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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
NASA NTRS1991

Multicomponent gas sorption Joule-Thomson refrigeration

The present invention relates to a cryogenic Joule-Thomson refrigeration capable of pumping multicomponent gases with a single stage sorption compressor system. Alternative methods of pumping a multicomponent gas with a single stage compressor are disclosed. In a first embodiment, the sorbent geometry is such that a void is defined near the output of the sorption compressor. When the sorbent is cooled, the sorbent primarily adsorbs the higher boiling point gas such that the lower boiling point gas passes through the sorbent to occupy the void. When the sorbent is heated, the higher boiling point gas is desorbed at high temperature and pressure and thereafter propels the lower boiling point gas out of the sorption compressor. A mixing chamber is provided to remix the constituent gases prior to expansion of the gas through a Joule-Thomson valve. Other methods of pumping a multicomponent gas are disclosed. For example, where the sorbent is porous and the low boiling point gas does not adsorb very well, the pores of the sorbent will act as a void space for the lower boiling point gas. Alternatively, a mixed sorbent may be used where a first sorbent component physically adsorbs the high boiling point gas and where the second sorbent component chemically absorbs the low boiling point gas.

Jones, Jack A.↗
NASA NTRS1994

Characterization of nanocrystallites in porous p-type 6H-SiC

We report the formation of porous p-type 6H-SiC. The existence of uniformly dispersed pores was confirmed by transmission electron microscopy, with interpore spacings in the range of 1-10 nm. The porous film as a whole is a single crystal. Luminescence peaks above the normal band gap of 6H-SiC have been observed in the porous layer, but were not distinguished in the bulk SiC substrate. Quantum confinement is discussed as a possible mechanism for the luminescence effects.

Shor, J. S.↗
DOE OSTI2020

Molecular Insight into Fluorocarbon Adsorption in Pore Expanded Metal–Organic Framework Analogs

The rapid growth in the global energy demand for space cooling requires the development of more efficient environmental chillers for which adsorption-based cooling systems can be utilized. Here, in this contribution, we explore sorbents for chiller use via a pore-engineering concept to construct analogs of the 1-dimensional pore metal–organic framework MOF-74 by using elongated organic linkers and stereochemistry control. The prepared pore-engineered MOFs show remarkable equilibrium adsorption of the selected fluorocarbon refrigerant that is translated to a modeled adsorption-based refrigeration cycle. To probe molecular level interactions at the origin of these unique adsorption properties for this series of Ni-MOFs, we combined in situ synchrotron X-ray powder diffraction, neutron powder diffraction, X-ray absorption spectroscopy, calorimetry, Fourier transform infrared techniques, and molecular simulations. Our results reveal the coordination of fluorine (of CH2F in R134a) to the nickel(II) open metal centers at low pressures for each Ni-MOF analog and provide insight into the pore filling mechanism for the full range of the adsorption isotherms. The newly designed Ni-TPM demonstrates exceptional R134a adsorption uptake compared to its parent microporous Ni-MOF-74 due to larger engineered pore size/volume. The application of this adsorption performance toward established chiller conditions yields a working capacity increase for Ni-TPM of about 400% from that of Ni-MOF-74, which combined with kinetics directly correlates to both a higher coefficient of performance and a higher average cooling capacity generated in a modeled chiller.

Zheng, Jian↗
DOE OSTI2024

Time‐And‐Space Averaging Applied to Intermittent Multiphase Flow Experiments

Abstract Various researchers have studied fluctuations in pore‐scale phase occupancy during multiphase flow in porous media using synchrotron‐based X‐ray microcomputed tomography (micro‐CT). However, the impact of these fluctuations on the concept of a representative volume is not yet fully understood. In this study, we performed spatial and temporal averaging of multiphase flow experiments visualized with synchrotron‐based micro‐CT, focusing on oil saturation as the key parameter to determine a representative time‐and‐space average. Our findings revealed that a saturation value representative of both time and space was achieved during fractional flow experiments in drainage mode with fractional flows of 0.8, 0.5, and 0.3. Furthermore, we computed a range of relative permeabilities on the basis of whether momentaneous saturation or time‐and‐space averaged saturation was utilized for direct simulation. Our results highlighted the importance of time‐and‐space averaging in determining a representative relative permeability and indicated that the temporal and spatial scales covered in a typical micro‐CT flow experiment were sufficient to obtain a representative saturation value for sandstone rock under intermittent flow conditions.

