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Highly Reversible Plating/Stripping of Porous Zinc Anodes for Multivalent Zinc Batteries
Zinc continues to garner immense interest due to its versatility as an anode material in several configurations utilizing either alkaline or mild-pH electrolytes. Current research on using mild-pH electrolytes has improved the rechargeability aspect of Zn-based batteries since Zn2+ is solely utilized for plating/stripping of Zn. Several studies have incorporated Zn metal foils, yet, dramatic improvements can be achieved by expressing Zn as a porous structure. Herein, we use a quasi-pulsed electrodeposition process to prepare a conformal Zn coating onto 3D porous copper foam. By tuning the electrodeposition parameters, we achieved an optimal Zn coating that undergoes reversible plating/stripping when tested in symmetric Zn cells, which supported a low overpotential of ~60 mV for up to 100 cycles. We further investigated changes in the surface morphology by studying the Zn surface of both foil and 3D structure using scanning electron microscopy and X-ray micro-computed tomography. Both techniques showed that the Zn foil undergoes dramatic alterations at the surface, which results in inhomogeneous deposition of Zn, whereas the 3D form exhibited minimal changes. Lastly, we paired both Zn foil and 3D Zn with vanadium oxide and demonstrated that the porous structure supports high rate capability and high specific capacity.
Suppressing proximity effects during rapid serial two-photon lithography through tuning of reaction–diffusion kinetics
The ability of two-photon lithography (TPL) to print deterministic nanoporous 3D structures is highly valuable for many applications. However, it is challenging to print such structures rapidly due to the proximity effects that cause closely spaced features to enlarge and merge. A key challenge is the limited understanding of the origins and spatiotemporal dynamics of the long-range proximity effects that extend beyond the optical focal spot. Here, we empirically investigate these proximity effects in serial TPL using custom-made acrylate-based photoresists. We demonstrate that the complex spatiotemporal dynamics of the proximity effects can be explained through the kinetics of the reaction–diffusion photopolymerization mechanisms that underlie the curing process. Specifically, we show that the proximity effects arise due to comparable timescales of reaction and diffusion of oxygen. Furthermore, we demonstrate that long-range proximity effects can be suppressed by introducing phenolic inhibitors, which reduce oxygen consumption through non-inhibiting side reactions and promote faster termination of curing reactions. These insights enabled improving the linewidths from >400 to 260 nm during printing of nanoporous 3D woodpiles at scanning speeds of 50 mm s −1 . Thus, the knowledge generated here can be applied to deterministically tune the proximity effects and enable rapid printing of high-resolution nanoporous 3D structures.
Pool boiling critical heat flux studies of accident tolerant fuel cladding materials
Pool boiling experiments have been performed at atmospheric pressure on potential accident tolerant fuel (ATF) cladding materials (Zirlo®, Cr coated Zirlo®, FeCrAl coated Zirlo®, and monolithic SiC) to evaluate the Critical Heat Flux (CHF) points. Corrosion resistant coatings of Cr and FeCrAl alloy were deposited on flat Zirlo® samples using cold spray technology. The as-prepared samples after uniform surface polishing were subjected to autoclave tests at 360 °C water and 18.6 MPa for 360 h to simulate prototypic corrosion of the ATF cladding materials in LWR normal operation. Surface characteristics potentially influencing CHF such as surface morphology, roughness, static contact angle, and surface chemistry were characterized using a suite of characterization methods including scanning electron microscopy, 3D optical profilometry, optical contact angle measurements, and x-ray photoelectron spectroscopy (XPS). Thermo-physical properties of the samples such as density, thermal conductivity, and heat capacity were measured by differential scanning calorimetry and laser flash thermal diffusivity measurement. FeCrAl coatings showed CHF values comparable to bare Zirlo® samples, while slightly lower CHF values were observed for Cr coated samples and bulk SiC flats (produced by chemical vapor deposition, CVD). As-deposited Cr coatings showed 67% higher CHF than the as-polished Cr coatings due to its higher surface roughness level. The autoclave testing for the prepared samples generally increased the CHF except for the surface polished Cr coatings. Similar CHF values of bare Zirlo®, FeCrAl coating, and CVD SiC samples were observed after autoclave test but there were negligible change CHF of Cr coatings. XPS studies indicated that the formation or deposition of a few monolayers of hydrophobic carbonaceous species on surface can affect CHF values. The trends in CHF data are discussed in terms of evolution of the surface characteristics of the ATF materials.
