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At least 361 records · Page 20

The role of faceting and elongation on the magnetic anisotropy of magnetite Fe3O4 nanocrystals

Abstract Fe 3 O 4 nanoparticles are one of the most promising candidates for biomedical applications such as magnetic hyperthermia and theranostics due to their bio-compatibility, structural stability and good magnetic properties. However, much is unknown about the nanoscale origins of the observed magnetic properties of particles due to the dominance of surface and finite size effects. Here we have developed an atomistic spin model of elongated magnetite nanocrystals to specifically address the role of faceting and elongation on the magnetic shape anisotropy. We find that for faceted particles simple analytical formulae overestimate the magnetic shape anisotropy and that the underlying cubic anisotropy makes a significant contribution to the energy barrier for moderately elongated particles. Our results enable a better estimation of the effective magnetic anisotropy of highly crystalline magnetite nanoparticles and is a step towards quantitative prediction of the heating effects of magnetic nanoparticles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Surface localized magnetism in transition metal doped alumina

Alumina is a structural ceramic that finds many uses in a broad range of applications. It is widely employed in the aerospace and biomedical sectors due to its stability at high temperatures and in harsh chemical environments. Here, we show that magnetism can be induced at alumina surfaces by doping with 3d transition metals. We analyze the electronic structure, spin magnetic moments, and spin density of α-Al 2 O 3 as a function of both dopant species (Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu) and depth using first principles calculations. Our results show that all dopants, with the exception of Sc, produce magnetic moments that are concentrated to the surface of alumina with varying degrees of delocalization. It is seen that all of the dopants are at least meta-stable on the surface and must overcome an energy barrier of 0.19–1.14 eV in order to diffuse from the surface into the bulk. As a result of judiciously doping with select 3$\textit{d}$ transition metals the surface of alumina can be made magnetic. This could lead to novel applications in data storage, catalysis, and biomedical engineering through an added surface functionality.

36 MATERIALS SCIENCE↗

Fingerprinting shock-induced deformations via diffraction

Abstract During the various stages of shock loading, many transient modes of deformation can activate and deactivate to affect the final state of a material. In order to fundamentally understand and optimize a shock response, researchers seek the ability to probe these modes in real-time and measure the microstructural evolutions with nanoscale resolution. Neither post-mortem analysis on recovered samples nor continuum-based methods during shock testing meet both requirements. High-speed diffraction offers a solution, but the interpretation of diffractograms suffers numerous debates and uncertainties. By atomistically simulating the shock, X-ray diffraction, and electron diffraction of three representative BCC and FCC metallic systems, we systematically isolated the characteristic fingerprints of salient deformation modes, such as dislocation slip (stacking faults), deformation twinning, and phase transformation as observed in experimental diffractograms. This study demonstrates how to use simulated diffractograms to connect the contributions from concurrent deformation modes to the evolutions of both 1D line profiles and 2D patterns for diffractograms from single crystals. Harnessing these fingerprints alongside information on local pressures and plasticity contributions facilitate the interpretation of shock experiments with cutting-edge resolution in both space and time.

36 MATERIALS SCIENCE↗

Ab initio structural dynamics of pure and nitrogen-containing amorphous carbon

Abstract Amorphous carbon (a-C) has attracted considerable interest due to its desirable properties, which are strongly dependent on its structure, density and impurities. Using ab initio molecular dynamics simulations we show that the sp 2 /sp 3 content and underlying structural order of a-C produced via liquid quenching evolve at high temperatures and pressures on sub-nanosecond timescales. Graphite-like densities ( $$\lesssim$$ ≲ 2.7 g/cc) favor the formation of layered arrangements characterized by sp 2 disordered bonding resembling recently synthesized monolayer amorphous carbon (MAC), while at diamond-like densities ( $$\gtrsim$$ ≳ 3.3 g/cc) the resulting structures are dominated by disordered tetrahedral sp 3 hybridization typical of diamond-like amorphous carbon (DLC). At intermediate densities the system is a highly compressible mixture of coexisting sp 2 and sp 3 regions that continue to segregate over 10’s of picoseconds. The addition of nitrogen (20.3%) (a-CN) generates major system features similar with those of a-C, but has the unexpected effect of reinforcing the thermodynamically disfavored carbon structural motifs at low and high densities, while inhibiting phase separation in the intermediate region. At the same time, no nitrogen elimination from the carbon framework is observed above $$\simeq$$ ≃ 2.8 g/cc, suggesting that nitrogen impurities are likely to remain embedded in the carbon structures during fast temperature quenches at high pressures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Two-dimensional forms of robust CO 2 reduction photocatalysts

