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At least 55 records · Page 3

Novel design and diagnostics improvements for increased production capacity and improved reliability at the Los Alamos Isotope Production Facility

The Isotope Production Facility (IPF) at Los Alamos National Laboratory (LANL) is used to produce an array of isotopes for medical, global security, and research applications with an intense beam of protons supplied by the linear accelerator at the Los Alamos Neutron Science Center (LANSCE). An Accelerator Improvement Project (AIP) was recently conducted at IPF to improve facility reliability and reduce programmatic risk while increasing general isotope production capacity and flexibility. This was accomplished through the installation of an improved beam window assembly, more robust beam diagnostics, an active and adjustable collimator, and a new beam rastering system. This paper will highlight the four exciting innovations and how they were designed, validated, and installed in parallel as well as the significant operational advantages they provide to IPF. Key experiments and the increased currents achieved in routine production runs demonstrating the enhanced capability from the AIP will be presented. As a result, the most notable capability enhancements include irradiations with beam currents ranging from 100 nA experimental runs up to 300 μA on routine production targets and utilization of a range of cylindrical target diameters.

100 MeV protons↗

Detection and imaging of chemicals and hidden explosives using terahertz time-domain spectroscopy and deep learning

Detecting concealed chemicals and explosives remains a critical challenge in global security. Terahertz time-domain spectroscopy (THz-TDS) offers a promising non-invasive and stand-off detection technique owing to its ability to penetrate optically opaque materials without causing ionization damage. While many chemicals exhibit distinct spectral features in the terahertz range, conventional terahertz-based detection methods often struggle in real-world environments, where variations in sample geometry, thickness, and packaging can lead to inconsistent spectral responses. In this study, we present a chemical imaging system that integrates THz-TDS with deep learning to enable accurate pixel-level identification and classification of different explosives. Operating in reflection mode and enhanced with plasmonic nanoantenna arrays, our THz-TDS system achieves a peak dynamic range of 96 dB and a detection bandwidth of 4.5 THz, supporting practical, stand-off operation. By analyzing individual time-domain pulses with deep neural networks, the system exhibits strong resilience to environmental variations and sample inconsistencies. Blind testing across eight chemicals—including pharmaceutical excipients and explosive compounds—resulted in an average classification accuracy of 99.42% at the pixel level. Notably, the system maintained an average accuracy of 88.83% when detecting explosives concealed under opaque paper coverings, demonstrating its robust generalization capability. These results highlight the potential of combining advanced terahertz spectroscopy with neural networks for highly sensitive and specific chemical and explosive detection in diverse and operationally relevant scenarios.

Imaging and sensing↗

Multiple monoenergetic gamma radiography (MMGR) with a compact superconducting cyclotron

Smuggling of special nuclear materials and nuclear devices through borders and ports of entry constitutes a major risk to global security. Technologies are needed to reliably screen the flow of commerce for the presence of high-Z materials such as uranium and plutonium. Here, we present an experimental proof-of-concept of a technique that uses inelastic (p,p') nuclear reactions to generate monoenergetic photons, which provide means to measure the areal density and the effective-Z (Z eff ) of an object with an accuracy surpassing that achieved by current methods. We use an ION-12 SC superconducting 12 MeV proton cyclotron to produce 4.4, 6.1, 6.9, and 7.1 MeV photons from a variety of nuclear reactions. Using these photons in a transmission mode, we show that we are able to accurately reconstruct the areal densities and Zeff of a test object. This methodology could enable mobile applications to screen commercial cargoes with high material specificity, providing a means of distinguishing common cargo materials from high-Z materials that include uranium and plutonium.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Anticipating Technical Expertise and Capability Evolution in Research Communities Using Dynamic Graph Transformers

