State-Tribal Collaboration: Tribal Right to Create Laws
One of 6 fact sheets for the State/Tribal Collaboration project. This is on the topic of Tribal Right to Create Laws.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
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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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A High-Order Eulerian–Lagrangian Runge–Kutta Finite Volume (EL–RK–FV) Method for Scalar Nonlinear Conservation Laws
Abstract We present a class of high-order Eulerian–Lagrangian Runge–Kutta finite volume methods that can numerically solve Burgers’ equation with shock formations, which could be extended to general scalar conservation laws. Eulerian–Lagrangian (EL) and semi-Lagrangian (SL) methods have recently seen increased development and have become a staple for allowing large time-stepping sizes. Yet, maintaining relatively large time-stepping sizes post shock formation remains quite challenging. Our proposed scheme integrates the partial differential equation on a space-time region partitioned by linear approximations to the characteristics determined by the Rankine–Hugoniot jump condition. We trace the characteristics forward in time and present a merging procedure for the mesh cells to handle intersecting characteristics due to shocks. Following this partitioning, we write the equation in a time-differential form and evolve with Runge–Kutta methods in a method-of-lines fashion. High-resolution methods such as ENO and WENO-AO schemes are used for spatial reconstruction. Extension to higher dimensions is done via dimensional splitting. Numerical experiments demonstrate our scheme’s high-order accuracy and ability to sharply capture post-shock solutions with large time-stepping sizes.
Chen, Jiajie↗
Ohm’s Law, the Reconnection Rate, and Energy Conversion in Collisionless Magnetic Reconnection
Magnetic reconnection is a ubiquitous plasma process that transforms magnetic energy into particle energy during eruptive events throughout the universe. Reconnection not only converts energy during solar flares and geomagnetic substorms that drive space weather near Earth, but it may also play critical roles in the high energy emissions from the magnetospheres of neutron stars and black holes. In this review article, we focus on collisionless plasmas that are most relevant to reconnection in many space and astrophysical plasmas. Guided by first-principles kinetic simulations and spaceborne in-situ observations, we highlight the most recent progress in understanding this fundamental plasma process. We start by discussing the non-ideal electric field in the generalized Ohm’s law that breaks the frozen-in flux condition in ideal magnetohydrodynamics and allows magnetic reconnection to occur. We point out that this same reconnection electric field also plays an important role in sustaining the current and pressure in the current sheet and then discuss the determination of its magnitude (i.e., the reconnection rate), based on force balance and energy conservation. This approach to determining the reconnection rate is applied to kinetic current sheets with a wide variety of magnetic geometries, parameters, and background conditions. We also briefly review the key diagnostics and modeling of energy conversion around the reconnection diffusion region, seeking insights from recently developed theories. Finally, future prospects and open questions are discussed.
79 ASTRONOMY AND ASTROPHYSICS↗
A buoyancy–shear–drag–scalar-based turbulence model for power-law acceleration-driven Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing
A previously developed phenomenological turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz instability-induced mixing based on a general buoyancy–shear–drag model [O. Schilling, “A buoyancy–shear–drag-based turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing,” Physica D 402, 132238 (2020)] is extended to include active or passive scalar mixing and power-law acceleration-driven Rayleigh–Taylor mixing. The buoyancy–shear–drag equations are coupled to a scalar variance equation that is used to define the molecular mixing parameter θ m , and when the scalar is active, modifies the Rayleigh–Taylor and Kelvin–Helmholtz mixing layer growth parameters to depend on the asymptotic value of this parameter, θ mol . Here, the scalar variance equation is closed by algebraically or differentially modeling the scalar variance dissipation rate. Nonlinear analytical solutions of the model are obtained in the total and separate bubble and spike mixing layer width formulations with the algebraic scalar variance dissipation rate for each instability, which are then used to calibrate the mechanical and scalar equation coefficients to predict specific values of physical observables and molecular mixing parameters. Surrogate mechanical and scalar turbulent fields can be constructed by multiplying a presumed self-similar spatial profile by appropriate functions of the width and its time derivative, and of the scalar obtained by solving the ordinary differential model equations. The explicit modeling and solution of turbulent transport equations are not required. The bubble and spike mixing layer width and scalar variance equations are then solved numerically for constant-acceleration Rayleigh–Taylor, impulsively reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing, confirming that the prescribed level of molecular mixing is correctly predicted and illustrating the spatiotemporal evolution of the scalar fields.
