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At least 91 records · Page 5

Influence of Initial fabric and water-wetting on particle fracture and force chain evolution in natural silica sand

Particle fracture has a significant influence on the engineering behavior of granular materials. However, the combined influence of the initial fabric and wetting on particle fracture and force chain evolution in granular materials, particularly in sands, remains insufficiently explored in the current literature. Here, in this paper, one-dimensional (1D) confined compression experiments were conducted on dry and wet specimens, and particle-level fracture was captured using three-dimensional (3D) in-situ Synchrotron Micro-Computed Tomography (SMT). A quantitative assessment of particle fracture revealed that wet specimens, which have disturbed fabric, exhibited a higher fracture percentage in comparison to dry specimens. Complementary 3D finite element (FE) simulations were performed using dry and wet (only solid fabric was considered and the influence of pore water is not considered) sand assemblies to assess interparticle contact forces and particle-scale stress distributions within the specimens. Force chain analysis was subsequently conducted, encompassing quantification of interparticle forces, characterization of force network structures, and monitoring the dynamic evolution of force chains under different strain levels. The results show that the specimens with disturbed fabric led to a more dynamic and less persistent force network, more fabric instability, and thus more reorganization of force chain structures. In addition, the frequent rearrangement of the force network in the presence of water (with reduced inter-particle contact friction) likely exacerbates localized stress concentrations, promoting failure in previously unengaged or weakly connected particles. The results reported in this paper offer a new insight into how the initial fabric and wetting cause different fracture behavior. The findings can also pave the way for more in-depth future investigations into the mechanics governing particle fracture in granular assemblies.

Finite element analysis↗

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Displacement driven balancing of a diamond turning machine flycutter

The spindle balancing operation is critical to the performance of precision lathes and should be conducted anytime the configuration of the spindle or its tooling is modified such that an unbalanced condition may occur. Within the machine tool community, accelerometers are typically used as the feedback device during the balancing operation. At Lawrence Livermore National Laboratory (LLNL), we have nearly 40 years of history using displacement sensors, such as capacitance gauges, in place of accelerometers when balancing precision spindles. The process of balancing a precision machine spindle using displacement sensors is presented in the context of two work examples. In this case, the details of the one-dimensional balancing operation performed after replacing a flycutter on the spindles of two unique large optic diamond turning machines is discussed. The pros and cons of accelerometer driven balancing and displacement driven balancing are also presented. In the accelerometer context, the level of balance achieved for our work example is less than 100 micro-g or a total indicator reading (TIR) of 1.6 µm. The process of balancing has been enhanced over the years as advances have been made in software, data acquisition systems, and instrumentation. The balancing system is described including details about instrumentation, set-up, how phase and spindle structure stiffness is calculated, and how the LLNL developed software that guides the user through the process by suggesting corrective action.

42 ENGINEERING↗

Understanding the limitations and potential of micro tensile testing of tungsten and needs for crystal plasticity modelling

Tungsten is the leading plasma facing material candidate due to its exceptional properties. Understanding the response to neutron irradiation is crucial for the lifetime evaluation of tungsten. The limited space in nuclear reactors and the high levels of radioactivity of the specimens after irradiation are significant barriers to accurately measuring the mechanical properties after neutron irradiation. Testing of micro tensile specimens is one approach to reduce the total amount of irradiated material needed for a set of mechanical testing experiments. However, micro samples are not necessarily measuring the bulk material properties, as size effects produce higher measured mechanical properties than is observed in engineering size counterparts. Determining the minimal sample size for reliable bulk property measurement, combined with modeling efforts, is essential. We conducted room temperature tensile tests on tungsten micro tensile specimens fabricated with focused ion beam, plasma focused ion beam and femto-second laser ablation system to dimension of 2×2×7?µm³, 7×7×18?µm³, and 80×100×233?µm³ (width×thickness×gauge-length), respectively. Elevated tensile testing was performed up to 475°C on 5×5×18?µm³ specimens fabricated with focused ion beam. The smallest specimens exhibited a high degree of ductility and strength, whereas the largest specimens demonstrated behavior akin to bulk tungsten. To investigate the effects introduced by the micro specimen fabrication processes and to obtain the necessary bulk dislocation density for the crystal plasticity model, we employed X-ray diffraction depth profiling. This measurement was performed using different X-ray sources with varying penetration depths. Finally, the potential and limitations of micro mechanical tests for tungsten will be discussed.