The ability to anticipate global technical expertise and capability evolution trends is essential for national and global security, especially in safety-critical domains such as nuclear nonproliferation (NN) and rapidly emerging fields like artificial intelligence (AI). Here, in this work, we extend traditional statistical relational learning approaches (e.g., link prediction in collaboration networks) and formulate a problem of anticipating technical expertise and capability evolution using dynamic heterogeneous graph representations. We develop novel capabilities to forecast collaboration patterns, authorship behavior, and technical capability evolution at different granularities (e.g., scientist and institution levels) in two distinct research fields. We implement a dynamic graph transformer (DGT) neural architecture, which pushes the state-of-the-art graph neural network models by: 1) forecasting heterogeneous (rather than homogeneous) nodes and edges; and 2) relying on both discrete- and continuous-time inputs. We demonstrate that our DGT models predict collaboration, partnership, and expertise patterns with 0.26, 0.73, and 0.53 mean reciprocal rank values for AI and 0.48, 0.93, and 0.22 for NN domains. DGT model performance exceeds the best-performing static graph baseline models by 30%–80% across AI and NN domains. Our findings demonstrate that DGT models boost inductive task performance when previously unseen nodes appear in the test data for the domains with emerging collaboration patterns (e.g., AI). Specifically, models accurately predict which established scientists will collaborate with early career scientists and vice versa in the AI domain.

97 MATHEMATICS AND COMPUTING↗

A Review of Recent and Emerging Machine Learning Applications for Climate Variability and Weather Phenomena

Abstract Climate variability and weather phenomena can cause extremes and pose significant risk to society and ecosystems, making continued advances in our physical understanding of such events of utmost importance for regional and global security. Advances in machine learning (ML) have been leveraged for applications in climate variability and weather, empowering scientists to approach questions using big data in new ways. Growing interest across the scientific community in these areas has motivated coordination between the physical and computer science disciplines to further advance the state of the science and tackle pressing challenges. During a recently held workshop that had participants across academia, private industry, and research laboratories, it became clear that a comprehensive review of recent and emerging ML applications for climate variability and weather phenomena that can cause extremes was needed. This article aims to fulfill this need by discussing recent advances, challenges, and research priorities in the following topics: sources of predictability for modes of climate variability, feature detection, extreme weather and climate prediction and precursors, observation–model integration, downscaling, and bias correction. This article provides a review for domain scientists seeking to incorporate ML into their research. It also provides a review for those with some ML experience seeking to broaden their knowledge of ML applications for climate variability and weather.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity Studies, Gap Analysis, and Benchmark Experiment Optimization for Reactor Physics and Criticality Safety Applications

Many new reactor designs, such as advanced reactors and micro reactors, have materials that lack nuclear data validation. This is also true for many other applications in criticality safety and global security. Both differential and integral experiments are needed to validate cross-section data. Without this, a user cannot have confidence in the predicted results of a radiation-transport code. This work describes an approach called ARCHIMEDES (Application Relevant Critical/Subcritical HEU/Pu-based Integral Measurements for Enhancing Data and Evaluating Sensitivities) to design new criticality experiments that have similar k eff cross-section sensitivities to an application of interest. This process involves simulations to generate cross-section sensitivities to a parameter of interest (such as k eff ), a gap analysis to determine which existing benchmarks are most similar to the application, and an experiment optimization. Recently, there has been a great deal of interest in the reactor physics community on advanced reactors, micro reactors, and accelerator driven systems (ADS). This work will apply the described method to specific examples in this area. The focus of this work will be on the sensitivity study and gap analysis, while future work will include experiment design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

ARIES team achieves major milestone in support of nonproliferation

The Advanced Recovery and Integrated Extraction System (ARIES) Program is a great example of LANL’s Weapons and Global Security programs working together to achieve important nuclear security mission goals. Executed at PF-4, a facility better known for its pit production mission, the ARIES Program is helping the nation meet its nonproliferation commitments by preparing surplus weapons-grade plutonium for final disposition. ARIES recently met a major milestone of producing 1 metric ton of plutonium oxide from material removed from surplus pits. The milestone was celebrated in an awards ceremony at LANL on January 28.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Major Power Rivalry and Nuclear Risk Reduction: Perspectives From Russia, China, and the United States

Since its founding in 1992, the Center for Global Security Research (CGSR) has had an abiding interest in nuclear threat reduction. In the 1990s it did some of the leading thinking about cooperative threat reduction with post-Soviet entities. In the early 2000s it focused increasingly on strengthening the nonproliferation regime. Since 2015 one of its primary interests has been exploring the future of cooperative strategies to reduce nuclear/strategic dangers. That future faces many challenges, both technical and geopolitical. By 2020, a rising sense of urgency of nuclear danger had clearly taken shape in the United States and internationally, driven in significant measure by the renewal of major power rivalry and potential military flashpoints among those powers. And that urgency has driven a rising national and international exploration of what can be done to reduce nuclear dangers.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

2019 LDRD Annual Report

This summary report provides an overview of all LDRD projects at Argonne that concluded in Fiscal Year 2019. Many projects are funded for multiple years, the initial fiscal year for each project is indicated by the first four digits of the LDRD project number. Focus areas were: Advanced Computing; Biological and Environmental Science Capability Development; Hard X-ray Sciences; Manufacturing Science and Engineering; Materials and Chemistry; National and Global Security; Photon Sciences; Securing Energy and Critical Resources; and, The Universe as Our Laboratory (ULab).

