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DOE OSTI2023

Second Target Station Project (CHESS Technical Report)

CHESS is a direct geometry neutron spectrometer designed to detect and analyze weak signals intrinsic to small cross-sections (e.g., small mass, small magnetic moments or neutron absorbing materials). This instrument is optimized to enable unprecedented characterization of quantum materials, spin liquids, thermoelectric and battery materials, liquids, and soft matter. The ability to simultaneously measure dynamic processes over a wide energy range for very small samples will make CHESS the spectrometer of choice for the initial exploration of new materials. The broad dynamic range will also be well matched to measurements of relaxation processes and excitations in soft and biological matter. The 15 Hz repetition rate of STS enables use of multiple incident energies within a single source pulse, greatly expanding the information gained in a single experiment. An essential feature of CHESS is the capability for polarization analysis to separate nuclear from magnetic scattering or coherent from incoherent scattering in hydrogenous materials, and better understanding spin-anisotropic correlations. This instrument will employ advanced sample environments such as high-pressure cells, dilution refrigerators, high field cryo-magnets and polarization devices, as well as combinations of these, to solve problems at the forefront of materials research. CHESS will be one of the flagship spectrometers of the Second Target Station (STS), providing world leading capabilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Scaling of Imbibition Front Dynamics in Heterogeneous Porous Media

Here we report a quantitative study on the dynamics of countercurrent imbibition in fractured rock samples with the application of CO 2 geosequestration, as the rock matrix is saturated with CO 2 and brine exists in the adjacent microfracture. Direct pore-scale simulations of spontaneous and forced imbibition in a three-dimensional heterogeneous porous matrix enable us to capture the effect of microscopic properties on the imbibition dynamics as these pore-level descriptions are ignored in the existing coarse-grained models. We have established new scaling classes for the propagation of the center of mass of the imbibition front and fluid-fluid interface broadening. It has become evident that the wettability is a major factor which leads to anomalies in these scaling laws. While the governing capillarity under the water-wet condition induces fast roughening dynamics of the interface, the adverse effect of capillary pressure under the intermediate-wet condition leads to a damping effect on the imbibition front fluctuations.

58 GEOSCIENCES↗

DOE OSTI2023

The Concentration–Mass relation of massive, dynamically relaxed galaxy clusters: agreement between observations and ΛCDM simulations

ABSTRACT The relationship linking a galaxy cluster’s total mass with the concentration of its mass profile and its redshift is a fundamental prediction of the Cold Dark Matter (CDM) paradigm of cosmic structure formation. However, confronting those predictions with observations is complicated by the fact that simulated clusters are not representative of observed samples where detailed mass profile constraints are possible. In this work, we calculate the symmetry-peakiness-alignment (SPA) morphology metrics for maps of X-ray emissivity from the three hundred project hydrodynamical simulations of galaxy clusters at four redshifts, and thereby select a sample of morphologically relaxed, simulated clusters, using observational criteria. These clusters have on average earlier formation times than the full sample, confirming that they are both morphologically and dynamically more relaxed than typical. We constrain the concentration–mass–redshift relation of both the relaxed and complete sample of simulated clusters, assuming power-law dependences on mass (κm) and 1 + z (κζ), finding κm = −0.12 ± 0.07 and κζ = −0.27 ± 0.19 for the relaxed subsample. From an equivalently selected sample of massive, relaxed clusters observed with Chandra, we find κm = −0.12 ± 0.08 and κζ = −0.48 ± 0.19, in good agreement with the simulation predictions. The simulated and observed samples also agree well on the average concentration at a pivot mass and redshift providing further validation of the ΛCDM paradigm in the properties of the largest gravitationally collapsed structures observed. This also represents the first clear detection of decreasing concentration with redshift, a longstanding prediction of simulations in data.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2014

