Insight into the coordinated jetting behavior in periodic lattice structures under dynamic compression
Abstract not provided
Lind, Jonathan↗
SEARCH · Engineering Papers
Results for “materials image simulations”
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.
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Investigating the dielectric properties of barium titanate nanocomposites using transmission electron microscopy image processing
Abstract Barium titanate (BTO) is a ferroelectric perovskite material used in energy storage applications because of its high dielectric constant. A previous study showed that the dielectric constant for BTO nanoparticles drastically increases to over 15,000 at a particle size of 70 nm. This result is highly contested, but its implications to energy storage motivated our investigation into the dielectric constants of BTO nanoparticles that are incorporated into a polymer matrix. We developed a novel method of using image processing techniques on transmission electron microscope images of BTO-polymer nanocomposites. Data on the positions, shapes, sizes, and orientations of BTO nanoparticles were used to build more realistic computational models that simulate the dielectric behavior of the nanocomposites. Here, we investigate the relationship between regions of enhanced electric field and the composite dielectric constant.
36 MATERIALS SCIENCE↗
Solvent-Mediated Control of Nanocellulose Dispersion: An Integrated Computational and Experimental Investigation
Fibrillated cellulose derived from forestry feedstocks represents a renewable and high-strength materials platform for circular bioeconomies. However, its practical implementation is hindered by the irreversible aggregation of nanocellulose architectures, including cellulose nanofibers (CNFs). Solvent-based dispersion offers a simple and practical route to prevent CNF aggregation. Here, in this work, we integrate classical and enhanced sampling molecular dynamics (MD) simulations with experimental suspension rheology and atomic force microscopy (AFM) to elucidate how solvent environments tune CNF–CNF interactions and dispersion stability. CNF–CNF contact free energies computed from MD simulations reveal reduced aggregation in acetone/water, γ-valerolactone (GVL)/water, and tetrahydrofuran (THF)/water and pure acetone compared with pure water, reflecting stronger CNF-solvent relative to inter-CNF interactions. Correspondingly, CNF-solvent suspensions in these solvent systems exhibit stronger inter-fibril network structures and enhanced recovery compared to water, indicating improved CNF-solvent affinity. Liquid cell AFM imaging in acetone–water mixtures and in pure acetone further confirm the presence of well-dispersed CNFs. By combining multiscale computation with targeted experiments, this study establishes a rational framework for solvent design to achieve stable nanocellulose dispersions for high-strength biobased materials and efficient bioenergy conversion.
cellulose↗
Imaging broadband soft X-ray transmission-grating spectrograph for a wavelength range λ > 111 Å
A family of aperiodic Mo/Be multilayer mirrors was designed for maximum uniform reflectivity in the ranges 111 – 138, 111 – 150, 111 – 200 and 111 – 222 Å at normal radiation incidence. The simulations took into account the existence of Mo-on-Be and Be-on-Mo transition layers. It was shown that the reflectivity may be as high as 10% in an octave wavelength range of 111 – 222 Å. We demonstrate the operation of an imaging transmission-grating spectrograph with a broadband Mo/Be multilayer mirror with a uniform reflectivity in the wavelength range 111 – 138 Å synthesised at the Institute for the Physics of Microstructures, RAS. The spectrograph was used to record the line spectra of multiply charged fluorine and magnesium ions from a laser-produced plasma. The role of the grating support structure in the formation of spectral source images is discussed. The spatial resolution of 50 μm is demonstrated. (laser applications and other topics in quantum electronics)
36 MATERIALS SCIENCE↗
Building envelope modeling calibration using aerial thermography
Not provided.
Construction & Building Technology↗
Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar
This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.
36 MATERIALS SCIENCE↗
Terahertz conductivity of two-dimensional materials: a review
Two-dimensional (2D) van der Waals materials are shaping the landscape of next-generation devices, offering significant technological value thanks to their unique, tunable, and layer-dependent electronic and optoelectronic properties. Time-domain spectroscopic techniques at terahertz (THz) frequencies offer noninvasive, contact-free methods for characterizing the dynamics of carriers in 2D materials. They also pave the path toward the applications of 2D materials in detection, imaging, manufacturing, and communication within the increasingly important THz frequency range. In this paper, we overview the synthesis of 2D materials and the prominent THz spectroscopy techniques: THz time-domain spectroscopy, optical-pump THz-probe technique, and optical pump–probe THz spectroscopy. Through a confluence of experimental findings, numerical simulation, and theoretical analysis, we present the current understanding of the rich ultrafast physics of technologically significant 2D materials: graphene, transition metal dichalcogenides, MXenes, perovskites, topological 2D materials, and 2D heterostructures. Finally, we offer a perspective on the role of THz characterization in guiding future research and in the quest for ideal 2D materials for new applications.
