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At least 37 records · Page 2

SuiteGoo [Slides]

SuiteGoo is a liquid product used to detect "undetectable" material traces. It is used when you need to improve detection limits, anywhere where cotton swiping is used, and anywhere where cotton swiping fails. It is also used by law enforcement to find DNA from fingerprints, used by health care to detect the presence of viruses and bacteria, used by emergency response to detect explosive traces, and used by environmental management to detect pollutant traces.

54 ENVIRONMENTAL SCIENCES↗

Ambient ion focusing from a field-free region to a detector: enhanced signal for explosives and drug detection with mass spectrometry

This study demonstrates ion focusing at ambient pressure and increased ion signal by creating a voltage gradient from a field-free region to a detector, thereby improving the detection of chemicals, such as explosives and drugs. At ambient pressure, ion loss and resulting signal reduction pose challenges that limit detection sensitivity in analytical instruments. Techniques to increase sensitivity, such as atmospheric flow tube-mass spectrometry (AFT-MS), extend ion-molecule reaction times but result in significant overall ion loss due to diffusion. Ion manipulation techniques, though challenging at ambient pressure, can mitigate these losses by concentrating ions toward the detector inlet. Using SIMION, ion trajectories were modeled with a voltage gradient applied between a flow tube and a detector, revealing ion focusing at ambient pressure. Experimental verification with an atmospheric flow tube employed both mass spectrometry and Faraday plate detectors to measure ion beam profiles across varying flow rates, tube diameters, and voltage gradients. Application of a voltage gradient effectively directed ions to the axial center of the flow tube, narrowed ion beam width, and increased signal intensity by 5 to 10 times compared to conditions without a voltage gradient. This ion focusing approach shows promise for improving sensitivity in ambient-pressure instruments. This technique has the potential to enhance detection levels in security and forensic applications, with particular benefits for field-portable devices used at checkpoints to identify explosives and drugs.

ambient pressure↗

A Methodological Overview of Seismic Analysis for Nuclear Event Detection

Underground explosions generate potentially detectable signatures, including energy waves that travel through the Earth’s subsurface (i.e., seismic waves), low-frequency sound waves (i.e., infrasound and hydroacoustic waves), and radioactive gases and/or particles that might leak from the test cavity (if the event was nuclear). There can also be intelligence indicators of a test, such as observations of modified patterns of life and activity at a suspected test site. If all of these detectable signatures and intelligence indicators are present and self-consistent, then analysts have high confidence in classifying a signature generating event as an explosion. However, because only partial information about an event is likely to be available, determining whether an event was natural (e.g., an earthquake or landslide) or manmade (e.g., a chemical or nuclear explosion) is much more challenging. This primer describes how one category of event signatures—seismic signatures—can augment event analyses. While universities and government organizations have generated detailed technical descriptions of seismic analytic techniques, we seek to translate seismic event analysis for a broad, non-technical audience. When the geologic conditions near an event are well-characterized, seismic data can be used to calculate critical information, such as event location and depth, with relatively high accuracy. Moreover, specific features within seismic datasets can help determine whether an event was an explosion. However, a key challenge in seismic analysis is that geologic site conditions are often poorly characterized, complicating the ability to discern the true nature of the event. To overcome this challenge, geologists answer a series of questions (discussed in section 1) to guide seismic event analysis and determine the most probable nature of an event. As more information is gathered during each analytic step, confidence grows regarding the nature of the event. Section 2 addresses uncertainties in seismic analysis and the vital nature of high-fidelity geologic data for accurate seismic event analysis.

58 GEOSCIENCES↗

High-quality microresonators in the longwave infrared based on native germanium

The longwave infrared (LWIR) region of the spectrum spans 8 to 14 μm and enables high-performance sensing and imaging for detection, ranging, and monitoring. Chip-scale LWIR photonics has enormous potential for real-time environmental monitoring, explosive detection, and biomedicine. However, realizing technologies such as precision sensors and broadband frequency combs requires ultra low-loss and low-dispersion components, which have so far remained elusive in this regime. Here, we use native germanium to demonstrate the first high-quality microresonators in the LWIR. These microresonators are coupled to partially-suspended Ge waveguides on a separate glass chip, allowing for the first unambiguous measurements of isolated linewidths. At 8 μm, we measured losses of 0.5 dB/cm and intrinsic quality (Q) factors of 2.5 × 10 5 , nearly two orders of magnitude higher than prior LWIR resonators. Our work portends the development of novel sensing and nonlinear photonics in the LWIR regime.

