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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Performance of plane wavefront Fizeau interferometers in power spectral density measurements with tilted plane optics

Binary pseudo-random array (BPRA) test samples are useful devices for calibrating the instrument transfer function (ITF) of Fizeau interferometers, interferometric microscopes, and other optical and non-optical surface and wavefront metrology instruments. The intrinsic white noise character of the power spectral density (PSD) function of the BPRA pattern simplifies the extraction of the ITF from the measured PSD. The ITF determined in a dedicated calibration experiment can be used to reconstruct the surface height profile from the measured data, effectively enhancing the instrument’s spatial resolution. For a high confidence reconstruction procedure, a reliable analytical model of the IFT is desirable. Usually, the model accounts for the contributions to the ITF related the imperfections of the instrument’s optical and detector systems. Here, we experimentally demonstrate that in the case of surface height metrology with Fizeau interferometers, the PSD measurements and, therefore, the efficacy of the ITF calibration of the tool, are strongly affected by the instrument data acquisition and processing procedures, as well as by the shape of the optic under test and its alignment with respect to the interferometer.

Yashchuk, V V↗
DOE OSTI2022

Data-driven simultaneous process optimization and adsorbent selection for vacuum pressure swing adsorption

Technologies for post-combustion carbon capture are essential for the reduction of greenhouse gas emissions to the atmosphere. However, they are still associated with high costs and energy consumption. Intensified processes for carbon capture have the potential to overcome these challenges due to their higher efficiency, lower capital cost, and increased operational flexibility. Here, this work investigates simultaneous optimization of process conditions and adsorbent selection for a modular Vacuum Pressure-Swing Adsorption system designed for CO 2 capture. Both surrogate-based Nonlinear Programming and Mixed-Integer Nonlinear Programming approaches are applied and compared in terms of computational efficiency and solution accuracy. Moreover, process performance results are examined by applying several data analytics techniques to gain insights into the material-process correlations. Data-driven classifiers and neural networks can accurately predict whether a material is likely to satisfy purity, recovery, and energy constraints when operated at optimal process conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The impact of gas purity on observed reactivity with NO using inductively coupled plasma tandem mass spectrometry

Interference removal in inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) is strongly dependent on the gas selected for use within the collision/reaction cell. There has been little investigation on the effects that reaction gas impurities may have on the resulting spectra. The reactivity of 60 elements was evaluated using nitric oxide (NO 99.5%) with and without a gas purifier to reduce H 2 O impurities to <100 pptV. Experiments were performed using V, Ce, Tl and Th to investigate the effects of purified NO at various flowrates (0.22–1.49 mL min -1 ). Purified NO was shown to significantly mitigate oxy-hydride interferences, improve total ion sensitivity (notable at high gas flows), and shift product distributions advantageously. The reduction in oxy-hydride species results in a product distribution favoring the major expected products, where signals were shown to increase by an order of magnitude. Reduced background and increased signal for the major expected products provides avenues for improving various analytical applications of ICP-MS/MS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Comparative Analysis of ML Techniques for Data-Driven Anomaly Detection, Classification and Localization in Distribution System

High penetration of Distributed Energy Resources (DERs), fundamental load behavior changes, controllable loads, and significant increase in Electrical Vehicles (EVs) lead to complex dynamic behavior of the electric distribution system. Increasing number of components also means more measurements, more data and more data anomalies. Detecting, classifying and localizing these anomalies are important for situational awareness, and at the same time, very challenging given increasing complexity of the system. Highly accurate and high-resolution analytical techniques are needed to support anomaly detection, classification and localization (AD-C-L) for monitoring, root cause analysis and decision making. This paper provides comprehensive review and analysis of the existing spatio-temporal AD-C-L techniques within the distribution system. Challenges for specific problems in AD-C- L have been also discussed in this paper. Existing AD-C- L techniques have been categorized and synthesized for specific merits and limitations of multiple Machine Learning (ML) methodologies using common developed metrics of performance. The comparative analysis is summarized and presented with the open research challenges and path forward for future research needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

