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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Interlayer Exciton Polarons in Mesoscopic V 2 O 5 for Broadband Optoelectronic Synapses

Persistent photoconductivity and optoelectronic synaptic behavior are demonstrated in solution-processed mesoscopic α-phase vanadium pentoxide (V 2 O 5 ) thin films. First-principles simulations coupled with the two-site Holstein polaron hopping model show that vacancies at the terminal oxygen position lead to long recombination times because photoexcited electrons and holes reside on different layers separated by the van der Waals gap, forming a weakly coupled interlayer exciton polaron. Mid-gap polaronic states also significantly broaden the photoresponse of the films to span across visible and infrared wavelengths. By controlling the amplitude/intensity, duration, and/or number of optical pulses, tunable optoelectronic memory functions, such as short-term and long-term plasticity, are experimentally established in V 2 O 5 -based optoelectronic synapses. Furthermore, device fabrication was extended to mechanically flexible ultrathin glass substrates. Flexible optoelectronic synapses maintained high performance after 150 bending cycles.

Phan, Thanh Luan [National Renewable Energy Labora↗
DOE OSTI2023

Acoustic Radiation From a Superconducting Qubit: From Spontaneous Emission to Rabi Oscillations

Hybrid quantum systems that utilize controllable coupling between phonons and superconducting qubits could pave the way for a new generation of compact quantum memories and sensor technologies. However, the same electromechanical interaction mechanisms that enable coherent qubit-phonon coupling can also lead to decoherence due to the spontaneous phonon emission. In this paper we study the dynamics of a qubit coupled to an acoustic resonator by a piezoelectric film. By varying the surface topography of the resonator from rough to flat to shaped, we explore the crossover from fast decay of an excited qubit to quantum-coherent coupling between the qubit and an isolated phonon mode. The developed theoretical model allows us to establish and check quantitative links between the results obtained for the rough and shaped topographies. Discrepancy between the theory and the data for the flat resonator points to the imperfections of the studied device. Our experimental approach may be used for precision measurements of crystalline vibrations, the design of quantum memories, and the study of electromechanical contributions to dielectric loss.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Giant Domain Wall Conductivity in Self‐Assembled BiFeO 3 Nanocrystals

Abstract Ever‐increasing demand on electronic devices with ultrahigh‐density non‐volatile data storage has attracted great interest in novel ferroelectric memories based on conductive ferroelectric domain walls. Embedded in an insulating material, ferroelectric domain walls have the capability of being (re)created, displaced, erased, and altered in their spatial configurations and electronic characteristics. However, the domain wall conductivities are in most cases not yet sufficiently high to ensure the current density required to drive read‐out circuits operating at high speeds. In this work, a giant domain wall current (>10 µA) of a single charged domain wall is obtained through conductive atomic force microscopy with a bias field of 4 V. This is achieved in self‐assembled BiFeO 3 nanocrystals grown by sol‐gel method on Nb‐doped SrTiO 3 substrates. Local configurations of domains and domain wall types are studied using vector piezoresponse force microscopy and high‐resolution transmission electronic microscopy. The enhancement of the wall current is shown to be due to the formation of conducting pathways of charged defects accumulated along domain walls and traversing the nanocrystals. The diverse domain walls can be manipulated by electric field in a perpendicular architecture. The perpendicular array structure of BiFeO 3 nanocrystals should have great potentials for developing perpendicular nanoelectronic prototypes.

