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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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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multiplexed color centers in a silicon photonic cavity array

Entanglement distribution is central to the modular scaling of quantum processors and establishing quantum networks. Color centers with telecom-band transitions and long spin coherence times are suitable candidates for long-distance entanglement distribution. However, high-bandwidth memory-enhanced quantum communication is limited by high-yield, scalable creation of efficient spin-photon interfaces. Here, we develop a silicon photonics platform consisting of arrays of bus-coupled cavities. The coupling to a common bus waveguide enables simultaneous access to individually addressable cavity-enhanced T center arrays. We demonstrate frequency-multiplexed operation of two T centers in separate photonic crystal cavities. In addition, we investigate the cavity enhancement of a T center through hybridized modes formed between physically distant cavities. Our results show that bus-coupled arrays of cavity-enhanced color centers could enable efficient on-chip and long-distance entanglement distribution.

Komza, Lukasz↗
DOE OSTI2020

Hidden Subsurface Reconstruction and Its Atomic Origins in Layered Oxide Cathodes

Structural transformations near surfaces of solid-state materials underpin functional mechanisms of a broad range of applications including catalysis, memory, and energy storage. It has been a long-standing notion that the outmost free surfaces, accompanied by broken translational symmetry and altered atomic configurations, are usually the birthplace for structural transformations. Here, in a layered oxide cathode for Li-ion batteries, we for the first time observe the incipient state of the well documented layered-to-spinel-like structural transformation, which is surprisingly initiated from subsurface layer, rather than the very surface. Coupling atomic level scanning transmission electron microscopy imaging with electron energy loss spectroscopy, we discover that the reconstructed subsurfaces, featuring a mix of discrete patches of layered and spinel-like structures, are associated with selective atomic species partition and consequent nanoscale non-uniform composition gradient distribution at the subsurface. In conclusion, our findings provide fundamental insights on atomic-scale mechanisms of structural transformation in layered cathodes.

25 ENERGY STORAGE↗
NASA NTRS2014

Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

Supercomputing↗
DOE OSTI2020

On the Marriage of Asynchronous Many Task Runtimes and Big Data: A Glance

The rise of the accelerator-based architectures and reconfigurable computing have showcased the weakness of software stack toolchains that still maintain a static view of the hardware instead of relying on a symbiotic relationship between static (e.g., compilers) and dynamic tools (e.g., runtimes). In the past decades, this need has given rise to adaptive runtimes with increasingly finer computational tasks. These finer tasks help to take advantage of the hardware by switching out when a long latency operation is encountered (because of the deeper memory hierarchies and new memory technologies that might target streaming instead of random access), thus trading off idle time for unrelated work. Examples of these finer task runtimes are Asynchronous Many Task (AMT) runtimes, in which highly efficient computational graphs run on a variety of hardware. Due to its inherent latency tolerant characteristics, Latency-sensitive applications, such as Graph Analytics and Big Data can effectively use these runtimes. This paper aims to present an example of how the careful design of an AMT can exploit the hardware substrate when faced with high latency applications such as the ones given in the Big Data domain. Moreover, with its introspection and adaptive capabilities, we aim to show the power of these runtimes when facing the changing requirements of the application workloads. We use the Performance Open Community Runtime (P-OCR) as our vehicle to demonstrate the concepts presented here.