Environmental Sciences & Ecology↗
DOE OSTI2024

Assessing Composite Structure in Metal–Organic Framework-Polymer Mixed-Matrix Membranes

Metal-organic frameworks (MOFs) are renowned for their tunable structure, porosity, and internal chemistry, with demonstrated applications in molecular separations, storage, and conversion. While they are widely usable, the powdery characteristics of MOF materials can be limiting for large-scale processing and implementation in devices. Incorporating MOF particles into polymer supports affords engineering solutions to overcome these issues, yet the nature of the resulting composites is difficult to assess. Here, in this work, we present spectroscopic and calorimetric methods that we believe help establish a holistic physicochemical picture of the composite structure using a series of Zr MOFs with different pore sizes as a testbed. Power law decays are observed in X-ray scattering profiles in low q-space ranging between 2.4 and 3.3, which we interpret as changes in scattering due to polymer infiltrating MOF particles. This interpretation is supported by solid-state nuclear magnetic resonance spectroscopy and differential scanning calorimetry measurements that identify populations of the MOF-associated polymer. Additionally, positron annihilation lifetime spectroscopy measurements collected on a series of composites with different MOF-polymer ratios show multiple decay constants, each correlated to a different free volume elements. In combination with the spectroscopic, calorimetric, and scattering results, we utilize the trends in decay constants as a function of polymer mass fraction to hypothesize a polymer infiltration mechanism whereby large pores are preferentially filled, followed by small pores and, later still, interstitial spaces between particles. Even with vigorous investigation of polymer, MOF, and interface characteristics, the complex and heterogeneous nature of the composites makes absolute structural assertions difficult. We envision that the approaches demonstrated here will be a useful foundation to assess and ultimately guide the design of future MOF-polymer composites.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Thermo-hydro-mechanical analysis of subsurface ice-based thermal energy storage

Ice-based thermal energy storage systems are widely utilized for cooling and managing peak electrical demand globally, offering daily or weekly storage capabilities for both individual homes and larger office buildings. However, scaling these systems for district-level cooling or integrating them with renewable energy sources presents challenges, especially in accommodating larger volumes and addressing seasonal storage requirements in densely populated urban areas. This paper proposes a novel solution by evaluating subsurface ice-based thermal energy storage, in which the underground is subjected to seasonal freeze/thaw cycles. However, these cycles may influence ground behavior, affecting pore pressure and inducing ground movement. To systematically investigate these challenges, we enhance the TOUGH-FLAC simulator by integrating water/ice phase change capabilities and updating the effective stress–strain constitutive relation. Both modifications are validated against analytical solutions or experimental data. Through numerical simulations spanning a decade with ten seasonal freeze/thaw cycles, we evaluate the performance and long-term stability of a generic subsurface ice-based thermal energy storage system, considering factors such as ground permeability, freezing pipe spacing, freeze/thaw damage, and glycol solution temperature. The simulations indicate that ice formation induces pore pressure variations that drive seasonal surface heave and settlement, controlled by ground permeability, pipe spacing, and glycol solution temperature, along with tensile and localized shear deformation around freeze pipes. This highlights the need for accurate ground property characterization and geomechanical analysis for subsurface ice-based thermal energy storage.

Ground freezing↗
NASA NTRS2006

On-Orbit Testing of Materials and Processes

The Pore Formation and Mobility Investigation (PFMI) and the In-Space Soldering Investigation (ISSI) were conducted aboard the International Space Station (ISS) with the intent of promoting our understanding of materials processing in a low-gravity environment. The numerous experiments were conducted by telescience with the results evaluated by real time video and subsequently returned tapes and samples. In addition to discussing the experimental results and analysis the presentation will include an account of the ISS facilities (Microgravity Science Glovebox and Maintenance Work Area) used as well as some lessons-learned comments.

