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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Multi‐Material Gradient Printing Using Meniscus‐enabled Projection Stereolithography (MAPS)

Light‐based additive manufacturing methods are widely used to print high‐resolution 3D structures for applications in tissue engineering, soft robotics, photonics, and microfluidics, among others. Despite this progress, multi‐material printing with these methods remains challenging due to constraints associated with hardware modifications, control systems, cross‐contamination, waste, and resin properties. Here, a new printing platform coined Meniscus‐enabled Projection Stereolithography (MAPS) is reported, a vat‐free method that relies on generating and maintaining a resin meniscus between a crosslinked structure and bottom window to print lateral, vertical, discrete, or gradient multi‐material 3D structures with no waste and user‐defined mixing between layers. MAPS is compatible with a wide range of resins shown and can print complex multi‐material 3D structures without requiring specialized hardware, software, or complex washing protocols. MAPS's ability to print structures with microscale variations in mechanical stiffness, opacity, surface energy, cell densities, and magnetic properties provides a generic method to make advanced materials for a broad range of applications.

bioprinting↗
NASA NTRS1990

Thermomechanical properties of polymeric materials and related stresses

The thermomechanical analysis (TMA) and dynamic mechanical analysis characterizations of a polymeric material yield useful data relating to the thermomechanical stresses of eight widely used polymeric materials. The materials encompass Lexan, Plexiglass, Epon, Conap, Uralane, Solithane, and Humiseal. A combined profile of the coefficient of thermal expansion (CTE) and the modulus change over a wide temperature range obtained by these analytical methods indicates the drastic effects of glass transition on both the CTE and the modulus of a polymer. TMA can also detect secondary transitions, and provides a convenient means for the study of a polymer's toughness.

Lee, Sheng Yen↗
DOE OSTI2026

High finesse buckled microcavities

Optical cavities are widely used in modern science and technology to enable a wide range of both quantum and classical applications. Recently, the growing demand for miniaturization and high performance has fueled the exploration of new fabrication methods beyond traditional polishing techniques and macroscopic mirrors. Visible and near-infrared (NIR) wavelengths are particularly important for quantum applications, where achieving low-loss resonators is also more challenging than in the telecom range, presenting unique challenges and opportunities for microscopic cavity systems. Here, we present a fabrication method for making NIR microcavities using buckled dielectric membrane mirrors, achieving a record finesse of 0.9 million at 780 nm for microcavities. We demonstrated flexible device geometries—including singular mirrors and mirror arrays, featuring radii of curvature ranging from 1 to 10 mm. The fabrication process offers high uniformity, high yield, and robust performance across a wide range of cavity lengths. Additionally, we can produce easy-to-assemble microcavity packages, with a total volume of ~2(4) mm 3 , featuring optical modes with a linewidth of 5.16 MHz (570 kHz) and a free spectral range (FSR) of 3.18 THz (150 GHz). Our results extend the frontier of microcavity fabrication for classical and quantum photonic technologies.

Ding, Sophie Weiyi [Harvard Univ., Cambridge, MA (↗
DOE OSTI2022

Monitoring of mechanical changes in a pipe assembly with complex geometry using multi-mode acoustic signals

Guided wave ultrasonic testing has been widely used for nondestructive and long-range evaluation of diverse mechanical structures, such as pipes and plates. In general, a large number of guided wave modes exist even in the simplest geometries, and they exhibit highly dispersive characteristics. Thus, sophisticated excitation methods and elaborate modal analyses need to be implemented to excite, acquire, and process well-defined pure modes as part of such a measurement method. If the interrogated structure has complex geometry, for example, with cross-sectional variations or multiple joints, the utilization of pure modes becomes significantly more difficult. To overcome this difficulty, this paper proposes the use of multi-mode, multi-frequency guided waves for long-range inspection of structures with arbitrarily complex geometries. Furthermore, using broadband chirp signals and multi-mode time–frequency analysis in a prototypical complex pipe assembly that includes multiple pipe diameters, elbows, and flange connections, we experimentally show sensitive detection of mechanical changes (both material addition and loss). In addition, we demonstrate that the complexity of the structure can be modeled in the digital domain with sufficient detail to allow accurate numerical simulation of the acoustic response using this method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Improving productivity and stability for CO 2 hydrogenation by using pincer-ligated Mn complexes with hemilabile ligands

