Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “multiscale structure”

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 OSTI2020

Internal structure of the San Jacinto fault zone at the Ramona Reservation, north of Anza, California, from dense array seismic data

SUMMARY We image the internal structure of the San Jacinto fault zone (SJFZ) near Anza, California, with seismic data recorded by two dense arrays (RA and RR) from ∼42 000 local and ∼180 teleseismic events occurring between 2012 and 2017. The RA linear array has short aperture (∼470 m long with 12 strong motion sensors) and recorded for the entire analysed time window, whereas the RR is a large three-component nodal array (97 geophones across a ∼2.4 km × 1.4 km area) that operated for about a month in September–October 2016. The SJFZ at the site contains three near-parallel surface traces F1, F2 and F3 from SW to NE that have accommodated several Mw > 6 earthquakes in the past 15 000 yr. Waveform changes in the fault normal direction indicate structural discontinuities that are consistent with the three fault surface traces. Relative slowness from local events and delay time analysis of teleseismic arrivals in the fault normal direction suggest a slower SW side than the NE with a core damage zone between F1 and F2. This core damage zone causes ∼0.05 s delay at stations RR26–31 in the teleseismic P arrivals compared with the SW-most station, and generates both P- and S-type fault zone trapped waves. Inversion of S trapped waves indicates the core damaged structure is ∼100 m wide, ∼4 km deep with a Q value of ∼20 and 40 per cent S-wave velocity reduction compared with bounding rocks. Fault zone head waves observed at stations SW of F3 indicate a local bimaterial interface that separates the locally faster NE block from the broad damage zone in the SW at shallow depth and merges with a deep interface that separates the regionally faster NE block from rocks to the SW with slower velocities at greater depth. The multiscale structural components observed at the site are related to the geological and earthquake rupture history at the site, and provide important information on the preferred NW propagation of earthquake ruptures on the San Jacinto fault.

Geochemistry & Geophysics↗
DOE OSTI2024

The hierarchical structure of organic mixed ionic–electronic conductors and its evolution in water

Polymeric organic mixed ionic–electronic conductors underpin several technologies in which their electrochemical properties are desirable. These properties, however, depend on the microstructure that develops in their aqueous operational environment. We investigated the structure of a model organic mixed ionic–electronic conductor across multiple length scales using cryogenic four-dimensional scanning transmission electron microscopy in both its dry and hydrated states. Four-dimensional scanning transmission electron microscopy allows us to identify the prevalent defects in the polymer crystalline regions and to analyse the liquid crystalline nature of the polymer. The orientation maps of the dry and hydrated polymers show that swelling-induced disorder is mostly localized in discrete regions, thereby largely preserving the liquid crystalline order. Therefore, the liquid crystalline mesostructure makes electronic transport robust to electrolyte ingress. Furthermore, this study demonstrates that cryogenic four-dimensional scanning transmission electron microscopy provides multiscale structural insights into complex, hierarchical structures such as polymeric organic mixed ionic–electronic conductors, even in their hydrated operating state.

36 MATERIALS SCIENCE↗
NASA NTRS2017

Realistic 3D Radiative Modeling of Turbulent Structure of Moderate-Mass Stars and Sun

Understanding the turbulent dynamics of the Sun and stars is a critical element for interpreting observed processes and phenomena on different scales and for predicting extreme events such as flares and super flares. High-­‐resolution observations of the Sun and high-­‐fidelity radiative MHD numerical simulations have substantially advanced our understanding of solar and stellar local dynamics and magnetism from the upper convection zone to the atmosphere and corona. However, global modeling of the Sun with such a high degree of realism is currently not affordable due to the extremely high computational cost of resolving the scales in the convection zone. The physics of the deep solar dynamics can be effectively addressed through modeling more massive solar-­‐type stars where the convection zone is shallower and the convective overturning time is much shorter than those on the Sun. We present recent 3D realistic simulation results of moderate-­‐mass stars and discuss links between solar and stellar dynamics, such as the multiscale structure of granulation, convective overshoot, and others. In particular, these simulations have provided better understanding of the dynamics of the tachocline (the overshoot layer at the bottom of the convection zone) and have explained long-­‐ standing results from helioseismology.

