Here, a new non-neutral generalized Ohm's law (GOL) model for atomic plasmas is presented. This model differs from previous models of this type in that quasi-neutrality is not assumed at any point. Collisional effects due to ionization, recombination, and elastic scattering are included, and an expression for the associated plasma conductivity is derived. An initial set of numerical simulations are considered that compare the GOL model to a two-fluid model in the ideal (collisionless) case. The results demonstrate that solutions obtained from the two models are essentially indistinguishable in most cases when the ion–electron mass ratio is within the range of physical values for atomic plasmas. Additionally, some limitations of the model are discussed.
As part of the project “Designing Resilient Communities (DRC): A Consequence-Based Approach for Grid Investment,” funded by the United States (US) Department of Energy’s (DOE) Grid Modernization Laboratory Consortium (GMLC), Sandia National Laboratories (Sandia) partnered with a variety of government, industry, and university participants to develop and test a framework for community resilience planning focused on modernization of the electric grid. This report provides a summary of the development, description, and demonstration of the resulting Resilient Community Design Framework.
Wave energy resource characterization investigations have been hindered because frequency-directional wave spectra are not broadly available for many coastal regions due to the insufficient spatial coverage of buoy observation networks and spectral wave model hindcast outputs. We address this problem by developing and validating a practical method for approximating temporally-averaged frequency-directional wave spectra averaged over periods of months or years from bulk wave parameters, which are available at a much greater coverage and resolution than frequency-directional wave spectra. While the temporally averaged frequency-directional wave spectrum over these periods cannot be used for analyzing a single sea state, it aggregates multiple sea states, identifies dominant wave energy systems representing wave climate, and resolves their spectral characteristics. Therefore, modelling temporally averaged frequency-directional wave spectra is of great value for planning and designing wave energy projects, e.g., resource characterization, site assessment, and conceptual design of wave energy converters. Temporally-averaged frequency-directional wave spectra and related important wave energy parameters approximated using this method are found to be more accurate than commonly used parametric wave spectrum models. This method can be applied to a wide range of wave climates given its universality and high accuracy. Also, the availability of bulk wave parameters from multi-decade high-resolution wave model hindcasts is increasing.
Protecting against multi-step attacks of uncertain start times and duration forces the defenders into indefinite, always ongoing, resource-intensive response. To allocate resources effectively, the defender must analyze and respond to an uncertain stream of potentially undetected multiple multi-step attacks and take measures of attack and response intensity over time into account. Such response requires estimation of overall attack success metrics and evaluating effect of defender strategies and actions associated with specific attack steps on overall attack metrics. We present a novel game-theoretic approach GPLADD to attack metrics estimation and demonstrate it on attack data derived from MITRE's ATT&CK Framework and other sources. In GPLADD, the time to complete attack steps is explicit; the attack dynamics emerges from attack graph and attacker-defender capabilities and strategies and therefore reflects 'physics' of attacks. The time the attacker takes to complete an attack step is drawn from a probability distribution determined by attacker and defender strategies and capabilities. This makes time a physical constraint on attack success parameters and enables comparing different defender resource allocation strategies across different attacks. We solve for attack success metrics by approximating attacker-defender games as discrete-time Markov chains and show evaluation of return on detection investments associated with different attack steps. We apply GPLADD to MITRE's APT3 data from ATT&CK Framework and show that there are substantial and un-intuitive differences in estimated real-world vendor performance against a simplified APT3 attack. We focus on metrics that reflect attack difficulty versus attacker ability to remain hidden in the system after gaining control. This enables practical defender optimization and resource allocation against multi-step attacks.
