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At least 721 records · Page 40

Erbium quantum memory platform with long optical coherence via back-end-of-line deposition on foundry-fabricated photonics

Realizing scalable quantum interconnects necessitates the integration of solid-state quantum memories with foundry photonics processes. While prior photonic integration efforts have relied upon specialized, laboratory-scale fabrication techniques, this work demonstrates the monolithic integration of a quantum memory platform with low-loss foundry photonic circuits via back-end-of-line deposition. We deposited thin films of titanium dioxide (Ti⁢O 2 ) doped with erbium (Er) onto silicon nitride nanophotonic waveguides and studied Er optical coherence at subkelvin temperatures with photon echo techniques. Furthermore, we suppressed optical dephasing through ex-situ oxygen annealing and optimized measurement conditions, which yielded an optical coherence time of 64 μ⁢s (a 5-kHz homogeneous linewidth) and slow spectral diffusion of 27 kHz over 4 ms, results that are comparable to state-of-the-art Er nanophotonic devices. Combined with second-long electron spin lifetimes and demonstrated electrical control of Er emission, our findings establish Er:Ti⁢O 2 on foundry photonics as a manufacturable platform for ensemble and single-ion quantum memories.

Electro-optic effects↗

Optimal strategies for optical quantum memories using long-lived noble-gas spins

Nuclear spins of noble gases exhibit exceptionally long coherence times and can potentially serve as a long-lived storage medium for quantum information. We analyze and compare the performance of two mechanisms for mapping the quantum state of light onto the collective spin state of noble gases. The first mechanism utilizes collisional exchange with the electronic spin state of metastable noble-gas atoms, while the second relies on spin-exchange collisions with ground-state alkali-metal atoms. We describe the operation of an optical quantum memory relying on these two mechanisms using a compact model and study strategies that optimize the memory storage efficiency. Through numerical simulations, we identify optimal sequences for storing optical signals with different signal bandwidths and electronic spin relaxation rates. This work highlights the qualitative difference between the two approaches for using noble gases as long-lived quantum memories at noncryogenic conditions and outlines the regimes in which they are expected to be efficient.

atomic ensemble↗

CMOS-Based Single-Cycle in-Memory XOR/XNOR

Big data applications are on the rise, and so is the number of data centers. The ever-increasing massive data pool needs to be periodically backed up in a secure environment. Moreover, a massive amount of securely backed-up data is required for training binary convolutional neural networks for image classification. XOR and XNOR operations are essential for large-scale data copy verification, encryption, and classification algorithms. The disproportionate speed of existing compute and memory units makes the von Neumann architecture inefficient to perform these Boolean operations. Compute-in-memory (CiM) has proved to be an optimum approach for such bulk computations. The existing CiM-based XOR/XNOR techniques either require multiple cycles for computing or add to the complexity of the fabrication process. Here, we propose a CMOS-based hardware topology for single-cycle in-memory XOR/XNOR operations. Our design provides at least 2× improvement in the latency compared with other existing CMOS-compatible solutions. We verify the proposed system through circuit/system-level simulations and evaluate its robustness using a 5000-point Monte Carlo variation analysis. This all-CMOS design paves the way for practical implementation of CiM XOR/XNOR at scaled technology nodes.

97 MATHEMATICS AND COMPUTING↗

Communication-Avoiding and Memory-Constrained Sparse Matrix-Matrix Multiplication at Extreme Scale

Sparse matrix-matrix multiplication (SpGEMM) is a widely used kernel in various graph, scientific computing and machine learning algorithms. In this paper, we consider SpGEMMs performed on hundreds of thousands of processors generating trillions of nonzeros in the output matrix. Distributed SpGEMM at this extreme scale faces two key challenges: (1) high communication cost and (2) inadequate memory to generate the output. Furthermore, we address these challenges with an integrated communication-avoiding and memory-constrained SpGEMM algorithm that scales to 262,144 cores (more than 1 million hardware threads) and can multiply sparse matrices of any size as long as inputs and a fraction of output fit in the aggregated memory. As we go from 16,384 cores to 262,144 cores on a Cray XC40 supercomputer, the new SpGEMM algorithm runs 10x faster when multiplying large-scale protein-similarity matrices.