CUDO: closed-form universal dwell-time optimization for computer-controlled optical surfacing

Precision optical figuring demands fast and accurate dwell time optimization to reach nanometer- and sub-nanometer-level accuracy in next-generation optical systems. We introduce CUDO (closed-form universal dwell-time optimization), the first, to the best of our knowledge, unified closed-form analytical framework that supports both function-form and matrix-form dwell time models in computer-controlled optical surfacing (CCOS). In contrast to traditional methods, which rely on iterative optimization and hyperparameter tuning, our framework derives direct analytical solutions with no adjustable parameters. This approach unifies the solution principles of existing methods within a single mathematical model, delivering three key advantages: (1) accuracy on par with, or superior to, iterative solvers, (2) substantial reduction in computation time, and (3) numerical robustness. Comparative studies with prior art confirm that closed-form solutions achieve equivalent residual error while removing runtime bottlenecks. By simplifying the implementation and enabling real-time, scalable deployment, CUDO establishes a practical foundation for future deterministic fabrication of large-aperture and high-performance optics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Testing of Helium-Cooled Metal Molybdenum Disk Target

NorthStar Medical Radioisotopes LLC is planning to produce an important medical radioisotope, molybdenum-99 (Mo-99), through photonuclear reaction on molybdenum-100 (Mo-100). In this approach, molybdenum metal will be bombarded with a 40-MeV electron beam. Because enriched Mo-100 is expensive, it is desired to use as much beam power as possible to achieve maximum production yield and minimize target mass. This objective leads to very high beam power density (heat deposition in the target), which sets challenging requirements for cooling. Together with scientists at Los Alamos National Laboratory, a team at Argonne National Laboratory has developed and demonstrated a cooling approach using pressurized helium, which allows for efficient heat removal. One of the main challenges in this approach is the management of the heat load on the target window. The target window separates the high-pressure helium inside the target from the vacuum in the beamline, so it is constantly under stress from differential pressure. Also, the window is cooled only by the helium gas flowing on one side, making the window cooling even more challenging. High heat deposition in the target disks also imposes a strict requirement on performance of the helium cooling system and thickness of the target disks. The target disks are produced from metal powder via a press-and-sinter process. The resulting disks do not possess tensile strength as high as solid molybdenum and might not survive the vibration from the high-velocity helium coolant and high thermal stress from beam heating. An Argonne team of scientists performed a series of tests at Argonne’s Low Energy Accelerator Facility (LEAF) [3-7]. This report describes two series of tests for scale down production target designs that utilize full-scale 29 millimeters diameter, 0.75 mm thick press-and-sintered disks. We performed two thermal tests with different beam parameters and configurations of the disk laminations. We compared the results of the window temperature measurements and cooling system parameters obtained in the experiments with those predicted by analytical calculations and Computation Flow Dynamic (CFD) simulations. Results of the experiments and calculations are presented below.

36 MATERIALS SCIENCE↗
NASA NTRS1982

Inlet design for high-speed propfans

A two-part study was performed to design inlets for high-speed propfan installation. The first part was a parametric study to select promising inlet concepts. A wide range of inlet geometries was examined and evaluated - primarily on the basis of cruise thrust and fuel burn performance. Two inlet concepts were than chosen for more detailed design studies - one apropriate to offset engine/gearbox arrangements and the other to in-line arrangements. In the second part of this study, inlet design points were chosen to optimize the net installed thrust, and detailed design of the two inlet configurations was performed. An analytical methodology was developed to account for propfan slipstream effects, transonic flow efects, and three-dimensional geometry effects. Using this methodology, low drag cowls were designed for the two inlets.

