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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Accelerating Convergence of Free Energy Computations with Hamiltonian Simulated Annealing of Solvent (HSAS)

Coupling between binding of a ligand to a receptor and the displacement of a number of bound water molecules is a common event in molecular recognition processes. When the binding site is deeply buried and the exchange of water molecules with the bulk region is difficult to sample, the convergence and accuracy in free energy calculations can be severely compromised. Traditionally, Grand Canonical Monte Carlo (GCMC) based methods have been used to accelerate equilibration of water-at the expense, however, of lengthy trials before a molecular dynamics (MD) simulation. In this paper, a user-friendly and cost-efficient method, Hamiltonian simulated annealing of solvent in combination with lambda-exchange of free energy perturbation (FEP) is proposed to accelerate the sampling of water molecules in free energy calculations. As an illustrative example with reliable data from previous GCMC simulations, absolute binding affinity of camphor to cytochrome P450 was calculated. The simulated hydration state change in the buried binding pocket quantitatively agrees with GCMC simulations. Finally, it is shown that the new protocol significantly accelerates sampling of water in a buried binding pocket and the convergence of free energy, with negligible setup and computing costs compared to GCMC methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Introducing GPU Acceleration into the Python-Based Simulations of Chemistry Framework

We introduce the first version of GPU4P Y SCF, a module that provides GPU acceleration of methods in P Y SCF. As a core functionality, this provides a GPU implementation of two-electron repulsion integrals (ERIs) for contracted basis sets comprising up to g functions using the Rys quadrature. As an illustration of how this can accelerate a quantum chemistry workflow, we describe how to use the ERIs efficiently in the integral-direct Hartree–Fock build and nuclear gradient construction. Benchmark calculations show a significant speedup of 2 orders of magnitude with respect to the multithreaded CPU Hartree–Fock code of P Y SCF and the performance comparable to other open-source GPU-accelerated quantum chemical packages, including GAMESS and QUICK, on a single NVIDIA A100 GPU.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Polymer Chain Diffusion in All-Polymer Nanocomposites: Confinement vs Chain Acceleration

All-polymer nanocomposites, in which soft, polymer-based nanoparticles are dispersed in the polymer matrix, have received great interest lately due to their potential use in a range of applications, including drug delivery and self-healing materials. However, the impact of this new class of nanoparticles on the dynamics of a linear polymer matrix in an all-polymer nanocomposite is still largely unknown. In this work, we report that the addition of polystyrene soft nanoparticles accelerates the diffusion of high molecular weight linear PS chains over a range of nanoparticle loadings. Our results show that at nanoparticle loadings below 1%, the diffusion of the linear matrix increases, presumably via a constraint release mechanism. At loadings above 1%, the increase in diffusion is mitigated by confinement effects of the nanoparticles. Thus, the response of these all-polymer nanocomposites is dominated by the balance of entropic confinement of the chain, which slows diffusion and a constraint release mechanism that speeds up the diffusion. However, the diffusion of the linear chain in the all-polymer nanocomposite is faster than that of the same chain in the melt at all loadings, diverging from the behavior of most nanocomposites with hard, impenetrable nanoparticles. Thus, the mechanism that accelerates the chain diffusion dominates in these systems. This behavior is unusual and fundamentally different than what has been reported for nanocomposites with hard inorganic nanoparticles, indicating that new perspectives are needed for these materials where the control of loading can either accelerate or decelerate the dynamics of the matrix in a distinctive manner.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Mechanically Accelerated Depolymerization of Entangled Linear Polymer Melts

Mechanical forces can enhance the chemical depolymerization of synthetic polymers when shear flow accelerates chain scission. To quantify the extent of mechanically-accelerated scission, the effect of simple shear flow (duration and strength) with low Weissenberg and Deborah numbers was investigated by considering the impact of applied work in both simple shear and shear dominated mixed flows. Hydrogenated polyisoprene was chosen as a model linear, entangled system. The conditions (strain amplitude, frequency, and shearing time) necessary to increase chain scission were assessed in the rubbery melt. Shear flow accelerated chain scission at higher temperatures, suggesting an activated process. Isothermal scission versus work curves were superposed by applying shift factors a T,S , whose Arrhenius-like temperature dependence gave an apparent activation energy for chain scission of ~ 110 kJ/mol, which is likely a combination of the activation energy of viscosity and bond energy. This work provides a base for quantifying the impact of shear on depolymerization of polymer melts and highlight the connection between viscous dissipation and scission chemistry.

