The apparent velocity measured by an interferometric surface velocimeter is a function of both the surface velocity and the time derivative of the refractive index along the measurement path. We employed this dual sensitivity to simultaneously measure km/s surface velocities and 1018 cm−3 average plasma densities with combined VISAR (velocity interferometer system for any reflector) and PDV (photonic Doppler velocimetry) measurements in experiments performed on the Z Pulsed Power Facility. We detail the governing equations, associated assumptions, and analysis specifics and show that the surface velocity can be extracted without knowledge of the specific plasma density profile.
This report investigates topics of interest with regard to Nuclear Power Plants (NPPs) utilizing flexible plant operations and generation (FPOG). Previous reports have identified the risk associated with co-located hydrogen generation facilities. This report evaluates special topics with regard to co-location of both hydrogen and syngas production facilities. A literature review was conducted to evaluate overpressure mitigation techniques that may be available to the NPP to reduce the consequence of an overpressure event. Also, the overpressure consequence of a catastrophic hydrogen storage tank failure event was analyzed. A comparison of the similarities and differences between the methodology utilized in HyRAM+ and Regulatory Guide 1.91 (R.G. 1.91) was performed for overpressure analysis. Also, the trinitrotoluene (TNT) equivalency methodology was utilized to evaluate an overpressure event at a Syngas production facility.
The use of structural mechanics models during the design process often leads to the development of models of varying fidelity. Often low-fidelity models are efficient to simulate but lack accuracy, while the high-fidelity counterparts are accurate with less efficiency. This paper presents a multifidelity surrogate modeling approach that combines the accuracy of a high-fidelity finite element model with the efficiency of a low-fidelity model to train an even faster surrogate model that parameterizes the design space of interest. The objective of these models is to predict the nonlinear frequency backbone curves of the Tribomechadynamics research challenge benchmark structure which exhibits simultaneous nonlinearities from frictional contact and geometric nonlinearity. The surrogate model consists of an ensemble of neural networks that learn the mapping between low and high-fidelity data through nonlinear transformations. Bayesian neural networks are used to assess the surrogate model’s uncertainty. Once trained, the multifidelity neural network is used to perform sensitivity analysis to assess the influence of the design parameters on the predicted backbone curves. Additionally, Bayesian calibration is performed to update the input parameter distributions to correlate the model parameters to the collection of experimentally measured backbone curves.
In this research, artificial intelligence and machine learning (ML) methods are used to search an uncertain parameter space more efficiently for the most important inputs with respect to response sensitivities. These methods are applied to the Extremely Low Probability of Rupture (xLPR) probabilistic fracture mechanics code used at the U.S. Nuclear Regulatory Commission (NRC) in support of nuclear regulatory research. This report documents two separate but related sub-tasks: (1) ranking important uncertain input features with respect to target outputs, determined by convergence in confidence intervals for increasing sample sizes using simple random sampling; and (2) implementation of a reduced-order surrogate model for fast, approximate sample generation. Unoptimized readily available off-the-shelf ML models were used in both sub-tasks.
Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the western system coordinating council 9-bus test system using synthetic multi-device outage scenarios.
This is an addendum to the Sierra/SolidMechanics 5.20 User’s Guide that documents additional capabilities available only in alternate versions of the Sierra/SolidMechanics (Sierra/SM) code. These alternate versions are enhanced to provide capabilities that are regulated under the U.S. Department of State’s International Traffic in Arms Regulations (ITAR) export control rules. The ITAR regulated codes are only distributed to entities that comply with the ITAR export control requirements. The ITAR enhancements to Sierra/SM include material models with an energy-dependent pressure response (appropriate for very large deformations and strain rates) and capabilities for blast modeling. This document is an addendum only; the standard Sierra/SolidMechanics 5.20 User’s Guide should be referenced for most general descriptions of code capability and use.
Presented in this document are tests that exist in the Sierra/SolidMechanics example problem suite, which is a subset of the Sierra/SM regression and performance test suite. These examples showcase common and advanced code capabilities. A wide variety of other regression and verification tests exist in the Sierra/SM test suite that are not included in this manual.
