms: Kinetic to Continuum Hydro Transition
- Advanced Algorithms for Multiphysics Modeling: Multi-fidelity Surrogates for Fast Prediction and Design
- Physics Models: HEDP
- Transition Modeling for Multi-Fluid Mixing
- Modeling and experimental verification of polymer-bonded crystals: A biphasic LS-DEM approach
- Advanced Algorithms for Multiphysics Modeling: Novel Methods for Multimaterial Hydrodynamics
- Artificial Intelligence: Foundation models and agentic frameworks for computational materials
- Advanced Algorithms for Multiphysics Modeling: Tensor-based Solvers for Thermal Transport with AMR
- Advanced Algorithms for Multiphysics Modeling: Efficient and Accurate Methods for Charged Particle Transport
- AI assisted discovery of new quantum states emerged in topological flatbands
- Codesign: Efficient computation
- FUSE collaboration
- Mixed Precision Methods for DFT-FE
- Materials: Computational Materials Science
- Intelligence search for materials inverse design
- Chemistry-informed modeling of critical material separation
- AI-ML-Conducive MCNP Output
- Molecular Modeling of PFAS Properties
- ArchEvolve – An evolutionary agentic AI system for deep co-design
- Transport Coefficients in Dense Plasmas
- An Autonomous AI Framework for Closed-Loop Nuclear Fuel Qualification
- Hierarchical, Extremely Reduced-order, Multiscale, Exascale Simulator (HERMES)
- Physics Models: HEDP and Optimal Experimental Design