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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 109 records · Page 6

Widen the resonance at ultra-high energies: novel probes of neutrino self-interactions in the high-mass regime

Neutrino self-interactions beyond the Standard Model are well motivated by the nonzero masses of neutrinos, which are the only known particles guaranteed to have new physics. Meanwhile, cosmic messengers, especially neutrinos, play a central role in probing new physics, as they provide experimental conditions far beyond the reach of laboratories and serve as the link between laboratory fundamental-physics discoveries and their roles in the Universe, where many new physics motivations originate.In this work, we propose a novel probe of neutrino self-interactions through ultrahigh-energy neutrinos scattering off the cosmic neutrino background when the lightest neutrino species remains relativistic today.This allows us to “Widen the Resonance” of such scattering [1].In addition, we also provide a semi-analytic framework for cosmogenic ultrahigh-energy neutrino production, avoiding computationally intensive simulations and yielding results precise enough for beyond-the-standard-model studies.The widened resonance enables future ultrahigh-energy neutrino telescopes,in particular GRAND, to probe mediator masses from MeV to GeV, reaching couplings down to g ∼ 10$^{-3}$ — up to two orders of magnitude beyond current bounds.Our results enhance the discovery potential of neutrino self-interactions in the high-mass regime, potentially offering crucial insights into the connections between the neutrino sector and dark sector.

Machado, Pedro A.N. [Fermilab] (ORCID:000000029118↗

SMART U(1)$$_X$$: standard model with axion, right handed neutrinos, two Higgs doublets and U(1)$$_X$$ gauge symmetry

Abstract To address five fundamental shortcomings of the Standard Model (SM) of particle physics and cosmology, we propose a phenomenologically viable framework based on a $$U(1)_X \times U(1)_{PQ}$$ U ( 1 ) X × U ( 1 ) PQ extension of the SM, that we call “SMART U(1) $$_X$$ X ”. The $$U(1)_X$$ U ( 1 ) X gauge symmetry is a well-known generalization of the $$U(1)_{B-L}$$ U ( 1 ) B - L symmetry and $$U(1)_{PQ}$$ U ( 1 ) PQ is the global Peccei–Quinn (PQ) symmetry. Three right handed neutrinos are added to cancel $$U(1)_X$$ U ( 1 ) X related anomalies, and they play a crucial role in understanding the observed neutrino oscillations and explaining the observed baryon asymmetry in the universe via leptogenesis. Implementation of PQ symmetry helps resolve the strong CP problem and also provides axion as a compelling dark matter (DM) candidate. The $$U(1)_X$$ U ( 1 ) X gauge symmetry enables us to implement the inflection-point inflation scenario with $$H_{inf} \lesssim 2 \times 10^{7}$$ H inf ≲ 2 × 10 7 GeV, where $$H_{inf}$$ H inf is the value of Hubble parameter during inflation. This is crucial to overcome a potential axion domain wall problem as well as the axion isocurvature problem. The SMART U(1) $$_X$$ X framework can be successfully implemented in the presence of SU (5) grand unification, as we briefly show.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Center for Alternate Synchronization and Timing (CAST) PTP Network Monitoring Report

The Oak Ridge National Laboratory Center for Alternative Synchronization and Timing (CAST) performs research, development, testing, and evaluation of alternative terrestrial-based timing and synchronization infrastructure for the US power grid and other critical infrastructures. Alternative timing options reduce reliance on GPS and enhance the overall resilience of critical infrastructures. CAST infrastructure uses Precision Time Protocol (PTP) as the primary conduit for delivery of synchronization packets. CAST deploys PTP over long terrestrial links to synchronize a multitude of remote boundary clocks and downstream power grid components with the authoritative grand master clocks. Network traffic issues can severely degrade PTP accuracy. This report focuses on examining network traffic anomalies and their effects on PTP operation as well as the potential implications to CAST’s high-precision remote synchronization operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Mystery of Baselevel Controls in the Incision History of the Central Colorado Plateau

