Search NASA⌕ Search

SEARCH · Search NASA

Results for “Size effect”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Parametric Instability of Alfvén Waves and Wave Packets in Periodic and Open Systems

The parametric decay instability of Alfvén waves has been widely studied, but few investigations have examined wave packets of finite size and the effect of different boundary conditions on the growth rate. In this paper, we perform a linear analysis of circular and arc-polarized wave trains and wave packets in periodic and open boundary systems in a low- β plasma. We find that both types of wave are 3–5 times more stable in open boundary conditions compared to periodic. Additionally, once the wave packet width ℓ becomes smaller than the system size L , the growth rate decreases nearly with a power law γ ∝ ℓ / L . This study demonstrates that the stability of a pump wave cannot be separated from the laboratory settings, and that the growth rate of daughter waves depends on the conditions downstream and upstream of the pump wave and on the fraction of volume it fills. Our results can explain simulations and experiments of localized Alfvén waves. They also suggest that Alfvénic fluctuations in the solar wind, including sharp impulses known as switchbacks, can be more stable than traditional theory suggests depending on wind conditions.

Alfven waves↗
DOE OSTI2024

Improving Text Classification with Large Language Model-Based Data Augmentation

Large Language Models (LLMs) such as ChatGPT possess advanced capabilities in understanding and generating text. These capabilities enable ChatGPT to create text based on specific instructions, which can serve as augmented data for text classification tasks. Previous studies have approached data augmentation (DA) by either rewriting the existing dataset with ChatGPT or generating entirely new data from scratch. However, it is unclear which method is better without comparing their effectiveness. This study investigates the application of both methods to two datasets: a general-topic dataset (Reuters news data) and a domain-specific dataset (Mitigation dataset). Our findings indicate that: 1. ChatGPT generated new data consistently enhanced model’s classification results for both datasets. 2. Generating new data generally outperforms rewriting existing data, though crafting the prompts carefully is crucial to extract the most valuable information from ChatGPT, particularly for domain-specific data. 3. The augmentation data size affects the effectiveness of DA; however, we observed a plateau after incorporating 10 samples. 4. Combining the rewritten sample with new generated sample can potentially further improve the model’s performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Alkali Cation Inhibition of Imidazolium-Mediated Electrochemical CO 2 Reduction on Silver

Imidazolium-based ionic liquids have led to enhanced CO 2 electroreduction activity due to cation effects at the cathode surface, stabilizing the reaction intermediates and decreasing the activation energy. In aqueous media, alkali cations are also known to improve CO 2 reduction activity on metals such as Ag, with the enhancement attributed to electrical double layer effects and trending with the size of the alkali cation. However, the effect of a mixed catholyte solution of alkali cations in the presence of an imidazolium-based ionic liquid has not been well-explored. Herein, 1-ethyl-3-methylimidazolium tetrafluoroborate, [EMIM][BF 4 ], in water was investigated with alkali salts to unravel the interaction effects for CO 2 electroreduction on Ag. Although both [EMIM] + and alkali cations have individually improved CO 2 to CO conversion on Ag in water, electrochemical results showed that alkali cations hindered imidazolium-mediated CO 2 electroreduction in most conditions. Li + , in particular, was sharply inhibitory compared to other alkali cations and strongly redirected the selectivity to hydrogen evolution. The nature of the alkali cation inhibition was investigated with spectroscopic techniques, including in situ surface-enhanced Raman spectroscopy (SERS) and dynamic electrochemical impedance spectroscopy (DEIS). Along with computational insights from density functional theory (DFT), the electrochemical and spectroscopic data suggest that alkali cations inhibit [EMIM]-mediated CO 2 reduction by competing for surface adsorption sites, preventing the potential-dependent structural reorientation of imidazolium, and promoting hydrogen evolution by bringing solvated water to the cathode surface.

cations↗
DOE OSTI2024

Femto-second Laser’s Enabling New Length Scale Fabrications for Rapid Post Irradiation Examination of Materials: Concluding LDRD Project Poster

