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Results for “Structural order parameter”

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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A pectin methyltransferase modulates polysaccharide dynamics and interactions in Arabidopsis primary cell walls: Evidence from solid-state NMR

Plant cell walls contain cellulose embedded in matrix polysaccharides. Understanding carbohydrate structures and interactions is critical to the production of biofuel and biomaterials using these natural resources. Here we present a solid-state NMR study of cellulose and pectin in 13 C-labeled cell walls of Arabidopsis wild-type and mutant plants. Using 1D 13 C and 2D 13 C– 13 C correlation experiments, we detected a highly branched arabinan structure in qua2 and tsd2 samples, two allelic mutants for a pectin methyltransferase. Both mutants show close physical association between cellulose and the backbones of pectic homogalacturonan and rhamnogalacturonan-I. Relaxation and dipolar order parameters revealed enhanced microsecond dynamics due to polymer disorder in the mutants, but restricted motional amplitudes due to tighter pectin-cellulose associations. These molecular data shed light on polymer structure and packing in these two pectin mutants, helping to elucidate how pectin could influence cell wall architecture at the nanoscale, cell wall mechanics, and plant growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

On the new universality class in structurally disordered n -vector model with long-range interactions

We study a stability boundary of a region where nontrivial critical behavior of an n-vector model with long-range power-law decaying interactions is induced by the presence of a structural disorder (e.g., weak quenched dilution). This boundary is given by the marginal dimension of the order parameter nc dependent on space dimension, d, and a control parameter of the interaction decay, σ, below which the model belongs to the new dilution-induced universality class. Exploiting the Harris criterion and recent field theoretical renormalization group results for the pure model with long-range interactions, we get nc as a three loop ɛ = 2σ – d-expansion. We provide numerical values for nc applying series resummation methods. Our results show that not only the Ising systems (n = 1) can belong to the new disorder-induced long-range universality class at d = 2 and 3.

Physics↗
DOE OSTI2022

Quantum simulation of quantum phase transitions using the convex geometry of reduced density matrices

Transitions of many-particle quantum systems between distinct phases at absolute-zero temperature, known as quantum phase transitions, require an exacting treatment of particle correlations. Here in this work, we present a general quantum-computing approach to quantum phase transitions that exploits the geometric structure of reduced density matrices. While typical approaches to quantum phase transitions examine discontinuities in the order parameters, the origin of phase transitions—their order parameters and symmetry breaking—can be understood geometrically in terms of the set of two-particle reduced density matrices (2-RDMs). The convex set of 2-RDMs provides a comprehensive map of the quantum system including its distinct phases as well as the transitions connecting these phases. Because 2-RDMs can potentially be computed on quantum computers at nonexponential cost, even when the quantum system is strongly correlated, they are ideally suited for a quantum-computing approach to quantum phase transitions. We compute the convex set of 2-RDMs for a Lipkin-Meshkov-Glick spin model on IBM superconducting-qubit quantum processors. Even though computations are limited to few-particle models due to device noise, comparisons with a classically solvable 1000-particle model reveal that the finite-particle quantum solutions capture the key features of the phase transitions including the strong correlation and the symmetry breaking.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

SPT-SLIM: Line Intensity Mapping with the South Pole Telescope

Line-intensity mapping (LIM) at millimeter wavelengths is a powerful emerging probe of the large-scale structure of the Universe, but achieving meaningful constraints on cosmological parameters with LIM requires focal planes with orders of magnitudes more detectors than existing instruments. SPT-SLIM is an upcoming experiment to demonstrate LIM observations of CO at 0.5 < z < 2.0 using on-chip spectrometers with kinetic inductance detectors (KIDs), a new technology that enables scaling to the much larger arrays of detectors needed to probe cosmology. I will describe the overall experimental design and specific goals of SPT-SLIM. In addition, I will highlight results of the detector and readout electronics development for SPT-SLIM and the status of the camera integration and commissioning in the lab.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1981

Parameter estimation of large flexible aerospace structures with application to the control of the Maypole Deployable Reflector

Systems such as the Maypole deployable reflector have a distributed parameter nature. The flexible column and hoop structure and the circular antenna of 30-100 meter diameter which it supports are described by partial, rather than ordinary, differential equations. Progress completed in reduced order modelling andd controller design and digital parameter estimation and control is summarized. Topics covered include depolyment and on-orbit operation; quasi-static (steady state) operation; dynamic distributed parameter system; autoregressive moving average identification; frequency domain procedures; direct or implicit active control; adaptive observers; parameter estimation using a linear reinforcement learning factor; feedback control; and reduced order modeling for nonlinear systems.

