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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Point Defects Control Guest Molecule Diffusion in the 1D Pores of Zn(tbip)

Molecular diffusion plays a critical role in metal-organic frameworks (MOFs) within the application of kinetic chemical separations. We carefully study in this work the unexpected role of point defects for short-chain alkanes diffusing in Zn(tbip), an MOF with rigid one-dimensional (1D) channels. Inside a defect-free Zn(tbip), guest molecules are expected to follow single-file diffusion along 1D channels. It has been found previously by Heinke et al. that these parallel 1D channels are connected for molecular diffusion. Our density functional theory (DFT) calculations suggest that linker vacancy defects could arise under experimentally relevant conditions by removing a pair of linkers. Further climbing-image nudged elastic band (cNEB) DFT calculations indicate that hopping of short-chain alkanes between adjacent 1D channels over defect windows can occur at moderate temperatures. In addition to providing insights into connected adjacent 1D channels in Zn(tbip), Heinke et al. also inferred that most 1D pores are blocked from a microkinetic model. Additionally, we explored the influence of hydrolyzed linker created by the formation of linker removal inside 1D pores. Our DFT calculations show that the linkers can effectively block the pores and the linker diffusion in 1D channels is slow. Our results, for the first time, offer a mechanistic explanation of the unexpected molecular diffusion behavior in this MOF with 1D channels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Probing the influence of dielectric environment on excitons in monolayer WSe 2 : Insight from high magnetic fields

Excitons in atomically thin semiconductors necessarily lie close to a surface, and therefore their properties are expected to be strongly influenced by the surrounding dielectric environment. However, systematic studies exploring this role are challenging, in part because the most readily accessible exciton parameter—the exciton’s optical transition energy—is largely unaffected by the surrounding medium. Here we show that the role of the dielectric environment is revealed through its systematic influence on the size of the exciton, which can be directly measured via the diamagnetic shift of the exciton transition in high magnetic fields. Using exfoliated WSe 2 monolayers affixed to single-mode optical fibers, we tune the surrounding dielectric environment by encapsulating the flakes with different materials and perform polarized low-temperature magneto-absorption studies to 65 T. The systematic increase of the exciton’s size with dielectric screening, and concurrent reduction in binding energy (also inferred from these measurements), is quantitatively compared with leading theoretical models. Furthermore, these results demonstrate how exciton properties can be tuned in future 2D optoelectronic devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Wetter California Projected by CMIP6 Models With Observational Constraints Under a High GHG Emission Scenario

As the world's fifth-largest economy entity, California (CA) is vulnerable to climate changes especially the magnitude of winter (wet season) precipitation that is closely linked to regional drought severity, vegetation growth, and wildfire activities. However, the fate of CA precipitation in the future remains highly uncertain, for example, the state-of-the-art Earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) projected –3% to +42% and –27% to +63% precipitation changes in northern and central-southern CA, respectively, under the high greenhouse gas (GHG) emission scenario (SSP585). In this work, we applied the Pareto optimality concept and used observed teleconnection patterns (causal relationships between ocean regions and CA precipitation) to mechanistically constrain CMIP6 projected CA precipitations. We estimated that precipitation will robustly increase by 0.4–1.3 mm d –1 (10–34%) over northern CA and increase by 0.1–0.5 mm d –1 (7–32%) over central-southern CA by the end of the 21st century compared with present-day. Up to 71% of ESM projection uncertainties were reduced mainly due to the strong and consistent causal relationship between North American west coast sea level pressure and CA precipitation in both observations and CMIP6 models. Our results suggest that teleconnection patterns are powerful mechanistic constraints that can help explain and reduce uncertainties in ESM projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming

Abstract Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93–0.99), precision (0.80–0.94), sensitivity (0.82–0.94), and specificity (0.95–0.98) on simulated communities, which are 10–160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and ‘drift’ (59%). Interestingly, warming decreases ‘drift’ over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics

Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach for gallium arsenide (GaAs) solar cells that identifies the root cause(s) of underperformance with layer-by-layer resolution and reveals alternative optimal process windows beyond traditional black-box optimization. Our Bayesian network approach links a key GaAs process variable (growth temperature) to material descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency). For this purpose, we combine a Bayesian inference framework with a neural network surrogate device-physics model that is 100× faster than numerical solvers. With the trained surrogate model and only a small number of experimental samples, our approach reduces significantly the time-consuming intervention and characterization required by the experimentalist. As a demonstration of our method, in only five metal organic chemical vapor depositions, we identify a superior growth temperature profile for the window, bulk, and back surface field layer of a GaAs solar cell, without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above traditional grid search methods.

