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At least 577 records · Page 32

Glennan Microsystems Initiative

During the 2001-2002 award period, we performed research on Pt/Ti/bare 6H-SiC and bare 4H-SiC interfaces in order to identify their electronic properties as a function of surface preparation. The overall aim of this work is to optimize the electronic properties of metal contacts to SiC as well as the active SiC material itself as a function of surface preparation and subsequent processing. Initially, this work has involved identifying bare surface, subsurface, and metal induced gap states at the metal-SiC contact and correlating energies and densities of deep levels with Schottky barrier heights. We used low energy electron-excited nanoluminescence (LEEN) spectroscopy, X-ray photoemission spectroscopy (XPS), and Secondary Ion Mass Spectrometry (SIMS) in order to correlate electronic states and energy bands with chemical composition, bonding, and crystal structure. A major development has been the discovery of polytype transformations that occur in 4H-SiC under standard microelectronic process conditions used to fabricate SiC devices. Our results are consistent with the stacking fault generation, defect formation, and consequent degradation of SiC recently reported for state-of-the-art ABB commercial diodes under localized electrical stress. Our results highlight the importance of -optimizing process conditions and material properties - anneal times, temperatures and doping to control such structural changes within epitaxial SiC layers. Thus far, we have established threshold times and temperatures beyond which 4H-SiC exhibits 3C-SiC transformation bands for a subset of dopant concentrations and process conditions. On the basis of this temperature time behavior, we have been able to establish an activation energy of approximately 2.5 eV for polytype transformation and dislocation motion. Work continues to establish the fundamental mechanisms underlying the polytype changes and its dependence on material parameters.

Brillson, Leonard J.↗

A Methodology for Surface Soil Moisture and Vegetation Optical Depth Retrieval Using the Microwave Polarization Difference Index

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz brightness temperature observations from the Scanning Multichannel Microwave Radiometer over several test sites in Illinois. Results using only nighttime data are presented at this time, due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a non-linear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness. Surface temperature is derived by a procedure using high frequency vertically polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and is totally independent of wavelength. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors.

Owe, Manfred↗

Ceruloplasmin and cardiovascular disease

Transition metal ion-mediated oxidation is a commonly used model system for studies of the chemical, structural, and functional modifications of low-density lipoprotein (LDL). The physiological relevance of studies using free metal ions is unclear and has led to an exploration of free metal ion-independent mechanisms of oxidation. We and others have investigated the role of human ceruloplasmin (Cp) in oxidative processes because it the principal copper-containing protein in serum. There is an abundance of epidemiological data that suggests that serum Cp may be an important risk factor predicting myocardial infarction and cardiovascular disease. Biochemical studies have shown that Cp is a potent catalyst of LDL oxidation in vitro. The pro-oxidant activity of Cp requires an intact structure, and a single copper atom at the surface of the protein, near His(426), is required for LDL oxidation. Under conditions where inhibitory protein (such as albumin) is present, LDL oxidation by Cp is optimal in the presence of superoxide, which reduces the surface copper atom of Cp. Cultured vascular endothelial and smooth muscle cells also oxidize LDL in the presence of Cp. Superoxide release by these cells is a critical factor regulating the rate of oxidation. Cultured monocytic cells, when activated by zymosan, can oxidize LDL, but these cells are unique in their secretion of Cp. Inhibitor studies using Cp-specific antibodies and antisense oligonucleotides show that Cp is a major contributor to LDL oxidation by these cells. The role of Cp in lipoprotein oxidation and atherosclerotic lesion progression in vivo has not been directly assessed and is an important area for future studies.

NASA Discipline Cell Biology↗

Solution of nonlinear finite difference ocean models by optimization methods with sensitivity and observational strategy analysis

The paper studies with finite difference nonlinear circulation models the uncertainties in interesting flow properties, such as western boundary current transport, potential and kinetic energy, owing to the uncertainty in the driving surface boundary condition. The procedure is based upon nonlinear optimization methods. The same calculations permit quantitative study of the importance of new information as a function of type, region of measurement and accuracy, providing a method to study various observing strategies. Uncertainty in a model parameter, the bottom friction coefficient, is studied in conjunction with uncertain measurements. The model is free to adjust the bottom friction coefficient such that an objective function is minimized while fitting a set of data to within prescribed bounds. The relative importance of the accuracy of the knowledge about the friction coefficient with respect to various kinds of observations is then quantified, and the possible range of the friction coefficients is calculated.