Laboratory shear tests were conducted on pulverized Sierra White granite (SWG) to investigate slip mechanisms in naturally occurring faults. Synthetic fault geometries were constructed by sandwiching fine grained SWG powder in between steel forcing blocks. For dry experiments, ~3.5 g of SWG powder was poured onto the face of the lower steel forcing block and leveled. For saturated experiments, enough fluid was added to the ~3.5 g of Sierra White granite powder to form a slurry. This slurry was applied to the lower forcing block and leveled. Inclined forcing blocks with 25.4 mm diameter and 35° faces, which were machined from ground steel rods with fine teeth on the faces, help to hold the gouge in place and prevent delamination at the interface. The top forcing block had a 2.03 mm centered hole to allow pore fluid access to the gouge. A fine steel mesh prevented back flow of the gouge into pore fluid lines. Samples were isolated from the confining medium using three layers of heat shrink polyolefin, as shown in Figure 1. The outer layer was shrunk over the o-rings on the end caps to form an impermeable seal, which was reinforced with steel tie wires on both sides of the o-rings. Hardened steel spacers and copper shim stock was placed between the steel forcing blocks and the end caps to preserve the parallelism of the Hastelloy wetted parts. For dry samples, the end caps were plugged, while the end caps for the saturated samples were connected to pore lines.
The flow and particle deposition patterns on surfaces in an idealized spacer grid for a 17x17 pressurized water reactor (PWR) assembly in a spent fuel canister are modeled using computational fluid dynamics (CFD) with laminar flow. The effects of gravitational settling, non-Stokesian flow, and particle slip are first rigorously analyzed. From the analysis, non-Stokesian effects and slip may be neglected for the particle sizes and conditions expected in a canister. For particles that do not settle out, a swirling flow pattern at the corners of a spacer grid channel directs particles to the leeward side of the flow vanes where much of the deposition occurs. Particle deposition increases with increasing particle diameter. Deposition also increases with decreasing flow velocity as this provides more time for particles to settle and deposit on the leeward side of the flow vanes. The fraction of particles that are transmitted through a spacer grid is determined as a function of inlet gas velocity and particle diameter by running the CFD calculation for each set of conditions and for each particle diameter. Curve fits of the transmission curve as a function of particle diameter for a specified spacer grid and flow velocity are applied to a lognormal particle mass density function for the inlet particles. The resulting mass density function and aerosol mass fraction that passes through the spacer grid can be determined analytically without resorting to numerical iteration. A sample calculation of the analytical solution is demonstrated for a lognormal particle mass density function.
In typical carbonyl-containing molecules, bond dissociation events follow initial excitation to $nπ_{C=O}$$^*$ states. However, in acetyl iodide, the iodine atom gives rise to electronic states with mixed $nπ_{C=O}$$^*$ and $nπ_{C–I}$$^*$ character, leading to complex excited-state dynamics, ultimately resulting in dissociation. Using ultrafast extreme ultraviolet (XUV) transient absorption spectroscopy and quantum chemical calculations, we present an investigation of the primary photodissociation dynamics of acetyl iodide via time-resolved spectroscopy of core-to-valence transitions of the I atom after 266 nm excitation. The probed I 4d-to-valence transitions show features that evolve on sub-100-fs time scales, reporting on excited-state wavepacket evolution during dissociation. These features subsequently evolve to yield spectral signatures corresponding to free iodine atoms in their spin–orbit ground and excited states with a branching ratio of 1.1:1 following dissociation of the C–I bond. Calculations of the valence excitation spectrum via equation-of-motion coupled cluster with single and double substitutions (EOM-CCSD) show that initial excited states are of spin-mixed character. From the initially pumped spin-mixed state, we use a combination of time-dependent density functional theory (TDDFT)-driven nonadiabatic ab initio molecular dynamics and EOM-CCSD calculations of the N$_{4,5}$ edge to reveal a sharp inflection point in the transient XUV signal that corresponds to rapid C–I homolysis. Here, by examining the molecular orbitals involved in the core-level excitations at and around this inflection point, we are able to piece together a detailed picture of C–I bond photolysis in which d → σ* transitions give way to d → p excitations as the bond dissociates. We also report theoretical predictions of short-lived, weak 4d → 5d transitions in acetyl iodide, validated by weak bleaching in the experimental transient XUV spectra. This joint experimental–theoretical effort has thus unraveled the detailed electronic structure and dynamics of a strongly spin–orbit coupled system.
The goal of this work is to develop a wafer level copper electrochemical deposition process for high aspect ratio through silicon vias and test the reliability and functionality of TSVs for integration into MEMS applications.
