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At least 793 records · Page 44

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DOE OSTI2021

Chemical Passivation of Crystalline Si by Al 2 O 3 Deposited Using Atomic Layer Deposition: Implications for Solar Cells

The atomistic-level mechanism for the chemical passivation of the monocrystalline Si (c-Si) surface with thermally annealed Al 2 O 3 was studied using in situ infrared spectroscopy and photoconductance decay measurements. Al 2 O 3 was deposited on high-lifetime, float-zone c-Si substrates using atomic layer deposition (ALD) from trimethylaluminum (TMA), and H 2 O or O 3 . Surface-sensitive attenuated total reflection Fourier transform infrared spectroscopy was used to monitor the c-Si/Al 2 O 3 interface, as well as the bulk of the Al 2 O 3 film during the entire process. Our results show that some surface Si–H bonds are preserved after the ALD of Al 2 O 3 on H-terminated Si. During the annealing step at 400 °C, restructuring occurs at the c-Si/Al 2 O 3 interface to form interfacial SiO x . Isotope labeling was used to differentiate interfacial SiD bonds on the c-Si surface from H incorporated in Al 2 O 3 . Within the sensitivity of our infrared setup (~10 13 cm –2 ), we did not observe any net migration of atomic H or D from Al 2 O 3 to the c-Si/Al 2 O 3 interface. To isolate the effects of chemical and field-effect passivation of Al 2 O 3 thin films, we carried out surface passivation studies on c-Si/SiO 2 /Al 2 O 3 stacks. We also annealed these stacks in different atmospheres to test the influence of annealing atmospheres on the chemical passivation of c-Si by Al 2 O 3 and observed that O 2 -containing atmosphere led to the best surface chemical passivation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1987

The Jeffcott equations in nonlinear rotordynamics

The Jeffcott equations are a system of coupled differential equations representing the behavior of a rotating shaft. This is a simple model which allows investigation of the basic dynamic behavior of rotating machinery. Nolinearities can be introduced by taking into consideration deadband, side force, and rubbing, among others. The properties of the solutions of the Jeffcott equations with deadband are studied. In particular, it is shown how bounds for the solution of these equations can be obtained from bounds for the solutions of the linearized equations. By studying the behavior of the Fourier transforms of the solutions, we are also able to predict the onset of destructive vibrations. These conclusions are verified by means of numerical solutions of the equations, and of power spectrum density (PSD) plots. This study offers insight into a possible detection method to determine pump stability margins during flight and hot fire tests, and was motivated by the need to explain a phenomenon observed in the development phase of the cryogenic pumps of the Space Shuttle, during hot fire ground testing; namely, the appearance of vibrations at frequencies that could not be accounted for by means of linear models.

Zalik, R. A.↗

NASA NTRS1997

Enhanced Multiobjective Optimization Technique for Comprehensive Aerospace Design

A multidisciplinary design optimization procedure which couples formal multiobjectives based techniques and complex analysis procedures (such as computational fluid dynamics (CFD) codes) developed. The procedure has been demonstrated on a specific high speed flow application involving aerodynamics and acoustics (sonic boom minimization). In order to account for multiple design objectives arising from complex performance requirements, multiobjective formulation techniques are used to formulate the optimization problem. Techniques to enhance the existing Kreisselmeier-Steinhauser (K-S) function multiobjective formulation approach have been developed. The K-S function procedure used in the proposed work transforms a constrained multiple objective functions problem into an unconstrained problem which then is solved using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. Weight factors are introduced during the transformation process to each objective function. This enhanced procedure will provide the designer the capability to emphasize specific design objectives during the optimization process. The demonstration of the procedure utilizes a computational Fluid dynamics (CFD) code which solves the three-dimensional parabolized Navier-Stokes (PNS) equations for the flow field along with an appropriate sonic boom evaluation procedure thus introducing both aerodynamic performance as well as sonic boom as the design objectives to be optimized simultaneously. Sensitivity analysis is performed using a discrete differentiation approach. An approximation technique has been used within the optimizer to improve the overall computational efficiency of the procedure in order to make it suitable for design applications in an industrial setting.

