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...
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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...
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...
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...
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...
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...
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...
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...
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...
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...
Releasing, detecting, and modeling trace aerosols and gases in Earth’s stratosphere
News Article, May 1, 2023 • Proposed actions to reduce ever-increasing global temperatures include geoengineering the Earth’s climate by injecting matter into the stratosphere to reflect sunlight. This proposition, known as Solar Radiation Management, is based on global climate model studies averaged in space and time and Plinian-style volcanic eruptions observations from near-single points. By increasing...
Researchers develop a tantalizing method to study cyberdeterrence
News Article, November 27, 2023 • TANTALUS — The online game simulates how success or failure is within a player’s reach. Experimental war gaming provides insightful data for real-world cyberattacks In Greek mythology, Tantalus was the king of Sipylus who so angered Zeus with his treachery that his punishment was to go thirsty and hungry while...
Sandia scientist testifies how AI is helping with science innovation
News Article, July 23, 2024 • Sandia’s Jennifer Gaudioso testifies during a Senate committee hearing June 4 that DOE data and supercomputing capabilities position U.S. national labs to shape future AI initiatives. (Image captured from hearing video) Sandia’s Jennifer Gaudioso testified before Congress on how scientists at U.S. national laboratories are poised to elevate artificial intelligence...
Soil carbon working group: Collaborative science to enhance predictive understanding.
News Article, April 30, 2024 • Project Description Current Energy Earth System Models (ESM) representation of soil organic matter (SOM) and its response to future environmental changes are not certain. The objective of SOM working group is to enhance our predictive understanding of the response of SOM under future environmental changes. The team hopes to achieve...
The study of Z-pinches with engineered defects
News Article, October 13, 2022 • 3D-magnetohydrodynamic simulations of electrothermal instability growth by studying Z-pinches with engineered defects Electrothermal instability (ETI) is driven by Joule heating and arises from the dependence of resistivity on temperature. When a metal is Joule-heated through the boiling point, ETI drives azimuthally correlated surface density variations or “strata,” which provide the dominant seed...
Transformational capabilities demonstrated by Sandia at AI Expo
News Article, June 17, 2024 • Danny Gomez from Sandia watches as Senator Martin Heinrich experiences the immersive extended reality environment of JARVIS. (Photo courtesy of John Feddema) Ten national laboratories, including Sandia, shared one of the largest booths at the AI Expo for National Competitiveness from May 7-8 in Washington, D.C. The new conference provided...
Understanding the effects of radiation on reconfigurable phase change materials
News Article, June 22, 2023 • David Adams was elected Fellow and President of American Vacuum Society: Science and Technology of Materials, Interfaces and Processing in 2023. Chalcogenide thin films that undergo reversible phase changes show promise for next-generation nanophotonics, metasurfaces, and other emerging technologies. This general class of thin films can be switched rapidly between...
Using machine learning to create rapid stronglink mechanisms
News Article, April 10, 2023 • Computer aided design (CAD) to simulation workflows for nuclear deterrence (ND) have shown dramatic performance improvements with ML. This work targets some of the most inefficient, tedious, and error-prone bottlenecks using new ML-based methods. Common mechanisms such as fasteners and springs can now be quickly identified and reduced to simulation-ready...
Using nonlocal interface problem allows for 7x speedup in large-scale simulations
News Article, May 9, 2023 • Multimaterial problems exist in mission applications such as mechanics and subsurface transport. To capture effects arising from long-range forces at the microscale and mesoscale that aren’t accounted for by classical partial differential equations, the MAThematical foundations for Nonlocal Interface Problems (MATNIP) project team developed a mathematically rigorous interface theory employing...