Mechanical testing campaigns are required to qualify materials for advanced reactor conditions, yet economical and safety limitations restrict the number of standardized mechanical tests that can be performed. Reducing the size of the sample is one approach to addressing these challenges and to accelerating testing. Previous research has shown that smaller mechanical test samples produce higher yield and ultimate stress values compared to values measured from standard sample sizes: the “smaller is stronger” effect. Specimens used in accelerated material testing campaigns must reflect bulk material performance to enable engineering scale material property measurement. The objective of this research project was to determine if engineering scale mechanical behavior—the yield stress—could be measured with micro-tensile test samples smaller than traditional standard testing geometries. The relationship between yield stress and sample size was explored with two different nuclear-relevant structural materials: Zircaloy-4 and tungsten. Mechanical testing of both metals demonstrated decreasing yield stress values with increasing sample gauge size across three different sizes. Yield stress values from the largest gauge size, fabricated with a femto-second laser ablation system, approach bulk material yield stress values reported in published literature. Preliminary analysis of the tungsten samples indicates the yield stress value depends on the grain characteristics within the gauge section, in addition to the gauge size. Accompanying modeling efforts, including response surface generation and crystal plasticity approaches, further demonstrated that the size of the sample gauge section alone cannot explain the change in yield stress values.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industry

NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum (Sorghum bicolor), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry.

09 BIOMASS FUELS↗
DOE OSTI2024

Effect of solvothermal synthesis parameters on the crystallite size and atomic structure of cobalt iron oxide nanoparticles

We here investigate how the synthesis method affects the crystallite size and atomic structure of cobalt iron oxide nanoparticles. By using a simple solvothermal method, we first synthesized cobalt ferrite nanoparticles of ca. 2 and 7 nm, characterized by Transmission Electron Microscopy (TEM), Small Angle X-ray scattering (SAXS), X-ray and neutron total scattering. The smallest particle size corresponds to only a few spinel unit cells. Nevertheless, Pair Distribution Function (PDF) analysis of X-ray and neutron total scattering data shows that the atomic structure, even in the smallest nanoparticles, is well described by the spinel structure, although with significant disorder and a contraction of the unit cell parameter. These effects can be explained by the surface oxidation of the small nanoparticles, which is confirmed by X-ray near edge absorption spectroscopy (XANES). Neutron total scattering data and PDF analysis reveal a higher degree of inversion in the spinel structure of the smallest nanoparticles. Neutron total scattering data also allow magnetic PDF (mPDF) analysis, which shows that the ferrimagnetic domains correspond to ca. 80% of the crystallite size in the larger particles. A similar but less well-defined magnetic ordering was observed for the smallest nanoparticles. Finally, we used a co-precipitation synthesis method at room temperature to synthesize ferrite nanoparticles similar in size to the smallest crystallites synthesized by the solvothermal method. Structural analysis with PDF demonstrates that the ferrite nanoparticles synthesized via this method exhibit a significantly more defective structure compared to those synthesized via a solvothermal method.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Hydrogen permeation in iron-chromium-aluminum (FeCrAl) alloys and the effects of microstructure and surface oxide

Iron–chromium–aluminum (FeCrAl) class alloys are candidates for use as cladding for accident-tolerant fuels and moderators. In this context, hydrogen isotope permeation in FeCrAl alloys is an important material property. Here, in the present work, the apparent permeability, effective diffusivity, and apparent solubility of hydrogen in the FeCrAl alloys C26M and Kanthal D (KD) were measured with gas-driven hydrogen permeation. Permeation measurements were conducted at temperatures of 400 to 700 °C and at gas-driven pressures from 1 to 100 kPa. In particular, the effect of grain size on hydrogen transport was studied with KD samples with three different microstructures: nanocrystalline (NC), ultra-fine grained (UFG), and coarse-grained (CG). The UFG and NC specimens had higher apparent activation energies (73.4 kJ mol -1 and 65.2 kJ mol -1 , respectively) for hydrogen permeability than the CG sample (46.9 kJ mol -1 ). An aluminum oxide layer formed on the primary- and secondary-side surfaces of all samples subjected to permeation experiments which demonstrated the propensity of FeCrAl alloys to form these innate oxide permeation barriers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Structure-dependent clustering-to-declustering solute segregation transitions near disconnections

Grain-boundary disconnections, characterized by a step and a dislocation, are pervasive interfacial line defects that play a critical role in governing the properties and performance of nanocrystalline alloys. Although segregation of alloying elements is frequently observed at GB disconnections, the underlying mechanisms remain poorly understood, particularly at elevated temperatures and non-dilute conditions. In this study, we employ atomistic simulations to study the segregation behavior of Ag at various faulted disconnections in Cu as a model material system. Our results demonstrate a pronounced size and compactness effect on the segregation behavior: more compact faulted disconnection structures promote the formation of Ag segregation clusters due to a highly localized tensile field, whereas more spread faulted disconnection structures (i.e., with wider partial dislocation spacing) exhibit much weaker clustering tendencies. Furthermore, with increasing temperature, Ag clustering in small disconnections initially intensifies and then disappears, indicating a thermally driven transition from clustering to declustering segregation behavior.

