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At least 289 records · Page 16

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Targeted Writing and Deleting of Magnetic Skyrmions in Two-Terminal Nanowire Devices

Controllable writing and deleting of nanoscale magnetic skyrmions are key requirements for their use as information carriers for next-generation memory and computing technologies. While several schemes have been proposed, they require complex fabrication techniques or precisely tailored electrical inputs, which limits their long-term scalability. In this work, we demonstrate an alternative approach for writing and deleting skyrmions using conventional electrical pulses within a simple, two-terminal wire geometry. X-ray microscopy experiments and micromagnetic simulations establish the observed skyrmion creation and annihilation as arising from Joule heating and Oersted field effects of the current pulses, respectively. The unique characteristics of these writing and deleting schemes, such as spatial and temporal selectivity, together with the simplicity of the two-terminal device architecture, provide a flexible and scalable route to the viable applications of skyrmions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2024

A nonlinear journey from structural phase transitions to quantum annealing

Motivated by an exact mapping between equilibrium properties of a one-dimensional chain of quantum Ising spins in a transverse field (the transverse field Ising (TFI) model) and a two-dimensional classical array of particles in double-well potentials (the “$\phi$ 4 model”) with weak inter-chain coupling, we explore connections between the driven variants of the two systems. Here, we argue that coupling between the fundamental topological solitary waves in the form of kinks between neighboring chains in the classical $\phi$ 4 system is the analog of the competing effect of the transverse field on spin flips in the quantum TFI model. As an example application, we mimic simplified measurement protocols in a closed quantum model system by studying the classical $\phi$ 4 model subjected to periodic perturbations. This reveals memory/loss of memory and coherence/decoherence regimes, whose quantum analogs are essential in annealing phenomena. In particular, we examine regimes where the topological excitations control the thermal equilibration following perturbations. This paves the way for further explorations of the analogy between lower-dimensional linear quantum and higher-dimensional classical nonlinear systems.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Mechanical reticulation of polymeric-based closed cell foams

Polymeric based closed cell foams, such as shape memory polymer foams, contain bubbles. Making these bubbles continuous is called reticulation. Disclosed are embodiments of a device and method to controllably reticulate polymer-based closed cell foams by puncturing the membranes of these polymer-based closed cell foams.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Mechanical reticulation of polymeric-based closed cell foams

Rodriguez, Jennifer N.↗

DOE OSTI2024

Mechanical reticulation of polymeric-based closed cell foams

Rodriguez, Jennifer N.↗

DOE OSTI2026

Hierarchical Epoxy Structures via Tunable Polymerization-Induced Phase Separation Combined with Additive Manufacturing

Polymerization-induced phase separation (PIPS) allows for the control of thermoset morphologies and properties, enabling the tuning of domain sizes and thermomechanical response. However, its use in generating substructural features in additively manufactured materials has been limited. In this work, we combine epoxy PIPS with UV curable acrylate and rheological modifiers to print nano- to macro-phase separating materials via a two-step, dual-cure approach. This method enables direct ink write printing of hierarchical structures with both controlled morphologies through phase separation and macroscale architecture through print design. We find that formulations for phase-separating materials require judicious incorporation of additives to enable printability and to provide sufficient green strength. Atomic force microscopy-nano infrared mapping reveals tunable, reticulated nano- to micron-scale domains of the resultant multiphase materials and their morphology changes due to additives, resulting in alterations to thermomechanical and tensile properties. Shape memory behavior is also demonstrated through multimaterial additive manufacturing of epoxies with functionally graded internal morphology using active mixing techniques, highlighting this method’s ability to fabricate complex architectures with controlled morphologies and thermomechanical response.

Van Meter, Kylie E [Organic Materials Science, San↗

DOE OSTI2020

Logical gates embedding in artificial spin ice

The realization and study of arrays of interacting magnetic nanoislands, such as artificial spin ices, have reached mature levels of control that allow design and demonstration of exotic, collective behaviors not seen in natural materials. Advances in the direct manipulation of their local, binary moments also suggest a use as nanopatterned, interacting memory media, for computation within a magnetic memory. Recent experimental work has demonstrated the possibility of building logic gates from clusters of interacting magnetic domains, and yet the possibility of large scale integration of such gates can prove problematic even at the theoretical level. Here we introduce theoretically complete sets of logical gates, in principle realizable in an experiment, and we study the feasibility of their integration into tree-like circuits. By evaluating the fidelity control parameter between their collective behavior and their expected logic functionality we determine conditions for integration. Also, we test our numerical results against the presence of disorder in the couplings, showing that the design gate structure is robust to small coupling perturbations, and thus possibly to small imperfections in the fabrication of the islands.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

