Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Structural properties”

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 271 records · Page 15

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this paper, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.

36 MATERIALS SCIENCE↗

Revisiting Multi-Material Composite Structures with Homogenized Composite Properties

Composite structures inherently develop residual stresses during their curing process. Driven predominately by mismatched thermal strains between differing materials or ply orientations, but also affected by curing process phenomena like polymer shrinkage, these residual stresses can lead to failure within composite structures. There are several methods varying in complexity that can be used to model the development of residual stresses, all of which are capable of capturing sufficient detail to understand the residual stress state at the ply level. However, explicitly modeling all plies of a layup in a composite structure can be prohibitively expensive based on the number of plies, structure size, and required element size. The computational cost can be reduced through the homogenization of the composite layup without losing much fidelity of the overall response of the structure. The homogenization process reduces the many plies of a laminate to a single lamina that reduces complexity and increases the mesh size where a single element can span multiple plies. This report focuses on verification and validation efforts for a homogenization process using a suite of finite element simulations rather than an analytic solution derived from classical laminate theory. Initial verification using representative element volumes indicated there was minimal error in the homogenization process; however, this compounded to a small, but acceptable error in strip and split ring experimental composite structures. The error does under predict the residual stress state in the strip and split ring and should be accounted for when simulating composite structures with homogenized properties.

36 MATERIALS SCIENCE↗

Ab initio study of the structure and properties of amorphous silicon hydride from accelerated molecular dynamics simulations

This paper presents a large-scale ab initio simulation study of amorphous silicon hydride (a-Si 1-x H x ) with an emphasis on the structure and properties of the material across a range of hydrogen concentration by combining accelerated molecular dynamics (MD) simulations with first-principles density-functional calculations. The accelerated MD scheme relied on classical metadynamics, which enabled the development of 2500+ high-quality structural models of a-Si 1-x H x , with system sizes ranging from 150 to 6000 atoms and hydrogen concentrations vary from 6 to 20 at. %. The resulting amorphous networks were found to be completely free from any coordination defects and that they all exhibited a pristine band-gap in their electronic spectrum. The microstructural properties of hydrogen distributions were examined with an emphasis on the presence of isolated and clustered environments of hydrogen atoms. The results were compared with experimental data obtained from X-ray diffraction, infrared spectroscopy and nuclear magnetic resonance studies.

36 MATERIALS SCIENCE↗

Ab initio study of the structure and properties of amorphous silicon hydride from accelerated molecular dynamics simulations

This paper presents a large-scale ab initio simulation study of amorphous silicon hydride (a-Si 1-x H x ) with an emphasis on the structure and properties of the material across a range of hydrogen concentration by combining accelerated molecular dynamics (MD) simulations with first-principles density-functional calculations. The accelerated MD scheme relied on classical metadynamics, which enabled the development of 2600+ high-quality structural models of a-Si 1-x H x , with system sizes ranging from 150 to 6,000 atoms and hydrogen concentrations vary from 6 to 20 at. %. The resulting amorphous networks were found to be completely free from any coordination defects and that they all exhibited a pristine band-gap in their electronic spectrum. The microstructural properties of hydrogen distributions were examined with great emphasis on the presence of isolated and clustered environments of hydrogen atoms. The results were compared with a suite of experimental data obtained from x-ray diffraction, infrared spectroscopy, spectroscopic ellipsometry and nuclear magnetic resonance studies.

36 MATERIALS SCIENCE↗

Investigation into the crystal structure–dielectric property correlation in barium titanate nanocrystals of different sizes