36 - MATERIALS SCIENCE↗

Reaching the potential of electron diffraction

Microcrystal electron diffraction (MicroED) is an emerging structural technique in which submicron crystals are used to generate diffraction data for structural studies. Structures allow for the study of molecular-level architecture and drive hypotheses about modes of action, mechanisms, dynamics, and interactions with other molecules. Combining cryoelectron microscopy (cryo-EM) instrumentation with crystallographic techniques, MicroED has led to three-dimensional structural models of small molecules, peptides, and proteins and has generated tremendous interest due to its ability to use vanishingly small crystals. In this perspective, we describe the current state of the field for MicroED methodologies, including making and detecting crystals of the appropriate size for the technique, as well as ways to best handle and characterize these crystals. Our perspective provides insight into ways to unlock the full range of potential for MicroED to access previously intractable samples and describes areas of future development.

3D ED↗

The role of micro-inertia on the shock structure in porous metals

The behavior of porous materials under shock loading is a multi-scale problem bridging orders of magnitude across the macroscale geometry and the microscale pores. Under static loading, this problem is well understood, relating mechanisms of pore closure and crushing to the equivalent macroscale models. The dynamic response of porous solids under shock loading is related to the effects of viscoplasticity and micro-acceleration fields around the void boundaries. The significance of the micro-inertia effects in modeling the dynamic behavior of porous materials remains an open question. In this work, an experimental investigation on closed-cell porous aluminum with small porosity provides the evidence for the first time of micro-inertia’s fundamental role in describing the shock structure in these materials. Materials with different levels of porosity were manufactured using a modified process of additive manufacturing to achieve a mean pore size below 50$\mu$m. Plate impact experiments on porous aluminum samples were conducted at pressures in the range of 2 to 11 GPa. The structure of the steady shock was characterized as a function of porosity and shown to validate behavior revealed by an analytical approach (Czarnota et al. [J. Mech. Phys. Solids 107 (2017)]), highlighting the fundamental role of micro-inertia effects in such cases.

36 MATERIALS SCIENCE↗

Uncertainty quantification of the convolutional neural networks on permeability estimation from micro-CT scanned sandstone and carbonate rock images

Rock permeability is one of the most crucial properties affecting subsurface fluid flow behaviors. To accurately and robustly estimate the permeability, Digital Rock Physics, including micro-CT scanning technology and direct flow simulations on scanned images, has prevailed in recent years. Besides, machine learning techniques such as convolutional neural networks (CNNs) have been widely adopted and achieved success in permeability estimations directly from rock images. However, existing ML methods used for permeability estimation from rock images lack uncertainty quantification that causes unreliable predictions and overconfident estimations on out-of-distribution (OOD) samples. Here, in this work, we propose a PI3NN-CNN framework to address this problem. PI3NN-CNN consists of a CNN model for absolute permeability estimation and a PI3NN method to quantify the estimation uncertainty. It is able to quantify the uncertainty for in-distribution (InD) data with a desired confidence level, and identify OOD samples to avoid overconfident predictions. We demonstrate the method using micro-CT scanned images from two sandstone and two carbonate rocks. We found that PI3NN-CNN generates accurate predictions for InD samples, while producing high-quality prediction uncertainties regardless of the prediction accuracy. Meanwhile, PI3NN-CNN identifies OOD samples using its special network initialization scheme. The unique feature of PI3NN-CNN makes it applicable to more complex real-world image-based data for robust learning and predictions without overconfident estimations when the ground-truth information is unavailable.

58 GEOSCIENCES↗

Efficiency cliff in scaling InGaN light-emitting diodes down to submicron

The top-down submicron fabrication of blue-emitting light-emitting diodes on Qromis Substrate Technology substrates is reported. Light-emitting diodes with mesa sizes as small as 250 × 250 nm 2 show ideal forward voltage and low leakage current density. It is observed that sidewall treatment and passivation methods used in micro-light-emitting diodes (2–20 μ m) do not lead to the same level of sidewall recombination suppression for submicron ones (< 1 μ m), as evidenced by a ∼70% decrease in peak external quantum efficiencies when mesa sizes are scaled from 2 μ m down to 250 nm. This is attributed to the lateral carrier diffusion being comparable to the mesa size, regardless of the sidewall passivation and recovery. The results call for rethinking the impact of sidewalls in emerging top-down fabricated (sub)micrometer-light-emitting diodes.