Electron tomography imaging methods with diffraction contrast for materials research
Transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) enable the visualization of three-dimensional (3D) microstructures ranging from atomic to micrometer scales using 3D reconstruction techniques based on computed tomography algorithms. This 3D microscopy method is called electron tomography (ET) and has been utilized in the fields of materials science and engineering for more than two decades. Although atomic resolution is one of the current topics in ET research, the development and deployment of intermediate-resolution (non-atomic-resolution) ET imaging methods have garnered considerable attention from researchers. This research trend is probably not irrelevant due to the fact that the spatial resolution and functionality of 3D imaging methods of scanning electron microscopy (SEM) and X-ray microscopy have come to overlap with those of ET. In other words, there may be multiple ways to carry out 3D visualization using different microscopy methods for nanometer-scale objects in materials. From the above standpoint, this review paper aims to (i) describe the current status and issues of intermediate-resolution ET with regard to enhancing the effectiveness of TEM/STEM imaging and (ii) discuss promising applications of state-of-the-art intermediate-resolution ET for materials research with a particular focus on diffraction contrast ET for crystalline microstructures (superlattice domains and dislocations) including a demonstration of in situ dislocation tomography.
Wood-reinforced composites by stereolithography with the stress whitening behavior
In this study, poplar wood flour at various concentrations (1–10 wt%) is incorporated into a methacrylate-based resin via solution blending to fabricate wood-reinforced composites using stereolithography apparatus (SLA) 3D printing. Differential scanning calorimetry (DSC) along with Fourier transform infrared spectroscopy (FTIR) analysis shows the presence of a small amount of residual monomer in the printed samples. For the printed composites, the glass transition temperature (T g ) from dynamic mechanical analysis (DMA) decreases as more wood flour is incorporated, which indicates an increase in free volume occupied by polymer chains. The tensile strength is improved up to 17.3% from 21.1 MPa (no wood flour) to 24.7 MPa (1.0 wt% wood flour). The highest Young’s modulus reaches 323.8 MPa (2.0 wt% wood flour), which is 1.9-fold of that of the sample without wood flour. Moreover, the composites show “stress whitening” with the addition of wood flour during the uniaxial drawing. Morphology analysis of the tested samples show that the formation of microcraze and microvoids likely causing the stress whitening. This is the first study that demonstrates wood flour can be utilized in SLA 3D printed wood plastic composites (WPC) which can reinforce the printed products with a modest loading amount.
Temporally continuous thermofluidic–thermomechanical modeling framework for metal additive manufacturing
Additive manufacturing (AM) is known to generate large magnitudes of residual stresses (RS) within builds due to steep and localized thermal gradients. In the current state of commercial AM technology, manufacturers generally perform heat treatments in effort to reduce the generated RS and its detrimental effects on part distortion and in-service failure. Computational models that effectively simulate the deposition process can provide valuable insights to improve RS distributions. Accordingly, it is common to employ Computational fluid dynamics (CFD) models or finite element (FE) models. While CFD can predict geometric and thermal-fluid behavior, it cannot predict the structural response (e.g., stress–strain) behavior. On the other hand, an FE model can predict mechanical behavior, but it lacks the ability to predict geometric and fluid behavior. Thus, an effectively integrated thermofluidic–thermomechanical modeling framework that exploits the benefits of both techniques while avoiding their respective limitations can offer valuable predictive capability for AM processes. In contrast to previously published efforts, the work herein describes a one-way coupled CFD-FEA framework that abandons major simplifying assumptions, such as geometric steady-state conditions, the absence of material plasticity, and the lack of detailed RS evolution/accumulation during deposition, as well as insufficient validation of results. Here, the presented framework is demonstrated for a directed energy deposition (DED) process, and experiments are performed to validate the predicted geometry and RS profile. Both single- and double-layer stainless steel 316L builds are considered. Geometric data is acquired via 3D optical surface scans and X-ray micro-computed tomography, and residual stress is measured using neutron diffraction (ND). Comparisons between the simulations and measurements reveal that the described CFD-FEA framework is effective in capturing the coupled thermomechanical and thermofluidic behaviors of the DED process. The methodology presented is extensible to other metal AM processes, including power bed fusion and wire-feed-based AM.