47 OTHER INSTRUMENTATION↗

Temperature and Pressure Instrumentation for LYNM PE1 Chemical Explosive Testing

Underground chemical explosive testing has been conducted at the Nevada National Security Site under the Physics Experiment 1 (PE1) to validate explosive computer modeling and, ultimately, improve the accuracy of subsurface explosive detection. This SAND Report describes the dynamic temperature and pressure measurements within the chamber induced by the chemical explosive for the first of three experiments, PE1-A. The report details the instrumentation used for the experiment, the emplacement of the hardware, and the measured results. Dynamic temperature measurements were accomplished with the use of optical spectrometers and dynamic pressure was measured with a series of high-rated pressure transducers. This report includes details of the design and results of four cavity sensor systems used to measure early-time temperature, early-time pressure, late-time temperature, and late time pressure. The outcomes of PE1-A were used to inform the design of the remaining PE1 series experiments, PE1-B and PE1-DL.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Quantifying the Potential of Argon Detection Capabilities for Nuclear Explosion Monitoring

Abstract Current noble gas detection systems for nuclear explosion monitoring are based on the detection of four radioxenon isotopes—Xe-131m, -133, -133m and -135. The data provided by radioxenon detection could be enhanced by other radionuclide signatures such as Ar-37. Activation of Ca-40 in rock by neutrons produces Ar-37, and monitoring for this additional nuclide could help distinguish detections of nuclear explosions from background sources, such as medical isotope production. This work studies the capabilities of a hypothetical argon detection network. A 10 kt explosion was modeled using MCNP and SCALE to determine the inventory of Ar-37 created in a representative granite rock layer, assuming either 0.1, 1 or 10% of the total inventory was released. The Ar-37 inventory was combined with atmospheric transport data from HYSPLIT compiled in a previous study, along with the detection limits of standard Ar-37 detection systems, to determine how many hypothetical monitoring stations would detect Ar-37 from an explosion. This method was repeated for 365 HYSPLIT data sets to create a year’s worth of hypothetical explosions, releases, and detections. The study quantified the average number of detections per release, the number of stations detecting Ar-37, and the possibility of detecting Ar-37 in coincidence with xenon.

37Ar↗

Impacts of future nuclear power generation on the international monitoring system

Many countries are considering nuclear power as a means of reducing greenhouse gas emissions, and the IAEA (IAEA, 2022) has forecasted nuclear power growth rates up to 224% of the 2021 level by 2050. Nuclear power plants release trace quantities of radioxenon, an inert gas that is also monitored under international agreements as a signature of nuclear weapons tests. To better understand how nuclear energy growth (and resulting Xe emissions) could affect this global nonproliferation architecture, we modeled daily releases of radioxenon isotopes used for nuclear explosion detection in the International Monitoring System (IMS) that is part of the Comprehensive Nuclear Test-Ban Treaty: 131m Xe, 133 Xe, 133m Xe, and 135 Xe to examine the change in the number of radioxenon detections as compared to the 2021 detection levels. If a 40-station IMS network is used, the detections of 133 Xe in 2050 would range from 82% for the low-power scenario to 195% for the high-power scenario, compared to the detections in 2021. If an 80-station IMS network is used, the detections of 133 Xe in 2050 would range from 83% of the 2021 detection rate for the low-power scenario to 209% for the high-power scenario. Essentially no detections of 131m Xe and 133m Xe are expected. The high growth scenario could lead to a six-fold increase in 135 Xe detections, but the total number of detections is still small (on the order of 1 detection per day in the entire network).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Exploring the MeV sky with a combined coded mask and Compton telescope: the Galactic Explorer with a Coded aperture mask Compton telescope (GECCO)