42 ENGINEERING↗

Development of a Hybrid Single/Two-Phase Capillary-Based Micro-Cooler using Copper Inverse Opals Wick with Silicon 3D Manifold for High-Heat-Flux Cooling Application

Previously, we reported two-phase capillary-based cooling using narrow (200 to 1000 ..mu..m) heater bridge copper inverse opal (CIO) wicks with heat flux level of 1400 Wcm -2 and superheat ~ 10 degrees C. Here, we demonstrate the area scaling of the proposed technology to a large-area micro-cooler for high-heat-flux cooling of microprocessors and power electronics. We developed a hybrid single/two-phase micro-cooler that relies on capillary-wicking in a 25-..mu..m-thick CIO with an open silicon microchannel 3D-manifold for liquid delivery and vapor extraction, achieving a high heat flux ~ 400 Wcm -2 over a heated area of 10 x 10 mm 2 . For a range of inlet water flowrates from 5 to 60 g(min) -1 , we achieved total thermal resistances and vapor qualities of 0.68 cm 2 degrees CW -1 to 0.2 cm 2 degrees CW -1 and 0.55 to 0.12, respectively. The flowrates are 10x smaller than those of conventional single- or two-phase microchannel cooling technology. The corresponding two-phase thermal resistances ranges from 0.05 to 0.02 cm 2 degrees CW -1 with temperature superheat of 8 to 6 degrees C, respectively. While the overall performance of the large-area (10 x 10 mm 2 ) capillary-based micro-cooler degraded compared to the previous demonstration of the technology for a heated area of 5 x 5 mm 2 , however, preliminary CFD modeling indicates that an improved manifold design will be able to achieve comparable performance.

capillary flow↗

3D pore structure reconstruction of fluff region in top of EBR-II irradiated fuel by X-ray micro-computed tomography

Metallic fuels comprised of U-Zr binary and U-Pu-Zr ternary alloys are a promising fuel candidate for sodium-cooled fast reactors and possess many advantages over ceramic fuels such as higher uranium density and improved thermal conductivity. Fluff is a highly porous structure forming at the top of metallic fuel slugs during irradiation and was extensively observed in past sodium-cooled fast reactor (SFR) experiments such as Idaho National Laboratory’s Experimental Breeder Reactor II (EBR-II). Previous investigations have shown that fluff is rich in fissile atoms and hence could have neutronics implications, but its formation mechanisms are not understood. In this work, two cube-shaped lift outs were taken from the fluff and bulk fuel regions of a high burnup U-19Pu-10Zr composition EBR-II fuel slug and characterized by micro computed tomography (Micro-CT) and energy dispersive x-ray spectroscopy (EDS). This was used to characterize differences in microscale porosity and composition between fluff and bulk fuel, and to support or oppose postulated fluff formation mechanisms. Surface EDS showed minimal differences between the elemental compositions of the fluff and fuel cubes. However, three-dimensional (3D) pore analysis from the tomography scans showed significant differences between the fluff and fuel cube pore size distributions at the microscale level. The high porosity and irregular pore distribution seen in macroscale fluff was also present within the micro-scale fluff cube, having a much higher porosity than the fuel cube which was concentrated in a few large pore networks. In conclusion, these results indicate support for a creep driven mechanism of fluff formation.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of a Hybrid Single/Two-Phase Capillary-Based Micro-Cooler Using Copper Inverse Opals Wick with Silicon 3D Manifold for High-Heat-Flux Cooling Application: Preprint

Previously, two-phase capillary-based cooling from narrow (200-1,000 micrometer) heater-bridge copper inverse opal (CIO) wicks with heat flux levels exceeding 1,400 watts per square cm with a low superheat of approximately 10 degrees C was demonstrated. Here, we demonstrate the area scaling of the proposed technology to large-area micro-cooler for the high-heat-flux cooling of microprocessors and power electronics. We developed a hybrid single/two-phase micro-cooler that relies on capillary wicking in 25-micrometer-thick CIOs with an open channel silicon 3D-manifold for liquid delivery and vapor extraction, to achieve a high heat flux of approximately 400 watts per square cm over a heated area of 1 square cm. For the range of inlet water (21 degrees C water temperature) flowrates from 5 to 60 mL per min, we achieved total thermal resistances and vapor qualities of 0.68-0.2 square cm Kelvin per watt and 0.55-0.12, respectively. The high heat flux levels are achieved with flowrates that are 10 times smaller than conventional single- or two-phase microchannel cooling technology. The corresponding two-phase thermal resistances are in the range of 0.05 to 0.02 square cm Kelvin per watt with temperature superheat of 8 to 6 degrees C. While the overall performance of the large-area (10 by 10 square millimeter) capillary-based micro-cooler degraded compared to previous demonstration of the technology for a heated area of 5 by 5 square millimeter, preliminary computational fluid dynamics (CFD) modeling indicates that an improved manifold design will be able to achieve comparable performance.

