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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 OSTI2016

Biogenic manganese oxides as reservoirs of organic carbon and proteins in terrestrial and marine environments

Manganese (Mn) oxides participate in a range of interactions with organic carbon (OC) that can lead to either carbon degradation or preservation. In this work, we examine the abundance and composition of OC associated with biogenic and environmental Mn oxides to elucidate the role of Mn oxides as a reservoir for carbon and their potential for selective partitioning of particular carbon species. Mn oxides precipitated in natural brackish waters and by Mn(II)-oxidizing marine bacteria and terrestrial fungi harbor considerable levels of organic carbon (4.1-17.0 mol OC per kg mineral) compared to ferromanganese cave deposits which contain 1-2 orders of magnitude lower OC. Spectroscopic analyses indicate that the chemical composition of Mn oxide-associated OC from microbial cultures is homogeneous with bacterial Mn oxides hosting primarily proteinaceous carbon and fungal Mn oxides containing both protein- and lipopolysaccharide-like carbon. The bacterial Mn oxide-hosted proteins are involved in both Mn(II) oxidation and metal binding by these bacterial species and could be involved in the mineral nucleation process as well. By comparison, the composition of OC associated with Mn oxides formed in natural settings (brackish waters and particularly in cave ferromanganese rock coatings) is more spatially and chemically heterogeneous. Cave Mn oxide-associated organic material is enriched in aliphatic C, which together with the lower carbon concentrations, points to more extensive microbial or mineral processing of carbon in this system relative to the other systems examined in this study, and as would be expected in oligotrophic cave environments. This study highlights Mn oxides as a reservoir for carbon in varied environments. Lastly, the presence and in some cases dominance of proteinaceous carbon within the biogenic and natural Mn oxides may contribute to preferential preservation of proteins in sediments and dominance of protein-dependent metabolisms in the subsurface biosphere.

58 GEOSCIENCES↗
DOE OSTI2023

Dipolar spin-exchange and entanglement between molecules in an optical tweezer array

Ultracold polar molecules are promising candidate qubits for quantum computing and quantum simulations. Their long-lived molecular rotational states form robust qubits, and the long-range dipolar interaction between molecules provides quantum entanglement. In this work, we demonstrate dipolar spin-exchange interactions between single calcium monofluoride (CaF) molecules trapped in an optical tweezer array. We realized the spin- 1 2 quantum XY model by encoding an effective spin- 1 2 system into the rotational states of the molecules and used it to generate a Bell state through an iSWAP operation. Conditioned on the verified existence of molecules in both tweezers at the end of the measurement, we obtained a Bell state fidelity of 0.89(6). Using interleaved tweezer arrays, we demonstrate single-site molecular addressability.

Science & Technology - Other Topics↗
DOE OSTI2024

Momentum-exchange interactions in a Bragg atom interferometer suppress Doppler dephasing

Large ensembles of laser-cooled atoms interacting through infinite-range photon-mediated interactions are powerful platforms for quantum simulation and sensing. Here we realize momentum-exchange interactions in which pairs of atoms exchange their momentum states by collective emission and absorption of photons from a common cavity mode, a process equivalent to a spin-exchange or XX collective Heisenberg interaction. The momentum-exchange interaction leads to an observed all-to-all Ising-like interaction in a matter-wave interferometer. A many-body energy gap also emerges, effectively binding interferometer matter-wave packets together to suppress Doppler dephasing in analogy to Mössbauer spectroscopy. The tunable momentum-exchange interaction expands the capabilities of quantum interaction–enhanced matter-wave interferometry and may enable the realization of exotic behaviors, including simulations of superconductors and dynamical gauge fields.