Balas, M. J.↗
NASA NTRS1991

Optimal simultaneous control and structure design

Optimization-based control/structure design methodologies are presented for large space structures with the H2 cost function. The order and/or structure of the compensator can be chosen in advance. It is assumed that the compensator parameters can vary freely, but the structural parameters are constrained. In addition, the CSI model is presented. The problem is stated, and algorithms are developed in MATRIXx software. Finally, the tools that are developed are tested using an 11-beam truss example.

Harn, Ywh-Pyng↗
NASA NTRS1993

Proton irradiation on materials

A computer code is developed by utilizing a radiation transport code developed at NASA Langley Research Center to study the proton radiation effects on materials which have potential application in NASA's future space missions. The code covers the proton energy from 0.01 Mev to 100 Gev and is sufficient for energetic protons encountered in both low earth and geosynchronous orbits. With some modification, the code can be extended for particles heavier than proton as the radiation source. The code is capable of calculating the range, stopping power, exit energy, energy deposition coefficients, dose, and cumulative dose along the path of the proton in a target material. The target material can be any combination of the elements with atomic number ranging from 1 to 92, or any compound with known chemical composition. The generated cross section for a material is stored and is reused in future to save computer time. This information can be utilized to calculate the proton dose a material would receive in an orbit when the radiation environment is known. It can also be used to determine, in the laboratory, the parameters such as beam current of proton and irradiation time to attain the desired dosage for accelerated ground testing of any material. It is hoped that the present work be extended to include polymeric and composite materials which are prime candidates for use as coating, electronic components, and structure building. It is also desirable to determine, for ground testing these materials, the laboratory parameters in order to simulate the dose they would receive in space environments. A sample print-out for water subject to 1.5 Mev proton is included as a reference.

Chang, C. Ken↗
NASA NTRS1988

Overview of structural parameter identification for large space structures needs, concepts, limits, potential

Virtually all space structure mission requirements include control of vibration, position, and possibly shape. In order to satisfy their requirements it is necessary to know the dynamic characteristics of the structure. Therefore, a means must be developed to continuously determine a dynamic model, or changes in the model, and to appropriately adapt the controls to these changes. The detection and location of physical damage would also be a very beneficial characteristic of such a procedure. A discussion outlining the methods to perform On-Orbit Model Determination is presented.

Berman, Alex↗
DOE OSTI2021

Segregation competition and complexion coexistence within a polycrystalline grain boundary network

Interfacial segregation can stabilize grain structures and even lead to grain boundary complexion transitions. However, understanding of the complexity of such phenomena in polycrystalline materials is limited, as most studies focus on bicrystal geometries. In this work, we investigate interfacial segregation and subsequent complexion transitions in polycrystalline Cu-Zr alloys using hybrid Monte Carlo/molecular dynamics simulations. No significant change in the grain size or structure is observed upon Zr dopant addition to a pure Cu polycrystal at moderate temperature, where grain boundary segregation is the dominant behavior. Segregation within the boundary network is inhomogeneous, with some boundaries having local concentrations that are an order of magnitude larger than the global value and others having almost no segregation, and changes to physical parameters such as boundary free volume and energy are found to correlate with dopant concentration. Further, another alloy sample is investigated at a higher temperature to probe the occurrence of widespread transitions in interfacial structure, where a significant fraction of the originally ordered boundaries transition to amorphous complexions, demonstrating the coexistence of multiple complexion types, each with their own distribution of boundary chemical composition. Overall, this work highlights that interfacial segregation and complexion structure can be diverse in a polycrystalline network. Here, the findings shown here complement existing computational and experimental studies of individual interfaces and help pave the way for unraveling the complexity of interfacial structure in realistic microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Kohn–Sham accuracy from orbital-free density functional theory via Δ-machine learning

Here, we present a Δ-machine learning model for obtaining Kohn–Sham accuracy from orbital-free density functional theory (DFT) calculations. In particular, we employ a machine-learned force field (MLFF) scheme based on the kernel method to capture the difference between Kohn–Sham and orbital-free DFT energies/forces. We implement this model in the context of on-the-fly molecular dynamics simulations and study its accuracy, performance, and sensitivity to parameters for representative systems. We find that the formalism not only improves the accuracy of Thomas–Fermi–von Weizsäcker orbital-free energies and forces by more than two orders of magnitude but is also more accurate than MLFFs based solely on Kohn–Sham DFT while being more efficient and less sensitive to model parameters. We apply the framework to study the structure of molten Al 0.88 Si 0.12 , the results suggesting no aggregation of Si atoms, in agreement with a previous Kohn–Sham study performed at an order of magnitude smaller length and time scales.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2013

Analytic Theory of Titans Schumann Resonance: Constraints on Ionospheric Conductivity and Buried Water Ocean