Grugel, R. N.↗
DOE OSTI2021

Non-linear hydrologic organization

We revisit three variants of the well-known Stommel diagrams that have been used to summarize knowledge of characteristic scales in time and space of some important hydrologic phenomena and modified these diagrams focusing on spatiotemporal scaling analyses of the underlying hydrologic processes. In the present paper we focus on soil formation, vegetation growth, and drainage network organization. We use existing scaling relationships for vegetation growth and soil formation, both of which refer to the same fundamental length and timescales defining flow rates at the pore scale but different powers of the power law relating time and space. The principle of a hierarchical organization of optimal subsurface flow paths could underlie both root lateral spread (RLS) of vegetation and drainage basin organization. To assess the applicability of scaling, and to extend the Stommel diagrams, data for soil depth, vegetation root lateral spread, and drainage basin length have been accessed. The new data considered here include timescales out to 150 Myr that correspond to depths of up to 240 m and horizontal length scales up to 6400 km and probe the limits of drainage basin development in time, depth, and horizontal extent.

58 GEOSCIENCES↗
DOE OSTI2024

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

42 ENGINEERING↗
NASA NTRS1993

Performance of high resolution decoding with Multi-Anode Microchannel Array detectors

The Multi-Anode Microchannel Array (MAMA) is a microchannel plate based photon counting detector with applications in ground-based and space-based astronomy. The detector electronics decode the position of each photon event, and the decoding algorithm that associates a given event with the appropriate pixel is determined by the geometry of the anode array. The standard MAMA detector has a spatial resolution set by the anode array of 25 microns, but the MCP pore resolution exceeds this. The performance of a new algorithm that halves the pixel spacing and improves the pixel spatial resolution is described. The new algorithm does not degrade the pulse-pair resolution of the detector and does not require any modifications to the detector tube. Measurements of the detector's response demonstrate that high resolution decoding yields a 60 percent enhancement in spatial resolution. Measurements of the performance of the high resolution algorithm with a 14 micron MAMA detector are also described. The parameters that control high resolution performance are discussed. Results of the application of high resolution decoding to speckle interferometry are presented.

Kasle, David B.↗
DOE OSTI2021

Contrasting thermally-induced structural and microstructural evolution of alumino-silicates with tubular and planar arrangements: Case study of halloysite and kaolinite

Materials with the similar chemical structures but different morphological organization exhibit considerable differences in thermally induced chemo-morphological evolution. With recent advancements in multi-scale X-ray scattering measurements, it is now possible to non-invasively probe the structural and microstructural evolution of such materials. In this study, we investigate the chemo-morphological evolution of halloysite and contrast the results with those for kaolinite. Halloysite and kaolinite have tubular and planar morphologies, respectively. Both materials are alumino-silicates comprising silica tetrahedra (T) and alumina octahedra (O) organized in a TO structure. Four distinct stages in the structural evolution were identified. Stages I, II, III, and IV correspond to temperature ranges of 25 to 125 °C, 125 to 400 °C, 400 to 625 °C, and 625 to 875 °C. Major structural changes correspond to the removal of interlayer/adsorbed water in stage I, the existence of the halloysite structure without interlayer water in stage II, dehydroxylation of halloysite in stage III, and the conversion of ordered halloysite to amorphous meta-halloysite in stage IV. Additionally, heating halloysite up to 875 °C resulted in slight widening of the nanotubes, as the average pore radius increased from 6.4 nm to 6.6 nm. Heating also resulted in an increase of wall thickness of the nanotubes from ~120 nm (25 °C) to 161 nm (875 °C). The increase in the halloysite nanotube diameter was attributed to the expansion of the structure and an increase in the surface roughness. The pore sizes in halloysite nanotubes were also confirmed using N 2 adsorption-desorption and nano-X-ray computed tomography (nano-XCT) measurements. The interlayer basal spacing in halloysite changed from 9.8 Å to 7.2 Å after the removal of interlayer water. At temperatures in the range of 625 to 875 °C, heating halloysite causes a small widening of nanotube pores and a minor increase in the surface area. In contrast, the interlayer spacing in kaolinite collapses on heating which reduces the nanoscale porosity. Furthermore, these studies demonstrate the differences in the chemo-morphological evolution of alumino-silicates with tubular and planar morphologies.