The sky at MeV energies is currently poorly explored. Here we present an innovative mission concept that builds upon the heritage of past and current missions improving the sensitivity and, very importantly, the angular resolution. This consists in combining a Compton telescope and a coded-mask telescope. We delineate the motivation for such a concept and we define the scientific goals for such a mission. The Galactic Explorer with a Coded Aperture Mask Compton Telescope (GECCO) is a novel concept for a next-generation telescope covering hard X-ray and soft gamma-ray energies. The potential and importance of this approach that bridges the observational gap in the MeV energy range are presented. With the unprecedented angular resolution of the coded mask telescope combined with the sensitive Compton telescope, a mission such as GECCO can disentangle the discrete sources from the truly diffuse emission. Individual Galactic and extragalactic sources are detected. This also allows to understand the gamma-ray Galactic center excess and the Fermi Bubbles, and to trace the low-energy cosmic rays, and their propagation in the Galaxy. Nuclear and annihilation lines are spatially and spectrally resolved from the continuum emission and from sources, addressing the role of low-energy cosmic rays in star formation and galaxy evolution, the origin of the 511 keV positron line, fundamental physics, and the chemical enrichment in the Galaxy. Such an instrument also detects explosive transient gamma-ray sources, which, in turn, enables identifying and studying the astrophysical objects that produce gravitational waves and neutrinos in a multi-messenger context. By looking at a poorly explored energy band it also allows discoveries of new astrophysical phenomena.

79 ASTRONOMY AND ASTROPHYSICS↗

Dose Measurement on Microfocus Computed Tomography Scanner

This Standard Operating Procedure (SOP) outlines the steps for measuring dose in x-ray computed tomography (CT) scans [1] on the MicroCT (MCT) system at the High Explosives Application Facility (HEAF) and other systems relevant to the Livermore Explosives Detection Program (LEDP). These systems include: the DHS LLNL MCT in HEAF, aka HEAFCAT, DHS LLNL MCT Testbed (TB) in B327, and the MCTs at TRMG, HEX2, HMEX, CBX, and IPMO, as described in Section 4.

42 ENGINEERING↗

Intelligent Consequence Control by Aerial Reconnoiter Using Unmanned Systems

In a nuclear accident, or in the aftermath of an improvised nuclear device or radiological dispersal device detonation, radioactive materials may pose a severe health threat to individuals near the site of the incident. The Intelligent Consequence Control by Aerial Reconnoiter Using Unmanned Systems (ICARUS) does the dull, dirty, and dangerous (and, sometimes, deep) work of mapping and characterizing valuable information to enable a safe and appropriate response. ICARUS provides timely answers to the questions, “What is it?” “Where is it?”, and “How far does it extend?” Using commercial, off-the-shelf proven components, the integrated chemical, biological, radiological, nuclear, and explosives detection architecture for our drones provides a solution for collecting radiological, chemical, and optical information on developing complex situations, returning actionable data for determining if it is safe for further response efforts. ICARUS can determine and transmit the location, identity, and intensity of radionuclide contamination to a remote base station. It can deliver on the unexpected.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Crystallization-induced emission enhancement of alkyl chain-dependent pyrene-based luminogens: Visual detection of nitro-explosives

In view of the widespread applications and urgent need for efficient blue emitting materials, the synthesis of such materials has seen renewed interest. In the present work, three alkyl chain-dependent blue emitting pyrene-based luminogens were synthesized and characterized. Here, the experimental results show that these luminogens exhibited high photoluminescence efficiency both in solution (>86%) and in the solid state (>35%). Interestingly, 1,3,6,8-tetrakis (pentylphenyl)pyrene (TPPy), as a photoelectric functional material, was endowed with higher quantum yield (72%) and competitiveness due to a remarkable crystallization-induced emission enhancement (CIEE) property. More importantly, TPPy exhibits high sensitivity and selectivity for ortho-nitroaniline (o-NA) with low limit of detection (9.99 × 10 -8 M), which is mainly due to the distinctive odd-even effects of the terminal alkyl chain. The results demonstrate that this type of luminogen can potentially be utilized for practical applications in the field of contaminant or explosive detection as a sensitive and portable fluorimeter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting multiphase flow and tracer transport for an underground chemical explosive test

