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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 829 records · Page 46

Mapping structures and dynamics with frequency-correlated diffusion exchange

Understanding molecular motion in diffusion-driven complex environments is critical for designing sustainable materials and improving chemical processes. Here, we introduce a multidimensional nuclear magnetic resonance (NMR) method that captures how molecular populations exchange across different dynamic regimes. By extending the modulated gradient spin-echo technique to include frequency-frequency correlations, our approach reveals diffusion pathways that are otherwise obscured in heterogeneous systems. Implemented on a unilateral NMR magnet, the method eliminates gradient pulsing constraints and accesses dynamics in the kilohertz regime. We apply this technique to swelling and acid-catalyzed deconstruction of cross-linked and linear polymers to observe how structural heterogeneity evolves over time. By linking molecular motion to topology and chemical state, we extract physical metrics such as fractal surface dimensionality and reaction wavefront velocity, properties inaccessible with standard diffusion measurements. This work expands the capabilities of NMR for probing soft matter, with implications for polymer recycling and materials design.

Fricke, Sophia N. [University of California, Berke↗

Deciphering competing elementary steps to correlate electrocatalyst chemical state with activity

The overpotential in multielectron transfer heterogeneous electrocatalysis fundamentally arises from thermodynamic and kinetic disparities among elementary steps; however, deciphering coupled and competing steps has long remained a challenge. Here, we establish an electrochemical deconvolution paradigm based on key processes in electrocatalytic reactions, such as charge accumulation, electron/proton transfer, and intermediate evolution, to resolve competing elementary steps. Taking the oxygen evolution reaction as a prototypical reaction, we design a model catalyst featuring a precise isolated cation-anion vacancy pair and track the previously elusive electrochemical behavior of lattice oxygen by disentangling interference from adsorbed oxygen intermediates. Mechanistically, the lattice oxygen oxidation pathway originates from the spontaneous, nonelectrochemical deprotonation of replenished water molecules coordinated to unsaturated cation sites. Alternating current techniques further reveal that although lattice oxygen oxidation requires a higher potential than metal oxidation, it exhibits faster kinetics, providing insight into its superior catalytic activity. These findings establish a direct experimental correlation between the initial chemical state and the catalytic activity and prove surface-confined lattice oxygen cycling. Furthermore, expanding conventional potential-current analysis into a multidimensional framework enables disentanglement of thermodynamic and kinetic contributions of key elementary steps, thereby guiding the rational optimization of various complex multielectron transfer reactions.

OER↗

A stable aluminosilicate zeolite with intersecting three-dimensional extra-large pores

Extra-large and intersecting pores Thermally stable zeolites with large pores, such as zeolite Y with 12-membered rings, are used for converting large molecules from petroleum into smaller, more useful hydrocarbons. Lin et al . report the synthesis of ZEO-1, a thermally stable zeolite with extra-large, 16-membered rings. The use of tricyclohexylmethylphosphonium as an organic structure–directing agent created a zeolite with a fully interconnected multidimensional framework and a very high specific surface area. —PDS

Science & Technology - Other Topics↗

A 3D extra-large-pore zeolite enabled by 1D-to-3D topotactic condensation of a chain silicate

Zeolites are microporous silicates with a large variety of applications as catalysts, adsorbents, and cation exchangers. Stable silica-based zeolites with increased porosity are in demand to allow adsorption and processing of large molecules but challenge our synthetic ability. We report a new, highly stable pure silica zeolite called ZEO-3, which has a multidimensional, interconnected system of extra-large pores open through windows made by 16 and 14 silicate tetrahedra, the least dense polymorph of silica known so far. This zeolite was formed by an unprecedented one-dimensional to three-dimensional (1D-to-3D) topotactic condensation of a chain silicate. With a specific surface area of more than 1000 square meters per gram, ZEO-3 showed a high performance for volatile organic compound abatement and recovery compared with other zeolites and metal-organic frameworks.

Science & Technology - Other Topics↗

Contribution of Vegetation to the Microbial Composition of Nearby Outdoor Air

Given that epiphytic microbes are often found in large population sizes on plants, we tested the hypothesis that plants are quantitatively important local sources of airborne microorganisms. The abundance of microbial communities, determined by quantifying bacterial 16S RNA genes and the fungal internal transcribed spacer (ITS) region, in air collected directly above vegetation was 2- to 10-fold higher than that in air collected simultaneously in an adjacent nonvegetated area 50 m upwind. Nonmetric multidimensional scaling revealed that the composition of airborne bacteria in upwind air samples grouped separately from that of downwind air samples, while communities on plants and downwind air could not be distinguished. In contrast, fungal taxa in air samples were more similar to each other than to the fungal epiphytes. A source-tracking algorithm revealed that up to 50% of airborne bacteria in downwind air samples were presumably of local plant origin. The difference in the proportional abundances of a given operational taxonomic unit (OTU) between downwind and upwind air when regressed against the proportional representation of this OTU on the plant yielded a positive slope for both bacteria and fungi, indicating that those taxa that were most abundant on plants proportionally contributed more to downwind air. Epiphytic fungi were less of a determinant of the microbiological distinctiveness of downwind air and upwind air than epiphytic bacteria. Emigration of epiphytic bacteria and, to a lesser extent, fungi, from plants can thus influence the microbial composition of nearby air, a finding that has important implications for surrounding ecosystems, including the built environment into which outdoor air can penetrate.