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

Acceleration of Oxygen Ions in Dipolarization Events: 1. CPS Distributions

Abstract Using an MHD simulation of near tail reconnection associated with a flow burst and the collapse (dipolarization) of the inner tail in combination with test particle tracing we study the acceleration and flux increases of energetic oxygen ions (O + ). The characteristic orbits, distributions, and acceleration mechanisms are governed by the dimensionless parameter σ = ω ci t n , where ω ci is the ion gyro frequency and t n a characteristic Alfvén time of the MHD simulation. For σ < 1, central plasma sheet (CPS) populations after the passage of the dipolarization front are found to resemble half‐shells in velocity space oriented toward dusk. They originate from within the CPS and are energized typically by a single encounter of the region of enhanced cross‐tail electric field associated with the flow burst. For larger σ values ( σ > 1) the O + distributions resemble more closely those of protons, consisting of two counter‐streaming field‐aligned beams and an, albeit more tenuous and irregular, ring population perpendicular to the magnetic field. The existence of the beams, however, depends on suitable earthward moving source populations in the plasma sheet boundary layer or the adjacent lobes. The acceleration to higher energies is found to indicate a charge dependence, consistent with a dominance of more highly charged ions at energies of a few hundred keV. As in earlier simulations, the simulated fluxes show large anisotropies and nongyrotropic effects, phase bunching, and spatially and temporally localized beams.

Birn, J.↗
DOE OSTI2023

Likely accelerated weakening of Atlantic overturning circulation emerges in optimal salinity fingerprint

The long-term response of the Atlantic meridional overturning circulation (AMOC) to anthropogenic forcing has been difficult to detect from the short direct measurements available due to strong interdecadal variability. Here, we present observational and modeling evidence for a likely accelerated weakening of the AMOC since the 1980s under the combined forcing of anthropogenic greenhouse gases and aerosols. This likely accelerated AMOC weakening signal can be detected in the AMOC fingerprint of salinity pileup remotely in the South Atlantic, but not in the classic warming hole fingerprint locally in the North Atlantic, because the latter is contaminated by the “noise” of interdecadal variability. Our optimal salinity fingerprint retains much of the signal of the long-term AMOC trend response to anthropogenic forcing, while dynamically filtering out shorter climate variability. Given the ongoing anthropogenic forcing, our study indicates a potential further acceleration of AMOC weakening with associated climate impacts in the coming decades.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Analyzing machine learning models to accelerate generation of fundamental materials insights

Abstract Machine learning for materials science envisions the acceleration of basic science research through automated identification of key data relationships to augment human interpretation and gain scientific understanding. A primary role of scientists is extraction of fundamental knowledge from data, and we demonstrate that this extraction can be accelerated using neural networks via analysis of the trained data model itself rather than its application as a prediction tool. Convolutional neural networks excel at modeling complex data relationships in multi-dimensional parameter spaces, such as that mapped by a combinatorial materials science experiment. Measuring a performance metric in a given materials space provides direct information about (locally) optimal materials but not the underlying materials science that gives rise to the variation in performance. By building a model that predicts performance (in this case photoelectrochemical power generation of a solar fuels photoanode) from materials parameters (in this case composition and Raman signal), subsequent analysis of gradients in the trained model reveals key data relationships that are not readily identified by human inspection or traditional statistical analyses. Human interpretation of these key relationships produces the desired fundamental understanding, demonstrating a framework in which machine learning accelerates data interpretation by leveraging the expertize of the human scientist. We also demonstrate the use of neural network gradient analysis to automate prediction of the directions in parameter space, such as the addition of specific alloying elements, that may increase performance by moving beyond the confines of existing data.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Genetic algorithms for computational materials discovery accelerated by machine learning