Land Surface Microwave Emissivity Dynamics: Observations, Analysis and Modeling

Land surface microwave emissivity affects remote sensing of both the atmosphere and the land surface. The dynamical behavior of microwave emissivity over a very diverse sample of land surface types is studied. With seven years of satellite measurements from AMSR-E, we identified various dynamical regimes of the land surface emission. In addition, we used two radiative transfer models (RTMs), the Community Radiative Transfer Model (CRTM) and the Community Microwave Emission Modeling Platform (CMEM), to simulate land surface emissivity dynamics. With both CRTM and CMEM coupled to NASA's Land Information System, global-scale land surface microwave emissivities were simulated for five years, and evaluated against AMSR-E observations. It is found that both models have successes and failures over various types of land surfaces. Among them, the desert shows the most consistent underestimates (by approx. 70-80%), due to limitations of the physical models used, and requires a revision in both systems. Other snow-free surface types exhibit various degrees of success and it is expected that parameter tuning can improve their performances.

Modeling↗

DOE OSTI2016

Modeling and simulation framework for dynamic strain localization in elasto-viscoplastic metallic materials subject to large deformations

This study describes a theoretical and computational framework for the treatment of adiabatic shear band formation in rate-sensitive polycrystalline metallic materials. From a computational perspective, accurate representation of strain localization behavior has been a long-standing challenge. In addition, the underlying physical mechanisms leading to the localization of plastic deformation are still not fully understood. The proposed framework is built around an enhanced-strain finite element formulation, designed to alleviate numerical pathologies known to arise in localization problems, by allowing a localization band of given finite width (weak discontinuity) to be embedded within individual elements. The mechanical threshold strength (MTS) model is used to represent the temperature and strain rate-dependent viscoplastic response of the material. This classical flow stress model employs an internal state variable to quantify the effect of dislocation structure evolution (work hardening and recovery). In light of growing evidence suggesting that the softening effect of dynamic recrystallization may play a significant role, alongside thermal softening, in the process of shear band formation and growth, a simple dynamic recrystallization model is proposed and cast within the context of the MTS model with the aid of the aforementioned internal state variable. An initiation criterion for shear localization in rate and temperature-sensitive materials is introduced and used in the present context of high-rate loading, where material rate-dependence is pronounced and substantial temperature increases are achieved due to the dissipative nature of viscoplastic processes. In addition, explicit time integration is adopted to facilitate treatment of the dynamic problems under consideration, where strain rates in excess of 10 4 s –1 are typically attained. Two series of experiments are conducted on AISI 316L stainless steel, employing the commonly used top-hat sample geometry and the Split-Hopkinson Pressure Bar dynamic test system. Axi-symmetric finite element simulation results are compared to cross-sectional micrographs of recovered samples and experimental load–displacement results, in order to examine the performance of the proposed framework and demonstrate its effectiveness in treating the initiation and growth of adiabatic shear banding in dynamically loaded metallic materials. These comparisons demonstrate that thermal softening alone is insufficient to induce shear localization behaviors observed in some materials, such as stainless steel, and support the hypothesis that dynamic recrystallization and/or other softening mechanisms play an essential role in this process.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Driving and characterizing nucleation of urea and glycine polymorphs in water

Crystal nucleation is relevant across the domains of fundamental and applied sciences. However, in many cases, its mechanism remains unclear due to a lack of temporal or spatial resolution. To gain insights into the molecular details of nucleation, some form of molecular dynamics simulations is typically performed; these simulations, in turn, are limited by their ability to run long enough to sample the nucleation event thoroughly. To overcome the timescale limits in typical molecular dynamics simulations in a manner free of prior human bias, here, we employ the machine learning-augmented molecular dynamics framework “reweighted autoencoded variational Bayes for enhanced sampling (RAVE).” We study two molecular systems—urea and glycine—in explicit all-atom water, due to their enrichment in polymorphic structures and common utility in commercial applications. From our simulations, we observe multiple back-and-forth nucleation events of different polymorphs from homogeneous solution; from these trajectories, we calculate the relative ranking of finite-sized polymorph crystals embedded in solution, in terms of the free-energy difference between the finite-sized crystal polymorph and the original solution state. We further observe that the obtained reaction coordinates and transitions are highly nonclassical.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Nanoparticle dynamics in the spatial afterglows of nonthermal plasma synthesis reactors