Science & Technology - Other Topics↗
DOE OSTI2016

Nuclear symmetry energy in terms of single-nucleon potential and its effect on the proton fraction of β-stable npeμ matter

Momentum and density dependence of single-nucleon potential u{sub τ} (k, ρ, β) is analyzed using a density dependent finite range effective interaction of the Yukawa form. Depending on the choice of the strength parameters of exchange interaction, two different trends of the momentum dependence of nuclear symmetry potential are noticed which lead to two opposite types of neutron and proton effective mass splitting. The 2nd-order and 4th-order symmetry energy of isospin asymmetric nuclear matter are expressed analytically in terms of the single-nucleon potential. Two distinct behavior of the density dependence of 2nd-order and 4th-order symmetry energy are observed depending on neutron and proton effective mass splitting. It is also found that the 4th-order symmetry energy has a significant contribution towards the proton fraction of β-stable npeμ matter at high densities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

On the unsteady Darcy–Forchheimer–Brinkman equation in local and nonlocal tumor growth models

A mathematical analysis of local and nonlocal phase-field models of tumor growth is presented that includes time-dependent Darcy–Forchheimer–Brinkman models of convective velocity fields and models of long-range cell interactions. A complete existence analysis is provided. In addition, a parameter-sensitivity analysis is described that quantifies the sensitivity of key quantities of interest to changes in parameter values. Two sensitivity analyses are examined; one employing statistical variances of model outputs and another employing the notion of active subspaces based on existing observational data. Remarkably, the two approaches yield very similar conclusions on sensitivity for certain quantities of interest. The work concludes with the presentation of numerical approximations of solutions of the governing equations and results of numerical experiments on tumor growth produced using finite element discretizations of the full tumor model for representative cases.

Mathematics↗
DOE OSTI2020

Representation of Modes of Variability in Six U.S. Climate Models

We compare the performance of several modes of variability across six U.S. climate modeling groups, with a focus on identifying robust improvements in recent models [including those participating in phase 6 of the Coupled Model Intercomparison Project (CMIP)] compared to previous versions. In particular, we examine the representation of the Madden–Julian oscillation (MJO), El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), the quasi-biennial oscillation (QBO) in the tropical stratosphere, and the dominant modes of extratropical variability, including the southern annular mode (SAM), the northern annular mode (NAM) [and the closely related North Atlantic Oscillation (NAO)], and the Pacific–North American pattern (PNA). Where feasible, we explore the processes driving these improvements through the use of “intermediary” experiments that utilize model versions between CMIP3/5 and CMIP6 as well as targeted sensitivity experiments in which individual modeling parameters are altered. We find clear and systematic improvements in the MJO and QBO and in the teleconnection patterns associated with the PDO and ENSO. Some gains arise from better process representation, while others (e.g., the QBO) from higher resolution that allows for a greater range of interactions. Our results demonstrate that the incremental development processes in multiple climate model groups lead to more realistic simulations over time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

An Electrostatic Funnel in the GABA-Binding Pathway

The γ-aminobutyric acid type A receptor (GABA A -R) is a major inhibitory neuroreceptor that is activated by the binding of GABA. The structure of the GABA A -R is well characterized, and many of the binding site residues have been identified. However, most of these residues are obscured behind the C-loop that acts as a cover to the binding site. Thus, the mechanism by which the GABA molecule recognizes the binding site, and the pathway it takes to enter the binding site are both unclear. Through the completion and detailed analysis of 100 short, unbiased, independent molecular dynamics simulations, we have investigated this phenomenon of GABA entering the binding site. In each system, GABA was placed quasi-randomly near the binding site of a GABA A -R homology model, and atomistic simulations were carried out to observe the behavior of the GABA molecules. GABA fully entered the binding site in 19 of the 100 simulations. The pathway taken by these molecules was consistent and non-random; the GABA molecules approach the binding site from below, before passing up behind the C-loop and into the binding site. This binding pathway is driven by long-range electrostatic interactions, whereby the electrostatic field acts as a ‘funnel’ that sweeps the GABA molecules towards the binding site, at which point more specific atomic interactions take over. These findings define a nuanced mechanism whereby the GABA A -R uses the general zwitterionic features of the GABA molecule to identify a potential ligand some 2 nm away from the binding site.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Atomic-precision advanced manufacturing for Si quantum computing