The mechanical behavior of partial-penetration laser welds exhibits significant variability in engineering quantities such as strength and apparent ductility. Understanding the root cause of this variability is important when using such welds in engineering designs. In Part II of this work, we develop finite element simulations with geometry derived from micro-computed tomography (μCT) scans of partial-penetration 304L stainless steel laser welds that were analyzed in Part I. We use these models to study the effects of the welds’ small-scale geometry, including porosity and weld depth variability, on the structural performance metrics of weld ductility and strength under quasi-static tensile loading. We show that this small-scale geometry is the primary cause of the observed variability for these mechanical response quantities. Additionally, we explore the sensitivity of model results to the conversion of the μCT data to discretized model geometry using different segmentation algorithms, and to the effect of small-scale geometry simplifications for pore shape and weld root texture. The modeling approach outlined and results of this work may be applicable to other material systems with small-scale geometric features and defects, such as additively manufactured materials.
Recent studies of power flow and particle transport in multi-MA pulsed-power accelerators demonstrate that electrode plasmas may reduce accelerator efficiency by shunting current upstream from the load. The detailed generation and evolution of these electrode plasmas are examined here using fully relativistic, Monte Carlo particle-in-cell (PIC) and magnetohydrodynamic (MHD) simulations over a range of peak currents (8–48 MA). The PIC calculations, informed by vacuum science, describe the electrode surface breakdown and particle transport prior to electrode melt. The MHD calculations show the bulk electrode evolution during melt. The physical description provided by this combined study begins with the rising local magnetic field that increases the local electrode surface temperature. This initiates the thermal desorption of contaminants from the electrode surface, with contributions from atoms outgassing from the bulk metal. The contaminants rapidly ionize forming a 1015-1018 cm-3 plasma that is effectively resistive while weakly collisional because it is created within, and rapidly penetrated by, a strong magnetic field (> 30 T). Prior to melting, the density of this surface plasma is limited by the concentration of absorbed contaminants in the bulk (~1019 cm-3 for hydrogen), its diffusion, and ionization. Eventually, the melting electrodes form a conducting plasma (1021-1023 cm-3) that experiences j × B compression and a typical decaying magnetic diffusion profile. This physical sequence ignores the transport of collisional plasmas of 1019 cm-3 which may arise from electrode defects and associated instabilities. Nonetheless, this picture of plasma formation and melt may be extrapolated to higher-energy pulsed-power systems.
Recent studies on off-stoichiometric thermosets reveal unique viscoelastic behavior derived from increased free volume and physical interactions between chain ends. To understand structural characteristics arising from cure and its effect on properties, we developed a Monte Carlo model based on step-growth polymerization. Our model accurately predicted structure-property trends for a two-component system of EPON 828 (EPON) and ethylenediamine. A second epoxy monomer, D.E.R. 732 (DER), was investigated to modulate Tg. Binary mixtures of EPON and DER in off-stoichiometric, amine-rich formulations resulted in nonlinear evolution of thermomechanical properties with respect to initial formulation stoichiometry. Modifying our model with kinetic parameters allowing for differential epoxide/amine reaction kinetics only partially accounted for trends in Tg, suggesting that spatiotemporal contributions─not captured by our model─were significant determinants of material properties compared to polymer architecture for three-component systems. These findings underpin the importance of spatial awareness in modeling to inform the development of dynamic thermosets.
This paper focuses on the development of multifidelity modeling approaches using neural network surrogates, where training data arising from multiple model forms and resolutions are integrated to predict high-fidelity response quantities of interest at lower cost. We focus on the context of quantum chemistry and the integration of information from multiple levels of theory. Important foundations include the use of symmetry function-based atomic energy vector constructions as feature vectors for representing structures across families of molecules and single-fidelity neural network training capabilities that learn the relationships needed to map feature vectors to potential energy predictions. These foundations are embedded within several multifidelity topologies that decompose the high-fidelity mapping into model-based components, including sequential formulations that admit a general nonlinear mapping across fidelities and discrepancy-based formulations that presume an additive decomposition. Methodologies are first explored and demonstrated on a pair of simple analytical test problems and then deployed for potential energy prediction for C5H5 using B2PLYP-D3/6-311++G(d,p) for high-fidelity simulation data and Hartree-Fock 6-31G for low-fidelity data. For the common case of limited access to high-fidelity data, our computational results demonstrate that multifidelity neural network potential energy surface constructions achieve roughly an order of magnitude improvement, either in terms of test error reduction for equivalent total simulation cost or reduction in total cost for equivalent error.