adaptive runtime, big data analysis↗
DOE OSTI2025

NLR HPC Eagle Jobs Data and Additional Energy Metrics

Overview: Anonymized job-level records from the Eagle high-performance computing (HPC) system at the National Laboratory of the Rockies (NLR). Each record represents a Slurm batch job with scheduling metadata, resource requests, resource utilization, CPU/GPU energy consumption, and efficiency metrics. Sensitive fields (user, account, job name) are replaced with cryptographic hashes. System & Timeframe: Eagle was a 2,000-node, 8-petaflop system operated at NLR from 2019–2024. Data covers the full operational lifetime of the system. Slurm data was processed nightly; timestamps are in Mountain Time. Funding provided by the U.S. Department of Energy, EERE. Files: esif.hpc.eagle.job-anon.zip — Core anonymized job records (Hive-partitioned Parquet) esif.hpc.eagle.job-anon-energy-metrics.zip — Same records with additional iLO and Ganglia energy metrics datacard.md — Full dataset documentation ~13.8 million rows, 62 variables. Readable with PyArrow, pandas, DuckDB, Apache Spark, or any Parquet-compatible tool. Data Collection: Jobs collected via sacct through a pipeline: Eagle Jobs API → Redpanda → StreamSets → HPCMON API → PostgreSQL. Node-level power from iLO (HP Integrated Lights-Out); GPU power from Ganglia monitoring, joined to jobs via node lists and time ranges. Preprocessing: Anonymization of name, user, and account fields via cryptographic hashing Derived columns: queue_wait, cpu_eff, max_mem_eff Simplified job state mapping (e.g., "CANCELLED BY 12345" → "CANCELLED") QoS accounting rules (buy-in, standby, or Slurm QoS value) CPU energy estimated from TDP (200W, Intel Xeon Gold 6154, 18 cores) Timezone-aware columns (_tz) sourced from LEX accounting database to correctly handle DST transitions Key Variables: Scheduling: job_id, partition, state_simple, submit_time_tz, start_time_tz, end_time_tz, queue_waitResources: nodes_req/used, processors_req/used, memory_req, wallclock_req/used, gpus_requested Efficiency: cpu_eff, max_mem_eff Energy: cpu_energy_tdp_estimated_max/used_watt_hours, node_energy_total_watt_hours (iLO), gpu0/1_energy_total_watt_hours (Ganglia) Partitions: bigmem, bigmem-8600, bigscratch, csc, dav, ddn, debug, gpu, haswell, long, mono, short, standard Job States: CANCELLED, COMPLETED, FAILED, NODE_FAIL, OUT_OF_MEMORY, PENDING, RUNNING, TIMEOUT QoS Levels: Unknown, normal, buy-in, debug, penalty, high, standby Important Notes: Non-_tz timestamp columns may be off by one hour across DST boundaries; use _tz columns for time difference calculations Energy fields are null for jobs without monitoring coverage Job step records and raw Slurm JSONB fields are excluded from this extract Do not attempt to re-identify individuals from hashed fields

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Strong Relativistic Effects in Lanthanide-Based Single-Molecule Magnets

Lanthanide-based single-molecule magnets (SMMs) are promising building blocks for quantum memory and spintronic devices. Designing lanthanide-based SMMs with long spin relaxation time requires a detailed understanding of their electronic structure, including the crucial role of the spin-orbit coupling (SOC). While traditional calculations of SOC using the perturbation theory applied to a solution of the non-relativistic Schrödinger equation are valid for light atoms, this approach is questionable for systems containing heavy elements such as lanthanides. We investigate the accuracy of the perturbation estimates of SOC by variationally solving the Dirac equation for the [DyO] + molecule, a prototype of a lanthanide-based SMM. We show that the energy splittings between the M J states involved in spin relaxation depend on the interplay between strong SOC and dynamic electron correlations. Here, we demonstrate that this interplay affects the resonances between the spin and vibrational transitions, and, therefore, the spin relaxation time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Robust Millisecond Coherence Times of Erbium Electron Spins

Erbium doped solids are prime candidates for quantum memories in optical quantum networks given their telecom-compatible photon emission. An electron spin of erbium with millisecond coherence time is desirable for generating remote entanglement between adjacent quantum network nodes. Here, in this study, we report GHz-range electron spin transitions of 167 Er 3+ in yttrium oxide (Y 2 O 3 ) matrix with coherence times that are consistently longer than a millisecond. By polarizing para magnetic impurity spins we achieve a spin T 2 up to 1.46 ms, and up to 7.1 ms after dynamical decoupling. These coherence lifetimes are among the longest found for erbium in crystalline matrices despite the presence of host nuclear spins. We further enhance the coherence time beyond conventional dynamical decoupling, using customized sequences to simultaneously mitigate spectral diffusion and dipolar interactions. Our study not only establishes 167 Er 3+ : Y 2 O 3 as a significant quantum memory platform but also provides a guideline for engineering long-lived erbium spins in a variety of host materials for quantum technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1984

Time scales for the decay of induced large-scale magnetic fields in the Venus ionosphere

Observations made with the aid of a magnetometer on the Pioneer Venus Orbiter have shown large-scale horizontal magnetic fields in the dayside ionosphere of Venus. According to Cloutier and Daniell (1981), the observed magnetic structures may be quasi-steady features produced by an ionospheric current system driven by solar wind interaction. Russell et al. (1983) have suggested that the altitude profiles of the horizontal field on different orbits exhibit a pattern which can be interpreted as phases in the temporal evolution of an initial state in which the ionosphere was permeated with magnetosheath-like fields. The present investigation is concerned with the argument in favor of a temporal versus spatial explanation for some of the observed field structure. A calculation indicates that the diffusion time for ionospheric fields is long enough to justify attributing the observed fields to the 'memory' of the Venus ionosphere in certain regions.

Luhmann, J. G.↗
NASA NTRS1987

System architecture of a gallium arsenide one-gigahertz digital IC tester

The design for a 1-GHz digital integrated circuit tester for the evaluation of custom GaAs chips and subsystems is discussed. Technology-related problems affecting the design of a GaAs computer are discussed, with emphasis on the problems introduced by long printed-circuit-board interconnect. High-speed interface modules provide a link between the low-speed microprocessor and the chip under test. Memory-multiplexer and memory-shift register architectures for the storage of test vectors are described in addition to an architecture for local data storage consisting of a long chain of GaAs shift registers. The tester is constructed around a VME system card cage and backplane, and very little high-speed interconnect exists between boards. The tester has a three part self-test consisting of a CPU board confidence test, a main memory confidence test, and a high-speed interface module functional test.