54 ENVIRONMENTAL SCIENCES↗

Impact of river channel lateral migration on microbial communities across a discontinuous permafrost floodplain

Permafrost soils store approximately twice the amount of carbon currently present in Earth’s atmosphere and are acutely impacted by climate change due to the polar amplification of increasing global temperature. Many organic-rich permafrost sediments are located on large river floodplains, where river channel migration periodically erodes and re-deposits the upper tens of meters of sediment. Channel migration exerts a first-order control on the geographic distribution of permafrost and floodplain stratigraphy and thus may affect microbial habitats. Here, to examine how river channel migration in discontinuous permafrost environments affects microbial community composition, we used amplicon sequencing of the 16S rRNA gene on sediment samples from floodplain cores and exposed riverbanks along the Koyukuk River, a large tributary of the Yukon River in west-central Alaska. Microbial communities are sensitive to permafrost thaw: communities found in deep samples thawed by the river closely resembled near-surface active layer communities in non-metric multidimensional scaling analyses but did not resemble floodplain permafrost communities at the same depth. Microbial communities also displayed lower diversity and evenness in permafrost than in both the active layer and permafrost-free point bars recently deposited by river channel migration. Taxonomic assignments based on 16S and quantitative PCR for the methyl-coenzyme M reductase functional gene demonstrated that methanogens and methanotrophs are abundant in older permafrost-bearing deposits, but not in younger, non-permafrost point bar deposits. The results suggested that river migration, which regulates the distribution of permafrost, also modulates the distribution of microbes potentially capable of producing and consuming methane on the Koyukuk River floodplain.

59 BASIC BIOLOGICAL SCIENCES↗

Bacterial Community Shift and Coexisting/Coexcluding Patterns Revealed by Network Analysis in a Uranium-Contaminated Site after Bioreduction Followed by Reoxidation

A site in Oak Ridge, TN, USA, has sediments that contain >3% iron oxides and is contaminated with uranium (U). The U(VI) was bioreduced to U(IV) and immobilized in situ through intermittent injections of ethanol. It then was allowed to reoxidize via the invasion of low-pH (3.6 to 4.0), high-nitrate (up to 200 mM) groundwater back into the reduced zone for 1,383 days. To examine the biogeochemical response, high-throughput sequencing and network analysis were applied to characterize bacterial population shifts, as well as cooccurrence and coexclusion patterns among microbial communities. A paired t test indicated no significant changes of α-diversity for the bioactive wells. However, both nonmetric multidimensional scaling and analysis of similarity confirmed a significant distinction in the overall composition of the bacterial communities between the bioreduced and the reoxidized sediments. The top 20 major genera accounted for >70% of the cumulative contribution to the dissimilarity in the bacterial communities before and after the groundwater invasion. Castellaniella had the largest dissimilarity contribution (17.7%). For the bioactive wells, the abundance of the U(VI)-reducing genera Geothrix, Desulfovibrio, Ferribacterium, and Geobacter decreased significantly, whereas the denitrifying Acidovorax abundance increased significantly after groundwater invasion. Additionally, seven genera, i.e., Castellaniella, Ignavibacterium, Simplicispira, Rhizomicrobium, Acidobacteria Gp1, Acidobacteria Gp14, and Acidobacteria Gp23, were significant indicators of bioactive wells in the reoxidation stage. Canonical correspondence analysis indicated that nitrate, manganese, and pH affected mostly the U(VI)-reducing genera and indicator genera. Cooccurrence patterns among microbial taxa suggested the presence of taxa sharing similar ecological niches or mutualism/commensalism/synergism interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Genomic fingerprints of the world’s soil ecosystems

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes—more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗

Effect of spatial nonuniformity of heating on compression and burning of a thermonuclear target under direct multibeam irradiation by a megajoule laser pulse

