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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Ferroelectric domain inversion and its stability in lithium niobate thin film on insulator with different thicknesses

Ferroelectric domain inversion and its effect on the stability of lithium niobate thin films on insulator (LNOI) are experimentally characterized. Two sets of specimens with different thicknesses varying from submicron to microns are selected. For micron thick samples (∼28 μm), domain structures are achieved by pulsed electric field poling with electrodes patterned via photolithography. No domain structure deterioration has been observed for a month as inspected using polarizing optical microscopy and etching. As for submicron (540 nm) films, large-area domain inversion is realized by scanning a biased conductive tip in a piezoelectric force microscope. A graphic processing method is taken to evaluate the domain retention. A domain life time of 25.0 h is obtained and possible mechanisms are discussed. Our study gives a direct reference for domain structure-related applications of LNOI, including guiding wave nonlinear frequency conversion, nonlinear wavefront tailoring, electro-optic modulation, and piezoelectric devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Controlling the spatio-temporal dose distribution during STEM imaging by subsampled acquisition: In-situ observations of kinetic processes in liquids

Subsampled image acquisition followed by image inpainting in the scanning transmission electron microscope (STEM) is a novel approach to control dose and increase the image frame rate during experiments, thereby allowing independent control of the spatial and temporal dose envelope during image acquisition. Here, subsampled imaging is shown to permit precise in-situ observations of the fundamental kinetic processes behind nucleation and growth of silver (Ag) nanoparticles from an aqueous solution. At high sampling-levels, nanoparticles can be observed with morphologies that are consistent with strong interface interactions, i.e. rafts and pillars, whereas at low sampling-levels, the particles exhibit regular spherical morphologies. The relative numbers of rafts/pillars and regular nanoparticles, their sizes and their incubation times can be attributed to local changes in the molar concentration of the Ag ions in the aqueous solution; higher sampling-levels significantly increase the reactants in the vicinity of the window, leading to rapid supersaturation and the precipitation on the window surface. These precisely controlled kinetics highlight subsampled imaging as a method by which the driving force for nucleation and growth (i.e the electron beam) can be disentangled from the spatial/temporal resolution of the observation in all in-situ experiments, providing a pathway to identify and quantify the importance of individual kinetic factors behind nucleation and growth in a wide variety of complex materialssystems and architectures.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Electronic structure theory on modeling short-range noncovalent interactions between amino acids

While short-range noncovalent interactions (NCIs) are proving to be of importance in many chemical and biological systems, these atypical bindings happen within the so-called van der Waals envelope and pose an enormous challenge for current computational methods. We introduce SNCIAA, a database of 723 benchmark interaction energies of short-range noncovalent interactions between neutral/charged amino acids originated from protein x-ray crystal structures at the “gold standard” coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory with a mean absolute binding uncertainty less than 0.1 kcal/mol. Subsequently, a systematic assessment of commonly used computational methods, such as the second-order Møller−Plesset theory (MP2), density functional theory (DFT), symmetry-adapted perturbation theory (SAPT), composite electronic-structure methods, semiempirical approaches, and the physical-based potentials with machine learning (IPML) on SNCIAA is carried out. It is shown that the inclusion of dispersion corrections is essential even though these dimers are dominated by electrostatics, such as hydrogen bondings and salt bridges. Overall, MP2, ωB97M-V, and B3LYP+D4 turned out to be the most reliable methods for the description of short-range NCIs even in strongly attractive/repulsive complexes. SAPT is also recommended in describing short-range NCIs only if the δMP2 correction has been included. The good performance of IPML for dimers at close-equilibrium and long-range conditions is not transferable to the short-range. We expect that SNCIAA will assist the development/improvement/validation of computational methods, such as DFT, force-fields, and ML models, in describing NCIs across entire potential energy surfaces (short-, intermediate-, and long-range NCIs) on the same footing.