Abstract A materials synthesis method that we call atomic-precision advanced manufacturing (APAM), which is the only known route to tailor silicon nanoelectronics with full 3D atomic precision, is making an impact as a powerful prototyping tool for quantum computing. Quantum computing schemes using atomic ( 31 P) spin qubits are compelling for future scale-up owing to long dephasing times, one- and two-qubit gates nearing high-fidelity thresholds for fault-tolerant quantum error correction, and emerging routes to manufacturing via proven Si foundry techniques. Multiqubit devices are challenging to fabricate by conventional means owing to tight interqubit pitches forced by short-range spin interactions, and APAM offers the required (Å-scale) precision to systematically investigate solutions. However, applying APAM to fabricate circuitry with increasing numbers of qubits will require significant technique development. Here, we provide a tutorial on APAM techniques and materials and highlight its impacts in quantum computing research. Finally, we describe challenges on the path to multiqubit architectures and opportunities for APAM technique development. Graphic Abstract

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cabana: A Performance Portable Library for Particle-Based Simulations

Particle-based simulations are ubiquitous throughout many fields of computational science and engineering, spanning the atomistic level with molecular dynamics (MD), to mesoscale particle-in-cell (PIC) simulations for solid mechanics, device-scale modeling with PIC methods for plasma physics, and massive N-body cosmology simulations of galaxy structures, with many other methods in between (Hockney & Eastwood, 1989). While these methods use particles to represent significantly different entities with completely different physical models, many low-level details are shared including performant algorithms for short- and/or long-range particle interactions, multi-node particle communication patterns, and other data management tasks such as particle sorting and neighbor list construction. Cabana is a performance portable library for particle-based simulations, developed as part of the Co-Design Center for Particle Applications (CoPA) within the Exascale Computing Project (ECP) (Alexander et al., 2020). The CoPA project and its full development scope, including ECP partner applications, algorithm development, and similar software libraries for quantum MD, is described in (Mniszewski et al., 2021). Cabana uses the Kokkos library for on-node parallelism (Edwards et al., 2014; Trott et al., 2022), enabling simulation on multi-core CPU and GPU architectures, and MPI for GPU-aware, multi-node communication. Cabana provides particle simulation capabilities on almost all current Kokkos backends, including serial execution, OpenMP (including OpenMP-Target for GPUs), CUDA (NVIDIA GPUs), HIP (AMD GPUs), and SYCL (Intel GPUs), providing a clear path for the coming generation of accelerator-based exascale hardware. Cabana builds on Kokkos by providing new particle data structures and particle algorithms resulting in a similar execution policy-based, node-level programming model that is intended to be used in addition to the core Kokkos library within an application. Cabana is designed as an application and physics agnostic, but particle-specific toolkit which can either be used to generate a new application, or to be used as needed in existing applications at various levels of invasiveness including through interfaces that wrap user memory in existing data structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Subsystem Rényi entropy of thermal ensembles for SYK-like models

The Sachdev-Ye-Kitaev model is an N N -modes fermionic model with infinite range random interactions. In this work, we study the thermal Rényi entropy for a subsystem of the SYK model using the path-integral formalism in the large- N N limit. The results are consistent with exact diagonalization and can be well approximated by thermal entropy with an effective temperature when subsystem size M\leq N/2 M ≤ N / 2 . We also consider generalizations of the SYK model with quadratic random hopping term or U(1) U ( 1 ) charge conservation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

LAMMPS strong scaling performance optimization on Blue Gene/Q

LAMMPS "Large-scale Atomic/Molecular Massively Parallel Simulator" is an open-source molecular dynamics package from Sandia National Laboratories. Significant performance improvements in strong-scaling and time-to-solution for this application on IBM's Blue Gene/Q have been achieved through computational optimizations of the OpenMP versions of the short-range Lennard-Jones term of the CHARMM force field and the long-range Coulombic interaction implemented with the PPPM (particle-particle-particle mesh) algorithm, enhanced by runtime parameter settings controlling thread utilization. Additionally, MPI communication performance improvements were made to the PPPM calculation by re-engineering the parallel 3D FFT to use MPICH collectives instead of point-to-point. Performance testing was done using an 8.4-million atom simulation scaling up to 16 racks on the Mira system at Argonne Leadership Computing Facility (ALCF). Speedups resulting from this effort were in some cases over 2x.