Buoyancy–drag↗
Numerical validation of scaling laws for stratified turbulence
Recent theoretical progress using multiscale asymptotic analysis has revealed various possible regimes of stratified turbulence. Notably, buoyancy transport can either be dominated by advection or diffusion, depending on the effective Péclet number of the flow. Two types of asymptotic models have been proposed, which yield measurably different predictions for the characteristic vertical velocity and length scale of the turbulent eddies in both diffusive and non-diffusive regimes. The first, termed a ‘single-scale model’, is designed to describe flow structures having large horizontal and small vertical scales, while the second, termed a ‘multiscale model’, additionally incorporates flow features with small horizontal scales, and reduces to the single-scale model in their absence. By comparing predicted vertical velocity scaling laws with direct numerical simulation data, we show that the multiscale model correctly captures the properties of strongly stratified turbulence within regions dominated by small-scale isotropic motions, whose volume fraction decreases as the stratification increases. Meanwhile its single-scale reduction accurately describes the more orderly, layer-like, quiescent flow outside those regions.
Mechanics↗
Above the Energy Gap Law: Heavy Chalcogenide Substitution in NIR II-Emissive Diradicaloid Qubits
Near-infrared (NIR, 700–1700 nm)- and telecom (∼1260–1625 nm)-emissive molecules are good candidates for biological imaging and quantum sensing applications, respectively; however, bright low energy emission is rare due to exponentially increasing nonradiative decay rates in these regions, a phenomenon known as the energy gap law. Recent literature has emphasized the importance of minimizing skeletal modes to prevent increased nonradiative decay rates, but most organic lumiphores in these regions utilize large, conjugated scaffolds containing many C═C modes. Here we report a compact, telecom-emissive scaffold, tetrathiafulvalene-2,3,6,7-tetraselenate, or TTFts, that displays remarkable air, water, and acid stability, exhibits record quantum yields and brightness values, and retains quantum coherence under ambient conditions. These properties are enabled through methodical selenium substitution, which bathochromically shifts emission while shifting skeletal vibrations to lower energies. This new scaffold validates heavy heteroatom substitution strategies and establishes a new class of bright telecom emitters and robust qubits.
biological imaging↗
Observation of Transition from Rate Law to Butler–Volmer Controlled Water Oxidation Kinetics on Hematite Photoanodes
Despite its central role in photoelectrochemical (PEC) water splitting, the mechanistic pathway of water oxidation on metal oxides remains unresolved, with population-based and Butler–Volmer (BV) models offering distinct views on how surface valence band holes drive the reaction. Here, we bring together these two perspectives by combining operando photoinduced absorption (PIA) spectroscopy with photocurrent analyses on α-Fe 2 O 3 (hematite) photoanodes as a function of light intensity. We find a crossover from population-controlled, rate law water oxidation at low hole densities to a BV-like, potential driven regime at high densities, triggered by band edge unpinning once surface M–OH species are fully oxidized, and excess holes accumulate without compensation. This mechanistic transition unifies competing models of interfacial charge transfer and reveals design principles for optimizing water oxidation in metal oxide photoelectrodes.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Semi-empirical model for Henry’s law constant of noble gases in molten salts
Henry’s law constant, which describes the proportionality of dissolved gas to partial pressure of free gas in liquid–gas equilibrium systems, can also be applied to mass transport applications. In this work, we investigated an approach for determining the solubility of noble gases in a molten salt liquid utilizing the equilibrium concept of Henry’s gas constant. Henry’s gas constant is described as a mathematical function dependent on the van der Waals radius of the noble gas and the temperature of the molten salt. The alteration in Gibbs free energy encompasses contributions from both surface and volume energies. Enthalpy and entropy are deduced from these surface and volume energies in the Gibbs free energy formulation. A comparative analysis was conducted between the conventional method and our proposed model. Moreover, useful chemical properties can be determined from examination of surface and volume energies. Our findings provide an accurate and general theory of Gibbs free energy that can be validated experimentally based on the model proposed herein. This work unifies the prediction of Henry gas constant and subsequently the entropy and enthalpy calculation for noble gases in a molten salt solution to a single functional form using van der Waals radius of the gas and temperature of the system. This functional form is then used to perform a multiple regression method to find two parameters corresponding to the surface energy and volume energy. These two parameters are consistent between all combinations of noble gas and molten salt.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Vegard's law in multivariate libraries of porous interpenetrated zirconia organic frameworks
In this contribution we demonstrate that metal–organic frameworks (MOFs) with suitable underlying topological structure are amenable for the preparation of MOF-based substitutional solid-solutions (SSS) that follow Vegard's law.