Nonthermal plasma flow tube reactors are industrially scalable systems for the production of nanocrystal (NC) based materials and coatings. One key advantage of nonthermal plasma synthesis is the ability to both synthesize NCs and deposit films in a single reactor, as at the reactor outlet, NCs can be inertially deposited onto a target substrate. The size and morphology of deposited particles can substantially influence the film structure and function. Though NCs are typically near-spherical and monodispersed as-produced in plasma synthesis reactors, NC charge and growth dynamics can be altered substantially when NCs are sampled out of the plasma and through the spatial afterglow region, affecting deposition. Experiments have demonstrated changes of NC size and charge in the spatial afterglow; however, these dynamics remain unexplored and unexplained via theory and simulation. To address this, we developed a constant number Monte Carlo (CNMC) simulation model to examine the mechanisms of NC decharging and growth in the spatial afterglow of plasma flow tube reactors. Collisions between NC and plasma species, diffusive deposition, and electron desorption from NCs are incorporated in the CNMC simulation. The simulation results are specifically compared with previous experiments on Si NCs synthesized from a low pressure Ar-SiH 4 nonthermal plasma reactor. Furthermore, the experiment-model comparison shows that CNMC models can be implemented which accurately model NC size distribution evolution in a spatial afterglow. Simultaneously, results show that improved collision models, energetic species diffusion models, and electron desorption models will be necessary to accurately depict NC dynamics in spatial afterglows.

42 ENGINEERING↗

DOE OSTI2017

Effect of defects in the rare-earth sublattice of the Kondo insulator YbB{sub 12} on its spectral characteristics and magnetic susceptibility

The results of measuring the static and dynamic magnetic susceptibilities of several series of samples, which are based on the YbB{sub 12} Kondo insulator and are substituted in the rare-earth sublattice, are analyzed. Substitution is performed by nonmagnetic isoelectronic Lu ions; magnetic isoelectronic Tm ions; and nonisoelectronic nonmagnetic Y, Sc, and Zr ions. The static susceptibility is measured by a SQUID magnetometer in weak fields, and the dynamic susceptibility is determined from inelastic neutron scattering data. The magnetic properties are simulated using the spectral function found from neutron experimental data. A one-to-one correspondence is established between the influence of an impurity on the initial neutron spectrum and the temperature dependence of the static susceptibility. The results obtained allow one to analyze the relation between the magnetic properties and the electronic structure of the compounds of the given class.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS2002

Adaptive Identification and Control of Flow-Induced Cavity Oscillations

Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

Kegerise, M. A.↗

DOE OSTI2021

Structural and Valence State Modification of Cobalt in CoPt Nanocatalysts in Redox Conditions

Platinum is the primary catalyst for many chemical reactions in the field of heterogeneous catalysis. However, platinum is both expensive and rare. Therefore, it is advantageous to combine Pt with another metal to reduce cost while also enhancing stability. To that end, Pt is often combined with Co to form Co-Pt nanocrystals. However, dynamical restructuring effects that occur during reaction in Co-Pt ensembles can impact catalytic properties. In this study, model Co 2 Pt 3 nanoparticles supported on carbon were characterized during a redox cycle with two in situ approaches, namely X-ray absorption spectroscopy (XAS) and scanning transmission electron microscopy (STEM) using a multimodal microreactor. The sample was exposed to temperatures up to 500 °C under H 2 , and then to O 2 at 300 °C. Irreversible segregation of Co in the Co-Pt particles was seen during redox cycling and substantial changes of the oxidation state of Co were observed. After the H 2 treatment, a fraction of Co could not be fully reduced and incorporated into a mixed Co-Pt phase. Re-oxidation of the sample increased Co segregation, and the segregated material had a different valence state than in the fresh, oxidized sample. Furthermore, this in situ study describes dynamical restructuring effects in CoPt nano-catalysts at the atomic scale that are crucial to understand to improve the design of catalysts used in major chemical processes.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Girsanov's transformation based variance reduced Monte Carlo simulation schemes for reliability estimation in nonlinear stochastic dynamics

