Mode-locked vertical external cavity semiconductor lasers are a unique class of nonlinear dynamical systems driven far from equilibrium. We present a novel, to the best of our knowledge, experimental result, supported by rigorous microscopic simulations, of two coexisting mode-locked V-cavity configurations sourced by a common gain medium and operating as independent channels at angle controlled separated wavelengths. Microscopic simulations support pulses coincident on the common gain chip extracting photons from a nearby pair of coexisting kinetic holes burned in the carrier distributions.
Traditional methods of shielding fragile goods and human tissues from impact energy rely on isotropic foam materials. The mechanical properties of these foams are inferior to an emerging class of metamaterials called plate lattices, which have predominantly been fabricated in simple 2.5-dimensional geometries using conventional methods that constrain the feasible design space. In this work, additive manufacturing is used to relax these constraints and realize plate lattice metamaterials with nontrivial, locally varying geometry. The limitations of traditional computer-aided design tools are circumvented and allow the simulation of complex buckling and collapse behaviors without a manual meshing step. By validating these simulations against experimental data from tests on fabricated samples, sweeping exploration of the plate lattice design space is enabled. Numerical and experimental tests demonstrate plate lattices absorb up to six times more impact energy at equivalent densities relative to foams and shield objects from impacts ten times more energetic while transmitting equivalent peak stresses. In contrast to previous investigations of plate lattice metamaterials, designs with nonuniform geometric prebuckling in the out-of-plane direction is explored and showed that these designs exhibit 10% higher energy absorption efficiency on average and 25% higher in the highest-performing design.
The effect of doping concentration on the temperature performance of the novel split-well resonant-phonon (SWRP) terahertz quantum-cascade laser (THz QCL) scheme supporting a clean 4-level system design was analyzed using non-equilibrium Green’s functions (NEGF) calculations. Experimental research showed that increasing the doping concentration in these designs led to better results compared to the split-well direct-phonon (SWDP) design, which has a larger overlap between its active laser states and the doping profile. However, further improvement in the temperature performance was expected, which led us to assume there was an increased gain and line broadening when increasing the doping concentration despite the reduced overlap between the doped region and the active laser states. Through simulations based on NEGF calculations we were able to study the contribution of the different scattering mechanisms on the performance of these devices. We concluded that the main mechanism affecting the lasers’ temperature performance is electron-electron (e-e) scattering, which largely contributes to gain and line broadening. Interestingly, this scattering mechanism is independent of the doping location, making efforts to reduce overlap between the doped region and the active laser states less effective. Optimization of the e-e scattering thus could be reached only by fine tuning of the doping density in the devices. By uncovering the subtle relationship between doping density and e-e scattering strength, our study not only provides a comprehensive understanding of the underlying physics but also offers a strategic pathway for overcoming current limitations. This work is significant not only for its implications on specific devices but also for its potential to drive advancements in the entire THz QCL field, demonstrating the crucial role of e-e scattering in limiting temperature performance and providing essential knowledge for pushing THz QCLs to new temperature heights.
This project has 2 major thrusts and 2 minor tasks – One of the major ones is a scoping study for improving uranium isotopics by analyzing higher energy, lower yield U-235 gamma emissions. The second major one benefits past projects such as auto-enrichment, and peak-based analysis routines previously added to GADRAS-DRF [1]. The two minor tasks involve an in-person or remote GADRAS-DRF training for the IAEA, and characterizing detectors of interest.