Liu, Lisha↗
DOE OSTI2024

Ferroelectric capacitors and field-effect transistors as in-memory computing elements for machine learning workloads

Abstract This study discusses the feasibility of Ferroelectric Capacitors (FeCaps) and Ferroelectric Field-Effect Transistors (FeFETs) as In-Memory Computing (IMC) elements to accelerate machine learning (ML) workloads. We conducted an exploration of device fabrication and proposed system-algorithm co-design to boost performance. A novel FeCap device, incorporating an interfacial layer (IL) and$$\text {Hf}_{0.5}\text {Zr}_{0.5}\text {O}_2$$ Hf 0.5 Zr 0.5 O 2 (HZO), ensures a reduction in operating voltage and enhances HZO scaling while being compatible with CMOS circuits. The IL also enriches ferroelectricity and retention properties. When integrated into crossbar arrays, FeCaps and FeFETs demonstrate their effectiveness as IMC components, eliminating sneak paths and enabling selector-less operation, leading to notable improvements in energy efficiency and area utilization. However, it is worth noting that limited capacitance ratios in FeCaps introduced errors in multiply-and-accumulate (MAC) computations. The proposed co-design approach helps in mitigating these errors and achieves high accuracy in classifying the CIFAR-10 dataset, elevating it from a baseline of 10% to 81.7%. FeFETs in crossbars, with a higher on-off ratio, outperform FeCaps, and our proposed charge-based sensing scheme achieved at least an order of magnitude reduction in power consumption, compared to prevalent current-based methods.

Science & Technology - Other Topics↗
DOE OSTI2022

Optical bistability in PECVD silicon-rich nitride

We present a study of optical bi-stability in a 3.02 refractive index at 1550nm plasma enhanced chemical vapor deposition (PECVD) silicon-rich nitride (SRN) film, as it pertains to bi-stable switching, memory applications, and thermal sensing applications. In this work we utilize an SRN ring resonator device, which we first characterize at low-power and then compare thermo-optic coefficients, (2.12 ± 0.125) × 10 −4 /°C, obtained from thermal-heating induced resonance shifts to optically induced resonance shifts as well as estimated propagation loss and absorption. We then measure the time response of this nonlinearity demonstrating the relaxation time to be 18.7 us, indicating the mechanism to be thermal in nature. Finally, we demonstrate bi-stable optical switching.

42 ENGINEERING↗
DOE OSTI2024

Incompatibility as a Resource for Programmable Quantum Instruments

Quantum instruments represent the most general type of quantum measurement, as they incorporate processes with both classical and quantum outputs. In many scenarios, it may be desirable to have some “on-demand” device that is capable of implementing one of many possible instruments whenever the experimenter desires. We refer to such objects as programmable instrument devices (PIDs), and this paper studies PIDs from a resource-theoretic perspective. A physically important class of PIDs are those that do not require quantum memories to implement, and these are naturally “free” in this resource theory. Additionally, these free objects correspond precisely to the class of unsteerable channel assemblages in the study of channel steering. The traditional notion of measurement incompatibility emerges as a resource in this theory since any PID controlling an incompatible family of instruments requires a quantum memory to build. We identify an incompatibility preorder between PIDs based on whether one can be transformed into another using processes that do not require additional quantum memories. Necessary and sufficient conditions are derived for when such transformations are possible based on how well certain guessing games can be played using a given PID. Ultimately our results provide an operational characterization of incompatibility, and they offer semi-device-independent tests for incompatibility in the most general types of quantum instruments. Published by the American Physical Society 2024

Physics↗
DOE OSTI2022

GenASiS Basics: Object-oriented utilitarian functionality for large-scale physics simulations (Version 4)

GenASiS Basics provides modern Fortran classes furnishing extensible object-oriented utilitarian functionality for large-scale physics simulations on distributed memory supercomputers. This functionality includes physical units and constants; display to the screen or standard output device; message passing; I/O to disk; and runtime parameter management and usage statistics. Herein, this revision—Version 4 of Basics—includes a name change and additions to functionality, including the facilitation of direct communication between GPUs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Trajectory prediction dimensionality reduction for low-cost connected automated vehicle systems

