Who is J Division? [Slides]
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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LANL is a non-profit Federally Funded Research & Development Center (FFRDC). LANL’s Integrated Weapons Experiments (J) Division addresses national security challenges by executing largescale, integrated, focused experiments, and tests of engineered devices and systems. J-NV plans, fields, and executes dynamic high explosive experiments at NNSS. This includes sub-critical experiments involving special nuclear material, as well as small- and largescale non-nuclear experiments. J-NV generates, analyzes, and disseminates unique, high-quality data.
Abstract Machine learning (ML) is a revolutionary technology with demonstrable applications across multiple disciplines. Within the Earth science community, ML has been most visible for weather forecasting, producing forecasts that rival modern physics‐based models. Given the importance of deepening our understanding and improving predictions of the Earth system on all time scales, efforts are now underway to develop Earth‐system models (ESMs) capable of representing all components of the coupled Earth system (or their aggregated behavior) and their response to external changes over long timescales. Building trust in ESMs is a much more difficult problem than for weather forecast models, not least because the model must represent the alternate (e.g., future or paleoclimatic) coupled states of the system for which there are no direct observations. Given that the physical principles that enable predictions about the response of the Earth system are often not explicitly coded in these ML‐based models, demonstrating the credibility of ML‐based ESMs thus requires us to build evidence of their consistency with the physical system. To this end, this paper puts forward five recommendations to enhance comprehensive, standardized, and independent evaluation of ML‐based ESMs to strengthen their credibility and promote their wider use.
JSNS 2 (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) is an experiment that is searching for sterile neutrinos via the observation of $\overline{ν}$ μ → $\overline{ν}$ e appearance oscillations using neutrinos from muon decay-at-rest. For this search, rejecting cosmic-ray-induced neutron events by Pulse Shape Discrimination (PSD) is essential because the JSNS2 detector is located above ground, on the third floor of the building. We have achieved 94.95% ± 0.15% rejection of neutron events while keeping 92.82% ± 1.77% of signal, electron-like events using a data-driven likelihood method. This article will report the PSD technique using the full fiducial volume of the JSNS2 detector.
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The first conjugated polymers with functional Si–Si crosslinks are reported. In addition to complete structural characterization using solid-state NMR techniques, the electronic structure of the polymers are supported by electrochemical studies.
Project Y laid the foundation for all work currently performed at LANL. LANL is responsible for the stewardship of most of the U.S. nuclear weapons, facilitates global security and nonproliferation, and has been a Federally Funded Research and Development Center (FFRDC) for more than 75 years.
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The 244 Pu ( 48 Ca,𝑥𝑛) 292−𝑥 Fl reaction was investigated at Lawrence Berkeley National Laboratory’s 88 Inch Cyclotron using the Berkeley Gas-filled Separator (BGS), the newly installed Superheavy Recoil detector, along with an upgraded digital electronics and data acquisition system. Seven decay chains were observed starting with an evaporation residue, followed by a single 𝛼 decay and a spontaneous fission. The decay characteristics of these seven decay chains led to an assignment to 288 Fl , the product of the 4𝑛 reaction channel. Two additional chains were (tentatively) assigned to the decay of the 3𝑛 exit channel, 289 Fl . Cross sections for the 4𝑛 and 3𝑛 exit channels were 𝜎 prod =6.7($^{36}_{25}$) pb and 𝜎 prod =1.6($^{22}_{11}$) pb, respectively. Another decay chain, tentatively assigned to the 5𝑛 exit channel through the 48 Ca + 244 Pu reaction or the 3𝑛 exit channel of the 48 Ca + 242 Pu reaction, was also detected. Detailed information regarding the observed decay chains and their nuclear structure aspects is discussed, along with the performance of the BGS and the new detection system.
Using measured and computed O K-edge XAS/XES, we identified electron holes on oxygen in highly OER active amorphous-IrO x powder and their absence in rutile-type IrO 2 , which supports the role of electron deficient oxygen in catalyzing the OER.
Correction for ‘A comprehensive approach for elucidating the interplay between 4f n +1 and 4f n 5d 1 configurations in Ln 2+ complexes’ by Maria J. Beltran-Leiva et al. , Chem. Sci ., 2025, 16 , 2024–2033, https://doi.org/10.1039/d4sc05438e.