Chemistry↗
DOE OSTI2019

Laser formation of luminescence bubble microstructures in polymer films

The results of laser-induced formation of luminescent structures on the surface of poly-2.2’-n-oxydiphenylene-5.5’-bis-benzimidazole films, obtained by the coating method from a formic acid solution, are presented. The structures are formed using cw 405-nm laser radiation with intensities of 10{sup 2} – 10{sup 4} W cm{sup –2}. It is shown (using methods of optical, atomic-force, and electron microscopy) that the structures formed on the surface are microbubble foam-like aggregations. Their formation is modelled as a sequence of the following processes: release of formic acid molecules, their condensation on matrix defects in the surface layer, and explosive boiling as a result of heating this layer of polymer film by the laser beam. The luminescence of these structures is due to the weakening of the concentration quenching from closely spaced luminescence centres in benzimidazole cycles during their emergence to the surface and the increase in the distance between them due to the extension on bubble aggregates on the surface. (interaction of laser radiation with matter. laser plasma)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Realistic operation of two residential cordwood-fired outdoor hydronic heater appliances—Part 3: Optical properties of black and brown carbon emissions

Residential biomass combustion is a source of carbonaceous aerosol. Inefficient combustion, particularly of solid fuels produces large quantities of black and brown carbon (BC and BrC). These particle types are important as they have noted effects on climate forcing and human health. One method of measuring these quantities is by measurement of aerosol light-absorption and scattering, which can be performed using an aethalometer and nephelometer, respectively. These instruments are widely deployed in the study of ambient air and are frequently used in air quality modeling and source apportionment studies. In this study, we will describe (1) a method for measuring primary BC and BrC emissions from two residential log-fired wood hydronic heaters and (2) the BC and BrC emission from these devices over a wide range of operating conditions, such as cold-starts, warm-starts, four different levels of output ranging from 15% to 100% maximum rated output, and periods of repeated cycling. The range in flue-gas BC concentrations, measured using an aethalometer at the 880 nanometer (nm) wavelength, were between 5.09 × 10 2 and 2.24 × 10 4 micrograms per cubic meter (µg/m 3 ) while the scattering coefficient of the flue-gas, measured by a nephelometer at 880 nm, ranged between 2.20 × 10 3 and 8.56 × 10 5 inverse megameters (Mm –1 ). The BrC concentrations, measured using the 370 nm wavelength of an aethalometer, were between 9.10 × 10 1 and 3.56 × 10 4 µg/m 3 . The calculated Angstrom Absorption Exponent (AAE) of the flue-gas aerosol ranged between 1.54 and 3.63. Performing a comparison between the measured BC concentration and an external particulate matter (PM) concentration showed that overall BC makes up roughly a quarter of the PM emitted by either of the two appliances. Further for both appliances, the cold-start and the test phase immediately following it had the highest BC and BrC concentrations, the highest measured scattering coefficient, as well as a low AAE.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Optical properties of hydrothermally synthesized Ti 3 C 2 T X MXene quantum dots and their application in biosensor

The remarkable properties of Ti 3 C 2 T X MXene quantum dots (MQDs) highlight their potential in diverse fields, including domains such as biocompatible nanoprobe, ion sensing, energy applications etc. Given their relevance in emerging technologies, a systematic study of their optical properties is crucial. MXene nanosheets were utilized in Acetylcholinesterase (AChE) based biosensors for the detection of organophosphate (OP) pesticides, this suggests there is significant potential for further development of electrochemical biosensor by incorporating MQDs in this field. The synthesis of MQDs has been achieved through various methods, either individually or in combination of methods, including hydrothermal, acoustic microfluidic, electrochemical, ball milling etc. Furthermore, we synthesized Ti 3 C 2 T X MQDs using hydrothermal method and characterized using atomic force microscopy, optical spectroscopy and cyclic voltammetry.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Normalizing Flows for Microscopic Many-Body Calculations: An Application to the Nuclear Equation of State

