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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Coupled Hydrological-Thermal-Biogeochemical Modeling for Predicting Arctic Carbon Emissions (CH4PACE)

The Arctic, with nearly 1,700 billion metric tons of carbon stored in its soils, is experiencing significant warming trends that raise concerns about the potential release of greenhouse gases, particularly methane. This report investigates the conversion of carbon stored in Arctic soils and permafrost into methane and its subsequent atmospheric release over the coming decades. Recent data indicate a rise in global methane concentrations, highlighting the importance of understanding the mechanisms of methane generation under anaerobic conditions prevalent in thawing permafrost. Our study employs a multi-faceted approach that integrates fieldwork, benchtop experiments, and numerical simulations to explore the subsurface hydrological-thermal-biogeochemical systems influencing methane emissions. We focus on the relationship between microbial activity in decomposing organic matter under oxygen-limited conditions and the transport of methane out of these saturated wetland soils. Key hydrological parameters, including permeability, porosity, and thermal conductivity, were measured on soil samples from Fairbanks, Alaska, and used to parameterize PFLOTRAN, a coupled hydrological-thermal-reactive transport simulator. Our model enables prediction of the evolution of the active layer and its impact on methane production and release. Our findings underscore the critical need for a mechanistic understanding of methane dynamics in permafrost environments to improve predictions of methane emissions in Earth systems models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Topological Materials for Functional Optoelectronic Devices

The recent realization of topology as a mathematical concept in condensed matter systems has shattered Landau's widely accepted classification of phases by spontaneous symmetry breaking as he famously said, “a particular symmetry property exists or does not exist.” Topological materials (TMs) such as topological insulators and topological semimetals, are characterized by properties that depend on the topology of the band structure. Such dependence has drastic implications on the optical, electrical, and thermal properties of the material. Fundamental physics of TMs is currently under active research in condensed matter, materials science, and high energy physics. Here, recent advances in exploiting the unique properties of TMs to realize functional optoelectronic devices are surveyed. Current and future applications that are, or may be, enabled by their unique properties are discussed. Although many theoretical ideas have been proposed over the past decade or so on using TMs in optoelectronic applications, the focus will be on experimentally realized devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Active Fluids Form System-Spanning Filamentary Networks

Recent experimental realizations of liquid-liquid phase separation of active liquid crystals have offered an insight into the interaction between phase separation, ubiquitous in soft matter and biology, and chaotic active flows. Here, in this Letter, we use continuum theory to examine phase separation of an active liquid crystal and a passive fluid and report two new results. First, we provide an analytical derivation of the activity-induced suppression of the phase boundary of the coexistence region—a result first reported in simulations and experiments. We show that the shift in the critical point is a result of the balance between self-stirring active flows and phase-separating diffusive fluxes. Second, we show that this same balance is responsible for dramatically changing the morphology of the phase separated state, resulting in the emergence of a new mixed active phase consisting of a dynamical filamentous active network that invades the entire system area, trapping droplets of passive material. This structure exists even for very low volume fractions of active material. Our work provides an important step towards the goal of understanding how to use activity as a new handle for sculpting interfaces.

active nematics↗
DOE OSTI2020

Large-volume centimeter-wave cavities for axion searches

The scan rate of an axion haloscope is proportional to the square of the cavity volume. In this paper, a new class of thin-shell cavities are proposed to search for axionic dark matter. These cavities feature active volume much larger (>20×) than that of a conventional cylindrical haloscope, comparable quality factor Q, and a similar frequency tuning range. Furthermore, full 3D numerical finite-element analyses have been used to show that the TM 010 eigenmodes are singly polarized throughout the volume of the cavity and can facilitate axion-photon conversion in uniform magnetic field produced by a superconducting solenoid. To mitigate spurious mode crowding and volume losses due to localization, a pre-amplification binary summing network will be used for coupling. Because of the favorable frequency-scaling, the new cavities are most suitable for centimeter-wavelength (~ 10–100 GHz), corresponding to the promising post-inflation axion production window. In this frequency range, the tight machining tolerances required for high-Q thin-shell cavities are achievable with standard machining techniques for near-infrared mirrors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Seasonal enhancement of the viral shunt catalyzes a subsurface oxygen maximum in the Sargasso Sea