36 MATERIALS SCIENCE↗

Applying Compression-Based Metrics to Seismic Data in Support of Global Nuclear Explosion Monitoring

The analysis of seismic data for evidence of possible nuclear explosion testing is a critical global security mission that relies heavily on human expertise to identify and mark seismic signals embedded in background noise. To assist analysts in making these determinations, we adapted two compression distance metrics for use with seismic data. First, we demonstrated that the Normalized Compression Distance (NCD) metric can be adapted for use with waveform data and can identify the arrival times of seismic signals. Then we tested an approximation for the NCD called Sliding Information Distance (SLID), which can be computed much faster than NCD. We assessed the accuracy of the SLID output by comparing it to both the Akaike Information Criterion (AIC) and the judgments of expert seismic analysts. Our results indicate that SLID effectively identifies arrival times and provides analysts with useful information that can aid their analysis process.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

19-LW-045 Full Length Final Report. Molecular Mechanisms of Bacterial Pathogenesis: Waging the Arms Race with Superbugs

As the current global pandemic makes abundantly clear, we need a better understanding of infectious disease to safeguard human health, the economy and global security. Modern omics techniques hold the promise of providing a comprehensive understanding of the molecular mechanisms of life, including causes of pathogenesis from infectious disease at the molecular level, but we there is a serious gap in annotation of gene function. For as much as half of the genes and gene products encoded in genomes the molecular and/or cellular function is unknown or only partially understood. Recent innovations in fluorescence microscopy for live cell imaging and genetic engineering make it possible to determine the temporal correlation between molecular events, such as a gene being expressed due to host-pathogen interaction, and cellular events, such as bacterial invasion of immune cells. This is turn allows us to gain new insight as to the molecular and cellular role of individual genes and will enable the discovery and validation of new molecular mechanisms essential for infectious disease. Knowing the molecular mechanisms of disease processes will provide new therapeutic targets or novel countermeasure strategies. We aimed to develop a lattice light sheet fluorescence microscope as a unique resource at LLNL for long time course live cell imaging experiments; to develop the reagents and cell lines needed to monitor molecular events during the course pathogenic bacteria infecting mammalian immune cells; and to demonstrate that we could capture molecular events during an infection. We fully commissioned the LLNL lattice light sheet microscope and conducted initial proof of principle imaging experiments on mammalian immune cells and pathogenic bacteria. It is clear from the experience gained that long time course live cell imaging has tremendous potential to help elucidate molecular mechanisms of host-pathogen interactions and to help annotate gene function, which would establish a basis for new countermeasures. It is also clear that if live cell imaging is to realize its full potential new data processing and analysis tools will need to be developed to facilitate analysis of molecular events within cells; new sample chambers and stages could facilitate studies with a wider range of cell and tissue types; and alternative molecular tagging methods need to be explored to enable more facile engineering of cells labeled with molecular specificity.

59 BASIC BIOLOGICAL SCIENCES↗

The 2021 Defense Strategy Review and Modern Strategic Conflict (Workshop Summary)

On December 15-17, 2020, the Center for Global Security Research (CGSR) at Lawrence Livermore National Laboratory (LLNL) hosted a workshop titled “The 2021 Defense Strategy Review and Modern Strategic Conflict.” This session was the 7 th Annual Deterrence Workshop that CGSR organized, bringing together participants drawn across the policy, military, and technical communities of the United States and its allies. The workshop examined the challenges of regional wars and multi-domain competition and how a potential 2021 defense strategy review should address them. A special attention was paid to the question of escalation and how it can be controlled at various levels of conflict.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Fit for Purpose? The U.S. Nuclear Posture in 2030 and Beyond (Workshop Summary)