14 SOLAR ENERGY↗
DOE OSTI2023

Multivariate chemogenomic screening prioritizes new macrofilaricidal leads

Development of direct acting macrofilaricides for the treatment of human filariases is hampered by limitations in screening throughput imposed by the parasite life cycle. In vitro adult screens typically assess single phenotypes without prior enrichment for chemicals with antifilarial potential. We developed a multivariate screen that identified dozens of compounds with submicromolar macrofilaricidal activity, achieving a hit rate of >50% by leveraging abundantly accessible microfilariae. Adult assays were multiplexed to thoroughly characterize compound activity across relevant parasite fitness traits, including neuromuscular control, fecundity, metabolism, and viability. Seventeen compounds from a diverse chemogenomic library elicited strong effects on at least one adult trait, with differential potency against microfilariae and adults. Our screen identified five compounds with high potency against adults but low potency or slow-acting microfilaricidal effects, at least one of which acts through a novel mechanism. We show that the use of microfilariae in a primary screen outperforms model nematode developmental assays and virtual screening of protein structures inferred with deep learning. These data provide new leads for drug development, and the high-content and multiplex assays set a new foundation for antifilarial discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A machine learning inversion scheme for determining interaction from scattering

Small angle scattering techniques have now been routinely used to quantitatively determine the potential of mean force in colloidal suspensions. However the numerical accuracy of data interpretation is often compounded by the approximations adopted by liquid state analytical theories. To circumvent this long standing issue, here we outline a machine learning strategy for determining the effective interaction in the condensed phases of matter using scattering. Via a case study of colloidal suspensions, we show that the effective potential can be probabilistically inferred from the scattering spectra without any restriction imposed by model assumptions. Comparisons to existing parametric approaches demonstrate the superior performance of this method in accuracy, efficiency, and applicability. This method can effectively enable quantification of interaction in highly correlated systems using scattering and diffraction experiments.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Revisiting trends in the exchange current for hydrogen evolution

Nørskov and collaborators proposed a simple kinetic model to explain the volcano relation for the hydrogen evolution reaction on transition metal surfaces such that j 0 = k 0 f(ΔG H ) where j 0 is the exchange current density, f(ΔG H ) is a function of the hydrogen adsorption free energy ΔG H as computed from density functional theory, and k 0 is a universal rate constant. Herein, focusing on the hydrogen evolution reaction in acidic medium, we revisit the original experimental data and find that the fidelity of this kinetic model can be significantly improved by invoking metal-dependence on k 0 such that the logarithm of k 0 linearly depends on the absolute value of ΔG H . Here, we further confirm this relationship using additional experimental data points obtained from a critical review of the available literature. Our analyses show that the new model decreases the discrepancy between calculated and experimental exchange current density values by up to four orders of magnitude. Furthermore, we show the model can be further improved using machine learning and statistical inference methods that integrate additional material properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Stochastic behavior of nanoscale dielectric wall buckling