For high capacitance multilayer ceramic capacitors, high dielectric constant and lead-free ceramic nanoparticles are highly desired. However, as the particle size decreases to a few tens of nanometers, their dielectric constant significantly decreases, and the underlying mechanism has yet to be fully elucidated. Herein, we report a systematic investigation into the crystal structure–dielectric property relationship of combustion-made BaTiO 3 (BTO) nanocrystals. When the nanocrystal size was 100 nm and below, a metastable paraelectric cubic phase was found in the as-received BTO (denoted as arBTO) nanocrystals based on an X-ray diffraction (XRD) study. A stable ferroelectric tetragonal phase was present when the nanocrystal size was above 200 nm. Notably, the cubic arBTO (particle size ≤100 nm) exhibited tetragonal fluctuations as revealed by Raman spectroscopy, whereas the tetragonal arBTO (particle size ≥200 nm) contained ~10% cubic fraction according to the Rietveld fitting of the XRD profiles. Thermal annealing of the multi-grain tetragonal arBTO at 950 °C yielded single crystals of annealed BTO (denoted as anBTO), whose dielectric constants were higher than those of arBTO. However, the single crystalline anBTO prevented the formation of 90° domains; therefore, they exhibited a low dielectric constant of ~300. Although X-ray photoelectron spectroscopy and high-resolution transmission electron microscopy could not identify the exact structural defects, our study revealed that surface and bulk defects formed during synthesis affect the final crystal structures and thus the dielectric properties of BTO nanocrystals with different sizes. Finally, the understanding obtained from this study will help us design high dielectric constant perovskite nanocrystals for next-generation multilayer ceramic capacitor applications.

36 MATERIALS SCIENCE↗

Impact of Dihedral Angle in Conjugated Organic Cation on the Structures and Properties of Organic‐Inorganic Lead Iodides

Abstract Conjugated organic cations are intriguing for organic‐inorganic halide perovskites due to their direct participation in the optoelectronic properties of hybrid materials. In conjugated cations, the dihedral angle, or torsion angle, between adjacent aromatic rings is a critical secondary structural element. This angle influences not only the shape of the cations but also the overlap between the π‐orbitals on adjacent rings, thereby affecting their electronic properties. Understanding how variations in the dihedral angle impact the structure and properties of hybrid organic‐inorganic metal halides (HOIMHs) is fundamentally important. In this study, we utilized 2,2′‐dimethyl bipyridinium as the organic cation, reacting it with PbI₂ to form hybrid lead iodides. Remarkably, variations in the dihedral angle between the two pyridinium rings resulted in the formation of two distinct crystal structures with different band gaps. Our findings demonstrate that manipulating the dihedral angle offers a novel approach to controlling the structures and properties of hybrid metal halides with conjugated cations.

Chandra Patra, Bidhan [Department of Chemistry and↗

Redox effects on the structure and properties of Na-Mo-Fe-phosphate glasses

Na-Mo-Fe-phosphate glasses were prepared with reducing and oxidizing raw materials and the effects of the different Fe 2+ /Fe 3+ and Mo 5+ /Mo 6+ ratios on glass structure and properties were determined. Mssbauer spectroscopy confirms significantly greater concentrations of Fe 2+ ions in the reduced glasses and distorted Fe 3+ O 4 sites preferred over the Fe 3+ O 6 sites in the oxidized glasses. Raman spectroscopy reveals the presence of isolated Mo 6+ O 6 sites in the oxidized glasses, and highly distorted Mo 5+ O 5 sites in reduced Mo-rich glasses. The presence of specific Fe- and Mo-polyhedra is correlated with the average phosphate anion length, as characterized by high-pressure liquid chromatography. Generally, for the similar compositions, oxidized glasses have greater molar volumes than the reduced glasses, associated with the formation of isolated Mo 6+ O 6 octahedra and the absence of highly crosslinked Mo 5+ OPO 4 units. Tg increases with increasing Fe 3+ fractions in the Fe-rich glasses, whereas for the Mo-rich glasses, T g increases with greater Mo 5+ fractions.

36 MATERIALS SCIENCE↗

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Active Causal Machine Learning for Molecular Property Prediction

Predicting properties from molecular structures is paramount to design tasks in medicine, materials science, and environmental management. However, design rules derived from the structure-property relationships using correlative data-driven methods fail to elucidate underlying causal mechanisms controlling chemical phenomena. This preliminary work proposes a workflow to actively learn robust cause-effect relations between structural features and molecular property for a broad chemical space utilizing smaller subsets, entailing partial information.