Disconnections↗
DOE OSTI2024

Exploring the Effects of Intersubunit Interface Mutations on Virus-Like Particle Structure and Stability

Virus-like particles (VLPs) from bacteriophage MS2 provide a platform to study protein self-assembly and create engineered systems for drug delivery. Here, we aim to understand the impact of intersubunit interface mutations on the local and global structure and function of MS2-based VLPs. In previous work, our lab identified locally supercharged double mutants [T71K/G73R] that concentrate positive charge at capsid pores, enhancing uptake into mammalian cells. To study the effects of particle size on cellular internalization, we combined these double mutants with a single point mutation [S37P] that was previously reported to switch particle geometry from T = 3 to T = 1 icosahedral symmetry. These new variants retained their enhanced cellular uptake activity and could deliver small-molecule drugs with efficacy levels similar to our first-generation capsids. Surprisingly, these engineered triple mutants exhibit increased thermostability and unexpected geometry, producing T = 3 particles instead of the anticipated T = 1 assemblies. Transmission electron microscopy revealed various capsid assembly states, including wild-type (T = 3), T = 1, and rod-like particles, that could be accessed using different combinations of these point mutations. Molecular dynamics experiments recapitulated the structural rationale in silico for the single point mutation [S37P] forming a T = 1 virus-like particle and showed that this assembly state was not favored when combined with mutations that favor rod-like architectures. Through this work, we investigated how interdimer interface dynamics influence VLP size and morphology and how these properties affect particle function in applications such as drug delivery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

High-Pressure Rate Rules for Ether Alkylperoxy Radical Isomerization

The first isomerization reaction of an alkylperoxy (RO 2 ) radical holds significant importance in low-temperature oxidation, as it governs the branching ratios of the hydroperoxyalkyl (QOOH) radicals, which influence the competition between the chain-propagation and chain-branching reactions. In this study, we systematically calculated high-pressure rate rules for the RO 2 isomerization reaction of monoethers, exploring 5-, 6-, 7-, and 8-membered ring transition states. Primary, secondary, and tertiary carbon sites, where both the abstracting peroxy group and the abstracted hydrogen are located, were considered, with particular emphasis on distinguishing between secondary carbons adjacent (alpha) and nonadjacent to the ether functional group. Using the G4//B3LYP/6-311++G(2df,2pd) level of theory and the transition state theory, we estimated the rate constants and the Arrhenius coefficient for over 120 possible isomerization reactions. We examined the effect of ring size and ring atoms, revealing that 6- and 7-membered ring isomerizations were generally the fastest. The impact of the ether functional group on transition states was investigated by comparing reactions with identical ring size, peroxy, and radical positions, but with the ether functional group positioned either outside (i.e., out) or inside (i.e., in) the transition state ring, leading to differences in the rate constants. When comparing to analogous alkane rate constants, differences of up to an order of magnitude were observed, underscoring the need for caution when assigning rate rules by analogy. We applied our rate constants in the di-iso-butyl ether kinetic model and evaluated their influence on low-temperature chemistry finding that they altered the branching ratios by up to a factor of 9, highlighting the significance of site-specific rate constants for more accurate low-temperature modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

In Situ Measurement of Adhesion for Multimetallic Nanoparticles

The adhesion of nanoparticles to their supports is key to their performance and stability. However, scientific advances in this area have been hampered by the difficulty of experimentally probing adhesion. To date, only a single technique has been developed that can directly measure nanoparticle adhesion, and this technique is inherently limited to monometallic systems. We present a versatile technique for the direct measurement of adhesion for bimetallic nanoparticle systems. This technique combines the spatial resolution of transmission electron microscopy with the force resolution of an atomic force microscope to probe individual, well-characterized nanoparticles. A first study of supported bimetallic nanoparticles provides new insights into the complex impact of alloying on nanoparticle adhesion, explained by charge transfer between constituent metals. The new experimental technique is readily extensible to study other multimetallic nanoparticle systems, including the effects of particle size, shape, and orientation, thus enabling advances in our understanding of nanoparticle physics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Flux-Closure Domain Structures in Ferroelectric K 0.5 Na 0.5 NbO 3 Thin Films

