Search NASA⌕ Search

SEARCH · Search NASA

Results for “Pore architecture”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Influence of Pore Length on Hydrogenolysis of Polyethylene within a Mesoporous Support Architecture

Due to the plastic waste crisis, selective chemical upcycling of polyolefins into value-added products is a topic of intense interest, demanding polymer deconstruction processes that afford control over the product chain lengths. Recently, a catalytic architecture was synthesized in which a polyolefin melt infiltrates a porous support, and its chains are cleaved by a metal nanoparticle catalyst at the bottom of the pores, yielding a narrow distribution of alkane products. Although the influence of various parameters of these catalytic materials, including the effects of the nanoparticle size and pore diameter on product chain length, has been examined before, here, we investigate the role of the pore length in the cleavage process through the first study that combines catalytic hydrogenolysis and coarse-grained modeling to gain insights not available by experiment alone. We show that the pore length can permit control over the average product length with qualitative agreement between experiment and simulation. In conclusion, we go beyond this observation to uncover the dynamic phenomenon responsible for the pore-length dependence of the cleavage products.

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

Size-Controlled Nanoparticles Embedded in a Mesoporous Architecture Leading to Efficient and Selective Hydrogenolysis of Polyolefins

A catalytic architecture, comprising a mesoporous silica shell surrounding platinum nanoparticles (NPs) supported on a solid silica sphere (mSiO2/Pt-X/SiO2; X is the mean NP diameter), catalyzes hydrogenolysis of melt-phase polyethylene (PE) into a narrow C23-centered distribution of hydrocarbons in high yield using very low Pt loadings (~10 -5 g Pt/g PE). During catalysis, a polymer chain enters a pore and contacts a Pt NP where the C–C bond cleavage occurs and then the smaller fragment exits the pore. mSiO 2 /Pt/SiO 2 resists sintering or leaching of Pt and provides high yields of liquids; however, many structural and chemical effects on catalysis are not yet resolved. Here, we report the effects of Pt NP size on activity and selectivity in PE hydrogenolysis. Time-dependent conversion and yields and a lumped kinetics model based on the competitive adsorption of long vs short chains reveal that the activity of catalytic material is highest with the smallest NPs, consistent with a structure-sensitive reaction. Remarkably, the three mSiO 2 /Pt-X/SiO 2 catalysts give equivalent selectivity. We propose that mesoscale pores in the catalytic architecture template the C 23 -centered distribution, whereas the active Pt sites influence the carbon–carbon bond cleavage rate. This conclusion provides a framework for catalyst design by separating the C–C bond cleavage activity at catalytic sites from selectivity for chain lengths of the products influenced by the structure of the catalytic architecture. The increased activity, selectivity, efficiency, and lifetime obtained using this architecture highlight the benefits of localized and confined environments for isolated catalytic particles under condensed-phase reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2006

Process for the preparation of metal-containing nanostructured films

Metal-containing nanostructured films are prepared by electrodepositing a metal-containing composition within the pores of a mesoporous silica template to form a metal-containing silica nanocomposite. The nanocomposite is annealed to strengthen the deposited metal-containing composition. The silica is then removed from the nanocomposite, e.g., by dissolving the silica in an etching solution to provide a self-supporting metal-containing nanostructured film. The nanostructured films have a nanowire or nanomesh architecture depending on the pore structure of the mesoporous silica template used to prepare the films.

Lu, Yunfeng↗
DOE OSTI2022

Gradient Architecture Design in Scalable Porous Battery Electrodes

Because it has been demonstrated to be effective toward faster ion diffusion inside the pore space, low-tortuosity porous architecture has become the focus in thick electrode designs, and other possibilities are rarely investigated. Here, to advance current understanding in the structure-affected electrochemistry and to broaden horizons for thick electrode designs, we present a gradient electrode design, where porous channels are vertically aligned with smaller openings on one end and larger openings on the other. With its 3D morphology carefully visualized by Raman mapping, the electrochemical properties between opposite orientations of the gradient electrodes are compared, and faster energy storage kinetics is found in larger openings and more concentrated active material near the separator. As further verified by simulation, this study on gradient electrode design deepens the knowledge of structure-related electrochemistry and brings perspectives in high-energy battery electrode designs.