Three-dimensional superlattice engineering with block copolymer epitaxy
Three-dimensional (3D) structures at the nanometer length scale play a crucial role in modern devices, but their fabrication using traditional top-down approaches is complex and expensive. Analogous to atomic lattices, block copolymers (BCPs) spontaneously form a rich variety of 3D nanostructures and have the potential to substantially simplify 3D nanofabrication. Here, we show that the 3D superlattice formed by BCP micelles can be controlled by lithographically defined 2D templates matching a crystallographic plane in the 3D superlattice. Using scanning transmission electron microscopy tomography, we demonstrate precise control over the lattice symmetry and orientation. Excellent ordering and substrate registration can be achieved, propagating through 284-nanometer-thick films. BCP epitaxy also showed exceptional lattice tunability, with a continuous Bain transformation from a body-centered cubic to a face-centered cubic lattice. Lattice stability was mediated by molecular packing frustration, and surface-induced lattice reconstruction was observed, leading to the formation of a unique honeycomb lattice.
Gargantuan Hail in Argentina
On 8 February 2018, a supercell storm produced gargantuan (>15 cm or >6 inches in maximum dimension) hail as it moved over the heavily populated city of Villa Carlos Paz in Cordoba Province, Argentina, South America. Observations of gargantuan hail are quite rare, but the large population density here yielded numerous witnesses and social media pictures and videos from this event that document multiple large hailstones. The storm was also sampled by the newly installed operational polarimetric C-band radar in Cordoba. During the RELAMPAGO campaign, the authors interviewed local residents about their accounts of the storm, and uncovered additional social media video and photographs revealing extremely large hail at multiple locations in town. This article documents the case, including the meteorological conditions supporting the storm (with the aid of a high-resolution WRF simulation), the storm's observed radar signatures, and three noteworthy hailstones observed by residents. These hailstones include a freezer-preserved 4.48-inch (11.38-cm) maximum dimension stone that was scanned with a 3D infrared laser scanner, a 7.1-inch (18-cm) maximum dimension stone, and a hailstone photogrammetrically estimated to be between 7.4 and 9.3 inches (18.8-23.7-cm) in maximum dimension, which is close to or exceeds the world record for maximum dimension. Such a well-observed case is an important step forward in understanding environments and storms that produce gargantuan hail, and ultimately how to anticipate and detect such extreme events.
304L Can Crush Validation Studies
Accurate prediction of ductile behavior of structural alloys up to and including failure is essential in component or system failure assessment, which is necessary for nuclear weapons alteration and life extensions programs of Sandia National Laboratories. Modeling such behavior requires computational capabilities to robustly capture strong nonlinearities (geometric and material), rate- dependent and temperature-dependent properties, and ductile failure mechanisms. This study's objective is to validate numerical simulations of a high-deformation crush of a stainless steel can. The process consists of identifying a suitable can geometry and loading conditions, conducting the laboratory testing, developing a high-quality Sierra/SM simulation, and then drawing comparisons between model and measurement to assess the fitness of the simulation in regards to material model (plasticity), finite element model construction, and failure model. Following previous material model calibration, a J 2 plasticity model with a microstructural BCJ failure model is employed to model the test specimen made of 304L stainless steel. Simulated results are verified and validated through mesh and mass-scaling convergence studies, parameter sensitivity studies, and a comparison to experimental data. The converged mesh and degree of mass-scaling are the mesh discretization with 140,372 elements, and a mass scaling with a target time increment of 1.0e-6 seconds and time step scale factor of 0.5, respectively. Results from the coupled thermal-mechanical explicit dynamic analysis are comparable to the experimental data. Simulated global force vs displacement (F/D) response predicts key points such as yield, ultimate, and kinks of the experimental F/D response. Furthermore, the final deformed shape of the can and field data predicted from the analysis are similar to that of the deformed can, as measured by 3D optical CMM scans and DIC data from the experiment.