Pincer ligands are widely used to support transition metal catalysts, but first-row systems often deactivate too quickly for widespread use. Here, pincer ligands bearing an additional hemilabile donor were designed to stabilize Mn catalysts for CO 2 hydrogenation to formate. Ligands of the type (RCH 2 CH 2 )N(CH 2 CH 2 P i Pr 2 ) 2 ( iPr PN R P; R = OMe, CH 2 OMe, NMe 2 , P i Pr 2 ) were synthesized and coordinated to Mn to form complexes of the type ( iPr PN R P)Mn(CO) 2 H. Their performance was compared to {MeN(CH 2 CH 2 P i Pr 2 ) 2 }Mn(CO) 2 H, which lacks a pendant donor. The pendant donor identity and arm length strongly influenced catalytic activity, but all pendant arm containing systems extended catalyst lifetime. Notably, ( iPr PN CH2OMe P)Mn(CO) 2 H achieved turnover frequencies of 158,000 h -1 and turnover numbers of 838,000, exceeding most state-of-the-art catalysts. Mechanistic studies revealed that hemilabile coordination enhances stability by avoiding deactivation, although excessive binding can lead to inactive states. Here, this work demonstrates hemilabile donors dramatically improve pincer-based Mn catalysts and provides design principles for broader applications.

CO2 hydrogenation↗
DOE OSTI2026

Geometrical optics without singularities: using the ray time as the coordinate space

Geometrical optics (GO) is widely used for reduced modelling of waves in plasmas, but it fails near reflection points, where it predicts a spurious singularity of the wave amplitude. We show how to avoid this singularity by adopting a different representation of the wave equation. Instead of the physical coordinate 𝑥 and the wavevector 𝑘, we use the ray time 𝜏 as the new canonical coordinate and the ray energy ℎ as the associated canonical momentum. To derive the envelope equation in the 𝜏-representation, we construct the Weyl symbol calculus on the (𝜏,ℎ) space and show that the corresponding Weyl symbols are related to their (𝑥,𝑘) counterparts by the Airy transform. This allows us to express the coefficients in the envelope equation through the known properties of the original dispersion operator. When necessary, solutions of this equation can be mapped to the 𝑥-space using a generalised metaplectic transform. However, the field per se might not even be needed in practice. Instead, knowing the corresponding Wigner function usually suffices for linear and quasilinear calculations. As a Weyl symbol itself, the Wigner function can be mapped analytically, using the aforementioned Airy transform. We show that the standard Airy patterns that form in regions where conventional GO fails are successfully reproduced within metaplectic GO (MGO) simply by remapping the field from the 𝜏-space to the 𝑥-space. An extension to mode-converting waves is also presented. This formulation, which we call generalised MGO, can be particularly useful, for example, for reduced modelling of the O–X conversion in inhomogeneous plasma near the critical density, an effect that is important for fusion applications and also occurs in the ionosphere. Overall, MGO can replace GO for any practical purposes, because it better handles cutoffs and is similar otherwise.

plasma waves↗
DOE OSTI2025

Benders Decomposition Using Graph Modeling and Multi-Parametric Programming

Benders decomposition is a widely used method for solving large and structured optimization problems, but its performance is affected by the repeated solution of subproblems. We propose a flexible and modular algorithmic framework for accelerating Benders decomposition. Specifically, we express the problem structure by using a graph-theoretic modeling abstraction in which nodes represent optimization subproblems and edges represent connectivity between subproblems. A key innovation of our approach is that we embed multiparametric programming (mp) surrogates for node subproblems, which maps the exact analytical map of the subproblem solution space. The use of mp surrogates allows us to replace subproblem solves with fast look-ups and function evaluations for primal and dual variables during the iterative Benders process. We formally show the equivalence between classical Benders cuts and those derived from the mp solution. We implement our framework in the open-source PlasmoBenders.jl software package. To demonstrate the capabilities of the proposed framework, we apply it to a two-stage stochastic programming problem, which aims to make optimal capacity expansion decisions under market uncertainty. We evaluate both single-cut and multicut variants of Benders decomposition and show that the use of mp surrogates achieves substantial speedups in subproblem solve time, while preserving the convergence guarantees of Benders decomposition. We highlight advantages in solution analysis and interpretability that is enabled by mp critical region tracking; specifically, we show that these reveal how decisions evolve geometrically across the Benders search. Our results aim to demonstrate that combining surrogate modeling with graph modeling offers a promising and extensible foundation for structure-exploiting decomposition. In addition, by decomposing the problem into more tractable subproblems, the proposed approach also aims to overcome scalability issues of mp. Finally, the use of mp surrogates provides a unifying and modular optimization framework that enables the representation of heterogeneous node subproblems as modeling objects with a homogeneous structure.

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

Phase Equilibrium of Water with Hexagonal and Cubic Ice Using the SCAN Functional

Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye toward studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ices Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Furthermore, our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic.