Photoelectrocatalysts that use sunlight to power the CO 2 reduction reaction will be crucial for carbon-neutral power and energy-efficient industrial processes. Scalable photoelectrocatalysts must satisfy a stringent set of criteria, such as stability under operating conditions, product selectivity, and efficient light absorption. Two-dimensional materials can offer high specific surface area, tunability, and potential for heterostructuring, providing a fresh landscape of candidate catalysts. From a set of promising bulk CO 2 reduction photoelectrocatalysts, we screen for candidate monolayers of these materials, then study their catalytic feasibility and suitability. For stable monolayer candidates, we verify the presence of visible-light band gaps, check that band edges can support CO 2 reduction, determine exciton binding energies, and compute surface reactivity. We find visible light absorption for SiAs, ZnTe, and ZnSe monolayers, and that due to a lack of binding, CO selectivity is possible. We thus identify SiAs, ZnTe, and ZnSe monolayers as targets for further investigation, expanding the chemical space for CO 2 photoreduction candidates.

36 MATERIALS SCIENCE↗

Denary oxide nanoparticles as highly stable catalysts for methane combustion

Oxide nanoparticles with elemental and structural diversity are widely studied for catalysis and energy applications. While compositional control holds great promise for materials discovery, current oxide nanoparticles are typically limited to a few cations due to the intrinsic complexity in nanoscale multi-element mixing. Here we report the rational design and synthesis of single-phase multi-element oxide nanoparticles with tunable composition, size and structure. We have identified temperature-, oxidation- and entropy-driven synthesis strategies to mix a range of elements with largely dissimilar oxidation potentials (including palladium), thus greatly expanding the compositional space. Through rapid synthesis and screening, we obtained a denary multi-element oxide catalyst showing high performance and superior stability for catalytic methane combustion over 100 hours due to the high-entropy design and stabilization. Finally, our work therefore provides a viable synthesis route with clear guidelines for multi-element oxide nanoparticles and enables materials design in the multi-element space towards highly stable catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The role of stacking fault tetrahedra on void swelling in irradiated copper

Abstract A long-standing and critical issue in the field of irradiated structural materials is that void swelling is significantly higher in face-centered cubic-structured (fcc) materials (1% dpa −1 ) as compared to that of body-centered cubic-structured (bcc) materials (0.2% dpa −1 ). Despite extensive research in this area, the underlying mechanism of the difference in swelling resistance between these two types of materials is not yet fully understood. Here, by combining atomistic simulations and STEM imaging, we find stacking fault tetrahedra (SFTs) are the primary cause of the high swelling rate in pure fcc copper. We reveal that SFTs in fcc copper are not neutral sinks, different from the conventional knowledge. On the contrary, they are highly biased compared to other types of sinks because of the SFT-point defect interaction mechanism. SFTs show strong absorption of mobile self-interstitial atoms (SIAs) from the faces and vertices, and weak absorption of mobile vacancies from the edges. We compare the predicted swelling rates with experimental findings under varying conditions, demonstrating the distinct contributions of each type of sink. These findings will contribute to understanding the swelling of irradiated structural materials, which may facilitate the design of materials with high swelling resistance.

36 MATERIALS SCIENCE↗

Atomistic origin of the entropy of melting from inelastic neutron scattering and machine learned molecular dynamics

The latent heat, L, is central to melting, but its atomic origin remains elusive. It is proportional to the entropy of fusion, ΔS fus = L/T m (T m is the melting temperature), which depends on changes of atom configurations, atom vibrations, and thermal electron excitations. Here, we combine inelastic neutron scattering and machine-learned molecular dynamics to separate ΔS fus into these components for Ge, Si, Bi, Sn, Pb, and Li. When the vibrational entropy of melting, ΔS vib , is zero, ΔS fus ≃ 1.2 kB per atom. This result provides a baseline for ΔSconfig and nearly coincides with “Richard’s Rule” of melting. The ΔSfus deviates from this value for most elements, however, and we show that this deviation originates with extra ΔS vib and extra ΔS config . These two components are correlated for positive and negative deviations from Richard’s rule – the extra ΔS config is consistently ~ 80% of ΔS vib . Our results, interpreted with potential energy landscape theory, imply a correlation between the change in the number of basins and the change in the inverse of their curvature for the melting of pure elements.