We report that normalizing flows are a class of machine learning models used to construct a complex distribution through a bijective mapping of a simple base distribution. We demonstrate that normalizing flows are particularly well suited as a Monte Carlo integration framework for quantum many-body calculations that require the repeated evaluation of high-dimensional integrals across smoothly varying integrands and integration regions. As an example, we consider the finite-temperature nuclear equation of state. An important advantage of normalizing flows is the ability to build highly expressive models of the target integrand, which we demonstrate enables precise evaluations of the nuclear free energy and its derivatives. Furthermore, we show that a normalizing flow model trained on one target integrand can be used to efficiently calculate related integrals when the temperature, density, or nuclear force is varied. This work will support future efforts to build microscopic equations of state for numerical simulations of supernovae and neutron star mergers that employ state-of-the-art nuclear forces and many-body methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Coupling 2D atomistic information to 3D kink-pair enthalpy models of screw dislocations in bcc metals

The kink-pair activation enthalpy is a fundamental parameter in the theory of plasticity of body-centered cubic (bcc) metals. It controls the thermally activated motion of screw dislocation at low and intermediate temperatures. While direct atomistic calculations of kink pairs on screw dislocations have reached a high degree of accuracy, they can only be practically performed using semiempirical interatomic force fields, as electronic structure methods have not yet reached the level of efficiency needed to capture the system sizes required to model kink-pair structures. In this context, an alternative approach based on standard three-dimensional elastic models, which are efficient but lack atomic-level information, coupled to a substrate potential that represents the underlying lattice, has been widely applied over the past few years. This class of methods, known as ‘line-on-substrate’ (LOS) models, uses the substrate potential to calculate the lattice contribution to the kink-pair energies. In this work, we introduce the stress dependence of the substrate potential into LOS models to evaluate its impact on kink-pair energies. In addition, we include asymmetric dislocation core energies as an extra descriptor of the dislocation character. This asymmetry is also elevated to the continuum level by adding core energies to the general LOS formulation and used to explain potential energy differences known to exist between left and right kinks in bcc metals. Finally, more importantly, by matching the total LOS energies to previously calculated atomistic energies of kink-pair configurations, we issue a rule to establish the value of the so-called core width in nonsingular elasticity theories and reduce its arbitrariness as a mathematical construct.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Structure and physicochemical properties of thin film photosemiconductor cells based on porphine derivatives

Photosemiconductor thin films based on two organic porphine derivatives have been investigated. These compounds have different pendent groups; the film morphology, along with the specific fabrication technique, is determined to a great extent by these groups. The films have been fabricated by vacuum sputtering and using the Langmuir−Schaefer method. According to the atomic force microscopy (AFM) data, the Langmuir−Schaefer films are more homogeneous than the sputtered ones. It is shown that the sputtered films based on substituted porphine have a looser stacking than the initial analog. A spectroscopy study revealed a bathochromic shift of the Soret band in the Langmuir−Schaefer films–sputtered films series. This shift is explained by the increase in the concentration and size of molecular aggregates in sputtered films. It is shown that a polycrystalline C{sub 60} fullerene film deposited onto an amorphous substituted porphine layer improves the photoelectric characteristics of the latter. Both the time stability of the photodiode structure and its ampere‒watt sensitivity increase (by a factor of 10 in the transition regime). The steady-state current does not change. The effect of polarity reversal of the photovoltaic signal is observed in a planar C{sub 60}‒substituted metalloporphine heterostructure, which is similar to the pyroelectric effect. The polarity reversal can be explained by the contribution of the trap charge and discharge current at the interface between the amorphous photosemiconductor and crystalline photosemiconductor to the resulting photoelectric current.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Possibilities of Using Combined Optical and AFM Investigations of Albumin

The results of a complex study of 10% aqueous solution of human serum albumin using methods of optical and atomic force microscopy have been presented. The fine structure of main structures of albumin facies (vitreous matrix and concretions) has been revealed and some observed structural effects have been interpreted from the viewpoint of polymer materials science.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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 OSTI2024

