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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Grain Boundary-Limited Thermal Transport in Suspended Thin Graphite across an Unexplored Thickness Regime

Here, we present systematic thermal conductivity (κ) measurements of suspended thin graphite ribbons, 234–527 nm thick, using a four-probe 3ω method. Unlike recent reports of phonon hydrodynamics and exceptionally high κ in micrometer-thick graphite ( Science, 2020), we observe significantly lower κ and no signatures of collective phonon flow in this intermediate thickness regime. Instead, our measured κ lies between few-layer graphene and bulk graphite. These results agree with a first-principles-informed Peierls–Boltzmann transport model with spatially resolved Monte Carlo sampling. Additionally, the temperature for the peak κ shifts lower with increasing thickness, due to the interplay of phonon-boundary and phonon-isotope scattering. Incorporating grain boundary scattering into simulations is necessary to replicate the experimental trends. These findings delineate the boundary between ballistic, hydrodynamic, and diffusive transport regimes in graphite and underscore the dominant role of disorder and geometry in phonon transport in quasi-two-dimensional materials, offering insights for nanoscale thermal management.

Boltzmann transport model↗
DOE OSTI2021

Simulation of hardened cement degradation and estimation of uncertainty in predicted failure times with peridynamics

Modeling the degradation of cement-based infrastructure due to aqueous environmental conditions continues to be a challenge. In order to develop a capability to predict concrete infrastructure failure due to chemical degradation, here we created a chemomechanical model of the effects of long-term water exposure on cement paste. The model couples the mechanical static equilibrium balance with reactive–diffusive transport and incorporates fracture and failure via peridynamics (a meshless simulation method). The model includes fundamental aspects of degradation of ordinary Portland cement (OPC) paste, including the observed softening, reduced toughness, and shrinkage of the cement paste, and increased reactivity and transport with water induced degradation. This version of the model focuses on the first stage of cement paste decalcification, the dissolution of portlandite. Given unknowns in the cement paste degradation process and the cost of uncertainty quantification (UQ), we adopt a minimally complex model in two dimensions (2D) in order to perform sensitivity analysis and UQ. We calibrate the model to existing experimental data using simulations of common tests such as flexure, compression and diffusion. Then we calculate the global sensitivity and uncertainty of predicted failure times based on variation of eleven unique and fundamental material properties. We observed particularly strong sensitivities to the diffusion coefficient, the reaction rate, and the shrinkage with degradation. Also, the predicted time of first fracture is highly correlated with the time to total failure in compression, which implies fracture can indicate impending degradation induced failure; however, the distributions of the two events overlap so the lead time may be minimal. Extension of the model to include the multiple reactions that describe complete degradation, viscous relaxation, post-peak load mechanisms, and to three dimensions to explore the interactions of complex fracture patterns evoked by more realistic geometry is straightforward and ongoing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Measurement of Helium and Xenon Knudsen permeability in graphite IG-11

Here, understanding the flow and diffusion (transport) of gases through nuclear graphite is of interest in both the prismatic and pebble bed high-temperature gas reactors (HTGRs), for normal operation and under accident conditions, for example, as related to graphite oxidation. Both the laminar and turbulent gaseous transport are of interest. It has also been noted that nuclear graphite can have pore sizes that can possibly lead to non-continuum transport, as the pore size can be comparable to the gaseous mean free path. We report measurements and analyzes of experiments performed with IG-11 graphite in the pressure range of 10 Pa to 14,700 Pa, 293 K, using Helium, and research grade xenon (99.999%), respectively. These values are in fair agreement with those reported for different graphites and gases by other investigators, but are also higher by six orders of magnitude than those reported for Kr permeability in a developmental very low permeability graphite-HXT-90. Our measured ratio of the Helium and Xenon permeabilities is about 4, different from $\sqrt{\frac{m_{Xe}}{m_{He}}}$ ≈ 5.72 that corresponds to diffuse reflection at the graphite surface for both gases. Simple analysis indicates that the two gases have slightly different accommodation coefficients (about 25%) with the graphite surface. However, there could also be other reasons, such as experimental uncertainties or the need for a more detailed analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Self-seeded growth of very large open-structured zeolite nanosheet assemblies with extraordinary micropore accessibility