Chemistry↗
Cyberattack Detection and Mitigation on Central Volt‐VAr Using Circuit Law and Machine Learning
ABSTRACT In a distribution grid, voltage is maintained within a nominal range through a Volt‐VAr function that controls capacitor banks, reactive power of distributed energy resources (DER), and on‐load tap changers (OLTC). Availability of communications helps with the implementation of central Volt‐VAr control; however, it also opens the system to cyberattacks, causing voltage disturbances. Previous work has shown the adverse impacts of false data injection (FDI) on the central Volt‐VAr control; however, very few works have studied methods to detect and mitigate FDI on Volt‐VAr control. This paper addresses gaps in the detection and mitigation of FDI on the measurement packets of a central Volt‐VAr control. This work uses a two‐stage algorithm for cyberattack detection since the accuracy of a single‐stage machine learning (ML)–based detection method decreases while dealing with unseen data. The first stage is based on the verification of measurements against circuit laws, and the second stage utilizes a tree search algorithm and an ML method to detect the falsified data. This paper compares long short‐term memory (LSTM) and bidirectional LSTM (BiLSTM) as the employed ML algorithms. Finally, the mitigation algorithm replaces the falsified data with the estimated output of the ML algorithm. The effectiveness of the proposed method is tested for several cases using the IEEE 13‐bus test system in PSCAD software.
Beikbabaei, Milad [Bradley Department of Electrica↗
The “energy gap law” for mid-infrared nanocrystals
Colloidal quantum dots are of increasing interest for mid-infrared detection and emission, but device performances will vastly benefit from reducing the non-radiative recombination. Empirically, the photoluminescence quantum yield decreases exponentially toward the mid-infrared, which appears similar to the energy gap law known for molecular fluorescence in the near-infrared. For molecules, the mechanism is electron–vibration coupling and fast internal vibrational relaxation. Here, we explore the possible mechanisms for inorganic quantum dots. The primary mechanism is assigned to an electric dipole near-field energy transfer from the quantum dot electronic transitions to the infrared absorption of surface organic ligands and then to the multiphonon absorption of the quantum dot inorganic core or the surrounding inorganic matrix. In order to obtain luminescent quantum dots in the 3–10 μm range, we motivate the importance of using inorganic matrices, which have a higher infrared transparency compared to organic materials. At longer wavelengths, inter-quantum dot energy transfer is noted to be much faster than radiative relaxation, indicating that bright mid-infrared colloidal quantum dot films might then benefit from dilution.
Chemistry↗
Interfacial defect reduction enhances universal power law response in Mo–SiNx granular metals
Granular metals (GMs), consisting of metal nanoparticles separated by an insulating matrix, frequently serve as a platform for fundamental electron transport studies. However, few technologically mature devices incorporating GMs have been realized, in large part because intrinsic defects (e.g., electron trapping sites and metal/insulator interfacial defects) frequently impede electron transport, particularly in GMs that do not contain noble metals. Here, we demonstrate that such defects can be minimized in molybdenum–silicon nitride (Mo–SiN x ) GMs via optimization of the sputter deposition atmosphere. For Mo–SiN x GMs deposited in a mixed Ar/N 2 environment, x-ray photoemission spectroscopy shows a 40%–60% reduction of interfacial Mo-silicide defects compared to Mo–SiN x GMs sputtered in a pure Ar environment. Electron transport measurements confirm the reduced defect density; the dc conductivity improved (decreased) by 10 4 –10 5 and the activation energy for variable-range hopping increased 10×. Since GMs are disordered materials, the GM nanostructure should, theoretically, support a universal power law (UPL) response; in practice, that response is generally overwhelmed by resistive (defective) transport. Here, the defect-minimized Mo–SiN x GMs display a superlinear UPL response, which we quantify as the ratio of the conductivity at 1 MHz to that at dc, Δσ ω . Remarkably, these GMs display a Δσ ω up to 10 7 , a three-orders-of-magnitude improved response than previously reported for GMs. By enabling high-performance electric transport with a non-noble metal GM, this work represents an important step toward both new fundamental UPL research and scalable, mature GM device applications.
