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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...

Accelerating phase field simulations to understand liquid-metal dealloying
News Article, March 3, 2025 • Liquid metal dealloying. The initial species fields (cA and cB at t=0) are contaminated with low-amplitude random white noise (left fields). Given the chaotic nature of the dealloying process, the initial noise perturbation eventually leads to widely different solid phase fields at late time (e.g., right fields, at t=6⁢μs, after 6 million time steps). When...

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...

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...

Deeper insight into radiation-formed defects
News Article, March 3, 2025 • Scientists at Sandia have created a new way to create atomic structures that show the important features of different materials. In the past, scientists could only recreate certain characteristics, like how atoms are arranged in a random mixture, using small crystal structures. Now, they have introduced a new method called...

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

DOE’s next-generation climate model empowers national security planning
News Article, August 24, 2026 • The Energy Exascale Earth System Model version 3 (E3SMv3), developed by Sandia researchers and collaborators as part of a large national lab effort, is a state-of-the-science tool designed to advance our understanding of the Earth and energy systems. This model simulates interactions between the atmosphere, land, rivers, oceans, and sea...

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

Enhancing metasurface performance potential
News Article, March 3, 2025 • By rotating the 𝐶3 symmetry breaking deformation ( 𝜑), the angular positions of the Dirac points and the corresponding polarization singularities for both bands can be controlled. New uses for metasurfaces in both regular and quantum optics are creating a need for better control over how light is polarized, especially...

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

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 gas-phase methyl radicals
News Article, March 3, 2025 • Positive and negative correlations of measured gas-phase methyl and formaldehyde with predicted surface coverages Scientists at Sandia are studying how certain chemical reactions happen on surfaces, especially when using special techniques that allows them to see what is occurring while the reactions are taking place. This is important because many...

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...

Integrase-On-Demand (IOD): simplifying site-specific DNA integration across diverse microbes
News Article, August 24, 2026 • As part of the Intrinsic Control for Genome and Transcriptome Editing in Communities (InCoGenTEC) team, Sandia researchers and academic partners developed a new method called Integrase-On-Demand (IOD), which makes it easier to insert large stretches of DNA into the chromosomes of a wide variety of bacteria, even those that are...

Lignin processing with machine learning approaches
News Article, March 3, 2025 • The schematic diagram for screening of solvents for lignin dissolution. Using ionic liquids (IL) to break down and make use of lignin is really important for creating eco-friendly energy sources and a sustainable economy. Scientists at Sandia, who are part of the Joint Bioenergy Institute (JBEI), are looking closely at...

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.

Molecular monolayers control ultrafast charge and heat transfer in gold for plasmonic applications
News Article, August 24, 2026 • Sandia researchers explore how energy and charge move on ultrafast time scales between gold nano-islands and a single layer of 4-mercaptobenzoic acid (4MBA) molecules attached to their surface, a process at the core of emerging technologies like plasmonic sensors and photocatalysts, which have clear national-security implications for chemical detection and...

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

Predicting Arctic shoreline loss to protect critical infrastructure and security
News Article, August 24, 2026 • Arctic coastlines underlain by ice-rich permafrost are eroding at unprecedented rates as warming air and more powerful storm waves undermine frozen soils. This shoreline loss threatens everything from local communities and pipelines to strategic military sites, making reliable forecasts vital for national security and infrastructure planning. To meet this need,...

Predicting catastrophic failure and collapse in infrastructure
News Article, March 20, 2023 • The team, led by Sandia principal investigator Jessica Rimsza, developed new modeling capabilities for evaluating multiphase phenomena in cement-based materials in energy and infrastructure applications, a chemo-mechanical model for cement fracture, identified sources of uncertainty in cement degradation and concrete fracture, and created six new capabilities for modeling brittle fracture...
A large urban suspension bridge

Rapid, high-fidelity turbulent combustion modeling for next-generation defense engines
News Article, August 24, 2026 • Accurately simulating how fuel burns in turbulent flows is essential for designing and running jet engines, rocket motors, and new hypersonic propulsion systems, which are important for national security. However, fully capturing the complex chemical reactions and fluid transport in these flames can require solving hundreds to thousands of coupled...
Results 1–25 of 37