Here, to facilitate low-cost connected automated vehicle (CAV) system development, this study proposes two interpretable dimensionality reduction techniques in vehicle trajectory prediction, i.e., the piecewise Taylor series approximation (PTA) and the piecewise Fourier series approximation (PFA), to lower computation complexity, reduce device investment, and decrease computation energy consumption. Two benchmarks are developed, the long short-term memory (LSTM)-based model without dimensionality reduction and the LSTM-based model with encoder-decoder (a widely used dimensionality reduction technique). Results show that the four predictions have similar accuracy, and the training time (proportional to computation energy consumption) of models with dimensionality reduction techniques is greatly reduced. The reduction is even more significant when PTA/PFA is used. Sensitivity analysis advises PFA/PTA parameter selections to reduce computation complexity without significant loss of prediction accuracy. Further, the robustness of the LSTM PTA/PFA is proven by the investigation of data noises.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Probing the Effects of the First Atomic Layer on the Dynamic Behavior of Sub-2 nm MgO/Al 2 O 3 Memristors

As electronic devices continue to scale down from the current sub-5 nm range, atomic-scale control of defects becomes increasingly crucial to suppressing their impact on the physical properties of the devices. Memristors present an excellent example as a nonlinear and dynamic device with high speed and endurance required for electronic applications ranging from neuromorphic computing to nonvolatile memories. Herein we investigate the impact of atomic defects in sub-2 nm thick MgO/Al 2 O 3 atomic layer stack (ALS) memristors that use an M1 (switching layer)/M2 (oxygen vacancy reservoir layer) bilayer structure grown using in vacuo atomic layer deposition (iALD). Intriguingly, we revealed a direct correlation of the atomic defects in the M2 layer with the memristor dynamic behavior using a combined analysis of in situ scanning tunneling spectroscopy (iSTS) on the M2 layer and ex situ characterization on the memristors. Specifically, incomplete coverage of the 1st ALD atomic layer of M2 on the electrode yields defects at the M2/electrode interface. Despite the monotonic increase of ALD coverage, by almost three-fold from ~30% to >90%, at completion of the M2 layer of ~ 0.7 nm in thickness, the impact of the defects on the M2/electrode interface has been found detrimental to both memristor switching speed and endurance. Guided by atomistic simulation, we addressed the issue of interface defects via tuning of the Al surface hydroxylation to increase the first atomic layer ALD coverage to ~75%, leading to improved memristor switching speed and endurance by several orders of magnitude. In conclusion, these findings shed light on the correlation between the atomic defects and the dynamic behavior of sub-2 nm memristors and the importance of minimizing the atomic defects in memristors for future electronic applications.

Atomic Layer Deposition↗
DOE OSTI2025

Experiences with SYCL on AMD GPUs with Kokkos

With the recent diversification of the hardware landscape in the high-performance computing (HPC) community, performance-portability solutions are becoming more and more important. One of the most popular choices is Kokkos, which recently became a Linux Foundation project. Most of its development is supported by the US Department of Energy and the French Alternative Energies and Atomic Energy Commission. Kokkos is implemented as a C++ library with multiple backends to support CPUs as well as various GPU architectures. These backends include OpenMP, CUDA, HIP, and also SCYL. This approach enables users to leverage the preferred vendor toolchain for the respective platform (e.g. CUDA, ROCm, OneAPI). The SYCL backend is used to target Intel GPUs, in particular to support the Aurora exascale supercomputer. However, SYCL itself also offers a large degree of portability, and in fact Kokkos’ CI for SYCL has been running on NVIDIA hardware due to a lack of access to Intel GPUs. In this report, we describe our experience with using Kokkos SYCL backend on AMD GPUs targeting the Frontier supercomputer at Oak Ridge National Laboratory. The two major SYCL implementations are DPC++ and AdaptiveCpp. While the Kokkos SYCL backend has been implemented using the former, the latter was the first implementation to target AMD GPUs. We will discuss the experience with both of these SYCL implementations in terms of functionality and performance. Using Kokkos to evaluate SYCL toolchains has a number of benefits. Kokkos’ use of SYCL is fairly complex, exercising features such as graphs, relocatable device functions, atomics – including for non-arithmetic types, as well as pinned and page migratable memory allocations. Kokkos also needs to implement capabilities such as Kokkos’ hierarchical parallelism that are not a straight-forward mapping to SYCL capabilities. Furthermore, a large number of libraries and applications that represent diverse use cases are implemented in Kokkos, providing readily available test cases for a toolchain evaluation. Preliminary results show that support for AMD GPUs in DPC++ is much less mature than for NVIDIA GPUs or Intel GPUs. While the situation has improved significantly over the last year, we still encounter many runtime failures, dispatching problems, and code generation issues. With AdaptiveCpp the challenges arise even earlier in the evaluation process. Since Kokkos’ SYCL implementation is largely focused on supporting Intel GPUs, we opted to leverage SYCL extensions which are available in DPC++ but not in AdaptiveCpp. Furthermore, AdaptiveCpp appears to be less conformant with the SYCL2020 standard which Kokkos relies on. In some cases, we are able to work around the lack of feature support, in other cases we have to disable certain Kokkos capabilities to evaluate the toolchain. Our evaluation will leverage Kokkos’ unit tests to establish basic functionality and feature completeness. We then use simple benchmarks for components of a CG implementation as a measure of usability and performance of the SYCL toolchains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Memory forensic analysis of a programmable logic controller in industrial control systems