Materials discovery is increasingly being impelled by machine learning methods that rely on pre-existing datasets. Where datasets are lacking, unbiased data generation can be achieved with genetic algorithms. Here a machine learning model is trained on-the-fly as a computationally inexpensive energy predictor before analyzing how to augment convergence in genetic algorithm-based approaches by using the model as a surrogate. This leads to a machine learning accelerated genetic algorithm combining robust qualities of the genetic algorithm with rapid machine learning. The approach is used to search for stable, compositionally variant, geometrically similar nanoparticle alloys to illustrate its capability for accelerated materials discovery, e.g., nanoalloy catalysts. The machine learning accelerated approach, in this case, yields a 50-fold reduction in the number of required energy calculations compared to a traditional “brute force” genetic algorithm. This makes searching through the space of all homotops and compositions of a binary alloy particle in a given structure feasible, using density functional theory calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2017

The case for electron re-acceleration at galaxy cluster shocks

On the largest scales, the Universe consists of voids and filaments making up the cosmic web. Galaxy clusters are located at the knots in this web, at the intersection of filaments. Clusters grow through accretion from these large-scale filaments and by mergers with other clusters and groups. In a growing number of galaxy clusters, elongated Mpc-sized radio sources have been found. Also known as radio relics, these regions of diffuse radio emission are thought to trace relativistic electrons in the intracluster plasma accelerated by low-Mach-number shocks generated by cluster–cluster merger events. A long-standing problem is how low-Mach-number shocks can accelerate electrons so efficiently to explain the observed radio relics. Here, we report the discovery of a direct connection between a radio relic and a radio galaxy in the merging galaxy cluster Abell 3411–3412 by combining radio, X-ray and optical observations. This discovery indicates that fossil relativistic electrons from active galactic nuclei are re-accelerated at cluster shocks. Lastly, it also implies that radio galaxies play an important role in governing the non-thermal component of the intracluster medium in merging clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Particle physics at accelerators in the United States and Asia

Particle physics experiments in the United States and Asia have greatly contributed to the understanding of elementary particles and their interactions. With the recent discovery of the Higgs boson at CERN, interest in the development of next-generation colliders has been rekindled. A linear electron–positron collider in Japan and a circular collider in China have been proposed for precision studies of the Higgs boson. In addition to the Higgs programme, new accelerator-based long-baseline neutrino mega-facilities are being built in the United States and Japan. Here, we outline the present status of key particle physics programmes at accelerators, and future plans in the United States and Asia that largely complement approaches being explored in the European Strategy for Particle Physics Update. Furthermore, we encourage the pursuit of this global approach, reaching beyond regional boundaries for optimized development and operations of major accelerator facilities worldwide, to ensure an active and productive future of the field.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Stable and tunable MeV $$\gamma$$-ray generation via dual-laser inverse Thomson scattering from a laser-plasma accelerator

Abstract Inverse Thomson scattering from laser-plasma accelerators offers a pathway to compact, tunable MeV $$\gamma$$ -ray sources for reduced-dose radiography and enhanced performance in nuclear resonance fluorescence (NRF)-based isotope identification. However, photon yield and spectral quality are often limited by constraints on interaction geometry and scatter-laser tunability. Here we demonstrate a MeV $$\gamma$$ -ray source based on a dual-laser inverse Thomson scattering configuration driven by a 100-TW laser-plasma accelerator. Electron beams tunable from 122 to 204 MeV with $$<5$$ mrad divergence and $$<1$$ mrad pointing stability generate $$\gamma$$ rays with peak energies from 276 keV to 1.2 MeV and yields up to $$2\times 10^{7}$$ photons per shot. By independently controlling the interaction position and the scatter-pulse duration, we experimentally match the scatter pulse to the walk-off-limited interaction length. Extending the scatter pulse to 200 fs increases photon production by approximately $$15\%$$ while maintaining operation in the linear Thomson regime, thereby preserving narrow spectral bandwidth and controlled radiation divergence. Radiographic characterization demonstrates MeV-level penetration and $$\approx 0.1$$ mm spatial resolution, while stable operation is sustained over multi-hour timescales across multiple days. These results show that interaction-length optimization provides a scalable strategy for improving photon yield, spectral control, and operational stability in compact laser-plasma-accelerator-driven $$\gamma$$ -ray sources.

Tsai, Hai-En↗
DOE OSTI2016

Is the detection of accelerated sea level rise imminent?

