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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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Nitrogen-assembled carbon (NAC) activates C–H bonds through closely spaced graphitic nitrogen sites, enabling efficient dehydrogenation and temperature-dependent kinetics without precious metals, offering a sustainable hydrogen storage platform.
Subcellular compartmentalization of macromolecules increases flux and prevents inhibitory interactions to control biochemical reactions. Inspired by this functionality, we sought to build designer compartments that function as hubs to regulate the flow of information through cellular control systems. Here we report a synthetic membraneless organelle platform to control endogenous cellular activities through sequestration and insulation of native proteins. We engineer and express a disordered protein scaffold to assemble micron size condensates and recruit endogenous clients via genomic tagging with high-affinity dimerization motifs. By relocalizing up to ninety percent of a targeted enzymes to synthetic condensates, we efficiently control cellular behaviors, including proliferation, division, and cytoskeletal organization. Further, we demonstrate multiple strategies for controlled cargo release from condensates to switch cells between functional states. These synthetic organelles offer a powerful and generalizable approach to modularly control cell decision-making in a variety of model systems with broad applications for cellular engineering.
The University of Rochester’s Laboratory for Laser Energetics is targeting laser-driven inertial confinement fusion, as part of National Nuclear Security Administration’s Stockpile Stewardship Program and in the quest for clean sources of energy. The Laboratory for Laser Energetics (LLE) is home to two extremely powerful lasers—OMEGA and OMEGA EP—and researchers are using them to explore laser-driven inertial confinement fusion (ICF). ICF involves compressing a small amount of fuel consisting of hydrogen isotopes, deuterium (D), and tritium (T), and heating it to temperatures greater than the center of stars. “When these conditions are reached, the fuel undergoes fusion—releasing enormous energy that can be used for research relevant to the National Nuclear Security Administration’s (NNSA) Stockpile Stewardship Program (SSP) and to drive carbon-free power plants,” explains Valeri Goncharov, distinguished scientist and director of the Theory Division at LLE. LLE was established at the University of Rochester in 1970 and is the largest U.S. Department of Energy university-based research program in the nation, supported by the National Nuclear Security Administration as part of its Stockpile Stewardship Program (SSP). “As a center for exploring the interaction of intense radiation with matter, LLE is a unique national resource for research and education in science and technology,” says Goncharov. “Our current research includes exploring fusion for the SSP program and as a future source of energy, developing new laser and materials technologies, and pursuing a better understanding of high-energy-density phenomena.”
In this issue, highlights of our contributions to mission operations include descriptions of the following. • How exact and scrupulous planning in concert with sophisticated science enabled a first-ever direct measurement of a radionuclide with a half-life as short as six days. The work, which included operations at the Los Alamos Neutron Science Centers (LANSCE) Weapons Neutron Research Facility and the Isotope Production Facility’s hot cell facility, is a boon for both astrophysics and weapons science. • An introduction to Christie Davis and her role in ensuring the Lab’s execution of simultaneous excellence. • A look at progress by AOT’s Target and Experimental Support Team in reclaiming long-dormant space in a radiological controlled area for new work improving target systems for the Lujan Center. • A story showcasing a cross-organizational effort to minimize the directorate’s legacy and environmental footprint. Staff from across the Lab joined together to ensure the safe and efficient disposal of Rocky Flats legacy waste stored in a transportainer at the Target Fabrication Facility. • How the Lab’s Utilities and Infrastructure experts collaborated with stakeholders in our directorate to safety execute preventive maintenance on the LANSCE mesa’s large electrical substation. The Safe Conduct of Research principles provided a common framework for the planning and process. • A description of the resources called upon and the procedures undertaken by MPA to inventory the division’s time-sensitive chemicals, including the careful and conscientious response of an alert team member when something seemed amiss.