Subsurface oxygen maxima (SOMs) occur directly beneath the mixed layer of stratified water columns across oligotrophic open ocean basins and have been associated with physical transport processes and localized increases in phytoplankton net primary productivity (NPP). We explore the hypothesis that viral lysis (i.e., the ‘viral shunt’) increases nutrient recycling and enhances NPP, supporting SOM formation in stratified water columns, focusing on a recurring SOM at the Bermuda Atlantic Time Series (BATS) in the Sargasso Sea. Reanalysis of historical BATS data showed enhanced Prochlorococcus and virus-like particle abundances associated with SOMs. Instances of high rates of primary and secondary production observed with oxygen supersaturation further implicate a biological mechanism for SOM formation. Leveraging metatranscriptomes, metaviromes, and polony-based data collected during a Lagrangian cruise (October 2019), we link the viral shunt to SOMs, including evidence of elevated cyanophage abundance and infection of Prochlorococcus, and transcriptomic evidence of increased organic matter uptake (i.e., catabolic activity) by copiotrophic bacteria. Cruise data also showed Prochlorococcus nitrogen metabolism transcripts consistent with increased responsiveness to bacterial remineralization. These findings illustrate the biogeochemical impacts of enhanced viral lysis in marine systems, including the potential role of the viral shunt in facilitating SOM formation in the oligotrophic oceans.

Gilbert, Naomi E. [Univ. of Tennessee, Knoxville, ↗
DOE OSTI2023

Optically controlled single-valley exciton doublet states with tunable internal spin structures and spin magnetization generation

Manipulating quantum states through light–matter interactions has been actively pursued in two-dimensional materials research. Significant progress has been made toward the optical control of the valley degrees of freedom in semiconducting monolayer transition-metal dichalcogenides, based on doubly degenerate excitons from their two distinct valleys in reciprocal space. Here, we introduce a type of optically controllable doubly degenerate exciton states that come from a single valley, dubbed as single-valley exciton doublet (SVXD) states. They are unique in that their constituent holes originate from the same valence band, making possible the direct optical control of the spin structure of the excited constituent electrons. Combining ab initio GW plus Bethe–Salpeter equation ( GW -BSE) calculations and a theoretical analysis method, we demonstrate such SVXD in substrate-supported monolayer bismuthene—which has been successfully grown using molecular beam epitaxy. In each of the two distinct valleys in the Brillouin zone, strong spin–orbit coupling and C 3 v symmetry lead to a pair of degenerate 1s exciton states (the SVXD states) with opposite spin configurations. Any coherent linear combinations of the SVXD in a single valley can be excited by light with a specific polarization, enabling full manipulation of their internal spin configurations. In particular, a controllable net spin magnetization can be generated through light excitation. Our findings open routes to control quantum degrees of freedom, paving the way for applications in spintronics and quantum information science.

2D materials↗
DOE OSTI2022

Cosmological dependence of sterile neutrino dark matter with self-interacting neutrinos

Unexplored interactions of neutrinos could be the key to understanding the nature of the dark matter (DM). In particular, active neutrinos with new self-interactions can produce keV-mass sterile neutrinos that account for the whole of the DM through the Dodelson-Widrow mechanism for a large range of active-sterile mixing values. This production typically occurs before Big-Bang Nucleosynthesis (BBN) in a yet uncharted era of the Universe. We assess how the mixing range for keV-mass sterile neutrino DM is affected by the uncertainty in the early Universe pre-BBN cosmology. This is particularly relevant for identifying the viable parameter space of sterile neutrino searches allowed by all astrophysical limits, as well as for cosmology, since the detection of a sterile neutrino could constitute the first observation of a particle providing information about the pre-BBN epoch. Here, we find that the combined uncertainties in the early Universe cosmology and neutrino interactions significantly expand the allowed parameter space for sterile neutrinos that can constitute the whole of the DM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening ∗

Abstract Interface structures in complex oxides remain an active area of condensed matter physics research, largely enabled by recent advances in scanning transmission electron microscopy (STEM). Yet the nature of the STEM contrast in which the structure is projected along the given direction precludes separation of possible structural models. Here, we utilize deep convolutional neural networks (DCNN) trained on simulated 4D STEM datasets to predict structural descriptors of interfaces. We focus on the widely studied interface between LaAlO 3 and SrTiO 3 , using dynamical diffraction theory and leveraging high performance computing to simulate thousands of possible 4D STEM datasets to train the DCNN to learn properties of the underlying structures on which the simulations are based. We test the DCNN on simulated data and show that it is possible (with >95% accuracy) to identify a physically rough from a chemically diffuse interface and create a DCNN regression model to predict step positions. We quantify the applicability of the model to different thicknesses and the transferability of the approach. The method shown here is general and can be applied for any inverse imaging problem where forward models are present.