Presented in this document are tests that exist in the Sierra/SolidMechanics example problem suite, which is a subset of the Sierra/SM regression and performance test suite. These examples showcase common and advanced code capabilities. A wide variety of other regression and verification tests exist in the Sierra/SM test suite that are not included in this manual.
We describe a data-driven, multiscale technique to model reactive wetting of a silver–aluminum alloy on a Kovar™ (Fe-Ni-Co alloy) surface. We employ molecular dynamics simulations to elucidate the dependence of surface tension and wetting angle on the drop's composition and temperature. A design of computational experiments is used to efficiently generate training data of surface tension and wetting angle from a limited number of molecular dynamics simulations. The simulation results are used to parameterize models of the material's wetting properties and compute the uncertainty in the models due to limited data. The data-driven models are incorporated into an engineering-scale (continuum) model of a silver–aluminum sessile drop on a Kovar™ substrate. Model predictions of the wetting angle are compared with experiments of pure silver spreading on Kovar™ to quantify the model-form errors introduced by the limited training data versus the simplifications inherent in the molecular dynamics simulations. The paper presents innovations in the determination of “convergence” of noisy MD simulations before they are used to extract the wetting angle and surface tension, and the construction of their models which approximate physio-chemical processes that are left unresolved by the engineering-scale model. Together, these constitute a multiscale approach that integrates molecular-scale information into continuum scale models.
Kim, Iltai I.; Lie, Yang; Park, Jaesung; Kim, Hyun J.; Kim, Hong C.; Yoon, Hongkyu
We show that the reflection interference fringe (RIF) is formed on a screen far away from the microdroplets placed on a prism-based substrate, which have low contact angles and thin droplet heights, caused by the dual convex-concave profile of the droplet, not a pure convex profile. The geometric formulation shows that the interference fringes are caused by the optical path difference when the reflected rays from the upper convex profile at the droplet-air interface interfere with reflection from the lower concave profile at oblique angles lower than the critical angle. Analytic solutions are obtained for the droplet height and the contact angle out of the fringe number and the fringe radius in RIF from the geometric formulation. Furthermore, the ray tracing simulation is conducted using the custom-designed code. The geometric formulation and the ray tracing show excellent agreement with the experimental observation in the relation between the droplet height and the fringe number and the relation between the contact angle and the fringe radius. This study is remarkable as the droplet's dual profile cannot be easily observed with the existing techniques. However, the RIF technique can effectively verify the existence of a dual profile of the microdroplets in a simple setup. In this work, the RIF technique is successfully developed as a new optical diagnostic technique to determine the microdroplet features, such as the dual profile, the height, the contact angle, the inflection point, and the precursor film thickness, by simply measuring the RIF patterns on the far-field screen.
Fluid flow through fractured media is typically governed by the distribution of fracture apertures, which are in turn governed by stress. Consequently, understanding subsurface stress is critical for understanding and predicting subsurface fluid flow. Although laboratory-scale studies have established a sensitive relationship between effective stress and bulk electrical conductivity in crystalline rock, that relationship has not been extensively leveraged to monitor stress evolution at the field scale using electrical or electromagnetic geophysical monitoring approaches. In this paper we demonstrate the use time-lapse 3-dimensional (4D) electrical resistivity tomography to image perturbations in the stress field generated by pressurized borehole packers deployed during shear-stimulation attempts in a 1.25 km deep metamorphic crystalline rock formation.
GaN/InGaN microLEDs are a very promising technology for next-generation displays. Switching control transistors and their integration are key components in achieving high-performance, efficient displays. Monolithic integration of microLEDs with GaN switching devices provides an opportunity to control microLED output power with capacitive (voltage)-controlled rather than current-controlled schemes. This approach can greatly reduce system complexity for the driver circuit arrays while maintaining device opto-electronic performance. In this work, we demonstrate a 3-terminal GaN micro-light emitting transistor that combines a GaN/InGaN blue tunneling-based microLED with a GaN n-channel FET. The integrated device exhibits excellent gate control, drain current control, and optical emission control. This work provides a promising pathway for future monolithic integration of GaN FETs with microLED to enable fast switching, high-efficiency microLED display and communication systems.