Topological domain structures in ferroelectric materials have garnered increasing attention due to their intriguing physical properties and promising applications. While most existing topological structures in ferroelectric perovskite oxides originate from tetragonal or rhombohedral bulk phases, much less is understood about their counterparts in orthorhombic ferroelectrics. Here, in this work, we employ ferroelectric K 0.5 Na 0.5 NbO 3 (KNN) thin films as a model system and leverage phase-field simulations to theoretically predict the static structures and dynamic behaviors of three types of flux-closure domain configurations: in-plane (Type-I), out-of-plane (Type-II), and superdomain (Type-III) flux-closure structures. We systematically investigate the effects of finite size, misfit strains, and electrical boundary conditions on the formation and switching of these topological structures. For the Type-I structure, size reduction or small misfit strain facilitates a transition of the flux-closure pattern to polar vortices. Type-II structures emerge under open-circuit electrical boundary conditions of the film, forming at the junctions of specific domain walls with the film surface or the film–substrate interface. The formation mechanisms of these two flux-closure structures are rationalized from an energy perspective. We demonstrated switching capabilities of Type-II and Type-III structures by obtaining polarization–electric field hysteresis loops. Our simulations also reveal a reversible electric-field-induced transition between the orthorhombic and rhombohedral ferroelectric phases with a checkerboard domain pattern, during which the integrity of the flux-closure structure is preserved. These findings provide theoretical insights and practical guidance for identifying and manipulating topological structures in low-symmetry ferroelectrics, paving the way for developing energy-efficient microelectronic devices based on topological structures.

P-E loop↗
DOE OSTI2024

Unveiling Spatial and Temporal Dynamics of Plasmon-Enhanced Localized Fields in Metallic Nanoframes through Ultrafast Electron Microscopy

Plasmonic nanomaterials, particularly noble metal nanoframes (NFs), are important for applications such as catalysis, biosensing, and energy harvesting due to their ability to enhance localized electric fields and atomic efficiency via localized surface plasmon resonance (LSPR). Yet the fundamental structure-function relationships and plasmonic dynamics of the NFS are difficult to study experimentally and thus far rely predominately on computational methodologies, limiting their utilization. This study leverages the capabilities of ultrafast electron microscopy (UEM), specifically photon-induced near-field electron microscopy (PINEM), to probe the light-matter interactions within plasmonic NF structures. Here, the effects of shape, size, and plasmonic coupling of Pt@Au core-shell NFs on spatial and temporal characteristics of plasmon-enhanced localized electric fields are explored. Importantly, time-resolved PINEM analysis reveals that the plasmonic fields around hexagonal NF prisms exhibit a spatially dependent excitation and decay rate, indicating a nuanced interplay between the spatial geometry of the NF and the temporal evolution of the localized electric field. These results and observations uncover nanophotonic energy transfer dynamics in NFs and highlight their potential for applications in biosensing and photocatalysis.

Plasmonics↗
DOE OSTI2026

Marine Aerosol to Refinery Emissions: Transport and Evolution of CCN in the Houston Metropolitan Area and Their Impact on Cloud Formation

The Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) campaign aimed to untangle the impacts of contrasting aerosol sources on cloud microphysical properties within deep convective cells using airborne observations with the National Research Council Canada (NRC) Convair CV‐580 research aircraft. Horizontal and vertical gradients of aerosol number size distributions, total aerosol concentrations and cloud condensation nuclei (CCN) spectra were measured in the lower troposphere to quantify the impact of different aerosol sources on aerosol‐cloud interactions. This study focuses on a research flight dedicated to characterizing the aerosol and CCN properties in the Houston Metropolitan region and identifies five main categories of aerosols based on characteristics of aerosol number size distributions, their CCN properties and meteorological conditions. These categories encompassed more than two orders of magnitude differences in aerosol and CCN concentrations, yet their hygroscopic properties remained similar. Aerosol number size distributions and effective hygroscopicity parameters are used to generate continuous CCN spectra to represent the major aerosol types. The different CCN spectra are then incorporated into a 1‐D aerosol‐cloud parcel model using a large range of updrafts selected in the range of those observed during the ESCAPE campaign to assess the impact of the major aerosol sources in Houston on deep convective cloud microphysical properties.