Porous liquids (PLs), which are solvent-based systems that contain permanent porosity due to the incorporation of a solid porous host, are of significant interest for the capture of greenhouse gases, including CO2. Type 3 PLs formed by using metal-organic frameworks (MOFs) as the nanoporous host provide a high degree of chemical turnability for gas capture. However, pore aperture fluctuation, such as gate-opening in zeolitic imidazole framework (ZIF) MOFs, complicates the ability to keep the MOF pores available for gas adsorption. Therefore, an understanding of the solvent molecular size required to ensure exclusion from MOFs in ZIF-based Type 3 PLs is needed. Through a combined computational and experimental approach, the solvent-pore accessibility of exemplar MOF ZIF-8 was examined. Density functional theory (DFT) calculations identified that the lowest-energy solvent-ZIF interaction occurred at the pore aperture. Experimental density measurements of ZIF-8 dispersed in various-sized solvents showed that ZIF-8 adsorbed solvent molecules up to 2 Å larger than the crystallographic pore aperture. Density analysis of ZIF dispersions was further applied to a series of possible ZIF-based PLs, including ZIF-67, −69, −71(RHO), and −71(SOD), to examine the structure-property relationships governing solvent exclusion, which identified eight new ZIF-based Type 3 PL compositions. Solvent exclusion was driven by pore aperture expansion across all ZIFs, and the degree of expansion, as well as water exclusion, was influenced by ligand functionalization. Using these results, a design principle was formulated to guide the formation of future ZIF-based Type 3 PLs that ensures solvent-free pores and availability for gas adsorption.
Cytokines and acute-phase proteins are promising biomarkers for inflammatory disease. Despite its potential, early diagnosis based on these biomarkers remains challenging without technology enabling highly sensitive protein detection immediately after sample collection, because of the low abundance and short half-life of these proteins in bodily fluids. Enzyme-linked immunosorbent assay (ELISA) is a gold-standard method for such protein analysis, but it often requires labor-intensive and time-consuming sample handling and as well as a bulky benchtop platereader, limiting its utility in the clinical site. We developed a portable microfluidic immunoassay device capable of sensitive, quantitative, and high-throughput protein detection at point-of-need. The portable microfluidic system performs eight magnetic bead-based sandwich immunoassays from raw samples in 40 min. An innovative bead actuation strategy was incorporated into the system to automate multiple sample handling steps with minimal user intervention. The device enables quantitative protein analysis with picomolar sensitivity, as demonstrated using human samples spiked with interleukin-6 and C-reactive protein. The affinity-based assays are highly specific to the target without cross-reactivity. Therefore, we envision the reported device offering ultrasensitive and field-deployable immunoassay tests for timely and accurate clinical diagnosis.
The need for clean, renewable energy has driven the expansion of renewable energy generators, such as wind and solar. However, to achieve a robust and responsive electrical grid based on such inherently intermittent renewable energy sources, grid-scale energy storage is essential. The unmet need for this critical component has motivated extensive grid-scale battery research, especially exploring chemistries “beyond Li-ion”. Among others, molten sodium (Na) batteries, which date back to the 1960s with Na-S, have seen a strong revival, owing mostly to raw material abundance and the excellent electrochemical properties of Na metal. Recently, many groups have demonstrated important advances in battery chemistries, electrolytes, and interfaces to lower material and operating costs, enhance cyclability, and understand key mechanisms that drive failure in molten Na batteries. For widespread implementation of molten Na batteries, though, further optimization, cost reduction, and mechanistic insight is necessary. In this light, this work provides a brief history of mature molten Na technologies, a comprehensive review of recent progress, and explores possibilities for future advancements.
Metal-organic frameworks (MOFs) are a class of porous, crystalline materials that have been systematically developed for a broad range of applications. Incorporation of two or more metals into a single crystalline phase to generate heterometallic MOFs has been shown to lead to synergistic effects, in which the whole is oftentimes greater than the sum of its parts. Because geometric proximity is typically required for metals to function cooperatively, deciphering and controlling metal distributions in heterometallic MOFs is crucial to establish structure-function relationships. However, determination of short- and long-range metal distributions is nontrivial and requires the use of specialized characterization techniques. Advancements in the characterization of metal distributions and interactions at these length scales is key to rapid advancement and rational design of functional heterometallic MOFs. This perspective summarizes the state-of-the-art in the characterization of heterometallic MOFs, with a focus on techniques that allow metal distributions to be better understood. Using complementary analyses, in conjunction with computational methods, is critical as this field moves toward increasingly complex, multifunctional systems.
