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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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First-in/first-out (FIFO) temporarily stores short surges of data generated by data-acquisition system at excessively high rate and releases data at lower rate suitable for processing by computer. Size and complexity reduced while capacity enhanced by use of newly developed, sophisticated integrated circuits and by "byte-folding" scheme doubling effective depth and data rate.
Epitaxial YBa2Cu3O7 films were grown on several microwave substrates. Surface resistance and penetration depth measurements were performed to determine the quality of these films. Here the properties of these films on key microwave substrates are described. The fabrication and characterization of a microwave ring resonator circuit to determine transmission line losses are presented. Lower losses than those observed in gold resonator circuits were observed at temperatures lower than critical transition temperature. Based on these results, potential applications of microwave superconducting circuits such as filters, resonators, oscillators, phase shifters, and antenna elements in space communication systems are identified.
Epitaxial YBa2Cu3O7 films were grown on several microwave substrates. Surface resistance and penetration depth measurements were performed to determine the quality of these films. Here, the properties of these films on key microwave substrates are described. The fabrication and characterization of a microwave ring resonator circuit to determine transmission line losses are presented. Lower losses than those observed in gold resonator circuits were observed at temperatures lower than critical transition temperature. Based on these results, potential applications of microwave superconducting circuits such as filters, resonators, oscillators, phase shifters, and antenna elements in space communication systems are identified.
The quantum approximate optimization algorithm (QAOA) has been put forth as a method for near-term quantum computers to solve optimization problems. However, assessments of QAOA performance have mostly focused on small structured problem instances while performance on more general instances is less clear. Here, we numerically simulate QAOA pure state dynamics for every instance of MaxCut on non-isomorphic unweighted graphs with nine or fewer vertices with depth parameters p ≤ 3. We find the approximation ratios and optimized circuit parameters concentrate across graphs of a given size and empirically show increases in concentration as graph size increases. The parameter concentration leads to two median-angle heuristics that overcome difficulties in QAOA parameter optimization and obtain mean approximation ratios within 3% and 0.2% of the optimal. We also analyze the probability to measure an optimal solution and find increasing variations between graphs as depth increases, in stark contrast to the approximation ratios which concentrate as depth increases. Furthermore, the resulting benchmark data set gives empirical bounds for on-going experimental realizations and lays groundwork for theoretical extensions to greater problem sizes and depths where QAOA may prove important for practically relevant problems.
A study was undertaken to examine the capacity maintenance features of SUPER nickel-cadmium cells when stored for extended periods to determine whether the features change when the same kinds of positive plates as that used in nickel-hydrogen cells are used, The cells maintained their capacity when stored at 0 C in the discharged state and at 0 C in the charged state by continuously trickle charging. There was a capacity loss when stored in the open-circuit condition at 28 C. A cycling test at 17% depth of discharge for 2400 cycles using cells stored at various conditions showed that cells maintained good end of discharge voltage regardless of their storage history. However, the EOD voltages of stored cells were lower by 10 mV compared to those of fresh cells. The capacity at the end of the cycling test decreased for the stored cells by 2-7 Ah. The storage related capacity loss is lower for SUPER Ni-Cd cells compared to that of Ni-H2 cells containing a hydrogen precharge. The results suggest the pivotal role of hydrogen pressure in the capacity loss phenomenon.
Mathematical models of the common-source and common-gate amplifiers using metal-ferroelectric- semiconductor field effect transistors (MOSFETs) are developed in this paper. The models are compared against data collected with MOSFETs of varying channel lengths and widths, and circuit parameters such as biasing conditions are varied as well. Considerations are made for the capacitance formed by the ferroelectric layer present between the gate and substrate of the transistors. Comparisons between the modeled and measured data are presented in depth as well as differences and advantages as compared to the performance of each circuit using a MOSFET.
Recent calculations by Wang et al. (1974) have shown that the short-circuit current for silicon solar cells is sensitive to the impurity distribution in the diffused and base region. In the present work, these theoretical results were verified by experimentally investigating the impurity profile and sheet resistance of the diffused layers of (n+)-p silicon solar cells fabricated by normal diffusion processes and at subsequently various drive-in times. Impurity profiles of the n+ diffused layer, measured by differential Hall and resistivity technique, resemble the erfc distribution. The junction depth is larger as drive-in time increases. Measured short-circuit current is in agreement with calculated ones. Open-circuit voltage is independent of drive-in times, and its calculated values are consistent with capacitance-voltage measurements.