Realistic↗
DOE OSTI2022

In situ visualization of multicomponents coevolution in a battery pouch cell

Lithium-ion battery (LIB) is a broadly adopted technology for energy storage. With increasing demands to improve the rate capability, cyclability, energy density, safety, and cost efficiency, it is crucial to establish an in-depth understanding of the detailed structural evolution and cell-degradation mechanisms during battery operation. Here, we present a laboratory-based high-resolution and high-throughput X-ray micro–computed laminography approach, which is capable of in situ visualizing of an industry-relevant lithium-ion (Li-ion) pouch cell with superior detection fidelity, resolution, and reliability. This technique enables imaging of the pouch cell at a spatial resolution of 0.5 μm in a laboratory system and permits the identification of submicron features within cathode and anode electrodes. We also demonstrate direct visualization of the lithium plating in the imaged pouch cell, which is an important phenomenon relevant to battery fast charging and low-temperature cycling. Our development presents an avenue toward a thorough understanding of the correlation among multiscale structures, chemomechanical degradation, and electrochemical behavior of industry-scale battery pouch cells.

25 ENERGY STORAGE↗
DOE OSTI2023

Chemo-mechanical-microstructural coupling in the tarsus exoskeleton of the scorpion Scorpio palmatus

The multiscale structure of biomaterials enables their exceptional mechanical robustness, yet the impact of each constituent at their relevant length scale remains elusive. Here, we used SAXD analysis to expose the intact chitin-fiber architecture within the exoskeleton on a scorpion's claw, revealing varying orientations, including Bouligand and unidirectional regions different from other arthropod species. We uncovered the contribution of individual components’ constituent behavior to its mechanical properties from the micro- to the nanoscale. At the microscale, in-situ micromechanical experiments were used to determine site-specific stiffness, strength, and failure of the biocomposite due to fiber orientation, while metal-crosslinking of proteins is characterized via fluorescence maps. At the constituent level, combined with FEA simulations, we uncovered the behavior of fiber-matrix deformation with fiber diameter <53.7 nm and protein modulus in the range 1.4–11 MPa. The unveiled microstructure-mechanics relationship sheds light on the evolved structural functionalities and constituents' interactions within the scorpion cuticle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Advances in imaging, scattering, spectroscopy, and machine learning-aided approaches for multiscale characterization of cementitious systems

Recent progress in methods used in the multiscale characterization of cementitious systems is reviewed, focusing on advances in imaging, scattering, and spectroscopy. The review includes relevant applications and developments in machine learning and other data analytics approaches to enhance characterization. Developments in imaging using light and electron microscopy as well as x-ray (i.e., from synchrotron) methods are summarized. Updates include scanning electron microscopy (SEM), transmission electron microscopy (TEM), tomography, and holography. A critical overview of spectroscopy (e.g., MAS NMR, Raman) and scattering (e.g., neutron, x-ray, synchrotron x-ray) methods is provided, and the intersection of these with imaging is developed (e.g., Raman imaging). Additionally, the paper summarizes recent developments in and implementations of state-of-the-art machine-learning algorithms and data analytics methods for automated, systematic, and/or quantitative analyses of image data sets. The review considers but is not limited to the application of these methods for investigating the hydration and microstructure development of cement phases, low-carbon-footprint cements (e.g., limestone calcined clay cements, LC3), environmental interactions (e.g., ASR) and model systems. Finally, the present work provides a critical presentation of advances in characterization methods that link together the composition and multiscale structure of cementitious materials.

42 ENGINEERING↗
DOE OSTI2025

Generative learning of densities on manifolds

A generative modeling framework is proposed that combines diffusion models and manifold learning to efficiently sample data densities on manifolds. The approach utilizes Diffusion Maps to uncover possible low-dimensional underlying (latent) spaces in the high-dimensional data (ambient) space. Two approaches for sampling from the latent data density are described. The first is a score-based diffusion model, which is trained to map a standard normal distribution to the latent data distribution using a neural network. The second one involves solving an Itô stochastic differential equation in the latent space. Additional realizations of the data are generated by lifting the samples back to the ambient space using Double Diffusion Maps , a recently introduced technique typically employed in studying dynamical system reduction; here the focus lies in sampling densities rather than system dynamics. The proposed approaches enable sampling high dimensional data densities restricted to low-dimensional, a priori unknown manifolds. The efficacy of the proposed framework is demonstrated through a benchmark problem and a material with multiscale structure.