Numerical challenges in modeling gravothermal collapse in Self-Interacting Dark Matter halos

When dark matter has a large cross section for self scattering, halos can undergo a process known as gravothermal core collapse, where the inner core rapidly increases in density and temperature. To date, several methods have been used to implement Self-Interacting Dark Matter (SIDM) in N-body codes, but there has been no systematic study of these different methods or their accuracy in the core-collapse phase. In this paper, we compare three different numerical implementations of SIDM, including the standard methods from the GIZMO and Arepo codes, by simulating idealized dwarf halos undergoing significant dark matter self interactions (σ/m = 50 cm 2 /g). When simulating these halos, we also vary the mass resolution, time-stepping criteria, and gravitational force-softening scheme. The various SIDM methods lead to distinct differences in a halo's evolution during the core-collapse phase, as each results in spurious scattering rate differences and energy gains/losses. The use of adaptive force softening for gravity can lead to numerical heating that artificially accelerates core collapse, while an insufficiently small simulation time step can cause core evolution to stall or completely reverse. Additionally, particle numbers must be large enough to ensure that the simulated halos are not sensitive to noise in the initial conditions. Even for the highest-resolution simulations tested in this study (10 6 particles per halo), we find that variations of order 10% in collapse time are still present. Here, the results of this work underscore the sensitivity of SIDM modeling on the choice of numerical implementation and motivate a careful study of how these results generalize to halos in a cosmological context.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Hybrid immersed interface-immersed boundary methods for AC dielectrophoresis

Dielectrophoresis, a nonlinear electrokinetic transport mechanism, has become popular in many engineering applications including manipulation, characterization and actuation of biomaterials, particles and biological cells. In this paper, we present a hybrid immersed interface–immersed boundary method to study AC dielectrophoresis where an algorithm is developed to solve the complex Poisson equation using a real variable formulation. An immersed interface method is employed to obtain the AC electric field in a fluid media with suspended particles and an immersed boundary method is used for the fluid equations and particle transport. The convergence of the proposed algorithm as well as validation of the hybrid scheme with experimental results is presented. In this paper, the Maxwell stress tensor is used to calculate the dielectrophoretic force acting on particles by considering the physical effect of particles in the computational domain. Thus, this study eliminates the approximations used in point dipole methods for calculating dielectrophoretic force. A comparative study between Maxwell stress tensor and point dipole methods for computing dielectrophoretic forces are presented. The hybrid method is used to investigate the physics of dielectrophoresis in microfluidic devices using an AC electric field. The numerical results show that with proper design and appropriate selection of applied potential and frequency, global electric field minima can be obtained to facilitate multiple particle trapping by exploiting the mechanism of negative dielectrophoresis. Our numerical results also show that electrically neutral particles form a chain parallel to the applied electric field irrespective of their initial orientation when an AC electric field is applied. This proposed hybrid numerical scheme will help to better understand dielectrophoresis and to design and optimize microfluidic devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

RACORO continental boundary layer cloud investigations. Part I: Case study development and ensemble large-scale forcings

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60-hour case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in-situ measurements from the RACORO field campaign and remote-sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be ~0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing datasets are derived from the ARM variational analysis, ECMWF forecasts, and a multi-scale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in 'trial' large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Time Series Classification for Locating Forced Oscillation Sources

Here, this article presents a machine learning based time-series classification method for using synchrophasor measurements to locate the source of forced oscillation (FO) for fast disturbance removal. First, multivariate time series (MTS) matrices are constructed by the most informative measurements selected by sequential feature selection from each power plant. Then, the Mahalanobis matrix is trained such that the Mahalanobis distance between the MTSs from the same class (i.e., with the same FO source location) are minimized and from different classes (i.e., with different FO source locations) are maximized. This allows MTSs to be classified by classifiers with class membership corresponding to the location of each FO source. To meet the runtime requirements of online matching, class templates are constructed to reduce data size and improve matching efficiency. To account for uncertainty in identifying the exact beginning of an FO event, dynamic time warping is used to align the out-of-sync MTSs. IEEE 39bus and WECC 179bus systems are used for algorithm development and validation. Simulation results demonstrate that the algorithm meets online operation runtime requirement with high accuracy using misaligned data sets.