A cloud of very fast, O(km/s), and very fine, O(µm), particles may be ejected when a strong shock impacts and possibly melts the free surface of a solid metal. To quantify these dynamics, this work develops an ultraviolet, long-working distance, two-pulse Digital Holographic Microscopy (DHM) configuration and is the first to replace film recording with digital sensors for this challenging application. A proposed multi-iteration DHM processing algorithm is demonstrated for automated measures of the sizes, velocities, and three-dimensional positions of non-spherical particles. Ejecta as small as 2 µm diameter are successfully tracked, while uncertainty simulations indicate that particle size distributions are accurately quantified for diameters ≥4 µm. These techniques are demonstrated on three explosively driven experiments. Measured ejecta size and velocity statistics are shown to be consistent with prior film-based recording, while also revealing spatial variations in velocities and 3D positions that have yet to be widely investigated. Having eliminated time-consuming analog film processing, the methodologies proposed here are expected to significantly accelerate future experimental investigation of ejecta physics.
Multimodal datasets of materials are rich sources of information which can be leveraged for expedited discovery of process–structure–property relationships and for designing materials with targeted structures and/or properties. For this data descriptor article, we provide a multimodal dataset of magnetron sputter-deposited molybdenum (Mo) thin films, which are used in a variety of industries including high temperature coatings, photovoltaics, and microelectronics. In this dataset we explored a process space consisting of 27 unique combinations of sputter power and Ar deposition pressure. Here, the phase, structure, surface morphology, and composition of the Mo thin films were characterized by x-ray diffraction, scanning electron microscopy, atomic force microscopy, and Rutherford backscattering spectrometry. Physical properties—namely, thickness, film stress and sheet resistance—were also measured to provide additional film characteristics and behaviors. Additionally, nanoindentation was utilized to obtain mechanical load-displacement data. The entire dataset consists of 2072 measurements including scalar values (e.g., film stress values), 2D linescans (e.g., x-ray diffractograms), and 3D imagery (e.g., atomic force microscopy images). An additional 1889 quantities, including film hardness, modulus, electrical resistivity, density, and surface roughness, were derived from the experimental datasets using traditional methods. Minimal analysis and discussion of the results are provided in this data descriptor article to limit the authors’ preconceived interpretations of the data. Overall, the data modalities are consistent with previous reports of refractory metal thin films, ensuring that a high-quality dataset was generated. The entirety of this data is committed to a public repository in the Materials Data Facility.
Focused ion beam implantation is ideally suited for placing defect centers in wide bandgap semiconductors with nanometer spatial resolution. However, the fact that only a few percent of implanted defects can be activated to become efficient single photon emitters prevents this powerful capability to reach its full potential in photonic/electronic integration of quantum defects. Here an industry adaptive scalable technique is demonstrated to deterministically create single defects in commercial grade silicon carbide by performing repeated low ion number implantation and in situ photoluminescence evaluation after each round of implantation. An array of 9 single defects in 13 targeted locations is successfully created—a ≈70% yield which is more than an order of magnitude higher than achieved in a typical single pass ion implantation. The remaining emitters exhibit non-classical photon emission statistics corresponding to the existence of at most two emitters. This approach can be further integrated with other advanced techniques such as in situ annealing and cryogenic operations to extend to other material platforms for various quantum information technologies.
Schiffman, Zachary R.; Fernanders, Marium S.; Davis, Ryan; Tolbert, Margaret A.
Mineral dust can indirectly impact climate by nucleation of atmospheric solids, for example, by heterogeneously nucleating ice in mixed-phase clouds or by impacting the phase of aerosols and clouds through contact nucleation. The effectiveness toward nucleation of individual components of mineral dust requires further study. Here, the nucleation behavior of metal oxide nanoparticle components of atmospheric mineral dust is investigated. A long-working-distance optical trap is used to study contact and immersion nucleation of ammonium sulfate by transition-metal oxides, and an environmental chamber is used to probe depositional ice nucleation on metal oxide particles. Previous theory dictates that ice nucleation and heterogeneous nucleation of atmospheric salts can be impacted by several factors including morphology, lattice match, and surface area. Here, we observe a correlation between the cationic oxidation states of the metal oxide heterogeneous nuclei and their effectiveness in causing nucleation in both contact efflorescence mode and depositional freezing mode. In contrast to the activity of contact efflorescence, the same metal oxide particles did not cause a significant increase in efflorescence relative humidity when immersed in the droplet. These experiments suggest that metal speciation, possibly as a result of cationic charge sites, may play a role in the effectiveness of nucleation that is initiated at particle surfaces.