We report a comparative study of three rectifying gate metals, W, Pd, and Pt/Au, on ultrawide bandgap Al0.86Ga0.14N barrier/Al0.7Ga0.3N channel high electron mobility transistors for use in extreme temperatures. The transistors were electrically characterized from 30 to 600 °C in air. Of the three gate metals, the Pt/Au stack exhibited the smallest change in threshold voltage (0.15 V, or 9% change between the 30 and 600 °C values, and a maximum change of 42%), the highest on/off current ratio (1.5 × 106) at 600 °C, and a modest forward gate leakage current (0.39 mA/mm for a 3 V gate bias) at 600 °C. These favorable results showcase AlGaN channel high electron mobility transistors' ability to operate in extreme temperature environments.
Rothchild, Eric; Asta, Mark D.; Chrzan, Daryl C.; Kuner, Matthew C.
The Set of Small Ordered Structures (SSOS) approach is an ab initio technique for modelling random solid solutions in which many small structures are averaged so that their correlation functions match those of a desired composition. SSOS has been shown to be effective in reducing the cost of density functional theory calculations relative to other well-known techniques such as cluster expansions and special quasirandom structures for modelling solid solutions. Here in this work, we demonstrate that SSOS’s can be constructed using cells with only a subset of elements while still accurately modelling multi-component systems. Specifically, we show that small binary cells can effectively model two quinary high entropy alloys – NbTaTiHfZr and MoNbTaVW – accurately capturing properties such as formation energy, lattice parameters, elastic constants, and root-mean-square atomic displacements. Overall, this insight is useful for those looking to construct databases of such small structures for predicting the properties of multi-component solid solutions, as it greatly decreases the number of structures that needs to be considered.
A computational model of aluminum melting is proposed which captures both the thermal fluid-solid phase transition and the mechanical effects of oxidation. The model hybridizes ideas from smoothed particle hydrodynamics and bonded particle models to simulate both hydrodynamic flows and solid elasticity. Oxidation is represented by dynamically adding and deleting spring-like bonds between surface fluid particles to represent the formation and rupture of the oxide skin. Various complex systems are simulated to demonstrate the adaptability of the method and to illustrate the significant impact of skin properties on material flow. As a result, initial comparison to experiments of a melting aluminum cantilever highlights that the computational model can reproduce key qualitative features of aluminum relocation.
The SIERRA Low Mach Module: Fuego, henceforth referred to as Fuego, is the key element of the ASC fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Using MPMD coupling, Scefire and Nalu handle the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.
Presented in this document is a portion of the tests that exist in the Sierra Thermal/Fluids verification test suite. Each of these tests is run nightly with the Sierra/TF code suite and the results of the test checked under mesh refinement against the correct analytic result. For each of the tests presented in this document the test setup, derivation of the analytic solution, and comparison of the code results to the analytic solution is provided. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems.
The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.
The multi-harmonic balance method combined with numerical continuation provides an efficient framework to compute a family of time-periodic solutions, or response curves, for large-scale, nonlinear mechanical systems. The predictor and corrector steps repeatedly solve a sequence of linear systems that scale by the model size and number of harmonics in the assumed Fourier series approximation. In this paper, a novel Newton–Krylov iterative method is embedded within the multi-harmonic balance and continuation algorithm to efficiently compute the approximate solutions from the sequence of linear systems that arise during the prediction and correction steps. The method recycles, or reuses, both the preconditioner and the Krylov subspace generated by previous linear systems in the solution sequence. A delayed frequency preconditioner refactorizes the preconditioner only when the performance of the iterative solver deteriorates. The GCRO-DR iterative solver recycles a subset of harmonic Ritz vectors to initialize the solution subspace for the next linear system in the sequence. The performance of the iterative solver is demonstrated on two exemplars with contact-type nonlinearities and benchmarked against a direct solver with traditional Newton–Raphson iterations.