42 ENGINEERING↗
DOE OSTI2025

Estimating ionization states and continuum lowering from ab initio path integral Monte Carlo simulations for warm dense hydrogen

Warm dense matter (WDM) is an active field of research, with applications ranging from astrophysics to inertial confinement fusion. Ionization degree and continuum lowering are important quantities to understand how materials behave under these conditions, but can be difficult to diagnose since experimental campaigns are limited and often require model-dependent analysis. This is especially true for hydrogen, which has a comparably low scattering cross section, making high-quality data particularly difficult to obtain. Consequently, building equation of state tables often relies on simulations in combination with untested approximations to extract properties from experiments. Here, we investigate an approach for extracting the ionization potential depression and ionization degree—quantities which are otherwise not directly accessible from the physical model—from first-principles path integral Monte Carlo (PIMC) simulations utilizing a chemical model. In contrast to experimental measurements, where noise and nonequilibrium effects add to the uncertainty of the inferred parameters, PIMC simulations provide a clean signal with well-defined thermodynamic conditions. Comparisons against commonly used models show a qualitative agreement, but we find deviations primarily for the high-density and high-temperature cases. We also demonstrate the decreasing sensitivity of the dynamic structure factor with respect to both ionization and continuum lowering for increasing scattering angles in x-ray Thomson scattering experiments. Our work has important implications for the design of future experiments, but also offers qualitative understanding of structure factors and the imaginary-time correlation function obtained from first-principles quantum Monte Carlo simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Fragment binding to the Nsp3 macrodomain of SARS-CoV-2 identified through crystallographic screening and computational docking

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) macrodomain within the nonstructural protein 3 counteracts host-mediated antiviral adenosine diphosphate–ribosylation signaling. This enzyme is a promising antiviral target because catalytic mutations render viruses nonpathogenic. Here, we report a massive crystallographic screening and computational docking effort, identifying new chemical matter primarily targeting the active site of the macrodomain. Crystallographic screening of 2533 diverse fragments resulted in 214 unique macrodomain-binders. An additional 60 molecules were selected from docking more than 20 million fragments, of which 20 were crystallographically confirmed. X-ray data collection to ultra-high resolution and at physiological temperature enabled assessment of the conformational heterogeneity around the active site. Several fragment hits were confirmed by solution binding using three biophysical techniques (differential scanning fluorimetry, homogeneous time-resolved fluorescence, and isothermal titration calorimetry). The 234 fragment structures explore a wide range of chemotypes and provide starting points for development of potent SARS-CoV-2 macrodomain inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Global distribution, formation and fate of mineral‐associated soil organic matter under a changing climate: A trait‐based perspective

Abstract Soil organic matter (SOM) is the largest actively cycling reservoir of terrestrial carbon (C), and the majority of SOM in Earth's mineral soils (~65%) is mineral‐associated organic matter (MAOM). Thus, the formation and fate of MAOM can exert substantial influence on the global C cycle. To predict future changes to Earth's climate, it is critical to mechanistically understand the processes by which MAOM is formed and decomposed, and to accurately represent this process‐based understanding in biogeochemical and Earth system models. In this review, we use a trait‐based framework to synthesize the interacting roles of plants, soil micro‐organisms, and the mineral matrix in regulating MAOM formation and decomposition. Our proposed framework differentiates between plant and microbial traits that influence total OM inputs to the soil (‘feedstock traits’) versus traits that influence the proportion of OM inputs that are ultimately incorporated into MAOM (‘MAOM formation traits’). We discuss how these feedstock and MAOM formation traits may be altered by warming, altered precipitation and elevated carbon dioxide. At a planetary scale, these feedstock and MAOM formation traits help shape the distribution of MAOM across Earth's biomes, and modulate biome‐specific responses of MAOM to climate change. We leverage a global synthesis of MAOM measurements to provide estimates of the total amount of MAOM‐C globally (~840–1540 Pg C; 34%–51% of total terrestrial organic C), and its distribution across Earth's biomes. We show that MAOM‐C concentration is highest in temperate forests and grasslands, and lowest in shrublands and savannas. Grasslands and croplands have the highest proportion of soil organic carbon (SOC) in the MAOM fraction (i.e. the MAOM‐C:SOC ratio), while boreal forests and tundra have the lowest MAOM‐C:SOC ratio. Drawing on our trait framework, we then review experimental data and posit the effects of climate change on MAOM pools in different biomes. We conclude by discussing how MAOM is integrated into soil C models, and how feedstock and MAOM formation traits may be included in these models. We also summarize the projected fate of MAOM under climate change scenarios (Representative Concentration Pathways 4.5 and 8.5) and discuss key model uncertainties. Read the free Plain Language Summary for this article on the Journal blog.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