The short-circuit response of inverter-interfaced distributed generators (IIDGs) is not adequately represented in many conventional protection studies. This paper presents an in-depth analysis of IIDG behavior during grid faults and proposes a more accurate reduced-order parameterized short-circuit current (RPSC) model of inverters. Typical inverter components are thoroughly investigated to identify those that play dominant roles during faults. The paper shows that the current limiter is the dominant factor for the steady-state fault-current of inverter; while the inverter filter along with the severity of the voltage disturbance largely determine the initial transient spike of inverter fault current. The proposed model is low-order and can be used in large scale simulations. The parameters of the proposed RPSC model can be extracted from laboratory experiments without requiring proprietary manufacturer information. The proposed fault-current model is analogous to the well-known synchronous machine model that segregates the inverter fault current into subtransient, transient, and steady-state fault currents. Finally, experimental and simulation tests are presented to validate the model.
This review explores the intersection of bio-plausible artificial intelligence in the form of spiking neural networks (SNNs) with the analog in-memory computing (IMC) domain, highlighting their collective potential for low-power edge computing environments. Through detailed investigation at the device, circuit, and system levels, we highlight the pivotal synergies between SNNs and IMC architectures. Additionally, we emphasize the critical need for comprehensive system-level analyses, considering the inter-dependencies among algorithms, devices, circuit, and system parameters, crucial for optimal performance. An in-depth analysis leads to the identification of key system-level bottlenecks arising from device limitations, which can be addressed using SNN-specific algorithm–hardware co-design techniques. This review underscores the imperative for holistic device to system design-space co-exploration, highlighting the critical aspects of hardware and algorithm research endeavors for low-power neuromorphic solutions.
Approaches to compute or estimate the output probability distributions from the quantum approximate optimization algorithm (QAOA) are needed to assess the likelihood it will obtain a quantum computational advantage. We analyze output from QAOA circuits solving 7200 random MaxCut instances, with $n$ = 14–23 qubits and depth parameter $p$ ≤ 12 and find that the average basis state probabilities follow approximate Boltzmann distributions: The average probabilities scale exponentially with their energy (cut value), with a peak at the optimal solution. Furthermore, we describe the rate of exponential scaling or effective temperature in terms of a series with a leading-order term $T$ ~ $C$ min /$n$ $\sqrt{p}$, with $C$ min the optimal solution energy. Using this scaling, we generate approximate output distributions with up to 38 qubits and find these give accurate accounts of important performance metrics in cases we can simulate exactly.
Simulations of collisions of fundamental particles on a quantum computer are expected to have an exponential advantage over classical methods and promise to enhance searches for new physics. Furthermore, scattering in scalar field theory has been shown to be bounded-error quantum polynomial time (BQP) complete, making it a representative problem for which quantum computation is efficient. As a step toward large-scale quantum simulations of collision processes, scattering of wave packets in one-dimensional scalar field theory is simulated using 120 qubits of IBM’s Heron superconducting quantum computer ibm_fez. Variational circuits compressing vacuum preparation, wave packet initialization, and time evolution are determined using classical resources. By leveraging physical properties of states in the theory, such as symmetries and locality, the variational quantum algorithm constructs scalable circuits that can be used to simulate arbitrarily large system sizes. A new strategy is introduced to mitigate errors in quantum simulations, which enables the extraction of meaningful results from circuits with up to 4924 two-qubit gates and two-qubit gate depths of 103. The effect of interactions is clearly seen, and is found to be in agreement with classical matrix product state simulations. Finally, the developments that will be necessary to simulate high-energy inelastic collisions on a quantum computer are discussed.
Several tests of specially fabricated nickel-cadmium batteries having circular disk type electrodes were considered. These batteries were evaluated as filter elements between a constant current power supply and a five hertz pulsed load demanding approximately twice the power supply current during the load on portion of the cycle. Short tests lasting 10,000 cycles were conducted at up to a 21 C rate and an equivalent energy density of over 40 Joules per pound. In addition, two batteries were subjected to 10 to the 7 charge/discharge cycles, one at a 6.5 C rate and the other at a 13 C rate. Assuming an electrode to battery weight ratio of 0.5, these tests represent an energy density of about 7 and 14 Joules per pound respectively. Energy density, efficiency, capacitance, average voltage, and available capacity were tracked during these tests. After 10 to the 7 cycles, capacity degradation was negligible for one battery and about 20% for the other. Cadmium electrode failure may be the factor limiting lifetime at extremely low depth of discharge cycling. The output was examined and a simple equivalent circuit was proposed.
The design of a coplanar waveguide low-pass filter made of YBa2Cu3O(7-delta) (YBCO) on an LaAlO3 substrate is described. Measurements were incorporated into simple models for microwave CAD analysis to develop a final design. The patterned and packaged coplanar waveguide low-pass filter of YBCO, with dimensions suited for integrated circuits, exhibited measured insertion losses when cooled in liquid nitrogen superior to those of a similarly cooled thin-film copper filter throughout the 0 to 9.5 GHz passband. Coplanar waveguide models for use with thin-film normal metal (with thickness either greater or less than the skin depth) and YBCO are discussed and used to compare the losses of the measured YBCO and copper circuits.