Chattopadhyay, Aditi↗

NASA NTRS1996

From Individuals to Epidemics

Heterogeneous mixing fundamentally changes the dynamics of infectious diseases; finding ways to incorporate it into models represents a critical challenge. Phenomenological approaches are deficient in their lack of attention to underlying processes; individual-based models, on the other hand, may obscure the essential interactions in a sea of detail. The challenge then is to find ways to bridge these levels of description, starting from individual-based models and deriving macroscopic descriptions from them that retain essential detail, and filter out the rest. In this paper, attempts to achieve this transformation are described for a class of models where non-random mixing arises from the spatial localization of interactions. In general, the epidemic threshold is found to be larger owing to spatial localization than for a homogeneous mixing population. An improved estimate of the dynamics is developed by the use of moment equations, and a simple estimate of the threshold in terms of a 'dyad heuristic'. For more general models in which local infection is not described by mass action, the connection with related partial differential equations is investigated.

Levin, Simon A.↗

DOE OSTI2026

Application of Ibuprofen Sodium Dihydrate for Thermochemical Energy Storage

Thermochemical energy storage (TCES) offers a transformative approach to address grid instability by harnessing reversible chemical reactions for efficient heat storage and release. Here, we introduce pharmaceutical organic salt hydrates as a class of materials with exceptional performance for low-grade waste heat recovery. We demonstrate ibuprofen sodium dihydrate (ISD) as an example organic hydrate exhibiting a dehydration temperature range of 60-110 °C and a remarkable dehydration enthalpy of up to 59.5 kJ/mol of water, ideally suited for capturing industrial and residential waste heat. Using rigorous multimodal characterization, including thermogravimetric analysis, differential scanning calorimetry, in-situ FTIR, in-situ PXRD, and NMR, we demonstrate ISD's superior thermal, chemical, and structural stability over 150 hydration-dehydration cycles, achieving an unprecedented cycling efficiency of ~99.9%. Compared to conventional inorganic salt hydrates like strontium chloride hexahydrate and calcium oxalate monohydrate, ISD showcases enhanced durability without deliquescence or pulverization, even under high-humidity conditions. In-situ analyses confirm the transition from ISD to ibuprofen sodium anhydrous (ISA) proceeds with structural reorganization, thereby combining the dehydration mechanism with phase transitions, resulting in higher energy storage capacity. Microstructural analyses reveal that repeated water intercalation and structural transitions aid in creating significant porosity that enhances water transport kinetics, further improving the hydration/dehydration performance. By combining the phase change and chemical dehydration mechanisms, ISD paves the way for designing a new class of organic salt hydrates, offering tunable properties to meet diverse thermal energy storage demands and supporting sustainable grid resilience.

Thangaraj, Kavin C.↗

NASA NTRS2005

Foundations of Tensor Analysis for Students of Physics and Engineering With an Introduction to the Theory of Relativity

Tensor analysis is one of the more abstruse, even if one of the more useful, higher math subjects enjoined by students of physics and engineering. It is abstruse because of the intellectual gap that exists between where most physics and engineering mathematics leave off and where tensor analysis traditionally begins. It is useful because of its great generality, computational power, and compact, easy to use, notation. This paper bridges the intellectual gap. It is divided into three parts: algebra, calculus, and relativity. Algebra: In tensor analysis, coordinate independent quantities are sought for applications in physics and engineering. Coordinate independence means that the quantities have such coordinate transformations as to leave them invariant relative to a particular observer s coordinate system. Calculus: Non-zero base vector derivatives contribute terms to dynamical equations that correspond to pseudoaccelerations in accelerated coordinate systems and to curvature or gravity in relativity. These derivatives have a specific general form in tensor analysis. Relativity: Spacetime has an intrinsic geometry. Light is the tool for investigating that geometry. Since the observed geometry of spacetime cannot be made to match the classical geometry of Euclid, Einstein applied another more general geometry differential geometry. The merger of differential geometry and cosmology was accomplished in the theory of relativity. In relativity, gravity is equivalent to curvature.