25 ENERGY STORAGE↗
DOE OSTI2023

Two Mesoporous Domains Are Better Than One for Catalytic Deconstruction of Polyolefins

Catalytic hydrogenolysis of polyolefins into valuable liquid, oil, or wax-like hydrocarbon chains for second-life applications is typically accompanied by the hydrogen-wasting co-formation of low value volatiles, notably methane, that increase greenhouse gas emissions. Catalytic sites confined at the bottom of mesoporous wells, under conditions in which the pore exerts the greatest influence over the mechanism, are capable of producing less gases than unconfined sites. A new architecture was designed to emphasize this pore effect, with the active platinum nanoparticles embedded between linear, hexagonal mesoporous silica and gyroidal cubic MCM-48 silica (mSiO 2 /Pt/MCM-48). This catalyst deconstructs polyolefins selectively into ~C 20 –C 40 paraffins and cleaves C–C bonds at a rate (TOF = 4.2 ± 0.3 s –1 ) exceeding that of materials lacking these combined features while generating negligible volatile side products including methane. The time-independent product distribution is consistent with a processive mechanism for polymer deconstruction. In contrast to time- and polymer length-dependent products obtained from non-porous catalysts, mSiO 2 /Pt/MCM-48 yields a C 28 -centered Gaussian distribution of waxy hydrocarbons from polyolefins of varying molecular weight, composition, and physical properties, including low-density polyethylene, isotactic polypropylene, ultrahigh-molecular-weight polyethylene, and mixtures of multiple, post-industrial polyolefins. Here, coarse-grained simulation reveals that the porous-core architecture enables the paraffins to diffuse away from the active platinum site, preventing secondary reactions that produce gases.

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

Temperature-Following Thermal Barrier Coatings for High Efficiency Engines (Final Report)

HRL Laboratories and General Motors (GM), pursued this effort to increase the efficiency of internal combustion engines (ICEs) by developing and implementing temperature-following thermal barrier coatings (TBCs) to decrease heat loss from the combustion chamber. HRL developed microsphere TBCs based on hollow high-temperature alloy spheres with average diameter of 50 μm and wall thickness ~1 μm (microspheres) that achieve unprecedented low thermal conductivity and heat capacity (10X lower than the state of the art) while offering exceptional environmental and mechanical resistance.> In current ICEs, approximately 29% of the fuel’s energy is lost to the cooling system and about 22% goes into moving the car. By limiting heat losses from the combustion chamber with insulating coatings, fuel energy can be redirected into additional piston work and into the exhaust stream. The additional energy that goes into the exhaust stream can be turned into useful work through the use of an exhaust energy recovery device, such as turbocompounding and/or through driving a turbocharger to increase the power density of the engine allowing downsizing. Insulating coatings for piston crowns have been pursued in the past, but previous materials—typically ceramics—exhibited low thermal conductivity but retained high heat capacity. Such materials reduce heat losses but stabilize at a high surface temperature. The high surface temperature heats the incoming gases, which lowers volumetric efficiency and increases propensity for knock, resulting in degraded engine performance. This program developed an innovative new material that combines low thermal conductivity with low heat capacity. These unique properties allow it to follow rapid changes in gas temperature during each combustion cycle. A metallic microsphere TBC has been demonstrated that exhibits increased surface temperature during the combustion period, resulting in reduced heat transfer losses, while still returning to a low surface temperature during the gas exchange period. A 10X lower thermal conductivity and heat capacity than state-of-the-art thermal barrier coatings has been demonstrated. These unprecedented thermal properties are achieved through the coating architecture, which consists of closed pores on the microscale and exhibits a total porosity of 90% to 95%. By selecting a high-temperature nickel alloy as the coating material, the ductility and strength of metals can be harnessed to achieve much better durability and damage tolerance than brittle ceramic coatings can achieve.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

