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At least 235 records · Page 13

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NASA NTRS2008

High-Density, High-Bandwidth, Multilevel Holographic Memory

A proposed holographic memory system would be capable of storing data at unprecedentedly high density, and its data transfer performance in both reading and writing would be characterized by exceptionally high bandwidth. The capabilities of the proposed system would greatly exceed even those of a state-of-the art memory system, based on binary holograms (in which each pixel value represents 0 or 1), that can hold .1 terabyte of data and can support a reading or writing rate as high as 1 Gb/s. The storage capacity of the state-of-theart system cannot be increased without also increasing the volume and mass of the system. However, in principle, the storage capacity could be increased greatly, without significantly increasing the volume and mass, if multilevel holograms were used instead of binary holograms. For example, a 3-bit (8-level) hologram could store 8 terabytes, or an 8-bit (256-level) hologram could store 256 terabytes, in a system having little or no more size and mass than does the state-of-the-art 1-terabyte binary holographic memory. The proposed system would utilize multilevel holograms. The system would include lasers, imaging lenses and other beam-forming optics, a block photorefractive crystal wherein the holograms would be formed, and two multilevel spatial light modulators in the form of commercially available deformable-mirror-device spatial light modulators (DMDSLMs) made for use in high speed input conversion of data up to 12 bits. For readout, the system would also include two arrays of complementary metal oxide/semiconductor (CMOS) photodetectors matching the spatial light modulators. The system would further include a reference-beam sterring device (equivalent of a scanning mirror), containing no sliding parts, that could be either a liquid-crystal phased-array device or a microscopic mirror actuated by a high-speed microelectromechanical system. Time-multiplexing and the multilevel nature of the DMDSLM would be exploited to enable writing and reading of multilevel holograms. The DMDSLM would also enable transfer of data at a rate of 7.6 Gb/s or perhaps somewhat higher.

Chao, Tien-Hsin↗

DOE OSTI2021

Ultrawide-bandgap semiconductors: An overview

Ultrawide-bandgap (UWBG) semiconductor technology is presently going through a renaissance exemplified by advances in material-level understanding, extensions of known concepts to new materials, novel device concepts, and new applications. as such, this focus issue presents a timely selection of papers spanning the current state of the art in UWBG materials and applications, including both experimental results and theoretical developments. It covers broad research subtopics on UWBG bulk crystals and substrate technologies, UWBG defect science and doping, UWBG epitaxy, UWBG electronic and optoelectronic properties, and UWBG power devices and emitters. In this overview article, we consolidate the fundamentals and background of key UWBG semiconductors including aluminum gallium nitride alloys (Al x Ga 1– x N), boron nitride (BN), diamond, β-phase gallium oxide (β-Ga 2 O 3 ), and a number of other UWBG binary and ternary oxides.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Efficient human activity recognition with spatio-temporal spiking neural networks

In this study, we explore Human Activity Recognition (HAR), a task that aims to predict individuals' daily activities utilizing time series data obtained from wearable sensors for health-related applications. Although recent research has predominantly employed end-to-end Artificial Neural Networks (ANNs) for feature extraction and classification in HAR, these approaches impose a substantial computational load on wearable devices and exhibit limitations in temporal feature extraction due to their activation functions. To address these challenges, we propose the application of Spiking Neural Networks (SNNs), an architecture inspired by the characteristics of biological neurons, to HAR tasks. SNNs accumulate input activation as presynaptic potential charges and generate a binary spike upon surpassing a predetermined threshold. This unique property facilitates spatio-temporal feature extraction and confers the advantage of low-power computation attributable to binary spikes. We conduct rigorous experiments on three distinct HAR datasets using SNNs, demonstrating that our approach attains competitive or superior performance relative to ANNs, while concurrently reducing energy consumption by up to 94%.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2002

