Coordinate transformations are a fundamental operation that must be performed by any animal relying upon sensory information to interact with the external world. We present a neural network model that performs a coordinate transformation from the dragonfly eye's frame of reference to the body's frame of reference while hunting. We demonstrate that the model successfully calculates turns required for interception, and discuss how future work will compare our model with biological dragonfly neural circuitry and guide neural-inspired neuromorphic implementations of coordinate transformations.
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
Mixture formation in a hydrogen-fueled heavy-duty engine with direct injection and a nearly-quiescent top-hat combustion chamber was investigated using laser-induced fluorescence imaging, with 1,4-difluorobenzene serving as a fluorescent tracer seeded into hydrogen. The engine was motored at 1200 rpm, 1.0 bar intake pressure, and 335 K intake temperature. An outward opening medium-pressure hollow-cone injector was operated at two different injection pressures and five different injection timings from early injection during the intake stroke to late injection towards the end of compression stroke. Fuel fumigation upstream of the intake provided a well-mixed reference case for image calibration. This paper presents the evolution of in-cylinder equivalence ratio distribution evaluated during the injection event itself for the cylinder-axis plane and during the compression stroke at different positions of the light sheet within the swirl plane. During the injection event, the originally annular jet collapses onto the jet axis within 1°CA after jet emergence and within 10 mm downstream of the nozzle. Multiple shock cells are visible - their size decreases with decreasing pressure ratio. The results of the equivalence ratio distribution show high cyclic variability of mixing for all injection timings during the compression stroke, but only minor variability with early injection during the intake stroke. The ensemble-mean fuel distribution shows that fuel-rich zones shift from the intake side to the exhaust side of the combustion chamber as the injection is advanced. Probability density functions of global equivalence ratio and equivalence ratio at potential spark locations suggest that retarded fuel injection might significantly increase NO emissions and the cyclic variability of early flame kernel development.
Liquefied Petroleum Gas (LPG), as a common alternative fuel for internal combustion engines is currently widespread in use for fleet vehicles. However, a current majority of the LPG-fueled engines, uses port-fuel injection that offers lower power density when compared to a gasoline engine of equivalent displacement volume. This is due to the lower molecular weight and higher volatility of LPG components that displaces more air in the intake charge due to the larger volume occupied by the gaseous fuel. LPG direct-injection during the closed-valve portion of the cycle can avoid displacement of intake air and can thereby help achieve comparable gasoline-engine power densities. However, under certain engine operating conditions, direct-injection sprays can collapse and lead to sub-optimal fuel-air mixing, wall-wetting, incomplete combustion, and increased pollutant emissions. Direct-injection LPG, owing to its thermo-physical properties is more prone to spray collapse than gasoline sprays. However, the impact of spray collapse for high-volatility LPG on mixture preparation and subsequent combustion is not fully understood. To this end, direct-injection, laser-spark ignition experiments using propane as a surrogate for LPG under lean and stoichiometric engine operating conditions were carried out in an optically accessible, single cylinder, heavy-duty, diesel engine. A quick-switching parallel propane and iso-octane fuel system allows for easy comparison between the two fuels. Fuel temperature, operating equivalence ratio and injection timing are varied for a parametric study. In addition to combustion characterization using conventional cylinder pressure measurements, optical diagnostics are employed. These include infrared (IR) imaging for quantifying fuel-air mixture homogeneity and high-speed natural luminosity imaging for tracking the spatial and temporal progression of combustion. Imaging of infrared emission from compression-heated fuel does not reveal any significant differences in the signal distribution between collapsing and non-collapsing sprays at the spark timing. Irrespective of coolant temperatures, early injection timing resulted in a homogeneous mixture that lead to repeatable flame evolution with minimal cycle-to-cycle variability for both LPG and iso-octane. However, late injection timing resulted in mixture inhomogeneity and non-isotropic turbulence distribution. Under lean operation with late injection timing, LPG combustion is shown to benefit from a more favorable mixture distribution and flow properties induced by spray collapse. On the other hand, identical operating conditions proved to be detrimental for iso-octane combustion most likely caused by distribution of lean mixtures near the spark location that negatively impact initial flame kernel growth leading to increased cycle-to-cycle variability.
