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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Atomically Resolved Electrically Active Intragrain Interfaces in Perovskite Semiconductors

Deciphering the atomic and electronic structures of interfaces is key to developing state-of-the-art perovskite semiconductors. However, conventional characterization techniques have limited previous studies mainly to grain-boundary interfaces, whereas the intragrain-interface microstructures and their electronic properties have been much less revealed. Herein using scanning transmission electron microscopy, we resolved the atomic-scale structural information on three prototypical intragrain interfaces, unraveling intriguing features clearly different from those from previous observations based on standalone films or nanomaterial samples. These intragrain interfaces include composition boundaries formed by heterogeneous ion distribution, stacking faults resulted from wrongly stacked crystal planes, and symmetrical twinning boundaries. The atomic-scale imaging of these intragrain interfaces enables us to build unequivocal models for the ab initio calculation of electronic properties. Our results suggest that these structure interfaces are generally electronically benign, whereas their dynamic interaction with point defects can still evoke detrimental effects. This work paves the way toward a more complete fundamental understanding of the microscopic structure-property-performance relationship in metal halide perovskites.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Modulated phases of graphene quantum Hall polariton fluids

There is a growing experimental interest in coupling cavity photons to the cyclotron resonance excitations of electron liquids in high-mobility semiconductor quantum wells or graphene sheets. These media offer unique platforms to carry out fundamental studies of exciton-polariton condensation and cavity quantum electrodynamics in a regime, in which electron–electron interactions are expected to play a pivotal role. Here, focusing on graphene, we present a theoretical study of the impact of electron–electron interactions on a quantum Hall polariton fluid, that is a fluid of magneto-excitons resonantly coupled to cavity photons. We show that electron–electron interactions are responsible for an instability of graphene integer quantum Hall polariton fluids towards a modulated phase. We demonstrate that this phase can be detected by measuring the collective excitation spectra, which is often at a characteristic wave vector of the order of the inverse magnetic length.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Towards complete assignment of the infrared spectrum of the protonated water cluster H + (H 2 O) 21

The spectroscopic features of protonated water species in dilute acid solutions have been long sought after for understanding the microscopic behavior of the proton in water with gas-phase water clusters H + (H 2 O) n extensively studied as bottom-up model systems. We present a new protocol for the calculation of the infrared (IR) spectra of complex systems, which combines the fragment-based Coupled Cluster method and anharmonic vibrational quasi-degenerate perturbation theory, and demonstrate its accuracy towards the complete and accurate assignment of the IR spectrum of the H + (H 2 O) 21 cluster. The site-specific IR spectral signatures reveal two distinct structures for the internal and surface four-coordinated water molecules, which are ice-like and liquid-like, respectively. The effect of inter-molecular interaction between water molecules is addressed, and the vibrational resonance is found between the O-H stretching fundamental and the bending overtone of the nearest neighboring water molecule. The revelation of the spectral signature of the excess proton offers deeper insight into the nature of charge accommodation in the extended hydrogen-bonding network underpinning this aqueous cluster.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Self-oscillating synchronematic colloids

Self-oscillators that sustain periodic dynamics under constant input are ubiquitous in natural and engineered systems, where their interactions enable spatiotemporal coordination among many individual units. New forms of organization can emerge when these self-oscillating units are free to move and rotate, coupling their spatial arrangement and alignment with their oscillation frequencies and phases. Here, we report experiments and simulations on populations of Quincke colloids that behave as self-oscillating units with position, orientation, frequency, and phase. Depending on the initial distribution, these active oscillators spontaneously organize into distinct collective states characterized by temporal synchronization and directional alignment, which we term synchronematic order. In fluid-like clusters, this order is short-ranged and decays over a length scale set by the competition between hydrodynamic interactions and athermal noise. In crystalline clusters, these interactions drive flobal synchronization and circular alignment-synchronematic crystals-whose collective frequency increases with cluster size due to non-reciprocal interactions. Our results establish self-oscillating colloids as a model system for active oscillatory matter and reveal fundamental principles by which synchronization, alignment, and structure co-emerge, offering new pathways for designing adaptive, frequency-tunable materials.