Zeolite nanosheets (ZNs) offer improved micropore accessibilities and transport properties for enhanced molecular catalysis and separations. However, practical application of the ZN materials is hampered by the lack of efficient synthesis methods. Here, in this work, a ZN self-seeded method is demonstrated for single-step reproduction of flower-like assemblies of very large MFI ZN plates. The ZN plates are ~60 nm-thick stacks of 4-nm-thick single-crystal sheets. The ZN flower growth involves terrace nucleation on the seed surfaces and subsequent ZN epitaxial growth in [010] orientation directed by a diquaternary agent. The open architecture of the assemblies prevented collapse and agglomeration of ZNs during thermal activation that effectively preserved the interconnected intra-sheet and inter-sheet micropore system. Thus, the ZN assemblies exhibited markedly enhanced molecular adsorption capacity and transport diffusivity for the probing xylene molecules as compared to the conventional crystals. The ZN assembly and its harvestable very large-sized ZNs have the potential for developing high-performance ZN adsorbents, catalysts, and molecular-sieve membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

NO formation by N 2 /O 2 plasma catalysis: The impact of surface reactions, gas-phase reactions, and mass transport

Pathways and timescales relevant to facilitate plasma-assisted N 2 -O 2 reactions are assessed by measuring the consumption of plasma-derived N and the formation of NO in the gas phase and over Ag catalytic surfaces. These measurements are enabled by a setup that enables N 2 activation in an atmospheric pressure RF plasma jet, enables O 2 addition in the plasma afterglow, facilitates reactions over an Ag wire catalyst, and allows species density quantification by molecular beam mass spectrometry. Gas-phase reactions consume N but do not form NO with high selectivity. The presence of the non-porous Ag wire catalyst increases the rate of N conversion to NO, though mass transfer processes, not surface reactions, dictate the rate of N consumption. When O 2 concentrations and the ratio of the surface area of the catalyst to the void volume of the reactor are high (3–5 mol% O 2 , 10900 m –1 ), N conversion to NO reaches 100 % selectivity. When both N 2 and O 2 are fed through the plasma jet, gas-phase NO production increases 10×, although plasma and gas-phase processes do not exclusively produce NO. Above a threshold NO density, N cannot diffuse to the catalyst surface faster than it is consumed in the gas phase by reactions with NO. Furthermore, the use of heterogeneous catalysts to enhance plasma-driven N x O y formation and control N x O y product selectivity is limited to cases where diffusive transport of N from the gas phase to the catalyst surface is faster than consumption of N from gas-phase reactions with NO.

Engineering↗
DOE OSTI2022

Geochemical Modeling of Celestite (SrSO 4 ) Precipitation and Reactive Transport in Shales

Celestite (SrSO 4 ) precipitation is a prevalent example of secondary sulfate mineral scaling issues in hydraulic fracturing systems, particularly in basins where large concentrations of naturally occurring strontium are present. Herein, we present a validated and flexible geochemical model capable of predicting celestite formation under such unconventional environments. Simulations were built using CrunchFlow and guided by experimental data derived from batch reactors. These data allowed the constraint of key kinetic and thermodynamic parameters for celestite precipitation under relevant synthetic hydraulic fracturing fluid conditions. Effects of ionic strength, saturation index, and the presence of additives were considered in the combined experimental and modeling construction. This geochemical model was then expanded into a more complex system where interactions between hydraulic fracturing fluids and shale rocks were allowed to occur subject to diffusive transport. We find that the carbonate content of a given shale and the presence of persulfate breaker in the system strongly impact the location and extent of celestite formation. The results of this study provide a novel multicomponent reactive transport model that may be used to guide future experimental design in the pursuit of celestite and other sulfate mineral scale mitigation under extreme conditions typical of hydraulic fracturing in shale formations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Design considerations for gallium arsenide pulse compression photoconductive switch