Direct-drive fusion targets are considered at present as an alternative to targets of indirect compression at a laser energy level of about 2 MJ. In this approach, the symmetry of compression and ignition of thermonuclear fuel play the major role. We report on the results of theoretical investigation of compression and burning of spherical direct-drive targets in the conditions of spatial nonuniformity of heating associated with a shift of the target from the beam center of focusing and possible laser radiation energy disbalance in the beams. The investigation involves numerous calculations based on a complex of 1D and 2D codes RAPID, SEND (for determining the target illumination and the dynamics of absorption), DIANA, and NUT (1D and multidimensional hydrodynamics of compression and burning of targets). The target under investigation had the form of a two-layer shell (ablator made of inertial material CH and DT ice) filled with DT gas. We have determined the range of admissible variation of compression and combustion parameters of the target depending on the variation of the spatial nonuniformity of its heating by a multibeam laser system. It has been shown that low-mode (long-wavelength) perturbations deteriorate the characteristics of the central region due to less effective conversion of the kinetic energy of the target shell into the internal energy of the center. Local initiation of burning is also observed in off-center regions of the target in the case of substantial asymmetry of irradiation. In this case, burning is not spread over the entire volume of the DT fuel as a rule, which considerably reduces the thermonuclear yield as compared to that in the case of spherical symmetry and central ignition.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Models for the dynamics of dust-like matter in the self-gravity field: The method of hydrodynamic substitutions

Models for the dynamics of a dust-like medium in the self-gravity field are investigated. Solutions of the corresponding problems are constructed by the method of hydrodynamic substitutions generalizing the Cole–Hopf substitutions. The method is extended to multidimensional ideal and viscous fluid flows with cylindrical and spherical symmetries for which exact solutions are constructed. Solutions for the dynamics of self-gravitating dust with arbitrary initial distributions of both fluid density and velocity are constructed using special coordinate transformations. In particular, the problem of cosmological expansion is considered in terms of Newton’s gravity theory. Models of a one-dimensional viscous dust fluid flow and some problems of gas hydrodynamics are considered. Examples of exact solutions and their brief analysis are provided.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Anisotropic diffusion in media with absorbing traps (application to the Keller–Dykhne theorem)

Anisotropic diffusion in multidimensional media with absorbing traps is investigated. It is shown that the diffusion asymptotic forms of the survival probability over long time intervals are determined by a new effective diffusion coefficient. Exact expressions derived for the effective diffusion coefficient generalize the well-known Dykhne–Keller 2D results to the 3D case. In other words, the dynamic diffusion approach is used for obtaining a generalization of the Dykhne–Keller theorem to the 3D case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Searches for Kaluza-Klein graviton excitations and microscopic black holes with the aid of the CMS detector at the LHC

A survey of the results of the Compact Muon Solenoid (CMS) experiment that concern searches for massive Kaluza-Klein graviton excitations and microscopic black holes, quantum black holes, and string balls within models of low-energy multidimensional gravity is presented on behalf of the CMS Collaboration. The analysis in question is performed on the basis of a complete sample of data accumulated for proton-proton collisions at the c.m. energies of 7 and 8 TeV at the Large Hadron Collider (LHC) over the period spanning 2010 and 2012.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Investigations of fission characteristics and correlation effects

We review the experimental results on the P-even and P-odd angular correlations of fission fragments in the fission of the {sup 235}U and {sup 239}Pu nuclei induced by unpolarized and polarized resonance neutrons, and on the TRI and ROT effects in the ternary and binary fission of actinides induced by polarized thermal neutrons. Also reported are the measured yields of prompt and delayed neutrons per fission event. The experimental data are analyzed within a novel theoretical framework developed by the JINR—RNC KI Collaboration, whereby the reduction of the multidimensional phase space of fission fragments to the JπK-channel space is consistently validated and the role of resonance interference in the observed correlation effects is revealed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Convergence of Spectral Discretizations of the Vlasov--Poisson System

Here we prove the convergence of a spectral discretization of the Vlasov-Poisson system. The velocity term of the Vlasov equation is discretized using either Hermite functions on the infinite domain or Legendre polynomials on a bounded domain. The spatial term of the Vlasov and Poisson equations is discretized using periodic Fourier expansions. Boundary conditions are treated in weak form through a penalty type term that can be applied also in the Hermite case. As a matter of fact, stability properties of the approximated scheme descend from this added term. The convergence analysis is carried out in detail for the 1D-1V case, but results can be generalized to multidimensional domains, obtained as Cartesian product, in both space and velocity. The error estimates show the spectral convergence under suitable regularity assumptions on the exact solution.