Novel Advancements in Internet-Based Real Time Data Technologies

AZ Technology has been working with MSFC Ground Systems Department to find ways to make it easier for remote experimenters (RPI's) to monitor their International Space Station (ISS) payloads in real-time from anywhere using standard/familiar devices. AZ Technology was awarded an SBIR Phase I grant to research the technologies behind and advancements of distributing live ISS data across the Internet. That research resulted in a product called "EZStream" which is in use on several ISS-related projects. Although the initial implementation is geared toward ISS, the architecture and lessons learned are applicable to other space-related programs. This paper presents the high-level architecture and components that make up EZStream. A combination of commercial-off-the-shelf (COTS) and custom components were used and their interaction will be discussed. The server is powered by Apache's Jakarta-Tomcat web server/servlet engine. User accounts are maintained in a My SQL database. Both Tomcat and MySQL are Open Source products. When used for ISS, EZStream pulls the live data directly from NASA's Telescience Resource Kit (TReK) API. TReK parses the ISS data stream into individual measurement parameters and performs on-the- fly engineering unit conversion and range checking before passing the data to EZStream for distribution. TReK is provided by NASA at no charge to ISS experimenters. By using a combination of well established Open Source, NASA-supplied. and AZ Technology-developed components, operations using EZStream are robust and economical. Security over the Internet is a major concern on most space programs. This paper describes how EZStream provides for secure connection to and transmission of space- related data over the public Internet. Display pages that show sensitive data can be placed under access control by EZStream. Users are required to login before being allowed to pull up those web pages. To enhance security, the EZStream client/server data transmissions can be encrypted to preclude interception. EZStream was developed to make use of a host of standard platforms and protocols. Each are discussed in detail in this paper. The I3ZStream server is written as Java Servlets. This allows different platforms (i.e. Windows, Unix, Linux . Mac) to host the server portion. The EZStream client component is written in two different flavors: JavaBean and ActiveX. The JavaBean component is used to develop Java Applet displays. The ActiveX component is used for developing ActiveX-based displays. Remote user devices will be covered including web browsers on PC#s and scaled-down displays for PDA's and smart cell phones. As mentioned. the interaction between EZStream (web/data server) and TReK (data source) will be covered as related to ISS. EZStream is being enhanced to receive and parse binary data stream directly. This makes EZStream beneficial to both the ISS International Partners and non-NASA applications (i.e. factory floor monitoring). The options for developing client-side display web pages will be addressed along with the development of tools to allow creation of display web pages by non-programmers.

Myers, Gerry↗

NASA NTRS2009

Auto-Generated Semantic Processing Services

Auto-Generated Semantic Processing (AGSP) Services is a suite of software tools for automated generation of other computer programs, denoted cross-platform semantic adapters, that support interoperability of computer-based communication systems that utilize a variety of both new and legacy communication software running in a variety of operating- system/computer-hardware combinations. AGSP has numerous potential uses in military, space-exploration, and other government applications as well as in commercial telecommunications. The cross-platform semantic adapters take advantage of common features of computer- based communication systems to enforce semantics, messaging protocols, and standards of processing of streams of binary data to ensure integrity of data and consistency of meaning among interoperating systems. The auto-generation aspect of AGSP Services reduces development time and effort by emphasizing specification and minimizing implementation: In effect, the design, building, and debugging of software for effecting conversions among complex communication protocols, custom device mappings, and unique data-manipulation algorithms is replaced with metadata specifications that map to an abstract platform-independent communications model. AGSP Services is modular and has been shown to be easily integrable into new and legacy NASA flight and ground communication systems.

Davis, Rodney↗

DOE OSTI2025

Performance Evaluation of Vertical Federated Machine Learning Against Adversarial Threats on Wide-Area Control System: Preprint

Federated machine learning (FL) is gaining significant popularity to develop cybersecurity solutions in power grids because of its advanced capability to support decentralized data handing at local devices, its privacy preservation, and its low-bandwidth requirement. However, the evolving adversarial machine learning (AML) threats raise significant concerns for the cybersecurity of FL architectures. The FL-based split neural network (SplitNN) achieves high performance through the decentralized training of local neural network models while preserving data privacy across multiple entities. In this paper, we propose a methodology for evaluating the performance of a vertical FLbased anomaly detector against different types of AML attacks, including denial-of-service attacks, adversarial data injection attacks, and replay attacks on the trained local models deployed in the grid network. For a case study, we consider the modified IEEE 13-bus system, and we develop SplitNN-based binary and multiclass classification models to detect, locate, and identify different types of data integrity attacks on the volt-watt control with two pooling layers: maximum pooling and AvgPool. Our experimental results, computed through performance metrics, reveal that the severity of these AML attacks varies with the integrated pooling mechanism, the type of classification model, and the nature of the cyberattack. Further, the AML attacks negatively impacted the prediction time per sample for the pretrained SplitNN during the online testing.

adversarial threats↗

DOE OSTI2024

Tetrahydrofuran Processable Organic Solar Cells with 19.45% Efficiency Realized by Introducing High Molecular Dipole Unit Into the Terpolymer