In this paper, we present the physics and design-space exploration of a novel pulse compression photoconductive switch (PCPS) using semi-insulating gallium arsenide (GaAs) operating in the negative differential mobility (NDM) regime of electron transport. We systematically quantify the relationship between the PCPS performance and various design options, including contact separation, laser energy and placement, and trap dynamics. Specifically, we report the full-width at half-maximum and the peak output current generated by the PCPS as a function of applied electrical and optical bias. We discuss the optimal spacing between the electrodes and the distance of the laser spot to the anode to achieve higher electron confinement and superior radio-frequency (RF) metrics. Reducing the laser energy is important to prevent the appearance of secondary peaks due to diffusive transport, but there exists a trade-off between the bandwidth and the maximum current of the PCPS. We also compare the PCPS response with and without trap dynamics and find that the electrostatic screening from the trap-induced space charge is time-independent when the trapping time constant is set larger than the recombination lifetime. Overall, trap dynamics are detrimental to performance, unless the compensation doping scheme to achieve semi-insulating GaAs is carefully selected. Results presented in this paper can be used by experimentalists to fine-tune the PCPS design parameters to meet the specifications of various RF applications. Moreover, our results will provide a strong theoretical basis to the measurements of PCPS devices using GaAs and other NDM materials under investigation.

42 ENGINEERING↗
DOE OSTI2022

A model of spatio-temporal regulation within biomaterials using DNA reaction–diffusion waveguides

In multi-cellular organisms, cells and tissues coordinate biochemical signal propagation across length scales spanning micrometres to metres. Designing synthetic materials with similar capacities for coordinated signal propagation could allow these systems to adaptively regulate themselves across space and over time. Here, we combine ideas from cell signalling and electronic circuitry to propose a biochemical waveguide that transmits information in the form of a concentration of a DNA species on a directed path. The waveguide could be seamlessly integrated into a soft material because there is virtually no difference between the chemical or physical properties of the waveguide and the material it is embedded within. We propose the design of DNA strand displacement reactions to construct the system and, using reaction–diffusion models, identify kinetic and diffusive parameters that enable super-diffusive transport of DNA species via autocatalysis. Finally, to support experimental waveguide implementation, we propose a sink reaction and spatially inhomogeneous DNA concentrations that could mitigate the spurious amplification of an autocatalyst within the waveguide, allowing for controlled waveguide triggering. Chemical waveguides could facilitate the design of synthetic biomaterials with distributed sensing machinery integrated throughout their structure and enable coordinated self-regulating programmes triggered by changing environmental conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A Computational Information Criterion for Particle-Tracking with Sparse or Noisy Data

Traditional probabilistic methods for the simulation of advection-diffusion equations (ADEs) often overlook the entropic contribution of the discretization, e.g., the number of particles, within associated numerical methods. Many times, the gain in accuracy of a highly discretized numerical model is outweighed by its associated computational costs or the noise within the data. Herein, we address the question of how many particles are needed in a simulation to best approximate and estimate parameters in one-dimensional advective-diffusive transport. To do so, we use the well-known Akaike Information Criterion (AIC) and a recently-developed correction called the Computational Information Criterion (COMIC) to guide the model selection process. Random-walk and mass-transfer particle tracking methods are employed to solve the model equations at various levels of discretization. Numerical results demonstrate that the COMIC provides an optimal number of particles that can describe a more efficient model in terms of parameter estimation and model prediction compared to the model selected by the AIC even when the data is sparse or noisy, the sampling volume is not uniform throughout the physical domain, or the error distribution of the data is non-IID Gaussian.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Loss and Isotopic Fractionation of Alkali Elements during Diffusion-Limited Evaporation from Molten Silicate: Theory and Experiments

