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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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We report low-energy proton and alpha particle SEE data on a 32 nm silicon-on-insulator (SOI) complementary metal oxide semiconductor (CMOS) static random access memory (SRAM) that demonstrates the criticality of understanding and using low-energy protons for SEE testing of highly-scaled technologies
The development of superconducting electronics based on nanocryotrons has been limited so far to few device circuits, in part due to the lack of standard and robust logic cells. Here, we introduce and experimentally demonstrate designs for a set of nanocryotron-based building blocks that can be configured and combined to implement memory and logic functions. The devices were fabricated by patterning a single superconducting layer of niobium nitride and measured in liquid helium on a wide range of operating points. The tests show 10 - 4 bit error rates with above ± 20 % margins up to 50 MHz and the possibility of operating under the effect of an out-of-plane 36 mT magnetic field, with ± 30 % margins at 10 MHz. Additionally, we designed and measured an equivalent delay-flip-flop made of two memory cells to show the possibility of combining multiple building blocks to make larger circuits. These blocks may constitute a solid foundation for the development of nanocryotron logic circuits and finite-state machines with potential applications in the integrated processing and control of superconducting nanowire single-photon detectors.
Microencapsulated phase change materials are being studied for applications for thermal energy storage in concentrated solar fields. During fabrication, the thickness of the encapsulation cannot be readily measured for real-time control. Therefore, a machine learning network, specifically a Long Short-Term Memory network, is being developed to estimate the ratio of the shell radius to core radius based on a one second temperature history. The mini-batch size determines how often the algorithm weights are updated during network training, and shuffle indicates whether the training data is shuffled during training. A general factorial design is used to analyze the effects of varying mini-batch size and shuffle, along with the core-to-shell ratio, on the RMSE of the response from the Long Short-Term Memory network. It was found that the network performed better for smaller core to shell ratios (less than 0.6) and had the lowest RMSE when the minibatch size was 128. The minimum RMSE found was 0.00501.
Hafnium oxide based ferroelectric thin films have shown potential as a promising alternative material for non-volatile memory applications. This work reports the switching stability of a Si-doped HfO{sub 2} film under bipolar pulsed-field operation. High field cycling causes a “wake-up” in virgin “pinched” polarization hysteresis loops, demonstrated by an enhancement in remanent polarization and a shift of negative coercive voltage. The rate of wake-up is accelerated by either reducing the frequency or increasing the amplitude of the cycling field. We suggest de-pinning of domains due to reduction of the defect concentration at bottom electrode interface as origin of the wake-up.
Evidence has accumulated over the past 15 years that affect in humans is cyclical. In winter there is a tendency to depression, with remission in summer, and this effect is stronger at higher latitudes. In order to determine whether human cognition is similarly rhythmical, this study investigated the cognitive processes of 100 participants living at 69 degrees N. Participants were tested in summer and winter on a range of cognitive tasks, including verbal memory, attention and simple reaction time tasks. The seasonally counterbalanced design and the very northerly latitude of this study provide optimal conditions for detecting impaired cognitive performance in winter, and the conclusion is negative: of five tasks with seasonal effects, four had disadvantages in summer. Like the menstrual cycle, the circannual cycle appears to influence mood but not cognition.
The effect of annealing on the exchange stiffness of ultrathin CoFeB films with perpendicular magnetic anisotropy was investigated through the observation of magnetic domain structures by magneto-optic Kerr-effect microscopy. A significant reduction of the exchange stiffness after an annealing process was observed, which is in striking contrast to a previous report that studied thick CoFeB films with in-plane magnetic anisotropy. Our results suggest that interdiffusion of non-magnetic atoms from the adjacent layer into CoFeB layer reduces the exchange stiffness, which explains the difference between the annealing effect on ultrathin and the thick CoFeB films. Thus, it is critical to prevent annealing-induced interdiffusion in order to suppress undesired sub-volume switching that degrades thermal stability of a free-layer in spin-transfer torque magnetic random access memory.
We investigate effect of the mechanical stress on the performance of magnetic tunnel junctions with perpendicular magnetic anisotropy. We developed a 4-point bending setup that allows us to apply a constant stress over a large substrate area with access to electrical measurements and an external magnetic field. This setup enables us to measure key device performance parameters, such as tunnel magnetoresistance, switching current ( I c 50 % ), and thermal stability (Δ), as a function of applied stress. Finally, we find that variations in these parameters are negligible: less than 2% over the entire measured range between the zero stress condition and the maximum stress at the point of wafer breakage.