Erosion can remain active and changing in landscapes long after tectonic drivers have ceased, potentially due to local-geologic controls, climate changes, or geodynamics. We present new fluvial incision-rate histories and terrain analyses of the Colorado River system through the central Colorado Plateau to understand what has caused the variable erosion across this post-orogenic landscape. Results from new cosmogenic and luminescence dating of fluvial terrace and upland gravel deposits in Glen and Meander Canyons establish incision-rate histories that are marked by an Early-Middle Pleistocene erosion hiatus, followed by ~200 m of rapid incision over the last ~350 kyr. Projection of fluvial topography from above knickzones of the Colorado River drainage system roughly agree with the observed magnitude of recent incision and reflect a common baselevel fall from Pliocene river integration through Grand Canyon, which is still propagating through the drainage. A response-time model indicates that baselevel fall from integration likely took 2–4 Myr to reach the central Colorado Plateau and 100s kyr to travel across the study area, potentially accounting for incision rate changes in the fluvial terrace records of Meander and Glen Canyons. The upstream-migrating incision has likely been partitioned into multiple waves across the landscape due to the local geologic controls of lava damming, salt tectonics, and heterogenous bedrock. As baselevel fall from Pliocene Colorado River integration diffuses upstream, it can only account for perhaps a quarter of the total ~2 km of exhumation in the central Colorado Plateau, demanding an unknown driver for significant erosion in the Pliocene.

58 GEOSCIENCES↗

Elucidation of the Active Site for the Oxygen Evolution Reaction on a Single Pt Atom Supported on Indium Tin Oxide

Single-atom catalysts (SACs) have attracted attention for their high catalytic activity and selectivity, but the nature of their active sites under realistic reaction conditions, involving various ligands, is not well understood. In this study, we use Density Functional Theory calculations and grand canonical basin hopping to theoretically investigate the active site for the oxygen evolution reaction (OER) on single Pt atom supported on Indium Tin Oxide, including the influence of the electrochemical potential. We show that the ligands on the Pt atom change from Pt-OH in the absence of electrochemical potential to PtO(OH) 4 in electrochemical conditions. This change of the chemical state of Pt is associated to a decrease of 0.3V for the OER overpotential. This highlights the importance of accurately identifying the nature of the active site under reaction conditions and the impact of adsorbates on the electrocatalytic activity. This theoretical investigation enhances our understanding of SACs for OER.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Skipper CCDs for the search of a daily modulation of Dark Matter signal in the DMSQUARE experiment

The Dark Matter Daily Modulation experiment (DMSQUARE) seeks for dark matter interactions with a Skipper CCD. It is currently running at surface level in Bariloche, Argentina, and will be moved to a shallow underground site at Sierra Grande, Argentina in November 2021. The low threshold achieved by Skipper CCDs allows to search for electron recoil events with an ionization energy down to 1.2 eV. In order to extract a potential dark matter signal from noise at the single electron level, we propose to search for a diurnal modulation of events, resulting from the potential interaction of the dark matter wind with the particles in the Earth. Depending on the model, mass and cross-section, this modulation can be maximum at 40deg of latitude in the Southern Hemisphere, where DMSQUARE is operated. In this article we present the experiment, report preliminary results with a prototype Skipper CCD taking data at surface level and comment on future prospects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Hydro-EKG: In-Stream Streaming-potential (SP) Electrical Monitoring of the Lifeblood of Watersheds during Disturbance

In order to develop improved methods for characterization and monitoring of hyporheic exchange along stream and river corridors, this project evaluated and compared concentration (C) and discharge (Q) correlations between the dam-managed, intermittent Rio Grande River and the perennial East Fork Poplar Creek in Oak Ridge, Tennessee. Additionally, a multimethod geoelectric survey was implemented between January and March 2022 along a 220-meter long reach of the bedrock-lined East Fork Poplar Creek in Oak Ridge, Tennessee to identify locations of surface-water and groundwater exchange in the bedrock-lined streambed and characterize the subsurface flow paths that convey water between the stream and flood plain.