Understanding the mobility of twinning dislocations is important for multiscale modeling of crystal plasticity, especially at high strain rates, where such dislocations may reach transonic or supersonic speeds. Here, we used molecular dynamics simulations to investigate the relationship between dislocation velocity and the applied resolved shear stress of an edge twinning dislocation in copper up to supersonic speeds. The twinning dislocation mobility relation is composed of two branches separated by a band of forbidden velocities. The lower velocity branch is limited by the first transverse sound speed ~2000 m/s while the upper branch stretches from ~3500 m/s in the transonic regime to supersonic velocities. Twinning dislocations cannot undergo uniform steady-state motion at velocities within the forbidden band. Our simulation results also reveal that edge twinning dislocation motion in copper is kink-mediated. We discuss the implications of our findings for the motion of twins, twinning dislocations, and twinning dislocation kinks in copper.
Electrical polarization and defect transport are examined in 0.8BaTiO3–0.2BiZn0.5Ti0.5O3, an attractive capacitor material for high power electronics. Oxygen vacancies are suggested to be the majority charge carrier at or below 250°C with a grain conduction hopping activation energy of 0.97 eV and 0.92 eV for thermally stimulated depolarization current (TSDC) and impedance spectroscopy measurements, respectively. At higher temperature, thermally generated electronic conduction with an activation energy of 1.6 eV is dominant. Significant oxygen vacancy concentration is indicated (up to ~1%) due to cation vacancy formation (i.e., acceptor defects) from observed Bi (and likely Zn) volatility. Oxygen vacancy diffusivity is estimated to be 10-12.8 cm2/s at 250°C. Low diffusivity and high activation energies are indicative of significant defect interactions. Dipolar oxygen vacancy defects are also indicated, with an activation energy of 0.59 eV from TSDC measurements. In conclusion, the large oxygen vacancy content leads to a short lifetime during high voltage (30 kV/cm), high temperature (250°C) direct current (DC) electrical measurements.
A new strategy is presented for computing anharmonic partition functions for the motion of adsorbates relative to a catalytic surface. Importance sampling is compared with conventional Monte Carlo. The importance sampling is significantly more efficient. This new approach is applied to CH3* on Ni(111) as a test case. The motion of methyl relative to the nickel surface is found to be anharmonic, with significantly higher entropy compared to the standard harmonic oscillator model. The new method is freely available as part of the Minima-Preserving Neural Network within the AdTherm package.
Nanoporous, gas-selective membranes have shown encouraging results for the removal of CO2 from flue gas, yet the optimal design for such membranes is often unknown. Therefore, we used molecular dynamics simulations to elucidate the behavior of CO2 within aqueous and ionic liquid (IL) systems ([EMIM][TFSI] and [OMIM][TFSI]), both confined individually and as an interfacial aqueous/IL system. We found that within aqueous systems the mobility of CO2 is reduced due to interactions between the CO2 oxygens and hydroxyl groups on the pore surface. Within the IL systems, we found that confinement has a greater effect on the [EMIM][TFSI] system as opposed to the [OMIM][TFSI] system. Paradoxically, the larger and more asymmetrical [OMIM]+ molecule undergoes less efficient packing, resulting in fewer confinement effects. Free energy surfaces of the nanoconfined aqueous/IL interface demonstrate that CO2 will transfer spontaneously from the aqueous to the IL phase.
NasGen provides a path for migration of structural models from Nastran bulk data format (BDF) into both an Exodus mesh file and an ASCII input file for Sierra Structural Dynamics (Salinas) and Solid Mechanics (Adagio). Many tools at Sandia National Labs (SNL) use the Exodus format. This document describes capabilities and limitations of the NasGen translation software.
Lasa, Ane; Park, Jae-Sun; Lore, Jeremy; Blondel, Sophie; Bernholdt, David E.; Canik, John M.; Cianciosa, Mark; Coburn, Jonathan D.; Curreli, Davide; Elwasif, Wael; Guterl, Jerome; Hoffman, Josh; Park, Jim M.; Sinclair, Gregory; Wirth, Brian D.