Song, Yueming; Bhargava, Bhuvsmita; Stewart, David M.; Talin, Albert A.; Rubloff, Gary W.; Albertus, Paul
Lithium metal solid-state batteries (LiSSBs) present new challenges in the measurement of material, component, and cell mechanical behaviors and in the measurement and theory of fundamental mechanical-electrochemical (thermodynamics, transport, and kinetics) couplings. Here, we classify the major mechanical and electrochemical-mechanical (ECM) studies underway and provide an overview of major mechanical testing platforms. We emphasize key distinctions among testing platforms, including tip- vs. platen-based sample compression, surface- vs. volume-based analysis, ease of integration with a vacuum or inert atmosphere environment, the ability to control and measure force/displacement over long periods of time, ranges of force and contact area, and others. Among the techniques we review, nanoindentation platforms offer some unique benefits associated with being able to use both tip-based nanoindentation techniques as well as platen-based compression over areas approaching 1 mm2. Sample design is also important: while most efforts are particle-based (i.e., using particles of solid electrolyte and cathode-active materials and densifying them using sintering or pressure), the resulting electrochemical response is from the overall collection of particles present. In contrast, thin-film (<1 μm) solid-state battery materials (e.g., Li, LiPON, LCO) provide well defined and uniform structures well suited for fundamental electrochemical-mechanical studies and offer an important opportunity to drive underlying scientific advances in LiSSB and other areas. We believe there are exciting opportunities to advance the measurement of both mechanical properties and electrochemical-mechanical couplings through the careful and novel co-design of test structures and experimental approaches for LiSSB materials, components, and cells.
Network intrusion detection systems (NIDS) are commonly used to detect malware communications, including command-and-control (C2) traffic from botnets. NIDS performance assessments have been studied for decades, but mathematical modeling has rarely been used to explore NIDS performance. This paper details a mathematical model that describes a NIDS performing packet inspection and its detection of malware's C2 traffic. Here, the paper further describes an emulation testbed and a set of cyber experiments that used the testbed to validate the model. These experiments included a commonly used NIDS (Snort) and traffic with contents from a pervasive malware (Emotet). Results are presented for two scenarios: a nominal scenario and a “stressed” scenario in which the NIDS cannot process all incoming packets. Model and experiment results match well, with model estimates mostly falling within 95 % confidence intervals on the experiment means. Model results were produced 70-3000 times faster than the experimental results. Consequently, the model's predictive capability could potentially be used to support decisions about NIDS configuration and effectiveness that require high confidence results, quantification of uncertainty, and exploration of large parameter spaces. Furthermore, the experiments provide an example for how emulation testbeds can be used to validate cyber models that include stochastic variability.
Lithium dendrite growth hinders the use of lithium metal anodes in commercial batteries. We present a 3D model to study the mechanical and electrochemical mechanisms that drive microscale plating. With this model, we investigate electrochemical response across a lithium protrusion characteristic of rough anode surfaces, representing the separator as a porous polymer in non-conformal contact with a lithium anode. The impact of pressure on separator morphology and electrochemical response is of particular interest, as external pressure can improve cell performance. We explore the relationships between plating propensity, stack pressure, and material properties. External pressure suppresses lithium plating due to interfacial stress and separator pore closure, leading to inhomogeneous plating rates. For moderate pressures, dendrite growth is completely suppressed, as plating will occur in the electrolyte-filled gaps between anode and separator. In fast-charging conditions and systems with low electrolyte diffusivities, the benefits of pressure are overridden by ion transport limitations.