Moderately volatile elements (MVEs) are variably depleted in planetary bodies, reflecting the imprints of nebular and planetary processes. Among MVEs, Na, K, and Rb are excellent tracers for unraveling the history of MVE depletion in planetary bodies because they have similar geochemical behaviors but can be chemically fractionated by evaporation and condensation processes. Furthermore, K and Rb are amenable to high-precision isotopic analyses, which can help constrain the conditions of evaporation and condensation. To quantitatively understand why Na, K, and Rb are depleted in planetary bodies, we have carried out vacuum evaporation experiments from basaltic melt at 1200 and 1400 °C to study their evaporation kinetics and isotopic fractionations. We chose this composition because it is relevant to evaporation from small differentiated planetesimals. The Rb isotopic compositions of the evaporation residues were measured by multicollector inductively coupled plasma mass spectrometry (MC-ICPMS), and the K isotopic compositions were measured along profiles across the residues by secondary ion mass spectrometry (SIMS). In the 1400 °C run products, we found that the concentrations of both K and Rb in the run products decreased from core to rim, which was accompanied by a heavy K isotope enrichment near the surface. This indicates that, in this run, evaporation was limited by diffusion. To use those data quantitatively, we derive analytical equations that describe the evaporation rate and isotopic fractionation associated with diffusion-limited evaporation from a sphere, slab, and cylinder in transient and quasi-steady state regimes. This model is used to tease out the roles that diffusive transport in the melt and evaporation at the melt/gas interface play in setting the elemental depletion and isotopic composition of the residue. Under our experimental conditions, volatility decreases in the order of Na, Rb, and K. Using our experimental results in a thermodynamic model, we have estimated the product γΓ of activity coefficients × evaporation coefficients of Na, Rb, and K. The measured isotopic compositions of the residues are well explained using Rayleigh distillations, whereby the relative volatilities of K and Rb isotopes are given by the square root of their masses. We use our results and previously published data to predict how K and Rb could have been lost as a function of temperature, melt composition, oxygen fugacity, and saturation degree relevant to Vesta’s building blocks. We find that the K and Rb depletions, K/Rb elemental fractionation, and δ 41 K and δ 87 Rb isotopic fractionations of Vesta (as sampled by howardite-eucrite-diogenite (HED) meteorites) are best explained by evaporation of submillimeter size objects for 0.1-10 years at moderate temperatures (~1050 °C) in a medium ~98.8% saturated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Two–Photon Printing of Shape–Memory Microstructures and Metasurfaces via Radical–Mediated Thiol–Vinyl Hydrothiolation

Shape-memory resists capable of high-resolution curing into arbitrarily designed structures are increasingly demanded for soft robotics, optical sensors, microscale manufacturing, and biomedicine. Amorphous, shape-memory thiol-vinyl networks were printed using two-photon polymerization (2PP) curing of a simple resin formulated with commercially available reagents. The ability to print high-resolution feature sizes down to 200 nm is attributed to the use of radicalmediated, thiol-vinyl step-growth polymerization that quickly crosslinks the resin, limiting diffusive transport. The thermomechanical behavior of the 2PP-cured material analyzed in compression, tension and three-point bending is similar to the behavior of the UV-polymerized samples. To demonstrate the ability to design, field, and test 4D responsive microstructures, an array of nine springs with coil diameters of 330 μm was printed. Following compressive shapefixing, printed arrays can release 11 μJ of stored elastic strain energy when reheated. Further, a new concept of dichroic-memory of a metamaterial device is demonstrated by printing a twisted woodpile structure with circular dichroism as characterized by Mueller Matrix ellipsometry. Furthermore, our results demonstrate how combining high-resolution 2PP curing with stimuli-responsive molecular architectures can further the engineering of responsive microstructures and metamaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

On the Impact of Mechanics on Electrochemistry of Lithium-Ion Battery Anodes

Abstract Models exploring electrochemistry-mechanics coupling in liquid electrolyte lithium-ion battery anodes have traditionally incorporated stress impact on thermodynamics, bulk diffusive transport, and fracture, while stress-kinetics coupling is more explored in the context of all solid-state batteries. Here, we showcase the existence of strong link between active particle surface pressure and reaction kinetics affecting performance even in liquid electrolyte systems. Traction-free and immobile particle surface mechanical boundary conditions are used to delineate the varying pressure magnitudes in graphite host during cycling. Both tensile and compressive stresses are generated in traction-free case, while a fixed surface subjects the entire particle to a compression state. Pressure magnitudes are nearly two to three orders of magnitude higher for the latter resulting in significant depression of open circuit potential and improvement of exchange current densities compared to stress-free state. The results demonstrate the need for incorporating stress-kinetics linkage in models and provide a rationale for putting battery electrodes under compression to improve kinetics.

25 ENERGY STORAGE↗
DOE OSTI2024

The Method of Finite Averages: A rigorous upscaling methodology for heterogeneous porous media