Integrated modeling of plasma-surface interactions provides a comprehensive and self-consistent description of the system, moving the field closer to developing predictive and design capabilities for plasma facing components. One such workflow, including descriptions for the scrape-off-layer plasma, ion-surface interactions and the sub-surface evolution, was previously used to address steady-state scenarios and has recently been extended to incorporate time-dependence and two-way information flow. The new model can address dynamic recycling in transient scenarios, such as the application presented in this paper: the evolution of W samples pre-damaged by helium and exposed to ELMy H-mode plasmas in the DIII-D DiMES. A first set of simulations explored the effect of ELM frequency. This study was discussed in detail in this conference's proceedings and is summarized here. The 2nd set of simulations, which is the focus of this paper, explores the effect of code-coupling frequency. These simulations include initial SOLPS solutions converged to the inter-ELM state, ion impact energy (Ein) and angles (Ain) calculated by hPIC2, and an improved heat transfer description in Xolotl. The model predicts increases in particle fluxes and decreases in heat fluxes by 10%–20% with the coupling time-step. Compared with the first set of simulations, the less shallow impact angle leads to smaller reflection rates and significant D implantation. The higher fraction of implanted flux (and deeper), in particular during ELMs, increases the accumulated D content in the W near-surface region. Future expansion of the workflow includes coupling to hPIC2 and GITR to ensure accurate descriptions of Ein and Ain, and W impurity transport.
The Example Problems Manual supplements the User's Manual and the Theory Manual. The goal of the Example Problems Manual is to reduce learning time for complex end to end analyses. These documents are intended to be used together. See the User's Manual for a complete list of the options for a solution case. All the examples are part of the salinas test suite. Each runs as is.
Understanding the limits of spatiotemporal carrier dynamics, especially in III-V semiconductors, is key to designing ultrafast and ultrasmall optoelectronic components. However, identifying such limits and the properties controlling them has been elusive. Here, using scanning ultrafast electron microscopy, in bulk n-GaAs and p-InAs, we simultaneously measure picosecond carrier dynamics along with three related quantities: subsurface band bending, above-surface vacuum potentials, and surface trap densities. We make two unexpected observations. First, we uncover a negative-time contrast in secondary electrons resulting from an interplay among these quantities. Second, despite dopant concentrations and surface state densities differing by many orders of magnitude between the two materials, their carrier dynamics, measured by photoexcited band bending and filling of surface states, occur at a seemingly common timescale of about 100 ps. This observation may indicate fundamental kinetic limits tied to a multitude of material and surface properties of optoelectronic III-V semiconductors and highlights the need for techniques that simultaneously measure electrooptical kinetic properties.
Experiments offer incredible value to science, but results must always come with an uncertainty quantification to be meaningful. This requires grappling with sources of uncertainty and how to reduce them. In wind energy, field experiments are sometimes conducted with a control and treatment. In this scenario uncertainty due to bias errors can often be neglected as they impact both control and treatment approximately equally. However, uncertainty due to random errors propagates such that the uncertainty in the difference between the control and treatment is always larger than the random uncertainty in the individual measurements if the sources are uncorrelated. As random uncertainties are usually reduced with additional measurements, there is a need to know the minimum duration of an experiment required to reach acceptable levels of uncertainty. We present a general method to simulate a proposed experiment, calculate uncertainties, and determine both the measurement duration and the experiment duration required to produce statistically significant and converged results. The method is then demonstrated as a case study with a virtual experiment that uses real-world wind resource data and several simulated tip extensions to parameterize results by the expected difference in power. With the method demonstrated herein, experiments can be better planned by accounting for specific details such as controller switching schedules, wind statistics, and postprocess binning procedures such that their impacts on uncertainty can be predicted and the measurement duration needed to achieve statistically significant and converged results can be determined before the experiment.