Herein, we report the synthesis of a novel, tetraphenylethylene-based ligand for metal-organic frameworks (MOFs). Incorporation of this ligand into a Zn- or Eu-based MOF increased the quantum yield (QY) by almost 2.5× compared to the linker alone. Furthermore, the choice of guest solvent impacted the QY and solvatochromatic response. These shifts are consistent with solvent dielectric constant as well as molecular polarizability.
Khalatpour, Ali; Tam, Man C.; Addamane, Sadhvikas J.; Reno, John; Wasilewski, Zbignew; Hu, Qing
Room temperature operation of terahertz quantum cascade lasers (THz QCLs) has been a long-pursued goal to realize compact semiconductor THz sources. In this paper, we report on improving the maximum operating temperature of THz QCLs to ∼261 K as a step toward the realization of this goal.
See, Judi E.; Rosenfeld, Robert B.; Taylor, Sylvester; Wedic, K.M.
An analogy is drawn between the study of human behavior and the study of plutonium to demonstrate that soft and hard sciences are more similar than different, making the distinction moot and unproductive. The studies of human behavior and plutonium follow a common scientific research cycle that aligns with Thomas Kuhn’s views of scientific change. This common research cycle provides evidence that the thought processes and methodologies required for success are congruent in the soft and hard sciences. The primary implication from this analogy is that scientists in all disciplines should eradicate the distinction between soft and hard sciences. Focusing on similarities rather than differences among researchers from different disciplines is necessary to enhance collective intelligence and the type of transdisciplinary collaboration required to tackle difficult sociotechnical problems.
A series of numerical simulations of wind farms, using different model fidelities and for different atmospheric stability conditions, were performed as a part of the American WAKE ExperimeNt. The simulations included using FLORIS wake models, a number of microscale AMR-Wind and Nalu-Wind runs, as well as idealized and complex terrain WRF runs. The largest computations used the AMR-Wind LES solver to simulate a 100 km x 100 km domain containing 541 turbines under unstable atmospheric conditions matching previous measurements, while other LES computations focused on sections of the King Plains wind farm. Results of this qualitative comparison illustrate the interactions with wind farms with large-scale ABL structures in the flow, as well as the extent of downstream wake penetration in the flow and blockage effects around wind farms.
This report describes the results of a field demonstration of the proposed surface sampling techniques and plan for the multi-year Canister Deposition Field Demonstration (CDFD). The CDFD will evaluate salt deposition rates on three commercial 32PTH2 NUHOMS welded stainless steel storage canisters in Advanced Horizontal Storage Modules. Exposure testing is planned for up to 10 years and will incorporate periodic surface sampling campaigns. The goal of the planned dust sampling and analysis is to determine important environmental parameters that impact the potential occurrence of stress corrosion cracking on spent nuclear fuel (SNF) dry storage canisters. Specifically, measured dust deposition rates and deposited particle sizes will improve parameterization of dust deposition models employed to predict the potential occurrence and timing of stress corrosion cracks on the stainless steel SNF canisters. Previously, a preliminary sampling plan was developed, identifying possible sampling locations on the canister surfaces and sampling intervals; possible sampling methods were also described. Building from previous work, this report documents hand sampling from a spent nuclear fuel canister on a transfer skid mockup designed by Sandia National Laboratories. The sampling took place from a boom lift and salts were collected from mounted sample plates. The results of these efforts are presented in this report and compared to previous laboratory-controlled tests. The information obtained from the CDFD will be critical for ongoing efforts to develop a detailed understanding of the potential for stress corrosion cracking of SNF dry storage canisters.
The resurgence of interest in hydrogen-related technologies has stimulated new studies aimed at advancing lesser-developed water-splitting processes, such as solar thermochemical hydrogen production (STCH). Progress in STCH has been largely hindered by a lack of new materials able to efficiently split water at a rate comparable to ceria under identical experimental conditions. BaCe0.25Mn0.75O3 (BCM) recently demonstrated enhanced hydrogen production over ceria and has the potential to further our understanding of two-step thermochemical cycles. A significant feature of the 12R hexagonal perovskite structure of BCM is the tendency to, in part, form a 6H polytype at high temperatures and reducing environments (i.e., during the first step of the thermochemical cycle), which may serve to mitigate degradation of the complex oxide. An analogous compound, namely BaNb0.25Mn0.75O3 (BNM) with a 12R structure was synthesized and displays nearly complete conversion to the 6H structure under identical reaction conditions as BCM. The structure of the BNM-6H polytype was determined from Rietveld refinement of synchrotron powder X-ray diffraction data and is presented within the context of the previously established BCM-6H structure.