Schroeter, Jens↗

Space transportation vehicle design evaluation using saturated designs

An important objective in the preliminary design and evaluation of space transportation vehicles is to find the best values of design variables that optimize the performance characteristic (e.g. dry weight). For a given configuration, the vehicle performance can be determined by the use of complex sizing and performance evaluation computer programs. These complex computer programs utilize iterative algorithms and they are generally too expensive and/or difficult to use directly in multidisciplinary design optimization. An alternative is to use response surface methodology (RSM) and obtain quadratic polynomial approximations to the functional relationships between performance characteristics and design variables. In RSM, these approximation models are then used to determine optimum design parameter values and for rapid sensitivity studies. Constructing a second-order model requires that 'n' design parameters be studied at least at 3 levels (values) so that the coefficients in the model can be estimated. There, 3(n) factorial experiments (point designs or observations) may be necessary. For small values of 'n' such as two or three, this design works well. However, when a large number of design parameters are under study, the number of design points required for a full-factorial design may become excessive. Fortunately, these quadratic polynomial approximations can be obtained by selecting an efficient design matrix using central composite designs (CCD) from design of experiments theory. Each unique point design from the CCD matrix is then conducted using computerized analysis tools (e.g. POST, CONSIZ, etc.). In the next step, least squares regression analysis is used to calculate the quadratic polynomial coefficients from the data. However, in some multidisciplinary applications involving a large number of design variables and several disciplines, the computerized performance synthesis programs may get too time consuming and expensive to run even with the use of efficient central composite designs. In such cases, it may be preferable to keep the number of design points to an absolute minimum and trade some model accuracy with cost. For this purpose, another class of experimental designs, called saturated D-optimal designs may be utilized for generating a matrix of vehicle designs. A design is called saturated when the number of design points is exactly equal to the number of terms in the model to be fitted. As a result, saturated designs require the absolute minimum number of design points ((n+1)(n+2)/s) to estimate the quadratic polynomial model coefficients. Saturated designs can be generated using the D-optimality criterion. A good saturated design should give rise to least squares estimates with minimum generalized variance.

Unal, Resit↗

Automated Fiber Placement Through Thickness Defect Stacking Optimization

In its 2022 commercial market outlook, Boeing forecasted an 80% increase in the global fleet through 2041 compared to 2019 pre-pandemic levels. This sharp rise in demand will drive pressure onto airframe manufacturers to ramp up production and find more efficient ways to design and manufacture airplanes. Complicating this challenge is the industry’s recent transformation from traditional metal-based airframes towards hybrid composite-metal aircraft. While composites have been used in aviation for decades, aircraft manufacturers are still struggling to design and manufacture quality parts at a high rate. Automated Fiber Placement (AFP) is one of the main manufacturing techniques used to produce large-scale composite parts. After a design has been created, a manufacturing strategy has to be developed based on the working material, part geometry, and machine capabilities. This process planning stage is essential to the AFP workflow and currently requires a high level of manual input from an experienced process planner. In an effort to automate and optimize this stage, the Computer Aided Process Planning (CAPP) module was developed. CAPP assists process planners in identifying optimal starting point location and layup strategy for each ply of a laminate. This Ply-Level Optimization (PLO) phase operates on the quantification of ply quality through predictable geometry-based defects such as gaps, overlaps, angle deviation, and steering. As you move from PLO to Laminate-Level Optimization (LLO) the design space grows exponentially, emphasizing the need for automated optimization. The work presented in this thesis expands CAPP’s functionality by comparing the planned fiber paths through the thickness of the laminate to mitigate stacked area defects and achieve an optimal laminate-level manufacturing strategy. Within CAPP, predicted gap and overlap defects are imported from Vericut Composites Programming (VCP) and then discretized to streamline the through-thickness comparison. Two objective functions are used to score different combinations of ply layup strategies based on defect stacking both globally and locally. Four combinatorial optimization algorithms were coupled with these objective functions to investigate the laminate-level manufacturing strategy design space and converge on the optimal plan. These algorithms were evaluated based on accuracy and efficiency through virtual testing on a complex tool surface. A separate LLO approach was developed to achieve near-optimal laminates in significantly less time. The end result is a software package which greatly reduces the required input from process planners, shortening the design-build cycle time and improving part quality.