Developing organic solar cells (OSCs) processable with halogen‐free, non‐aromatic solvents is crucial for practical applications, yet challenging due to the limited solubility of most photoactive materials. Here, this study introduces high‐performance terpolymers processable in tetrahydrofuran (THF) by incorporating dithienophthalimide (DPI) into the PM6 backbone. DPI extends the absorption band, lowers HOMO levels, and improves THF solubility and film crystallinity through its large dipole moment effect. Optimal PBD‐10:L8‐BO devices processed with THF achieved a competitive power conversion efficiency (PCE) of 18.79%, approaching chloroform‐processed devices (19.04%). By introducing PBTz‐F as a second donor, ternary OSCs reached an impressive 19.45% PCE when processed with THF. This improvement stems from enhanced photon generation, improved morphology, better charge transport, longer exciton lifetimes, efficient charge dissociation and collection, and suppressed recombination. These PCEs of 18.79% and 19.45% for binary and ternary blend OSCs, respectively, represent the highest reported efficiencies for OSCs processed with halogen‐free, non‐aromatic solvents. This work demonstrates significant progress in eco‐friendly OSC fabrication, paving the way for more sustainable and commercially viable organic photovoltaic technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Quantum annealing algorithms for Boolean tensor networks

Abstract Quantum annealers manufactured by D-Wave Systems, Inc., are computational devices capable of finding high-quality heuristic solutions of NP-hard problems. In this contribution, we explore the potential and effectiveness of such quantum annealers for computing Boolean tensor networks. Tensors offer a natural way to model high-dimensional data commonplace in many scientific fields, and representing a binary tensor as a Boolean tensor network is the task of expressing a tensor containing categorical (i.e., $$\{0, 1\}$$ { 0 , 1 } ) values as a product of low dimensional binary tensors. A Boolean tensor network is computed by Boolean tensor decomposition, and it is usually not exact. The aim of such decomposition is to minimize the given distance measure between the high-dimensional input tensor and the product of lower-dimensional (usually three-dimensional) tensors and matrices representing the tensor network. In this paper, we introduce and analyze three general algorithms for Boolean tensor networks: Tucker, Tensor Train, and Hierarchical Tucker networks. The computation of a Boolean tensor network is reduced to a sequence of Boolean matrix factorizations, which we show can be expressed as a quadratic unconstrained binary optimization problem suitable for solving on a quantum annealer. By using a novel method we introduce called parallel quantum annealing, we demonstrate that Boolean tensor’s with up to millions of elements can be decomposed efficiently using a DWave 2000Q quantum annealer.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1996

BPSK Demodulation Using Digital Signal Processing

A digital communications signal is a sinusoidal waveform that is modified by a binary (digital) information signal. The sinusoidal waveform is called the carrier. The carrier may be modified in amplitude, frequency, phase, or a combination of these. In this project a binary phase shift keyed (BPSK) signal is the communication signal. In a BPSK signal the phase of the carrier is set to one of two states, 180 degrees apart, by a binary (i.e., 1 or 0) information signal. A digital signal is a sampled version of a "real world" time continuous signal. The digital signal is generated by sampling the continuous signal at discrete points in time. The rate at which the signal is sampled is called the sampling rate (f(s)). The device that performs this operation is called an analog-to-digital (A/D) converter or a digitizer. The digital signal is composed of the sequence of individual values of the sampled BPSK signal. Digital signal processing (DSP) is the modification of the digital signal by mathematical operations. A device that performs this processing is called a digital signal processor. After processing, the digital signal may then be converted back to an analog signal using a digital-to-analog (D/A) converter. The goal of this project is to develop a system that will recover the digital information from a BPSK signal using DSP techniques. The project is broken down into the following steps: (1) Development of the algorithms required to demodulate the BPSK signal; (2) Simulation of the system; and (3) Implementation a BPSK receiver using digital signal processing hardware.

Garcia, Thomas R.↗

DOE OSTI2021

Scalable nanomanufacturing of chalcogenide inks: a case study on thermoelectric V–VI nanoplates

Solution-processed semiconducting main-group chalcogenides (MMCs) have attracted increasing research interest for next-generation device technologies owing to their unique nanostructures and superior properties. To achieve the full potential of MMCs, the development of highly universal, scalable, and sustainable synthesis and processing methods of chalcogenide particles is thus becoming progressively more important. Here we studied scalable factors for the synthesis of two-dimensional (2D) V–VI chalcogenide nanoplates (M 2 Q 3 : M = Sb, Bi; Q = Se, Te) and systematically investigated their colloidal behaviour and chemical stability. Based on a solvent engineering technique, we demonstrated scale-up syntheses of MMCs up to a 900% increase of batch size compared with conventional hydrazine-based gram-level syntheses, and such a scalable approach is highly applicable to various binary and ternary MMCs. Furthermore, we studied the stability of printable chalcogenide nanoparticle inks with several formulation factors including solvents, additives, and pH values, resulting in inks with high chemical stability (>4 months). As a proof of concept, we applied our solution-processed chalcogenide particles to multiple additive manufacturing methods, confirming the high printability and processability of MMC inks. Furthermore, the ability to combine the top-down designing freedom of additive manufacturing with bottom-up scalable synthesis of chalcogenide particles promises great opportunities for large-scale design and manufacturing of chalcogenide-based functional devices for broad application.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Uncontrolled Learning: Codesign of Neuromorphic Hardware Topology for Neuromorphic Algorithms

