Anomalous proximity effects at the interface of s- and s±- superconductors
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phonons, thermal conductivity, energy storage (inc↗
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Results for “PROXIMITY”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Implications of z ~ 6 Quasar Proximity Zones for the Epoch of Reionization and Quasar Lifetimes
In this paper, we study quasar proximity zones in the redshift range $5.77\leqslant z\leqslant 6.54$ by homogeneously analyzing 34 medium-resolution spectra, encompassing both archival and newly obtained data, and exploiting recently updated systemic redshift and magnitude measurements. Whereas previous studies found strong evolution of proximity zone sizes with redshift and argued that this provides evidence for a rapidly evolving intergalactic medium (IGM) neutral fraction during reionization, we measure a much shallower trend $\propto {(1+z)}^{-1.44}$. We compare our measured proximity zone sizes to predictions from hydrodynamical simulations post-processed with one-dimensional radiative transfer and find good agreement between observations and theory, irrespective of the ionization state of the ambient IGM. This insensitivity to IGM ionization state has been previously noted, and results from the fact that the definition of proximity zone size as the first drop of the smoothed quasar spectrum below the 10% flux transmission level probes locations where the ionizing radiation from the quasar is an order of magnitude larger than the expected ultraviolet ionizing background that sets the neutral fraction of the IGM. Our analysis also uncovered three objects with exceptionally small proximity zones (two have ${R}_{p}\lt 1$ proper Mpc), which constitute outliers from the observed distribution and are challenging to explain with our radiative transfer simulations. Finally, we consider various explanations for their origin, such as strong absorption line systems associated with the quasar or patchy reionization, but find that the most compelling scenario is that these quasars have been shining for ≲10 5 years.
79 ASTRONOMY AND ASTROPHYSICS↗
Distribution of Supercurrent Switching in Graphene under the Proximity Effect
Not Available
Coskun, U. C.↗
Modeling tunneling for the unconventional superconducting proximity effect
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phonons, thermal conductivity, energy storage (inc↗
Test of the CLAS12 RICH large-scale prototype in the direct proximity focusing configuration
A large-area ring-imaging Cherenkov detector has been designed to provide clean hadron identi- fication capability in the momentum range from 3 GeV/c up to 8 GeV/c for the CLAS12 experiment at the upgraded 12 GeV continuous electron beam accelerator facility of Jefferson Laboratory. The adopted solution foresees a novel hybrid optics design based on aerogel radiator, composite mirrors and highly packed and highly segmented photon detectors. Cherenkov light will either be imaged directly (forward tracks) or after two mirror reflections (large-angle tracks). We report here the results of the tests of a large-scale prototype of the RICH detector performed with the hadron beam of the CERN T9 experimental hall for the direct detection configuration. The tests demonstrated that the proposed design provides the required pion-to-kaon rejection factor of 1 : 500 in the whole momentum range.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Integrated proximity, contact and force sensing using elastomer-embedded commodity proximity sensors
Here, we describe a combined proximity, contact and force (PCF) sensor based on a commodity infrared distance sensor embedded in a transparent elastomer with applications in robotic manipulation. Prior to contact, the sensor works as a distance sensor, whereas after contact the elastomer magnifies the near field of the proximity sensors letting the sensor interpret the indentation on elastomer as force. Contact occurs at the transition of proximity and force. We describe in detail the sensor design, its principle of operation and experimentally characterize the design parameters including polymer thickness, its mixing ratio, and emitter current of the infrared sensor. We also show that the sensor response has an inflection point at contact that is independent of an object’s surface properties, making it a robust detector for contact events. We finally demonstrate a series of use cases for the proposed PCF sensor, including (1) improving pre-grasp alignment, (2) determining contact event with objects, (3) obtaining simple 3D point cloud models of objects using both proximity and contact, and (4) registering self-generated point clouds to those from a RGB-D camera using a Baxter robot and Kinova Jaco arm.
42 ENGINEERING↗
The ATPase mechanism of UvrA[subscript 2] reveals the distinct roles of proximal and distal ATPase s
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Case, Brandon C.↗
Toward a scalable robust security-constrained optimal power flow using a proximal projection bundle method
Robust security-constrained optimal power flow (rSCOPF) aims to find the worst-case contingencies of alternating current optimal power flow (ACOPF) in power systems. With the rise of GPU architectures on the upcoming supercomputer architectures, optimization algorithms that rely on sparse linear algebra and indefinite linear systems are becoming increasingly hard to solve efficiently (e.g. interior-point method). To address this we revisit a maximin optimization formulation of the rSCOPF and the single-level mixed-integer semidefinite programming (MISDP) reformulation, which is obtained by taking the Lagrangian relaxation of the inner minimization ACOPF problem. In this paper, we focus on the development of a proximal projection bundle method (PPBM) for solving continuous relaxation node subproblems of the MISDP problem, based primarily on the well-known alternating direction method of multipliers. Cutting planes reminiscent of bundle method ideas are also applied in coordination with updates of the proximal parameter. The cutting-plane method can generate a large number of linear inequalities, leading to a large scale but decomposable quadratic programming (QP) subproblem that is amenable to GPUs. We present the numerical results on the IEEE 30, 57, 118, and 300-bus systems by using our PBMM method. We discuss the main computational bottleneck of our method, which is the time taken to solve each iteration of a QP subproblem instance of the PPBM, and how GPU architectures can accelerate this solution process.
bundle method↗
Local imaging of diamagnetism in proximity-coupled niobium nanoisland arrays on gold thin films.