Fox, Zach↗

Electronic Structure, Optical Properties, and Photoelectrochemical Activity of Sn-Doped Fe 2 O 3 Thin Films

Hematite (Fe 2 O 3 ) is a well-known oxide semiconductor suitable for photoelectrochemical (PEC) water splitting and industry gas sensing. It is widely known that Sn doping of Fe 2 O 3 can enhance the device performance, yet the underlying mechanism remains elusive. In this work, we determine the relationship between electronic structure, optical properties and PEC activity of Sn doped Fe 2 O 3 by studying highly crystalline, well-controlled thin films prepared by pulsed laser deposition (PLD). We show that Sn doping substantially increases the n-type conductivity of Fe 2 O 3 , and the conduction mechanism is better described by small-polaron hoping (SPH) model. Only 0.2% Sn doping significantly reduce the activation energy barrier for SPH conduction from at least 0.5 eV for undoped Fe 2 O 3 to 0.14 eV for doped ones. A combination of X-ray photoemission, X-ray absorption spectroscopy and DFT calculations reveals the Fermi level gradually shifts toward the conduction band minimum with Sn doping. A localized Fe 2+ like gap state is observed at the top of valence band, accounting for the SPH conduction. Interestingly, in contrast to the literature, we find that only 0.2% Sn doping in Fe 2 O 3 significantly improves the PEC activity, while more Sn decreases it. The improved PEC activity is partially attributed to an increased band bending potential which facilitates the charge separation at space charge region. The reduced activation energy barrier for SPH will facilitate the transport of photo-excited carriers for the enhanced PEC, which is of interest for further carrier dynamics study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Physical properties, internal structure, and the three‐dimensional petrography of CI chondrites

physical properties and the nature of their breccation, we investigated nine samples of the Ivuna and Orgueil CI chondrites ranging in size from 1 mm to 4 cm in approximate diameter. The combined mass of unique material investigated in this work is 113 g. For our investigations, we use ideal gas pycnometry, 3-D laser scanning, x-ray computed microtomography (μCT), and accompanying digital data extraction techniques. We found that the bulk density of the samples ranged from 1.61 to 2.10 g cm −3 . Larger samples tend to have a lower bulk density. Grain density (ranging from 2.44 to 2.55 g cm −3 ) is significantly less variable than the bulk density in our samples and the quantity of porosity (ranging from 14.6% to 33.8%) is the dominant factor in determining the bulk density of CI chondrite material. Our μCT results show that the visible porosity across all sizes of our CI chondrite samples is in the form of cracks, but these cracks can account for less than two-thirds of the porosity in the CI chondrites. Other porosity is not visible, even at μCT resolutions of 2.7 μm voxel edge −1 and we conclude that it is sub-micron in nature. It is not clear if the cracks seen in our samples are indigenous to the chondrites or are a result of terrestrial processes. We also find that the CI chondrites are excellent examples of the fractal-like nature of brecciation, where clasts can be observed at all scales we imaged. The breccias are composed of sub-equant-shaped and sub-rounded-textured clasts like melt-free impact breccias on other solar system bodies. From our μCT volume and digital data extraction, we determine that the Ivuna CI chondrite breccia is organized: the mostly sub-equant clasts within our ~2 cm chunk of Ivuna have a mean diameter of 1.33 mm and their aligned longest axes define a lineation structure. We speculate that the lineation was imparted after fragmentation of the clasts by slight shear on the parent asteroid which could be the result of seismic-related granular flow or mild non-axial impact-related compaction. These data will help to place returned asteroidal material from asteroids 162173 Ryugu and 101955 Bennu and the CI chondrites into a mutual geological context.

CI chondrite↗

Structure–Transport Properties Governing the Interplay in Humidity-Dependent Mixed Ionic and Electronic Conduction of Conjugated Polyelectrolytes