Kolecki, Joseph C.↗

DOE OSTI2022

Single-stage gradient-based stellarator coil design: Optimization for near-axis quasi-symmetry

Here we present a new coil design paradigm for magnetic confinement in stellarators. Our approach directly optimizes coil shapes and coil currents to produce a vacuum quasi-symmetric magnetic field with a target rotational transform on the magnetic axis. This approach differs from the traditional two-stage approach in which first a magnetic configuration with desirable physics properties is found, and then coils to approximately realize this magnetic configuration are designed. The proposed single-stage approach allows us to find a compromise between confinement and engineering requirements, i.e., find easy-to-build coils with good confinement properties. Using forward and adjoint sensitivities, we derive derivatives of the physical quantities in the objective, which is constrained by a nonlinear periodic differential equation. In two numerical examples, we compare different gradient-based descent algorithms and find that incorporating approximate second-order derivative information through a quasi-Newton method is crucial for convergence. We also explore the optimization landscape in the neighborhood of a minimizer and find many directions in which the objective is mostly flat, indicating ample freedom to find simple and thus easy-to-build coils.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Neural network surrogate models for equations of state

Equation of state (EOS) data provide necessary information for accurate multiphysics modeling, which is necessary for fields such as inertial confinement fusion. Here, we suggest a neural network surrogate model of energy and entropy and use thermodynamic relationships to derive other necessary thermodynamic EOS quantities. We incorporate phase information into the model by training a phase classifier and using phase-specific regression models, which improves the modal prediction accuracy. Our model predicts energy values to 1% relative error and entropy to 3.5% relative error in a log-transformed space. Although sound speed predictions require further improvement, the derived pressure values are accurate within 10% relative error. Our results suggest that neural network models can effectively model EOS for inertial confinement fusion simulation applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Multislice forward modeling of coherent surface scattering imaging on surface and interfacial structures

To study nanostructures on substrates, surface-sensitive reflection-geometry scattering techniques such as grazing incident small angle X-ray scattering are commonly used to yield an averaged statistical structural information of the surface sample. Grazing incidence geometry can probe the absolute three-dimensional structural morphology of the sample if a highly coherent beam is used. Coherent surface scattering imaging (CSSI) is a powerful yet non-invasive technique similar to coherent X-ray diffractive imaging (CDI) but performed at small angles and grazing-incidence reflection geometry. A challenge with CSSI is that conventional CDI reconstruction techniques cannot be directly applied to CSSI because the Fourier-transform-based forward models cannot reproduce the dynamical scattering phenomenon near the critical angle of total external reflection of the substrate-supported samples. To overcome this challenge, we have developed a multislice forward model which can successfully simulate the dynamical or multi-beam scattering generated from surface structures and the underlying substrate. The forward model is also demonstrated to be able to reconstruct an elongated 3D pattern from a single shot scattering image in the CSSI geometry through fast-performing CUDA-assisted PyTorch optimization with automatic differentiation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

NASA NTRS1987

Damage growth in composite laminates with interleaves

The influence of placing interleaves between fiber reinforced plies in multilayered composite laminates is investigated. The geometry of the composite is idealized as two dimensional, isotropic, linearly elastic media made of a damaged layer bonded between two half planes and separated by thin interleaves of low extensional and shear moduli. The damage in the layer is taken in the form of a symmetric crack perpendicular to the interface and may extend up to the interface. The case of an H-shaped crack in the form of a broken layer with delamination along the interface is also analyzed. The interleaves are modeled as distributed shear and tension springs. Fourier integral transform techniques are used to develop solutions in terms of singular integral equations. An asymptotic analysis of the integral equations based on Muskhelishvili's techniques reveals logarithmically singular axial stresses in the half plane at the crack tips for the broken layer. For the H shaped crack, similar singularities are found to exist in the axial stresses at the interface crack tips in the layer and the half plane. The solution of the equations is found numerically for the stresses and displacements by using the Hadamard's concept of direct differentiation of Cauchy integrals as well as Gaussian integration techniques.

Goree, James G.↗

NASA NTRS1994

Postinstability Models in Dynamics

This paper is devoted to the concept of instability in dynamical systems with the main emphasis on orbital, Hadamard, and Reynolds instabilities. It demonstrates that the requirement about differentiability in dynamics in some cases is not consistent with the physical nature of motions, and may lead to unrealistic solutions. Special attention is paid to the fact that instability is not an invariant of motion: it depends upon frames of reference, the metric of configuration space, and classes of functions selected for mathematical models of physical phenomena. This leads to the possibility of elimination of certain types of instabilities (in particular, those which lead to chaos and turbulence) by enlarging the class of functions using the Reynolds-type transformation in combination with the stabilization principle: the additional terms (the so-called Reynolds stresses) are found from the conditions that they suppress the original instability. Based upon these ideas, a new approach to chaos and turbulence as well as a new mathematical formalism for nonlinear dynamics are discussed.