Little, B. H., Jr.↗
NASA NTRS1994

Integrated active and passive control design methodology for the LaRC CSI evolutionary model

A general design methodology to integrate active control with passive damping was demonstrated on the NASA LaRC CSI Evolutionary Model (CEM), a ground testbed for future large, flexible spacecraft. Vibration suppression controllers designed for Line-of Sight (LOS) minimization were successfully implemented on the CEM. A frequency-shaped H2 methodology was developed, allowing the designer to specify the roll-off of the MIMO compensator. A closed loop bandwidth of 4 Hz, including the six rigid body modes and the first three dominant elastic modes of the CEM was achieved. Good agreement was demonstrated between experimental data and analytical predictions for the closed loop frequency response and random tests. Using the Modal Strain Energy (MSE) method, a passive damping treatment consisting of 60 viscoelastically damped struts was designed, fabricated and implemented on the CEM. Damping levels for the targeted modes were more than an order of magnitude larger than for the undamped structure. Using measured loss and stiffness data for the individual damped struts, analytical predictions of the damping levels were very close to the experimental values in the (1-10) Hz frequency range where the open loop model matched the experimental data. An integrated active/passive controller was successfully implemented on the CEM and was evaluated against an active-only controller. A two-fold increase in the effective control bandwidth and further reductions of 30 percent to 50 percent in the LOS RMS outputs were achieved compared to an active-only controller. Superior performance was also obtained compared to a High-Authority/Low-Authority (HAC/LAC) controller.

Voth, Christopher T.↗
NASA NTRS2017

Data Collection and Analysis Software Development for Rotor Dynamics Testing in Spin Laboratory

Gas turbine engine components undergo high rotational loading another complex environmental conditions. Such operating environment leads these components to experience damages and cracks that can cause catastrophic failure during flights. There are traditional crack detections and health monitoring methodologies currently being used which rely on periodic routine maintenances, nondestructive inspections that often times involve engine and components dis-assemblies. These methods do not also offer adequate information about the faults, especially, if these faults at subsurface or not clearly evident. At NASA Glenn research center, the rotor dynamics laboratory is presently involved in developing newer techniques that are highly dependent on sensor technology to enable health monitoring and prediction of damage and cracks in rotor disks. These approaches are noninvasive and relatively economical. Spin tests are performed using a subscale test article mimicking turbine rotor disk undergoing rotational load. Non-contact instruments such as capacitive and microwave sensors are used to measure the blade tip gap displacement and blade vibrations characteristics in an attempt develop a physics based model to assess/predict the faults in the rotor disk. Data collection is a major component in this experimental-analytical procedure and as a result, an upgrade to an older version of the data acquisition software which is based on LabVIEW program has been implemented to support efficiently running tests and analyze the results. Outcomes obtained from the tests data and related experimental and analytical rotor dynamics modeling including key features of the updated software are presented and discussed.

Rotor Dynamics↗
NASA NTRSDate not supplied

Instabilities in the Wake of Roughness on a Flat Plate in a Quiet Supersonic Tunnel

Roughness-induced transition is an unavoidable reality in practical high-speed vehicles. Typical prediction of transition due to roughness include algebraic correlations and, more recently, semi-empirical methods. In the NASA Langley Research Center Supersonic Low Disturbance Tunnel, a Mach 3.5 quiet tunnel, several transition experiments have been performed in the past decade to better understand the mechanisms by which small roughness causes transition in a supersonic boundary layer. The study started first with isolated roughness elements of different planforms and shapes and progressed to increasingly more complicated geometries before arriving at a pseudorandom roughness, defined by an analytic function. Concurrent computational efforts progressed with these studies as well, starting with the use of linear stability theory and progressing to the use of harmonic linearized Navier-Stokes to predict the growth of boundary layer stabilities.