In-situ sensor monitoring of multi-class gas porosity formation in laser powder bed fusion using convolutional neural network

In-situ monitoring of defect formation remains a significant challenge in the laser powder bed fusion (LPBF) process. Recent advances have enabled real-time defect detection with machine learning and in-situ sensing technologies; however, most studies focus on binary classification of keyhole pores, limiting nuanced multi-class pore differentiation and formation mechanisms. This work introduces a multi-class pore detection framework (no pore, small pores < 15 µm, and large pores > 15 µm) by leveraging photodiode sensor data alongside high-fidelity synchrotron X-ray imaging. The 15 µm threshold is selected to distinguish between two fundamentally different defect mechanisms, following the physical size-mechanism boundary established by prior high-resolution synchrotron X-ray characterization of Al6061 LPBF. Distinguishing these classes is critical because large keyhole pores are structurally detrimental, whereas small gas pores are often benign, requiring different process control strategies. Thermal emission monitoring data collected simultaneously with high-speed X-ray imaging at the Stanford Synchrotron Radiation Lightsource (SSRL), are correlated with subsurface melt pool dynamics to establish ground truth. Continuous Wavelet Transform (CWT) with optimized parameters converts the photodiode time-series signals into time–frequency images, facilitating feature extraction. Convolutional Neural Networks (CNN) are then applied for real-time multi-class pore classification in an average inference time of 1 ms per signal window. It achieves 79% accuracy and an Area Under the Receiver Operating Characteristic curve (AUC ROC) score of 0.89 with five-fold cross-validation. The results demonstrate that coupling CWT-based feature engineering with CNN architecture enables reliable multi-class pore detection in Al6061 builds using affordable in-situ sensors. This approach advances scalable and affordable quality assurance in additive manufacturing by moving beyond binary defect detection toward more nuanced classification of porosity mechanisms with in-situ sensors and machine learning.

Laser powder bed fusion, Multi-class pores, In-sit↗
DOE OSTI2023

A Comparative Study of Deep Learning Models for Fracture and Pore Space Segmentation in Synthetic Fractured Digital Rocks

This study focuses on the comparative study of deep learning (DL) models for pore space and discrete fracture networks (DFNs) segmentation in synthetic fractured digital rocks, specifically targeting low-permeability rock formations, such as shale and tight sandstones. Accurate characterization of pore space and DFNs is critical for subsequent property analysis and fluid flow modeling. Four DL models, SegNet, U-Net, U-Net-wide, and nested U-Net (i.e., U-Net++), were trained, validated, and tested using synthetic datasets, including input and label image pairs with varying properties. The model performance was assessed regarding pixel-wise metrics, including the F1 score and pixel-wise difference maps. In addition, the physics-based metrics were considered for further analysis, including sample porosity and absolute permeability. Particularly, We first simulated the permeability of porous media containing only pore space and then simulated the permeability of porous media with DFNs added. The difference between these two values is used to quantify the connectivity of segmented DFNs, which is an important parameter for low-permeability rocks. The pixel-wise metrics showed that the nested U-Net model outperformed the rest of the DL models in pore space and DFNs segmentation, with the SegNet model exhibiting the second-best performance. Particularly, nested U-Net enhanced segmentation accuracy for challenging boundary pixels affected by partial volume effects. The U-Net-wide model achieved improved accuracy compared to the U-Net model, which indicated the influence of parameter numbers. Similarly, nested U-Net has the closest match to the ground truth of physics-based metrics, including the porosity of pore space and DFNs, and the permeability difference quantifying the connectivity of DFNs. The findings highlight the effectiveness of DL models, especially the U-Net++ model with nested architecture and redesigned skip connections, in accurately segmenting pore spaces and DFNs, which are crucial for pore-scale fluid flow and transport simulation in low-permeability rocks.