mystic : software for autonomous discovery and design under uncertainty

Throughout the diverse range of science and engineering applications, there is a growing desire to develop computational methods that can reliably predict the behavior of complex systems. Specifically, there is a strategic need for tools that can robustly forecast the behavior of complex physical systems, where data may be high-dimensional, noisy, or sparse, and models of the system may be time-dependent or include uncertainty. We use mystic to build tools that leverage statistical learning, physics-informed learning, and active learning in the efficient generation of reliably predictive surrogates for complex physical systems. mystic is a robust, proven, open-source optimization and uncertainty quantification toolkit with over a decade of use in the design and optimization of neutron instrumentation, solar-powered drones, and gasguns, and in iterative tuning of models for Raman spectroscopy and elastoplastic materials strength. Recent developments have focused on automated learning of statistically robust surrogates under uncertainty, with applications in materials in extreme environments, nanostructures, materials simulations and strength models, and the failure of shielding under particle radiation. In 2020, McKerns demonstrated active learning of optimally robust surrogates with respect to new simulated data for molecular dynamics simulations of materials mixing in warm dense matter, and is currently applying active learning to the automated steering of particle accelerator beams and the optimal design and control of quantum optical sensor instrumentation.

42 ENGINEERING↗
DOE OSTI2023

Active Colloids as Models, Materials, and Machines

Active colloids use energy input at the particle level to propel persistent motion and direct dynamic assemblies. We consider three types of colloids animated by chemical reactions, time-varying magnetic fields, and electric currents. For each type, we review the basic propulsion mechanisms at the particle level and discuss their consequences for collective behaviors in particle ensembles. These microscopic systems provide useful experimental models of nonequilibrium many-body physics in which dissipative currents break time-reversal symmetry. Freed from the constraints of thermodynamic equilibrium, active colloids assemble to form materials that move, reconfigure, heal, and adapt. Colloidal machines based on engineered particles and their assemblies provide a basis for mobile robots with increasing levels of autonomy. This review provides a conceptual framework for understanding and applying active colloids to create material systems that mimic the functions of living matter. We highlight opportunities for chemical engineers to contribute to this growing field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Self-generated electrokinetic flows from active-charged boundary patterns

We develop a hydrodynamic description of self-generated electrolyte flow in capillaries whose bounding walls feature nonuniform distributions of charge nonuniform active ionic fluxes. The hydrodynamic velocity arising in such a system has components that are forbidden by symmetry in the absence of charge and fluxes. However, when these two boundary mechanisms are simultaneously present, they can lead to a symmetry broken state where steady flows with both unidirectional and circulatory components emerge. We show that these flow states arise when modulated boundary patterns of charge and fluxes are offset by a flux-charge phase difference, which is associated with the separation between sites of their peak densities on the wall. Mismatch in diffusivity of cationic and anionic species can modify the flow states and becomes an enhancing factor when fluxes of both ion species are being produced together at the same site. We demonstrate that this mechanism can be realized with a microfluidic generator that is powered by enzyme-coated patches that catalyze reactants in the solution to produce fluxes of ions. The local ionic elevation or depletion, which disrupts a nonuniform double layer, promotes self-induced gradients yielding persistent body forces to generate bulk fluid motion. Our work quantifies a boundary-driven mechanism behind self-sustained electrolyte flow in confined environments that exists without any external bulk-imposed fields or gradients. It provides a theoretical framework for understanding the combined effect of active and charged boundaries that are relevant in biological or soft matter systems, and can be utilized in electrofluidic and iontronic applications.

active matter↗
DOE OSTI2024

Primordial black hole sterile neutrinogenesis: sterile neutrino dark matter production independent of couplings

Abstract Sterile neutrinos (ν s s) are well-motivated and actively searched for hypothetical neutral particles that would mix with the Standard Model active neutrinos. They are considered prime warm dark matter (DM) candidates, typically when their mass is in the keV range, although they can also be hot or cold DM components. We discuss in detail the characteristics and phenomenology ofν s s that minimally couple only to active neutrinos and are produced in the evaporation of early Universe primordial black holes (PBHs), a process we called “PBH sterile neutrinogenesis”. Contrary to the previously studiedν s production mechanisms, this novel mechanism does not depend on the active-sterile mixing. The resultingν s s have a distinctive spectrum and are produced with larger energies than in typical scenarios. This characteristic enablesν s s to be WDM in the unusual 0.3 MeV to 0.3 TeV mass range, if PBHs do not matter-dominate the Universe before evaporating. When PBHs matter-dominate before evaporating, the possible coincidence of induced gravitational waves associated with PBH evaporation and astrophysical X-ray observations fromν s decays constitutes a distinct signature of our scenario.