97 MATHEMATICS AND COMPUTING↗

Oxygen plasma immersion ion implantation treatment to enhance data retention of tungsten nanocrystal nonvolatile memory

Data retention characteristics of tungsten nanocrystal (W-NC) memory devices using an oxygen plasma immersion ion implantation (PIII) treatment are investigated. With an increase of oxygen PIII bias voltage and treatment time, the capacitance–voltage hysteresis memory window is increased but the data retention characteristics become degraded. High-resolution transmission electron microscopy images show that this poor data retention is a result of plasma damage on the tunneling oxide layer, which can be prevented by lowering the bias voltage to 7 kV. In addition, by using the elevated temperature retention measurement technique, the effective charge trapping level of the WO{sub 3} film surrounding the W-NCs can be extracted. This measurement reveals that a higher oxygen PIII bias voltage and treatment time induces more shallow traps within the WO{sub 3} film, degrading the retention behavior of the W-NC memory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Narrow thermal hysteresis of NiTi shape memory alloy thin films with submicrometer thickness

NiTi shape memory alloy (SMA) thin films were fabricated using biased target ion beam deposition (BTIBD), which is a new technique for fabricating submicrometer-thick SMA thin films, and the capacity to exhibit shape memory behavior was investigated. The thermally induced shape memory effect (SME) was studied using the wafer curvature method to report the stress-temperature response. The films exhibited the SME in a temperature range above room temperature and a narrow thermal hysteresis with respect to previous reports. To confirm the underlying phase transformation, in situ x-ray diffraction was carried out in the corresponding phase transformation temperature range. The B2 to R-phase martensitic transformation occurs, and the R-phase transformation is stable with respect to the expected conversion to the B19′ martensite phase. The narrow hysteresis and stable R-phase are rationalized in terms of the unique properties of the BTIBD technique.

36 MATERIALS SCIENCE↗

Experimental test of Landauer’s principle in single-bit operations on nanomagnetic memory bits

Minimizing energy dissipation has emerged as the key challenge in continuing to scale the performance of digital computers. The question of whether there exists a fundamental lower limit to the energy required for digital operations is therefore of great interest. A well-known theoretical result put forward by Landauer states that any irreversible single-bit operation on a physical memory element in contact with a heat bath at a temperature T requires at least k B T ln(2) of heat be dissipated from the memory into the environment, where k B is the Boltzmann constant. We report an experimental investigation of the intrinsic energy loss of an adiabatic single-bit reset operation using nanoscale magnetic memory bits, by far the most ubiquitous digital storage technology in use today. Through sensitive, high-precision magnetometry measurements, we observed that the amount of dissipated energy in this process is consistent (within 2 SDs of experimental uncertainty) with the Landauer limit. This result reinforces the connection between “information thermodynamics” and physical systems and also provides a foundation for the development of practical information processing technologies that approach the fundamental limit of energy dissipation. The significance of the result includes insightful direction for future development of information technology.

42 ENGINEERING↗

Comparison of flash-memory elements using materials based on graphene

Charge capture on flash-memory test structures with floating gates made of graphene (few-layer graphene) and its compounds (graphene oxide and partially fluorinated graphene) is investigated. A comparison of the memory window for different structures has shown the potential of using reduced graphene oxide, graphene with only a few layers, and fluorographene. For the first time, partially fluorinated graphene has been employed as a floating gate in flash-memory structures. Graphene-based materials are promising for 2D printing technologies and flexible electronics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Fractionation of Lignin for Selective Shape Memory Effects at Elevated Temperatures