AFP↗

Development and Testing of Femtosecond Laser Surface Processing (FLSP) Treated Guide Vanes for Application to Advanced Cryogenic Liquid Acquisition Devices

Liquid Acquisition Devices (LADs) are used inside propellant tanks in microgravity to collect liquid propellant to move towards the sump or outlet of a tank during expulsion or transfer. In microgravity, vehicle thrusters can produce necessary phase separation, but in the absence of thrust, surface tension is the driver of fluid behavior. Liquid in microgravity will tend to form a sphere to minimize surface area. If a LAD can be made more “attractive” to a propellant (omniphilic), then it should perform its function more effectively. This paper presents preliminary results on using femtosecond laser surface processing (FLSP) to change the wetting properties of a vane LAD. FLSP can make metals superhydrophilic or omniphilic; by controlling the applied laser parameters, the resulting micro and nanoscale surface features can be tailored to control and optimize hydrophilic/omniphilic properties. Two LAD galleries with guide vanes were recently fabricated, a control sample and an FLSP-treated sample. The LADs were ground tested and also implemented in a parabolic flight experiment. Based on contact angle and roll-off angle measurements of the surface-treated vane, FLSP appears to be a promising technique to improve efficiency of LADs

Liquid Acquisition Devices↗

Clouds Versus Carbon: Predicting Vegetation Roughness by Maximizing Productivity

Surface roughness is one of the dominant vegetation properties that affects land surface exchange of energy, water, carbon, and momentum with the overlying atmosphere. We hypothesize that the canopy structure of terrestrial vegetation adapts optimally to climate by maximizing productivity, leading to an optimum surface roughness. An optimum should exist because increasing values of surface roughness cause increased surface exchange, leading to increased supply of carbon dioxide for photosynthesis. At the same time, increased roughness enhances evapotranspiration and cloud cover, thereby reducing the supply of photosynthetically active radiation. We demonstrate the optimum through sensitivity simulations using a coupled dynamic vegetation-climate model for present day conditions, in which we vary the value of surface roughness for vegetated surfaces. We find that the maximum in productivity occurs at a roughness length of 2 meters, a value commonly used to describe the roughness of today's forested surfaces. The sensitivity simulations also illustrate the strong climatic impacts of vegetation roughness on the energy and water balances over land: with increasing vegetation roughness, solar radiation is reduced by up to 20 W/sq m in the global land mean, causing shifts in the energy partitioning and leading to general cooling of the surface by 1.5 K. We conclude that the roughness of vegetated surfaces can be understood as a reflection of optimum adaptation, and it is associated with substantial changes in the surface energy and water balances over land. The role of the cloud feedback in shaping the optimum underlines the importance of an integrated perspective that views vegetation and its adaptive nature as an integrated component of the Earth system.

Olsen, Lola M.↗

Multidisciplinary Aerodynamic-Structural Shape Optimization Using Deformation (MASSOUD)

This paper presents a multidisciplinary shape parameterization approach. The approach consists of two basic concepts: (1) parameterizing the shape perturbations rather than the geometry itself and (2) performing the shape deformation by means of the soft object animation algorithms used in computer graphics. Because the formulation presented in this paper is independent of grid topology, we can treat computational fluid dynamics and finite element grids in a similar manner. The proposed approach is simple, compact, and efficient. Also, the analytical sensitivity derivatives are easily computed for use in a gradient-based optimization. This algorithm is suitable for low-fidelity (e.g., linear aerodynamics and equivalent laminated plate structures) and high-fidelity (e.g., nonlinear computational fluid dynamics and detailed finite element modeling analysis tools. This paper contains the implementation details of parameterizing for planform, twist, dihedral, thickness, camber, and free-form surface. Results are presented for a multidisciplinary design optimization application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, and a simple performance module.