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

CO 2 capture from wet flue gas using a water-stable and cost-effective metal-organic framework

We report the use of MIL-120 as a water-stable and cost-effective metal-organic framework (MOF) for selectively capturing CO 2 from wet flue gas. Synthesized using inexpensive and environmentally benign reagents in water, MIL-120 possesses one-dimensional pores decorated with hydroxyl-bridged Al(III) ions and benzene rings with an interstitial spacing of 4.78 Å. Carbon dioxide isotherms show steep uptake at low pressure, and the affinity of MIL-120 for CO 2 is 44 kJ mol –1 . CO 2 -loading 13 C solid-state nuclear magnetic resonance and Fourier transform infrared spectra tracking the sorption of CO 2 into MIL-120 revealed that the interplay of pore size, functionality, and dimensionality is vital for CO 2 restriction within the pores of MIL-120. Breakthrough experiments reveal that MIL-120 can capture CO 2 from dry and wet flue gas with uptake capacities of 1.215 and 1.118 mmol g –1 , respectively. Our work highlights the synthetic benefits of MIL-120 and elucidates its selective capture of CO 2 from wet flue gas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2001

Effect of Marangoni Convection Generated by Voids on Segregation During Low-G and 1-G Solidification

Solidification experiments, especially microgravity solidification experiments, are often compromised by the evolution of unwanted voids or bubbles in the melt. Although these voids and/or bubbles are highly undesirable, there is currently no effective means of preventing their formation or of eliminating their adverse effects, particularly during microgravity experiments. Marangoni convection caused by these voids can drastically change the transport processes in the melt. Recent microgravity experiments by Matthiesen (1) Andrews (2) and Fripp (3) are perfect examples of how voids and bubbles can affect the outcome of costly space experiments and significantly increase the level of difficulty in interpreting their results. Formation of bubbles have caused problems in microgravity experiments for a long time. Even in the early Skylab mission an unexpectedly large number of bubbles were detected in the four materials processing experiments reported by Papazian and Wilcox (4). They demonstrated that while during ground-based tests bubbles were seen to detach from the interface easily and float to the top of the melt, in low-gravity tests no detachment from the interface occurred and large voids were grown in the crystal. More recently, the lead-tin-telluride crystal growth experiment of Fripp et al.(3) flown aboard the USMP-3 mission has provided very interesting results. The purpose of the study was to investigate the effect of natural convection on the solidification process by growing the samples at different orientations with respect to the gravitational field. Large pores and voids were found in the three solid crystal samples processed in space. Post-growth characterization of the compositional profiles of the cells indicated considerable levels of mixing even in the sample grown in the hot-on-top stable configuration. The mixing was attributed to thermocapillary convection caused by the voids and bubbles which evolved during growth. Since the thermocapillary convection is orientation-independent, diffusion-controlled growth was not possible in any of the samples, even the top-heated one. These results are consistent with recent studies of thermocapillary convection generated by a bubble on a heated surface undertaken by Kassemi and Rashidnia (5-7) where it is numerically and experimentally shown that the thermocapillary flow generated by a bubble in a model fluid (silicone oil) can drastically modify the temperature field through vigorous mixing of the fluid around it, especially under microgravity conditions.