This study presents an approximate model for the atypical Schumann resonance in Titan's atmosphere that accounts for the observations of electromagnetic waves and the measurements of atmospheric conductivity performed with the Huygens Atmospheric Structure and Permittivity, Wave and Altimetry (HASI-PWA) instrumentation during the descent of the Huygens Probe through Titan's atmosphere in January 2005. After many years of thorough analyses of the collected data, several arguments enable us to claim that the Extremely Low Frequency (ELF) wave observed at around 36 Hz displays all the characteristics of the second harmonic of a Schumann resonance. On Earth, this phenomenon is well known to be triggered by lightning activity. Given the lack of evidence of any thunderstorm activity on Titan, we proposed in early works a model based on an alternative powering mechanism involving the electric current sheets induced in Titan's ionosphere by the Saturn's magnetospheric plasma flow. The present study is a further step in improving the initial model and corroborating our preliminary assessments. We first develop an analytic theory of the guided modes that appear to be the most suitable for sustaining Schumann resonances in Titan's atmosphere. We then introduce the characteristics of the Huygens electric field measurements in the equations, in order to constrain the physical parameters of the resonating cavity. The latter is assumed to be made of different structures distributed between an upper boundary, presumably made of a succession of thin ionized layers of stratospheric aerosols spread up to 150 km and a lower quasi-perfect conductive surface hidden beneath the non-conductive ground. The inner reflecting boundary is proposed to be a buried water-ammonia ocean lying at a likely depth of 55-80 km below a dielectric icy crust. Such estimate is found to comply with models suggesting that the internal heat could be transferred upwards by thermal conduction of the crust, while convective processes cannot be ruled out.

TITAN↗
DOE OSTI2025

A phase-field fracture formulation for generalized standard materials: The interplay between thermomechanics and damage

Accurately modeling fracture of ductile materials poses open challenges in the field of computational mechanics due to the multiphysics nature of their failure processes. Integrating the interplay between thermodynamics and damage into ductile fracture models is vital for predicting critical failure modes. Here, in this paper, we develop a versatile phase-field (PF) framework for modeling ductile fracture, taking into account finite-strain elasto-plasticity. The framework stems from a variational formulation of constitutive relations for generalized standard materials (GSMs), whose response is described by a Helmholtz free energy and a dissipation pseudo-potential. Its variational structure is based on a minimum principle for a functional that expresses the sum of power densities for reversible and irreversible processes. By minimizing this functional with a constraint on a von Mises yield function, we derive the evolution equation for the equivalent plastic strain and an associative flow rule. This constrained optimization problem is analytically solved for a wide class of thermo-viscoplasticity models. The key innovations of the current work include (i) a cubic plastic degradation function that accounts for a non-vanishing damage-dependent yield stress, (ii) closed-form expressions of the Helmholtz free energy and dissipation pseudo-potential for three thermo-viscoplasticity models, (iii) an extended Johnson–Cook plasticity model with a nonlinear hardening law, and (iv) a plastic work heat source that depends on the plastic degradation function and a variable Taylor–Quinney (TQ) coefficient. The capabilities of the proposed framework are tested with the aid of four ductile fracture problems, including the Sandia Fracture Challenge. In each of these problems, we examine the evolution of relevant field variables such as the PF order parameter, the equivalent plastic strain, the temperature, and the internal power dissipation density, in addition to the overall structural response quantified by the force–displacement curve. These numerical studies demonstrate that the proposed framework effectively represents ductile fracture, yielding computational results that exhibit good agreement with experimental data.

36 MATERIALS SCIENCE↗
NASA NTRS1990

A simple analytic model for the evolution of captured galactic disks

The general analytic solution developed by Steinman-Cameron and Durisen and published in 1988 for the evolution of dissipative nonplanar disks is applied to captured galactic disks in model galaxies with nonspherical, scale-free, logarithmic gravitational potentials. Such potentials produce flat rotation curves, similar to those seen in real galaxies. In this case, the analytic solution yields a self-similar structure for the warps and twists that develop while the disks is settling. Being scale-free in a simple, analytic form, this solution is completely defined by only a few dimensionless fitting parameters. As a result, it can be utilized as a mathematical tool to fit settling disks in real galaxies. The minimum time it takes for a disk to settle into a steady state orientation is also a scale-free quantity when expressed in units of the precession period or the orbit period. For realistic parameters, settling times are on the order of one-half to two periods. The use of the time-dependent structure of settling disks as a probe of the three-dimensional mass distribution of the host galaxies, including dark halos, is discussed.