colloids↗
DOE OSTI2019

Visualization of clustered protocadherin neuronal self-recognition complexes

Neurite self-recognition and avoidance are fundamental properties of all nervous systems. These processes facilitate dendritic arborization, prevent formation of autapses and allow free interaction among non-self neurons. Avoidance among self neurites is mediated by stochastic cell-surface expression of combinations of about 60 isoforms of α-, β- and γ-clustered protocadherin that provide mammalian neurons with single-cell identities. Avoidance is observed between neurons that express identical protocadherin repertoires, and single-isoform differences are sufficient to prevent self-recognition. Protocadherins form isoform-promiscuous cis dimers and isoform-specific homophilic trans dimers. Although these interactions have previously been characterized in isolation, structures of full-length protocadherin ectodomains have not been determined, and how these two interfaces engage in self-recognition between neuronal surfaces remains unknown. Here we determine the molecular arrangement of full-length clustered protocadherin ectodomains in single-isoform self-recognition complexes, using X-ray crystallography and cryo-electron tomography. We determine the crystal structure of the clustered protocadherin γB4 ectodomain, which reveals a zipper-like lattice that is formed by alternating cis and trans interactions. Using cryo-electron tomography, we show that clustered protocadherin γB6 ectodomains tethered to liposomes spontaneously assemble into linear arrays at membrane contact sites, in a configuration that is consistent with the assembly observed in the crystal structure. These linear assemblies pack against each other as parallel arrays to form larger two-dimensional structures between membranes. Furthermore, our results suggest that the formation of ordered linear assemblies by clustered protocadherins represents the initial self-recognition step in neuronal avoidance, and thus provide support for the isoform-mismatch chain-termination model of protocadherin-mediated self-recognition, which depends on these linear chains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

In-situ weak-beam and polarization control of multidimensional laser sidebands for ultrafast optical switching

All-optical switching has myriad applications in optoelectronics, optical communications, and quantum information technology. To achieve ultrafast optical switching in a compact yet versatile setup, we demonstrate distinct sets of two-dimensional (2D) broadband up-converted multicolor arrays (BUMAs) in a thin type-I β-barium-borate crystal with two noncollinear near-IR femtosecond pulses at various phase-matching conditions. The unique interaction mechanism is revealed as quadratic spatial solitons (QSSs)-coupled cascaded four-wave mixing (CFWM), corroborated by numerical calculations of the governing phase-matching conditions. Broad and continuous spectral-spatial tunability of the 2D BUMAs are achieved by varying the time delay between the two incident pulses that undergo CFWM interaction, rooted in the chirped nature of the weak white light and the QSSs generation of the intense fundamental beam. The control of 2D BUMAs is accomplished via seeding a weak second-harmonic pulse in situ to suppress the 2D arrays with polarization dependence on the femtosecond timescale that matches the control pulse duration of ∼35 fs. A potential application is proposed on femtosecond all-optical switching in an integrated wavelength-time division multiplexing device.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Fast and anisotropic flexibility-rigidity index for protein flexibility and fluctuation analysis