54 ENVIRONMENTAL SCIENCES↗

Predicting Partial Atomic Charges in Metal–Organic Frameworks: An Extension to Ionic MOFs

Molecular simulation is an invaluable tool to predict and understand the usage of metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges, commonly obtained from density functional theory (DFT) calculations, are often required to model the electrostatic interactions between the MOF and adsorbates, especially when the adsorbates have dipole or quadrupole moments, such as water and CO 2 . Machine learning (ML) models have been previously employed to predict partial charges and avoid the computational cost associated with DFT calculations. However, previous ML models suffer from small training data sets, which limit their scope of application. In this work, we introduce two novel machine learning models, PACMOF2-neutral and PACMOF2-ionic, aimed at predicting the density-derived electrostatic and chemical (DDEC6) partial atomic charges for both neutral and ionic MOFs. These models not only yield DFT-level accuracy at a fraction of the computational cost but also demonstrate a remarkable improvement in prediction of adsorption, as validated with grand canonical Monte Carlo simulations. Furthermore, the robustness and fast computational time of the PACMOF2 models, along with their transferability to other porous materials such as covalent organic frameworks and zeolites, underscores their potential in high-throughput screening of MOFs for diverse applications.

36 MATERIALS SCIENCE↗

Predictive coarse-grained (CG) modeling of morphologies in polymer nanocomposites with specific and directional intermolecular interactions (Final Report)

The overarching goal of the proposed work was to develop predictive models for investigating structure and dynamics in soft materials with chemistries that have specific and directional molecular interactions. The motivation behind studying materials with specific and directional interactions lies in the many desirable features these interactions provide when designing novel soft materials. Soft materials with specific and direction interactions (such as hydrogen bonds or H-bonds) can have a) thermally reversible phase behavior with different functions with varying temperature, b) precisely tuned nanostructure with desirable geometries that afford unique physical properties (e.g., color response, mechanical properties) and c) well-mixed/blended morphologies that are useful for variety of applications in energy field (e.g., materials for batteries require use of blended polymers where one domain gives superior mechanical properties and one domain promotes electrical conduction). Notably, biology makes extensive use of specific and directional interactions, in many cases based on H-bonds, to construct materials with precisely defined architectures and properties. Engineered soft materials with precisely tuned nanostructures and improved processiblity through thermoresponsive phase behavior are useful in numerous applications that are relevant to the Department of Energy (DOE) including high efficiency electronic devices, light-weight high-strength composite materials for batteries and fuel cells, and polymer membranes for separations, etc. While past computational studies have been tremendously useful in understanding molecular phenomena and guiding synthesis of new macromolecular soft materials for a wide variety of applications, the inability to capture small scale specific and directional interactions alongside macromolecular length and time scales represented a key limitation of most studies to date. Our work in this project addressed this grand challenge in computational materials chemistry, i.e., ability to model the anisotropic, directional, and specific interactions that govern the behavior of many macromolecular soft matter systems of interest, thus, has greatly expanded the predictive potential of simulations. Specifically the key outcomes were: successful development of new coarse-grained (CG) polymer models to study generic and specific polymer chemistries in which hydrogen-bonding interactions are dominant. These CG models were then used in molecular simulations to study structure and thermodynamics in polymer nanocomposites and blends; some studies were conducted in collaboration with experimentalists. We also published a perspective and a viewpoint which included some of the work we completed in this DOE project; we believe these perspective and viewpoint articles guide other researchers in the soft materials community on how to extend the computational approaches and models we have developed for the purposes of their studies.

36 MATERIALS SCIENCE↗

Methane Remediation using Biocatalysts in Gas-Solid Reactor – Challenges and Prospects

One of the engineering grand challenges of the 21 st century is to develop carbon sequestration methods due to human activities. Carbon dioxide and methane are the two most abundant greenhouse gases with methane having a higher global warming potential (GWP) than carbon dioxide. Methanotrophs are a time of bacteria that consumes methane and can produce different kinds of organic acids. Wild methanotrophs produce a range of products and can be specifically selected and genetically engineered to produce a specific product. Improvement of bioreactor design for a solid-gas mass transfer is necessary for this technology to move forward. Poor solubility of methane requires high energy input for the conversion of methane. This paper reviews some relevant technology in bioreactor design of gas and liquid/solid interfaces and describes the scope of the project here at LLNL and the objectives it seeks to achieve in the geometric design of reactor of methanotroph.