36 MATERIALS SCIENCE↗

Molecular latent space simulators

Latent space simulators learn kinetic models for atomistic simulations and generate novel trajectories at six orders of magnitude lower cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nucleation-mediated reshaping of facetted metallic nanocrystals: Breakdown of the classical free energy picture

Shape stability is key to avoiding degradation of performance for metallic nanocrystals synthesized with facetted non-equilibrium shapes to optimize properties for catalysis, plasmonics, and so on. Reshaping of facetted nanocrystals is controlled by the surface diffusion-mediated nucleation and growth of new outer layers of atoms. Here, Kinetic Monte Carlo (KMC) simulation of a realistic stochastic atomistic-level model is applied to precisely track the reshaping of Pd octahedra and nanocubes. Unexpectedly, separate constrained equilibrium Monte Carlo analysis of the free energy profile during reshaping reveals a fundamental failure of the classical nucleation theory (CNT) prediction for the reshaping barrier and rate. Why? Nucleation barriers can be relatively low for these processes, so the system is not locally equilibrated before crossing the barrier, as assumed in CNT. This claim is supported by an analysis of a first-passage problem for reshaping within a master equation framework for the model that reasonably captures the behavior in KMC simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combined molecular and spin dynamics simulation of BCC iron with vacancy defects

Utilizing an atomistic computational model, which handles both translational and spin degrees of freedom, combined molecular and spin dynamics simulations have been performed to investigate the effect of vacancy defects on spin wave excitations in ferromagnetic iron. Fourier transforms of space- and time-displaced correlation functions yield the dynamic structure factor, providing characteristic frequencies and lifetimes of the spin wave modes. A comparison of the system with a 5% vacancy concentration with pure lattice data shows a decrease in frequency and a decrease in lifetime for all transverse spin wave excitations observed. In addition, the clearly defined transverse spin wave excitations are distorted with the introduction of vacancy defects, and we observe reduced excitation lifetimes due to increased magnon–magnon scattering. We observe further evidence of increased magnon–magnon scattering, as the peaks in the longitudinal spin wave spectrum become less distinct. Finally, similar impacts are observed in the vibrational subsystem, with a decrease in characteristic phonon frequency and flattening of lattice excitation signals due to vacancy defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating the diffusion of Kr in UO 2 and ADOPT TM using time-of-flight elastic recoil detection analysis (ToF-erda)

A combination of 300 keV 84 Kr ion implantation and Time-of-Flight Elastic Recoil Detection Analysis is utilized to investigate the diffusion of Kr in UO 2 and ADOPT TM fuels. Composition depth-profiles on the nanometer scale were obtained, both for as-implanted samples and after annealing at 800°C for 1 hour. Observed drifts in the 84 Kr profiles could be associated with short-range diffusion mechanisms. The approach employed here provides the possibility to make direct comparisons with atomistic scale modelling data, and can be of service as a separate effect test in line with the Accelerated Fuel Qualification initiative.

ADOPT UO2↗

Structural and thermodynamic characterization of CuZr metallic glass nanoparticles: Insights from atomistic simulations

Metallic crystalline nanoparticles (NPs) have been shown to display intriguing size-dependent properties. However, the properties of metallic glass (MG) NPs remain largely unexplored. Here, using molecular dynamics simulations, we produce Cu 64 Zr 36 MG NPs ranging in size from 1 to 20 nm by cooling molten systems at a relatively slow rate of 10 9 K/s. Results indicate that NPs are coated with a Cu-rich layer with a thickness that increases with NP size. We employ various simulated rates of heating, from 10 11 to 10 13 K/s, to determine the melting points of these NPs. The results show a significant decrease in the solidus temperature for NPs smaller than 10 nm. Furthermore, as NP size decreases, the fraction of Cu full icosahedra within the NPs increases, suggesting that smaller NPs are stronger and harder. These findings provide insights for designing heterogeneous metallic nanoglass materials that leverage the size-dependent properties of MG NPs.

36 MATERIALS SCIENCE↗

Multi-Scale Modeling of the Evolution of Structure and Properties in Materials for Nuclear Energy Applications [Slides]

Nuclear energy is an important component of an overall strategy to address climate change. Idaho National Laboratory (INL) is the U.S. Department of Energy’s primary facility for research and development in nuclear science and technology for energy generation, supporting the improvement and life extension of the existing reactor fleet and the development and licensing of new reactor designs. Computational modeling is an important component of these activities, particularly in the area of materials for nuclear applications, where experimental data can be very challenging and expensive to acquire, and where data is especially scarce for new reactor designs. INL has used multi-scale modeling – linking atomistic, mesoscale, and engineering scales – to improve the ability to predict the performance of materials for nuclear energy applications. In this talk, I will give an overview of the approach and tools used, and several examples of application, including performance of nuclear fuels, understanding radiation-driven formation of nanoscale void and gas bubble superlattices, and powder densification through electric field assisted sintering.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The Development of Catalysts for Upgrading of Pyrolysis Vapor for Refinery Feedstocks and Intermediates (CRADA Final Report)