The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations. - Highlights: • The distance minimizing control forces minimize a bound on the sampling variance. • Establishing Girsanov controls via solution of a two-point boundary value problem. • Girsanov controls via Volterra's series representation for the transfer functions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Emergent Optical Phononic Modes upon Nanoscale Mesogenic Phase Transitions

The investigation of phononic collective excitations in soft matter systems at the molecular scale has always been challenging due to limitations of experimental techniques in resolving low-energy modes. Recent advances in inelastic X-ray scattering (IXS) enabled the study of such systems with unprecedented spectral contrast at meV excitation energies. In particular, it has become possible to shed light on the low-energy collective motions in materials whose morphology and phase behavior can easily be manipulated, such as mesogenic systems. The understanding of collective mode behavior with a Q-dependence is the key to implement heat management based on the control of a sample structure. The latter has great potential for a large number of energy-inspired innovations. As a first step toward this goal, we carried out high contrast IXS measurements on a liquid crystal sample, D7AOB, which exhibits solid-like dynamic features, such as the coexistence of longitudinal and transverse phononic modes. For the first time, we found that these terahertz phononic excitations persist in the crystal, smectic A, and isotropic phases. Furthermore, the intermediate smectic A phase is shown to support a van der Waals-mediated nonhydrodynamic mode with an optical-like phononic behavior. In conclusion, the tunability of the collective excitations at nanometer–terahertz scales via selection of the sample mesogenic phase represents a new opportunity to manipulate optomechanical properties of soft metamaterials.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Probability Density Function Control for Stochastic Nonlinear Systems using Monte Carlo Simulation

This paper presents a fast implementation framework of output probability density function (PDF) control for a class of stochastic nonlinear systems which are subjected to non-Gaussian noises. The statistical properties of the system outputs can be adjusted by shaping the dynamic output probability density function to track the reference stochastic distribution. However, the dynamic probability density function evolution is very difficult to obtain analytically even if the system model and the stochastic distributions of the noises are known. Motivated by Monte Carlo simulation, the dynamic probability density function can be estimated by sampling data which forms the contribution of this paper. In particular, the sampling points are generated following the stochastic distribution of the noise for each instant. These points go through the system would generate the histogram for system outputs, then the dynamic model can be established based on the dynamic histogram which reflects the randomness and the nonlinear dynamics of the investigated system. Based on the established model, the output probability density function tracking can be achieved and the simulation results and discussions show the effectiveness and benefits of the presented framework.

Zhang, Qichun↗

DOE OSTI2025

Phase-field modeling and experiments of dynamic fracture in single crystal quartz

Predicting the onset and characteristics of brittle fracture is important for a wide range of engineering and geological material applications. In this paper, we study important aspects of brittle fracture in α-quartz by phase-field modeling and experiments using a top-down approach. In the modeling framework, the work term in the Griffith energy balance is replaced with internal energy contributions that represent surface energy, thermal energy, and elastic strain energy stored in defects. This allows parametrization of individual energy contributions in terms of internal state variables and keeps track of energy partitioning after the onset of fracture. The path and history dependence of fracture is included in evolution laws for internal state variables, e.g., entropy evolution, while the energy remains a true potential. In the experimental part, dynamic compression experiments coupled with X-ray phase contrast imaging are performed on cube-like samples with a hole. In the top-down analysis, dynamic compression and three point bending experiments from the literature are simulated with the developed phase-field damage model. In conclusion, the fitted model highlights the strain rate, size, and stress state dependence of damage nucleation and evolution in single crystal α-quartz.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Extension of the Highly Mobile Membrane Mimetic to Transmembrane Systems through Customized in Silico Solvents