Protein structural fluctuation, typically measured by Debye-Waller factors, or B-factors, is a manifestation of protein flexibility, which strongly correlates to protein function. The flexibility-rigidity index (FRI) is a newly proposed method for the construction of atomic rigidity functions required in the theory of continuum elasticity with atomic rigidity, which is a new multiscale formalism for describing excessively large biomolecular systems. The FRI method analyzes protein rigidity and flexibility and is capable of predicting protein B-factors without resorting to matrix diagonalization. A fundamental assumption used in the FRI is that protein structures are uniquely determined by various internal and external interactions, while the protein functions, such as stability and flexibility, are solely determined by the structure. As such, one can predict protein flexibility without resorting to the protein interaction Hamiltonian. Consequently, bypassing the matrix diagonalization, the original FRI has a computational complexity of O(N{sup 2}). This work introduces a fast FRI (fFRI) algorithm for the flexibility analysis of large macromolecules. The proposed fFRI further reduces the computational complexity to O(N). Additionally, we propose anisotropic FRI (aFRI) algorithms for the analysis of protein collective dynamics. The aFRI algorithms permit adaptive Hessian matrices, from a completely global 3N × 3N matrix to completely local 3 × 3 matrices. These 3 × 3 matrices, despite being calculated locally, also contain non-local correlation information. Eigenvectors obtained from the proposed aFRI algorithms are able to demonstrate collective motions. Moreover, we investigate the performance of FRI by employing four families of radial basis correlation functions. Both parameter optimized and parameter-free FRI methods are explored. Furthermore, we compare the accuracy and efficiency of FRI with some established approaches to flexibility analysis, namely, normal mode analysis and Gaussian network model (GNM). The accuracy of the FRI method is tested using four sets of proteins, three sets of relatively small-, medium-, and large-sized structures and an extended set of 365 proteins. A fifth set of proteins is used to compare the efficiency of the FRI, fFRI, aFRI, and GNM methods. Intensive validation and comparison indicate that the FRI, particularly the fFRI, is orders of magnitude more efficient and about 10% more accurate overall than some of the most popular methods in the field. The proposed fFRI is able to predict B-factors for α-carbons of the HIV virus capsid (313 236 residues) in less than 30 seconds on a single processor using only one core. Finally, we demonstrate the application of FRI and aFRI to protein domain analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Guided ink and process design for aerosol jet printing based on annular drying effects

Aerosol jet printing is a promising microscale additive manufacturing technology for emerging applications in printed and flexible electronics. However, the more widespread adoption of this emerging technique is hindered by a limited fundamental understanding of the process. This work focuses on a critical and underappreciated aspect of the process, the interaction between drying induced by the sheath gas and impaction. Combining focused experiments with support from numerical modeling, it is shown that these effects have a dramatic impact on key outputs of the process, including deposition rate, resolution, and morphology. These effects can amplify minor changes in ink composition or atomization yield, increasing process sensitivity and drift. Moreover, these effects can confound strategies for in-line process monitoring and control based on empirical observables. Strategies to directly manipulate this annular drying phenomenon are presented, providing a viable tool to tailor and study the process. This work clarifies coupled effects of printer design, ink formulation, and print parameters, establishing a more robust theoretical framework for understanding the aerosol jet printing process and advancing the maturity of this promising technology.

42 ENGINEERING↗
DOE OSTI2018

Simulating the weak death of the neutron in a femtoscale universe with near-Exascale computing

The fundamental particle theory called Quantum Chromodynamics (QCD) dictates everything about protons and neutrons, from their intrinsic properties to interactions that bind them into atomic nuclei. Quantities that cannot be fully resolved through experiment, such as the neutron lifetime (whose precise value is important for the existence of light-atomic elements that make the sun shine and life possible), may be understood through numerical solutions to QCD. We directly solve QCD using Lattice Gauge Theory and calculate nuclear observables such as neutron lifetime. We have developed an improved algorithm that exponentially decreases the time-tosolution and applied it on the new CORAL supercomputers, Sierra and Summit. We use run-time autotuning to distribute GPU resources, achieving 20% performance at low node count. We also developed optimal application mapping through a job manager, which allows CPU and GPU jobs to be interleaved, yielding 15% of peak performance when deployed across large fractions of CORAL.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Designing Metabolic Division of Labor in Microbial Communities

ABSTRACT Microbes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A “gedanken” (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor. IMPORTANCE Understanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

The UPR Branch IRE1- bZIP60 in Plants Plays an Essential Role in Viral Infection and Is Complementary to the Only UPR Pathway in Yeast

