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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Antiferromagnetic memory storage devices from magnetic transition metal dichalcogenides

Switchable antiferromagnetic (AFM) memory devices are provided based on magnetically intercalated transition metal dichalcogenides (TMDs) of the form AxMC2, where A is a magnetic element of stoichiometry x between 0 and 1, M is a transition metal of stoichiometry 1, and C is a chalcogen of stoichiometry 2. Memory storage is achieved by fabricating these materials into crosses of two or more bars and driving DC current pulses along the bars to rotate the AFM order to a fixed angle with respect to the current pulse. Application of current pulses along different bars can switch the AFM order between multiple directions. Standard resistance measurements can detect the orientation of the AFM order as high or low resistance states. The state of the device can be set by the input current pulses, and read-out by the resistance measurement, forming a non-volatile, AFM memory storage bit.

Analytis, James G.↗
DOE OSTI2020

A New Capability of E4D For 3D Parallel Joint Inversion of DC Resistivity And Traveltime Data on Unstructured Mesh

A major challenge in interpreting geophysical data is how to derive consistent three-dimensional (3D) earth models of different physical properties from spatially and temporally limited measurements. Joint inversion with cross-gradient constraints is an approach to find such models by imposing structural similarities between different physical parameters. We have developed a parallel distributed-memory joint inversion code for direct-current (DC) resistivity and traveltime data using the cross-gradient constraint on unstructured mesh. The code utilizes existing E4D framework for parallel forward simulation, distributed storage and computation of the Jacobian matrix of forward operator, and parallel execution of matrix-vector multiplication during inversion. Besides, the joint inversion is solved by nonlinear conjugate gradient algorithm parallelized for DC resistivity and traveltime data. The joint inversion capability of E4D was tested using synthetic data from cross-borehole DC resistivity and traveltime data. The results indicate that the shape and size of the anomalies from the joint inversion are more reliable than those from separate inversions.

58 GEOSCIENCES↗
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 OSTI2023

Spatially Distributed Ramp Reversal Memory in VO 2

Ramp‐reversal memory has recently been discovered in several insulator‐to‐metal transition materials where a non‐volatile resistance change can be set by repeatedly driving the material partway through the transition. This study uses optical microscopy to track the location and internal structure of accumulated memory as a thin film of VO 2 is temperature cycled through multiple training subloops. These measurements reveal that the gain of insulator phase fraction between consecutive subloops occurs primarily through front propagation at the insulator‐metal boundaries. By analyzing transition temperature maps, it is found, surprisingly, that the memory is also stored deep inside both insulating and metallic clusters throughout the entire sample, making the metal‐insulator coexistence landscape more rugged. This non‐volatile memory is reset after heating the sample to higher temperatures, as expected. Diffusion of point defects is proposed to account for the observed memory writing and subsequent erasing over the entire sample surface. By spatially mapping the location and character of non‐volatile memory encoding in VO 2 , this study results enable the targeting of specific local regions in the film where the full insulator‐to‐metal resistivity change can be harnessed in order to maximize the working range of memory elements for conventional and neuromorphic computing applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Interactions Enhance Ramp Reversal Memory in Locally Phase Separated Materials

The ramp-reversal memory (RRM) effect in metal–insulator transition metal oxides (TMOs), a non-volatile resistance change induced by repeated temperature cycling, has attracted considerable interest in neuromorphic computing and non-volatile memory devices. Our previous defect motion model successfully explained RRM in vanadium dioxide (VO 2 ), capturing observed critical temperature shifts and memory accumulation throughout the sample. However, this approach lacked interactions between metallic and insulating domains. Here, we extend our model by combining a correlated Random Field Ising Model with defect diffusion-segregation, enabling accurate hysteresis modeling while predicting the relationship between RRM and domain interactions. Our simulations demonstrate that the maximum RRM occurs when the turnaround temperature approaches the inflection point. This peak in RRM vs. turnaround temperature is consistent with prior transport measurements, as well as our own optical measurements reported here. Significantly, we find that increasing nearest-neighbor interactions enhances the maximum memory effect, thus providing a clear mechanism for optimizing RRM performance. Since our model employs minimal assumptions, we predict that RRM should be a widespread phenomenon in materials exhibiting patterned phase coexistence of electronic domains. This work not only advances fundamental understanding of memory behavior in TMOs but also establishes a much-needed theoretical framework for optimizing device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mechanisms enabling reconfigurability and long-term retention in vanadium oxide electrochemical memory

Phase coexistence in nanoscale electrochemical random-access memory (ECRAM) has recently been demonstrated to enable both information storage and extraordinary reconfigurability. These proof-of-principle demonstrations have left the mechanistic details of such a process unresolved. Particularly, the mechanisms that stabilize the multiple phases, and the underlying processes behind sustained memory retention, remain unclear, and are necessary to design such devices. Here we report microscale ECRAM devices composed of V⁢O𝑥, which enables us to directly probe the active region in an operando fashion using optical techniques. Using Raman mapping, we show the phase coexistence driven by the electrochemical injection of O vacancies to be spatially uniform (i.e., with no filaments). The stability was observed to be unusually long, with 1% loss over 14 years in ambient conditions. First-principles calculations of the oxygen vacancy formation energies in V⁢O 𝑥 further support the thermodynamic coexistence of multiple V⁢O 𝑥 phases and clarify the origin of the observed long-term retention in the ECRAM devices. Further, we demonstrate single devices that can be voltage programmed to exhibit synaptic, neuronal, and reconfigurable logic gate functionalities. Furthermore, we not only uncover the phase coexistence mechanism that may help device design, but also demonstrate the circuit-level applications of reconfigurability.