In this work, we study the effect of engineered disorder on the local magnetic response of proximity-coupled superconducting island arrays by comparing scanning superconducting quantum interference device (SQUID) susceptibility measurements to a model in which we treat the system as a network of one-dimensional (1D) superconductor-normal-metal-superconductor Josephson junctions, each with a Josephson coupling energy E-J determined by the junction length or distance between islands. We find that the disordered arrays exhibit a spatially inhomogeneous diamagnetic response which, for low local applied magnetic fields, is well described by this junction network model, and we discuss these results as they relate to inhomogeneous 2D superconductors. Our model of the static magnetic response of the arrays does not fully capture the onset of nonlinearity and dissipation with increasing applied field, as these effects are associated with vortex motion due to the dynamic nature of the scanning SQUID susceptometry measurement. This work demonstrates a model 2D superconducting system with engineered disorder, and it highlights the impact of dissipation on the local magnetic properties of 2D superconductors and Josephson junction arrays.
Bishop-Van Horn, Logan↗
Proximity fingerprint of s ± -superconductivity
We suggest a straightforward and unambiguous test to identify possible opposite signs of the superconducting order parameter in different bands proposed for iron-based superconductors (s±-state). We consider the proximity effect in a weakly coupled sandwich composed of a s±-superconductor and a thin layer of the s-wave superconductor. In such system the s-wave order parameter is coupled differently with different s±-gaps and it typically aligns with one of these gaps. This forces the other s±-gap to be anti-aligned with the s-wave gap. In such situation the aligned band induces a peak in the s-wave density of states (DoS), while the anti-aligned band induces a dip. Observation of such contact-induced negative feature in the s-wave DoS would provide a definite proof for s±-superconductivity.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Data for A Hybrid Biophysical-Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing
Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.
AI/ML↗
Triangular Elastomeric Stamps for Optical Applications: Near-Field Phase Shift Photolithography, 3D Proximity Field Patterning, Embossed Antireflective Coatings, and SERS Sensing
The use of a decal transfer lithography technique to fabricate elastomeric stamps with triangular cross-sections, specifically triangular prisms and cones, is described. These stamps are used in demonstrations for several prototypical optical applications, including the fabrication of multiheight 3D photoresist patterns with near zero-width features using near-field phase shift lithography, fabrication of periodic porous polymer structures by maskless proximity field nanopatterning, embossing thin-film antireflection coatings for improved device performance, and efficient fabrication of substrates for surface-enhanced Raman spectroscopic sensing. Furthermore, the applications illustrate the utility of the triangular poly(dimethylsiloxane) decals for a wide variety of optics-centric applications, particularly those that exploit the ability of the designed geometries and materials combinations to manipulate light–matter interactions in a predictable and controllable manner.
36 MATERIALS SCIENCE↗
Proximity Spin–Orbit Torque on a Two-Dimensional Magnet within van der Waals Heterostructure: Current-Driven Antiferromagnet-to-Ferromagnet Reversible Nonequilibrium Phase Transition in Bilayer CrI 3
The recently discovered two-dimensional magnetic insulator CrI 3 is an intriguing case for basic research and spintronic applications since it is a ferromagnet in the bulk but an antiferromagnet in bilayer form, with its magnetic ordering amenable to external manipulations. Using the first-principles quantum transport approach, we predict that injecting unpolarized charge current parallel to the interface of the bilayer-CrI 3 /monolayer-TaSe 2 van der Waals (vdW) heterostructure will induce spin–orbit torque and thereby drive the dynamics of magnetization on the first monolayer of CrI 3 in direct contact with TaSe 2 . By combining the calculated complex angular dependence of spin–orbit torque with the Landau-Lifshitz-Gilbert equation for classical dynamics of magnetization, we demonstrate that current pulses can switch the direction of magnetization on the first monolayer to become parallel to that of the second monolayer, thereby converting CrI 3 from antiferromagnet to ferromagnet while not requiring any external magnetic field. We explain the mechanism of this reversible current-driven nonequilibrium phase transition by showing that first monolayer of CrI 3 carries current due to evanescent wave functions injected by metallic transition metal dichalcogenide TaSe 2 , while concurrently acquiring strong spin–orbit coupling via such a proximity effect, whereas the second monolayer of CrI 3 remains insulating. Furthermore, the transition can be detected by passing vertical read current through the vdW heterostructure, encapsulated by a bilayer of hexagonal boron nitride and sandwiched between graphite electrodes, where we find a tunneling magnetoresistance of ≃240%.
2D magnetic materials↗
A proximity‐based image‐processing algorithm for colloid assignment in segmented multiphase flow datasets
Summary Colloidal transport and deposition are of both environmental and engineering importance. Easier access to x‐ray microtomography (XMT) coupled with improved imaging resolution has made XMT a unique and viable tool for visualizing and quantifying these processes. Currently, there is scant information in the literature addressing colloid segmentation and analysis in saturated and unsaturated porous media, in particular related to spatial partitioning of colloids. To support this need, an approach to assign segmented colloidal particles and aggregates to different partitioning classes based on their proximity to different phases is presented here. The method uses different markers for each attachment site (e.g. wetting‐nonwetting phase interfaces). An example XMT dataset from a drainage experiment is used to demonstrate the efficacy of the image processing algorithms. Flow conditions, and fluid and colloid properties, can thus be compared to the behaviour of colloids within the porous medium. This algorithm can help elucidate colloidal deposition mechanisms and the importance of different attachment sites, explore the importance of fluid properties, as well as the arrangement and shape of the colloids.
BRUECK, C. L.↗