LDRD

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Accelerating multiscale materials modeling with machine learning
News Article, May 9, 2023 • Multiscale materials modeling fundamental insight into microscopic mechanisms that determine materials properties in nuclear stockpile applications that leverage radiation harden semiconductors, advanced manufacturing, shock compression, and energetic materials. This LDRD team including three postdoctoral researchers developed a new ML surrogate model for density functional theory using deep neural networks to...
A cube with balls represents atoms configured on a grid.

Accelerating navigation algorithms
News Article, July 14, 2025 • Thinking creatively about rotations, the team discovered new numerical methods for solving differential equations on rotation groups with increased precision. Here, Mike Walker (left), Daniel Foreman (center), and Michael Sparapany (right) spin toy tops. (Photo by Jennifer Sanderson) One Laboratory Directed Research & Development (LDRD) team took on a critical...

Advancing turbulence models for hypersonic flows using machine learning 
News Article, July 14, 2025 • Sandia researchers utilized machine learning techniques to address the limitations of Reynolds-averaged Navier-Stokes (RANS) turbulence models in predicting hypersonic turbulent flows, with a particular emphasis on inaccuracies in wall heating predictions for flows involving shock boundary layer interactions. This research has led to the development of neural-network-based machine learned turbulence...

Advancing understanding of acoustic signals in underground tunnel structures
News Article, July 14, 2025 • Sandia researchers are using remote data to determine the structure of underground tunnels. Specifically, their research focuses on understanding acoustic resonance in these structures, specifically how changes in tunnel configurations affect the acoustic signals observed from a distance. The potential benefits of this work were presented in May 2024 at...

Biometric calcification for carbon sequestration from seawater 
News Article, June 7, 2023 • Numerous objectives are involved in helping researchers work on biomimetic calcification for carbon sequestration from seawater. An integrated data science and experimental approach is being taken to the challenges of direct capture of CO2 from the ocean. A large group of marine microalgae, coccolithophores, produce calcium carbonate (calcite) plates referred...
A circular diagram with the research project goal broken into three objectives being worked on by researchers.

Catherine Mageeney is seeking a “kill shot” in bacterial pathogens
News Article, January 17, 2023 • Catherine Mageeney, a senior member of Sandia’s technical staff in bioengineering and biotechnology, has expertise in phage biology and genetics with broad applications and implications for scientific research. Phages, or viruses that infect bacteria, are the most numerous and diverse biological-organism in Earth’s biosphere. With approximately 1031 existing phages to be...
Catherine Mageeney in front of Sandia’s Thunderbird logo.

Confirming dismantlement of nuclear warheads while protecting sensitive information
News Article, July 14, 2025 • When it comes to nuclear arms control, verification is essential. By detecting unique metastable radionuclide signatures in non-nuclear material disposition pathways, an LDRD research team created a reliable verification measure to confirm dismantlement of nuclear warheads without disclosing sensitive information. Researcher Peter Marleau led an LDRD team that developed a...

Detonation in multilayer explosives: Effects of characteristic length scale of mixing
News Article, April 10, 2023 • Predicting explosive performance at length scales near the minimum needed for a detonation to propagate is often a challenge—surrounding materials, non-ideal interfaces, sample geometry, and local microstructure variations can all significantly impact explosive output. For accurate predictions of performance, reactive burn models are needed that can capture the details around...
A graphic indicates testing measurements

Developing new and improved safety technology for nuclear weapons
News Article, May 13, 2026 • Two B61-12 joint test assemblies loaded on an F-35 aircraft for a flight test on Aug. 19, 2025. (Photo by Craig Fritz) The Time-Resolved Elastodynamic Discrimination (TRUE-D) Laboratory Directed Research & Development project is focused on improving safety systems for new nuclear weapons, with the goal of making them more...

Enabling fully predictive simulations using disruptive computational mechanics and novel diagnostics
News Article, April 10, 2023 • Sandia Researcher Rekha Rao Accurately capturing solidification of fluids and the development of residual stress is critical for fully predictive simulations for numerous applications in geoscience, nuclear safety, manufacturing, energy production, and bioscience. Researchers on this LDRD project developed, implemented, and demonstrated advanced constitutive models with yield stress to represent...
A female engineer

Extreme environments: Sandia is ready
News Article, May 13, 2026 • Accelerating real-time AI with advanced analog in-memory computing Sandia LDRD researchers have developed tools to go from the invention of new computing devices to application-level performance estimates. (Click image to expand) Sandia is advancing computing capabilities in environments where traditional digital systems struggle, such as space missions exposed to radiation....

Facing radiation challenges head on
News Article, May 13, 2026 • Evolving semiconductor technology for national security applications Silicon wafers serve as the foundationalsubstrate in semiconductor production. With the goal of enhancing the reliability and performance of microelectronics in the face of radiation challenges, Laboratory Directed Research & Development researchers have made significant strides in developing non-volatile, radiation-hard ferroelectric memory using...