We report a facile approach to control the shape memory effects and thermomechanical characteristics of a lignin-based multiphase polymer. Solvent fractionation of a syringylpropane-rich technical organosolv lignin resulted in selective lignin structures having excellent thermal stability coupled with high stiffness and melt-flow resistance. The fractionated lignins were reacted with rubber in melt-phase to form partially networked elastomer enabling selective programmability of the material shape either at 70 °C, a temperature that is high enough for rubbery matrix materials, or at an extremely high temperature, 150 °C. Utilizing appropriate functionalities in fractionated lignins, tunable shape fixity with high strain and stress recovery, particularly high-stress tolerance were maintained. Detailed studies of lignin structures and chemistries were correlated to molecular rigidity, morphology, and stress relaxation, as well as shape memory effects of the materials. The fractionation of lignin enabled enrichment of specific lignin properties for efficient shape memory effects that broaden the materials’ application window. Electron microscopy, melt-rheology, dynamic mechanical analysis and ultra-small angle neutron scattering were conducted to establish morphology of acrylonitrile butadiene rubber (NBR)-lignin elastomers from solvent fractionated lignins.

36 MATERIALS SCIENCE↗

A Highly Effective African Swine Fever Virus Vaccine Elicits a Memory T Cell Response in Vaccinated Swine

African Swine Fever Virus (ASFV) is the causative agent of a highly contagious and lethal vector-borne disease in suids. Recently, a live attenuated virus strain, developed using the currently circulating, virulent Georgia strain (ASFV-G) with a single gene deletion (ASFV-G-ΔI177L), resulted in an effective vaccine. Nevertheless, protective immune response mechanisms induced by this candidate are poorly understood. In this study, Yorkshire crossbred swine intramuscularly vaccinated with 10 6 50% hemadsorption dose (HAD 50 ) of ASFV-G-ΔI177L or a vehicle control were challenged at 28 days post-inoculation (dpi) with 10 2 HAD 50 of ASFV-G. Analysis of purified peripheral blood mononuclear cells following inoculation and challenge revealed that CD4+, CD8+ and CD4+CD8+ central memory T cells (CD44+CD25–CD27–CD62L+CCR7+, T cm ) decreased significantly by 28 dpi in ASFV-G-ΔI177L-vaccinated swine compared to baseline and time-matched controls. Conversely, CD4+, CD8+ and CD4+CD8+ effector memory T cells (CD44+CD25–CD27–CD62–CCR7–, T em ) increased significantly among ASFV-G-ΔI177L-vaccined swine by 28 dpi compared to baseline and time-matched controls. Additionally, the percentage of natural killer (NK), CD4+ and CD4+CD8+ T em and CD8+ T cm and T em positive for IFNγ increased significantly following inoculation, surpassing that of controls by 28 dpi or earlier. These results suggest that NK and memory T cells play a role in prote

60 APPLIED LIFE SCIENCES↗

Solid State Memory Study Final Report

Existing and future solid state nonvolatile memory technologies are described and evaluated in this report. Solid state memory technologies can offer size, speed, power, weight, and ruggedness advantages over conventional moving media storage technologoies such as disk or tape. This technology list is a broad sampling of past, present, emerging, and future solid state memory technologies.

Solid State Memory↗

Compact holographic memory using E - O beam steering

An innovative holographic memory system has been developed at JPL for high-density and high speed data storage in a space environment. This system ulitlizes a newly developed electro-optic (E-O) beam steering technology for beam steering to enable high-speed random access memory read/write without moving parts. Recently, a compact CD-sized holographic memory broadboard has been developed and demonstrated for holographic data storage adn retrieval. Detail technical progress will be presented in this paper.