aerosol-cloud interactions↗
DOE OSTI2024

Unusual plastic strain-induced phase transformation phenomena in silicon

Pressure-induced phase transformations (PTs) in Si, the most important electronic material, have been broadly studied, whereas strain-induced PTs have never been studied in situ. Here, we reveal in situ various important plastic strain-induced PT phenomena. A correlation between the direct and inverse Hall-Petch effect of particle size on yield strength and pressure for strain-induced PT is predicted theoretically and confirmed experimentally for Si-I→Si-II PT. For 100 nm particles, the strain-induced PT Si-I→Si-II initiates at 0.3 GPa under both compression and shear while it starts at 16.2 GPa under hydrostatic conditions. The Si-I→Si-III PT starts at 0.6 GPa but does not occur under hydrostatic pressure. Pressure in small Si-II and Si-III regions of micron and 100 nm particles is ~5–7 GPa higher than in Si-I. For 100 nm Si, a sequence of Si-I → I + II → I + II + III PT is observed, and the coexistence of four phases, Si-I, II, III, and XI, is found under torsion. Retaining Si-II and single-phase Si-III at ambient pressure and obtaining reverse Si-II→Si-I PT demonstrates the possibilities of manipulating different synthetic paths. The obtained results corroborate the elaborated dislocation pileup-based mechanism and have numerous applications for developing economic defect-induced synthesis of nanostructured materials, surface treatment (polishing, turning, etc.), and friction.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Colloidal synthesis of ultrathin KFeS 2 and RbFeS 2 magnetic nanowires with non-van der Waals 1D structures

Design of one-dimensional (1D) nanomaterials based on non-van der Waals (non-vdW) 1D chain structures is emerging as a new materials frontier, owing to their strong intrinsic anisotropy and broad compositional diversity. However, achieving ultrathin 1D morphology in such systems remains a significant challenge. In this work, we report the colloidal synthesis of ultrathin KFeS 2 and RbFeS 2 nanowires—representing the first fabrication of ultrathin 1D nanomaterials driven by non-vdW 1D crystal structures. The nanowires exhibit diameters of ∼5 nm and lengths of microns, with anisotropic growth directed by covalent [FeS 2 ] − chains. Magnetic characterization reveals significantly reduced antiferromagnetic transition temperatures and suppressed interchain ferromagnetic interactions, demonstrating pronounced size and morphology effects. Control experiments on structurally related materials indicate that direct nucleation of the 1D phase is essential for achieving the nanowire morphology. These findings establish a new synthetic pathway to an understudied family of non-vdW 1D nanomaterials, enabling exploration of their emergent quantum and magnetic properties.

Sun, Zhaohong [University of Southern California, ↗
DOE OSTI2025

Local orthorhombic phase in zirconium oxide nanocrystals: insights from X-ray pair distribution function analysis

Zirconium dioxide (ZrO 2 ) and hafnium dioxide (HfO 2 ) have emerged as promising alternatives to conventional ferroelectric materials. Understanding the crystal phases of these oxides under different conditions is crucial for optimizing their properties. There are several theories for the (anti)ferroelectric properties; however, comprehensive analysis, particularly at the local structure level, is lacking. In this study, we investigate the local structure of ZrO 2 nanocrystals using X-ray pair distribution function (PDF) analysis, revealing an unexpected local orthorhombic distortion irrespective of crystallite size. This finding suggests the potential existence of an intermediate orthorhombic phase during the microscopic switching pathway observed in previous studies. Additionally, we explore the influence of crystallite size and surface effects on the PDF. These results contribute to a deeper understanding of the structural dynamics in ZrO 2 and offer insights for the design of next-generation ferroelectric materials.

Pokratath, Rohan (ORCID:0000000268383939)↗
DOE OSTI2025

Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling

Atomistic materials modeling is a critical task with wide-ranging applications, from drug discovery to materials science, where accurate predictions of the target material property can lead to significant advancements in scientific discovery. Graph Neural Networks (GNNs) represent the state-of-the-art approach for modeling atomistic material data thanks to their capacity to capture complex relational structures. While machine learning performance has historically improved with larger models and datasets, GNNs for atomistic materials modeling remain relatively small compared to large language models (LLMs), which leverage billions of parameters and terabyte-scale datasets to achieve remarkable performance in their respective domains. To address this gap, we explore the scaling limits of GNNs for atomistic materials modeling by developing a foundational model with billions of parameters, trained on extensive datasets in terabytescale. Our approach incorporates techniques from LLM libraries to efficiently manage large-scale data and models, enabling both effective training and deployment of these large-scale GNN models. This work addresses three fundamental questions in scaling GNNs: the potential for scaling GNN model architectures, the effect of dataset size on model accuracy, and the applicability of LLM-inspired techniques to GNN architectures. Specifically, the outcomes of this study include (1) insights into the scaling laws for GNNs, highlighting the relationship between model size, dataset volume, and accuracy, (2) a foundational GNN model optimized for atomistic materials modeling, and (3) a GNN codebase enhanced with advanced LLM-based training techniques. Our findings lay the groundwork for large-scale GNNs with billions of parameters and terabyte-scale datasets, establishing a scalable pathway for future advancements in atomistic materials modeling.

Li, Chaojian [ORNL] (ORCID:0000000340309777)↗