The random buckling patterns of nanoscale dielectric walls are analyzed using a nonlinear multi-scale stochastic method that combines experimental measurements with simulations. The dielectric walls, approximately 200 nm tall and 20 nm wide, consist of compliant, low dielectric constant (low-k) fins capped with stiff, compressively stressed TiN lines that provide the driving force for buckling. The deflections of the buckled lines exhibit sinusoidal pseudoperiodicity with amplitude fluctuation and phase decorrelation arising from stochastic variations in wall geometry, properties, and stress state at length scales shorter than the characteristic deflection wavelength of about 1000 nm. The buckling patterns are analyzed and modeled at two length scales: a longer scale (up to 5000 nm) that treats randomness as a longer-scale measurable quantity, and a shorter-scale (down to 20 nm) that treats buckling as a deterministic phenomenon. Statistical simulation is used to join the two length scales. Through this approach, the buckling model is validated and material properties and stress states are inferred. In particular, the stress state of TiN lines in three different systems is determined, along with the elastic moduli of low-k fins and the amplitudes of the small-scale random fluctuations in wall properties—all in the as-processed state. The important case of stochastic effects giving rise to buckling in a deterministically sub-critical buckling state is demonstrated. The nonlinear multiscale stochastic analysis provides guidance for design of low-k structures with acceptable buckling behavior and serves as a template for how randomness that is common to nanoscale phenomena might be measured and analyzed in other contexts.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

First study of Hohlraum x-ray preheat asymmetry inside an ICF capsule

In indirect drive inertial confinement fusion (ICF), laser induced Hohlraum preheat radiation (so-called M-band, >1.8 keV) asymmetry will lead to asymmetric ablation front and ablator–fuel interface hydrodynamic instability growth in an imploding capsule. First experiments to infer the M-band asymmetries at the capsule were performed on the National Ignition Facility for high density carbon (HDC) ICF capsules in low density fill (0.3 mg/cc 4 He) Au Hohlraums by time resolved imaging of 2.3 keV fluorescence emission of a smaller Mo sphere placed inside the capsule. In this study, the measured Mo emission is pole hot (P 2 > 0) since M-band is generated mainly by the outer laser beams as their irradiance at the Hohlraum wall is 5× higher than for the inner beams. P 2 has a greater negative than positive swing vs time [Δ(P 2 /P 0 )/Δt ~ 0.2/ns], giving insight into laser heated Hohlraum dynamics. P 4 asymmetry is small at the sphere due to efficient geometric smoothing of Hohlraum asymmetries at large Hohlraum -to-capsule ratios. The M-band P 2 history is qualitatively reproduced by radiation hydrodynamic HYDRA simulations. The smaller P 2 than that calculated earlier suggests either less outer beam spot motion and/or preheat emission. At late times, the observed P 2 swing is larger and P 4 is more negative than simulated, which could be due to inner beams being stopped more in the outer beams wall plasma bubble than simulated. Asymmetry at the HDC capsule inner surface (“ice–ablator interface”) is also inferred from the Mo emission asymmetry by an analytic viewfactor model, accounting for the Mo/HDC radius difference and HDC capsule opacity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Correlations between asymmetric compression, burn amplification, and hot-spot velocities in inertial confinement fusion implosions

Here, this manuscript examines the correlations between the hot-spot velocity (an observable signature of residual kinetic energy), low-mode implosion asymmetries, and burn amplification in inertial confinement fusion implosions on the National Ignition Facility (NIF). Using a combination of two-dimensional axis-symmetric and three-dimensional radiation-hydrodynamic simulations coupled to neutronics, we find that for typical NIF implosions, the stagnation asymmetry multiplies the observed hot-spot velocity anywhere from 80% to 120%, while burn amplification always increases it. Additionally, we find stagnation asymmetry typically deflects the observed hot-spot flow. The two mechanisms (low-mode implosion asymmetries and burn amplification) can be decoupled, and application of a simple model to a database of cryogenic implosions on the NIF infers the total hot-spot velocity amplification. This finding modifies the interpretation of data collected from inertial confinement fusion experiments and impacts the magnitude and origin of low-mode asymmetries.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

BIASES IN PHYSICAL PARAMETER ESTIMATES THROUGH DIFFERENTIAL LENSING MAGNIFICATION

We study the lensing magnification effect on background galaxies. Differential magnification due to different magnifications of different source regions of a galaxy will change the lensed composite spectra. The derived properties of the background galaxies are therefore biased. For simplicity, we model galaxies as a superposition of an axis-symmetric bulge and a face-on disk in order to study the differential magnification effect on the composite spectra. We find that some properties derived from the spectra (e.g., velocity dispersion, star formation rate, and metallicity) are modified. Depending on the relative positions of the source and the lens, the inferred results can be either over- or underestimates of the true values. In general, for an extended source at strong lensing regions with high magnifications, the inferred physical parameters (e.g., metallicity) can be strongly biased. Therefore, detailed lens modeling is necessary to obtain the true properties of the lensed galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A formal method for identifying distinct states of variability in time-varying sources: SGR A* as an example