We present a CPU–GPU system for runtime acceleration of large molecular simulations using GPU computation and memory swaps. The memory architecture of the GPU can be used both as container for simulation data stored on the graphics card and as floating-point code target, providing an effective means for the manipulation of atomistic or molecular data on the GPU. To fully take advantage of this mechanism, efficient GPU realizations of algorithms used to perform atomistic and molecular simulations are essential. Our system implements a versatile molecular engine, including inter-molecule interactions and orientational variables for performing the Metropolis Monte Carlo (MMC) algorithm, which is one type of Markov chain Monte Carlo. By combining memory objects with floating-point code fragments we have implemented an MMC parallel engine that entirely avoids the communication time of molecular data at runtime. Our runtime acceleration system is a forerunner of a new class of CPU–GPU algorithms exploiting memory concepts combined with threading for avoiding bus bandwidth and communication. The testbed molecular system used here is a condensed phase system of oligopyrrole chains. A benchmark shows a size scaling speedup of 60 for systems with 210,000 pyrrole monomers. Our implementation can easily be combined with MPI to connect in parallel several CPU–GPU duets. -- Highlights: •We parallelize the Metropolis Monte Carlo (MMC) algorithm on one CPU—GPU duet. •The Adaptive Tempering Monte Carlo employs MMC and profits from this CPU—GPU implementation. •Our benchmark shows a size scaling-up speedup of 62 for systems with 225,000 particles. •The testbed involves a polymeric system of oligopyrroles in the condensed phase. •The CPU—GPU parallelization includes dipole—dipole and Mie—Jones classic potentials.
Abstract Artificial atom qubits in diamond have emerged as leading candidates for a range of solid-state quantum systems, from quantum sensors to repeater nodes in memory-enhanced quantum communication. Inversion-symmetric group IV vacancy centers, comprised of Si, Ge, Sn, and Pb dopants, hold particular promise as their neutrally charged electronic configuration results in a ground-state spin triplet, enabling long spin coherence above cryogenic temperatures. However, despite the tremendous interest in these defects, a theoretical understanding of the electronic and spin structure of these centers remains elusive. In this context, we predict the ground-state and excited-state properties of the neutral group IV color centers from first principles. We capture the product Jahn–Teller effect found in the excited state manifold to second order in electron–phonon coupling, and present a nonperturbative treatment of the effect of spin–orbit coupling. Importantly, we find that spin–orbit splitting is strongly quenched due to the dominant Jahn–Teller effect, with the lowest optically-active 3 E u state weakly split into m s -resolved states. The predicted complex vibronic spectra of the neutral group IV color centers are essential for their experimental identification and have key implications for use of these systems in quantum information science.
Plug-and-play priors (PnP) is a broadly applicable methodology for solving inverse problems by exploiting statistical priors specified as denoisers. Recent work has reported the state-of-the-art performance of PnP algorithms using pre-trained deep neural nets as denoisers in a number of imaging applications. However, current PnP algorithms are impractical in large-scale settings due to their heavy computational and memory requirements. This work addresses this issue by proposing an incremental variant of the widely used PnP-ADMM algorithm, making it scalable to problems involving a large number measurements. Here, we theoretically analyze the convergence of the algorithm under a set of explicit assumptions, extending recent theoretical results in the area. Additionally, we show the effectiveness of our algorithm with nonsmooth data-fidelity terms and deep neural net priors, its fast convergence compared to existing PnP algorithms, and its scalability in terms of speed and memory.
Major risks associated with radiation exposures on deep space missions include carcinogenesis due to heavy-particle exposure of cancer-prone tissues and performance decrements due to neurological damage produced by heavy particles. Because exposure to heavy particles can cause oxidative stress, it is possible that antioxidants can be used to mitigate these risks (and possibly some health risks of microgravity). To assess the capacity of antioxidant diets to mitigate the effects of exposure to heavy particles, rats were maintained on antioxidant diets containing 2% blueberry or strawberry extract or a control diet for 8 weeks prior to exposure to 1.5 or 2.0 Gy of accelerated iron particles at Brookhaven National Laboratory. Following irradiation rats were tested on a series of behavioral tasks: amphetamine-induced taste aversion learning, operant responding and spatial learning and memory. The results indicated that the performance of the irradiated rats maintained on the antioxidant diets was, in general, significantly better than that of the control animals, although the effectiveness of the diets ameliorating the radiation-induced deterioration in performance varied as a function of both the specific diet and the specific endpoint. In addition, animals fed antioxidant diets prior to exposure showed reduced heavy particle-induced tumorigenesis one year after exposure compared to the animals fed the control diet. These results suggest that antioxidant diets have the potential to serve as part of a system designed to provide protection to astronauts against the effects of heavy particles on exploratory missions outside the magnetic field of the earth.