Abstract The large‐scale implementation of geological carbon sequestration has raised concerns about potential fault activation and induced seismicity, which could compromise storage integrity and pose seismic risks. We theoretically compared two failure criteria, Mohr‐Coulomb (MC) and Modified Cam‐Clay criteria (MCC), to assess fault rupture during CO 2 storage. Both criteria characterize fault behavior in a specific stress regime but differ in reducing the complexity of fault rupture to a few key mechanisms. Using a coupled hydromechanical model, we demonstrate that the choice of a failure criterion and the physics of fault weakening associated with these criteria strongly condition fault response to a given fluid injection. MC mainly relates rupture to friction, while MCC relates rupture to fault poro‐plasticity. Our findings highlight that the selection of a failure criterion, being inherently subjective, can significantly alter the predicted fault behavior during CO 2 storage, thereby impacting the reliability of geomechanical risk assessments.
csv data for LIF measurements of Ar* species in Ar+N2 plasma at 60-70 mTorr Pressure
Viruses rely on host machinery to replicate, and growing evidence demonstrates that they utilize host epigenetic regulation, including histone modification, to modulate host gene expression for their benefit. Herein, we employed top-down proteomics to quantify histone proteoforms in a model human lung cell line following human coronavirus 229E (HCoV-229E) infection and compared them to mock-infected controls. A total of 572 proteoforms from mock-infected and HCoV-229E infected human lung fibroblast (MRC5) cells (N = 5 per condition) were identified; this included 461 histone proteoforms that were assigned to H2A, H2B, H3, or H4. 200 histone proteoforms were quantifiable, and differential abundance analysis revealed several statistically significant changes in both reversible post-translational modifications (e.g. phosphorylation, acetylation) and the truncation states of core histones. Notably, we found decreased abundance of C-terminally truncated histone H2A and N-terminally truncated histone H3 in HCoV-229E-infected samples. These findings underscore the power of top-down proteomics to resolve unique truncation states of proteoforms and support the hypothesis that viruses alter histone length (removing regulatory sites) to influence host gene expression.
Chemically modified plastics have emerged as practical solutions to plastic waste increases. Here, the inherent novelty of decorating polymer chains with chemical functionality results in distinct properties that expand the available application space. Nevertheless, developing designer materials for specific applications beyond compatibilization or mild property enhancement is difficult due to the synergistic effects of both the polar functionality imparted and the parent materials' intrinsic properties. By incorporating perfluoro-alkyl side-chains onto the backbone of dehydrogenated waste HDPE, unique surface properties intermediate between polytetrafluoroethylene (PTFE, the model fluoropolymer) and HDPE become apparent, while the overall material mechanical and thermal properties result in more LLDPE-like materials. This is demonstrated through moderate decreases in the surface free energy of the perfluoroalkylated polyolefin surface (increase in H 2 O contact angle of ~ 6°) and increased ordering under shear when blended with PTFE nanoparticles where the crossover point occurred at higher strains. Critically, perfluoroalkylated HDPE possesses improved rheological modification properties at elevated temperatures with PTFE nanoparticles, resulting in more thermally robust and stable composite materials.
Chemical synthesis of Li 3 N through lithium nitridation has potential to advance rechargeable battery and nitrogen fixation technology. However, studies of the conditions for forming Li 3 N on the lithium surface via nitrogen gas exposure report contradictory findings, such as the spontaneous reaction of Li with pure N 2 , the impossibility of forming Li 3 N through pure Li and N 2 interaction, the requirement of trace H 2 O to catalyze the reaction, and evidence to the contrary. In this study, ambient pressure X-ray photoelectron spectroscopy (APXPS) was applied to evaluate the in situ chemical evolution of the lithium metal surface under nitrogen gas up to 800 mTorr. At pressures ≤10 mTorr, no Li 3 N was detected. At higher pressures, surface Li 3 N rapidly reacts with trace CO 2 . Additionally, because metallic lithium is readily oxidized by trace gases, the atomic nitrogen concentration of the lithium surface remains below 2%. When nitridation follows oxidation by O 2 gas, CO 2 gas, or H 2 O vapor, surface Li 3 N formation is inhibited. These results suggest that nitrogen gas can diffuse through the oxidized lithium metal surface to react with subsurface metallic lithium.
Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.
Photoelectrochemical (PEC) CO 2 reduction (CO 2 R) directly on chalcogenide semiconductor surface in an aqueous environment.