Zak, Michail↗

DOE OSTI2024

Solving differential‐algebraic equations in power system dynamic analysis with quantum computing

Abstract Power system dynamics are generally modeled by high dimensional non‐linear differential‐algebraic equations (DAEs) given a large number of components forming the network. These DAEs' complexity can grow exponentially due to the increasing penetration of distributed energy resources, whereas their computation time becomes sensitive due to the increasing interconnection of the power grid with other energy systems. This paper demonstrates the use of quantum computing algorithms to solve DAEs for power system dynamic analysis. We leverage a symbolic programming framework to equivalently convert the power system's DAEs into ordinary differential equations (ODEs) using index reduction methods and then encode their data into qubits using amplitude encoding. The system non‐linearity is captured by Hamiltonian simulation with truncated Taylor expansion so that state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can solve the power system's DAEs accurately with a computational complexity polynomial in the logarithm of the system dimension. We also illustrate the use of recent advanced tools in scientific machine learning for implementing complex computing concepts, that is, Taylor expansion, DAEs/ODEs transformation, and quantum computing solver with abstract representation for power engineering applications.

computational complexity↗

NASA NTRS1988

Numerical modeling of multidimensional flow in seals and bearings used in rotating machinery

The rotordynamic behavior of turbomachinery is critically dependent on fluid dynamic rotor forces developed by various types of seals and bearings. The occurrence of self-excited vibrations often depends on the rotor speed and load. Misalignment and rotor wobbling motion associated with differential clearance were often attributed to stability problems. In general, the rotative character of the flowfield is a complex three dimensional system with secondary flow patterns that significantly alter the average fluid circumferential velocity. A multidimensional, nonorthogonal, body-fitted-grid fluid flow model is presented that describes the fluid dynamic forces and the secondary flow pattern development in seals and bearings. Several numerical experiments were carried out to demonstrate the characteristics of this complex flowfield. Analyses were performed by solving a conservation form of the three dimensional Navier-Stokes equations transformed to those for a rotating observer and using the general-purpose computer code PHOENICS with the assumptions that the rotor orbit is circular and that static eccentricity is zero. These assumptions have enabled a precise steady-state analysis to be used. Fluid injection from ports near the seal or bearing center increased fluid-film direct dynamic stiffness and, in some cases, significantly increased quadrature dynamic stiffness. Injection angle and velocity could be used for active rotordynamic control; for example, injection, when compared with no injection, increased direct dynamic stiffness, which is an important factor for hydrostatic bearings.

Hendricks, R. C.↗

DOE OSTI2022

Influence of Thermal Treatment on Preceramic Polymer Grafted Nanoparticle Network Formation: Implications for Thermal Protection Systems and Aerospace Propulsion Components

Preceramic polymer grafted nanoparticles (PCP GNPs) offer potential advantages in the production of polymer-derived ceramic composites compared to neat preceramic polymers (PCPs), such as reduced thermal shrinkage and increased char yield. In comparison to traditional composites (particles + free polymer), PCPs avoid issues of compatibility, agglomeration, and phase separation during processing and provide routes to control nanoparticle arrangement. Prior literature has established that the conversion efficiency of PCPs and PCP GNPs to ceramics and ceramic composites is linked to the thermal pretreatment of these precursor polymers (e.g., curing). In this paper, we investigate the material transformations that occur when exposing PCP GNPs to a low-temperature thermal treatment (≤250 °C) prior to pyrolysis. The PCP GNPs explored in this study possessed silica nanoparticle cores but were distinct in their PCP coronas, having poly(1,1-dimethylpropylsilane) (allyl-GNP)- or poly(1,1-dimethylbenzylethylsilane) (styryl-GNP)-grafted polymers. After undergoing low-temperature thermal treatment, these PCP GNPs exhibited increased char yield at 800 °C; however, unlike commercial PCPs (e.g., allylhydridopolycarbosilane (SMP-10)), obvious cross-linkable sites are not present in the PCP corona structure. Differential scanning calorimetry, oscillatory rheology, and X-ray photon correlation spectroscopy were utilized to elucidate the thermally induced material changes in the allyl- and styryl-GNPs. Thermally induced changes to the structure and behavior of the PCP GNPs were determined to be linked to the chemical structure of the grafted polycarbosilane chains. Styryl-GNPs experienced a curing event between 180 and 250 °C, effecting the formation of a network, which contributed to char yield improvement (at 800 °C). The nanoscale dynamics of this material also shows a transition from diffuse behavior to ballistic behavior because of the cross-linking event. Conversely, the allyl-GNPs did not exhibit a curing event under heat treatment but did show an increase in thermally induced physical cross-linking. The allyl-GNP physical network is stronger after the first cycle of thermal treatment, and it is considered that this contributed to the improvement in char yield post thermal treatment. The advancements in the understanding of the cross-linking behavior of these hybrid materials are expected to advance the application of these materials to turbine engine, advanced friction, and heat-shielding components.