capillary flow↗

Elastic Properties and Deformation Mechanisms in the van der Waals Single-Crystalline Indium Selenide

The bulk van der Waals (vdW) single-crystalline indium selenide (β-InSe) displays exceptional plasticity in a layered crystalline form at both micro- and macroscale. However, the nanoscale origin of plasticity remains unclear. Herein, an atomic-level study on the deformation mechanisms of InSe by using first-principles calculations is reported. Remarkable anisotropic elasticity is observed in the vdW InSe layered crystal, and the stiffness is dramatically softened because of the vdW gap in the layered structure. The simulations capture the distinct fracture modes in the uniaxial tensile deformation, depending on the loading directions—brittle fracture in the [100] and [110] directions while ductile failure in the [001] direction. The InSe layered crystal structure exhibits superplastic deformability under uniaxial compression. Different transition pathways, including interlayer tangling, amorphization, and cross-linking, are tracked along respective deformation directions. The unprecedented plasticity of InSe layered crystals can be attributed to the phase transition coupled with interlayer gliding and cross-layer dislocation slipping. Here, this study deepens our understanding of the deformation mechanisms of layered materials at the atomistic level and provides insights into tailoring material properties for low-dimensional material design based on its deformation mechanisms.

2D materials↗

Dynamics of N 2 O in vicinity of plant residues: a microsensor approach

Plant residues decomposing within the soil matrix are known to serve as hotspots of N 2 O production. However, the lack of technical tools for microscale in-situ N 2 O measurements limits understanding of hotspot functioning. Our aim was to assess performance of microsensor technology for evaluating the temporal patterns of N 2 O production in immediate vicinity to decomposing plant residues. We incorporated intact switchgrass leaves and roots into soil matrix and monitored O 2 depletion and N 2 O production using electrochemical microsensors along with N 2 O emission from the soil. We also measured residue’s water absorption and b-glucosidase activity on the surface of the residue - the characteristics related to microenvironmental conditions and biological activity near the residue. N 2 O production in the vicinity of switchgrass residues began within 0–12 h after the wetting, reached peak at ~0.6 day and decreased by day 2. N 2 O was higher near leaf than near root residues due to greater leaf N contents and water absorption by the leaves. However, N 2 O production near the roots started sooner than near the leaves, in part due to high initial enzyme levels on root surfaces. Electrochemical microsensor is a useful tool for in-situ micro-scale N 2 O monitoring in immediate vicinity of soil incorporated plant residues. Monitoring provided valuable information on N 2 O production near leaves and roots, its temporal dynamic, and the factors affecting it. The N 2 O production from residues measured by microsensors was consistent with the N 2 O emission from the whole soil, demonstrating the validity of the microsensors for N 2 O hotspot studies.

59 BASIC BIOLOGICAL SCIENCES↗

Analysis of the Value Proposition of High-Efficiency, Multijunction Solar Modules for Residential Rooftop Installations

Utilizing detailed bottom-up models, we analyze the potential markets for high-efficiency photovoltaic modules in the United States. We first estimate the fraction of area-constrained residential rooftops that could benefit from increasing the availability of high-efficiency systems. We then model the impact of efficiency on installed system costs in these area-constrained scenarios. Finally, we explore the value proposition of high-efficiency, fixed-tilt micro-concentrator photovoltaic modules in a series of case studies of residential customers, modeling the levelized cost of energy, payback period, and annual bill savings. We find that efficiency can provide significant savings in installed system cost and improve value to the solar system owner. The improvement in value depends on location and the size of the rooftop, as well as the ability of a given technology to collect diffuse light and achieve low module costs.