Fouts, Douglas J.↗
DOE OSTI2025

Dual-ion ECRAM as a stable and accurate analog synapse

Electrochemical random-access memory (ECRAM) works by tuning the bulk electronic conductance of functional materials via reversible, electrochemical insertion of ions, resulting in stable analog resistive switching, attractive for analog in-memory and neuromorphic computing. However, achieving fast programming for training and long retention for inference has been elusive. Protonic ECRAM demonstrates fast programming but insufficient retention, while oxygen-based ECRAM with excellent retention requires elevated programming temperatures. Cu-based ECRAM offers a compromise, with an activation energy (E A ) of ≈0.76 eV between protons (E A ≈ 0.4 eV) and oxygen (E A > 1 eV), enabling extensive retention and room temperature programming. Combining Cu 2+ ions with protons to form a dual-ion ECRAM, we demonstrate two distinct switching behaviors: fast switching at ≤5 V, (E A ≈ 0.45 eV) via protons, and nonvolatile, room temperature switching at ≥8 V, with E A ≈ 0.76 eV via Cu 2+ ions. In conclusion, the Cu-based state exhibits a wide conductance range, with excellent retention, low noise, and linear current-voltage behavior, achieving digital-equivalent ImageNet inference accuracy.

analog in-memory computing↗
NASA NTRS2001

Highly Survivable Avionics Systems for Long-Term Deep Space Exploration

The design of highly survivable avionics systems for long-term (> 10 years) exploration of space is an essential technology for all current and future missions in the Outer Planets roadmap. Long-term exposure to extreme environmental conditions such as high radiation and low-temperatures make survivability in space a major challenge. Moreover, current and future missions are increasingly using commercial technology such as deep sub-micron (0.25 microns) fabrication processes with specialized circuit designs, commercial interfaces, processors, memory, and other commercial off the shelf components that were not designed for long-term survivability in space. Therefore, the design of highly reliable, and available systems for the exploration of Europa, Pluto and other destinations in deep-space require a comprehensive and fresh approach to this problem. This paper summarizes work in progress in three different areas: a framework for the design of highly reliable and highly available space avionics systems, distributed reliable computing architecture, and Guarded Software Upgrading (GSU) techniques for software upgrading during long-term missions. Additional information is contained in the original extended abstract.

Alkalai, L.↗
DOE OSTI2023

Hybrid stochastic synapses enabled by scaled ferroelectric field-effect transistors

Achieving brain-like density and performance in neuromorphic computers necessitates scaling down the size of nanodevices emulating neuro-synaptic functionalities. However, scaling nanodevices results in reduction of programming resolution and emergence of stochastic non-idealities. While prior work has mainly focused on binary transitions, in this work, we leverage the stochastic switching of a three-state ferroelectric field-effect transistor to implement a long-term and short-term two-tier stochastic synaptic memory with a single device. Experimental measurements are performed on a scaled 28 nm high-k metal gate technology-based device to develop a probabilistic model of the hybrid stochastic synapse. In addition to the advantage of ultra-low programming energies afforded by scaling, our hardware–algorithm co-design analysis reveals the efficacy of the two-tier memory in comparison to binary stochastic synapses in on-chip learning tasks—paving the way for algorithms exploiting multi-state devices with probabilistic transitions beyond deterministic ones.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Spin-Photon Entanglement of a Single Er 3 + Ion in the Telecom Band

Entanglement between photons and a quantum memory is a key component of quantum repeaters, which allow long-distance quantum entanglement distribution in the presence of fiber losses. Spin-photon entanglement has been implemented with a number of different atomic and solid-state qubits with long spin coherence times, but none directly emit photons into the 1.5 − μ m telecom band where losses in optical fibers are minimized. Here, we demonstrate spin-photon entanglement using a single rare earth ion in the solid-state Er 3 + coupled to a silicon nanophotonic cavity, which directly emits photons at 1532.6 nm. We infer an entanglement fidelity of 73(3)% after propagating through 15.6 km of optical fiber. This work opens the door to large-scale quantum networks based Er 3 + ions, leveraging scalable silicon device fabrication and spectral multiplexing. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1987

Resistive synaptic interconnects for electronic neural networks

The use of the alpha-Ge(1-x):Al(x) and alpha-Ge(1-x):Cu(x) alloys and Pt/Al2O3 cermet thin films as resistive interconnects for binary synaptic memory arrays is evaluated. The fabrication of the 10-20 microns long, 10 microns wide, and 0.1 micron thick interconnects from the alloys and cermet is described. The current-voltage and switching characteristics of the as-deposited films and the patterned test structure are studied. The resistivity, uniformity, stability, and compatibility of the interconnects are examined. It is observed that alpha-Ge(1-x):Cu(x) alloys have a wide resistivity range and low temperature coefficients of resistance; however, their long-term stability is limited due to their low crystallization temperature. It is detected that the alpha-Ge(1-x):Al(x) alloys have higher crystallization temperatures and their resistivity is not greatly affected by large changes in metal content. The Pt/Al2O3 samples display excellent stability, easy fabrication, and control of resistivity with metal content.