Rigorous upscaling techniques offer accurate and computationally-efficient strategies for modeling the average behaviors of multi-physical, multiscale phenomena in geological porous media. However, such techniques often rely on a variety of methodological assumptions that prohibit their rigorous application to practical systems (e.g., systems involving heterogeneous porous media, system-scale boundary conditions, and fine-scale dynamics that are not diffusion-dominant). In this work, we aim to formulate an upscaling methodology with few methodological assumptions to provide high levels of model generality and foster the utilization of rigorously-derived upscaled models in practice. In particular, we introduce the Method of Finite Averages (MoFA), a novel upscaling methodology for rigorously modeling heterogeneous porous media and system-scale boundary conditions. We then detail MoFA’s implementation for the advective–diffusive transport of a single species and compare the methodology with classic numerical techniques, as well as other rigorous upscaling techniques, to highlight MoFA’s unique combination of rigor and generality. We then validate the derived model while demonstrating its benefits in three numerical experiments. The results suggest that (1.) the applicability and a priori error guarantees of MoFA models do not directly depend on system geometry, (2.) a model’s applicability and error guarantees can be can arbitrarily expanded and reduced, respectively, with further computational expense, and (3.) downscaling with MoFA provides an efficient strategy for generating accurate pore-scale solutions from upscaled results. Ultimately, the results evidence that upscaled models can be rigorously derived for heterogeneous porous media systems and resolved in a fraction of the time it takes to perform the equivalent pore-scale simulations.

58 GEOSCIENCES↗
DOE OSTI2023

Machine learning-based ethylene and carbon monoxide estimation, real-time optimization, and multivariable feedback control of an experimental electrochemical reactor

Electrochemical reduction of CO 2 gas is a novel CO 2 utilization technique that has the potential to mitigate the global climate crisis caused by anthropogenic CO 2 emissions, and enable the large-scale storage of energy generated from renewable sources in the form of carbon-based chemicals and fuels. However, due to the complexity of the electrochemical reactions, the explicit first-principles models for CO2 reduction are not available yet, and there has been a limited effort to develop process modeling, optimization and control of CO 2 electrochemical reactors. To this end, a rotating cylinder electrode (RCE) reactor has been constructed at UCLA to understand the mass transfer and reaction kinetics effects separately on the productivity. In the RCE reactor, the applied potential strongly influences the reaction energetics and the electrode rotation speed affects the hydrodynamic boundary layer and modifies the film mass transfer coefficient, which involves convective and diffusive transport. Further, the present work aims to develop a multi-input multi-output (MIMO) control scheme for the RCE reactor that integrates techniques from artificial and recurrent neural network modeling, nonlinear optimization, and process controller design. Specifically, production rates of two products from the experimental reactor, ethylene and carbon monoxide, are controlled by manipulating two inputs, applied potential and catalyst rotation speed. Process dynamics and controllability are analyzed, a feedback control strategy is designed and the controllers are tuned accordingly. The experimental electrochemical cell is employed to gather data for process modeling and implement the multivariable control system. Finally, the experimental results are presented which demonstrate excellent closed-loop performance by the control system and regulation of the outputs at three different set-points including an economically-optimal set-point.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Characterization of mechanical discontinuities based on data-driven classification of compressional-wave travel times

Wave propagation and diffusive transport phenomena are influenced by the mechanical discontinuities in material. Here this study shows that certain bulk properties of the network of low-velocity mechanical discontinuities (e.g. air-filled cracks) in a material can be characterized by processing compressional-wave travel times using traditional data-driven classification techniques. To that end, we perform three tasks in chronological order: (1) use the discrete fracture network (DFN) method to create two-dimensional (2D) numerical models of crack-bearing material embedded with various types of low-velocity mechanical discontinuities, (2) use the fast marching method (FMM) to simulate the propagation of the wave/diffusion front from a single source through the 2D crack-bearing material to multiple receivers placed on the boundary of the material, and (3) train 9 data-driven classifiers to characterize the crack-bearing materials (i.e. bulk properties of the network of mechanical discontinuities in the crack-bearing material) by learning from the simulations of travel times detected by multiple receivers placed around the crack-bearing material. The classifiers identified the orientation, spatial distribution, and dispersion of the low-velocity mechanical discontinuities. Voting classifier performs the best among the 9 classifiers. For the characterization of bulk dispersion and distribution of discontinuities, the sensors located on the adjacent boundaries are more important; whereas for the characterization of bulk orientation of discontinuities, the sensors located on the opposite side are more important.