36 MATERIALS SCIENCE↗

NASA NTRS1981

Variable N-type negative resistance in an injection-gated double-injection diode

Double-injection (DI) switching devices consist of p+ and n+ contacts (for hole and electron injection, respectively), separated by a near intrinsic semiconductor region containing deep traps. Under proper conditions, these devices exhibit S-type differential negative resistance (DNR) similar to silicon-controlled rectifiers. With the added influence of a p+ gate appropriately placed between the anode (p+) and cathode (n+), the current-voltage characteristic of the device has been manipulated for the first time to exhibit a variable N-type DNR. The anode current and the anode-to-cathode voltage levels at which this N-type DNR is observed can be varied by changing the gate-to-cathode bias. In essence, the classical S-type DI diode can be electronically transformed into an N-type diode. A first-order phenomenological model is proposed for the N-type DNR.

Kapoor, A. K.↗

NASA NTRS1988

Crystallization kinetics of BaO-Al2O3-SiO2 glasses

Barium aluminosilicate glasses are being investigated as matrix materials in high-temperature ceramic composites for structural applications. Kinetics of crystallization of two refractory glass compositions in the barium aluminosilicate system were studied by differential thermal analysis (DTA), X-ray diffraction (XRD), and scanning electron microscopy (SEM). From variable heating rate DTA, the crystallization activation energies for glass compositions (wt percent) 10BaO-38Al2O3-51SiO2-1MoO3 (glass A) and 39BaO-25Al2O3-35SiO2-1MoO3 (glass B) were determined to be 553 and 558 kJ/mol, respectively. On thermal treatment, the crystalline phases in glasses A and B were identified as mullite (3Al2O3-2SiO2) and hexacelsian (BaO-Al2O3-2SiO2), respectively. Hexacelsian is a high-temperature polymorph which is metastable below 1590 C. It undergoes structural transformation into the orthorhombic form at approximately 300 C accompanied by a large volume change which is undesirable for structural applications. A process needs to be developed where stable monoclinic celsian, rather than hexacelsian, precipitates out as the crystal phase in glass B.

Bansal, Narottam P.↗

NASA NTRS1989

Crystallization kinetics of BaO-Al2O3-SiO2 glasses

Bansal, Narottam P.↗

NASA NTRS2000

Aqueous two-phase partition applied to the isolation of plasma membranes and Golgi apparatus from cultured mammalian cells

Partitioning in dextran-poly(ethylene)glycol (PEG) aqueous-aqueous phase systems represents a mature technology with many applications to separations of cells and to the preparation of membranes from mammalian cells. Most applications to membrane isolation and purification have focused on plasma membranes, plasma membrane domains and separation of right side-out and inside-out plasma membrane vesicles. The method exploits a combination of membrane properties, including charge and hydrophobicity. Purification is based upon differential distributions of the constituents in a sample between the two principal compartments of the two phases (upper and lower) and at the interface. The order of affinity of animal cell membranes for the upper phase is: endoplasmic reticulum <mitochondria<Golgi apparatus<lysosomes and endosomes< plasma membranes. Salt concentrations and temperature affect partitioning behavior and must be precisely standardized. In some cases, it is more fortuitous to combine aqueous two-phase partition with other procedures to obtain a more highly purified preparation. A procedure is described for preparation of Golgi apparatus from transformed mammalian cells that combines aqueous two-phase partition and centrifugation. Also described is a periodic NADH oxidase, a new enzyme marker for right side-out plasma membrane vesicles not requiring detergent disruptions for measurement of activity.

Non-NASA Center↗