Many essential cellular processes, including cell division and the establishment of cell polarity during embryogenesis, are regulated by pattern-forming proteins. These proteins often need to bind to a substrate, such as the cell membrane, onto which they interact and form two-dimensional (2D) patterns. It is unclear how the membrane’s continuity and dimensionality impact pattern formation. Here, we address this gap using the MinDE system, a prototypical example of pattern-forming membrane proteins. We show that when the lipid substrate is fragmented into submicrometer-sized diffusive liposomes, adenosine triphosphate-driven protein–protein interactions generate three-dimensional (3D) spatially extended patterns, despite the complete loss of membrane continuity. Remarkably, these 3D patterns emerge at scales four orders of magnitude larger than the individual liposomes. By systematically varying protein concentration, liposome size, and density, we observed and characterized a variety of 3D dynamical patterns not seen on continuous 2D membranes, including traveling waves, dynamical spirals, and a coexistence phase. Simulations and linear stability analysis of a coarse-grained model revealed that the physical properties of the dispersed membrane effectively rescale both the protein–membrane binding rates and diffusion, two key parameters governing pattern formation and wavelength selection. These findings highlight the robustness of Min’s pattern-forming ability, suggesting that protein–membrane suspensions could serve as an adaptable template for studying out-of-equilibrium self-organization in 3D, beyond in vivo contexts.
Single atom, low valent transition metals are important for heterogeneous catalysis but are challenging to generate and stabilize in a well-defined manner. Herein, we explored the functionalization of silica with well-defined N-heterocyclic phosphenium (NHP) ions to heterogenize low-valent metals. The surface electro-statically bound [NHP] + coordinate to Pt(0) precursors resulting in well-defined, chemisorbed [(NHP)Pt(0)L n ] + sites. The resulting materials catalyze the hydrosilylation of alkynes and exhibit activities and selectivities that rival the current industry standard homogeneous catalysts. The catalysts leach Pt limiting their recyclability; however, recycling studies support that the high regioselectivities arise from heterogeneous sites and Pt particles do not form on the surface. Here we suspect that this phosphenium-based immobilization strategy will result in stable, tunable, low valent heterogeneous transition metal catalysts in a wider array of catalytic reactions.
The fourth edition of the workshop “Quantum Materials Young Investigators” was held June 6-7, 2019 at the Oak Ridge National Laboratory (ORNL). This workshop followed up on previous meetings that took place at ORNL starting in 2016. This important series of annual workshops, organized by Adam Aczel and Stuart Calder, ensures continuous engagement with the early career principal investigators (PIs) of the quantum materials neutron scattering community. Through a series of short scientific talks presented by the external PIs, members of the Neutron Scattering Division (NSD) learn about their scientific interests and needs. Presentations from ORNL staff members also help to inform the external PIs about the current state of ORNL’s quantum materials neutron scattering program. Topics covered include the current instrument suites, sample environment, data reduction, visualization, and analysis, and future neutron scattering and complementary capabilities. Feedback is solicited from the external PIs in all these key areas and communicated to NSD management in the form of a workshop report. This workshop series also helps to foster collaborations between NSD scientists and the research groups of the external PIs and plays an important role in attracting new neutron scattering users.
The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.
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Nuclear forensics is a key part of the nuclear security strategy for the United States and the international community. The NACS Division is central to the leadership role that LLNL has had in nuclear forensics over the past 25 years. Our current nuclear forensic program includes conducting R&D on provenance and attribution signatures, collaborating with international partners, training the next generation of nuclear forensic experts, developing test materials for verification and validation exercises, and providing expert advice to national and international policy makers. Key to our success in these areas has been the strong and continuing involvement in nuclear forensic casework obtained through law enforcement and intelligence channels as well as our outstanding analytical capabilities. NACS must continue to conduct forward-thinking R&D in nuclear forensics that supports operational programs and addresses intelligence gaps. To maintain leadership in nuclear forensics, we must attract, develop, and retain the best talent. The NNSA has a central leadership role in developing educational initiatives for nuclear forensics. In concert with the Glenn T. Seaborg Institute, the NACS Division will continue to participate in all nuclear forensic educational initiatives (undergraduate, graduate, postdoctoral) and incorporate LLNL’s D&I vision into its student and postdoc recruitment efforts. We will continue to build formal relationships with key academic partners and institutions with active and emerging nuclear forensic research interests. We will also strengthen relationships with NNSA DNN and SSAA funded university consortia (e.g. NSSC, ACE, CNEC, CVT, ETI, MTV), helping them conduct research of interest and relevance to nuclear forensics, while at the same time evaluating and recruiting promising talent from these programs.
