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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Experimental and Numerical Investigation of a Miniature Additively Manufactured Vortex Tube

Ranque–Hilsch vortex tubes are simple devices that can produce a cooling effect using compressed air. A key advantage of vortex tubes is the lack of moving solid parts; however, their efficiencies are relatively low. The present study focuses on the development of a miniature variable-diameter tube using additive manufacturing. A metal-based 3D printing technique was utilized to fabricate this vortex tube monolithically. Computational fluid dynamics simulations employing software STAR-CCM + with a compressible Reynolds-Averaged Navier–Stokes (RANS) approach and the elliptic-blending lag k-epsilon turbulence model have been applied to model thermofluid processes inside the vortex tube, to good agreement with the experiment. In conclusion, a temperature decrease of 13.3 °C and a cooling power of approximately 4 W were experimentally achieved with a pressure ratio of 4 in the air at normal conditions. This result shows promise for the goal of utilizing additive manufacturing to design and build complex-geometry vortex tubes intended for use with cryogenic fluids.

08 HYDROGEN↗
DOE OSTI2020

Facile diamond synthesis from lower diamondoids

Carbon-based nanomaterials have exceptional properties that make them attractive for a variety of technological applications. Here, we report on the use of diamondoids (diamond-like, saturated hydrocarbons) as promising precursors for laser-induced high-pressure, high-temperature diamond synthesis. The lowest pressure and temperature $(P-T)$ conditions that yielded diamond were 12 GPa (at ~2000 K) and 900 K (at ~20 GPa), respectively. This represents a substantially reduced transformation barrier compared with diamond synthesis from conventional (hydro)carbon allotropes, owing to the similarities in the structure and full sp 3 hybridization of diamondoids and bulk diamond. At 20 GPa, diamondoid-to-diamond conversion occurs rapidly within <19 μs. Molecular dynamics simulations indicate that once dehydrogenated, the remaining diamondoid carbon cages reconstruct themselves into diamond-like structures at high $P-T$. This study is the first successful mapping of the $P-T$ conditions and onset timing of the diamondoid-to-diamond conversion and elucidates the physical and chemical factors that facilitate diamond synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Gaussian approximation potentials for accurate thermal properties of two-dimensional materials

Two-dimensional materials (2DMs) continue to attract a lot of attention, particularly for their extreme flexibility and superior thermal properties. Molecular dynamics simulations are among the most powerful methods for computing these properties, but their reliability depends on the accuracy of interatomic interactions. While first principles approaches provide the most accurate description of interatomic forces, they are computationally expensive. In contrast, classical force fields are computationally efficient, but have limited accuracy in interatomic force description. Machine learning interatomic potentials, such as Gaussian Approximation Potentials, trained on density functional theory (DFT) calculations offer a compromise by providing both accurate estimation and computational efficiency. Here, in this work, we present a systematic procedure to develop Gaussian approximation potentials for selected 2DMs, graphene, buckled silicene, and h-XN (X = B, Al, and Ga, as binary compounds) structures. We validate our approach through calculations that require various levels of accuracy in interatomic interactions. The calculated phonon dispersion curves and lattice thermal conductivity, obtained through harmonic and anharmonic force constants (including fourth order) are in excellent agreement with DFT results. HIPHIVE calculations, in which the generated GAP potentials were used to compute higher-order force constants instead of DFT, demonstrated the first-principles level accuracy of the potentials for interatomic force description. Molecular dynamics simulations based on phonon density of states calculations, which agree closely with DFT-based calculations, also show the success of the generated potentials in high-temperature simulations.

2D Materials↗
DOE OSTI2020

Nanometer-Scale Correlations in Aqueous Salt Solutions

The intermediate-range (1–4 nm) correlation of cations, an- ions, and water in aqueous alkaline earth salt solutions is measured using synchrotron X-ray diffraction. We differentiate from the entire solution structure factor, S(Q), a separate region at low Q (<1 °A-1) containing local diffraction maxima (pre-peaks) that indicate nanometer-scale oscillatory behavior. These features are quantitatively reproduced with classical molecular dynamics simulations. At high concentrations, the pre-peaks emerge from correlations arising from existence of small quasi close-packed lattice- like structures comprised of cation hydration spheres. We also analyze the concentration dependence of the pre-peak and discuss the overall results in light of the rich literature dealing with intermediate-range correlations underlying universal phenomena in concentrated electrolytes. The authors were supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences. Pacific Northwest National Laboratory (PNNL) is operated by Battelle for the U.S. Department of Energy under Contract No. DE-AC05-76RL01830. Computing resources were generously allocated by PNNL's Institutional Computing program. DOE Contract No. DEAC02- 06CH11357 supports operation of the Advanced Photon Source at Argonne National Laboratory.