In industrial control systems (ICS), programmable logic controllers (PLCs) are used to automate physical processes such as nuclear plants and power grid stations, and are often subject to cyber attacks. As in conventional IT domain, the memory analysis of the PLCs can help answer important forensic questions about the attack, such as the presence of malicious firmware, injection of modified control logic (the program running on the PLC), and manipulation of I/O devices (e.g., sensors and actuators). Unlike conventional IT domain, PLCs have heterogeneous hardware architecture, proprietary firmware and control software, making it challenging to employ a unified framework for their memory forensics. For merely extracting artifacts of forensic importance, reverse-engineering the firmware is a tedious task, and the effort needs to be repeated for every PLC model. As a community, a step-wise approach to tackle this challenge is to analyze the memory of specific PLCs, and subsequently find a generic framework applicable to all PLCs. Our work is a step forward in this direction. By following a methodology that focuses on the functional layer of PLCs instead of reverse engineering the firmware, we analyze the digital forensic artifacts available in a common PLC, Allen-Bradley ControlLogix 1756-L61. Before diving into the memory dump, we analyze the PLC control software to create a list of important artifacts that are sure to exist in the PLC memory dump. The approach employs a setup where PLC control software RSLogix-5000 is connected to the PLC, and the memory dump can be obtained as and when needed. We create test cases that sequentially highlight each category of artifacts, followed by an examination of the resultant impact on memory. After attaining the listed artifacts, we employ conventional string and known data searches to extract interesting information present in this PLC's memory. The memory analysis profile, presented as a Python library and shared with the community, can help a forensic investigator to readily extract forensic artifacts from the same model's controller. The adopted approach may help researchers in creating memory profile of other PLCs, and ultimately formulating a generic PLC memory analysis framework.

Rais, Muhammad Haris↗
DOE OSTI2023

Magnetic tunnel junctions with voltage tunable interlayer coupling for memory and sensor applications

Various examples are provided for magnetic tunnel junctions and applications thereof. In one example, a magnetic tunnel junction (MTJ) device includes a first ferromagnetic (FM) layer; a gadolinium oxide (GdOX) tunnel barrier disposed on the first ferromagnetic layer; and a second FM layer disposed on the GdOX tunnel barrier. In another example, a perpendicular MTJ (pMTJ) device includes a first layer including a magnetic material; a tunnel barrier disposed on the first layer to form the pMTJ; and a second layer including the magnetic material, the second layer disposed on the tunnel barrier.