dlppi2 (b1)
The Doppler lidar (DL) is an active remote-sensing instrument that provides range- and time-resolved measurements of the line-of-sight component of air velocity (i.e., radial velocity) and attenuated aerosol backscatter. The DL operates in the near-infrared and is sensitive to backscatter from atmospheric aerosol, which are assumed to be ideal tracers of atmospheric wind fields. The DL works by transmitting short pulses of infrared laser light into the atmosphere. Atmospheric aerosols scatter a small fraction of that light energy back to the transceiver, where it is collected and recorded as a time-resolved signal. From the delay between the outgoing pulse and the backscattered signal, the instrument infers the distance to the scattering volume. Coherent detection is used to measure the Doppler frequency shift of the backscatter signal. This is accomplished by mixing the backscatter signal with a reference laser beam (i.e., local oscillator) of known frequency. The onboard signal processor then determines the Doppler frequency shift from the spectrum of the mixed signal. The Doppler frequency shift and thus the radial air velocity is determined from the peak of the Doppler spectrum. The attenuated backscatter is determined from the energy content of the Doppler spectra. The DL provides accurate measurements of radial velocity in regions of the atmosphere where aerosol concentrations are high enough to ensure good signal-to-noise ratio. Thus, valid data are usually limited to the atmospheric boundary layer where aerosol is ubiquitous. Valid measurements can also be obtained in elevated aerosol layers or in optically thin clouds above the boundary layer. Most of the ARM DLs have full upper-hemispheric scanning capability, enabling 3D mapping of turbulent flows in the atmospheric boundary layer. With the scanner pointed vertically, the DL provides height- and time-resolved measurements of vertical velocity.
Correlation approach for quality assurance of additive manufactured parts based on optical metrology
Surface topography and surface finish are two significant factors for evaluating the quality of products in additive manufacturing (AM). AM parts are fabricated layer by layer, which is quite different from traditional formative or subtractive methods. Despite rapid progress in additive manufacturing and associated optical metrology for quality control and in-situ monitoring, limited research has been conducted to investigate the reliability of 3D surface measurement data. The surface topologies scanned by multiple optical systems demonstrated significant differences due to varying sampling mechanisms, resolutions, system noises, etc. The 3D datasets should be trustworthy in order to extract parameters for quality assurance or feedback control from 3D surface measurements. In this paper, we set up new standards to evaluate the reliability of 3D surface measurement data and analyze the variation in the topographical profile. In this study, two non-contact optical methods based on Focus Variation Microscopy (FVM) and Structured Light System (SLS) were adopted to measure the surface topography of the target components. The two optical metrology systems generated two entirely different point cloud datasets. Statistical methods were applied to test the difference between the data obtained from the two systems. By using a data analytics approach for comparison, it was found that the surface roughness estimated from the point cloud data sets of FVM and SLS has no significant difference, though the point cloud data sets were completely different. This paper provides standard validation approach to evaluate the plausibility of metrology data from in-situ real-time surface analysis for process planning of AM.
X-ray microscopy enables multiscale high-resolution 3D imaging of plant cells, tissues, and organs
Capturing complete internal anatomies of plant organs and tissues within their relevant morphological context remains a key challenge in plant science. While plant growth and development are inherently multiscale, conventional light, fluorescence, and electron microscopy platforms are typically limited to imaging of plant microstructure from small flat samples that lack a direct spatial context to, and represent only a small portion of, the relevant plant macrostructures. We demonstrate technical advances with a lab-based X-ray microscope (XRM) that bridge the imaging gap by providing multiscale high-resolution three-dimensional (3D) volumes of intact plant samples from the cell to the whole plant level. Serial imaging of a single sample is shown to provide sub-micron 3D volumes co-registered with lower magnification scans for explicit contextual reference. High-quality 3D volume data from our enhanced methods facilitate sophisticated and effective computational segmentation. Advances in sample preparation make multimodal correlative imaging workflows possible, where a single resin-embedded plant sample is scanned via XRM to generate a 3D cell-level map, and then used to identify and zoom in on sub-cellular regions of interest for high-resolution scanning electron microscopy. In total, we present the methodologies for use of XRM in the multiscale and multimodal analysis of 3D plant features using numerous economically and scientifically important plant systems.