Multivalent-ion battery technologies are increasingly attractive options for meeting diverse energy storage needs. Calcium ion batteries (CIB) are particularly appealing candidates for their earthly abundance, high theoretical volumetric energy density, and relative safety advantages. At present, only a few Ca-ion electrolyte systems are reported to reversibly plate at room temperature: for example, aluminates and borates, including Ca[TPFA]2, where [TPFA]− = [Al(OC(CF3)3)4]− and Ca[B(hfip)4]2, [B(hfip)4]2- = [B(OCH(CF3)2)4]−. Analyzing the structure of these salts reveals a common theme: the prevalent use of a weakly coordinating anion (WCA) consisting of a tetracoordinate aluminum/boron (Al/B) center with fluorinated alkoxides. Leveraging the concept of theory-aided design, we report an innovative, one-pot synthesis of two new calcium-ion electrolyte salts (Ca[Al(tftb)4]2, Ca[Al(hftb)4]2) and two reported salts (Ca[Al(hfip)4]2 and Ca[TPFA]2) where hfip = (−OCH(CF3)2), tftb = (−OC(CF3)(Me)2), hftb = (−OC(CF3)2(Me)), [TPFA]− = [Al(OC(CF3)3)4]−. We also reveal the dependence of Coulombic efficiency on their inherent propensity for cation-anion coordination.
Stress corrosion cracking behavior of stainless steel 304 L was investigated in full immersion, evaporated artificial sea salt brines (ASW) at 55 °C. It was observed that brines representative of thermodynamically stable brines at lower relative humidity (40% RH, MgCl2-dominant) had a faster crack growth rate than high relative humidity brines (76% RH, NaCl-dominant). Observed crack growth rates (da/dt) under constant stress intensity (K) conditions were determined to be independent of transitioning procedure (rising K or decreasing frequency) regardless of solutions investigated for the orientation presented. Further, positive strain rates had little to no impact on the observed da/dt. The observed behavior suggests an anodic dissolution enhanced hydrogen embrittlement mechanism for SS304L in concentrated ASW environments at 55 °C. Additional explorations further examined environmental influences on da/dt. Nitrate additions to 40% ASW at 55 °C solutions were shown to decrease measured da/dt and further additions stopped measurable crack growth. After sufficient nitrate had been added to fully stifle crack growth, a temperature increase to 75 °C induced cracking again, and a subsequent decrease to 55 °C once again stopped da/dt. These tests demonstrate the importance of ascertaining both brine-specific chemical and dynamic environmental influences on da/dt.
Neural operators, which can act as implicit solution operators of hidden governing equations, have recently become popular tools for learning the responses of complex real-world physical systems. Nevertheless, most neural operator applications have thus far been data-driven and neglect the intrinsic preservation of fundamental physical laws in data. In this work, we introduce a novel integral neural operator architecture called the Peridynamic Neural Operator (PNO) that learns a nonlocal constitutive law from data. This neural operator provides a forward model in the form of state-based peridynamics, with objectivity and momentum balance laws automatically guaranteed. As applications, we demonstrate the expressivity and efficacy of our model in learning complex material behaviors from both synthetic and experimental data sets. We also compare the performances with baseline models that use predefined constitutive laws. We show that, owing to its ability to capture complex responses, our learned neural operator achieves improved accuracy and efficiency. Moreover, by preserving the essential physical laws within the neural network architecture, the PNO is robust in treating noisy data. The method shows generalizability to different domain configurations, external loadings, and discretizations.