Oscillatory devices have gained significant interest recently as key components of computing systems based on biomimetic neuronal spiking. An understanding of the time scales underlying the spiking is essential for engineering fast, controllable, low energy devices. However, we find that the intrinsic dynamics of these devices are difficult to properly characterize, as they can be heavily influenced by the external circuitry used to measure them. Here we demonstrate these challenges using a VO2 Mott oscillator with a sub-100 nm effective size, achieved using a nanogap cut in a metallic carbon nanotube electrode. Given the nanoscale thermal volume of this device, it would be expected to exhibit rapid oscillations. However, due to external parasitics present within commonly used current sources, we see orders of magnitude slower dynamics. Here, we outline methods for determining when measurements are dominated by extrinsic factors and discuss the operating conditions under which intrinsic oscillation frequencies may be observed.
Rare-earth terephthalic acid (BDC)-based metal-organic frameworks (MOFs) are promising candidate materials for acid gas separation and adsorption from flue gas streams. However, previous simulations have shown that acid gases (H2O, NO2, and SO2) react with the hydroxyl on the BDC linkers to form protonated acid gases as a potential degradation mechanism. Herein, gas-phase computational approaches were used to identify the formation energies of these secondary protonated acid gases across multiple BDC linker molecules. Formation energies for secondary protonated acid gases were evaluated using both density functional theory (DFT) and correlated wave function methods for varying BDC-gas reaction mechanisms. Upon validation of DFT to reproduce wave function calculation results, rotated conformational linkers and chemically functionalized BDC linkers with −OH, −NH2, and −SH were investigated. The calculations show that the rotational conformation affects the molecule stability. Double-functionalized BDC linkers, where two functional groups are substituted onto BDC, showed varied reaction energies depending on whether the functional groups donate or withdraw electrons from the aromatic system. Based on these results, BDC linker design must balance adsorption performance with degradation via linker dehydrogenation for the design of stable MOFs for acid gas separations.
Chalcogenide thin films that undergo reversible phase changes show promise for use in next-generation nanophotonics, microelectronics, and other emerging technologies. One of the many studied compounds, Ge2Sb2Te5, has demonstrated several useful properties and performance characteristics. However, the efficacy of benchmark Ge2Sb2Te5 is restricted by amorphous phase thermal stability below ∼150 °C, limiting its potential use in high-temperature applications. In response, previous studies have added a fourth species (e.g., C) to sputter-deposited Ge2Sb2Te5, demonstrating improved thermal stability. Our current research confirms reported thermal stability enhancements and assesses the effects of carbon on crystalline phase radiation response. Through in situ transmission electron microscope irradiation studies, we examine the effect of C addition on the amorphization behavior of initially cubic and trigonal polycrystalline films irradiated using 2.8 MeV Au to various doses up to 1 × 1015 cm−2. It was found that increased C content reduces radiation tolerance of both cubic and trigonal phases.
Plasmonic heating by nanoparticles has been used to promote a range of chemical reactions. Now, thermoplasmonic activation has been applied to latent ruthenium catalysts, enabling olefin metathesis initiated by visible and infrared light. Additionally, the desire to harness light to drive chemical transformations has surely existed as long as the study of chemistry itself. In the earliest documented applications, light was used simply as a heat source — for example, in the distillation of liquids. Since that time, our knowledge of how light and matter interact has increased exponentially, with greater mechanistic and molecular understanding enabling modern photochemists to design molecules with a myriad of finely tuned optical properties for catalysis, biochemistry, optoelectronics and more. Nonetheless, the design and optimization of molecules to achieve specific optical properties is still challenging, and for some applications, a return to the ‘simplest’ transformation — that of light to heat — can offer a more efficient approach to achieve light-mediated chemical reactions. Now, writing in Nature Chemistry, Yossi Weizmann and colleagues describe a strategy for organic and polymer synthesis driven by the conversion of light to heat.
The Sandia National Laboratories, in California (Sandia/CA) is a research and development facility, owned by the U.S. Department of Energy’s National Nuclear Security Administration agency (DOE/NNSA). The laboratory is located in the City of Livermore (the City) and is comprised of approximately 410 acres. The Sandia/CA facility is operated by National Technology and Engineering Solutions of Sandia, LLC (NTESS) under a contract with the DOE/NNSA. The DOE/ NNSA’s Sandia Field Office (SFO) oversees the operations of the site. North of the Sandia/CA facility is the Lawrence Livermore National Laboratory (LLNL), in which Sandia/CA’s sewer system combines with before discharging to the City’s Publicly Owned Treatment Works (POTW) for final treatment and processing. The City’s POTW authorizes the wastewater discharge from Sandia/CA via the assigned Wastewater Discharge Permit #1251 (the Permit), which is issued to the DOE/NNSA’s main office for Sandia National Laboratories, located in New Mexico (Sandia/NM). The Permit requires the submittal of this Monthly Sewer Monitoring Report to the City by the twenty-fifth day of each month.