Double diffusion maps↗
DOE OSTI2020

Multi-scale stabilization of high-voltage LiCoO 2 enabled by nanoscale solid electrolyte coating

LiCoO 2 (LCO) possess a high theoretical specific capacity of 274 mAh g -1 , and currently LCO charged to 4.48 V with a capacity of ~190–195 mAh g -1 is penetrating the commercial markets. Scalable strategies to further enhance the performance of LCO are highly attractive. Here, we develop a scalable ball-milling and sintering method to tackle this long-standing challenge by modifying LCO surface with only 1.5–3.5% ceramic solid electrolyte nanoparticles, specifically Li 1.5 Al 0.5 Ge 1.5 (PO 4 ) 3 (LAGP) as an example. Consequently, the atomic-to-meso multiscale structural stabilities have been significantly improved, even with a high cut-off voltage of 4.5 V vs. Li/Li + , leading to excellent electrochemical stabilities. The nano-LAGP modified Li|LCO cell exhibits high discharge capacity of 196 mAh g -1 at 0.1 C, capacity retention of 88% over 400 cycles, and remarkably enhanced rate capability (163 mAh g -1 at 6 C). These results show significant improvement compared to the Li|LCO cells. The as-prepared graphite|LAGP-LCO full cells also show steady cycling with 80.4% capacity retention after 200 cycles with a voltage cut-off of 4.45 V. This work provides a simple and scalable approach to achieve stable cycling of LCO at high voltage with high energy density.

25 ENERGY STORAGE↗
DOE OSTI2023

Multimodal and multiscale strengthening mechanisms in Al-Ni-Zr-Ti-Mn alloy processed by laser powder bed fusion additive manufacturing

The unique thermokinetics of laser-powder bed fusion additive manufacturing (L-PBFAM) has been exploited for development of a novel high-strength Al-Ni-Ti-Zr-Mn alloy. The addition of 0.5 wt% Mn leads to extraordinary improvement in ultimate tensile strength (502 MPa) and work hardening due to the activation of two Mn-induced strengthening mechanisms. First, by a bimodal particle strengthening effect due to Al 31 Mn 6 Ni 12 nano-quasi-crystal particles rejected in inter-dendritic spaces and fibrous Al 3 Ni eutectic dendritic channels, which predominately contributes to the strength improvement, and second by solid solution strengthening from remaining Mn entrapped in Al. These mechanisms supplement the particle strengthening effect imparted by coherent and incoherent Al 3 (Ti,Zr) co-precipitates present at melt pool boundaries, dislocation strengthening due to solidification induced strain, and Hall-Petch and backstress strengthening effect due to heterogenous grain size distribution occurring at various length scales. In conclusion, the solidification dynamics and hierarchical heat distribution that are associated with L-PBFAM resulted in complex spatial variations in these strengthening phenomena and were investigated via a high-throughput multiscale structure–property correlation that involved thermokinetic simulation, X-ray diffraction, high-resolution nanoindentation mapping, and site-specific transmission electron microscopy of the alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Anisotropic Coarse-Grained Model for Conjugated Polymers: Investigations into Solution Morphologies

The optoelectronic properties of conjugated polymers are dictated by the interplay of multiscale structural features, including intrachain dihedrals, interchain pi-pi stacking, and the complex mesoscale morphology. While much is known about the structures of polymers with isotropically interacting monomers, little is known about polymers with strongly anisotropic backbone monomers, a class of materials to which conjugated polymers belong. Fundamental understanding is further complicated when the semiflexible and molecularly heterogeneous nature of conjugated polymers is taken into account. We present an anisotropic coarse-grained (CG) model for conjugated polymers that incorporates key molecular features (monomer anisotropy, intermonomer dihedrals, and side chains). Finally, the model is employed to characterize the single-chain conformational properties of conjugated polymers, revealing a rich temperature-dependent conformational landscape. These studies provide a critical link between CG molecular descriptors and conformational ordering in conjugated polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modular Approach for the Synthesis of Bottlebrush Diblock Copolymers from Poly(Glycidyl Methacrylate)-block-Poly(Vinyldimethylazlactone) Backbones