Wang, Hongsheng↗
DOE OSTI2022

Qualitative and quantitative analysis of neutron irradiation effects in SiC/SiC composites using X-ray computed tomography

Silicon carbide fiber-reinforced silicon carbide matrix (SiC/SiC) composites are candidate materials for cladding of light water reactor (LWR) fuels. Loss of fission product gas retention due to the formation of microcrack networks is considered a potential failure mechanism for SiC/SiC-cladded fuels. In this work, a variety of SiC/SiC composite tubes were irradiated with and without an LWR-relevant radial heat flux in the High Flux Isotope Reactor, followed by detailed characterization with X-ray computed tomography (XCT). This first set of XCT data for neutron-irradiated samples confirmed that the internal stresses arising from a combination of temperature gradients and irradiation-induced swelling act as the primary driver for cracking. Consequently, while the observed cracking patterns varied depending on the tube architectures, the sharp edges of relatively large pores were found to be the common stress concentrator. These findings are useful to help improve the design and manufacturing of SiC/SiC fuel claddings for reduced failure probability.

42 ENGINEERING↗
DOE OSTI2025

Truncating 2D Framework Materials Down to a Single Pore: Synthetic Approaches and Opportunities

Here, in this Accounts article, we summarize our recent work on truncating conjugated two-dimensional framework materials down to a single pore, or a single macrocycle. Conjugated 2D architectures have emerged as one of the most synthetically adaptable motifs for coupling semiconductivity and porosity in metal–organic frameworks (MOFs) and covalent organic frameworks (COFs). However, despite their prevalence, 2D architectures have several limitations. In particular, the strong interlayer π–π stacking can limit both processability and the accessibility of internal active sites. We have found that simple macrocycles preserve key aspects of 2D framework structure and function, including porosity and out-of-plane electrical conductivity, while providing improved processability, surface tunability, and mass transport properties. In this article, we first describe our synthetic approach and general design considerations. Specifically, we show how ditopic analogues of the tritopic ligands commonly found in the synthesis of 2D MOFs and COFs can be used to achieve a diverse library of conjugated macrocycles that resemble fragments of semiconducting frameworks in both form and function. The length of the peripheral side chains, the size of the aromatic core, and the solubility of intermediates are all key variables in favoring selective macrocycle formation over undesired linear polymers and oligomers. Next, we highlight the unique advantages that macrocycles provide, including improved processability, atomically precise surface tunability, and greater active site accessibility. In particular, the identity of the peripheral side chains dramatically impacts both solubility and colloidal stability as well as crystal size and morphology. We further show how the solution processability and nanoscale dimensions of macrocycles can simplify electronic device fabrication and improve electrochemical performance. Finally, we end with a forward-looking discussion on how macrocycles offer a unique bridge between conjugated molecules and extended frameworks, enabling new application areas and fundamental science.

charge transport↗
DOE OSTI2023

Pore Pressure Diffusion and Onset of Induced Seismicity

The Raton Basin of Southern Colorado and Northern New Mexico experienced a significant increase in seismicity over the last several decades, including two M5+ earthquakes. The increase in seismicity started soon after an increase in wastewater disposal associated with coal-bed methane production. Twenty-nine wastewater injection wells have operated in the Basin, with several high-rate injectors located within a kilometer of the most seismically active regions. We developed a pore pressure model to investigate the relationship between pore pressure diffusion and onset of induced seismicity, with an emphasis on the Trinidad fault zones. Our model indicates that sufficient pore pressure increase had accumulated on the northern extent of the Trinidad fault zone to induce seismicity at the time of early-stage seismic activity. The hydrogeologic architecture of the Basin played a key role in controlling pore pressure perturbation. The basal sedimentary interval with moderately low diffusivity restricted vertical pore pressure diffusion, creating a substantial lag time between wells becoming active and the expression of perturbation in the fault zones. The spatiotemporal relationship between early-stage seismicity and wastewater injection in conjunction with modeled pore pressures suggests that the early-stage seismicity in the Raton Basin was likely triggered by pore pressure diffusion.