97 MATHEMATICS AND COMPUTING↗

Dynamic Looping of a Free-Draining Polymer

Here, we revisit the celebrated Wilemski--Fixman (WF) treatment for the looping time of a free-draining polymer. The WF theory introduces a sink term into the Fokker--Planck equation for the $3(N+1)$-dimensional Ornstein--Uhlenbeck process of polymer dynamics, which accounts for the appropriate boundary condition due to the formation of a loop. The assumption for WF theory is considerably relaxed. A perturbation method approach is developed that justifies and generalizes the previous results using either a delta sink or a Heaviside sink. For both types of sinks, we show that under the condition of a small dimensionless $\epsilon$, the ratio of capture radius to the Kuhn length, we are able to systematically produce all known analytical and asymptotic results obtained by other methods. This includes most notably the transition regime between the $N^2$ scaling of Doi, and $N\sqrt{N}/\epsilon$ scaling of Szabo, Schulten, and Schulten. The mathematical issue at play is the nonuniform convergence of $\epsilon\to 0$ and $N\to\infty$, the latter being an inherent part of the theory of a Gaussian polymer. Our analysis yields a novel term in the analytical expression for the looping time with small $\epsilon$, which was previously unknown. Monte Carlo numerical simulations corroborate the analytical findings. The systematic method developed here can be applied to other systems modeled by multidimensional Smoluchowski equations.

Ye, Felix X. -F.↗

A Method for Dimensionally Adaptive Sparse Trigonometric Interpolation of Periodic Functions

We present a method for dimensionally adaptive sparse trigonometric interpolation of multidimensional periodic functions belonging to a smoothness class of finite order. This method targets applications where periodicity must be preserved and the precise anisotropy is not known a priori. To the authors' knowledge, this is the first instance of a dimensionally adaptive sparse interpolation algorithm that uses a trigonometric interpolation basis. The motivating application behind this work is the adaptive approximation of a multi-input model for a molecular potential energy surface (PES) where each input represents an angle of rotation. Our method is based on an anisotropic quasi-optimal estimate for the decay rate of the Fourier coefficients of the model; a least-squares fit to the coefficients of the interpolant is used to estimate the anisotropy. Thus, our adaptive approximation strategy begins with a coarse isotropic interpolant, which is gradually refined using the estimated anisotropic rates. The procedure takes several iterations where ever-more accurate interpolants are used to generate ever-improving anisotropy rates. We present several numerical examples of our algorithm where the adaptive procedure successfully recovers the theoretical “best” convergence rate, including an application to a periodic PES approximation. An open-source implementation of our algorithm resides in the Tasmanian UQ library developed at Oak Ridge National Laboratory.

97 MATHEMATICS AND COMPUTING↗

Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker--Planck Equation and Physics-Informed Neural Networks

The Fokker--Planck (FP) equation governing the evolution of the probability density function (PDF) is applicable to many disciplines, but it requires specification of the coefficients for each case, which can be functions of space-time and not just constants and hence require the development of a data-driven modeling approach. When the data available is directly on the PDF, there exist methods for inverse problems that can be employed to infer the coefficients and thus determine the FP equation and subsequently obtain its solution. Herein, we address a more realistic scenario, where only sparse data are given on the particles' positions at a few time instants, which are not sufficient to accurately construct directly the PDF even at those times from existing methods, e.g., kernel estimation algorithms. To this end, we develop a general framework based on physics-informed neural networks (PINNs) that introduces a new loss function using the Kullback--Leibler divergence to connect the stochastic samples with the FP equation to simultaneously learn the equation and infer the multidimensional PDF at all times. In particular, we consider two types of inverse problems, type I, where the FP equation is known but the initial PDF is unknown, and type II, in which, in addition to the unknown initial PDF, the drift and diffusion terms are also unknown. In both cases, we investigate problems with either Brownian or Lévy noise or a combination of both. Here, we demonstrate the new PINN framework in detail in the one-dimensional (1D) case, but we also provide results for up to five dimensions demonstrating that we can infer both the FP equation and dynamics simultaneously at all times with high accuracy using only very few discrete observations of the particles.

97 MATHEMATICS AND COMPUTING↗

Communication Lower Bounds and Optimal Algorithms for Multiple Tensor-Times-Matrix Computation

Multiple tensor-times-matrix (Multi-TTM) is a key computation in algorithms for computing and operating with the Tucker tensor decomposition, which is frequently used in multidimensional data analysis. Here, we establish communication lower bounds that determine how much data movement is required (under mild conditions) to perform the Multi-TTM computation in parallel. The crux of the proof relies on analytically solving a constrained, nonlinear optimization problem. We also present a parallel algorithm to perform this computation that organizes the processors into a logical grid with twice as many modes as the input tensor. We show that, with correct choices of grid dimensions, the communication cost of the algorithm attains the lower bounds and is therefore communication optimal. Finally, we show that our algorithm can significantly reduce communication compared to the straightforward approach of expressing the computation as a sequence of tensor-times-matrix operations when the input and output tensors vary greatly in size.

HBL-inequalities↗