Chemical physics, nucleation, Madelung potential↗
DOE OSTI2020

Polymer Conformations and Diffusion Through a Monolayer of Confining Nanoparticles

We present coarse-grained molecular dynamics simulations to probe chain-scale polymer conformations and diffusion between confining nanoparticles (NPs). By constructing a monolayer of hexagonally-packed NPs in a polymer melt with athermal interactions, we observe the magnitude and length-scale over which homogeneously confining NPs impact the polymer behavior, which provides fundamental insights into more complex polymer nanocomposites. We show that polymer conformations are more perturbed under strong confinement (i.e. when the interparticle distance, ID, is less than twice the polymer radius of gyration, 2R g ) as compared to around an isolated NP, and the effect depends on the ratio of R NP /R g rather than either independently. In fact, these conformations can be quantitatively replicated by executing a simple random walk in a similarly confining environment. We also show that polymer diffusion is slowed by the presence of NPs and the slowing persists far beyond the length-scale over which polymer conformations are perturbed. Although the slowing is strongest ~R g from the NPs, the diffusion coefficient is slower even beyond ~5R g from the NPs. Furthermore, by analyzing the directional van Hove distributions, we show polymer diffusion away from the NP monolayer is bulk-like while diffusion through the monolayer is slower with increasing NP confinement. Furthermore, these molecular dynamics simulations provide fundamental insights into the temporal and spatial effect of confining, athermal NPs on chain-scale polymer conformations and diffusion.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Size- and temperature-dependent magnetization of iron nanoclusters

In this paper, the magnetic behavior of bcc iron nanoclusters, with diameters between 2 and 8 nm, is investigated by means of spin dynamics simulations coupled to molecular dynamics, using a distance-dependent exchange interaction. Finite-size effects in the total magnetization as well as the influence of the free surface and the surface/core proportion of the nanoclusters are analyzed in detail for a wide temperature range, going beyond the cluster and bulk Curie temperatures. Comparison is made with experimental data and with theoretical models based on the mean-field Ising model adapted to small clusters, and taking into account the influence of low coordinated spins at free surfaces. Our results for the temperature dependence of the average magnetization per atom M (T), including the thermalization of the transnational lattice degrees of freedom, are in very good agreement with available experimental measurements on small Fe nanoclusters. In contrast, significant discrepancies with experiment are observed if the translational degrees of freedom are artificially frozen. The finite-size effects on M (T) are found to be particularly important near the cluster Curie temperature. Simulated magnetization above the Curie temperature scales with cluster size as predicted by models assuming short-range magnetic ordering. Analytical approximations to the magnetization as a function of temperature and size are proposed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Quantum simulation of real-space dynamics

Quantum simulation is a prominent application of quantum computers. While there is extensive previous work on simulating finite-dimensional systems, less is known about quantum algorithms for real-space dynamics. We conduct a systematic study of such algorithms. In particular, we show that the dynamics of a d-dimensional Schrödinger equation with η particles can be simulated with gate complexity O ~ (ηdFpoly(log(g'/ϵ))), where ϵ is the discretization error, g' controls the higher-order derivatives of the wave function, and F measures the time-integrated strength of the potential. Compared to the best previous results, this exponentially improves the dependence on ϵ and g' from poly(g'/ϵ) to poly(log(g'/ϵ)) and polynomially improves the dependence on T and d, while maintaining best known performance with respect to η. For the case of Coulomb interactions, we give an algorithm using η 3 (d + η)Tpoly(log(ηdTg'/(Δϵ)))/Δ one- and two-qubit gates, and another using η 3 (4d) d/2 Tpoly(log(ηdTg'/(Δϵ)))/Δ one- and two-qubit gates and QRAM operations, where T is the evolution time and the parameter Δ regulates the unbounded Coulomb interaction. We give applications to several computational problems, including faster real-space simulation of quantum chemistry, rigorous analysis of discretization error for simulation of a uniform electron gas, and a quadratic improvement to a quantum algorithm for escaping saddle points in nonconvex optimization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Differences in the dynamics of the tandem-SH2 modules of the Syk and ZAP-70 tyrosine kinases