2D materials↗
Accurate real space iterative reconstruction (RESIRE) algorithm for tomography
Tomography has made a revolutionary impact on the physical, biological and medical sciences. The mathematical foundation of tomography is to reconstruct a three-dimensional (3D) object from a set of two-dimensional (2D) projections. As the number of projections that can be measured from a sample is usually limited by the tolerable radiation dose and/or the geometric constraint on the tilt range, a main challenge in tomography is to achieve the best possible 3D reconstruction from a limited number of projections with noise. Over the years, a number of tomographic reconstruction methods have been developed including direct inversion, real-space, and Fourier-based iterative algorithms. Here, we report the development of a real-space iterative reconstruction (RESIRE) algorithm for accurate tomographic reconstruction. RESIRE iterates between the update of a reconstructed 3D object and the measured projections using a forward and back projection step. The forward projection step is implemented by the Fourier slice theorem or the Radon transform, and the back projection step by a linear transformation. Our numerical and experimental results demonstrate that RESIRE performs more accurate 3D reconstructions than other existing tomographic algorithms, when there are a limited number of projections with noise. Furthermore, RESIRE can be used to reconstruct the 3D structure of extended objects as demonstrated by the determination of the 3D atomic structure of an amorphous Ta thin film. We expect that RESIRE can be widely employed in the tomography applications in different fields. Finally, to make the method accessible to the general user community, the MATLAB source code of RESIRE and all the simulated and experimental data are available at https://zenodo.org/record/7273314.
97 MATHEMATICS AND COMPUTING↗
Sim2Real Autonomous Robotic Exploration [Poster]
Autonomous robots offer promising solutions for exploration in environments that are inaccessible or hazardous to humans. Despite this, physical training of such robots is often constrained by safety risks, high cost or limited accessibility. This project presents an end-to-end simulation to reality pipeline leveraging Nvidia Isaac Sim and Boston Dynamics' Spot to enable autonomous navigation in indoor environments. A reinforcement learning policy is first trained using Nvidia Isaac Lab to establish Spot's locomotion pattern. Virtual LiDAR sensors are then integrated to perform SLAM-based navigation using simulated odometry. Finally, the simulated navigation scheme is transferred to a physical Spot robot to inspect and record images of a real-world room by repeating the learnt trajectory. The proposed framework highlights the potential of scalable training in simulation and reliable deployment in physical environments. Future directions include dynamic trajectory generation in unseen and challenging environments and integration of environmental sensing like temperature, radiation or humidity via sensor and material simulation.
97 - MATHEMATICS AND COMPUTING↗
Optical contrast analysis of α -RuCl 3 nanoflakes on oxidized silicon wafers
α-RuCl 3 , a narrow-band Mott insulator with a large work function, offers intriguing potential as a quantum material or as a charge acceptor for electrical contacts in van der Waals devices. In this work, we perform a systematic study of the optical reflection contrast of α-RuCl 3 nanoflakes on oxidized silicon wafers and estimate the accuracy of this imaging technique to assess the crystal thickness. Via spectroscopic micro-ellipsometry measurements, we characterize the wavelength-dependent complex refractive index of α-RuCl 3 nanoflakes of varying thickness in the visible and near-infrared. Building on these results, we simulate the optical contrast of α-RuCl 3 nanoflakes with thicknesses below 100 nm on SiO 2 /Si substrates under different illumination conditions. We compare the simulated optical contrast with experimental values extracted from optical microscopy images and obtain good agreement. Finally, we show that optical contrast imaging allows us to retrieve the thickness of the RuCl 3 nanoflakes exfoliated on an oxidized silicon substrate with a mean deviation of –0.2 nm for thicknesses below 100 nm with a standard deviation of only 1 nm. Our results demonstrate that optical contrast can be used as a non-invasive, fast, and reliable technique to estimate the α-RuCl 3 thickness.
2D materials↗
Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns
Abstract A fast, robust pipeline for strain mapping of crystalline materials is important for many technological applications. Scanning electron nanodiffraction allows us to calculate strain maps with high accuracy and spatial resolutions, but this technique is limited when the electron beam undergoes multiple scattering. Deep-learning methods have the potential to invert these complex signals, but require a large number of training examples. We implement a Fourier space, complex-valued deep-neural network, FCU-Net, to invert highly nonlinear electron diffraction patterns into the corresponding quantitative structure factor images. FCU-Net was trained using over 200,000 unique simulated dynamical diffraction patterns from different combinations of crystal structures, orientations, thicknesses, and microscope parameters, which are augmented with experimental artifacts. We evaluated FCU-Net against simulated and experimental datasets, where it substantially outperforms conventional analysis methods. Our code, models, and training library are open-source and may be adapted to different diffraction measurement problems.