High-Endurance Magneto-Electronic Switchable Molecular Electronic Crystal

Electrically switchable magnetic and electronic properties are promising for quantum sensing and information technology. Here, we report an electrically driven magnetic and electronic phase transition in molecular electronic crystal, potassium-7,7,8,8-tetracyanoquinodimethan, with the magneto-electric switching over 105 cycles at room temperature. Electron spin resonance study reveals the cooperative transition between spin and charge degrees of freedom. In addition, the mechanistic spectroscopy studies suggest the charges in an inhomogeneous conductor–insulator mixed state. Furthermore, the findings shown here suggest electrically controlled ordering in strongly correlated molecular crystal leads to dynamic magneto-electric switching, paving the way for developing molecular-based memory and switching devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2024

Privacy-Preserving Control of Partitioned Energy Resources

Distributed energy resources are an increasingly important part of the electric grid. We examine the problem of partitioning a distributed energy resource among many users while providing privacy to them. In this model, clients can send requests to a server, the server can verify that the requests are valid and aggregate them, but it cannot see the actual values in the requests. Without privacy, each user is forced to reveal their daily schedule or energy use. Energy resources add a novel challenge that prior systems do not address: they require verifying limits on private power (a rate over time) and energy (a sum) values. Furthermore, the cryptographic mechanisms must run on embedded energy control systems. We describe Weft, a novel cryptographic system that verifies both power (rate) and energy (integral) constraints on private client values and aggregates them. The key insight behind the approach is to rely on additively homomorphic secret shares, which allows servers to compute sums from rates. We present 3 cryptographic proof systems with different system trade-off for embedded systems: bit-splitting proofs minimize memory use, sorting proofs minimize computation, and commitment proofs minimize network communication. Using bit-splitting proofs, it takes an IoT client using a CortexM microcontroller 4 minutes of compute time to privately control its share of an energy resource for a day at 20s granularity.

Laufer, Evan↗

DOE OSTI2026

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING↗

DOE OSTI2025

Manipulating Ferroelectric Topological Polar Structures with Twisted Light

Abstract The dynamic control of non‐equilibrium states represents a central challenge in condensed matter physics. While intense terahertz fields drive metal‐insulator transitions and ferroelectricity via soft phonon modes, recent theory suggests that twisted light with orbital angular momentum (OAM) offers a distinct route to manipulate ferroelectric order and stabilize topological excitations including skyrmions, vortices, and Hopfions. Control of ferroelectric polarization in quasi‐2D CsBiNb 2 O 7 (CBNO) is demonstrated using non‐resonant twisted ultra‐violet (UV) light (375 nm, 800 THz). Combining in situ X‐ray Bragg coherent diffractive imaging (BCDI), twisted optical Raman spectroscopy, and density functional theory (DFT), three‐dimensional (3D) ionic displacements, strain fields, and polarization changes are resolved in single crystals. Operando measurements reveal light‐induced strain hysteresis under twisted light–a hallmark of nonlinear, history‐dependent ferroelastic switching driven by OAM. Discrete, irreversible domain transitions emerge as the topological charge ℓ is cycled, stabilizing non‐trivial domain textures including vortex‐antivortex pairs, Bloch/anti‐Bloch points, and merons. These persist after OAM removal, indicating a memory effect. Competing mechanisms are discussed, including multiphoton absorption, strain‐mediated polarization switching, and defect‐wall interactions. The findings establish structured light as a tool for deterministic, reversible control of ferroic states, enabling optically reconfigurable non‐volatile devices.

Chemistry↗

DOE OSTI2025

Oxidative stress is a shared characteristic of ME/CFS and Long COVID

Over 65 million individuals worldwide are estimated to have Long COVID (LC), a complex multisystemic condition marked by fatigue, post-exertional malaise, and other symptoms resembling myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). With no clinically approved treatments or reliable diagnostic markers, there is an urgent need to define the molecular underpinnings of these conditions. By studying bioenergetic characteristics of peripheral blood lymphocytes in 25 healthy controls, 27 ME/CFS, and 20 LC donors, we find both ME/CFS and LC donors exhibit signs of elevated oxidative stress, especially in the memory subset. Using a combination of flow cytometry, RNA-seq, mass spectrometry, and systems chemistry analysis, we observed aberrations in reactive oxygen species (ROS) clearance pathways including elevated glutathione levels, decreases in mitochondrial superoxide dismutase protein levels, and glutathione peroxidase 4–mediated lipid oxidative damage. Strikingly, these redox pathways changes show sex-specific trends. While ME/CFS females exhibit higher total ROS and mitochondrial calcium levels, males have normal ROS levels, with pronounced mitochondrial lipid oxidative damage. In females, these higher ROS levels correlate with T cell hyperproliferation, consistent with the known role of elevated ROS in initiating proliferation. This hyperproliferation can be attenuated by metformin, suggesting this Food and Drug Administration (FDA)-approved drug as a possible treatment, as also suggested by a recent clinical study of LC patients. Moreover, these results suggest a shared mechanistic basis for the systemic phenotypes of ME/CFS and LC, which can be detected by quantitative blood cell measurements, and that effective, patient-tailored drugs might be discovered using standard lymphocyte stimulation assays.