Samareh, Jamshid A.↗

Pairing a Global Optimization Algorithm with EXAFS to Characterize Lanthanide Structure in Solution

Ensemble-average sampling of structures from ab initio molecular dynamics (AIMD) simulations can be used to predict theoretical extended X-ray absorption fine structure (EXAFS) signals that closely match experimental spectra. However, AIMD simulations are time-consuming and resource-intensive, particularly for solvated lanthanide ions, which often form multiple nonrigid geometries with high coordination numbers. Here, to accelerate the characterization of lanthanide structures in solution, we employed the Northwest Potential Energy Surface Search Engine (NWPEsSe), an adaptive-learning global optimization algorithm, to efficiently screen first-shell structures. As case studies, we examine two systems: Eu(NO 3 ) 3 dissolved in acetonitrile with a terpyridine ligand (terpyNO 2 ), and Nd(NO 3 ) 3 dissolved in acetonitrile. The theoretical spectra for structures identified by NWPEsSe were compared to both experimental and AIMD-derived EXAFS spectra. The NWPEsSe algorithm successfully identified the proper solvation structure for both Eu(NO 3 ) 3 (terpyNO 2 ) and Nd(NO 3 )(acetonitrile) 3 , with the calculated EXAFS signals closely matching the experimental spectra for the Eu-ligand complex and showing good similarity for the Nd salt; the better agreement with the ligand-containing structure is attributed to a less dynamic coordination environment due to the rigid ligand. The key advantage of the global optimization algorithm lies in its ability to sample the coordination environment across the potential energy surface and reduce the time required to identify structures from generally a month to within a week. Additionally, this approach is versatile and can be adapted to characterize main-group metal complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Massively parallel and universal approximation of nonlinear functions using diffractive processors

Nonlinear computation is essential for a wide range of information processing tasks, yet implementing nonlinear functions using optical systems remains a challenge due to the weak and power-intensive nature of optical nonlinearities. Overcoming this limitation without relying on nonlinear optical materials could unlock unprecedented opportunities for ultrafast and parallel optical computing systems. Here, we demonstrate that large-scale nonlinear computation can be performed using linear optics through optimized diffractive processors composed of passive phase-only surfaces. In this framework, the input variables of nonlinear functions are encoded into the phase of an optical wavefront—e.g., via a spatial light modulator (SLM)—and transformed by an optimized diffractive structure with spatially varying point-spread functions to yield output intensities that approximate a large set of unique nonlinear functions–all in parallel. We provide proof establishing that this architecture serves as a universal function approximator for an arbitrary set of bandlimited nonlinear functions, also covering wavelength-multiplexed nonlinear functions as well as multi-variate and complex-valued functions that are all-optically cascadable. Our analysis also indicates the successful approximation of typical nonlinear activation functions commonly used in neural networks, including the sigmoid, tanh, ReLU (rectified linear unit), and softplus. We numerically demonstrate the parallel computation of one million distinct nonlinear functions, accurately executed at wavelength-scale spatial density at the output of a diffractive optical processor. Furthermore, we experimentally validated this framework using in situ optical learning and approximated 35 unique nonlinear functions in a single shot using a compact setup consisting of an SLM and an image sensor. These results establish diffractive optical processors as a scalable platform for massively parallel universal nonlinear function approximation, paving the way for new capabilities in analog optical computing based on linear materials.