The catalytic activity of Syk-family tyrosine kinases is regulated by a tandem Src homology 2 module (tSH2 module). In the autoinhibited state, this module adopts a conformation that stabilizes an inactive conformation of the kinase domain. The binding of the tSH2 module to phosphorylated immunoreceptor tyrosine-based activation motifs necessitates a conformational change, thereby relieving kinase inhibition and promoting activation. We determined the crystal structure of the isolated tSH2 module of Syk and find, in contrast to ZAP-70, that its conformation more closely resembles that of the peptide-bound state, rather than the autoinhibited state. Hydrogen–deuterium exchange by mass spectrometry, as well as molecular dynamics simulations, reveal that the dynamics of the tSH2 modules of Syk and ZAP-70 differ, with most of these differences occurring in the C-terminal SH2 domain. Our data suggest that the conformational landscapes of the tSH2 modules in Syk and ZAP-70 have been tuned differently, such that the autoinhibited conformation of the Syk tSH2 module is less stable. This feature of Syk likely contributes to its ability to more readily escape autoinhibition when compared to ZAP-70, consistent with tighter control of downstream signaling pathways in T cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Failure of molecular dynamics to provide appropriate structures for quantum mechanical description of the aqueous chloride ion charge-transfer-to-solvent ultraviolet spectrum

The lowest band in the charge-transfer-to-solvent ultraviolet absorption spectrum of aqueous chloride ion is studied by experiment and computation. Interestingly, the experiments indicate that at concentrations up to at least 0.25 M, where calculations indicate ion pairing to be significant, there is no notable effect of ionic strength on the spectrum. The experimental spectra are fitted to aid comparison with computations. Classical molecular dynamic simulations are carried out on dilute aqueous Cl - , Na + , and NaCl, producing radial distribution functions in reasonable agreement with experiment and, for NaCl, clear evidence of ion pairing. Clusters are extracted from the simulations for quantum mechanical excited state calculations. Accurate ab initio coupled-cluster benchmark calculations on a small number of representative clusters are carried out and used to identify and validate an efficient protocol based on time-dependent density functional theory. The latter is used to carry out quantum mechanical calculations on thousands of clusters. The resulting computed spectrum is in excellent agreement with experiment for the peak position, with little influence from ion pairing, but is in qualitative disagreement on the width, being only about half as wide. It is concluded that simulation by classical molecular dynamics fails to provide an adequate variety of structures to explain the experimental CTTS spectrum of aqueous Cl - .

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

Dynamic and weak electric double layers in ultrathin nanopores

The unique properties of aqueous electrolytes in ultrathin nanopores have drawn a great deal of attention in a variety of applications, such as power generation, water desalination, and disease diagnosis. Inside the nanopore, at the interface, properties of ions differ from those predicted by the classical ionic layering models (e.g., Gouy–Chapman electric double layer) when the thickness of the nanopore approaches the size of a single atom (e.g., nanopores in a single-layer graphene membrane). Here, using extensive molecular dynamics simulations, the structure and dynamics of aqueous ions inside nanopores are studied for different thicknesses, diameters, and surface charge densities of carbon-based nanopores [ultrathin graphene and finite-thickness carbon nanotubes (CNTs)]. The ion concentration and diffusion coefficient in ultrathin nanopores show no indication of the formation of a Stern layer (an immobile counter-ionic layer) as the counter-ions and nanopore atoms are weakly correlated in time compared to the strong correlation observed in thick nanopores. The weak correlation observed in ultrathin nanopores is indicative of a weak adsorption of counter-ions onto the surface compared to that of thick pores. The vanishing counter-ion adsorption (ion–wall correlation) in ultrathin nanopores leads to several orders of magnitude shorter ionic residence times (picoseconds) compared to the residence times in thick CNTs (seconds). The results of this study will help better understand the structure and dynamics of aqueous ions in ultrathin nanopores.