14 SOLAR ENERGY↗

Modeling and Design of Micro Flux Monitors for Neutron Fluence Measurements

Measuring neutron flux is critical to understanding the characteristics of nuclear reactors and can provide information on the energy spectrum, total neutron fluence, and operational history of a facility. Such measurements are typically performed by irradiating high-purity materials in an operating reactor for a known length of time. By measuring and identifying activation products in the irradiated materials and referencing the energy-dependent cross section of each isotope, the neutron energy spectrum and total fluence can be determined. Historical techniques use a variety of small, individually pressed foils or wires for dosimeter devices, which can result in excessively high levels of radioactivity and complications in handling after irradiation. The present work describes a new neutron dosimetry concept, named the micro flux monitor, that uses semiconductor device fabrication processes to deposit thin films of flux monitoring materials in precise geometries onto a SiC wafer. This approach allows multiple dosimetry materials to be located on a single device, simplifying irradiation and subsequent analysis. The geometry, and therefore mass, of each material can be custom-tailored for a specific application—considering the expected neutron flux, duration of irradiation, and device retrieval time of a facility. Additionally, hundreds of identical dosimetry monitors can be produced simultaneously, reducing fabrication costs. Finally, the extremely thin metal dimensions of these devices could improve the fidelity of neutron fluence measurements by reducing neutron self-shielding and gamma self-attenuation effects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Origin of structural degradation in Li-rich layered oxide cathode

Li- and Mn-rich (LMR) cathode materials that utilize both cation and anion redox can yield substantial increases in battery energy density 1,2,3 . However, although voltage decay issues cause continuous energy loss and impede commercialization, the prerequisite driving force for this phenomenon remains a mystery 3,4,5,6 In this work, with in situ nanoscale sensitive coherent X-ray diffraction imaging techniques, we reveal that nanostrain and lattice displacement accumulate continuously during operation of the cell. Evidence shows that this effect is the driving force for both structure degradation and oxygen loss, which trigger the well-known rapid voltage decay in LMR cathodes. By carrying out micro- to macro-length characterizations that span atomic structure, the primary particle, multiparticle and electrode levels, we demonstrate that the heterogeneous nature of LMR cathodes inevitably causes pernicious phase displacement/strain, which cannot be eliminated by conventional doping or coating methods. We therefore propose mesostructural design as a strategy to mitigate lattice displacement and inhomogeneous electrochemical/structural evolutions, thereby achieving stable voltage and capacity profiles. These findings highlight the significance of lattice strain/displacement in causing voltage decay and will inspire a wave of efforts to unlock the potential of the broad-scale commercialization of LMR cathode materials.

25 ENERGY STORAGE↗

A Superconducting Micro-Magnetometer for Quantum Vortex in Superconducting Nanoflakes

Superconducting quantum interferometer device (SQUID) plays a key role in understanding electromagnetic properties and emergent phenomena in quantum materials. The technological appeal of SQUID is that its detection accuracy for the electromagnetic signal can precisely reach the quantum level of a single magnetic flux. However, conventional SQUID techniques normally can only be applied to a bulky sample and do not have the capability to probe the magnetic properties of micro-scale samples with small magnetic signals. Here, in this paper, it is demonstrated that, based on a specially designed superconducting nano-hole array, the contactless detection of magnetic properties and quantized vortices in micro-sized superconducting nanoflakes is realized. An anomalous hysteresis loop and a suppression of Little–Parks oscillation are observed in the detected magnetoresistance signal, which originates from the disordered distribution of the pinned vortices in Bi 2 Sr 2 CaCu 2 O 8+δ . Therefore, the density of pinning centers of the quantized vortices on such micro-sized superconducting samples can be quantitatively evaluated, which is technically inaccessible for conventional SQUID detection. The superconducting micro-magnetometer provides a new approach to exploring mesoscopic electromagnetic phenomena of quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

MAPredict: Static Analysis Driven Memory Access Prediction Framework for Modern CPUs

Application memory access patterns are crucial in deciding how much traffic is served by the cache and forwarded to the dynamic random-access memory (DRAM). However, predicting such memory traffic is difficult because of the interplay of prefetchers, compilers, parallel execution, and innovations in manufacturer-specific micro-architectures. This research introduced MAPredict, a static analysis-driven framework that addresses these challenges to predict last-level cache (LLC)-DRAM traffic. By exploring and analyzing the behavior of modern Intel processors, MAPredict formulates cache-aware analytical models. MAPredict invokes these models to predict LLC-DRAM traffic by combining the application model, machine model, and user-provided hints to capture dynamic information. MAPredict successfully predicts LLC-DRAM traffic for different regular access patterns and provides the means to combine static and empirical observations for irregular access patterns. Evaluating 130 workloads from six applications on recent Intel micro-architectures, MAPredict yielded an average accuracy of 99% for streaming, 91% for strided, and 92% for stencil patterns. By coupling static and empirical methods, up to 97% average accuracy was obtained for random access patterns on different micro-architectures.

Monil, M. A. H.↗