42 ENGINEERING↗
DOE OSTI2026

Ionic Liquid-Enhanced Interfaces to Boost Reactive C O2 Capture

The addition of ionic liquids (ILs) to a mixture containing a molecular solvent and other ionic species can induce the heterogeneous redistribution of cations and anions at the gas–liquid interface. This nonuniform redistribution of cations and anions driven by the differences in the solvophilicity of ions can improve the thermophysical and interfacial properties of such mixtures, creating a local chemical environment that is conducive to some reactions. In this work, ILs are added to a mixture of potassium hydroxide (KOH) and ethylene glycol (EG), used as a reactive absorbent and electrolyte in the migration-assisted moisture-gradient (MAMG) process for CO 2 capture. Molecular dynamics (MD) simulations are employed to probe into the effects of complex ion–ion and ion–solvent interactions and to examine the chemical composition at the gas–liquid interface. A total of 12 systems are investigated using molecular simulations to identify trends in the performance of IL additives based on the choice of cation, anion, and IL concentration. The cation effects are studied using IL additives based on 1-ethyl-3-methylimidazolium ([EMIM] + ) and 1-butyl-3-methylimidazolium ([BMIM] + ), while the impact of anions is examined using additives based on dicyanamide [DCA] − , triflate [TfO] − , bistriflimide [NTf 2 ] − , and hexafluorophosphate [PF 6 ] − anions, respectively. The influence of the IL concentration is also evaluated at molar concentrations between 1% and 4%. The simulation results indicate that the use of IL additives can affect the physical CO 2 solubility, surface tension, and the localization of CO 2 around the [OH] − ions at the gas–liquid interface. It is also evident that the choice of cations, anions, and IL concentration determines the extent to which the IL additives impact the local physicochemical properties. Physical dissolution, diffusive transport, and interaction with [OH] − are critical intermediate steps toward reactive CO 2 capture using a liquid absorbent. Hence, the improvement in one or more of these properties, aided by IL additives, is expected to improve the overall CO 2 capture performance. Experiments reaffirmed the impact of IL additives on CO 2 capture performance and the sensitivity to the choice of the cation, anion, and concentration of the IL additive.

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

Scalable Bottom-Up Synthesis of Nanoporous Hexagonal Boron Nitride ( h -BN) for Large-Area Atomically Thin Ceramic Membranes

Nanopores embedded within monolayer hexagonal boron nitride (h-BN) offer possibilities of creating atomically thin ceramic membranes with unique combinations of high permeance (atomic thinness), high selectivity (via molecular sieving), increased thermal stability, and superior chemical resistance. However, fabricating size-selective nanopores in monolayer h-BN via scalable top-down processes remains nontrivial due to its chemical inertness, and characterizing nanopore size distribution over a large area remains extremely challenging. Here, we demonstrate a facile and scalable approach of exploiting the chemical vapor deposition (CVD) process temperature to enable direct incorporation of subnanometer/nanoscale pores into the monolayer h-BN lattice, in combination with manufacturing compatible polymer casting to fabricate centimeter-scale nanoporous atomically thin ceramic membranes. We leverage diffusive transport of analytes including size-selective Ficoll sieving to characterize subnanometer-scale and nanoscale defects that manifest as pores in centimeter-scale h-BN membranes, overcoming previous limitations in large-area characterization of nanoscale defects in h-BN. Our approach opens a new frontier to advance atomically thin membranes to 2D ceramic materials, such as h-BN via facile and direct formation of nanopores, for size-selective separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Medium Energy Electron Flux in Earth's Outer Radiation Belt (MERLIN): A Machine Learning Model

The radiation belts of the Earth, filled with energetic electrons, comprise complex and dynamic systems that pose a significant threat to satellite operation. While various models of electron flux both for low and relativistic energies have been developed, the behavior of medium energy (120–600 keV) electrons, especially in the MEO region, remains poorly quantified. At these energies, electrons are driven by both convective and diffusive transport, and their prediction usually requires sophisticated 4D modeling codes. In this paper, we present an alternative approach using the Light Gradient Boosting (LightGBM) machine learning algorithm. The Medium Energy electRon fLux In Earth's outer radiatioN belt (MERLIN) model takes as input the satellite position, a combination of geomagnetic indices and solar wind parameters including the time history of velocity, and does not use persistence. MERLIN is trained on >15 years of the GPS electron flux data and tested on more than 1.5 years of measurements. Tenfold cross validation yields that the model predicts the MEO radiation environment well, both in terms of dynamics and amplitudes o f flux. Evaluation on the test set shows high correlation between the predicted and observed electron flux (0.8) and low values of absolute error. The MERLIN model can have wide space weather applications, providing information for the scientific community in the form of radiation belts reconstructions, as well as industry for satellite mission design, nowcast of the MEO environment, and surface charging analysis.

79 ASTRONOMY AND ASTROPHYSICS↗