On June 8-10, the Center for Global Security Research (CGSR) at Lawrence Livermore National Laboratory (LLNL) hosted a workshop titled “Fit for Purpose? The U.S. Nuclear Posture in 2030 and Beyond.” This session brought together participants drawn across the policy, military, and technical communities. The workshop aimed to examine the existing modernization plans, the challenges that might obstruct their implementation, and the new deterrence requirements that might emerge in the future, in light of the modernization efforts of Russia and China.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Nuclear Risk Reduction in an Era of Major Power Rivalry (Workshop Summary)

On February 19-20, the Center for Global Security Research (CGSR) at Lawrence Livermore National Laboratory (LLNL) hosted a workshop titled “Nuclear Risk Reduction in an Era of Major Power Rivalry.” This session brought together participants drawn across the policy, military, and technical communities. Among the participants, there were experts from allied countries in Europe and the Asia-Pacific region, as well as experts from Russia and China.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Properties, Theory, and Measurements for Understanding the Function of Heavy Elements (Project 20180474CR, Final Technical Report)

The FY18-20 Laboratory Directed Research and Development (LDRD) funded Properties, Theory, and Measurements for Understanding the Function of Heavy Elements Project aim has been to advance heavy element science in a comprehensive project connecting targeted research with Los Alamos mission imperatives. The mechanisms for project implementation were (1) support of a multi-year broad-based postdoctoral fellows project, (2) a summer student fellows research project and two seminar series, and (3) organization of structured workshops and integrated educational and career development opportunities. The project was successfully administered by the Glenn T. Seaborg Institute (GTSI) for Transactinium Science and has shown to be an exceptional investment in supporting the Los Alamos National Laboratory (LANL) mission areas requiring heavy element and actinide science by attracting and funding the future generation of scientists and engineers. This project exhibited its value across the laboratory in heavy element and actinide science areas include materials, material properties, signatures, modeling, predictions, fabrication, detection, disposal, global security implications, forensics, and the specialized science surrounding plutonium, uranium, and their surrogates as fuels for energy and nuclear weapons. In this report, the GTSI project staff documents the “high return on investment” implementation as measured against the successes of previous actinide research and science-based projects and as evidenced by the retention of 30% of G.T. Seaborg Postdoctoral Fellows as permanent employees. With additional funding through LDRD Reserve funding during this project period, the GTSI expanded its support for heavy element and actinide science research with a Visiting Research Seaborg Scholar and a Rapid Response Small Projects call. These innovations have served to advance GTSI pursuits as communicated in our FY21-23 LDRD Proposal Project#: 20210527CR Seaborg Institute: Center for Advancing Actinide Science and Technology at LANL

36 MATERIALS SCIENCE↗

Applications of seismic threshold monitoring at an Antarctic glacier [Slides]

Geophysical waveforms collected from Arctic regions provides data required for monitoring global security targets. Some seismic instruments deployed on Scandinavian and Greenlandic sites provide waveform data, but these installations include specific challenges: Sea ice and glacial ice generates waveform interference; Meltwater generates narrowband interference, resembling tonal noise.

58 GEOSCIENCES↗

Power Over Ethernet Investigation Report

This report provides insight into collaboration between Savannah River National Laboratory’s (SRNL) Global Security Directorate, Augusta University (AU) and the Georgia Cyber Center (GCC) team with regards to device analysis, investigation, and R&D efforts. Most recently, the GCC/AU team approached SRNL to receive cybersecurity expertise in a joint effort to identify differences between a potentially questionable PoE injector recovered by Columbia County and an identical one purchased by the GCC. The questionable device was installed at a fire station operated in Columbia County, shown in the figure 1-1 below.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Associate Laboratory Directorate for Weapon Physics (ALDX) [Slides]

ALDX is one of seven technical Directorates at the Laboratory and resides within the Weapons Program. The Weapons Physics Directorate stewards a number of critical capabilities to meet its mission. Our mission is to sustain the resilience of the US nuclear stockpile and help shape a globalized nuclear world. Sustaining the aging stockpile poses scientific challenges to assess and certify the stockpile without testing. We are helping to solve major technical challenges in the nuclear global security regime. Geopolitical realities demand the Laboratory’s excellence in providing solutions to national security problems. High Performance Computing at Los Alamos opens the doors to many sophisticated modeling techniques. We use many experimental facilities to probe weapons physics. The diverse skill set required to execute ALDX’s mission has benefited greatly from the Postdoc program.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