Detecting radionuclide gas seepage from clandestine underground nuclear tests is central to nonproliferation explosion monitoring research. Yet, early-time (<6 day) gas transport driven by the explosive pressure wave remains poorly constrained due to scarcity of field data. We simulate multi-phase gas transport in the vadose zone using pre-shot data from a recent chemical explosion in P-Tunnel at the Nevada National Security Site, USA. Despite using a simplified 2D-radial model, predictions of tracer arrival matched observations within one order-of-magnitude. Our results show how transient blast forcing rapidly mobilizes gases from the cavity into surrounding rock – critical for optimizing sensor placement and test planning. This unique integration of field data and modeling represents a significant improvement in our ability to predict gas migration from underground explosions. More broadly, it offers insights into the coupled dynamics of pressure waves and contaminant transport in the vadose zone, with implications for monitoring and hazard assessment.

54 ENVIRONMENTAL SCIENCES↗

Modeling Buried Object Brightness and Visibility for Ground Penetrating Radar

Comparing the observed brightness of various buried objects is a straightforward way to characterize the performance of a ground penetrating radar (GPR) system. However, a limitation arises. A simple comparison of buried object brightness values does not disentangle the effects of the GPR system itself from the system's operating environment and the objects being observed. Therefore, with brightness values exhibiting an unknown synthesis of systemic, environmental, and object factors, GPR system analysis becomes a convoluted affair. In this work, we use an experimentally collected dataset of over 25,000 object observations from five different multistatic radar arrays to develop models of buried object brightness and control for these various effects. Additionally, our modeling efforts provide a means for quantifying the relative brightness of GPR systems, the objects they detect, and the physical properties of those objects that influence observed brightness. To evaluate the models' performance on new object observations, we repeatedly simulate fitting them to half the dataset and predicting the observed brightness values of the unseen half. In addition, we introduce a method for estimating the probability that individual observations constitute a visible object, which aids in failure analysis, performance characterization, and dataset cleaning.

97 MATHEMATICS AND COMPUTING↗

Data Fusion and Feature Extraction of Explosions Recorded on Smartphones

The prompt detection of explosions is a key element of the nuclear non-proliferation mission. With traditional sensors being limited in number and scale, smartphones as compact and economical multi-modal sensors are gaining traction and are being deployed. To address the flood of heterogeneous smartphone data, our team proposes a feature extraction using standardized constant-Q frequency bands across acoustic, barometric, and accelerometer data. The work presented in this poster utilizes three explosions collected on smartphones with Idaho National Lab. More explosions are planned in the near future at INL and NNSS. These extracted features will be used in machine learning methods in future iterations.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Radioxenon Detection for Monitoring Subsurface Nuclear Explosion

The Comprehensive Nuclear-Test-Ban Treaty (CTBT) bans the testing of nuclear weapons anywhere on the earth (atmospheric, surface, underwater and subsurface). Identification of nuclear explosions in the atmosphere, surface, and underwater is relatively straightforward considering a wide range of signatures resulting from such an event. However, for a subsurface explosion, most of the signatures traditionally associated with a nuclear explosion are not readily available. Therefore, the international community has increasingly relied on the atmospheric measurement of noble gases to identify subsurface nuclear weapon explosions. This chapter initially covers the basic principles of subsurface nuclear explosion identification and the importance of detecting radioxenon. This is followed by reviewing some of the early radioxenon detection systems that were developed by research groups around the world in the late 1990s and early 2000s. The detection media employed, results from laboratory and field testing, and some challenges/drawbacks for these systems are detailed. The next section of the chapter is dedicated to innovative detector concepts that have emerged in the past ten to fifteen years using novel detection material, algorithms, and signal readout techniques. The advances achieved in terms of energy resolution, coincidence detection efficiencies, system performance, and the minimum detectable concentration are covered. The final section goes over some of the potential improvements that can be incorporated in the design to enhance detector sensitivity and new detection material that can be explored in the field of radioxenon detection.

Gadey, Harish Reddy↗

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↗