Kassemi, M.↗
DOE OSTI2020

From particle attachment to space-filling coral skeletons

Reef-building corals and their aragonite (CaCO 3 ) skeletons support entire reef ecosystems, yet their formation mechanism is poorly understood. Here we used synchrotron spectromicroscopy to observe the nanoscale mineralogy of fresh, forming skeletons from six species spanning all reef-forming coral morphologies: Branching, encrusting, massive, and table. In all species, hydrated and anhydrous amorphous calcium carbonate nanoparticles were precursors for skeletal growth, as previously observed in a single species. The amorphous precursors here were observed in tissue, between tissue and skeleton, and at growth fronts of the skeleton, within a low-density nano- or microporous layer varying in thickness from 7 to 20 µm. Brunauer-Emmett-Teller measurements, however, indicated that the mature skeletons at the microscale were space-filling, comparable to single crystals of geologic aragonite. Nanoparticles alone can never fill space completely, thus ion-by-ion filling must be invoked to fill interstitial pores. Such ion-by-ion diffusion and attachment may occur from the supersaturated calcifying fluid known to exist in corals, or from a dense liquid precursor, observed in synthetic systems but never in biogenic ones. Concomitant particle attachment and ion-by-ion filling was previously observed in synthetic calcite rhombohedra, but never in aragonite pseudohexagonal prisms, synthetic or biogenic, as observed here. Models for biomineral growth, isotope incorporation, and coral skeletons’ resilience to ocean warming and acidification must take into account the dual formation mechanism, including particle attachment and ion-by-ion space filling.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2011

Characterization of the as Manufactured Variability in a CVI SiC/SiC Woven Composite

The microstructure of a 2D woven ceramic matrix composite displays significant variability and irregularity. For example, a chemical vapor infiltrated (CVI) SiC/SiC composite exhibits significant amount of porosity arranged in irregular patterns. Furthermore, the fiber tows within a ply frequently have irregular shape and spacing, and the stacked plies are often misaligned and irregularly nested within each other. The goal of an ongoing project at NASA Glenn is to investigate the effects of the complex microstructure and its variability on the properties and the durability of the material. One key requirement for this effort is the development of methods to characterize the distribution in as-fabricated ceramic matrix composite (CMC) microstructures with the objective of correlating microstructural distribution parameters with mechanical performance. An initial task in this effort was to perform quantitative image analysis of polished cross sections of CVI SiC/SiC composite specimens. This analysis provided sample distributions of various microstructural composite features, including: inter-tow pore sizes and shapes, transverse sectioned tow sizes and shapes, and within ply tow spacing. This information can then be used to quantify the effect of extreme values of these features on the local stress state with the goal of determining the likelihood of matrix cracking at a given external load.

Bonacuse, Peter J.↗
DOE OSTI2020

Ultra-breathable and protective membranes with sub-5 nm carbon nanotube pores

In one embodiment, a product includes a plurality of carbon nanotubes and a fill material in interstitial spaces between the carbon nanotubes for limiting or preventing fluidic transfer between opposite sides of the product except through interiors of the carbon nanotubes. Moreover, the longitudinal axes of the carbon nanotubes are substantially parallel, where an average inner diameter of the carbon nanotubes is about 20 nanometers or less. In addition, the ends of the carbon nanotubes are open and the fill material is impermeable or having an average porosity that is less than the average inner diameter of the carbon nanotubes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Uncovering acoustic signatures of pore formation in laser powder bed fusion

Abstract We present a machine learning workflow to discover signatures in acoustic measurements that can be utilized to create a low-dimensional model to accurately predict the location of keyhole pores formed during additive manufacturing processes. Acoustic measurements were sampled at 100 kHz during single-layer laser powder bed fusion (LPBF) experiments, and spatio-temporal registration of pore locations was obtained from post-build radiography. Power spectral density (PSD) estimates of the acoustic data were then decomposed using non-negative matrix factorization with custom $$\varvec{k}$$ k -means clustering (NMF $$\varvec{k}$$ k ) to learn the underlying spectral patterns associated with pore formation. NMF $$\varvec{k}$$ k returned a library of basis signals and matching coefficients to blindly construct a feature space based on the PSD estimates in an optimized fashion. Moreover, the NMF $$\varvec{k}$$ k decomposition led to the development of computationally inexpensive machine learning models which are capable of quickly and accurately identifying pore formation with classification accuracy of supervised and unsupervised label learning greater than 95% and 90%, respectively. The intrinsic data compression of NMF k , the relatively light computational cost of the machine learning workflow, and the high classification accuracy makes the proposed workflow an attractive candidate for edge computing toward in-situ keyhole pore prediction in LPBF.

36 MATERIALS SCIENCE↗