Heating of the surficial layer of the atmosphere often generates convective vortices, known as “dust devils” when they entrain visible debris. Convective vortices are common on both Earth and Mars, where they affect the climate via dust loading, contribute to wind erosion, impact the efficiency of photovoltaic systems, and potentially result in injury and property damage. However, long-duration terrestrial convective vortex activity records are rare. We have developed a high-precision and high-recall method to extract convective vortex signatures from infrasound microbarometer data streams. The techniques utilizes a wavelet-based detector to capture potential events and then a template matching system to extract the duration of the vortex. Since permanent and temporary infrasound sensors networks are present throughout the globe (many with open data), our method unlocks a vast new convective vortex dataset without requiring the deployment of specialized instrumentation. SIGNIFICANCE STATEMENT: Convective vortices, or “dust devils,” contribute to regional dust loading in Earth’s atmosphere. However, long-duration convective vortex activity records are rare. We came up with a way to autonomously detect the pressure signatures left by convective vortices striking low-frequency sound, or “infrasound,” sensors. Since permanent infrasound stations have been active for decades, our method has the potential to add ordersof-magnitude more events than previously catalogued.
A generalized closed-form equation for the shaded collector fraction in solar arrays on rolling or undulating terrain is provided for single-axis tracking and fixed-tilt systems. The equation accounts for different rotation angles between the shaded and shading trackers, cross-axis slope between the two trackers, and offset between the collector plane and axis of rotation. The validity of the equation is demonstrated through comparison with numerical ray-tracing simulations and remaining minor sources of error are quantified. Additionally, a simple procedure to determine backtracking rotations for each row in an array installed on the rolling terrain (varying in the direction perpendicular to the tracker axes) is provided. The backtracking equation accounts for a desired shaded fraction (including complete shade avoidance) as well as an axis-collector offset. Test cases are provided to facilitate implementation of these equations.
During fracture amorphous oxides exhibit irreversible processes, including inelastic and nonrecoverable relaxation effects in the process zone surrounding the crack tip. Here, classical molecular dynamics simulations were used with a reactive forcefield to evaluate inelastic relaxation processes in five amorphous sodium silicate compositions. Overall, the 20% Na2O-SiO2(NS20) composition exhibited the most inelastic relaxation, followed by the 15% Na2O-SiO2(NS15) composition, the 25% Na2O-SiO2(NS25) composition, and finally the 10% (NS10) and 30% (NS30) Na2O-SiO2 compositions. Coordination analysis of the Na+ ions identified that during inelastic relaxation the Na+ ions were increasingly coordinated by nonbridging oxygens (NBOs) for the NS10 and NS15 compositions, which was supported by radial analysis of the O-Na-O bond angles surrounding the crack tip. Across the sodium silicate compositional range, two different inelastic relaxation mechanism were identified based on the amount of bridging oxygens (BOs) and NBOs in the Na+ ion coordination shell. At lower (NS10) and higher (NS30) sodium compositions, the entire structured relaxed toward the crack tip. In contrast at intermediate sodium concentrations (NS20) the Na+ ion migrates toward the crack tip separately from the network structure. By developing a fundamental understanding of how modified silica systems respond to static stress fields, we will be able to predict how varying amorphous silicate systems exhibit slow crack growth.
The complex nature of manufacturing processes stipulates electrodes to possess high variability with increased heterogeneity during production. X-ray computed tomography imaging has proved to be critical in visualizing the complicated stochastic particle distribution of as-manufactured electrodes in lithium-ion batteries. However, accurate prediction of their electrochemical performance necessitates precise evaluation of kinetic and transport properties from real electrodes. Image segmentation that characterizes voxels to particle/pore phase is often meticulous and fraught with subjectivity owing to a myriad of unconstrained choices and filter algorithms. We utilize a Bayesian convolutional neural network to tackle segmentation subjectivity and quantify its pertinent uncertainties. Otsu inter-variance and Blind/Referenceless Imaging Spatial Quality Evaluator are used to assess the relative image quality of grayscale tomograms, thus evaluating the uncertainty in the derived microstructural attributes. We analyze how image uncertainty is correlated with the uncertainties and magnitude of kinetic and transport properties of an electrode, further identifying pathways of uncertainty propagation within microstructural attributes. The coupled effect of spatial heterogeneity and microstructural anisotropy on the uncertainty quantification of transport parameters is also understood. This work demonstrates a novel methodology to extract microstructural descriptors from real electrode images through quantification of associated uncertainties and discerning the relative strength of their propagation, thus facilitating feedback to manufacturing processes from accurate image based electrochemical simulations.