Wang, Weigang↗
DOE OSTI2021

Recent Trends and Innovation in Additive Manufacturing of Soft Functional Materials

The growing demand for wearable devices, soft robotics, and tissue engineering in recent years has led to an increased effort in the field of soft materials. With the advent of personalized devices, the one-shape-fits-all manufacturing methods may soon no longer be the standard for the rapidly increasing market of soft devices. Recent findings have pushed technology and materials in the area of additive manufacturing (AM) as an alternative fabrication method for soft functional devices, taking geometrical designs and functionality to greater heights. For this reason, this review aims to highlights recent development and advances in AM processable soft materials with self-healing, shape memory, electronic, chromic or any combination of these functional properties. Furthermore, the influence of AM on the mechanical and physical properties on the functionality of these materials is expanded upon. Additionally, advances in soft devices in the fields of soft robotics, biomaterials, sensors, energy harvesters, and optoelectronics are discussed. Lastly, current challenges in AM for soft functional materials and future trends are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Field-free spin-orbit torque switching assisted by in-plane unconventional spin torque in ultrathin [Pt/Co] N

Electrical manipulation of magnetization without an external magnetic field is critical for the development of advanced non-volatile magnetic-memory technology that can achieve high memory density and low energy consumption. Several recent studies have revealed efficient out-of-plane spin-orbit torques (SOTs) in a variety of materials for field-free type-z SOT switching. Here, we report on the corresponding type-x configuration, showing significant in-plane unconventional spin polarizations from sputtered ultrathin [Pt/Co] N , which are either highly textured on single crystalline MgO substrates or randomly textured on SiO 2 coated Si substrates. The unconventional spin currents generated in the low-dimensional Co films result from the strong orbital magnetic moment, which has been observed by X-ray magnetic circular dichroism (XMCD) measurement. The x-polarized spin torque efficiency reaches up to −0.083 and favors complete field-free switching of CoFeB magnetized along the in-plane charge current direction. Micromagnetic simulations additionally demonstrate its lower switching current than type-y switching, especially in narrow current pulses. Our work provides additional pathways for electrical manipulation of spintronic devices in the pursuit of high-speed, high-density, and low-energy non-volatile memory.

42 ENGINEERING↗
DOE OSTI2026

Tunable Interfacial to Filamentary Resistive Switching Mechanism in Room-Temperature-Grown Amorphous YBa 2 Cu 3 O x with Excess Cu Addition

Resistive switching technologies have the potential not only to create large efficiency gains in computer memory but also to revolutionize emerging fields such as neuromorphic computing. In this paper, we report on novel resistive switching behavior in devices made from room-temperature-grown Cu-rich amorphous YBa 2 Cu 3 O x (YBCO) films, a material otherwise well-known as a high-temperature superconductor. In Nb:STO substrate/amorphous YBCO film (≈200 nm)/metallic Cu (15 nm)/metallic Pt (15 nm) devices, we demonstrate that the resistive switching can be tuned between mechanisms involving extended areas of the YBCO/electrode interface and a single-point filamentary mechanism simply by changing the Cu content of the deposition target and hence in the films. Changing the Cu content can also be used to optimize the properties of the devices further, with devices with an added 15 mol % of Cu in YBCO initially providing an on/off ratio >100, switching endurance potential >6500 cycles, and state retention >2 × 10 4 s, all at low switching fields of 0.3 MV/cm. The amalgam of promising resistive switching properties, fast growth (150 nm/min) at room temperature, and tuneability of the switching mechanism indicates the strong potential of this proof-of-concept amorphous system for future memory applications.

Cu↗
DOE OSTI2022

Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination

Post-training model compression can reduce the inference costs of deep neural networks, but uncompressed training still consumes enormous hardware resources and energy. To enable low-energy training on edge devices, it is highly desirable to directly train a compact neural network from scratch with a low memory cost. Low-rank tensor decomposition is an effective approach to reduce the memory and computing costs of large neural networks. However, directly training low-rank tensorized neural networks is a very challenging task because it is hard to determine a proper tensor rank a priori, and the tensor rank controls both model complexity and accuracy. Here, this paper presents a novel end-to-end framework for low-rank tensorized training. We first develop a Bayesian model that supports various low-rank tensor formats (e.g., CANDECOMP/PARAFAC, Tucker, tensor-train, and tensor-train matrix) and reduces neural network parameters with automatic rank determination during training. Then we develop a customized Bayesian solver to train large-scale tensorized neural networks. Our training methods shows orders-of-magnitude parameter reduction and little accuracy loss (or even better accuracy) in the experiments. On a very large deep learning recommendation system with over 4.2 ×10 9 model parameters, our method can reduce the parameter number to 1.6 ×10 5 automatically in the training process (i.e., by 2.6 ×10 4 times) while achieving almost the same accuracy. Code is available at https://github.com/colehawkins/bayesian-tensor-rank-determination.