Fin-ion tunable transistor for ultra-low power computing 
News Article, June 7, 2023 • Work on this project revealed fundamental principles of electrochemical random access memory and established a viable path toward its integration with complementary metal-oxide semiconductor. Data-heavy workflows such as AI require in to increase system efficiency. Work on this memory computing, so this LDRD team focused on creating analog resistive nonvolatile...
NM - 218372 - Ulta Low Power Computing.png

Fortifying fire control algorithms for cooperative hypersonic target prediction and interception
News Article, May 13, 2026 • Side-by-side comparison of aimpoint selection methods including traditional, literature-based, and Sandia’s multi-hypothesis approach for defending an asset from a hypersonic threat. (Click image to expand) Hypersonic weapons pose a challenge to missile defense systems due to their extreme speed, unpredictable maneuvers, and aimpoint ambiguity. To meet this threat, Sandia Laboratory...

High-quality feedstocks address sustainability challenges associated with rising global demand for protein
News Article, January 23, 2023 • RuBisCO variants increase Methionine and Lysine content. (Graphic courtesy of Sandia Licensing and Technology Transfer.) Ryan Davis, a principal member of Sandia’s technical staff in Bioresource and Environmental Security, and his team developed a high-quality feedstock to address sustainability challenges to meet the growing global demand for protein. RuBisCO (Ribulose-1,5-bisphosphate...
Image of a male scientist looking at a test tube

Imaging the visible emissions from plasmas in pulsed power experiments
News Article, March 16, 2023 • The center section of Sandia's Z Machine Low density plasmas are predicted to impact Sandia’s Z machine experiments in a variety of ways. Magnetic Resonance Tomography instability development during the target implosion can lead to broad trailing density profiles and potentially redistribute current away from the on-axis stagnation region. Low...
A technician gets a target ready for the center section in the Z machine pulsed power facility

Improving assurance of high-consequence systems using formal methods and automated reasoning 
News Article, July 14, 2025 • Error from imperfect computer representations of numbers when visualizing a sphere at 1km and 20,000km distance from an observer. Computers typically represent numbers one of two ways: fixed-point (via integers) and floating-point numbers. Floating point provides improved efficiency and productivity, but errors can accumulate if not managed carefully. Error from...

Improving predictive capability in REHEDS simulations with fast, accurate, and consistent nonequilibrium material properties 
News Article, June 22, 2023 • Sandia scientist Stephanie Hansen was elected Fellow of the American Physical Society by its Division of Plasma Physics. (Photo by Randy Montoya) Predictive design of experiments in Radiation, Electrical, and High Energy Density Science (REHEDS) requires knowledge of material properties (e.g., equations of state (EOS), transport coefficients, and radiation physics). Interpreting...
Sandia scientist Stephanie Hansen

Improving understanding of microbial roles in permafrost carbon release
News Article, June 2, 2025 • As permafrost thaws, it exposes ancient organic matter that microbes can use as fuel. This process contributes to the release of gases like carbon dioxide, methane (CH₄) and volatile organic compounds (VOCs). In areas like the Yedoma permafrost, which holds large amounts of frozen organic material, the formation of thermokarst...

Leveraging machine learning to refine material models for fusion applications
News Article, July 14, 2025 • To enable future innovative designs for fusion platforms on the Z machine, a Sandia LDRD team developed an automated framework for constructing material models. This directly addressed the challenge of creating comprehensive material models that can leverage machine learning and integrate data from multi-fidelity datasets, something vital for uncertainty quantification...

Microbiome editing to improve economic viability of algae growth as a feedstock
News Article, June 27, 2023 • The major challenge with using algae as a feedstock is growing it economically, which hinges strongly on the ability to prevent pond crashes due to biotic factors, like bacteria. Phages, the viruses of bacteria, offer an unexplored solution to this problem. In contrast to antibiotics, phages are typically species-specific and...
Algae is shown growing from underneath the water.

New 2.5D neuromorphic discovery platform will enable AI-enhanced co-design 
News Article, June 7, 2023 • AI-enhanced co-design will be enabled through Sandia’s 2.5D neuromorphic discovery platform. Novel material and device concepts previously took years for iteration. Discoveries in this LDRD project will now allow them to be iterated on in weeks thanks to a new easy fabrication substrate platform for novel devices. The team designed...
A segmented graphic design showing six elements of Sandia’s 2.5D neuromorphic discovery platform.

New technology for heterogeneously integrated devices allows for underfilling of complex geometries using driven fluids 
News Article, June 7, 2023 • Underfilling is a widely used manufacturing process that helps stabilize and reinforce solder joints in electronic parts. However, heterogeneously integrated (HI) devices are challenging to underfill using standard capillary flow methods, due to large areas with narrow gaps—trenches that act as strong flow barriers, and high bump density that cause...

Optimizing machine learning decisions with prediction uncertainty
News Article, May 9, 2023 • Digital background depicting innovative technologies in (AI) artificial systems, neural interfaces and internet machine learning technologies While ML classifiers are widespread, output is often not part of a follow-on decision-making process because of lack of uncertainty quantification. Through this project, the team developed decision analysis methods that combined uncertainty estimates...
Digital background image of brain connectors
Results 1–25 of 40