Li 7 P 2 S 8 Br 0.5 I 0.5 (LPSBI) solid state electrolyte by XPS
There have been increasing surface characterization studies of battery materials specifically in the context of before and after cell operation to determine any chemical changes. Therefore, providing reliable reference spectra of battery-related materials is important. In this paper, survey and high-energy resolution data are reported for the solid-state electrolyte Li 7 P 2 S 8 Br 0.5 I 0.5 (LPSBI), which has been synthesized and characterized at Pacific Northwest National Laboratory. The current data presents narrow scan regions of I 3d, I 4d, Br 3d, O 1s, P 2p, S 2p, and C 1s core level spectra as well as wide-scan survey data that was obtained using Al K a x-ray source with a Thermo Fisher Nexsa instrument.
3D imaging of magnetic domains in Nd 2 Fe 14 B using scanning hard X-ray nanotomography
Nanoscale structural and electronic heterogeneities are prevalent in condensed matter physics. Investigating these heterogeneities in 3D has become an important task for understanding material properties. To provide a tool to unravel the connection between nanoscale heterogeneity and macroscopic emergent properties in magnetic materials, scanning transmission X-ray microscopy (STXM) is combined with X-ray magnetic circular dichroism. A vector tomography algorithm has been developed to reconstruct the full 3D magnetic vector field without any prior noise assumptions or knowledge about the sample. Two tomographic scans around the vertical axis are acquired on single-crystalline Nd 2 Fe 14 B pillars tilted at two different angles, with 2D STXM projections recorded using a focused 120 nm X-ray beam with left and right circular polarization. Image alignment and iterative registration have been implemented based on the 2D STXM projections for the two tilts. Dichroic projections obtained from difference images are used for the tomographic reconstruction to obtain the 3D magnetization distribution at the nanoscale.
We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric Uncertainty
Deep learning has been successfully applied to the segmentation of 3D Computed Tomography (CT) scans. Establishing the credibility of these segmentations requires uncertainty quantification (UQ) to identify untrustworthy predictions. Recent UQ architectures include Monte Carlo dropout networks (MCDNs), which approximate deep Gaussian processes, and Bayesian neural networks (BNNs), which learn the distribution of the weight space. BNNs are advantageous over MCDNs for UQ but are thought to be computationally infeasible in high dimension, and neither architecture has produced interpretable geometric uncertainty maps. We propose a novel 3D Bayesian convolutional neural network (BCNN), the first deep learning method which generates statistically credible geometric uncertainty maps and scales for application to 3D data. We present experimental results on CT scans of graphite electrodes and laser-welded metals and show that our BCNN outperforms an MCDN in recent uncertainty metrics. The geometric uncertainty maps generated by our BCNN capture distributions of sigmoid values that are interpretable as confidence intervals, critical for applications that rely on deep learning for high-consequence decisions.
Modeling of carbon pellets disruption mitigation in an NSTX-U plasma
Single carbon pellet disruption mitigation simulations using M3D-C1 were conducted for an NSTX-U-like plasma to support the electromagnetic pellet injection concept (EPI). A carbon ablation model has been implemented in M3D-C1 and tested with available data. 2D simulations were conducted in order to estimate the amount of carbon needed to quench the plasma, finding that the content in a 1 mm radius vitreous carbon pellet (~3.2x10E20 atoms) would be enough if it is entirely ablated. 3D simulations were performed, scanning over pellet velocity and parallel thermal conductivity, as well as different injection directions and pellet concepts (solid pellets and shell pellets). The sensitivity of the thermal quench and other related quantities to these parameters has been evaluated. A 1 mm radius solid pellet only partially ablates at velocities of 300 m/s or higher, thus being unable to fully quench the plasma. To further enhance the ablation, approximations to an array of pellets and the shell pellet concept were also explored. 3D field line stochastization plays an important role in both quenching the center of the plasma and in heat flux losses, thus lowering the amount of carbon needed to mitigate the plasma when compared to the 2D case. This study constitutes an important step forward in `predict-first' simulations for disruption mitigation in NSTX-U and other devices, such as ITER.