Continuously time variable sources are often characterized by their power spectral density and flux distribution. These quantities can undergo dramatic changes over time if the underlying physical processes change. However, some changes can be subtle and not distinguishable using standard statistical approaches. Here, we report a methodology that aims to identify distinct but similar states of time variability. We apply this method to the Galactic supermassive black hole, where 2.2 μm flux is observed from a source associated with Sgr A* and where two distinct states have recently been suggested. Our approach is taken from mathematical finance and works with conditional flux density distributions that depend on the previous flux value. The discrete, unobserved (hidden) state variable is modeled as a stochastic process and the transition probabilities are inferred from the flux density time series. Using the most comprehensive data set to date, in which all Keck and a majority of the publicly available Very Large Telescope data have been merged, we show that Sgr A* is sufficiently described by a single intrinsic state. However, the observed flux densities exhibit two states: noise dominated and source dominated. Our methodology reported here will prove extremely useful to assess the effects of the putative gas cloud G2 that is on its way toward the black hole and might create a new state of variability.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

INFERRING THE STRUCTURE OF THE SOLAR CORONA AND INNER HELIOSPHERE DURING THE MAUNDER MINIMUM USING GLOBAL THERMODYNAMIC MAGNETOHYDRODYNAMIC SIMULATIONS

Observations of the Sun’s corona during the space era have led to a picture of relatively constant, but cyclically varying solar output and structure. Longer-term, more indirect measurements, such as from {sup 10}Be, coupled by other albeit less reliable contemporaneous reports, however, suggest periods of significant departure from this standard. The Maunder Minimum was one such epoch where: (1) sunspots effectively disappeared for long intervals during a 70 yr period; (2) eclipse observations suggested the distinct lack of a visible K-corona but possible appearance of the F-corona; (3) reports of aurora were notably reduced; and (4) cosmic ray intensities at Earth were inferred to be substantially higher. Using a global thermodynamic MHD model, we have constructed a range of possible coronal configurations for the Maunder Minimum period and compared their predictions with these limited observational constraints. We conclude that the most likely state of the corona during—at least—the later portion of the Maunder Minimum was not merely that of the 2008/2009 solar minimum, as has been suggested recently, but rather a state devoid of any large-scale structure, driven by a photospheric field composed of only ephemeral regions, and likely substantially reduced in strength. Moreover, we suggest that the Sun evolved from a 2008/2009-like configuration at the start of the Maunder Minimum toward an ephemeral-only configuration by the end of it, supporting a prediction that we may be on the cusp of a new grand solar minimum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Time-resolved site-selective imaging of predissociation and charge transfer dynamics: the CH 3 I B-band

The predissociation dynamics of the 6s (B 2 E) Rydberg state of gas-phase CH 3 I were investigated by time-resolved Coulomb-explosion imaging using extreme ultraviolet (XUV) free-electron laser pulses. Inner-shell ionization at the iodine 4d edge was utilized to provide a site-specific probe of the ensuing dynamics. The combination of a velocity-map imaging (VMI) spectrometer coupled with the pixel imaging mass spectrometry (PImMS) camera permitted three-dimensional ionic fragment momenta to be recorded simultaneously for a wide range of iodine charge states. In accord with previous studies, initial excitation at 201.2 nm results in internal conversion and subsequent dissociation on the lower-lying A-state surface on a picosecond time scale. Examination of the time-dependent yield of low kinetic energy iodine fragments yields mechanistic insights into the predissociation and subsequent charge transfer following multiple ionization of the iodine products. The effect of charge transfer was observed through differing delay-dependencies of the various iodine charge states, from which critical internuclear distances for charge transfer could be inferred and compared to a classical over-the-barrier model. Time-dependent photofragment angular anisotropy parameters were extracted from the central slice of the Newton sphere, without Abel inversion, and highlight the effect of rotation of the parent molecule before dissociation, as observed in previous works. Our results demonstrate the ability to perform three-dimensional ion imaging at high event rates and showcase the potential benefits of this approach, particularly in relation to further time-resolved studies at free-electron laser facilities.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Bayesian forecasts for dark matter substructure searches with mock pulsar timing data