compact neural networks↗
DOE OSTI2021

Leveraging Spin-Orbit Coupling in Ge/SiGe Heterostructures for Quantum Information Transfer

Hole spin qubits confined to lithographically - defined lateral quantum dots in Ge/SiGe heterostructures show great promise. On reason for this is the intrinsic spin - orbit coupling that allows all - electric control of the qubit. That same feature can be exploited as a coupling mechanism to coherently link spin qubits to a photon field in a superconducting resonator, which could, in principle, be used as a quantum bus to distribute quantum information. The work reported here advances the knowledge and technology required for such a demonstration. We discuss the device fabrication and characterization of different quantum dot designs and the demonstration of single hole occupation in multiple devices. Superconductor resonators fabricated using an outside vendor were found to have adequate performance and a path toward flip-chip integration with quantum devices is discussed. The results of an optical study exploring aspects of using implanted Ga as quantum memory in a Ge system are presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Title Coherent X-ray Studies of Surface Growth and Patterning Processes

X-ray Photon Correlation Spectroscopy (XPCS) is being developed as a tool to study nanoscale dynamics of fluctuations during thin film growth and surface patterning. XPCS examines the evolution of the X-ray scattering speckle pattern in reciprocal space to reveal dynamics information not accessible through any other means. Unlike low-coherence conventional X-ray scattering, which incoherently averages over different regions of a sample, coherent X-ray scattering is sensitive to the detailed structure of a given sample at that moment in time. In thin film growth processes, heterodyning, which occurs due to coherent mixing of two scattered signals, can be used to investigate the relationship between surface growth velocity and defect propagation. And, for polycrystalline thin film growth, the spatial coherence of the X-ray beam can substitute for the missing spatial coherence of the growth process to track layered growth in detail, even in a growth regime in which there are no conventional growth oscillations of the X-ray intensity. This has opened the door for detailed dynamics studies of individual atomic layers during real-world growth and patterning, not just in perfect single-crystal growth cases, which greatly expands the applicability of in-situ X-ray scattering methods. Step-flow dynamics in mounded polycrystalline growth has been studied separately for two thin film organic semiconductors deposited by thermal deposition in a vacuum environment, C60 and diindenoperylene (DIP). Highly oriented polycrystalline thin films are readily obtained in both systems, where mounds are composed of crystalline monolayer-height steps and terraces in a so-called wedding cake morphology. The formation of mounds is understood to be due to significant Ehrlich-Schwoebel step edge barriers that inhibit molecules from hopping down from one layer to the one below. The mounds exhibit local step flow, which can be monitored using coherent X-ray scattering. This is made possible due to heterodyning between scattering from the average mounds and the moving steps, which becomes visible in XPCS analysis. The effect of desorption, i.e. re-evaporation of deposited molecules is found to be important for understanding these processes. The impact of this work is to enable testing of models of step dynamics, the shape of mounds, and merging of mounds to form continuous thin films. Highly ordered polycrystalline thin films deposited on inexpensive substrates have applications in thin film solar cells and other organic electronic devices. In a separate set of experiments, speckle analysis during self-organized ion beam nanopatterning reveals memory stretching back to the beginning of patterning in the early stages and enables measurement of the velocity of self-organized patterns across surfaces providing the possibility of stringent new tests of the theory of pattern formation and motion.

36 MATERIALS SCIENCE↗