2D materials↗
DOE OSTI2021

Spin dynamics of the antiferromagnetic Heisenberg model on a kagome bilayer

We research the spin dynamics of a classical Heisenberg antiferromagnet with nearest-neighbor interactions on a quasi-two-dimensional kagome bilayer. This geometrically frustrated lattice consists of two kagome layers connected by a triangular-lattice linking layer. By combining Monte Carlo with precessional spin dynamics simulations, we compute the dynamical structure factor of the classical spin liquid in the kagome bilayer and investigate the thermal and dilution effects. While the low-frequency and long-wavelength dynamics of the cooperative paramagnetic phase is dominated by spin diffusion, weak magnon excitations persist at higher energies, giving rise to the half-moon pattern in the dynamical structure factor. In the presence of spin vacancies, the dynamical properties of the diluted system can be understood within the two-population picture. The spin diffusion of the “correlated” spin clusters is mainly driven by the zero-energy weather-vane modes, giving rise to an autocorrelation function that decays exponentially with time. On the other hand, the diffusive dynamics of the quasifree “orphan” spins leads to a distinctive longer-time power-law tail in the autocorrelation function. We discuss the implications of our work for the glassy behaviors observed in the archetypal frustrated magnet SrCr 9p Ga 12-9 pO 19 (SCGO).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

CASTELO: clustered atom subtypes aided lead optimization—a combined machine learning and molecular modeling method

Background: Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials. Among its stages, lead optimization easily consumes more than half of the pre-clinical budget. We propose a combined machine learning and molecular modeling approach that partially automates lead optimization workflow in silico, providing suggestions for modification hot spots. Results: The initial data collection is achieved with physics-based molecular dynamics simulation. Contact matrices are calculated as the preliminary features extracted from the simulations. To take advantage of the temporal information from the simulations, we enhanced contact matrices data with temporal dynamism representation, which are then modeled with unsupervised convolutional variational autoencoder (CVAE). Finally, conventional and CVAE-based clustering methods are compared with metrics to rank the submolecular structures and propose potential candidates for lead optimization. Conclusion: With no need for extensive structure-activity data, our method provides new hints for drug modification hotspots which can be used to improve drug potency and reduce the lead optimization time. It can potentially become a valuable tool for medicinal chemists.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Surface Engineering by Simultaneous Action of Multiple External Fields (Final Technical Report)

This research project aims at enabling surface engineering strategies based on the fundamental understanding and predictive modeling of the surface morphological response of solid materials subjected to the combined action of multiple external forces. Surface morphological response to mismatch strain in strained-layer heterostructures also is analyzed. Our research focuses on the surface morphological evolution and stability of electrically conducting (metallic, such as Cu) and semiconducting (such as Si) solids under the simultaneous application of mechanical stresses, electric fields, and temperature gradients. We emphasize on identifying the conditions under which the multiply driven surface morphology is stable and on exploring the complexity of the corresponding various morphologically stable surface patterns. We also emphasize on the driven evolution of nanoscale features aiming at stabilizing and controlling nanoscale patterns on surfaces by their manipulation through simultaneously applied multiple external forces. Specifically, we address systematically the morphological response to the combined action of multiple external forces of bulk solid surfaces, surfaces of thin films grown epitaxially on thick or thin substrates, as well as nanoscale surface features such as coherently strained islands grown epitaxially on substrate surfaces. The research is based on a modeling approach that combines theoretical analyses of surface morphological stability with self-consistent dynamical simulations of surface evolution based on properly parameterized continuum and multiscale surface transport models.

36 MATERIALS SCIENCE↗
DOE OSTI2021

mystic : software for autonomous discovery and design under uncertainty

Throughout the diverse range of science and engineering applications, there is a growing desire to develop computational methods that can reliably predict the behavior of complex systems. Specifically, there is a strategic need for tools that can robustly forecast the behavior of complex physical systems, where data may be high-dimensional, noisy, or sparse, and models of the system may be time-dependent or include uncertainty. We use mystic to build tools that leverage statistical learning, physics-informed learning, and active learning in the efficient generation of reliably predictive surrogates for complex physical systems. mystic is a robust, proven, open-source optimization and uncertainty quantification toolkit with over a decade of use in the design and optimization of neutron instrumentation, solar-powered drones, and gasguns, and in iterative tuning of models for Raman spectroscopy and elastoplastic materials strength. Recent developments have focused on automated learning of statistically robust surrogates under uncertainty, with applications in materials in extreme environments, nanostructures, materials simulations and strength models, and the failure of shielding under particle radiation. In 2020, McKerns demonstrated active learning of optimally robust surrogates with respect to new simulated data for molecular dynamics simulations of materials mixing in warm dense matter, and is currently applying active learning to the automated steering of particle accelerator beams and the optimal design and control of quantum optical sensor instrumentation.

42 ENGINEERING↗