42 ENGINEERING↗
DOE OSTI2015

Cross-type optical separation of elastic oblate capsules in a uniform flow

The dynamic behavior of an elastic capsule with an initially oblate spheroidal shape during cross-type optical separation was numerically investigated. The penalty immersed boundary method was adopted for the fluid-membrane interaction, and the optical force calculation was conducted by using the ray optics method including the ray-surface intersection algorithm. The oblate elastic capsule of b/a = 0.5 with different surface Young's moduli and different initial inclination angles was considered. The oblate capsule with higher surface Young's moduli was less deformed, and was more migrated for each initial inclination angle. Unlike the oblate rigid particle, the initially inclined capsules with moderate inclination angles were similarly migrated since the oblate elastic capsule was deformed during rotation near the laser beam axis. The oblate capsules can be separated according to the surface Young's modulus, except for nearly non-inclined capsules. As the fluid velocity decreased, the migration distance increased. The maximum deformation parameter was insensitive to the fluid velocity. Furthermore, a new dimensionless number (S{sub ec}) was introduced to predict the migration distance of the oblate elastic capsule.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Protein Molecular Dynamics Simulations with Approximate QM: What Can We Learn?

Classical force fields are essential for computer simulations of proteins and are typically parameterized to reproduce secondary and tertiary structure of isolated proteins. However, while protein-protein interactions are ubiquitous in nature, they are not considered in parameterization efforts and are far less understood than isolated proteins. A better characterization of intermolecular interactions is widely recognized as a key to revolutionizing drug and therapeutic developments with high-throughput computational screening. Urgently needed is a critical assessment of the performance of modern protein force fields against first-principles electronic structure methods and experiments. In a daring step toward this goal, we here describe a comparison of peptide folding dynamics as predicted by a molecular mechanics force field on the one hand and by an approximate electronic structure quantum mechanical (QM) method based on density-functional tight-binding (DFTB) on the other. We further compare the dynamics from straightforward DFTB simulations with a near-linear scaling version of DFTB for massively parallel computation based on the fragment molecular orbital (FMO-DFTB) method. We illustrate differences between the phenomenology of the folding dynamics from these three methods for a small model peptide, as well as charge polarization and dynamic fluctuations, point out possible correlations and implications for force field developers, and discuss the lessons learned that might become applicable to future predictive high-throughput computer screening for personalized neoantigen cancer therapy.

Irle, Stephan↗
DOE OSTI2023

Uncertainty-aware molecular dynamics from Bayesian active learning for phase transformations and thermal transport in SiC

Abstract Machine learning interatomic force fields are promising for combining high computational efficiency and accuracy in modeling quantum interactions and simulating atomistic dynamics. Active learning methods have been recently developed to train force fields efficiently and automatically. Among them, Bayesian active learning utilizes principled uncertainty quantification to make data acquisition decisions. In this work, we present a general Bayesian active learning workflow, where the force field is constructed from a sparse Gaussian process regression model based on atomic cluster expansion descriptors. To circumvent the high computational cost of the sparse Gaussian process uncertainty calculation, we formulate a high-performance approximate mapping of the uncertainty and demonstrate a speedup of several orders of magnitude. We demonstrate the autonomous active learning workflow by training a Bayesian force field model for silicon carbide (SiC) polymorphs in only a few days of computer time and show that pressure-induced phase transformations are accurately captured. The resulting model exhibits close agreement with both ab initio calculations and experimental measurements, and outperforms existing empirical models on vibrational and thermal properties. The active learning workflow readily generalizes to a wide range of material systems and accelerates their computational understanding.

36 MATERIALS SCIENCE↗