Current nuclear facility emergency planning zones (EPZs) are based on outdated distance-based criteria, predating comprehensive dose and risk-informed frameworks. Recent advancements in simulation tools have permitted the development of site-specific, dose, and risk-based consequence-driven assessment frameworks. This study investigated the computation of advanced reactor (AR) EPZs using two atmospheric dispersion models: a straight-line Gaussian plume model (GPM) and a semi-Lagrangian Particle in Cell (PIC). Two case studies were conducted: (1) benchmarking the NRC SOARCA study for the Peach Bottom Nuclear Generating Station and (2) analyzing an advanced INL Heat Pipe Design A microreactor's end-of-cycle inventory. The dose criteria for both cases were 10 mSv at mean weather conditions and 50 mSv at 95th percentile weather conditions at 96 h post-release. Results demonstrated that GPM and PIC estimated similar mean peak dose levels for large boiling water reactors in the farfield case, placing EPZ limits beyond current regulations. For ARs with source terms remaining in the nearfield, PIC modeling without specific nearfield considerations could result in excessively high doses and inaccurate EPZ designations. PIC dispersion demonstrated an order of magnitude higher estimate of nearfield inhalation dose contribution when compared to GPM results. Both models significantly reduced EPZ sizing within the nearfield. Thus, reductions in the AR source term may eliminate the need for a separate EPZ.
Ground heat flux (G0) is a key component of the land-surface energy balance of high-latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming, G0 is sparsely measured and not well represented in the outputs of global scale model simulation. In this study, an analytical heat transfer model is tested to reconstruct G0 across seasons using soil temperature series from field measurements, Global Climate Model, and climate reanalysis outputs. The probability density functions of ground heat flux and of model parameters are inferred using available G0 data (measured or modeled) for snow-free period as a reference. When observed G0 is not available, a numerical model is applied using estimates of surface heat flux (dependent on parameters) as the top boundary condition. These estimates (and thus the corresponding parameters) are verified by comparing the distributions of simulated and measured soil temperature at several depths. Aided by state-of-the-art uncertainty quantification methods, the developed G0 reconstruction approach provides novel means for assessing the probabilistic structure of the ground heat flux for regional permafrost change studies.
Magnetized Liner Inertial Fusion experiments have been performed at the Z facility at Sandia National Laboratories. These experiments use deuterium fuel, which produces 2.45 MeV neutrons on reaching thermonuclear conditions. To study the spatial structure of neutron production, the one-dimensional imager of neutrons diagnostic was fielded to record axial resolved neutron images. In this diagnostic, neutrons passing through a rolled edge aperture form an image on a CR-39-based solid state nuclear track detector. Here, we present a modified generalized expectation-maximization algorithm to reconstruct an axial neutron emission profile of the stagnated fusion plasma. We validate the approach by comparing the reconstructed neutron emission profile to an x-ray emission profile provided by a time-integrated pinhole camera.
Laccases from white-rot fungi catalyze lignin depolymerization, a critical first step to upgrading lignin to valuable biodiesel fuels and chemicals. In this study, a wildtype laccase from the basidiomycete Fomitiporia mediterranea (Fom_lac) and a variant engineered to have a carbohydrate-binding module (Fom_CBM) were studied for their ability to catalyze cleavage of β-O-4′ ether and C–C bonds in phenolic and non-phenolic lignin dimers using a nanostructure-initiator mass spectrometry-based assay. Fom_lac and Fom_CBM catalyze β-O-4′ ether and C–C bond breaking, with higher activity under acidic conditions (pH < 6). The potential of Fom_lac and Fom_CBM to enhance saccharification yields from untreated and ionic liquid pretreated pine was also investigated. Adding Fom_CBM to mixtures of cellulases and hemicellulases improved sugar yields by 140% on untreated pine and 32% on cholinium lysinate pretreated pine when compared to the inclusion of Fom_lac to the same mixtures. Adding either Fom_lac or Fom_CBM to mixtures of cellulases and hemicellulases effectively accelerates enzymatic hydrolysis, demonstrating its potential applications for lignocellulose valorization. We postulate that additional increases in sugar yields for the Fom_CBM enzyme mixtures were due to Fom_CBM being brought more proximal to lignin through binding to either cellulose or lignin itself.