Catalytic fast pyrolysis (CFP) is a versatile technology platform to convert biomass into fungible hydrocarbon transportation fuels and chemical co-products. Key technical barriers to reaching this goal include increasing the product yields and achieving the desired fuel properties for gasoline, diesel, and jet range fuels or blendstocks that would be suitable for introduction into existing refinery unit operations. Overcoming these barriers will require durable catalysts that are effective at upgrading and stabilizing biomass pyrolysis vapors. Towards these goals, this CRADA leveraged NREL experience as a leader in biomass pyrolysis research and Johnson Matthey's (JM) experience as a leader in the production of advanced catalytic materials. The scope spanned CFP catalyst development, characterization, multi-scale reaction testing, and computational modeling. CRADA benefits to DOE, Participant, and U.S. Taxpayer: Assists laboratory in achieving programmatic scope, Uses the laboratory’s core competencies. The purpose of this CRADA was to develop and deploy catalysts for biomass CFP to help achieve cost-competitive biofuels and bio-based products. This was accomplished through a close collaboration between biomass conversion researchers at NREL and catalyst development researchers at JM. Summary of Research Results: Focus Area 1. Foundational research on catalytic conversion and deactivation: Key interactions between pyrolysis vapors and heterogeneous catalysts were probed through catalyst characterization, model compound reaction testing, and atomistic-scale computational modeling. Catalyst development focused on multifunctional materials, which include zeolites, oxides, carbides, and nitrides. Computational modeling identified reaction mechanisms and elucidated surface chemistry to test hypotheses regarding mechanisms of deoxygenation, coupling, cracking, dehydration, coke formation, hydrogen transfer, and aromatic ring reactions. This information was used to design multifunctional catalysts to increase product yields, control product selectivity, and reduce deactivation during CFP and downstream processing steps. The results served to increase fundamental understanding of key catalyst attributes and durability features for the upgrading of biomass pyrolysis vapors. Model compound experiments confirmed the importance of metal-acid bifunctionality for the deoxygenation of lignin-derived phenolic species under hydrodeoxygenation conditions. This insight led to the development of catalysts such as Pt/TiO2 and Mo2C, which were confirmed as high-performing materials during subsequent bench-scale experiments using biomass-derived pyrolysis vapors. This focus area also led to the identification of important catalyst deactivation mechanisms associated with the deposition of inorganic contaminants such as potassium. The molecular-level insight from model compound experiments and computational modeling, shown in Figure 1, informed the development of regeneration procedures that have been shown to be effective for restoration of > 90% of initial catalyst activity. This understanding has subsequently been translated to other catalyst systems, including zeolite materials that can be operated without requirements for co-fed hydrogen.

09 BIOMASS FUELS↗

Multiscale Modeling, Simulation and Visualization and Their Potential for Future Aerospace Systems

This document contains the proceedings of the Training Workshop on Multiscale Modeling, Simulation and Visualization and Their Potential for Future Aerospace Systems held at NASA Langley Research Center, Hampton, Virginia, March 5 - 6, 2002. The workshop was jointly sponsored by Old Dominion University's Center for Advanced Engineering Environments and NASA. Workshop attendees were from NASA, other government agencies, industry, and universities. The objectives of the workshop were to give overviews of the diverse activities in hierarchical approach to material modeling from continuum to atomistics; applications of multiscale modeling to advanced and improved material synthesis; defects, dislocations, and material deformation; fracture and friction; thin-film growth; characterization at nano and micro scales; and, verification and validation of numerical simulations, and to identify their potential for future aerospace systems.

Noor, Ahmed K.↗

Building and Breaking Carbon Composites with REACTER

Carbon-based composites have become indispensable materials in aerospace and other high-performance applications, yet obtaining a detailed, nanoscale understanding of their morphology and failure mechanisms using only experimental methods remains a difficult challenge. REACTER is a versatile computational modeling tool for atomistic molecular dynamics simulations designed to model chemical reactions at the speed and length scales of classical force fields. In this work, several recent features of REACTER were applied to the creation and subsequent mechanical testing of two classes of carbon composites: carbon nanotube (CNT) composites and carbon fiber reinforced polymers (CFRP). A network of CNTs was grown dynamically using the new ‘create atoms’ feature of REACTER. The CNT filler was embedded into a polyarylacetylene (PAA) matrix by simulated in situ polymerization to obtain the final composite model. To generate the second class of carbon composite, fully carbonized (graphitic) carbon fiber morphologies were created by the method of Desai et al. [1], but using the advanced reaction constraints framework of REACTER. Two fiber models were created, representing a circular carbon fiber core and a flat surface, and similarly infiltrated with resin to obtain the final CFRP structure. Failure mechanisms were elucidated by simulating mechanically induced bond breaking, as characterized by third order DFT-based tight-binding simulations, via a reaction constraint on the total potential energy of the involved atoms.

Polymer↗