Polymeric mixed ionic-electronic conductors (MIECs) are of broad interest in the field of energy storage and conversion, opto-electronics, and bioelectronics. A class of polymeric MIECs are conjugated polyelectrolytes (CPEs), which possess a p-conjugated backbone imparting electronic transport characteristics along with side chains comprised of a pendant ionic group to allow for ionic transport. Here, our study focuses on the humidity-dependent structure-transport properties of poly[3-(potassium-n-alkanoate) thiophene-2,5-diyl] (P3KnT) CPEs with varied side-chain lengths of n = 4, 5, 6, and 7. UV-Vis spectroscopy along with electronic paramagnetic resonance (EPR) spectroscopy reveal the infiltration of water leads to a hydrated, self-doped state that allows for electronic transport. The resulting humidity-dependent ionic conductivity (σ i ) of the thin films shows a monotonic increase with relative humidity (RH) while electronic conductivity (σ e ) follows a nonmonotonic profile. The values of σ e continue to rise with increasing RH reaching a local maximum after which σ e begins to decrease. P3KnTs with higher n values demonstrate greater resiliency to increasing RH before suffering decrease in σ e . This drop in σ e is attributed to two factors. First, disruption of the locally-ordered π-stacked domains observed through in situ humidity-dependent grazing incidence wide angle X-ray scattering (GIWAXS) experiments can account for some of the decrease in σ e . A second and more dominant factor is attributed to the swelling of the amorphous domains where electronic transport pathways connecting ordered domains are impeded. P3K7T is most resilient to swelling (based on ellipsometry and water uptake measurements) where sufficient hydration allows for high σ i (1.0 × 10 -1 S/cm at 95% RH) while not substantially disrupting σ e (1.7 × 10 -2 S/cm at 85% RH and 8.0 × 10 -3 S/cm at 95% RH). Overall, our study highlights the complexity of balancing electronic and ionic transport in hydrated CPEs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting the Dissolution Rate of Borosilicate Glasses using QSPR analysis based on molecular dynamics simulations

Quantitative Structure Property Relationship (QSPR) analysis based on molecular dynamics (MD) simulations is a promising approach for establishing the composition-property relationships of glass and other materials with complex structures. A series of 20 borosilicate and boroaluminosilicate glasses have been modeled by using MD simulations with recently developed effective potentials. Short- and medium-range structures of these glasses were analyzed and, based on these structural information, QSPR analysis of the initial dissolution rate (r0) was made and compared with measured r0 at 90°C and pH 9 using various structural descriptors such as percentage of bridging oxygen species, network connectivity and average ring size. The structural descriptors, Fnet, containing energetic information such as single bond strength and other structural information were also used. It was found that overall network connectivity, average ring size and Fnet give reasonable predictions of the r0 of studied glasses, given the conditions that the glasses are homogeneous and dissolve congruently. Modifying glass compositions to account preferential release of modifiers gives a better prediction for incongruently dissolving glasses. The results were compared with our recent work of predicting glass dissolution behavior from compositions using the topological-constraints-based models.

Du, Jincheng↗

The influence of nitrogen and nitrides on the structure and properties of proton irradiated ferritic/martensitic steel

The 12Cr1MoWV (wt%) ferritic/martensitic steel HT9 is a candidate material for fuel cladding in advanced nuclear reactors, such as the Versatile Test Reactor currently under development. As such, understanding the relationship between microstructure and mechanical properties in the context of irradiation environments for these steels is critical. N content, and more specifically interstitial N, has been hypothesized to be detrimental to irradiated properties at lower temperatures (less than 0.3T m ) to a total of 6 dpa; however, in this work at a dose of 1 dpa the irradiated microstructure was improved with added N, leading to less irradiation hardening. Three variants of HT9 were irradiated with 1.5 MeV protons to a dose of 1 dpa at 300°C. The HT9 variants included Low (10 ppm), Mid (190 ppm), and High (440 ppm) N alloys that were otherwise nearly identical. Changing the N content had a variety of effects on the irradiated defect structures. As N content increased, the average dislocation loop diameter decreased, while the number density of loops increased. Additionally, extensive Ni clustering was observed on dislocations and interfaces. The Mid and High N specimens exhibited significantly less hardening (ΔHV≃100) relative to the Low N specimen (ΔHV≃160). The decrease in hardening is attributed to vanadium carbonitride acting as a sink for Ni clusters that would otherwise form on dislocations. Under the irradiation conditions used, these results suggest increasing the N content in HT9 may have a desirable effect on the irradiated structure and properties at the dose studied, as well as the swelling resistance at higher doses. In other words, N content appears to be a powerful tool for tailoring the self-interstitial atom cluster mobility in F/M steels for different temperature and dose applications.

36 MATERIALS SCIENCE↗