Coffman, Paul↗
DOE OSTI2015

Advancing the Theory of Nuclear Reactions with Rare Isotopes. From the Laboratory to the Cosmos

The mission of the Topical Collaboration on the Theory of Reactions for Unstable iSotopes (TORUS) was to develop new methods to advance nuclear reaction theory for unstable isotopes—particularly the (d,p) reaction in which a deuteron, composed of a proton and a neutron, transfers its neutron to an unstable nucleus. After benchmarking the state-of-the-art theories, the TORUS collaboration found that there were no exact methods to study (d,p) reactions involving heavy targets; the difficulty arising from the long-range nature of the well known, yet subtle, Coulomb force. To overcome this challenge, the TORUS collaboration developed a new theory where the complexity of treating the long-range Coulomb interaction is shifted to the calculation of so-called form-factors. An efficient implementation for the computation of these form factors was a major achievement of the TORUS collaboration. All the new machinery developed are essential ingredients to analyse (d,p) reactions involving heavy nuclei relevant for astrophysics, energy production, and stockpile stewardship.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Neutrino-Nucleus Interactions and the Short-Range Structure of Nuclei

Improvements in theoretical modeling of Short Range structures and phenomena, and comparisons with data, will require sustained collaboration between nuclear theorists and neutrino experimentalists. The extensive history of studying this area of nuclear physics in electron- and hadron-scattering experiments, coupled with the transformative capabilities of LArTPCs to identify neutrinos, will provide a ripe opportunity for new discoveries that will further our understanding of the nucleus.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Stochastic modeling of catalytic processes in nanoporous materials: Beyond mean-field approach

Transport and reaction in zeolites and other porous materials, such as mesoporous silica particles, has been a focus of interest in recent years. This is in part due to the possibility of anomalous transport effects (e.g. single-file diffusion) and its impact in the reaction yield in catalytic processes. Computational simulations are often used to study these complex nonequilibrium systems. Computer simulations using Molecular Dynamics (MD) techniques are prohibitive, so instead coarse grained one-dimensional models with the aid of Kinetic Monte Carlo (KMC) simulations are used. Both techniques can be computationally expensive, both time and resource wise. These coarse-grained systems can be exactly described by a set of coupled stochastic master equations, that describe the reaction-diffusion kinetics of the system. The equations can be written exactly, however, coupling between the equations and terms within the equations make it impossible to solve them exactly; approximations must be made. One of the most common methods to obtain approximate solutions is to use Mean Field (MF) theory. MF treatments yield reasonable results at high ratios of reaction rate k to hop rate h of the particles, but fail completely at low k=h due to the over-estimation of fluxes of particles within the pore. We develop a method to estimate fluxes and intrapore diffusivity in simple one- dimensional reaction-diffusion models at high and low k=h, where the pores are coupled to an equilibrated three-dimensional fluid. We thus successfully describe analytically these simple reaction-diffusion one-dimensional systems. Extensions to models considering behavior with long range steric interactions and wider pores require determination of multiple boundary conditions. We give a prescription to estimate the required parameters for these simulations. For one dimensional systems, if single-file diffusion is relaxed, additional parameters to describe particle exchange have to be introduced. We use Langevin Molecular Dynamics (MD) simulations to assess these parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Pi+ Cross Section on Argon for the LArIAT Experiment

LArIAT (Liquid Argon in a Testbeam) was a LArTPC experiment exposed to a charged-particle beam at the test-beam facility at Fermi National Accelerator Laboratory. This analysis measures the $\pi^+$-Ar cross section over an interacting energy range of 50-1100 MeV, accounting for background species and reconstruction effects. This is the first such measurement of this process. The result can be useful in tuning simulations for future liquid argon experiments such as DUNE and SBN.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Sliding Dynamics for Bubble Phases on Periodic Modulated Substrates

We analyze a bubble-forming system composed of particles with competing long-range repulsive and short range attractive interactions driven over a quasi-one-dimensional periodic substrate. We find various pinned and sliding phases as a function of substrate strength and drive amplitude. When the substrate is weak, a pinned bubble phase appears that depins elastically into a sliding bubble lattice. For stronger substrates, we find anisotropic bubbles, disordered bubbles, and stripe phases. Plastic depinning occurs via the hopping of individual particles from one bubble to the next in a pinned bubble lattice, and as the drive increases, there is a transition to a state where all of the bubbles are moving but are continuously shedding and absorbing individual particles. This is followed at high drives by a moving bubble lattice in which the particles can no longer escape their individual bubbles. The transition between the plastic and elastic sliding phases can be detected via signatures in the velocity-force curves, differential conductivity, and noise. When the bubbles shrink due to an increase in the attractive interaction term, they fit better inside the pinning troughs and become more strongly pinned, leading to a reentrant pinning phase. For weaker attractive terms, the size of the bubbles becomes greater than the width of the pinning troughs and the depinning becomes elastic with a reduced depinning threshold.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Datasets for Custom-trained Machine-learning Interatomic Potentials: Nitric Acid Aqueous Solution