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

Robust Interpretation of Electrochemical Impedance Spectra Using Numerical Complex Analysis

Electrochemical Impedance Spectroscopy (EIS) is a noninvasive technique widely used for understanding charge transfer and charge transport processes in electrochemical systems and devices. Standard approaches for the interpretation of EIS data involve starting with a hypothetical circuit model for the physical processes in the device based on experience/intuition and then fitting the EIS data to this circuit model. This work explores a mathematical approach for extracting key characteristic features from EIS data by relying on fundamental principles of complex analysis. These characteristic features can suggest the presence of inductors and constant phase elements (nonideal capacitors) from impedance data and enable us to answer questions about the identifiability and nonuniqueness of equivalent circuit models. In certain scenarios such as models with only resistors and capacitors, we are able to enumerate all possible families of circuit models. Finally, we apply the mathematical framework presented here to real-world electrochemical systems and highlight results using impedance measurements from a lithium-ion battery coin cell.

charge transfer↗
DOE OSTI2020

Temporal X-ray Reconstruction using Temporal and Spectral Measurements at LCLS

Transverse deflecting structures (TDSs) are widely used in accelerator physics to measure the longitudinal density of particle bunches. When used in combination with a dispersive section, the whole longitudinal phase space density can be imaged. At the Linac Coherent Light Source (LCLS), the installation of such a device downstream of the undulators enables the reconstruction of the X-ray temporal intensity profile by comparing longitudinal phase space distributions with lasing on and lasing off. However, the resolution of this TDS is limited to around 1 fs rms (root mean square), and therefore, it is not possible to resolve single self-amplified spontaneous emission (SASE) spikes within an X-ray photon pulse. By combining the power spectrum from a high resolution photon spectrometer and the temporal structure from the TDS, the overall resolution is enhanced, thus allowing the observation of temporal, single SASE spikes. The combined data from the spectrometer and the TDS is analysed using an iterative algorithm to obtain the actual intensity profile. In this paper, we present some improvements to the reconstruction algorithm as well as real data taken at LCLS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Advancing Dynamic Modeling of Grid-Connected PV Inverter Using Bi-LSTM-Based AI Model

Power electronic converters (PECs) are widely used in modern power systems to facilitate the interconnection between various AC or DC sources and loads. Because of the extensive integration, the power system has grown into a more dynamic system in which the dynamics of the PECs must be adequately modeled. The paper presents a new bidirectional long short-term memory (Bi-LSTM) method for evaluating grid-connected inverter-based resources (IBR) dynamics. The method is tested using real hardware data from a grid -connected commercial inverter in laboratory experiments. Results show the Bi-LSTM model accurately reproduces the detailed IBR model's dynamics, even when the internal structure is unknown and parameters are unknown, preventing the disclosure of the manufacturer's confidential data.

Subedi, Sunil [ORNL] (ORCID:000000034069090X)↗
DOE OSTI2026

Efficient CP Rounding Using Alternating Least Squares with QR Decomposition

The CANDECOMP/PARAFAC (CP) decomposition is widely used for analyzing multidimensional data, and the alternating least squares (CP-ALS) algorithm is a common method for its computation. CP rounding is the problem of computing a lower-rank CP decomposition of an input already in a higher-rank CP format. While the normal equations (NE) approach in CP-ALS is efficient for the CP rounding problem and frequently used, it becomes unstable in the presence of ill-conditioned subproblems. This paper presents a new QR-based CP-ALS method for CP rounding that preserves both numerical stability and computational efficiency. Here, our experiments show that the proposed method offers significant speedup over a previous QR-based approach and the Tensor Toolbox's NE-based implementation, particularly for higher-order tensors. Furthermore, our approach demonstrates a marked reduction in error for ill-conditioned problems, with error reductions several orders of magnitude smaller compared to the NE-based method, while achieving faster convergence and more accurate solutions. By using a more numerically stable approach, we can solve more problems in reduced working precision, which enables further reduction in time to solution.

CANDECOMP/PARAFAC↗
DOE OSTI2025

Probing the pH Effect on Boehmite Particles in Water Using Vacuum Ultraviolet Single-Photon Ionization Mass Spectrometry

Boehmite has been widely used in theoretical research and industry, especially for hazardous material processing. For the liquid-phase treating process, the interfacial properties of boehmite are believed to be affected by pH conditions, which change its physicochemical behavior. However, molecular-level detection on cluster ions is challenging when using bulk approaches. Herein we employ in situ vacuum ultraviolet single-photon ionization mass spectrometry (VUV SPI-MS) coupled with a vacuum-compatible microreactor system for analysis at the liquid–vacuum interface (SALVI) to investigate the solute molecular composition of boehmite under different pH conditions for the first time. The mass spectral results show that more complex clustering of solute molecules exists at the solid–liquid (s–l) interface than conventionally perceived in a “simple” aqueous solution. Besides solute ions, such as boehmite molecules and fragments, the composition and appearance energies of these newly discovered solvated cluster ions are determined by VUV SPI-MS in different pH solutions. We offer new results for the pH-dependent effect of boehmite and provide insights into a more detailed solvation mechanism at the s–l interface. By comparing the key products under different pH conditions, fundamental understanding of boehmite dissolution is revealed to assist the engineering design of waste processing and storage solutions.