Rahman, Md Sadman Sakib [University of California,↗

Improved Method Being Developed for Surface Enhancement of Metallic Materials

Surface enhancement methods induce a layer of beneficial residual compressive stress to improve the impact (FOD) resistance and fatigue life of metallic materials. A traditional method of surface enhancement often used is shot peening, in which small steel spheres are repeatedly impinged on metallic surfaces. Shot peening is inexpensive and widely used, but the plastic deformation of 20 to 40 percent imparted by the impacts can be harmful. This plastic deformation can damage the microstructure, severely limiting the ductility and durability of the material near the surface. It has also been shown to promote accelerated relaxation of the beneficial compressive residual stresses at elevated temperatures. Low-plasticity burnishing (LPB) is being developed as an improved method for the surface enhancement of metallic materials. LPB is being investigated as a rapid, inexpensive surface enhancement method under NASA Small Business Innovation Research contracts NAS3-98034 and NAS3-99116, with supporting characterization work at NASA. Previously, roller burnishing had been employed to refine surface finish. This concept was adopted and then optimized as a means of producing a layer of compressive stress of high magnitude and depth, with minimal plastic deformation (ref. 1). A simplified diagram of the developed process is given in the following figure. A single pass of a smooth, free-rolling spherical ball under a normal force deforms the surface of the material in tension, creating a compressive layer of residual stress. The ball is supported in a fluid with sufficient pressure to lift the ball off the surface of the retaining spherical socket. The ball is only in mechanical contact with the surface of the material being burnished and is free to roll on the surface. This apparatus is designed to be mounted in the conventional lathes and vertical mills currently used to machine parts. The process has been successfully applied to nickel-base superalloys by a team from the NASA Glenn Research Center, Lambda Research, and METCUT Research, as supported by the NASA Small Business Innovation Research Phase I and II programs, the Ultra Safe program, and the Ultra- Efficient Engine Technology (UEET) Program.

Gabb, Timothy P.↗

Enhanced Fuel-Optimal Trajectory-Generation Algorithm for Planetary Pinpoint Landing

An enhanced algorithm is developed that builds on a previous innovation of fuel-optimal powered-descent guidance (PDG) for planetary pinpoint landing. The PDG problem is to compute constrained, fuel-optimal trajectories to land a craft at a prescribed target on a planetary surface, starting from a parachute cut-off point and using a throttleable descent engine. The previous innovation showed the minimal-fuel PDG problem can be posed as a convex optimization problem, in particular, as a Second-Order Cone Program, which can be solved to global optimality with deterministic convergence properties, and hence is a candidate for onboard implementation. To increase the speed and robustness of this convex PDG algorithm for possible onboard implementation, the following enhancements are incorporated: 1) Fast detection of infeasibility (i.e., control authority is not sufficient for soft-landing) for subsequent fault response. 2) The use of a piecewise-linear control parameterization, providing smooth solution trajectories and increasing computational efficiency. 3) An enhanced line-search algorithm for optimal time-of-flight, providing quicker convergence and bounding the number of path-planning iterations needed. 4) An additional constraint that analytically guarantees inter-sample satisfaction of glide-slope and non-sub-surface flight constraints, allowing larger discretizations and, hence, faster optimization. 5) Explicit incorporation of Mars rotation rate into the trajectory computation for improved targeting accuracy. These enhancements allow faster convergence to the fuel-optimal solution and, more importantly, remove the need for a "human-in-the-loop," as constraints will be satisfied over the entire path-planning interval independent of step-size (as opposed to just at the discrete time points) and infeasible initial conditions are immediately detected. Finally, while the PDG stage is typically only a few minutes, ignoring the rotation rate of Mars can introduce 10s of meters of error. By incorporating it, the enhanced PDG algorithm becomes capable of pinpoint targeting.

Acikmese, Behcet↗

Monitoring the Stability of Porous Coordination Cages during the Photoreduction of Porous Salt Thin Films

This study investigates the photochemical properties and stability of zirconium-based porous salts composed of coordination cages and redox-active polyoxometalates (POMs). While bulk porous salts demonstrated photoreduction confined to surface regions due to lim-ited light penetration and scattering effects, thin films of cage-POM assemblies were fabricated to address these challenges. These optically transparent films allowed access to the catalyst core, enabling enhanced photochemical characterization. Comparative studies revealed that the thin films exhibited superior photochemical activity and maintained porosity under optimized conditions, whereas bulk powders suffered from surface-limited photoreduction and cage decomposition. Furthermore, this work highlights the utility of thin films as a platform for studying and advancing the photochemical applications of porous salts.