ME/CFS↗

DOE OSTI2021

Progress and Challenges for Memtransistors in Neuromorphic Circuits and Systems

Due to the increasing importance of artificial intelligence (AI), significant recent effort has been devoted to the development of neuromorphic circuits that seek to emulate the energy-efficient information processing of the brain. While non-volatile memory (NVM) based on resistive switches, phase-change memory, and magnetic tunnel junctions has shown potential for implementing neural networks, additional multi-terminal device concepts are required for more sophisticated bio-realistic functions. Of particular interest are memtransistors based on low-dimensional nanomaterials, which are capable of electrostatically tuning memory and learning behavior at the device level. Herein, a conceptual overview of the memtransistor is provided in the context of neuromorphic circuits. Recent progress is surveyed for memtransistors and related multi-terminal NVM devices including dual-gated floating-gate memories, dual-gated ferroelectric transistors, and dual-gated van der Waals heterojunctions. Further, the different materials systems and device architectures are classified based on the degree of control and relative tunability of synaptic behavior, with an emphasis on device concepts that harness the reduced dimensionality, weak electrostatic screening, and phase-changes properties of nanomaterials. Finally, strategies for achieving wafer-scale integration of memtransistors and multi-terminal NVM devices are delineated, with specific attention given to the materials challenges for practical neuromorphic circuits.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Maximizing dynamic range and performance of anatase TiO 2 ECRAM through structure and programming

Here, in this study, we investigate the structure-dependent modulation characteristics of all-solid-state three-terminal electrochemical random-access memory (ECRAM) based on an anatase Li x TiO 2 channel. By directly comparing “asymmetric” and “symmetric” ECRAM device architectures, we reveal significant insight into the impact of a non-zero gate-drain open-circuit voltage and its influence on voltage vs. current-controlled gating. We also explore the impact of potentiation/depression write parameters on the symmetry, linearity, and dynamic range of the device response. Together, initial results from optimizing structure and programming approaches yielded unprecedented G max /G min ratios of >1,000 for ECRAM and hundreds of tunable memory states with excellent linearity and symmetry. Simulations based on these ECRAM devices further illustrate the promise of this analog memory technology, achieving near 2% classification error in the MNIST digit recognition benchmark for a range of training parameters compared to a theoretical best of 1.66% and outperforming other device models extracted from the literature.

AIHWKit↗

DOE OSTI2023

Tuning In-Plane Magnetic Anisotropy and Interfacial Exchange Coupling in Epitaxial La 2/3 Sr 1/3 CoO 3 /La 2/3 Sr 1/3 MnO 3 Heterostructures

Controlling the in-plane magnetocrystalline anisotropy and interfacial exchange coupling between ferromagnetic (FM) layers plays a key role in next-generation spintronic and magnetic memory devices. In this work, we explored the effect of tuning the magnetocrystalline anisotropy of La 2/3 Sr 1/3 CoO 3 (LSCO) and La 2/3 Sr 1/3 MnO 3 (LSMO) layers and the corresponding effect on interfacial exchange coupling by adjusting the thickness of the LSCO layer (t LSCO ). The epitaxial LSCO/LSMO bilayers were grown on (110) o -oriented NdGaO 3 (NGO) substrates with a fixed LSMO (top layer) thickness of 6 nm and LSCO (bottom layer) thicknesses varying from 1 to 10 nm. Despite the small difference (~0.2%) in lattice mismatch between the two in-plane directions, [001] o and [11̅0] o , a pronounced in-plane magnetic anisotropy was observed. Soft X-ray magnetic circular dichroism hysteresis loops revealed that for t LSCO ≤ 4 nm, the easy axes for both LSCO and LSMO layers were along the [001] o direction, and the LSCO layer was characterized by magnetically active Co 2+ ions that strongly coupled to the LSMO layer. No exchange bias effect was observed in the hysteresis loops. In contrast, along the [11̅0] o direction, the LSCO and LSMO layers displayed a small difference in their coercivity values, and a small exchange bias shift was observed. As t LSCO increased above 4 nm, the easy axis for the LSCO layer remained along the [100] o direction, but it gradually rotated to the [11̅0] o direction for the LSMO layer, resulting in a large negative exchange bias shift. Therefore, we provide a way to control the magnetocrystalline anisotropy and exchange bias by tuning the interfacial exchange coupling between the two FM layers.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Approaches for the Simulation of Coupled Processes in Evolving Fractured Porous Media Enabled by Exascale Computing