36 MATERIALS SCIENCE↗

Advanced Microstructured BaTiO 3 -Embedded PVDF–HFP/PEO Film for Enhanced Triboelectric Interface in Self-Sufficient Energy Generation and Sensing

The global reliance on fossil fuels and natural gas has largely dominated the energy production field, but due to finite resource depletion and escalating greenhouse gas emissions, the immediate exploration of sustainable energy alternatives to mitigate climate change and ensure resource security has been a major concern. There has been extensive research into other more renewable methods of energy production, such as wind and hydropower. Of these current energy generation types, there are many areas of untapped potential from the mechanical movements generated ambiently not only in the large scale of power generation but also on a smaller scale. The piezoelectric and triboelectric effects are phenomena where these ambient mechanical movements can generate electrical energy. Developing a hybrid system that leverages both mechanical stress and surface charges presents an ideal opportunity to exploit these untapped energy sources. Producing a hybrid PVDF–HFP/PEO film with perovskite BaTiO 3 (BTO) enables ambient power harvesting from both mechanical movement and surface charge. The optimized cell produced a potential of up to 15 V and a current of 200 nA with a 68 kΩ resistor, a substantial increase from a base system with an average of 2.1 V and 40 nA. These hybrid TENGs offer significant potential for energy harvesting in small-scale applications, such as health monitoring devices and indicators in electric circuits.

Ybarra, Rigobert [University of Texas Rio Grande V↗

Machine Learning Interatomic Potentials for Modeling Framework Flexibility and Water Uptake in NbOFFIVE-1-Ni Metal–Organic Framework

Metal–organic frameworks (MOFs), with their distinctive porous structures and tunable chemical properties, have shown immense promise in the separation and storage of gases. Currently, the accurate simulation of their adsorptive properties remains challenging, especially for systems where the molecules fit very tightly into the pores. Traditional simulation methods often approximate the frameworks as rigid and do not account for the framework flexibility seen in materials such as NbOFFIVE-1-Ni. First-principles molecular dynamics (FPMD) simulations offer the desired accuracy in modeling this flexibility but are limited by their extensive computational demands, rendering them impractical for long simulations. Conversely, classical force field-based simulations offer computational efficiency but lack the necessary accuracy. Here, to break this accuracy-efficiency trade-off, we have developed machine learning interatomic potentials trained on energies and forces from FPMD to model the framework flexibility of NbOFFIVE-1-Ni in the presence of water over nanosecond time scales. Furthermore, by integrating MLIP-driven molecular dynamics (MLIP-MD) with grand canonical Monte Carlo (GCMC) simulations, we further incorporated framework flexibility into adsorption predictions, yielding water adsorption isotherms that better align with experimental data compared to those of conventional GCMC simulations. These advances offer new opportunities for the design and optimization of MOFs in gas storage and separation applications.

adsorption↗

Nitrate-To-Ammonia Electroconversion at Neutral pH on Polycrystalline Vanadium Sulfide Derived from Vanadium Disulfide

The electrochemical nitrate reduction reaction (NO3RR) offers a pathway to produce NH3 for fuel and fertilizer from waste NO3-. In this work, a polycrystalline vanadium sulfide (VSx), which is derived from solvothermally grown and annealed VS2, is shown to exhibit excellent NO3RR activity (2.3 +- 0.6 mg.cm-2 geo..h-1 @ -0.92 VRHE) and Faradaic efficiency to NH4+ (69 +- 6% at -0.69 VRHE) in buffered neutral pH electrolyte containing 0.1 M NO3-. A variety of characterization techniques are leveraged to support the VSx assignment, including X-ray photoelectron spectroscopy, near-edge X-ray absorption fine structure spectroscopy, selected area electron diffraction, and X-ray diffraction measurements. The VS2 annealing step reduces the oxide character and generates VSx, which, based on the improved NO3RR activity, results in the creation of active sites for NO3- binding. To help shed light on NO3RR on VSx, VS2 is used as a model system, and a grand-canonical density functional theory (GC-DFT) investigation of VS2 shows strong evidence that S vacancies are active sites for NO3RR, where NO3- outcompetes H+ for adsorption at the S-vacancy sites. Moreover, GC-DFT results highlight a thermodynamically favorable reaction to generate NH4+ in an aqueous electrolyte at relevant cathodic potentials. As an annealed material, VSx may contain undersaturated V sites, which show an electronic structure similar to the theoretically calculated S-vacancy site of VS2, and these sites may contribute to the observed increase in NO3RR activity and selectivity for NH4+ on VSx versus unannealed VS2. Finally, kinetic isotope effect measurements suggest that the kinetic rate-limiting step of the NO3RR on VSx is not proton-coupled, indicating it may be the first electron transfer to adsorbed NO3*.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular‐Level Insight into the Chlorofluorocarbons Adsorption by Defective Covalent Organic Polymers