36 MATERIALS SCIENCE↗
Phase evolution and structural modulation during in situ lithiation of MoS 2 , WS 2 and graphite in TEM
Li-ion batteries function by Li intercalating into and through the layered electrode materials. Intercalation is a solid-state interaction resulting in the formation of new phases. The new observations presented here reveal that at the nanoscale the intercalation mechanism is fundamentally different from the existing models and is actually driven by nonuniform phase distributions rather than the localized Li concentration: the lithiation process is a ‘distribution-dependent’ phenomena. Direct structure imaging of 2H and 1T dual-phase microstructures in lithiated MoS 2 and WS 2 along with the localized chemical segregation has been demonstrated in the current study. Li, a perennial challenge for the TEM, is detected and imaged using a low-dose, direct-electron detection camera on an aberration-corrected TEM and confirmed by image simulation. This study shows the presence of fully lithiated nanoscale domains of 2D host matrix in the vicinity of Li-lean regions. This confirms the nanoscale phase formation followed by Oswald ripening, where the less-stable smaller domains dissolves at the expense of the larger and more stable phases.
25 ENERGY STORAGE↗
Evaluation of ceria as a surrogate material for UO 2 in experiments on fuel cracking driven by resistive heating
A variety of normal operation and accident scenarios can generate thermal stresses large enough to cause cracking in light-water reactor (LWR) fuel pellets. Cracking of fuel pellets can lead to reduced heat removal, larger centerline temperatures, and localized stress in cladding all of which impact fuel performance. Furthermore, pellet cracking also contributes to a temperature reduction in the pellet since the pellet fragments tend to move towards the heat sink (cladding), and the heat flow remains predominantly radial despite the presence of cracks. It is important to understand the temperature profile on the pellet before and after cracking to improve cracking models in fuel performance codes However, in-reactor observation and measurement of cracking is very challenging owing to the harsh environment and design of fuel rods. Recently, an experimental pellet cracking test stand was developed for separate effects testing of normal operations and accident temperature conditions, using thermal imaging to capture the pellet surface temperature for evaluation of thermal stresses and optical imaging to capture the evolution of cracking in real time. Cracking experiments were initially performed using ceria (CeO 2 ) as a surrogate fuel material, which is useful for developing and demonstrating the experimental approaches but is also valuable in its own right for cracking model development and validation. A combination of induction and resistance heating was used for volumetric heat generation in the pellet creating a thermal gradient. The material properties of CeO 2 and UO 2 are reviewed and compared for use in model development. Simulations of the experiment were performed to evaluate the behavior of the surrogate (CeO 2 ) fuel in BISON. The measured temperature profiles from BISON models match reasonably well with the observed experiments for the ceria pellets before cracking. The findings from this work will help improve confidence in fracture models used for fuel pellets under similar in-reactor conditions.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Probing the Role of Multi-scale Heterogeneity in Graphite Electrodes for Extreme Fast Charging
Electrode-scale heterogeneity can combine with complex electrochemical interactions to impede lithium-ion battery performance, particularly during fast charging. This research investigates the influence of electrode heterogeneity at different scales on the lithium-ion battery electrochemical performance under operational extremes. We employ image-based mesoscale simulation in conjunction with a three-dimensional electrochemical model to predict performance variability in 14 graphite electrode X-ray computed tomography data sets. Our analysis reveals that the tortuous anisotropy stemming from the variable particle morphology has a dominating influence on the overall cell performance. Cells with platelet morphology achieve lower capacity, higher heat generation rates, and severe plating under extreme fast charge conditions. On the contrary, the heterogeneity due to the active material clustering alone has minimal impact. Our work suggests that manufacturing electrodes with more homogeneous and isotropic particle morphology will improve electrochemical performance and improve safety, enabling electromobility.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Study of Shock Formation Parameters With Drive Conditions in Magnetically Accelerated Plasma Flows