Global mean sea level rise estimated from satellite altimetry provides a strong constraint on climate variability and change and is expected to accelerate as the rates of both ocean warming and cryospheric mass loss increase over time. In stark contrast to this expectation however, current altimeter products show the rate of sea level rise to have decreased from the first to second decades of the altimeter era. Here, a combined analysis of altimeter data and specially designed climate model simulations shows the 1991 eruption of Mt Pinatubo to likely have masked the acceleration that would have otherwise occurred. This masking arose largely from a recovery in ocean heat content through the mid to late 1990 s subsequent to major heat content reductions in the years following the eruption. As a result, a consequence of this finding is that barring another major volcanic eruption, a detectable acceleration is likely to emerge from the noise of internal climate variability in the coming decade.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Capturing Structural Dynamics in Crystalline Silicon Using Chirped Electrons from a Laser Wakefield Accelerator

Recent progress in laser wakefield acceleration has led to the emergence of a new generation of electron and X-ray sources that may have enormous benefits for ultrafast science. These novel sources promise to become indispensable tools for the investigation of structural dynamics on the femtosecond time scale, with spatial resolution on the atomic scale. Here in this paper, we demonstrate the use of laser-wakefield-accelerated electron bunches for time-resolved electron diffraction measurements of the structural dynamics of single-crystal silicon nano-membranes pumped by an ultrafast laser pulse. In our proof-of-concept study, we resolve the silicon lattice dynamics on a picosecond time scale by deflecting the momentum-time correlated electrons in the diffraction peaks with a static magnetic field to obtain the time-dependent diffraction efficiency. Further improvements may lead to femtosecond temporal resolution, with negligible pump-probe jitter being possible with future laser-wakefield-accelerator ultrafast-electron-diffraction schemes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enhanced reactivity at the oil–water interface accelerates the synthesis of zymonic acid in microemulsions

Chemical reactions in microscale compartments, such as aerosols and emulsions, can exhibit significantly faster reaction rates relative to macroscale containers. This enhancement in chemistry is often due to the elevated importance of surfaces as reaction vessels are reduced to picoliter volumes. While most studies have focused on the air-water interface of droplets, there are comparably fewer studies of reactions in micron-scale aqueous solutions encapsulated by oil. Here we investigate the condensation reaction of pyruvic acid (PA) to form zymonic acid (ZA) and water. Using microfluidics and optical trapping, chemical kinetics are measured in monodisperse micron-sized emulsion droplets in situ via Raman spectroscopy. Relative to a macroscopic bulk solution, which exhibits little to no reaction over many days, we find efficient production of ZA over the same time period. A kinetic model is developed to elucidate the role of the interface in accelerating the microdroplet reaction kinetics. After quantifying the surface partitioning of PA from interfacial tension measurements, the rate coefficient for the condensation reaction at the oil-water interface is determined to be 1.8 × 10-2 M-1 s-1. This rate coefficient is estimated to be 105 larger than the reaction rate in bulk aqueous solutions. Compared to previous studies of accelerated ZA formation at the air-water interface on nanodroplets, we find that the reaction at the oil-water interface is 20 times more efficient. Despite this difference, the overall ZA formation rate in emulsions is significantly slower than in the same-sized aerosols, which arises from the weaker partitioning of PA to the oil-aqueous relative to air-water interface. These results highlight the interplay between interfacial partitioning and reactivity in accelerating chemistry in microcompartments and provides new insights into how interfacial composition influences condensation reactions.