Typically, the mechanics of the protein–lipid interactions of transmembrane proteins are difficult to capture with conventional atomic molecular dynamics, due to the slow lateral diffusion of lipids restricting sampling to states near the initial membrane configuration. The highly mobile membrane mimetic (HMMM) model accelerates lipid dynamics by modeling the acyl tails nearest to the membrane center as a fluid organic solvent while maintaining an atomic description of the lipid headgroups and short acyl tails. The HMMM has been applied to many peripheral protein systems; however, the organic solvent used to date caused deformations in transmembrane proteins by intercalating into the protein and disrupting interactions between individual side chains. We ameliorate the effect of the solvent on transmembrane protein structure through the development of two new in silico Lennard-Jones solvents. The parameters for the new solvents were determined through an extensive parameter search in order to match the bulk properties of alkanes in a highly simplified model. Using these new solvents, we substantially improve the insertion free energy profiles of 10 protein side chain analogues across the entire bilayer. Furthermore, we reduce the intercalation of solvent into transmembrane systems, resulting in native-like transmembrane protein structures from five different topological classes within a HMMM bilayer. The parametrization of the solvents, in addition to their computed physical properties, is discussed. By combining high lipid lateral diffusion with intact transmembrane proteins, we foresee the developed solvents being useful to efficiently identify membrane composition inhomogeneities and lipid binding caused by the presence of membrane proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1985

Some effects of digital sampling on orbiter flight control system operation

An entry dynamic stability ground test of the OV102 Space Shuttle Orbiter revealed some small amplitude oscillatory output of the flight control system which could have constrained flight of the STS-1 mission. These limit-cycle-type outputs were attributed to a combination of rigid body motion of the Orbiter on its landing gear and some interesting effects of its digital flight control system. These effects included frequency aliasing and phenomena associated with digital quantitization of low amplitude sensor signals. The digital effects suggest significant improvements possible in future designs.

Murray, S. V.↗

NASA NTRS2015

Airborne Lidar-Based Estimates of Tropical Forest Structure in Complex Terrain: Opportunities and Trade-Offs for REDD+

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. Results: We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (approx. 20 returns/sq m) data was highly accurate (mean signed error of 0.19 +/-0.97 m), while those derived from reduced-density datasets (8/sq m, 4/sq m, 2/sq m and 1/sq m) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4/sq m, the bias in height estimates translated into errors of 80-125 Mg/ha in predicted aboveground biomass. Conclusions: Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

Airborne lidar↗

NASA NTRS1998

Galaxy Cluster Masses at Moderate Redshifts

The masses of galaxy clusters are dominated by dark matter, and a robust determination of their masses has the potential of indicating how much dark matter exists on large scales in the universe, and the cosmological parameter Omega. X-ray observations of galaxy clusters provide a direct measure of both the gas mass in the intra-cluster medium, and also the total gravitating mass of the cluster. We used new and archival ROSAT observations to measure these quantities for a sample of intermediate redshift clusters which have also been subject to intensive dynamical studies, in order to compare the mass estimates from different methods. We used data from 14 of the CNOC cluster sample at 0.18 less than z less than 0.55 for this study. A direct comparison of dynamical mass estimates from Carlberg, Yee & Ellingson (1997) yielded surprisingly good results. The X-ray/dynamical mass ratios have a mean of 0.96+/- 0.10, indicating that for this sample, both methods are probably yielding very robust mass estimates. Comparison with mass estimates from gravitational lensing studies from the literature showed a small systematic with weak lensing estimates, and large discrepancies with strong lensing estimates. This latter is not surprising, given that these measurement are made close to the central core, where optical and X-ray estimates are less certain, and where substructure and the effects of individual galaxies will be more pronounced. These results are presented in Lewis, Ellingson, Morris/Carlberg, 1998, submitted to the Astrophysical Journal. (Note that Lewis is Ellingson's Ph.D. thesis, who received direct support from this grant and is using this investigation as part of his thesis.) Three additional papers are in preparation. The first provides a comparison of the mass profiles as measured in X- rays and in galaxy dynamics. These profiles are difficult to determine for individual clusters, and are subject to asphericity and other individual quirks of each cluster. However, a composite profile for each method will allow us to test our assumptions of hydrostatic/dynamical equilibrium in the sample as a whole. A second paper provides a more detailed look at the cluster MS0906+11, which is a merging system. A third paper authord with J. Mohr at U. Chicago will invetigate the size-temoerature relationship for intermediate redshift clusters and its impications on cluster formation and cosmology. Future work on these data will include comparisons of the cluster galaxy populations and the extent of the intra-cluster medium, and a more homogeneous analysis of gravitational lensing.

Ellingson, E.↗