Amanda Chou↗
DOE OSTI2022

Computational Identification and Experimental Demonstration of High‐Performance Methane Sorbents

Abstract Remarkable methane uptake is demonstrated experimentally in three metal‐organic frameworks (MOFs) identified by computational screening: UTSA‐76, UMCM‐152 and DUT‐23‐Cu. These MOFs outperform the benchmark sorbent, HKUST‐1, both volumetrically and gravimetrically, under a pressure swing of 80 to 5 bar at 298 K. Although high uptake at elevated pressure is critical for achieving this performance, a low density of high‐affinity sites (coordinatively unsaturated metal centers) also contributes to a more complete release of stored gas at low pressure. The identification of these MOFs facilitates the efficient storage of natural gas via adsorption and provides further evidence of the utility of computational screening in identifying overlooked sorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Direct Insertion Polymerization of Ionic Monomers: Rapid Production of Anion Exchange Membranes

The limited number of methods to directly polymerize ionic monomers currently hinders rapid diversification and production of ionic polymeric materials, namely anion exchange membranes (AEMs) which are essential components in emerging alkaline fuel cell and electrolyzer technologies. Herein, we report a direct coordination-insertion polymerization of cationic monomers, providing the first direct synthesis of aliphatic polymers with high ion incorporations and allowing facile access to a broad range of materials. We demonstrate the utility of this method by rapidly generating a library of solution processable ionic polymers for use as AEMs. We investigate these materials to study the influence of cation identity on hydroxide conductivity and stability. Furthermore, we found that AEMs with piperidinium cations exhibited the highest performance, with high alkaline stability, hydroxide conductivity of 87 mS cm –1 at 80 °C, and a peak power density of 730 mW cm –2 when integrated into a fuel cell device.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Breaking the trade-off between selectivity and adsorption capacity for gas separation

It is generally recognized that porous solids (sorbents) with high selectivity and high adsorption capacity offer potential for energy-efficient gas separations. Unfortunately, there is generally a trade-off between capacity and selectivity, which represents a roadblock to the utility of sorbents in key industrial processes. For example, acetylene (C 2 H 2 ), an important fuel and chemical intermediate, is produced with CO 2 as an impurity, and the similar physicochemical properties of C 2 H 2 and CO 2 mean that most sorbents are poorly selective. Hybrid ultramicroporous materials (HUMs) are candidates for gas separations as they exhibit benchmark selectivity for several key gas pairs. Unfortunately, existing HUMs are handicapped by low capacity. Here, we report a new HUM, SIFSIX-21-Ni, that addresses the trade-off between selectivity and capacity that has plagued sorbents, as its high uptake and high selectivity renders it the new benchmark for C 2 H 2 /CO 2 separation performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Spectroscopic Insight on Neodymium Solvation in Lithium Borohydride-Supported Electrolyte

Borohydride-based electrolytes have recently emerged as promising media for the electrodeposition of electropositive metals, including rare earth (RE) elements. While the presence of supporting alkali metal cations and RE counteranions provides essential electrochemical conductivity for achieving fast metal electrodeposition, interactions between the host ligand and solvated neodymium (Nd) complexes remain unclear. This study provides insights into the coordination structure of a concentrated and directly solvated Nd salt in a lithium borohydride-supported electrolyte. Our spectroscopic results indicate that the RE coordination environment is significantly influenced by the solvation mechanism, which can vary between metathesis and complexation pathways, primarily dictated by stoichiometric factors. Under dilute conditions, nearly complete metathesis of anions leads to a high coordination number for the host ligand (borohydride), consistent with the previously reported solvated Nd speciation in chlorine-free electrolytes. In contrast, concentrated dissolution of the Nd salt in the supported electrolyte is dominated by a complexation pathway featuring a Li-ion-paired complex with a low coordination number of the host ligand. Density functional theory (DFT) calculations indicated that the observed blue shift in the borohydride vibration was the result of an increase in electron density drawn into the terminal B–H interbond region from the hydride as the coordination changed from Li to Nd. In conjunction with DFT results, vibrational analyses allowed correlation of the experimental shifts associated with changes in Nd ligation and coordination spheres, further consolidating the prevalence of highly chloride-coordinated species under concentrated conditions. In conclusion, the outcomes of this work illuminate the distinctive and heterogeneous coordination structures that the electroactive RE species can adopt at high concentrations in lithium borohydride-supported electrolytes, as a key step to comprehend the reported metal electrodeposition performance in these media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Is solid copper oxalate a spin chain or a mixture of entangled spin pairs?