Abstract Halocarbons have important industrial applications, but because of their contribution to global warming and the fact that they can cause ozone depletion, they are considered highly toxic. Hence, the techniques that can capture and recover the used halocarbons with energy‐efficient methods have been recently received greater attention. In this contribution, we report the capture of dichlorodifluoromethane (R12), which has high global warming and ozone depletion potential, using covalent organic polymers (COPs). The defect‐engineered COPs were synthesized and demonstrated outstanding sorption capacities, ~226 wt % of R12 combined with linear‐shaped adsorption isotherms. We further identified the plausible microscopic adsorption mechanism of the investigated COPs via grand canonical Monte Carlo simulations applied to non‐defective and a collection of atomistic models of the defective COPs. The modeling work suggests that significant R12 adsorption performance is attributed to a gradual increment of porosities due to isolated/interconnected micro‐/meso‐pore channels and the change of the long‐range ordering of both COPs. The successive hierarchical‐pore‐filling mechanism promotes R12 molecular adsorption via moderate van der Waals adsorbate‐adsorbent interactions in the micropores of both COPs at low pressure followed by adsorbate‐adsorbate interactions in the extra‐voids created at moderate to high pressure ranges. This continuous pore‐filling mechanism makes defective COPs as promising sorbents for halocarbon adsorption.

Shen, Jian↗

Implementation of Genetic Algorithms to Optimize Metal–Organic Frameworks for CO 2 Capture

Metal-organic frameworks (MOFs) are promising materials for CO 2 capture with the potential to use less energy than current industrial CO 2 capture methods. MOFs are highly versatile sorbents, and there is an almost unlimited number of MOFs that could be synthesized. In this work, we used a genetic algorithm (GA) and grand canonical Monte Carlo (GCMC) simulations to efficiently search for high-performing MOFs for CO 2 capture. We analyzed the effects of important GA parameters, including the mutation probability, the number of MOFs per generation and the number of GA generations, on the GA performance. Here, we performed GCMC simulations on-the-fly during the GA procedure to determine the performance of proposed MOFs and optimized their structures using multiple objective functions across different topologies. The GA was able to determine top-performing MOFs balancing CO 2 selectivity versus working capacity and reduced the cost of molecular simulations by a factor of 25 versus brute-force screening of an entire database of structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Copper Tantalate by a Sodium-Driven Flux-Mediated Synthesis for Photoelectrochemical CO 2 Reduction

Copper-tantalate, Cu 2 Ta 4 O 11 (CTO), shows significant promise as an efficient photocathode for multi-carbon compounds (C 2+ ) production through photoelectrochemical (PEC) CO 2 reduction, owing to its suitable energy bands and catalytic surface. However, synthesizing CTO poses a significant challenge due to its metastable nature and thermal instability. In this study, this challenge is addressed by employing a flux-mediated synthesis technique using a sodium-based flux to create sodium-doped CTO (Na-CTO) thin films, providing enhanced nucleation and stabilization for the CTO phase. To evaluate the PEC performance and catalytic properties of the films, copper(II) oxide (CuO) at the Na-CTO surface is selectively etched. The etched Na-CTO shows a lower dark current, with decreased contribution from photocorrosion, unlike the non-etched Na-CTO which has remaining CuO on the surface. Furthermore, Na-CTO exhibits 7.3-fold ethylene selectivity over hydrogen, thus highlighting its promising potential as a photocathode for C 2+ production through PEC CO 2 reduction.

copper tantalate↗

Atomistic learning in the electronically grand-canonical ensemble

Abstract A strategy is presented for the machine-learning emulation of electronic structure calculations carried out in the electronically grand-canonical ensemble. The approach relies upon a dual-learning scheme, where both the system charge and the system energy are predicted for each image. The scheme is shown to be capable of emulating basic electrochemical reactions at a range of potentials, and coupling it with a bootstrap-ensemble approach gives reasonable estimates of the prediction uncertainty. The method is also demonstrated to accelerate saddle-point searches, and to extrapolate to systems with one to five water layers. We anticipate that this method will allow for larger length- and time-scale simulations necessary for electrochemical simulations.

36 MATERIALS SCIENCE↗