Astronomy & Astrophysics↗
DOE OSTI2020

Solar Neutrino Observations at the Sudbury Neutrino Observatory

The Sudbury Neutrino Observatory (SNO) is a 1000-tonne heavy water Cherenkov detector. Its usage of \dto as target allows the simultaneous measurements of the $\nu_e$ flux from $^8$B decay in the Sun and the total flux of all active neutrino species through the charged-current and the neutral-current interactions on the deuterons. Assuming the standard $^{8}$B shape, the $\nu_e$ component of the $^{8}$B solar neutrino flux is measured to be $\phi_e = 1.76^{+0.05}_{-0.05}{(stat.)}^{+0.09}_{-0.09} {(syst.)} x 10^6 {\rm cm}^{-2} {\rm s}^{-1}$ for a kinetic energy threshold of 5 MeV. The non-\nue component is found to be Φ μτ $\= 3.41^{+0.45}_{-0.45}{(stat.)}^{+0.48}_{-0.45} {(syst.)} x 10^6 {\rm cm}^{-2} {\rm s}^{-1}$. This $5.3\sigma$ difference provides strong evidence for $\nu_{e}$ flavor transformation in the solar neutrino sector. The total active neutrino flux is measured with the neutral-current reaction at a neutrino energy threshold of 2.2 MeV. This flux is determined to be $\phi_{NC} = 5.09^{+0.44}_{-0.43}{(stat.)}^{+0.46}_{-0.43} {(syst.)} x 10^6 {\rm cm}^{-2} {\rm s}^{-1}$, and is consistent with solar model predictions. Assuming an undistorted $^8$B spectrum, the night minus day rate is 14.0$\pm$6.3(stat.)$^{+1.5}_{-1.4}$(sys.)\% of the average rate in the charged-current channel. If the total active neutrino flux is constrained to have no asymmetry, the night-day asymmetry in the $\nu_e$ flux is found to be 7.0$\pm$4.9(stat.)$^{+1.3}_{1.2}$(sys.)\%. A global analysis of all the available solar neutrino data in terms of matter-enhanced oscillations of two active flavors strongly favors the Large Mixing Angle (LMA) solution.

Poon, A. W. P.↗
DOE OSTI2022

Biotropic liquid crystal phase transformations in cellulose-producing bacterial communities

Biological functionality is often enabled by a fascinating variety of physical phenomena that emerge from orientational order of building blocks, a defining property of nematic liquid crystals that is also pervasive in nature. Out-of-equilibrium, “living” analogs of these technological materials are found in biological embodiments ranging from myelin sheath of neurons to extracellular matrices of bacterial biofilms and cuticles of beetles. However, physical underpinnings behind manifestations of orientational order in biological systems often remain unexplored. For example, while nematiclike birefringent domains of biofilms are found in many bacterial systems, the physics behind their formation is rarely known. Here, using cellulose-synthesizing Acetobacter xylinum bacteria, we reveal how biological activity leads to orientational ordering in fluid and gel analogs of these soft matter systems, both in water and on solid agar, with a topological defect found between the domains. Furthermore, the nutrient feeding direction plays a role like that of rubbing of confining surfaces in conventional liquid crystals, turning polydomain organization within the biofilms into a birefringent monocrystal-like order of both the extracellular matrix and the rod-like bacteria within it. We probe evolution of scalar orientational order parameters of cellulose nanofibers and bacteria associated with fluid-gel and isotropic-nematic transformations, showing how highly ordered active nematic fluids and gels evolve with time during biological-activity-driven, disorder-order transformation. In conclusion, with fluid and soft-gel nematics observed in a certain range of biological activity, this mesophase-exhibiting system is dubbed “biotropic,” analogously to thermotropic nematics that exhibit solely orientational order within a temperature range, promising technological and fundamental-science applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Direct matter disassembly via electron beam control: electron-beam-mediated catalytic etching of graphene by nanoparticles

Here, we report electron-beam activated motion of a catalytic nanoparticle along a graphene step edge and associated etching of the edge. The catalytic hydrogenation process was observed to be activated by a combination of elevated temperature and electron beam irradiation. Reduction of beam fluence on the particle was sufficient to stop the process, leading to the ability to switch on and off the etching. Such an approach enables the targeting of individual nanoparticles to induce motion and beam-controlled etching of matter through activated electrocatalytic processes. The applications of electron-beam control as a paradigm for molecular-scale robotics are discussed.

77 NANOSCIENCE AND NANOTECHNOLOGY↗