Models have historically represented fractured porous media with continuum descriptions that characterize the media using bulk parameters. The impact of small-scale features is not captured in these models, although they may be controlling the performance of subsurface applications. Pore-scale models can simulate processes in small-scale features by representing the pore space geometry explicitly but are computationally expensive for large domains. The alternative multiscale approach entails the combination of pore-scale and continuum-scale descriptions in a single framework. We use Chombo-Crunch, a computational capability that discretizes complex geometries with an adaptive, embedded boundary method to contrast these two approaches. Chombo-Crunch takes advantage of recent computational performance and memory bandwidth improvements resulting from the emergence of exascale computing resources. These combined improvements enable the efficient simulation of reactive transport in fractured media with a high degree of fidelity and the ability to capture the control small-scale processes exert on the overall medium evolution.

42 ENGINEERING↗

DOE OSTI2022

Reduced Stochastic Resistive Switching in Organic-Inorganic Hybrid Memristors by Vapor-Phase Infiltration

We report resistive random-access memory (RRAM) is promising for next-generation data storage and non-von Neumann computing hardware. However, tuning device switching characteristics and particularly, controlling their stochastic variation remain as critical challenges. Here, new organic-inorganic hybrid RRAM media are reported whose bipolar switching characteristics and stochasticity can be controlled by vapor-phase infiltration (VPI), an ex situ hybridization technique derived from atomic layer deposition. Hybrid RRAMs based on AlO x -infiltrated SU-8 feature facile tunability of device switching voltages, off-state current, and on-off ratio by adjusting the amount of infiltrated AlO x in the hybrid. Furthermore, a significant reduction in the stochastic, cycle-to-cycle variations of switching parameters is enabled by AlO x infiltration, driven by the infiltration-induced changes in mechanical, dielectric, and chemical properties of organic medium and their influence on the dimension and formation characteristics of conductive filaments. Finally, multi-level analog switching potentially useful for neuromorphic applications are demonstrated, along with direct, one-step device patterning exploiting the negative-tone resist feature of SU-8. With the demonstrated control over switching characteristics and stochastic variation, combined with analog switching and one-step patterning capabilities, the results not only present a novel hybrid medium for RRAM applications but also showcase the utility of VPI for developing new, high-performance hybrid RRAM devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2023

Deployment of Dynamic Neural Network Optimization to Minimize Heat Rate During Ramping for Coal Power Plants (Final Technical Report)

Much success was achieved throughout the course of this project. A successful implementation of Dynamic Neural Network Optimization (D-NNO) was coupled with Adaptive Predictive Controls (APC) and a novel hardware installation comprised of an advanced sensor network (ASN) measuring mass-weighted averages of flue gas constituents above the horizontal superheater of a coal-fired utility boiler. From 2019 through 2023 (including an extension due to COVID delays), the team was able to prototype, evaluate, deploy, iterate, and ultimately finalize an advanced closed-loop control D-NNO system which demonstrated the ability to: •improve unit efficiency ~2.0% relative to unoptimized operation (represented as total fuel fired per MWh generated) •improve unit NOx emission rates 10%+ beyond static optimization baselines •improve unit temperature stability as much as 58% and on average 12% •improve operating load stability as much as 35% The culmination of this project has generated an advanced methodology of deploying specially designed recurrent neural networks (long short-term memory, gated recurrent unit, encoder-decoder networks, transformers, etc.), customized trajectory planning and closed-loop optimization modules capable of adapting to live electric grid responses and demands, self-tuning and adaptive expert controls constantly adjusting prediction parameters to real-time unit behavior, and a hardware/software package able to reliably calculate net unit heat rate (NUHR) in real-time using flue gas constituents, machine learning, and known combustion relationships. Through this real-time NUHR value, immediate feedback on system adjustments relative to operating efficiency was available, allowing for rapid improvements to system performance. In addition to development and deployment of the advanced D-NNO system, the approach methodology has been readily commercialized through the project platform Griffin Open Systems, LLC, the D-NNO software platform host. Similar methodologies to those developed by this project have already been deployed at 5 other units across the United States, with another 6 implementations scheduled, and more expected. Over the course of the project, multiple academic papers were submitted and accepted for publication within esteemed academic journals, and PhD students were trained and graduated, as well as undergraduate students becoming involved and participating to project objectives.

01 COAL, LIGNITE, AND PEAT↗