A strategy that enables the facile synthesis of bottlebrush block copolymers with flexible backbones was developed. A demonstration of the strategy’s utility was carried out by grafting end-functionalized polymethylmethacrylate (PMMA) and polystyrene (PS) to the dually reactive block copolymer, poly(glycidyl methacrylate)-block-poly(vinyldimethylazlactone) (PGMA-b-PVDMA). Five different bottlebrush diblock copolymers were investigated by size-exclusion chromatography (SEC), 1H NMR, Fourier transform infrared (FT-IR), differential scanning calorimetry (DSC), X-ray scattering methods, atomic force microscopy (AFM), rheology and computational simulations using molecular dynamics (MD), and self-consistent field theory (SCFT). A relationship between the glass transition temperature and the fraction of chain ends was demonstrated by DSC and highlights the potential of this synthetic method to tailor polymer properties. All five samples were found to be in a disordered phase exhibiting multiscale structures revealed by two broad peaks in small-angle X-ray scattering (SAXS) that can be attributed to graft-to-graft and backbone-to-backbone density correlations using MD simulations. The SCFT-based simulations justify the observation of a disordered phase due to its stabilization by the grafts. Additionally, this modular approach can be easily extended to other grafts, including responsive, conducting, and charged polymers with the prerequisite end groups. The versatility and ease of assembling these functional bottlebrushes constitute a powerful “toolbox” method for the rapid and scalable synthesis of novel bottlebrush block copolymers with desired properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Porous cage-derived nanomaterial inks for direct and internal three-dimensional printing

The convergence of 3D printing techniques and nanomaterials is generating a compelling opportunity space to create advanced materials with multiscale structural control and hierarchical functionalities. While most nanoparticles consist of a dense material, less attention has been payed to 3D printing of nanoparticles with intrinsic porosity. Here, we combine ultrasmall (about 10 nm) silica nanocages with digital light processing technique for the direct 3D printing of hierarchically porous parts with arbitrary shapes, as well as tunable internal structures and high surface area. Thanks to the versatile and orthogonal cage surface modifications, we show how this approach can be applied for the implementation and positioning of functionalities throughout 3D printed objects. Furthermore, taking advantage of the internal porosity of the printed parts, an internal printing approach is proposed for the localized deposition of a guest material within a host matrix, enabling complex 3D material designs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Strategies for simultaneous strengthening and toughening via nanoscopic intracrystalline defects in a biogenic ceramic

While many organisms synthesize robust skeletal composites consisting of spatially discrete organic and mineral (ceramic) phases, the intrinsic mechanical properties of the mineral phases are poorly understood. Using the shell of the marine bivalve Atrina rigida as a model system, and through a combination of multiscale structural and mechanical characterization in conjunction with theoretical and computational modeling, we uncover the underlying mechanical roles of a ubiquitous structural motif in biogenic calcite, their nanoscopic intracrystalline defects. These nanoscopic defects not only suppress the soft yielding of pure calcite through the classical precipitation strengthening mechanism, but also enhance energy dissipation through controlled nano- and micro-fracture, where the defects’ size, geometry, orientation, and distribution facilitate and guide crack initialization and propagation. These nano- and micro-scale cracks are further confined by larger scale intercrystalline organic interfaces, enabling further improved damage tolerance.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Enamel nanocrystal misorientation increased with meat-eating and agriculture

Enamel covers teeth, is the hardest tissue in the vertebrate body and has a complex multiscale structure from nanometres to millimetres. The structure comprises thin, long hydroxyapatite (Ca 5 (PO 4 ) 3 OH) nanocrystals, 50–70 nm wide, many micrometres long, parallel and bundled into approximately 5-µm-wide rods. The rods undulate and cross into a microscale ‘decussation pattern’ that toughens enamel by deflecting cracks. However, the crystallographic orientation of enamel nanocrystals is poorly understood. Here we show that the misorientation angle of adjacent nanocrystals varies markedly across 12 primate teeth spanning 9 species, 17.8 million years of evolution and diverse diets. Using a method called Polarization Enabled Large Input of Crystal Angles at the Nanoscale (PELICAN), we compare nanocrystals in the same (pre)molar locations and show that misorientation increases with food hardness in extant and fossil non-human apes and monkeys. We compare misorientation across three major dietary shifts in human evolution: the transition to meat-eating about 2.0–1.5 million years before present, to agriculture (about 12,000 years before present), and the Industrial Revolution (about 250 years before present). We show that over the past 1.6 million years, in the human lineage misorientation increased with time, especially when meat and stone-ground grains were introduced into human diets, but not with the Industrial Revolution. Thus, besides macro-changes, teeth adapted to dietary change at the nanoscale and crystallographically. This observation suggests that misorientation may contribute to enamel’s resilience; thus, bioinspired materials may consider small misorientation angles for added resilience.

biomaterials↗
DOE OSTI2023

A multifunctional copper single-atom electrocatalyst aerogel for smart sensing and producing ammonia from nitrate