Steiman-Cameron, Thomas Y.↗
DOE OSTI2021

Borderline first-order magnetic phase transition in AlFe 2 B 2

The thermal evolution of lattice parameters coupled with heat capacity data provide insight into tailorable magnetism-structure attributes in the orthorhombic compound AlFe 2 B 2 that was synthesized with and without small additions of gallium. Temperature-dependent X-ray powder diffraction experiments conducted through the magnetic phase transition reveal that the a- and b-parameters of both samples increase with increasing temperature while the c-parameter decreases. While a weak volumetric thermal expansion is noted over a range of temperatures well below and above the magnetic phase transition, anomalous behavior was observed within the phase transition region itself to reveal a magnetostructural phase transition with borderline first-order character in the Ga-modified sample but of more second-order character in the Ga-free sample. It is established that the nearest-neighbor Fe-Fe interatomic distance within the (ab)-plane plays a dominant role in influencing the magneto-functional response of these compounds. The magnetocaloric properties are discussed in the context of temperature-induced changes of the interatomic bonding that are influenced by the hypothesized presence of iron antisite defects in the AlFe 2 B 2 lattice.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

A reliable algorithm for optimal control synthesis

In recent years, powerful design tools for linear time-invariant multivariable control systems have been developed based on direct parameter optimization. In this report, an algorithm for reliable optimal control synthesis using parameter optimization is presented. Specifically, a robust numerical algorithm is developed for the evaluation of the H(sup 2)-like cost functional and its gradients with respect to the controller design parameters. The method is specifically designed to handle defective degenerate systems and is based on the well-known Pade series approximation of the matrix exponential. Numerical test problems in control synthesis for simple mechanical systems and for a flexible structure with densely packed modes illustrate positively the reliability of this method when compared to a method based on diagonalization. Several types of cost functions have been considered: a cost function for robust control consisting of a linear combination of quadratic objectives for deterministic and random disturbances, and one representing an upper bound on the quadratic objective for worst case initial conditions. Finally, a framework for multivariable control synthesis has been developed combining the concept of closed-loop transfer recovery with numerical parameter optimization. The procedure enables designers to synthesize not only observer-based controllers but also controllers of arbitrary order and structure. Numerical design solutions rely heavily on the robust algorithm due to the high order of the synthesis model and the presence of near-overlapping modes. The design approach is successfully applied to the design of a high-bandwidth control system for a rotorcraft.

Vansteenwyk, Brett↗
DOE OSTI2023

Towards the extraction of the crystal cell parameters from pair distribution function profiles

The approach based on atomic pair distribution function (PDF) has revolutionized structural investigations by X-ray/electron diffraction of nano or quasi-amorphous materials, opening up the possibility of exploring short-range order. However, the ab initio crystal structural solution by the PDF is far from being achieved due to the difficulty in determining the crystallographic properties of the unit cell. A method for estimating the crystal cell parameters directly from a PDF profile is presented, which is composed of two steps: first, the type of crystal cell is inferred using machine-learning approaches applied to the PDF profile; second, the crystal cell parameters are extracted by means of multivariate analysis combined with vector superposition techniques. The procedure has been validated on a large number of PDF profiles calculated from known crystal structures and on a small number of measured PDF profiles. The lattice determination step has been benchmarked by a comprehensive exploration of different classifiers and different input data. The highest performance is obtained using the k -nearest neighbours classifier applied to whole PDF profiles. Descriptors calculated from the PDF profiles by recurrence quantitative analysis produce results that can be interpreted in terms of PDF properties, and the significance of each descriptor in determining the prediction is evaluated. The cell parameter extraction step depends on the cell metric rather than its type. Monometric, dimetric and trimetric cells have top-1 estimates that are correct 40, 20 and 5% of the time, respectively. Promising results were obtained when analysing real nanocrystals, where unit cells close to the true ones are found within the top-1 ranked solution in the case of monometric cells and within the top-6 ranked solutions in the case of dimetric cells, even in the presence of a crystalline impurity with a weight fraction up to 40%.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ice Phase Classification Made Easy with Score-Based Denoising

Accurate identification of ice phases is essential for understanding various physicochemical phenomena. However, such classification for structures simulated with molecular dynamics is complicated by the complex symmetries of ice polymorphs and thermal fluctuations. For this purpose, both traditional order parameters and data-driven machine learning approaches have been employed, but they often rely on expert intuition, specific geometric information, or large training data sets. In this work, we present an unsupervised phase classification framework that combines a score-based denoiser model with a subsequent model-free classification method to accurately identify ice phases. Further, the denoiser model is trained on perturbed synthetic data of ideal reference structures, eliminating the need for large data sets and labeling efforts. The classification step utilizes the smooth overlap of atomic position (SOAP) descriptors as the atomic fingerprint, ensuring Euclidean symmetries and transferability to various structural systems. Our approach achieves a remarkable 100% accuracy in distinguishing ice phases of test trajectories using only seven ideal reference structures of ice phases as model inputs. This demonstrates the generalizability of the score-based denoiser model in facilitating phase identification for complex molecular systems. The proposed classification strategy can be broadly applied to investigate structural evolution and phase identification for a wide range of materials, offering new insights into the fundamental understanding of water and other complex systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