The fifth edition of the workshop “Quantum Materials Young Investigators” was held August 18-19, 2022 at the Oak Ridge National Laboratory (ORNL). This workshop followed up on previous meetings that took place at ORNL starting in 2016. This important series of annual workshops, organized by Adam Aczel and Stuart Calder, ensures continuous engagement with the early career principal investigators (PIs) of the quantum materials neutron scattering community. Through a series of short scientific talks presented by the external PIs, members of the Neutron Scattering Division (NSD) learn about their scientific interests and needs. Presentations from ORNL staff members also help to inform the external PIs about the current state of ORNL’s quantum materials neutron scattering program. Topics covered include neutron scattering instruments, sample environment, neutron polarization, data reduction, visualization, and analysis, and future neutron scattering and complementary capabilities. Feedback is solicited from the external PIs in some or all of these key areas and communicated to NSD management in the form of a workshop report. This workshop series also helps to foster collaborations between NSD scientists and the research groups of the external PIs and plays an important role in attracting new neutron scattering users.
The Global Spectra-Trait Initiative (GSTI) aims to generate generalizable spectra trait models using reflectance data to predict leaf traits associated with the photosynthesis capacity of leaves. It comprises a synthesized dataset of leaf trait data, input datasets and code. Leaf traits include the maximum carboxylation rate of rubisco (Vcmax), the maximum electron transport rate (Jmax), the dark respiration, as well as the prediction of leaf nitrogen, leaf mass per area (LMA), and leaf water content (LWC). The dataset comprises >7500 paired observations from around 400 species from a broad range of biomes. This dataset comprises a zip file of the GSTI GitHub repository (https://github.com/plantphys/gsti), the synthesized database (.csv) and database metadata files. This dataset was updated on 2025-12-12 with minor edits to mirror the accepted manuscript version and GitHub release (Version 1.0.0 (ESSD accepted version)). Edits included minor changes to the project documentation on GitHub and removal of 12 duplicate entries from the database.
The International Atomic Energy Agency (IAEA) applies safeguards to nuclear facilities that are not operating, including those undergoing decommissioning, and the IAEA’s effort in this area is both considerable and increasing. Specifically, the IAEA Department of Safeguards’ Division of Concepts and Planning (SGCP-003: Safeguards Approaches) identified an R&D need to “Develop safeguards implementation guidelines for facilities under decommissioning and safeguards concepts for post-accident facilities under decommissioning”. Nuclear facilities undergoing decommissioning are not exempt from safeguards agreements between the IAEA and Host State, and, accordingly, the requirement for verification of no diversion of nuclear material and detection of undeclared activities at decommissioned facilities remain even after facility shutdown. However, the effort required to meet safeguards objectives diminishes as nuclear material and essential equipment are removed during the decommissioning process which shifts the emphasis from verification of ever-diminishing fissile or source material inventories to verification of changes in facility design and equipment operability.
We present results from ATTO-Campina, a new permanent observational site in central Amazon, about 4 km from the ATTO towers. Operational since 2020, ATTO-Campina characterizes atmospheric, cloud and rainfall properties through remote sensing. The goal is to provide continuous, complementary measurements to the ATTO towers, addressing the rainforest’s complex gas-aerosol-cloud-precipitation dynamics. Using a 3.5-year dataset, we classified convective clouds into three types: shallow cumulus (ShCu), congestus (Con) or (Deep) clouds. The shallow-to-deep transition takes about three hours, starting with ShCu formation at 11:00 local time. The accumulated rainfall peak follows at about 16:00. Only weak downdrafts are present in the upper troposphere where previous studies indicate new particle formation (NPF) occurrence. Strong downdrafts are mostly limited to heights below 5 km. Con and Deep convective days have higher concentrations of ultrafine aerosol and lower concentrations of accumulation-mode particles compared to ShCu. Convective clouds also significantly modify gas mixing ratios. Deep convective clouds are associated with high near-surface O3, consistent with downward transport from the midtroposphere. Our results showcase the added detail achieved by integrating data from the ATTO towers and ATTO-Campina sites. Together, these sites support better understanding of interconnected gas-aerosol-cloud-precipitation processes in the Amazon and their evolution under climate change.