Wallace, Brandon J↗
DOE OSTI2017

How anomalous resistivity accelerates magnetic reconnection

Whether turbulence induced anomalous resistivity (AR) can facilitate a fast magnetic reconnection in collisionless plasma is a subject of active debate for decades. Recent space observations suggest that the reconnection rate can be higher than the Hall-reconnection rate and turbulent dissipation is required. In this paper, using particle-in-cell simulations, we present a case study of how AR produced by Buneman instability accelerates magnetic reconnection. We first show that the AR/drag produced by Buneman instability in a thin electron current layer (1) can dissipate magnetic energy stored in the current layer through dissipation of the kinetic energy of electron beams; (2) the inhomogeneous drag caused by wave couplings spontaneously breaks the magnetic field lines and causes impulsive fast non-Hall magnetic reconnection on electron-scales with a mean rate reaching of 0.6 V A . We then show that a Buneman instability driven by intense electron beams around the x-point in a 3D magnetic reconnection significantly enhances the dissipation of the magnetic energy. Electron-scale magnetic reconnections driven by the inhomogeneous drag around the x-line enhance the reconnection electric field and the in-plane perpendicular magnetic field. About 40% of the released magnetic energy is converted into electron thermal energy by AR while 50% is converted into kinetic energy of the electron beams through the acceleration by the reconnection electric field. The enhanced magnetic energy dissipation is balanced by a net Poynting flux in-flow. About 10% of the released magnetic energy is brought out by an enhanced Poynting flux out-flow. Furthermore these results suggest that AR with sufficient intensity and electron-scale inhomogeneity can significantly accelerate magnetic reconnection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Scaling methods for accelerating kinetic Monte Carlo simulations of chemical reaction networks

Various kinetic Monte Carlo algorithms become inefficient when some of the population sizes in a system are large, which gives rise to a large number of reaction events per unit time. In this work, we present a new acceleration algorithm based on adaptive and heterogeneous scaling of reaction rates and stoichiometric coefficients. The algorithm is conceptually related to the commonly used idea of accelerating a stochastic simulation by considering a subvolume λΩ (0 < λ < 1) within a system of interest, which reduces the number of reaction events per unit time occurring in a simulation by a factor 1/λ at the cost of greater error in unbiased estimates of first moments and biased overestimates of second moments. Our new approach offers two unique benefits. First, scaling is adaptive and heterogeneous, which eliminates the pitfall of overaggressive scaling. Second, there is no need for an a priori classification of populations as discrete or continuous (as in a hybrid method), which is problematic when discreteness of a chemical species changes during a simulation. The method requires specification of only a single algorithmic parameter, N c , a global critical population size above which populations are effectively scaled down to increase simulation efficiency. The method, which we term partial scaling, is implemented in the open-source BioNetGen software package. We demonstrate that partial scaling can significantly accelerate simulations without significant loss of accuracy for several published models of biological systems. Finally, these models characterize activation of the mitogen-activated protein kinase ERK, prion protein aggregation, and T-cell receptor signaling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Direct laser acceleration of electrons in the plasma bubble by tightly focused laser pulses

We present an analytical theory that reveals the importance of the longitudinal laser electric field in the course of the resonant acceleration of relativistic electrons by a tightly confined laser beam. It is shown that this laser field component always counteracts the transverse one and effectively decreases the final energy gain of electrons via the direct laser acceleration (DLA) mechanism. This effect is demonstrated by carrying out particle-in-cell simulations of the DLA of the electrons injected into the accelerating phase of the plasma wake. It is shown that the electron energy gain from the wakefield is substantially compensated by the quasiresonant energy loss to the longitudinal laser field component. The analytically obtained scalings and estimates are in good agreement with the results of the numerical simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

GronOR: Massively Parallel and GPU-Accelerated Non-Orthogonal Configuration Interaction for Large Molecular Systems

GronOR is a program package for non-orthogonal configuration interaction calculations for an electronic wave function built in terms of anti-symmetrized products of multi-configuration molecular fragment wave functions. The two-electron integrals that have to be processed may be expressed in terms of atomic orbitals or in terms of an orbital basis determined from the molecular orbitals of the fragments. The code has been specifically designed for execution on distributed memory massively parallel and Graphics Processing Unit (GPU)-accelerated computer architectures, using an MPI+OpenACC/OpenMP programming approach. The task-based execution model used in the implementation allows for linear scaling with the number of nodes on the largest pre-exascale architectures available, provides hardware fault resiliency, and enables effective execution on systems with distinct central processing unit-only and GPU-accelerated partitions. The code interfaces with existing multi-configuration electronic structure codes that provide optimized molecular fragment orbitals, configuration interaction coefficients, and the required integrals. Algorithm and implementation details, parallel and accelerated performance benchmarks, and an analysis of the sensitivity of the accuracy of results and computational performance to thresholds used in the calculations are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