SALVI↗
NASA NTRS2015

Wind Tunnel Interference Effects on Tilt Rotor Testing Using Computational Fluid Dynamics

Experimental techniques to measure rotorcraft aerodynamic performance are widely used. However, most of them are either unable to capture interference effects from bodies, or require an extremely large computational budget. The objective of the present research is to develop an XV-15 Tilt Rotor Research Aircraft rotor model for investigation of wind tunnel wall interference using a novel Computational Fluid Dynamics (CFD) solver for rotorcraft, RotCFD. In RotCFD, a mid-fidelity URANS solver is used with an incompressible flow model and a realizable k-ε turbulence model. The rotor is, however, not modeled using a computationally expensive, unsteady viscous body-fitted grid, but is instead modeled using a blade element model with a momentum source approach. Various flight modes of the XV-15 isolated rotor, including hover, tilt and airplane mode, have been simulated and correlated to existing experimental and theoretical data. The rotor model is subsequently used for wind tunnel wall interference simulations in the National Full-Scale Aerodynamics Complex (NFAC) at NASA Ames Research Center in California. The results from the validation of the isolated rotor performance showed good correlation with experimental and theoretical data. The results were on par with known theoretical analyses. In RotCFD the setup, grid generation and running of cases is faster than many CFD codes, which makes it a useful engineering tool. Performance predictions need not be as accurate as high-fidelity CFD codes, as long as wall effects can be properly simulated. For both test sections of the NFAC wall interference was examined by simulating the XV-15 rotor in the test section of the wind tunnel and with an identical grid but extended boundaries in free field. Both cases were also examined with an isolated rotor or with the rotor mounted on the modeled geometry of the Tiltrotor Test Rig (TTR). A 'quasi linear trim' was used to trim the thrust for the rotor to compare the power as a unique variable. Power differences between free field and wind tunnel cases were found from -7 % to 0 % in the 80- by 120-Foot Wind Tunnel test section and -1.6 % to 4.8 % in the 40- by 80-Foot Wind Tunnel, depending on the TTR orientation, tunnel velocity and blade setting. The TTR will be used in 2016 to test the Bell 609 rotor in a similar fashion to the research in this report.

CFD↗
NASA NTRS2016

Wind Tunnel Interference Effects on Tilt Rotor Testing Using Computational Fluid Dynamics

Experimental techniques to measure rotorcraft aerodynamic performance are widely used. However, most of them are either unable to capture interference effects from bodies, or require an extremely large computational budget. The objective of the present research is to develop an XV-15 Tiltrotor Research Aircraft rotor model for investigation of wind tunnel wall interference using a novel Computational Fluid Dynamics (CFD) solver for rotorcraft, RotCFD. In RotCFD, a mid-fidelity Unsteady Reynolds Averaged Navier-Stokes (URANS) solver is used with an incompressible flow model and a realizable k-ε turbulence model. The rotor is, however, not modeled using a computationally expensive, unsteady viscous body-fitted grid, but is instead modeled using a blade-element model (BEM) with a momentum source approach. Various flight modes of the XV-15 isolated rotor, including hover, tilt, and airplane mode, have been simulated and correlated to existing experimental and theoretical data. The rotor model is subsequently used for wind tunnel wall interference simulations in the National Full-Scale Aerodynamics Complex (NFAC) at Ames Research Center in California. The results from the validation of the isolated rotor performance showed good correlation with experimental and theoretical data. The results were on par with known theoretical analyses. In RotCFD the setup, grid generation, and running of cases is faster than many CFD codes, which makes it a useful engineering tool. Performance predictions need not be as accurate as high-fidelity CFD codes, as long as wall effects can be properly simulated. For both test sections of the NFAC wall, interference was examined by simulating the XV-15 rotor in the test section of the wind tunnel and with an identical grid but extended boundaries in free field. Both cases were also examined with an isolated rotor or with the rotor mounted on the modeled geometry of the Tiltrotor Test Rig (TTR). A "quasi linear trim" was used to trim the thrust for the rotor to compare the power as a unique variable. Power differences between free field and wind tunnel cases were found from -7 to 0 percent in the 80- by 120-Foot Wind Tunnel and -1.6 to 4.8 percent in the 40- by 80-Foot Wind Tunnel, depending on the TTR orientation, tunnel velocity, and blade setting. The TTR will be used in 2016 to test the Bell 609 rotor in a similar fashion to the research in this report.