In a small fraction of magnetic-tunnel-junction-based magnetic random-access memory devices with in-plane free layers, the write-error rates (WERs) are higher than expected on the basis of the macrospin or quasi-uniform magnetization reversal models. In devices with increased WERs, the product of effective resistance and area, tunneling magnetoresistance, and coercivity do not deviate from typical device properties. However, the field-swept, spin-torque, ferromagnetic resonance (FS-ST-FMR) spectra with an applied DC bias current deviate significantly for such devices. With a DC bias of 300 mV (producing 9.9 × 10{sup 6} A/cm{sup 2}) or greater, these anomalous devices show an increase in the fraction of the power present in FS-ST-FMR modes corresponding to higher-order excitations of the free-layer magnetization. As much as 70% of the power is contained in higher-order modes compared to ≈20% in typical devices. Additionally, a shift in the uniform-mode resonant field that is correlated with the magnitude of the WER anomaly is detected at DC biases greater than 300 mV. These differences in the anomalous devices indicate a change in the micromagnetic resonant mode structure at high applied bias.
We reformulate the scattering amplitudes of 4D at space gauge theory and gravity in the language of a 2D CFT on the celestial sphere. The resulting CFT structure exhibits an OPE constructed from 4D collinear singularities, as well as infinite-dimensional Kac-Moody and Virasoro algebras encoding the asymptotic symmetries of 4D at space. We derive these results by recasting 4D dynamics in terms of a convenient foliation of flat space into 3D Euclidean AdS and Lorentzian dS geometries. Tree-level scattering amplitudes take the form of Witten diagrams for a continuum of (A)dS modes, which are in turn equivalent to CFT correlators via the (A)dS/CFT dictionary. The Ward identities for the 2D conserved currents are dual to 4D soft theorems, while the bulk-boundary propagators of massless (A)dS modes are superpositions of the leading and subleading Weinberg soft factors of gauge theory and gravity. In general, the massless (A)dS modes are 3D Chern-Simons gauge fields describing the soft, single helicity sectors of 4D gauge theory and gravity. Consistent with the topological nature of Chern-Simons theory, Aharonov-Bohm effects record the \tracks" of hard particles in the soft radiation, leading to a simple characterization of gauge and gravitational memories. Soft particle exchanges between hard processes define the Kac-Moody level and Virasoro central charge, which are thereby related to the 4D gauge coupling and gravitational strength in units of an infrared cutoff. Lastly, we discuss a toy model for black hole horizons via a restriction to the Rindler region.
Fast read-out of two to six charges per dot from the ground and first excited state in a quantum dot (QD)-based memory is demonstrated using a two-dimensional electron gas. Single-shot measurements on modulation-doped field-effect transistor structures with embedded InAs/GaAs QDs show read-out times as short as 3 ns. At low temperature (T = 4.2 K) this read-out time is still limited by the parasitics of the setup and the device structure. Faster read-out times and a larger read-out signal are expected for an improved setup and device structure.
We report an investigation of electric-field (EF) control of spin re-orientation as functions of the thicknesses of CoFeB free layer (FL) and MgO layer in synthetic-antiferromagnetic pinned magnetic tunnel junctions with perpendicular magnetic anisotropy. It is found that the EF modulates the coercivity (Hc) of the FL almost linearly for all FL thicknesses, while the EF efficiency, i.e., the slope of the linearity, increases as the FL thickness increases. This linear variation in Hc is also observed for larger MgO thicknesses (≥1.5 nm), while the EF efficiency increases only slightly from 370 to 410 Oe nm/V when MgO thickness increases from 1.5 to 1.76 nm. We have further observed the absence of quasi-DC unipolar switching. We discuss its origin and highlight the underlying challenges to implement the EF controlled switching in a practical magnetic memory.
Silicon on insulator (SOI)-based transistors gated by nanogranular SiO{sub 2} proton conducting electrolytes were fabricated to mimic synapse behaviors. This SOI-based device has both top proton gate and bottom buried oxide gate. Electrical transfer properties of top proton gate show hysteresis curves different from those of bottom gate, and therefore, excitatory post-synaptic current and paired pulse facilitation (PPF) behavior of biological synapses are mimicked. Moreover, we noticed that PPF index can be effectively tuned by the spike interval applied on the top proton gate. Synaptic behaviors and functions, like short-term memory, and its properties are also experimentally demonstrated in our device. Such SOI-based electronic synapses are promising for building neuromorphic systems.
The possibility of implementing an off-resonant Raman scheme of optical quantum memory on the basis of an ensemble of three-level atoms is investigated under the condition of equal polarisations of resonant transitions forming the Λ-scheme. The developed model is used to analyse the signal-to-noise ratio at the output of an optical quantum memory device in {sup 143}Nd{sup 3+} : Y {sup 7}LiF{sub 4}. It is shown that this ratio can significantly exceed unity for single-photon input pulses. The required values of the parameters can be obtained by using an impurity crystal in the form of a whispering-gallery mode ring resonator. (paper)
Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk, the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.