Engineering the transition metal dichalcogenide (TMD)-metal interface is critical for the development of two-dimensional semiconductor devices. By directly probing the electronic structures of WS2-Au and WSe2-Au interfaces with high spatial resolution, we delineate nanoscale heterogeneities in the composite systems that give rise to local Schottky barrier height modulations. Photoelectron spectroscopy reveals large variations (>100 meV) in TMD work function and binding energies for the occupied electronic states. Characterization of the composite systems with electron backscatter diffraction and scanning tunneling microscopy leads us to attribute these heterogeneities to differing crystallite orientations in the Au contact, suggesting an inherent role of the metal microstructure in contact formation. We then leverage our understanding to develop straightforward Au processing techniques to form TMD-Au interfaces with reduced heterogeneity. Our findings illustrate the sensitivity of TMDs’ electronic properties to metal contact microstructure and the viability of tuning the interface through contact engineering.
Strong and ultrastrong coupling between intersubband transitions in quantum wells and cavity photons have been realized in mid-infrared and terahertz spectral regions. However, most previous works employed a large number of quantum wells on rigid substrates to achieve coupling strengths reaching the strong or ultrastrong coupling regime. In this work, we experimentally demonstrate ultrastrong coupling between the intersubband transition in a single quantum well and the resonant mode of photonic nanocavity at room temperature. We also observe strong coupling between the nanocavity resonance and the second-order intersubband transition in a single quantum well. Furthermore, we implement for the first time such intersubband cavity polariton systems on soft and flexible substrates and demonstrate that bending of the single quantum well does not significantly affect the characteristics of the cavity polaritons. This work paves the way to broaden the range of potential applications of intersubband cavity polaritons including soft and wearable photonics.
Shunting inhibition is a potential mechanism by which biological systems multiply two time-varying signals, most recently proposed in single neurons of the fly visual system. Our work demonstrates this effect in a biological neuron model and the equivalent circuit in neuromorphic hardware modeling dendrites. We present a multi-compartment neuromorphic dendritic model that produces a multiplication-like effect using the shunting inhibition mechanism by varying leakage along the dendritic cable. Dendritic computation in neuromorphic architectures has the potential to increase complexity in single neurons and reduce the energy footprint for neural networks by enabling computation in the interconnect.
Ruiz-Gomez, Sandra; Perez, Lucas; Mascaraque, Arantzazu; Santos, Benito; El Gabaly, Farid; Schmid, Andreas K.; De La Figuera, Juan
The magnetization patterns on three atomic layers thick islands of Co on Ru(0001) are studied by spin-polarized low-energy electron microscopy (SPLEEM). In-plane magnetized micrometer wide triangular Co islands are grown on Ru(0001). They present two different orientations correlated with two different stacking sequences which differ only in the last layer position. The stacking sequence determines the type of magnetization pattern observed: the hcp islands present very wide domain walls, while the fcc islands present domains separated by much narrower domain walls. The former is an extremely low in-plane anisotropy system. We estimate the in-plane magnetic anisotropy of the fcc regions to be 1.96 × 104 J m−3 and of the hcp ones to be 2.5 × 102 J m−3
Approximation algorithms for computationally complex problems are of significant importance in computing as they provide computational guarantees of obtaining practically useful results for otherwise computationally intractable problems. The demonstration of implementing formal approximation algorithms on spiking neuromorphic hardware is a critical step in establishing that neuromorphic computing can offer cost-effective solutions to significant optimization problems while retaining important computational guarantees on the quality of solutions. Here, we demonstrate that the Loihi platform is capable of effectively implementing the Goemans-Williamson (GW) approximation algorithm for MAXCUT, an NP-hard problem that has applications ranging from VLSI design to network analysis. We show that a Loihi implementation of the approximation step of the GW algorithm obtains equivalent maximum cuts of graphs as conventional algorithms, and we describe how different aspects of architecture precision impacts the algorithm performance.