CFD↗
NASA NTRS2015

Implications for Climate Sensitivity from the Response to Individual Forcings

Climate sensitivity to doubled CO2 is a widely-used metric of the large-scale response to external forcing. Climate models predict a wide range for two commonly used definitions: the transient climate response (TCR: the warming after 70 years of CO2 concentrations that riseat 1 per year), and the equilibrium climate sensitivity (ECS: the equilibrium temperature change following a doubling of CO2 concentrations). Many observational datasets have been used to constrain these values, including temperature trends over the recent past 16, inferences from paleo-climate and process-based constraints from the modern satellite eras. However, as the IPCC recently reported different classes of observational constraints produce somewhat incongruent ranges. Here we show that climate sensitivity estimates derived from recent observations must account for the efficacy of each forcing active during the historical period. When we use single forcing experiments to estimate these efficacies and calculate climate sensitivity from the observed twentieth-century warming, our estimates of both TCR and ECS are revised upward compared to previous studies, improving the consistency with independent constraints.

Sensitivity↗
DOE OSTI2022

Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM

We report three-dimensional (3D) X-ray micro-computed tomography (μCT) has been widely used in petroleum engineering because it can provide detailed pore structural information for a reservoir rock, which can be imported into a pore-scale numerical model to simulate the transport and distribution of multiple fluids in the pore space. The partial volume blurring (PVB) problem is a major challenge in segmenting raw μCT images of rock samples, which impacts boundaries and small targets near the resolution limit. We developed a deep-learning (DL)-based workflow for accurate and fast partial volume segmentation. The DL model's performance depends primarily on the training data quality and model architecture. This study employed the entropy-based-masking indicator kriging (IK-EBM) to segment 3D Berea sandstone images as training datasets. The comparison between IK-EBM and manual segmentation using a 3D synthetic sphere pack, which had a known ground truth, showed that IK-EBM had higher accuracy on partial volume segmentation. We then trained and tested the UNet++ model, a state-of-the-art supervised encoder-decoder model, for binary (i.e., void and solid) and four-class segmentation. We compared the UNet++ with the commonly used U-Net and wide U-Net models and showed that the UNet++ had the best performance in terms of pixel-wise and physics-based evaluation metrics. Specifically, boundary-scaled accuracy demonstrated that the UNet++ architecture outperformed the regular U-Net architecture in the segmentation of pixels near boundaries and small targets, which were subjected to the PVB effect. Feature map visualization illustrated that the UNet++ bridged the semantic gaps between the feature maps extracted at different depths of the network, thereby enabling faster convergence and more accurate extraction of fine-scale features. The developed workflow significantly enhances the performance of supervised encoder-decoder models in partial volume segmentation, which has extensive applications in fundamental studies of subsurface energy, water, and environmental systems.

02 PETROLEUM↗
NASA NTRS2005

Performance Characterization of a Prototype Ultra-Short Channel Monolith Catalytic Reactor for Air Quality Control Applications

Contaminated air and process gases, whether in a crewed spacecraft cabin atmosphere, the working volume of a microgravity science or ground-based laboratory experiment facility, or the exhaust from an automobile, are pervasive problems that ultimately effect human health, performance, and well-being. The need for highly-effective, economical decontamination processes spans a wide range of terrestrial and space flight applications. Adsorption processes are used widely for process gas decontamination. Most industrial packed bed adsorption processes use activated carbon because it is cheap and highly effective. Once saturated, however, the adsorbent is a concentrated source of contaminants. Industrial applications either dump or regenerate the activated carbon. Regeneration may be accomplished in-situ or at an off-site location. In either case, concentrated contaminated waste streams must be handled appropriately to minimize environmental impact. As economic and regulatory forces drive toward minimizing waste and environmental impact, thermal catalytic oxidation is becoming more attractive. Through novel reactor and catalyst design, more complete contaminant destruction and greater resistance to poisoning can achieved leading to less waste handling, process down-time, and maintenance. Performance of a prototype thermal catalytic reactor, based on ultra-short channel monolith (USCM) catalyst substrate design, under a variety of process flow and contaminant loading conditions is discussed. The experimental results are evaluated against present and future air quality control and process gas purification processes used on board crewed spacecraft.

Perry, J. L.↗