electo - optic (E - O ) beam↗

Surface Control of Cold Hibernated Elastic Memory Self-Deployable Structure

A new class of simple, reliable, lightweight, low packaging volume and cost, self-deployable structures has been developed for use in space and commercial applications. This technology called 'cold hibernated elastic memory' (CHEM) utilizes shape memory polymers (SMP)in open cellular (foam) structure or sandwich structures made of shape memory polymer foam cores and polymeric composite skins. Some of many potential CHEM space applications require a high precision deployment and surface accuracy during operation. However, a CHEM structure could be slightly distorted by the thermo-mechanical processing as well as by thermal space environment Therefore, the sensor system is desirable to monitor and correct the potential surface imperfection. During these studies, the surface control of CHEM smart structures was demonstrated using a Macro-Fiber Composite (MFC) actuator developed by the NASA LaRC and US Army ARL. The test results indicate that the MFC actuator performed well before and after processing cycles. It reduced some residue compressive strain that in turn corrected very small shape distortion after each processing cycle. The integrated precision strain gages were detecting only a small flat shape imperfection indicating a good recoverability of original shape of the CHEM test structure.

glass transition temperature Tg↗

Assessment of Shape Memory Alloys - From Atoms To Actuators - Via In Situ Neutron Diffraction

As shape memory alloys (SMAs) become an established actuator technology, it is important to identify the fundamental mechanisms responsible for their performance by understanding microstructure performance relationships from processing to final form. Yet, microstructural examination of SMAs at stress and temperature is often a challenge since structural changes occur with stress and temperature and microstructures cannot be preserved through quenching or after stress removal, as would be the case for conventional materials. One solution to this dilemma is in situ neutron diffraction, which has been applied to the investigation of SMAs and has offered a unique approach to reveal the fundamental micromechanics and microstructural aspects of bulk SMAs in a non-destructive setting. Through this technique, it is possible to directly correlate the micromechanical responses (e.g., internal residual stresses, lattice strains), microstructural evolutions (e.g., texture, defects) and phase transformation properties (e.g., phase fractions, kinetics) to the macroscopic actuator behavior. In this work, in situ neutron diffraction was systematically employed to evaluate the deformation and transformation behavior of SMAs under typical actuator conditions. Austenite and martensite phases, yield behavior, variant selection and transformation temperatures were characterized for a polycrystalline NiTi (49.9 at. Ni). As the alloy transforms under thermomechanical loading, the measured textures and lattice plane-level variations were directly related to the cyclic actuation-strain characteristics and the dimensional instability (strain ratcheting) commonly observed in this alloy. The effect of training on the shape memory characteristics of the alloy and the development of two-way shape memory effect (TWSME) were also assessed. The final conversion from a material to a useful actuator, typically termed shape setting, was also investigated in situ during constrained heatingcooling and subsequent shape recovery experiments. Neutron diffraction techniques are also being applied to the investigation of novel high temperature SMAs with the objective of designing alloys with better stability, higher transition temperatures and ultimately superior durability.

Shape Memory Alloys↗

Comparison of TID Response and SEE Characterization of Single and Multi Level High Density NAND Flash Memories

Heavy ion single-event measurements and TID response for 8Gb commercial NAND flash memories are reported. Radiation results of multi-level flash technology are compared with results from single-level flash technology. In general, these commercial high density memories appear to be much less susceptible to SEE and have better TID response compared to older generations of flash memories. The charge pump survived up to 600 krads.

nonvolatile memory↗

Engineering Design Tools for Shape Memory Alloy Actuators: CASMART Collaborative Best Practices and Case Studies