Dark matter substructure, such as primordial black holes (PBHs) and axion miniclusters, can induce phase shifts in pulsar timing arrays (PTAs) measurements due to gravitational effects. In order to gain a more realistic forecast for the detectability of such models of dark matter with PTAs, we propose a Bayesian inference framework to search for phase shifts generated by PBHs and perform the analysis on mock PTA data. Furthermore, for most PBH masses the constraints on the dark matter abundance agree with previous (frequentist) analyses (without mock data) to $\mathcal{O}$(1) factors. This further motivates a dedicated search for PBHs (and dense small scale structures) in the mass range from 10 -8 M ⊙ to well above 10 2 M ⊙ with the Square Kilometer Array. Moreover, with a more optimistic set of timing parameters, future PTAs are predicted to constrain PBHs down to 10 -11 M ⊙ . Lastly, we discuss the impact of backgrounds, such as Supermassive Black Hole Mergers, on detection prospects, suggesting a future program to separate a dark matter signal from other astrophysical sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Reconstruction and interpretation of ionization asymmetry in magnetic confinement via synthetic diagnostics

Abstract Strong poloidal refueling asymmetry in the DIII-D tokamak is inferred from line radiation measurements. Synthetic diagnostics in neutral transport modeling coupled to gyrokinetic simulations illuminate implications for the plasma flow profile in the scrape-off layer of single-null beam-driven discharges. Recycling occurs primarily either on the inner or outer divertor legs, depending on the toroidal magnetic field direction. By reversing the toroidal magnetic field, the observed line radiation asymmetry is nearly eliminated or reversed. It is determined that, while relatively simple physics can describe the observed ionization asymmetry, predicting the overall brightness of the hydrogenic Lyman- α signal requires detailed simulation of the plasma and resulting turbulence. To this end, kinetic plasma simulations fully coupled to comprehensive neutral transport calculations—a novel capability—provide first-principles reproduction of Lyman- α observations on DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Graph reinforcement learning for exploring model spaces beyond the standard model

We present a methodology for performing scans of beyond the standard model (BSM) parameter spaces with reinforcement learning. We identify a novel procedure using graph neural networks that is capable of exploring spaces of models without the user specifying a fixed particle content, allowing broad classes of BSM models to be explored—in theory, the technique is applicable to nearly any model space with a prespecified gauge group. We provide a generic procedure by which a suitable graph grammar can be developed for any BSM model that features user-specified symmetry groups and a finite number of different possible particle species, the use of which is applicable to a variety of machine learning tasks over the actions of BSM theories beyond our particular reinforcement learning use case. As a proof of concept, we construct the graph grammar for theories with vectorlike leptons that may or may not be charged under a dark U ( 1 ) group, inspired by portal matter extensions of the sub-GeV vector portal/kinetic mixing simplified dark matter models. We then use this graph grammar to create a reinforcement learning environment tasked with creating models with these vectorlike leptons that are consistent with a list of a variety of precision observables. The reinforcement learning agent succeeds in developing models that can address the observed muon anomalous magnetic moment discrepancy while remaining consistent with flavor violation and electroweak precision observables, including both constructions that have previously been studied as well as new models that have not, to our knowledge, previously been identified. By inspecting the resulting ensembles of models that the agent produces and experimenting with different configurations for our reinforcement learning environment and graph grammar, we also infer various lessons about the development of these environments that can be transferable to reinforcement learning scans of more complicated model spaces and comment on future directions for the development of this technique into a more mature tool. Published by the American Physical Society 2025

Wojcik, George N.↗