Abstract If an open quantum system is initially uncorrelated from its environment, then its dynamics can be written in terms of a Lindblad-form master equation. The master equation is divided into a unitary piece, represented by an effective Hamiltonian, and a dissipative piece, represented by a hermiticity-preserving superoperator; however, the division of open system dynamics into unitary and dissipative pieces is non-unique. For finite-dimensional quantum systems, we resolve this non-uniqueness by specifying a norm on the space of dissipative superoperators and defining the canonical Hamiltonian to be the one whose dissipator is minimal. We show that the canonical Hamiltonian thus defined is equivalent to the Hamiltonian initially defined by Lindblad, and that it is uniquely specified by requiring the dissipator’s jump operators to be traceless, extending a uniqueness result known previously in the special case of Markovian master equations. For a system weakly coupled to its environment, we give a recursive formula for computing the canonical effective Hamiltonian to arbitrary orders in perturbation theory, which we can think of as a perturbative scheme for renormalizing the system’s bare Hamiltonian.
This paper provides a high-level comparison between the international and domestic nuclear criticality safety (NCS) standards, as requested by members of the Nuclear Criticality Safety Division. Currently, there are 18 enacted American National Standards Institute (ANSI)/American National Standards (ANS) standards, and 1 ANSI/ANS standard, in progress. There are 11 NCS standards from the International Organization for Standardization (ISO), Technical Committee 85 (TC85) on Nuclear Energy, Subcommittee 5 (SC5) on Nuclear Fuel Cycle, Working Group 8 (WG8). NCS standard revisions are in progress for both standards organizations. The key differences between the ISO TC85/SC5/WG8 and ANSI/ANS-8 consensus NCS standards are summarized. The hard work done by the ANS-8 and WG8 volunteers allows for applicable, high-quality consensus standards for use by the NCS community. This paper defines the current status of each ANSI/ANS and ISO standard, the work in in progress, the revisions/amendments in progress, and WG8/ANS-8 non-standard business in progress. A forthcoming paper will compare the development process for ISO and ANSI/ANS standards.
The E989 Muon g-2 experiment at Fermilab aims to measure the anomalous magnetic moment, a$_\mu$, of the muon with a precision of 140 parts-per-billion. This requires a precise measurement of both the anomalous spin precession frequency, $\omega_a$, and the average magnetic field in terms of the equivalent, free proton Larmor frequency, $\omega_p$. The measurement of $\omega_p$ with a total systematic uncertainty of 70 parts-per-billion involves a combination of various NMR probes. There are 378 probes in fixed locations constantly monitoring field drifts. A water-based probe provides the calibration in terms of $\omega_p$. A crucial element for the multi-step measurement of $\omega_p$ is the regular mapping of the magnetic field over the muon storage region. The former E821 experiment at Brookhaven employed an in-vacuum field mapping system equipped with 17 NMR probes, which was developed by the University of Heidelberg. We have refurbished and upgraded this system with new probes and electronics. The upgrades include a new communication scheme incorporating time-division multiplexing to separate the important NMR reference clock from the data communication. The addition digitization of the NMR signals replaced the hardware-implemented zero-crossing counting of the E821 system. The digitized signals offer new capabilities in the NMR frequency analysis and its related systematic uncertainties. While the mechanical systems that move the field mapper around the ring have been mostly refurbished, the motion control system was completely replaced with a custom-built electronics centered around a commercial Galil motion controller. Both the field mapping NMR system and its motion control were successfully commissioned at Fermilab and have been in reliable operation during the first data taking periods. This article provides details of the upgrades of the field mapper and its performance.
AdditiveFOAM is a computational framework that simulates transport phenomena in Additive Manufacturing (AM) processes. It is built on OpenFOAM (Weller et al., 1998), the leading free, open-source software package for computational fluid dynamics (CFD). OpenFOAM offers an extensible platform for solving complex multiphysics problems using state-of-the-art finite volume methods. AdditiveFOAM leverages these capabilities to develop specialized tools aimed at addressing challenges in AM processing. Metal additive manufacturing, also known as metal 3D printing, is an advanced manufacturing technique that creates physical parts from a three-dimensional (3D) digital model by melting metal powder or wire feedstock. A significant area of research in metal AM focuses on process planning to mitigate anomalous features during printing that are deleterious to part performance (e.g., porosity and cracking), as well as controlling localized microstructure and material properties. Given the high costs and substantial time requirements associated with experimental methods for qualifying new materials and processes, there is a compelling incentive for researchers to utilize advanced computational simulations. In this context, AdditiveFOAM offers a simulation framework to better understand undesirable features in printing, thereby enhancing process planning and reducing the reliance on labor-intensive experimental campaigns.