58 GEOSCIENCES↗
DOE OSTI2021

Mathematical modeling of novel porous transport layer architectures for proton exchange membrane electrolysis cells

Thin foil based porous transport layers (PTLs) that contain highly structured pore arrays have shown promise as anode PTLs in proton exchange membrane electrolysis cells. These novel PTLs, fabricated with advanced manufacturing techniques, produce thin, tunable, multifunctional layers with reduced flow and interfacial resistances and high thermal and electric conductivities. To further optimize their design, it is important to understand their fundamental impact on the transport of protons, electrons, and liquid/vapor mixtures in the electrode. In this work, we develop a two-dimensional multiphysics model to simulate the coupled electrochemistry and multiphase transport in an electrolysis cell operated with the novel PTL architecture. The results show that larger pores improve access of water to the anode catalyst layer, which is beneficial for both the oxygen evolution reaction and membrane hydration. Larger pore sizes also improve oxygen gas transport from the catalyst layer, because generated oxygen gas is forced to travel in-plane through the anode catalyst layer until it reaches a pore opening that is connected to a channel. The discussed results confirm that the proposed thin foil based PTLs are fundamentally different from conventional PTLs, such as felts or layered meshes. The model developed in this work also provides generalizable insight into fundamental PEMEC phenomena, such as the competition between liquid and gas phase transport, membrane hydration and water management, and nonuniform electrochemical reactions, which are processes relevant to all PEMEC designs.

25 ENERGY STORAGE↗
DOE OSTI2023

Interfacial engineering via laser ablation for high-performing PEM water electrolysis

A rationalized interfacial design strategy was applied to tailor the porous transport layer (PTL)-catalyst layer (CL) contact and the PTL bulk-phase architecture. Particularly, at the PTL-CL interface, our results reveal that laser ablated sintered titanium power-based PTLs improve electrolyzer performance at both the H2NEW Consortium baseline catalyst loading of 0.4 mgIr cm -2 as well as at the ultra-low catalyst loading of 0.055 mgIr cm -2 . Under ultra-low catalyst loadings, the laser ablated PTL demonstrates maximum reduction of 230 mV compared to the commercial PTL at 4 A cm -2 , and reduces by 68 mV at 3.2 A cm -2 under H2NEW baseline loading. Laser ablation alters the titanium phase at the interface, so it forms more uniform structure like a microporous layer or a backing layer, leading to an increase in the surface area in contact with the catalyst layer while preventing the membrane from deforming into the PTL. Moreover, we reveal that bulk-phase architecture modification of the PTL by ablating patterned pores at the flow field-PTL interface improves mass transport without sacrificing contact at the CL-PTL interface. Overall, laser ablation of the PTL is an effective method to customize interfacial design to enhance proton exchange membrane electrolyzer performance.

08 HYDROGEN↗
DOE OSTI2023

Mechanistic Insights into Processive Polyethylene Hydrogenolysis through In Situ NMR

Chemical polymer upcycling by processive catalysts is a promising plastic waste remediation strategy, with the capability of producing selective, high-value products from waste plastics with minimal energy input. We previously designed a novel processive catalyst with a mesoporous SiO 2 shell/Pt nanoparticle/SiO 2 core architecture (mSiO 2 /Pt/SiO 2 ) that deconstructs polyolefins within narrow pores. Here, in this paper, we elucidate the mechanism of processive polyolefin hydrogenolysis using in situ magic-angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy and coarse-grained molecular dynamics simulations. We observe that most polyethylene–Pt interactions do not lead to C–C bond cleavage but rather to the release of the polymer via a dehydrogenation–rehydrogenation cycle. The porous architecture increases the likelihood that a released polymer is later cleaved and enables the catalyst to perform multiple successive cleavages to the same polymer chain. Both experiment and simulation show that the extent of processivity is strongly correlated with the length of the pores, with longer pores leading to a higher processivity.