Radiation-hard high-voltage vertical GaN p-n diodes are being developed for use in power electronics subjected to ionizing radiation. We present a comparison of the measured and simulated photocurrent response of diodes exposed to ionizing irradiation with 70 keV and 20 MeV electrons at dose rates in the range of 1.4× 107 - 5.0× 108 rad(GaN)/s. The simulations correctly predict the trend in the measured steady-state photocurrent and agree with the experimental results within a factor of 2. Furthermore, simulations of the transient photocurrent response to dose rates with uniform and non-uniform ionization depth profiles uncover the physical processes involved that cannot be otherwise experimentally observed due to orders of magnitude larger RC time constant of the test circuit. The simulations were performed using an eXploratory Physics Development code developed at Sandia National Laboratories. The code offers the capability to include defect physics under more general conditions, not included in commercially available software packages, extending the applicability of the simulations to different types of radiation environments.
This report describes the creation process and final content of a spectral irradiance dataset for Albuquerque, New Mexico accompanied by a set of spectral response measurements for modules deployed at the same location. The spectral irradiance measurements were made using horizontally mounted spectroradiometers; therefore, they represent global horizontal irradiance. The dataset combines non-continuous spectroradiometer and weather measurements from a two-year period into a single calendar year. The data files are accompanied by extensive metadata as well as example calculations and graphs to demonstrate the potential uses of this database. The spectral response measurements were carried out by the National Renewable Energy Laboratory using 12 commercial silicon modules types that are undergoing long-term evaluation at Sandia National Laboratories in Albuquerque.
This report describes the structure and content of an open dataset created for the purpose of testing and validating PV module temperature prediction models and their parameters. The dataset contains the main environmental parameters that affect temperature: irradiance, ambient temperature, wind speed and down-welling infrared radiation, as well as measured back-of-module temperature.
The SALSA3D project aims to improve our models used in travel time prediction. The current version uses tomographic modeling for propagation through the Earth’s mantle because of the large number (order of millions) of observations of seismic phases which primarily traverse the Earth’s mantle and the ability to pose the travel time problem as a set of linear equations. However, all seismic rays traverse the crust to reach receivers at the surface and therefore models of propagation through the crust are required. Therefore, the primary motivation for this study is to explore how to increase the scope of the SALSA3D project to phases which travel primarily through the crust. In this report, we evaluate new, machine learning based and physics-based methods to model these travel times for integration into the SALSA3D framework. Our results suggest that using our existing physics-based travel time tomography method is a viable approach for the regional to global scale, but better predictive capabilities can be achieved through a neural network trained on the region of interest for near-regional offsets. We suggest future iterations of SALSA3D should incorporate machine learning tools such as Physics-Informed Neural Networks or Bayesian Neural Networks.
The computational modeling of nearly incompressible materials is a difficult task for many numerical methods, and even after several decades of investigation, it is still an active research area. This report seeks to address the treatment of incompressible materials in meshfree methods using a synergistic combination of two treatments. The first treatment is an $\bar{F}$ method, where the decomposed dilatational and deviatoric parts are calculated over different smoothing domains. The second treatment “activates” additional nodes throughout the domain to increase the flexibility of the model. We implement this synergistic combination in the context of the reproducing kernel particle method (RKPM) and present results for the Cook’s membrane benchmark problem. The results are compared with those using the composite tet10 finite element with a volume-averaged J formulation. We show that the combined treatment is an effective way to deal with nearly incompressible materials in a meshfree framework and compares well with other highly-effective treatments.