36 MATERIALS SCIENCE↗
Asymptotic scaling laws for the stagnation conditions of Z-pinch implosions
Implosions of magnetically driven annular shells (Z pinches) are studied in the laboratory to produce high-energy-density plasmas. Such plasmas have a wide-range of applications including x-ray generation, controlled thermonuclear fusion, and astrophysics studies. In this work, we theoretically investigate the in-flight dynamics of a magnetically driven, imploding cylindrical shell that stagnates onto itself upon collision on axis. The converging flow of the Z-pinch is analyzed by considering the implosion trajectory in the (A, M) parametric plane, where A is the in-flight aspect ratio and M is the implosion Mach number. For an ideal implosion in the absence of instabilities and in the limit of A ≫ 1, we derive asymptotic scaling laws for hydrodynamic quantities evaluated at stagnation (e.g., density, temperature, and pressure) and for performance metrics (e.g., soft x-ray emission, K-shell x-ray emission, and neutron yield) as functions of target-design parameters.
Ruiz, D. E. [Sandia National Laboratories (SNL-NM)↗
Cosmic quenching and scaling laws for the evolution of supermassive black holes and host galaxies
ABSTRACT Observations suggest a co-evolution of supermassive black holes (SMBHs) and host galaxies. In this paper, we consider the mass and energy flow in a near-equilibrium bulge suffused by gases of varying temperatures. By assuming the rate of energy flow independent of the distance r from the bulge center and the local virial equilibrium for permeated gases on scale r, a key parameter $\varepsilon _b$ was identified that quantifies the mass and energy flow in gases and the efficiency of gas cooling (or the "specific" cooling rate per unit mass), and thus regulates the co-evolution of both SMBHs and hosts. With the help of Illustris simulations and observations, we determined the redshift variation $\varepsilon _b\propto (1+z)^{5/2}$. A higher $\varepsilon _b$ in the early Universe means a higher specific cooling rate that allows rapid evolution of SMBHs and hosts. This simple theory, characterized by a single parameter $\varepsilon _b$, provides the dominant mean cosmic evolution of SMBHs and hosts. All other transient phenomena may only contribute to the dispersion around this mean evolution. Based on this theory and relevant assumptions, scaling laws involving $\varepsilon _b$ were identified for the evolution of SMBHs and hosts. For host galaxies, the mass–size relation $M_b\propto \varepsilon _b^{2/3}r_b^{5/3}G^{-1}$, the dispersion–size relation $\sigma _b^2\propto (\varepsilon _b r_b)^{2/3}\propto (1+z)$, or the mass–dispersion relation $M_b\propto \varepsilon _b^{-1}G^{-1}\sigma _b^5$ were identified, where $r_b\propto (1+z)^{-1}$ is the bulge size. For SMBHs, three evolution phases were found involving an initial rapid growth stage with a rising luminosity $L_B\propto (\varepsilon _b M_{\rm BH})^{4/5}$, a transition stage with a declining $L_B\propto \varepsilon _b^2 M_{\rm BH} \propto (1+z)^5$, and a dormant stage with $L_B\propto (\varepsilon _b M_{\rm BH})^{4/3}$. Our results suggest a rapid initial super-Eddington growth in a short period with a new redshift-dependent luminosity limit $L_X\propto\varepsilon _b^{4/5}M_{\rm BH}^{4/5}G^{-1/5}c$, in contrast to the Eddington limit. Analytical solutions were formulated for the BH mass function $\Phi _{\rm BH}$, active galactic nucleus (AGN) mass function $\Phi _{\rm AGN}$, and duty cycle U that predict $\Phi _L\propto L^{-1/5}$ for the faint-end luminosity function, $\Phi _{\rm AGN}\propto M^{-1/5}$ for small-mass-end AGN mass function $\Phi _L$, and $U\propto M^{-1/5}$ at high redshift.
(galaxies:) quasars: supermassive black holes↗
Test of the Gravitational Force Law on Cosmological Scales Using the Kinematic Sunyaev-Zeldovich Effect
The mean pairwise velocity of massive halos reflects the gravitational force law on cosmic scales. For this work, we combine cosmic microwave background intensity maps from the Atacama Cosmology Telescope and a galaxy catalog from the Sloan Digital Sky Survey to estimate the mean pairwise velocity using the kinematic Sunyaev-Zeldovich (kSZ) effect. On scales from 30 to 230 megaparsecs, we constrain the gravitational acceleration between pairs of halos at separation 𝑟 to be 𝑔 ∝ 1/𝑟 𝑛 with 𝑛 = 2.1 ± 0.3, which is consistent with Newtonian gravity in an expanding spacetime (i.e., the standard Λ CDM model). This constraint shows agreement with an inverse quadratic radial dependence over the large distances separating galaxy halos, as expected in standard cosmology. Upcoming surveys have the potential to rule out 𝑛 = 1 at 10𝜎 significance. Our results establish the kSZ effect as a powerful tool for testing gravity on cosmological scales.