This dataset was generated using an iterative active learning strategy with the ArcaNN software package (https://github.com/arcann-chem/arcann_training) to train machine-learning interatomic potentials (MLIPs) for aqueous nitric acid. Each active-learning cycle consisted of three stages: (1) training, (2) exploration, and (3) labeling. The initial training set comprised approximately 800 randomly selected configurations from a previous study by Lewis et al. (https://doi.org/10.1021/jp205510q), which investigated nitric acid solutions at 2, 3, 4, and 5 mol/L. For all configurations, single-point calculations of atomic forces and total energies were performed at the quantum density functional theory BLYP-D2 and PBE-D3 levels of theory using the CP2K Quickstep module. Valence electrons were treated explicitly, while core electrons on all atoms were represented by norm-conserving Goedecker–Teter–Hutter (GTH) pseudopotentials. Long-range dispersion interactions were accounted for using Grimme dispersion corrections. Wave functions were expanded in a mixed Gaussian-and-plane-wave scheme using TZV2P-MOLOPT basis sets for all elements and an 800 Ry auxiliary plane-wave cutoff for the electron density. Self-consistent field convergence was accelerated using orbital transformation and Direct Inversion in the Iterative Subspace, with a convergence threshold of 10^{-6}. All single-point calculations were carried out in periodic orthorhombic cells whose dimensions match those of the molecular configurations sampled from earlier trajectories. The CELL_REF keyword in CP2K was used to define a fixed reference cell, ensuring consistency in the reference data used for MLIP training, particularly when cell fluctuations are present in NpT simulations. The resulting high-fidelity energies and forces constitute the ground-truth labels used to train the MLIPs contained in this dataset.

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗
DOE OSTI2015

Comparative analysis of secretomes from Ectomycorrhizal fungi with an emphasis on small-secreted proteins

Fungi are major players in the carbon cycle in forest ecosystems due to the wide range of interactions they have with plants either through soil degradation processes by litter decayers or biotrophic interactions with pathogenic and ectomycorrhizal symbionts. Secretion of fungal proteins mediates these interactions by allowing the fungus to interact with its environment and/or host. Ectomycorrhizal (ECM) symbiosis independently appeared several times throughout evolution and involves approximately 80% of trees. Despite extensive physiological studies on ECM symbionts, little is known about the composition and specificities of their secretomes. In this study, we used a bioinformatics pipeline to predict and analyze the secretomes of 49 fungal species, including 11 ECM fungi, wood and soil decayers and pathogenic fungi to tackle the following questions: (1) Are there differences between the secretomes of saprophytic and ECM fungi? (2) Are small-secreted proteins (SSPs) more abundant in biotrophic fungi than in saprophytic fungi? and (3) Are there SSPs shared between ECM, saprotrophic and pathogenic fungi? We showed that the number of predicted secreted proteins is similar in the surveyed species, independently of their lifestyle. The secretome from ECM fungi is characterized by a restricted number of secreted CAZymes, but their repertoires of secreted proteases and lipases are similar to those of saprotrophic fungi. Focusing on SSPs, we showed that the secretome of ECM fungi is enriched in SSPs compared with other species. Most of the SSPs are coded by orphan genes with no known PFAM domain or similarities to known sequences in databases. Finally, based on the clustering analysis, we identified shared- and lifestyle-specific SSPs between saprotrophic and ECM fungi. The presence of SSPs is not limited to fungi interacting with living plants as the genome of saprotrophic fungi also code for numerous SSPs. As a result, ECM fungi shared lifestyle-specific SSPs likely involved in symbiosis that are good candidates for further functional analyses.

59 BASIC BIOLOGICAL SCIENCES↗