Multivalent battery chemistries have been explored in response to the increasing demand for high-energy rechargeable batteries utilizing sustainable resources. Solvation structures of working cations have been recognized as a key component in the design of electrolytes; however, most structure−property correlations of metal ions in organic electrolytes usually build upon favorable static solvation structures, often overlooking solvent exchange dynamics. We here report the ion solvation structures and solvent exchange rates of magnesium electrolytes in various solvents by using multimodal nuclear magnetic resonance (NMR) analysis and molecular dynamics/density functional theory (MD/DFT) calculations. These magnesium solvation structures and solvent exchange dynamics are correlated to the combined effects of several physicochemical properties of the solvents. Moreover, Mg2+ transport and interfacial charge transfer efficiency are found to be closely correlated to the solvent exchange rate in the binary electrolytes where the solvent exchange is tunable by the fraction of diluent solvents. Our primary findings are (1) most battery-related solvents undergo ultraslow solvent exchange coordinating to Mg2+ (with time scales ranging from 0.5 μs to 5 ms), (2) the cation transport mechanism is a mixture of vehicular and structural diffusion even at the ultraslow exchange limit (with faster solvent exchange leading to faster cation transport), and (3) an interfacial model wherein organic-rich regions facilitate desolvation and inorganic regions promote Mg2+ transport is consistent with our NMR, electrochemistry, and cryogenic X-ray photoelectron spectroscopy (cryo-XPS) results. This observed ultraslow solvent exchange and its importance for ion transport and interfacial properties necessitate the judicious selection of solvents and informed design of electrolyte blends for multivalent electrolytes.
We show that the deposition of the solid-state electrolyte LiPON onto films of V2O5 leads to their uniform lithiation of up to 2.2 Li per V2O5, without affecting the Li concentration in the LiPON and its ionic conductivity. Our results indicate that Li incorporation occurs during LiPON deposition, in contrast to earlier mechanisms proposed to explain postdeposition Li transfer between LiPON and LiCoO2. We use our discovery to demonstrate symmetric thin film batteries with a capacity of >270 mAh/g, at a rate of 20C, and 1600 cycles with only 8.4% loss in capacity. We also show how autolithiation can simplify fabrication of Li iontronic transistors attractive for emerging neuromorphic computing applications. Our discovery that LiPON deposition results in autolithiation of the underlying insertion oxide has the potential to substantially simplify and enhance the fabrication process for thin film solid state Li ion batteries and emerging lithium iontronic neuromorphic computing devices.
Adams, David P.; Mcclure, Zachary D.; Appleton, Robert J.; Strachan, Alejandro
Ge-Sb-Te (GST) alloys are leading phase-change materials for data storage due to the fast phase transition between amorphous and crystalline states. Ongoing research aims at improving the stability of the amorphous phase to improve retention. This can be accomplished by the introduction of carbon as a dopant to Ge2Sb2Te5, which is known to alter the short- and mid-range structure of the amorphous phase and form covalently bonded C clusters, both of which hinder crystallization. The relative importance of these processes as a function of C concentration is not known. We used molecular dynamics simulation based on density functional theory to study how carbon doping affects the atomic structure of GST-C. Carbon doping results in an increase in tetrahedral coordination, especially of Ge atoms, and this is known to stabilize the amorphous phase. We observe an unexpected, non-monotonous trend in the number of tetrahedral bonded Ge with the amount of carbon doping. Our simulations show an increase in the number of tetrahedral bonded Ge up to 5 at.% C, after which the number saturates and begins to decrease above 14 at.% C. The carbon atoms aggregate into clusters, mostly in the form of chains and graphene flakes, leaving less carbon to disrupt the GST matrix at higher carbon concentrations. Different degrees of carbon clustering can explain divergent experimental results for recrystallization temperature for carbon doped GST.
High-nickel-content layered oxides are among the most promising electric vehicle battery cathode materials. However, their interfacial reactivity with electrolytes and tendency toward oxygen release (possibly yielding reactive 1O2) remain degradation concerns. Elucidating the most relevant (i.e., fastest) interfacial degradation mechanism will facilitate future mitigation strategies. We apply screened hybrid density functional (HSE06) calculations to compare the reaction kinetics of LixNiO2 surfaces with ethylene carbonate (EC) with those of O2 release. On both the (001) and (104) facets, EC oxidative decomposition exhibits lower activation energies than O2 release. Our calculations, coupled with previously computed liquid-phase reaction rates of 1O2 with EC, strongly question the role of “reactive 1O2” species in electrolyte oxidative degradation. The possible role of other oxygen species is discussed. To deal with the challenges of modeling LixNiO2 surface reactivity, we emphasize a “local structure” approach instead of pursuing the global energy minimum.