Macroscopic assemblies of interacting spins give rise to a broad spectrum of behaviors determined by the spatial arrangement of the magnetic sites and the electronic interactions between them. Compounds of copper (II), in which each copper carries spin 1/2, exhibit a vast variety of physical properties. For antiferromagnetically coupled spin sites, there are two limiting scenarios: spin chains in which the spins can exhibit a long-range order or a mixture of dimers in which the spins within each pair are entangled but do not communicate with the spins from other dimers. In principle, the two types can be distinguished on the basis of experimental observations and modeling using empirically parameterized effective Hamiltonians, but in practice, ambiguity may persist for decades, as is the case for copper oxalate. Here we use high-level ab initio calculations to establish the validity of the nearest-site Heisenberg model and to predict the interaction strength between the magnetic sites. Finally, the computed magnetic susceptibility provides an unambiguous interpretation of magnetic experiments performed throughout half a century, clearly supporting the infinite spin-chain behavior of solid copper oxalate.

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

Machine learning overcomes human bias in the discovery of self-assembling peptides

Peptide materials have a wide array of functions, from tissue engineering and surface coatings to catalysis and sensing. Tuning the sequence of amino acids that comprise the peptide modulates peptide functionality, but a small increase in sequence length leads to a dramatic increase in the number of peptide candidates. Traditionally, peptide design is guided by human expertise and intuition and typically yields fewer than ten peptides per study, but these approaches are not easily scalable and are susceptible to human bias. Here, in this work, we introduce a machine learning workflow—AI-expert—that combines Monte Carlo tree search and random forest with molecular dynamics simulations to develop a fully autonomous computational search engine to discover peptide sequences with high potential for self-assembly. We demonstrate the efficacy of the AI-expert to efficiently search large spaces of tripeptides and pentapeptides. The predictability of AI-expert performs on par or better than our human experts and suggests several non-intuitive sequences with high self-assembly propensity, outlining its potential to overcome human bias and accelerate peptide discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Leveraging lifetime information to perform real-time 3D single-particle tracking in noisy environments

A microscopy platform that leverages the arrival time of individual photons to enable 3D single-particle tracking of fast-moving (translational diffusion coefficient of ≃ 3.3 µm 2 /s) particles in high-background environments is reported here. It combines a hardware-based time-gating module, which enables the rate of photon processing to be as high as 100 MHz, with a two-photon excited 3D single-particle tracking confocal microscope to enable high sample penetration depth. Proof-of-principle experiments where single quantum dots are tracked in solutions containing dye-stained cellulose are shown, with tracking performance markedly improved using the hardware-based time-gating module. Furthermore, such a microscope design is anticipated to be of use to a variety of communities who wish to track single-particles in cellular environments, which commonly have high fluorescence and scattering background.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

HPC4Mfg with ACS

Distillation in the chemical industry accounts for roughly 10% of energy use in the U.S. While porous mass separating agents (MSAs) appear capable of achieving the same separations for a fraction of the energy, the fundamental lack of a well-understood relationship between the behavior of fluid mixtures confined in MSA pores and the selectivity of MSA-based processes presents a major barrier to their widespread industrial application. This work is the first study to systematically and self-consistently explore a range of parameters describing various molecule-material interactions in MSA-based separations. Through high performance computing (HPC), this study has yielded a fundamental understanding of the influence of confined fluid behavior on selectivity. The results also serve as a knowledge base for subsequent investigations needed to transform the framework for rational design of MSA-based separation processes. This will significantly reduce the energy required for separations central to chemical manufacturing.

36 MATERIALS SCIENCE↗