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

Influence of Fault Architecture on Induced Earthquake Sequence Evolution Revealed by High-Resolution Focal Mechanism Solutions

The increasing seismicity and improved seismic observation network in recent years provide an opportunity to explore factors that influence the triggering processes, spatiotemporal evolution, and maximum magnitude of induced sequences. We map the fault architecture and stress state of four induced sequences in Oklahoma to determine their influence on the seismicity. We systematically relocate the earthquakes and compute hundreds of focal mechanisms of small to medium events (1.0 < M < 5.1) using various techniques, including machine learning, for the Guthrie, Woodward, Cushing, and Fairview sequences. The detailed fault geometry and spatiotemporal evolution of seismicity and stress states reveal different dominant driving forces for each sequence. In Cushing and Fairview (largest event ≥M5.0), the main fault structures are near-vertical narrow strike-slip faults, with most of the small earthquake fault planes optimally oriented. The two sequences exhibit discontinuous temporal migration but strong earthquake self-driven rupture growth. In Guthrie and Woodward (largest event <M5.0), the two sequences show more complex diffuse fault structures with varying dipping angles along depth. The inverted focal mechanisms show a mix of strike-slip faulting and normal faulting in both sequences, and the normal faulting events are less optimally oriented than strike-slip events. The two sequences are dominated by continuous diffusive migration in time driven by pore pressure propagation. The above results suggest that fault architecture and stress state influence sequence evolution, major driving forces, and possibly maximum magnitude.

58 GEOSCIENCES↗
DOE OSTI2024

Sub-millisecond keyhole pore detection in laser powder bed fusion using sound and light sensors and machine learning

Laser powder bed fusion is a mainstream additive manufacturing technology widely used to manufacture complex parts in prominent sectors, including aerospace, biomedical, and automotive industries. However, during the printing process, the presence of an unstable vapor depression can lead to a type of defect called keyhole porosity, which is detrimental to the part quality. In this study, we developed an effective approach to locally detect the generation of keyhole pores during the printing process by leveraging machine learning and a suite of optical and acoustic sensors. Simultaneous synchrotron x-ray imaging allows the direct visualization of pore generation events inside the sample, offering high-fidelity ground truth. A neural network model adopting SqueezeNet architecture using single-sensor data was developed to evaluate the fidelity of each sensor for capturing keyhole pore generation events. Our comparative study shows that the near infrared images gave the highest prediction accuracy, followed by 100 kHz and 20 kHz microphones, and the photodiode sensitive to processing laser wavelength had the lowest accuracy. Using a single sensor, over 90% prediction accuracy can be achieved with a temporal resolution as short as 0.1 ms. A data fusion scheme was also developed with features extracted using SqueezeNet neural network architecture and classification using different machine learning algorithms. Our work demonstrates the correlation between the characteristic optical and acoustic emissions and the keyhole oscillation behavior, and thereby provides strong physics support for the machine learning approach.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Unraveling the Effects of Hierarchical Bimodal Microscale Porosity on Thick Electrodes

The thick electrode design is preferential in high-energy lithium-ion batteries (LIBs) systems. However, the sluggish ionic transport in homogeneous porous thick electrodes severely limits the areal capacity at high charging/discharging rates. The hierarchical porous design is a promising approach to mitigate kinetic limitations because it can distribute mass effectively in natural systems. In this study, the effects of bimodal microscale pores are fully investigated in thick electrodes from both architectural and electrochemical perspectives. Notably, by introduction of the bimodal microscale porous structure, the rate capability improves remarkably in thick electrodes with a low porosity (39%). Herein, by combining experimental results with simulations, this work presents a rational design guideline for preparing thick electrodes with a porosity at the commercial level, as well as simultaneous high energy and power densities, which brings new insights into the advanced electrode architecture design in scalable high-energy and high-power energy storage systems for practical applications.

25 ENERGY STORAGE↗