The unfolded protein response (UPR) signaling network encompasses two pathways in plants, one mediated by inositol-requiring protein-1 (IRE1)-bZIP60 mRNA and the other by site-1/site-2 proteases (S1P/S2P)-bZIP17/bZIP28. As the major sensor of UPR in eukaryotes, IRE1, in response to endoplasmic reticulum (ER) stress, catalyzes the unconventional splicing of HAC1 in yeast, bZIP60 in plants and XBP1 in metazoans. Recent studies suggest that IRE1p and HAC1 mRNA, the only UPR pathway found in yeast, evolves as a cognate system responsible for the robust UPR induction. However, the functional connectivity of IRE1 and its splicing target in multicellular eukaryotes as well as the degree of conservation of IRE1 downstream signaling effectors across eukaryotes remains to be established. Here, we report that IRE1 and its substrate bZIP60 function as a strictly cognate enzymesubstrate pair to control viral pathogenesis in plants. Moreover, we show that the S1P/ S2P-bZIP17/bZIP28 pathway, the other known branch of UPR in plants, does not play a detectable role in virus infection, demonstrating the distinct function of the IRE1-bZIP60 pathway in plants. Furthermore, we provide evidence that bZIP60 and HAC1, products of the enzyme-substrate duet, rather than IRE1, are functionally replaceable to cope with ER stress in yeast. Taken together, we conclude that the downstream signaling of the IRE1- mediated splicing is evolutionarily conserved in yeast and plants, and that the IRE1-bZIP60 UPR pathway not only confers overlapping functions with the other UPR branch in fundamental biology but also may exert a unique role in certain biological processes such as virus-plant interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

An Overview of RF Systems for the EIC

The Electron Ion Collider (EIC) to be constructed at Brookhaven National Laboratory in the USA will be a complex system of accelerators providing high luminosity, high polarization, variable center of mass energy collisions between electrons and protons or ions. To achieve this a variety of RF systems are required. They must provide for capture, formation and storage of Ampere-class beams in the electron and hadron storage rings (ESR and HSR), fast acceleration of high-charge polarized electron bunches in the rapid cycling synchrotron (RCS), provision of cold high current electron bunches in the high-energy cooler ERL and precise high-gradient crabbing of electrons and hadrons either side of the interaction point. The challenges include strong HOM damping in the storage ring cavities and cooler ERL, very high fundamental mode power in the ESR and cooler injector, extremely stable low-noise operation of the crab cavities, mitigation of transient beam loading from gaps, and operating over a wide range of energies and beam currents. We describe the high-level system parameters and principal design choices made and progress on the R&D plan to develop these state of the art systems.

Rimmer, R. A.↗
DOE OSTI2022

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impacts of phase state and water content on secondary organic aerosol formation and partitioning (Final Technical Report)

Secondary organic aerosols (SOA) account for a major fraction of particulate matter in the atmosphere, affecting climate, air quality, and public health. SOA formation and evolution are highly complex processes involving both chemical reactions and transport of molecules in air, at particle surfaces, and within particles. The state of the matter, or “phase state,” comprising SOA can vary from a liquid, over an amorphous semi-solid, to a glassy solid, depending on chemical composition, water content, relative humidity (RH), and temperature. The occurrence of glassy and amorphous semi-solid states can pose limitations on the rate of transport of molecules, affecting gas-particle interactions and challenging the treatment of SOA in atmospheric models. The objective of this project was to improve fundamental understanding of the interplay of the phase state of particles and water content on the evolution of SOA formation. We have developed a method to estimate the glass transition temperature (T g ) of organic compounds to predict the phase state and viscosity of SOA. This method has been applied to high resolution mass spectrometry data of various types of SOA, achieving a good agreement with viscosity measurements. In addition, the viscosity estimation method was implemented into a regional model CMAQ to simulate diel and seasonal variations of SOA phase state over the U.S. Applying kinetic multilayer modeling, we analyzed laboratory experiments and ARM field measurements (e.g., HI-SCALE) on kinetic limitations of amine uptake. We have also conducted numerical simulations to estimate equilibration timescales of SOA partitioning. Overall, we have evaluated the impacts of phase state and water content on SOA lifecycle that should contribute to reducing the uncertainty of SOA representation in regional climate and air quality predictions. The project has yielded 17 publications, in which DE-SC0018349 is explicitly acknowledged. Please see the list of publications as below, followed by summary of research activities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Electron-Ion Collider - Plans for Realization