Despite modern chemistry’s success in providing affordable fertilizers for feeding the population and supporting the ammonia industry, ineffective nitrogen management has led to pollution of water resources and air, contributing to climate change. Here, we report a multifunctional copper single-atom electrocatalyst-based aerogel (Cu SAA) that integrates the multiscale structure of coordinated single-atomic sites and 3D channel frameworks. The Cu SAA demonstrates an impressive faradaic efficiency of 87% for NH 3 synthesis, as well as remarkable sensing performance with detection limits of 0.15 ppm for NO 3 − and 1.19 ppm for NH 4 + . These multifunctional features enable precise control and conversion of nitrate to ammonia in the catalytic process, facilitating accurate regulation of the ammonium and nitrate ratios in fertilizers. We thus designed the Cu SAA into a smart and sustainable fertilizing system (SSFS), a prototype device for on-site automatic recycling of nutrients with precisely controlled nitrate/ammonium concentrations. The SSFS represents a forward step toward sustainable nutrient/waste recycling, thus permitting efficient nitrogen utilization of crops and mitigating pollutant emissions. This contribution exemplifies how electrocatalysis and nanotechnology can be potentially leveraged to enable sustainable agriculture.

Science & Technology - Other Topics↗
DOE OSTI2025

Nucleation and growth of polar clusters with in-phase tilts into a long-range ferroelectric matrix in a sodium niobate based complex relaxor

In this study, we have investigated the temperature dependence of atomic ordering at multiple length scales in a lead-free sodium niobate-based relaxor, i.e., 0.75 NaNbO 3 -0.25 Ba 0.9⁢ Ca 0.1⁢ TiO 3 (NN-25BCT) via synchrotron x-ray diffraction, Raman spectroscopy, and pair distribution function analysis. High-resolution synchrotron x-ray powder diffraction (SXRD) measurements reveal a ferroelectric phase transition in the relaxor ferroelectric NN-25BCT below the Vogel-Fulcher freezing temperature (𝑇 VF ≈ 270 K). In addition, SXRD analysis demonstrates the competition between in-phase octahedral tilting and ferroelectric order at the long-range scale using mode crystallography. On the other hand, Raman spectroscopic analysis provides evidence of polar ordering for 𝑇 > 𝑇 VF (with tetragonal symmetry) persisting up to the Burns temperature (𝑇 B ). Furthermore, pair distribution function (PDF) analysis reveals the presence of a polar antiferrodistortive tetragonal phase with 𝑃⁢4⁢𝑏𝑚 space group at short ranges throughout the studied temperatures (i.e., 110 K ≤ 𝑇 ≤500 K), irrespective of nonpolar long-range ordering above 𝑇 VF . Therefore, our measurements provide direct evidence for the presence of polar ordering at short ranges and their gradual transformation into long-range polar ordering using an integrated multiscale structural analysis. In conclusion, as a result of a transition from relaxor to a ferroelectric phase in the vicinity of room temperature, NN-25BCT can be exploited for applications in pyroelectric detectors, electrocaloric devices, and multilayered ceramic capacitors.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Supervised pixel classification using a feature space derived from an artificial visual system

Image segmentation involves labelling pixels according to their membership in image regions. This requires the understanding of what a region is. Using supervised pixel classification, the paper investigates how groups of pixels labelled manually according to perceived image semantics map onto the feature space created by an Artificial Visual System. Multiscale structure of regions are investigated and it is shown that pixels form clusters based on their geometric roles in the image intensity function, not by image semantics. A tentative abstract definition of a 'region' is proposed based on this behavior.

Baxter, Lisa C.↗
DOE OSTI2022

LigninGraphs: lignin structure determination with multiscale graph modeling

Lignin is an aromatic biopolymer found in ubiquitous sources of woody biomass. Designing and optimizing lignin valorization processes requires a fundamental understanding of lignin structures. Experimental characterization techniques, such as 2D-heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra, could elucidate the global properties of the polymer molecules. Computer models could extend the resolution of experiments by representing structures at the molecular and atomistic scales. We introduce a graph-based multiscale modeling framework for lignin structure generation and visualization. The framework employs accelerated rejection-free polymerization and hierarchical Metropolis Monte Carlo optimization algorithms. We obtain structure libraries for various lignin feedstocks based on literature and new experimental NMR data for poplar wood, pinewood, and herbaceous lignin. The framework could guide researchers towards feasible lignin structures, efficient space exploration, and future kinetics modeling. Its software implementation in Python, LigninGraphs, is open-source and available on GitHub.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