alternative gravity theories↗
Design and Analysis of an Integral MPPT Control Law for Wave Energy Conversion Systems
In this paper, we propose an integral-based maximum power point tracking (MPPT) algorithm for point absorber wave energy conversion (WEC) systems. A permanent magnet synchronous generator (PMSG) is coupled to the point absorber and its drive implements the proposed MPPT control. While the rotating frame of reference of the PMSG implements power control, the slower mechanical frequency of the incident waves are processed with an additional transformation that yields another set of dc dynamics. The computed dc power in the new reference frame, which is focused on slow wave dynamics, is input to the MPPT control law that tunes the emulated resistance of the machine drive to extract peak power from the wave absorber device. We derive a stability condition for the proposed controller and validate our control design on a simulated 10kW system.
wave energy, maximum power point tracking (MPPT), ↗
Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling
Atomistic materials modeling is a critical task with wide-ranging applications, from drug discovery to materials science, where accurate predictions of the target material property can lead to significant advancements in scientific discovery. Graph Neural Networks (GNNs) represent the state-of-the-art approach for modeling atomistic material data thanks to their capacity to capture complex relational structures. While machine learning performance has historically improved with larger models and datasets, GNNs for atomistic materials modeling remain relatively small compared to large language models (LLMs), which leverage billions of parameters and terabyte-scale datasets to achieve remarkable performance in their respective domains. To address this gap, we explore the scaling limits of GNNs for atomistic materials modeling by developing a foundational model with billions of parameters, trained on extensive datasets in terabytescale. Our approach incorporates techniques from LLM libraries to efficiently manage large-scale data and models, enabling both effective training and deployment of these large-scale GNN models. This work addresses three fundamental questions in scaling GNNs: the potential for scaling GNN model architectures, the effect of dataset size on model accuracy, and the applicability of LLM-inspired techniques to GNN architectures. Specifically, the outcomes of this study include (1) insights into the scaling laws for GNNs, highlighting the relationship between model size, dataset volume, and accuracy, (2) a foundational GNN model optimized for atomistic materials modeling, and (3) a GNN codebase enhanced with advanced LLM-based training techniques. Our findings lay the groundwork for large-scale GNNs with billions of parameters and terabyte-scale datasets, establishing a scalable pathway for future advancements in atomistic materials modeling.
Li, Chaojian [ORNL] (ORCID:0000000340309777)↗
Virtual Reality for Shoot/No-Shoot Decision Training in Law Enforcement: A Literature Review and Research Agenda
Virtual reality (VR) can materially improve “shoot / no-shoot” (SNS) training by giving officers realistic, repeatable practice making high-stakes decisions under pressure. Traditional tools—live-fire ranges and video simulators—build basics, but they cannot adapt to each officer in real time or fully mirror the complexity of the field. VR closes that gap by creating immersive scenarios that are safer, more flexible, easier to scale across units, and able to capture objective performance data. SNS decisions are not just about marksmanship; they rely on perception, judgment, memory, and the ability to hold fire when a threat is uncertain. Effective training therefore needs realism, decision complexity, and branching outcomes that reflect the true consequences of choices. These elements strengthen recognition of hostile intent while reducing false positives and building the self-control required in ambiguous situations. VR brings specific advantages: dynamic environments, full-body interaction, and the ability to measure performance with precision—enabling targeted feedback and better transfer of learning to the street. At the same time, responsible deployment must address scenario quality (credible environments and behaviors), lawful decision models, and user wellbeing (appropriate stress levels, comfort, and safety). Sandia’s VIPER Lab is positioned to lead this work. The team combines human-performance science, AI/ML, and VR/AR development with a deep equipment bench (e.g., omnidirectional treadmill, eye-tracking, haptics, multiple HMDs). This ecosystem supports building and validating next-generation SNS training that is immersive, measurable, and trustworthy. Bottom line: Investment in VR-enabled SNS training that blends evidence-based design with careful validation and legal safeguards is expected to pay off in safer, more consistent decision-making and improved community trust, delivered through training that is practical to deploy at scale.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