We present experimental data regarding the formation of high-energy-density shocks in magnetically accelerated plasma flows using pulsed power drivers. We quantify the flow velocity and temperature of the ablated plasma using optical Thomson scattering and gated emission imaging across two different generators. We show that, regardless of the drive parameters, the plasma flows show continuous acceleration over centimeter spatial scales, in line with trends in published simulation work. When stationary targets are placed in these supersonic flows, bow-shock formation is observed at all drive parameters in a range of materials. In the higher density flow generated on the 1-MA COBRA generator at Cornell University, heating of the upstream flow ahead of the shock is observed and quantified, which is not observed at the lower density flow on the 0.2-MA Bertha driver at UC San Diego. Here, when combined with previous work on the XP generator at Cornell, we can show that these three experimental setups allow control of the effect of radiation loss and upstream absorption on the formation of the bow shock.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Wavelength-tunable infrared chiral metasurfaces with phase-change materials
Optical phase-change materials exhibit tunable permittivity and switching properties during phase transition, which offers the possibility of dynamic control of optical devices. Here, a wavelength-tunable infrared chiral metasurface integrated with phase-change material GST-225 is demonstrated with the designed unit cell of parallelogram-shaped resonator. By varying the baking time at a temperature above the phase transition temperature of GST-225, the resonance wavelength of the chiral metasurface is tuned in the wavelength range of 2.33 µm to 2.58 µm, while the circular dichroism in absorption is maintained around 0.44. The chiroptical response of the designed metasurface is revealed by analyzing the electromagnetic field and displacement current distributions under left- and right-handed circularly polarized (LCP and RCP) light illumination. Moreover, the photothermal effect is simulated to investigate the large temperature difference in the chiral metasurface under LCP and RCP illumination, which allows for the possibility of circular polarization-controlled phase transition. The presented chiral metasurfaces with phase-change materials offer the potential to facilitate promising applications in the infrared regime, such as chiral thermal switching, infrared imaging, and tunable chiral photonics.
36 MATERIALS SCIENCE↗
Nanoparticle self-assemblies with modern complexity
Thanks to decades of tireless efforts, nanoparticle assemblies have reached at an extremely high level of controllability, sophistication, and complexity, with new insights provided by integration with graph theory, cutting-edge characterization, and machine learning (ML)-based computation and modeling, as well as with ever-diversifying applications in energy, catalysis, biomedicine, optics, electronics, magnetics, organic biosynthesis, and quantum technology. Nanoparticle assemblies can be crystalline, known as superlattices or supracrystals. Their assembly entails a transition from disorder—dispersed nanoparticles—to order, which can be achieved through classical nucleation pathways or nonclassical pathways via prenucleation precursors or particle aggregation. Further, the periodic lattices allow facile manipulations of electrons, phonons, photons, and even spins, leading to advanced device components and metamaterials. Meanwhile, aperiodic assemblies out of nanoparticles, such as gels, networks, and amorphous solids, also start to attract attentions. Despite the loss of periodicity, symmetry-lowering or symmetry-breaking three-dimensional (3D) structures emerge with unique properties, such as chiroptical activity, topological mechanical strength, and quantum entanglement. Real-space imaging such as electron microscopy and X-ray based tomography methods are utilized to characterize these complex structures, while mathematical tools such as graph theories are in need to describe such complex structures. This issue aims to provide a timely review of the efforts in this greatly broadened materials design space including experiment, simulation, theory, and applications. Nine top experts (and their teams) from four countries deliver six review papers, summarizing fundamental mechanistic understandings of nanoparticle assemblies, highlighted with the developments of state-of-the-art in situ characterization tools and ML-assisted reverse engineering, and newly emergent applications of nanoarchitectures.
36 MATERIALS SCIENCE↗
Bragg coherent diffraction imaging by simultaneous reconstruction of multiple diffraction peaks
Bragg coherent diffractive imaging (BCDI) is a non-invasive microscopy technique that can visualize the morphology and internal lattice deviations of crystals with nanoscale spatial resolution and picometer deformation sensitivity. While BCDI has been successfully applied in various studies of materials, it is less successful for highly-strained crystals. Specifically, it is difficult to correctly reconstruct the electron density of a highly-strained object using conventional phase retrieval algorithms. Although various algorithms have been developed to overcome this challenge, most of them require a priori knowledge that is not always available in practice. Here we report on a new phase retrieval workflow that can invert diffraction patterns from multiple Bragg peaks simultaneously. The new workflow is explored via simulated diffraction from crystals with various strain conditions. Furthermore, reconstructions from the new workflow consistently demonstrate more accurate electron density maps, in comparison with the conventional method. For highly-strained crystals, the new workflow improves the reliability and consistency of BCDI phase retrieval significantly.
36 MATERIALS SCIENCE↗