Hoq, Jahidul [Indiana University, Bloomington, IN ↗

Ni-Rich Li[Ni x MnyCo 1– x – y ]O 2 Single Crystals as Superior Fast Charge Cathodes for Lithium-Ion Batteries

The utilization of single-crystal (SC) Li[Ni x MnyCo 1-x-y ]O 2 (NMC) cathodes has facilitated unparalleled performance in commercial high-energy lithium-ion batteries (LIBs). In the current study, we evaluate the application of SC cathodes in fast charge (FC)-LIBs where particle cracking is a predominant failure mechanism. Ni-rich SC-NMC samples with various compositions, sizes, and shapes are synthesized and investigated for their influence on FC performance. We reveal the necessity of utilizing smaller SCs (<1 μm) as larger sizes (>2 μm) experience significant particle-level lithium concentration gradients under FC conditions. To improve lithium transport and minimize side reactivities, we strategically expose the (104) crystal facets on the surface. Exceptional performance was observed on an optimized SC-LiNi 0.80 Mn 0.05 Co 0.15 O 2 , delivering a discharge capacity of 165 mAh/g even after 150 cycles at 6C charge. Our study not only demonstrates the promise of SC-NMC but also provides the key insights for the design and optimization of advanced cathodes for FC-LIBs.

25 ENERGY STORAGE↗

Experimental considerations and applications for time-resolved impedance on silicon-anode battery systems

Dynamic electrochemical impedance spectroscopy (dEIS) utilizes a superimposed multi-sinusoidal waveform and enables temporally resolved investigations on various electrochemical processes; however, the signal-to-noise ratio must be maximized while retaining linearity and stationarity within the system. In the present work, we probe the impact of the waveform’s total amplitude as well as the waveform and phase profiles. The equal amplitude multi-sinusoidal waveform with 35 mV total amplitude (<1 mV per frequency) and random phase profile exhibits the lowest impedance noise. This input signal is sufficient in avoiding the high frequency signal attenuation from the potentiostat’s low-pass filter. Additionally, we demonstrate the optimized dEIS waveform’s utility in investigating surface passivation within thin-film and composite silicon (Si) anodes. Within a two-electrode Si-lithium metal coin cell, the charge transfer resistance (RCT) associated with alloying kinetics dominates the overall impedance. RCT increases with state of charge indicating a kinetic bottleneck at higher lithiation states. To explore this further, we utilize a three-electrode Si-LiNi0.8Mn0.1Co0.1O2 pouch cell to deconvolute the Si impedance contributions. The evolution of the solid electrolyte interphase (SEI) and charge transfer resistances correlate to specific Li–Si alloy phases. We attribute this to the influence of Si particle volume expansion on SEI instabilities and a kinetic bottleneck at higher lithiation states.

Lam, Steven [ORNL]↗

Polarized Photocathodes development for the EIC: Optimizing Spin and Quantum Efficiency

GaAs/GaAsP superlattice photocathodes play a critical role for producing highly polarized electron beams for the Electron-Ion Collider (EIC) at Brookhaven National Laboratory. The electron pre-injector for the EIC requires electron bunches with high bunch charge (1-2 nC) and high polarization, from GaAs-based superlattice photocathode. Herein, we have systematically investigated a range of GaAs/GaAsP superlattice photocathodes fabricated via molecular beam epitaxy (MBE) and metal-organic chemical vapor deposition (MOCVD). Through optimization of pre-cleaning procedures and surface doping conditions, we aim to identify the most promising photocathode configurations for future EIC operations. To enhance the quantum efficiency (QE), a Distributed Bragg Reflector structure is frequently incorporated beneath the superlattice. While this approach effectively increases QE, it also introduces additional complexities that can adversely influence spin polarization and the spectral response at specific laser wavelengths. This note provides an overview of superlattice GaAs development and outlines the EIC team’s ongoing efforts to address related challenges and advance high-performance photocathode development tailored for the EIC. Over five years of multi-institutional collaboration and measurements of about 50 SL-GaAs samples, our analysis presents statistics on samples exhibiting high ESP and high QE. It will help to set the initial ESP requirements for the EIC project.

43 PARTICLE ACCELERATORS↗