Neuromorphic computing has the potential to revolutionize future technologies and our understanding of intelligence, yet it remains challenging to realize in practice. The learning-from-mistakes algorithm, inspired by the brain's simple learning rules of inhibition and pruning, is one of the few brain-like training methods. This algorithm is implemented in neuromorphic memristive hardware through a codesign process that evaluates essential hardware trade-offs. While the algorithm effectively trains small networks as binary classifiers and perceptrons, performance declines significantly with increasing network size unless the hardware is tailored to the algorithm. This work investigates the trade-offs between depth, controllability, and capacity—the number of learnable patterns—in neuromorphic hardware. This highlights the importance of topology and governing equations, providing theoretical tools to evaluate a device's computational capacity based on its measurements and circuit structure. The findings show that breaking neural network symmetry enhances both controllability and capacity. Additionally, by pruning the circuit, neuromorphic algorithms in all-memristive circuits can utilize stochastic resources to create local contrasts in network weights. Through combined experimental and simulation efforts, the parameters are identified that enable networks to exhibit emergent intelligence from simple rules, advancing the potential of neuromorphic computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1995

Prototype Focal-Plane-Array Optoelectronic Image Processor

Prototype very-large-scale integrated (VLSI) planar array of optoelectronic processing elements combines speed of optical input and output with flexibility of reconfiguration (programmability) of electronic processing medium. Basic concept of processor described in "Optical-Input, Optical-Output Morphological Processor" (NPO-18174). Performs binary operations on binary (black and white) images. Each processing element corresponds to one picture element of image and located at that picture element. Includes input-plane photodetector in form of parasitic phototransistor part of processing circuit. Output of each processing circuit used to modulate one picture element in output-plane liquid-crystal display device. Intended to implement morphological processing algorithms that transform image into set of features suitable for high-level processing; e.g., recognition.

Fang, Wai-Chi↗

DOE OSTI2024

Advanced Closures for Nonlinear Fluid Simulations of Plasmas (Final Report)

Advanced Closures for Nonlinear Fluid Simulations of Plasmas E. Held, Utah State University (Principal Investigator) J.-Y. Ji, Utah State University (Co-Investigator) Utah State University (USU) continued to develop and apply closures for hybrid fluid/kinetic simulations of magnetized fusion plasmas. The closures developed by USU's fusion theory and computation group use the drift ordering and are referred to as "continuum" and "general moment" approaches. They differ in their representation for the distribution functions which probabilistically describe the density of particles in 5 dimensional phase space. The two chosen velocity variables, needed in studies of kinetic physics for magnetized plasmas, are the speed and the component of a particle's velocity along the magnetic field. In magnetized plasmas, the charged particle trajectories are tied closely to the magnetic field lines. Both approaches account for binary interactions between particles using the Coulomb collision operator. Theoretical and computational development along both lines provided avenues for verification between the two approaches. This funding allowed USU to further develop physically accurate and numerically efficient models that advance our understanding of kinetic physics in experiments like the International Thermonuclear Experimental Reactor (ITER). The ITER device will likely prove the physical practicality of thermonuclear fusion by producing 500 megawatts of clean, abundant fusion power. This work helped to realize this goal by advancing our simulation capability using hybrid fluid/kinetic models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1988

Operation of a deformable mirror device as a Fourier plane phase modulating filter

The operation of a deformable mirror device (DMD) as a Fourier plane phase modulating filter is described. An analysis of the optical characteristics of the DMD elements as phase modulators is summarized. Analytical and experimental results indicating the existence of a quasi-phase-only operational mode are presented. These results are used to specify the mirror deflection required to implement a binary phase-only image correlation operation. An optical correlator system is implemented using the DMD Fourier plane filter and experimental results from this system are compared with computer simulations of the correlator operation.