Software reverse engineering (RE) requires analysts to closely read and make decisions about code. Little is known about what makes an analyst successful, making it difficult to train new analysts or design tools to augment existing ones. The goal of this project was to quantify the eye movement behaviors supporting RE and code comprehension more generally. We applied eye-tracking methods from the language comprehension literature to understand where analysts direct their attention over time when completing tasks (e.g., function identification, bug detection). Across three studies, we manipulated aspects of code hypothesized to impact comprehension (e.g., variable name meaningfulness, code complexity) and presentation methods (e.g., line-by-line, free viewing, gaze-contingent moving window) to understand effects on accuracy and gaze patterns. Results showed clear benefits of meaningful variable names, and effects of expertise on global and line-specific viewing patterns. Findings could inspire empirically-supported tool or analytic adaptations that help to reduce analyst workload.
Barekzi, Nazir; Wilkins, Meagan N.; Williams, Aumon L.; Moore, Afiya J.; Duckett, Zachary R.; Tindall, Danielle M.; Eaddy, Donnetta R.; Johnson, Mary B.; Bass, Malcolm; Mageeney, Catherine M.
Bassalto is a newly isolated phage of Mycobacterium smegmatis mc2155 from the campus grounds of Norfolk State University in Norfolk, VA. Bassalto belongs to the cluster B and subcluster B3 mycobacteriophages, based on the nucleotide composition and comparison to known mycobacteriophages.
For computational physics simulations, code verification plays a major role in establishing the credibility of the results by assessing the correctness of the implementation of the underlying numerical methods. In computational electromagnetics, surface integral equations, such as the method-of-moments implementation of the magnetic-field integral equation, are frequently used to solve Maxwell's equations on the surfaces of electromagnetic scatterers. These electromagnetic surface integral equations yield many code-verification challenges due to the various sources of numerical error and their possible interactions. In this paper, we provide approaches to separately measure the numerical errors arising from these different error sources. We demonstrate the effectiveness of these approaches for cases with and without coding errors.
Lankiewicz, Thomas S.; Choudhary, Hemant; Gao, Yu; Amer, Bashar; Lillington, Stephen P.; Leggieri, Patrick A.; Brown, Jennifer L.; Swift, Candice L.; Lipzen, Anna; Na, Hyunsoo; Amirebrahimi, Mojgan; Theodorou, Michael K.; Baidoo, Edward E.K.; Barry, Kerrie; Grigoriev, Igor V.; Timokhin, Vitaliy I.; Gladden, John M.; Singh, Seema S.; Mortimer, Jenny C.; Ralph, John; Simmons, Blake A.; Singer, Steven W.; O'Malley, Michelle A.
Lignocellulose forms plant cell walls, and its three constituent polymers, cellulose, hemicellulose and lignin, represent the largest renewable organic carbon pool in the terrestrial biosphere. Insights into biological lignocellulose deconstruction inform understandings of global carbon sequestration dynamics and provide inspiration for biotechnologies seeking to address the current climate crisis by producing renewable chemicals from plant biomass. Organisms in diverse environments disassemble lignocellulose, and carbohydrate degradation processes are well defined, but biological lignin deconstruction is described only in aerobic systems. It is currently unclear whether anaerobic lignin deconstruction is impossible because of biochemical constraints or, alternatively, has not yet been measured. We applied whole cell-wall nuclear magnetic resonance, gel-permeation chromatography and transcriptome sequencing to interrogate the apparent paradox that anaerobic fungi (Neocallimastigomycetes), well-documented lignocellulose degradation specialists, are unable to modify lignin. We find that Neocallimastigomycetes anaerobically break chemical bonds in grass and hardwood lignins, and we further associate upregulated gene products with the observed lignocellulose deconstruction. These findings alter perceptions of lignin deconstruction by anaerobes and provide opportunities to advance decarbonization biotechnologies that depend on depolymerizing lignocellulose.
We report ion trapping in crystalline domains of electrochemical transistors can be used to create a device capable of both volatile and non-volatile operation.
In this report, we developed and validated a network protector relay digital twin model and interfaced a commonly used network protector relay hardware with our real-time simulation system. Hardware-in-the-loop protection studies are performed to assess the impact of distributed energy resources (DER) and benchmark a rate-of-change-based mitigation strategy. Simulation results suggest that the network protector reverse trip and auto-reclose functions are negatively impacted by the high distributed energy resource penetration. To accommodate DER backfeed while remaining secure and reliable for faults on primary feeders, we recommend options for a rate-of-change-based blocking scheme and a protection setting change. Finally, future mitigation ideas and standard revisions are discussed.