Lamb, J. L.↗
NASA NTRS1990

Contour-map encoding of shape for early vision

Contour maps provide a general method for recognizing 2-D shapes. All but blank images give rise to such maps, and people are good at recognizing objects and shapes from them. The maps are encoded easily in long feature vectors that are suitable for recognition by an associative memory. These properties of contour maps suggest a role for them in early visual perception. The prevalence of direction sensitive neurons in the visual cortex of mammals supports this view.

Kanerva, Pentti↗
NASA NTRS2003

Pressure-Sensor Assembly Technique

Nielsen Engineering & Research (NEAR) recently developed an ultrathin data acquisition system for use in turbomachinery testing at NASA Glenn Research Center. This system integrates a microelectromechanical- systems- (MEMS-) based absolute pressure sensor [0 to 50 psia (0 to 345 kPa)], temperature sensor, signal-conditioning application-specific integrated circuit (ASIC), microprocessor, and digital memory into a package which is roughly 2.8 in. (7.1 cm) long by 0.75 in. (1.9 cm) wide. Each of these components is flip-chip attached to a thin, flexible circuit board and subsequently ground and polished to achieve a total system thickness of 0.006 in. (0.15 mm). Because this instrument is so thin, it can be quickly adhered to any surface of interest where data can be collected without disrupting the flow being investigated. One issue in the development of the ultrathin data acquisition system was how to attach the MEMS pressure sensor to the circuit board in a manner which allowed the sensor s diaphragm to communicate with the ambient fluid while providing enough support for the chip to survive the grinding and polishing operations. The technique, developed by NEAR and Jabil Technology Services Group (San Jose, CA), is described below. In the approach developed, the sensor is attached to the specially designed circuit board, see Figure 1, using a modified flip-chip technique. The circular diaphragm on the left side of the sensor is used to actively measure the ambient pressure, while the diaphragm on the right is used to compensate for changes in output due to temperature variations. The circuit board is fabricated with an access hole through it so that when the completed system is installed onto a wind tunnel model (chip side down), the active diaphragm is exposed to the environment. After the sensor is flip-chip attached to the circuit board, the die is underfilled to support the chip during the subsequent grinding and polishing operations. To prevent this underfill material from getting onto the sensor s diaphragms, the circuit board is fabricated with two 25- micrometer-tall polymer rings, sized so that the diaphragms fit inside the rings once the chip is attached.

Pruzan, Daniel A.↗
DOE OSTI2022

High-Temperature Ferroelectric Behavior of Al 0.7 Sc 0.3 N

Currently, there is a lack of nonvolatile memory (NVM) technology that can operate continuously at temperatures > 200 °C. While ferroelectric NVM has previously demonstrated long polarization retention and >10 13 read/write cycles at room temperature, the largest hurdle comes at higher temperatures for conventional perovskite ferroelectrics. Here, we demonstrate how AlScN can enable high-temperature (>200 °C) nonvolatile memory. The c-axis textured thin films were prepared via reactive radiofrequency magnetron sputtering onto a highly textured Pt (111) surface. Photolithographically defined Pt top electrodes completed the capacitor stack, which was tested in a high temperature vacuum probe station up to 400 °C. Polarization–electric field hysteresis loops between 23 and 400 °C reveal minimal changes in the remanent polarization values, while the coercive field decreased from 4.3 MV/cm to 2.6 MV/cm. Even at 400 °C, the polarization retention exhibited negligible loss for up to 1000 s, demonstrating promise for potential nonvolatile memory capable of high–temperature operation. Fatigue behavior also showed a moderate dependence on operating temperature, but the mechanisms of degradation require additional study.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Method and apparatus for providing thermal wear leveling

Exemplary embodiments provide thermal wear spreading among a plurality of thermal die regions in an integrated circuit or among dies by using die region wear-out data that represents a cumulative amount of time each of a number of thermal die regions in one or more dies has spent at a particular temperature level. In one example, die region wear-out data is stored in persistent memory and is accrued over a life of each respective thermal region so that a long term monitoring of temperature levels in the various die regions is used to spread thermal wear among the thermal die regions. In one example, spreading thermal wear is done by controlling task execution such as thread execution among one or more processing cores, dies and/or data access operations for a memory.

Roberts, David A.↗