Florence, James M.↗

NASA NTRS2004

Design Space Issues for Intrinsic Evolvable Hardware

This paper discusses the problem of increased programming time for intrinsic evolvable hardware (EM) as the complexity of the circuit grows. As the circuit becomes more complex, then more components will be required and a longer programming string, L, is required. We develop equations for the size of the population, n, and the number of generations required for the population to converge, based on L. Our analytical results show that even though the design search space grows as 2L (assuming a binary programming string), the number of circuit evaluations, n*ngen, only grows as O(Lg3), or slightly less than O(L). This makes evolvable techniques a good tool for exploring large design spaces. The major hurdle for intrinsic EHW is evaluation time for each possible circuit. The evaluation time involves downloading the bit string to the device, updating the device configuration, measuring the output and then transferring the output data to the control processor. Each of these steps must be done for each member of the population. The processing time of the computer becomes negligible since the selection/crossover/mutation steps are only done once per generation. Evaluation time presently limits intrinsic evolvable hardware techniques to designing only small or medium-sized circuits. To evolve large or complicated circuits, several researchers have proposed using hierarchical design or reuse techniques where submodules are combined together to form complex circuits. However, these practical approaches limit the search space of available designs and preclude utilizing parasitic coupling or other effects within the programmable device. The practical approaches also raise the issue of why intrinsic EHW techniques do not easily apply to large design spaces, since the analytical results show only an O(L) complexity growth.

Hereford, James↗

DOE OSTI2023

Polythiophene-based terpolymers with modulated aggregation behaviors for high-performance organic solar cells with 16.6% efficiency

Polythiophenes (PTs) are an attractive class of polymer donors (PDs) for organic solar cells (OSCs) owing to their relatively simple structures and scalable synthesis. Herein, a series of chlorinated thiazole-incorporated PT terpolymers are designed and high-performance OSCs with a power conversion efficiency (PCE) of 16.6% are demonstrated. By incorporating two different units, 3,3'-difluoro-2,2'-bithiophene (T2F2) and thieno[3,2-b]thiophene (TT), the aggregation properties of the terpolymers (PTz-FX; X = 0, 30, 50, 70, and 100, where X represents the mole percentage of T2F2 to total T2F2 +TT) are modulated. Among the PTz-FX series, PTz-F70 is found to be the optimal P D because its suitably tuned aggregation property leads to an optimized blend morphology with well-developed crystalline structures and donor–acceptor intermixed domains. The balanced morphology not only promotes charge generation/transport but also suppresses charge recombination in OSC devices. Thus, the PTz-F70-based OSCs achieve the highest PCE (16.6%), outperforming the OSCs based on PTz-FX with extremely strong (PTz-F100, PCE = 14.7%) or weak (PTz-F0, PCE = 12.0%) aggregation properties. The PCE of the PTz-F70-based OSCs is one of the highest performances among PT-based binary OSCs. Finally, this study highlights the importance of controlling the aggregation property of PTs for achieving high-performance PT-based OSCs.

14 SOLAR ENERGY↗

DOE OSTI2026

Harmonic suppression gratings for soft X-ray monochromators

We describe an approach to harmonic suppression in soft X-ray monochromators by engineering the reflection grating’s diffraction pattern to approximate a sinusoidal amplitude. At synchrotron and free-electron laser sources, X-ray beamlines powered by insertion devices produce a spectrum containing harmonic photon energies that can couple unwanted light into experiments. Beamlines in the soft X-ray energy range (100 eV to 2 keV) commonly employ energy-filtering elements to suppress these harmonics. Available approaches tend to be inefficient, significantly reducing the transmitted power. We show that with pseudo-grayscale binary halftone patterns, gratings can approximate a sinusoidal amplitude and suppress higher diffraction orders. Prototype demonstrations of lithographically fabricated gratings were conducted on a soft X-ray beamline with photon energies of 110 eV and 330 eV. Relative to a square-wave amplitude grating, the third-harmonic intensity was reduced by a factor of 9.0 with a first-order efficiency reduction of 38%.

Goldberg, Kenneth A. [Lawrence Berkeley National L↗

DOE OSTI2025

Probability Density Function for the spatial and intensity distribution of neutron-induced defects in Silicon

The ability to model semiconductor device degradation under neutron irradiation depends upon having a robust modeling capability for the neutron-induced collision cascades as well as a means to analytically fit the resulting probability distributions of defect production and ionizing energy deposition for purposes of extrapolation to low-probability, high-consequence scenarios. In this paper, the widely-utilized binary collision approximation codes MARLOWE and SRIM are deployed in conjunction with a critical examination of their parameterizations as benchmarked against higher-fidelity molecular dynamics simulations. A simple 3-parameter form described by the Generalized Logistic Distribution is shown to be a good fit to Frenkel pair and ionization intensity distributions in bulk silicon. The BCA codes are then applied to simulate cascades in 5 nm layers of a representative gate-all-around nanosheet transistor, where joint probability distributions of threshold levels of damage to multiple layers are evaluated.

36 MATERIALS SCIENCE↗