The primary goal of the Consortium for the Advancement of Shape Memory Alloy Research and Technology (CASMART) is to enable the design of revolutionary applications based on shape memory alloy (SMA) technology. In order to help realize this goal and reduce the development time and required experience for the fabrication of SMA actuation systems, several modeling tools have been developed for common actuator types and are discussed herein along with case studies, which highlight the capabilities and limitations of these tools. Due to their ability to sustain high stresses and recover large deformations, SMAs have many potential applications as reliable, lightweight, solid-state actuators. Their advantage over classical actuators can also be further improved when the actuator geometry is modified to fit the specific application. In this paper, three common actuator designs are studied: wires, which are lightweight, low-profile, and easily implemented; springs, which offer actuation strokes upwards of 200 at reduced mechanical loads; and torque tubes, which can provide large actuation forces in small volumes and develop a repeatable zero-load actuation response (known as the two-way shape memory effect). The modeling frameworks, which have been implemented in the design tools, are developed for each of these frequently used SMA actuator types. In order to demonstrate the versatility and flexibility of the presented design tools, as well as validate their modeling framework, several design challenges were completed. These case studies include the design and development of an active hinge for the deployment of a solar array or foldable space structure, an adaptive solar array deployment and positioning system, a passive air temperature controller for regulation flow temperatures inside of a jet engine, and a redesign of the Corvette active hatch, which allows for pressure equalization of the car interior. For each of the presented case studies, a prototype or proof-of-concept was fabricated and the experimental results and lessons learned are discussed. This analysis presents a collection of CASMART collaborative best practices in order to allow readers to utilize the available design tools and understand their modeling principles. These design tools, which are based on engineering models, can provide first-order optimal designs and are a basic and efficient method for either demonstrating design feasibility or refining design parameters. Although the design and integration of an SMA-based actuation system always requires application- and environment-specific engineering considerations, common modeling tools can significantly reduce the investment required for actuation system development and provide valuable engineering insight.

Design tools↗

NOR Flash Memory Scrubbing Application for Boot File Preservation of NASA’s Descent and Landing Computer (DLC)

Progress on NASA’s Safe and Precise Landing Integrated Capabilities Evolution (SPLICE)project continues, specifically with this development of the Descent and Landing Computer(DLC). One of the DLC’s primary contributions as a SPLICE technology is its implementationof algorithms and operation of sensors to autonomously guide a spacecraft in performing moreprecise and safer landings on celestial bodies such as the Moon and Mars. The second iterationof the DLC is known as the Engineering Test Unit (ETU) and one of its desired functionalitiesis the ability to preserve the fidelity of the system’s boot file through the use of memoryscrubbing. The ETU has two primary boards, one for housing a Multi-Processor System ona Chip (MPSoC) and the other for housing a Xilinx Kintex Ultrascale FPGA3. To emulate amemory scrubbing function implemented on the ETU’s FPGA board, the design and testingof a software application was performed on a Xilinx KCU105 FPGA evaluation board. Thememory scrubbing application had to meet certain key criteria such as (1) properly utilize withthe flash memory’s Serial Peripheral Interface (SPI) to read, write, and erase flash memoryproperly, (2) be able to detect arbitrarily large or small amounts of bit-errors, (3) be able tocorrect all detected errors, and (4) perform memory scrubbing indefinitely and autonomously.A prototype implementation was constructed and tested, demonstrating successful detectionand correction of bit errors in multiple configurations. In the form of burst errors or singularbit flips, and in amounts of errors ranging from one to fifteen (per 256 Bytes), the applicationwas successful in preserving memory fidelity.

Radiation tolerant↗

Data-Driven Study of Shape Memory Behavior of Multi-Component Ni-Ti Alloys

Ni-Ti based shape memory alloys (SMAs) have found wide-spread use in aerospace, automotive, biomedical, and commercial applications owing to their favorable properties and ease of operation. Especially important for many NASA applications is the ability to tune the martensitic transformation temperature of Ni-Ti alloys by varying the alloy composition and processing conditions. Recently, researchers at NASA have compiled an extensive database of shape memory properties of materials, including over 8,000 multi-component Ni-Ti alloys containing 37 different alloying elements. Using this dataset, machine learning models are trained to predict transformation temperatures, hysteresis, and transformation strain with extremely low mean absolute errors. These models are used to learn relationships between shape memory behavior and input parameters in the composition and processing space. ML predictions are validated through new experiments. The combination of an extensive experimental dataset and accurate learning models, together, make our approach highly suitable for the rapid discovery and design of novel SMAs with targeted properties. We are not aware of any current approaches capable of predicting SMA transformation behavior over such a wide range of compositions and processing conditions.

Shape memory alloys↗