Understanding the emergence of nucleons and nuclei and their interactions from the properties and dynamics of quarks and gluons in Quantum Chromo-Dynamics (QCD) is a fundamental and compelling goal of nuclear science. An Electron-Ion Collider (EIC) was designated in the 2007 Nuclear Physics Long Range Plan as "embodying the vision for reaching the next QCD frontier," extending the QCD science programs in the U.S. established at both the CEBAF accelerator at JLab and RHIC at BNL in dramatic and fundamentally important ways. The 2013 Report of the NSAC Subcommittee on Major Nuclear Physics Facilities for the Next Decade reaffirmed an EIC as "absolutely central in its ability to contribute to world-leading science in the next decade." Two proposals for the EIC are being considered in the U.S.: one each at BNL and at Jefferson Laboratory. In this presentation we will review these proposals of the EIC, their implementation plan, and comment on the physics opportunities they present to the nuclear science communities in the next decade

Rossi, Patrizia↗
DOE OSTI2018

Design Principles of Microbial Communities: From Understanding to Engineering

The goal of this thematic issue is to provide an overview of advances in fundamental and applied research on microbial communities - advances that promote our understanding of the design principles of microbial interactions. The three papers in this issue address this goal by providing focused reviews on the following key science topics: 1) the resistome, which is the collection of all genes and their precursors involved in antibiotic resistance; 2) community metabolic network modeling; and 3) synthesis of model consortia

Song, Hyun-Seob↗
DOE OSTI2022

Editorial: Particulate Matter Emissions From Conventional and Reformulated Fuel Combustion: Advances in Experiments and Simulations

Particulate matter (PM or soot) emissions generated by combustion of conventional and reformulated fuels adversely impact the environment and human health (Bond et al., 2013; Landrigan et al., 2018; World Health Organization (WHO), 2016), generating public awareness and motivating efforts towards the mitigation of their harmful effects. Soot formation is one of the most complex phenomena in combustion, involving interactions between combustion chemistry, fluid mechanics, mass/heat transport, and particle dynamics, spanning different spatial and temporal scales. A fundamental understanding of soot formation process is thus necessary to achieve a strong reduction of PM emissions and design cleaner and more efficient combustion systems. This has motivated a longstanding and ongoing research activity aimed at improving our understanding of the physical and chemical processes involved in soot formation, well reviewed in these recent works (Wang and Chung, 2019; Michelsen et al., 2020; Martin et al., 2022). Despite the wide interest, the transition from gas-phase molecules to incipient soot particles is still elusive and the successive particle growth and oxidation processes are far from being fully understood, especially in conditions relevant to real-world applications. Recent advances in combustion PM emission diagnostic and computational capabilities helped in improving the predictability of fundamental chemical and aerosol models for practical applications, thus tackling some of the above-mentioned challenges. The aim of this research topic is to display the ongoing research efforts in addressing the existing gaps on particulate formation from various fuel sources and in conditions typical of practical combustion applications (e.g. flames, engines, pool fires), through both experimental and numerical approaches.

42 ENGINEERING↗
DOE OSTI2015

A Data Analysis Center for Electromagnetic and Hadronic Interaction

The GW Data Analysis Center (DAC) has made significant progress in its program to enhance and expand the partial-wave and multipole analyses of fundamental reactions, while maintaining and expanding each associated database. These efforts provide guidance to national and international experimental and theoretical efforts, and are an important link between theory and experiment. Our principal goals are focused on baryon and meson physics programs and related topics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