Negatively precharged nickel hydrogen cells will experience a useable capacity loss during extended open circuit storage periods. Some of the lost capacity can be recovered through cycling. Capacity recovery through cycling can be enhanced by cycling at high depths of discharge (DOD). The most timely procedure for recovering the faded capacity is to charge the cell fully and allow the cell to sit open-circuit at room temperature. This procedure seems to be effective in part because of the enlarged structure of the active materials. The compounds that formed during storage at the low electrode potentials can more easily dissolve and redistribute. All of the original capacity cannot be recovered because the lattice structure of the active material is irreversibly altered during storage. The recommendation is to use positively precharged cells activated with 26 percent KOH if possible. In aerospace applications, the benefits of negative precharge are offset by the possibility of delays and storage periods.
Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimensional quantum circuits. Many attempts to close this gap have utilized classical simulations based on tensor network techniques, and their limitations shed light on the improvements to quantum hardware required to frustrate classical simulability. In particular, quantum computers having in excess of approximately 50 qubits are primarily vulnerable to classical simulation due to restrictions on their gate fidelity and their connectivity, the latter determining how many gates are required (and, therefore, how much infidelity is suffered) in generating highly entangled states. Here, we describe recent hardware upgrades to Quantinuum’s H2 quantum computer, enabling it to operate on up to 56 qubits with arbitrary connectivity and 99.843(5)% two-qubit gate fidelity. We define a class of circuits with random geometries that become hard to classically simulate in very low depth and implement them utilizing the flexible connectivity of H2. A careful analysis demonstrating the fast saturation of classical simulation complexity with depth indicates that H2 can yield data well beyond the reach of state-of-the art classical simulation methods at unprecedented fidelities. We find that the considerable difficulty of classically simulating H2 is likely limited only by qubit number, demonstrating the promise and scalability of the quantum charge-coupled device architecture as continued progress is made toward building larger machines. Published by the American Physical Society 2025
Concatenated bosonic-stabilizer codes have recently gained prominence as promising candidates for achieving low-overhead fault-tolerant quantum computing in the long term. In such systems, analog information obtained from the syndrome measurements of an inner bosonic code is used to inform decoding for an outer code layer consisting of a discrete-variable stabilizer code such as a surface code. The use of Quantum Low-Density Parity Check (QLDPC) codes as an outer code is of particular interest due to the significantly higher encoding rates offered by these code families, leading to a further reduction in overhead for large-scale quantum computing. Recent works have investigated the performance of QLDPC-GKP codes in detail, and the use of analog information from the inner code significantly boosts decoder performance. However, the noise models assumed in these works are typically limited to depolarizing or phenomenological noise. In this paper, we investigate the performance of QLDPC-GKP concatenated codes under circuit-level noise, based on a model introduced by Noh et al. in the context of the surface-GKP code. To demonstrate the performance boost from analog information, we investigate three scenarios: (a) decoding without soft information, (b) decoding with precomputed error probabilities but without real-time soft information, and (c) decoding with real-time soft information obtained from round-to-round decoding of the inner GKP code. Results show minimal improvement between (a) and (b), but a significant boost in (c), indicating that real-time soft information is critical for concatenated decoding under circuit-level noise. We also study the effect of measurement schedules with varying depths and show that using a schedule with minimum depth is essential for obtaining reliable soft information from the inner code.
Abstract Non‐von‐Neumann computing using neuromorphic systems based on two‐terminal resistive nonvolatile memory elements has emerged as a promising approach, but its full potential has not been realized due to the lack of materials and devices with the appropriate attributes. Unlike memristors, which require large write currents to drive phase transformations or filament growth, electrochemical random access memory (ECRAM) decouples the “write” and “read” operations using a “gate” electrode to tune the conductance state through charge‐transfer reactions, and every electron transferred through the external circuit in ECRAM corresponds to the migration of ≈1 ion used to store analogue information. Like static dopants in traditional semiconductors, electrochemically inserted ions modulate the conductivity by locally perturbing a host's electronic structure; however, ECRAM does so in a dynamic and reversible manner. The resulting change in conductance can span orders of magnitude, from gradual increments needed for analog elements, to large, abrupt changes for dynamically reconfigurable adaptive architectures. In this in‐depth perspective, the history of ECRAM, the recent progress in devices spanning organic, inorganic, and 2D materials, circuits, architectures, the rich portfolio of challenging, fundamental questions, and how ECRAM can be harnessed to realize a new paradigm for low‐power neuromorphic computing are discussed.
A custom designed SRAM was used to measure the thickness of integrated circuit over layers and the epi-layer thickness using alpha particles and a test SRAM. The over layer consists of oxide, nitride, metal, and junction regions.