Electrical conductivity↗
DOE OSTI2020

PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-Efficient ReRAM

The wide adoption of deep neural networks has been accompanied by ever-increasing energy and performance demands due to the expensive nature of training them. Additionally, numerous special-purpose architectures have been proposed to accelerate training: both digital and hybrid digital-analog using resistive RAM (ReRAM) crossbars. ReRAM-based accelerators have demonstrated the effectiveness of ReRAM crossbars at performing matrix-vector multiplication operations that are prevalent in training. However, they still suffer from inefficiency due to the use of serial reads and writes for performing the weight gradient and update step. A few works have demonstrated the possibility of performing outer products in crossbars, which can be used to realize the weight gradient and update step without the use of serial reads and writes. However, these works have been limited to low precision operations which are not sufficient for typical training workloads. Moreover, they have been confined to a limited set of training algorithms for fully-connected layers only. To address these limitations, we propose a bit-slicing technique for enhancing the precision of ReRAM-based outer products, which is substantially different from bit-slicing for matrix-vector multiplication only. We incorporate this technique into a crossbar architecture with three variants catered to different training algorithms. To evaluate our design on different types of layers in neural networks (fully-connected, convolutional, etc.) and training algorithms, we develop PANTHER, an ISA-programmable training accelerator with compiler support. Our design can also be integrated into other accelerators in the literature to enhance their efficiency. Our evaluation shows that PANTHER achieves up to 8.02×, 54.21×, and 103× energy reductions as well as 7.16×, 4.02×, and 16× execution time reductions compared to digital accelerators, ReRAM-based accelerators, and GPUs, respectively.

42 ENGINEERING↗
DOE OSTI2023

Atomic layer deposition and its derivatives for extreme ultraviolet (EUV) photoresist applications

Solution-processed photoresists have been forerunners in semiconductor patterning for decades. Even with the drastic reduction in photolithography wavelength, traditional spin-on resists still support the fabrication of the most advanced, sub-5 nm node logic and memory devices using EUV lithography (EUVL) (λ = 13.5 nm). However, trade-off between resolution, sensitivity, and roughness in the conventional resists pose a critical challenge in the race towards device downscaling to 1 nm node. While great efforts are being made to improve spin-on EUV photoresist performance, there has been emergence of new approaches focused on developing novel resists via vapor-phase processing routes, such as atomic layer deposition (ALD) and its analogs. This review summarizes recent advances in EUVL photoresist development based on ALD and its derivative techniques, which include ALD-based inorganic–organic dry resists and hybrid resists synthesized by infiltrating conventional spin-on resists. Despite being in the early stage, initial studies have shown the great potential of ALD applications in EUVL photoresist development.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multifunctional Fiber-Reinforced Polymer Composites for Damage Detection and Memory

Self-structural health monitoring (SHM) functionalities for fiber-reinforced polymer composites have become highly sought after to ensure the structural safety of newly advancing components in the automotive, civil, mechanical, and aerospace industries. This paper introduces a self-damage detection and memory (SDDM) hybrid composite material, where the structural carbon fiber tow is transformed into a piezoresistive sensor network, and the structural glass fiber operates as electrical insulation. In this study, SDDM specimens were fabricated, and tensile and impact tests were performed. The tensile tests of SDDM specimens find two distinct loading peaks: first where the carbon fiber fails, and second where the glass fiber fails. A linear correlation was observed between the carbon fiber resistance and composite strain up to a threshold, beyond which a sharp nonlinear increase in resistance occurred. The resistance then approached infinity, coinciding with the first loading peak and failure of the carbon fiber elements. This demonstrates the potential for a damage early warning threshold. Additionally, the effect of stitching the sensor tow in a zig-zag pattern over a large area was investigated using tailored fiber placement (TFP) of 1-loop, 3-loop, and 5-loop specimens. Tensile testing found that increasing the number of loops improved the sensor’s accuracy for strain sensing. Furthermore, impact tests were conducted, and as the impact energy progressively increased, the sensor resistance permanently increased. This illustrates a capability for self-memory of microdamage throughout the life cycle of the structure, potentially useful for predicting the remaining life of the composite.

Demo, Luke B. (ORCID:0000000208806522)↗
DOE OSTI2023

Tuning anisotropic bonding via chemistry and pressure in layered pnictides and chalcogenides (Final Report)

The overarching goal of this research program, as originally delineated in the proposal “Tuning anisotropic bonding via chemistry and pressure in layered pnictides and chalcogenides” was to develop a predictive, chemistry-driven understanding of the impact of the phonon behavior on thermal properties of bulk layered materials. At finite temperatures, atomic vibrations (phonons) strongly impact the thermodynamics, thermal and electrical transport, and phase-switching properties of functional materials. In particular, soft phonon modes and strongly anharmonic potentials can have spectacular consequences, including structural phase transitions (for example in ferroelectrics and phase-change memory materials), metal-insulator transitions, and extreme thermal resistance preventing heat propagation. Bulk materials with highly-anisotropic bonding may provide unique strategies to induce soft-phonon modes and lattice instabilities. Recently, increasingly detailed investigations of the lattice dynamics in layered materials have been made possible by the advent of first-principles phonon calculations and advanced characterization techniques based on neutron and X-ray scattering. However, due to the lack of studies in which composition and bonding character are systematically varied, there are still fundamental questions regarding the impacts of anisotropic bonding and anharmonicity on lattice stability and thermal transport. One of the major goals of this research program is therefore to address this gap by coherently tuning bonding anisotropy and anharmonicity across families of related compounds. Such approaches have revealed new strategies for exploiting structural anisotropy in quasi-1D and 2D bulk materials to obtain tailored functional properties. This project systematically explored the lattice dynamics, phase stability, and transport properties in bulk layered materials by using both composition and applied pressure to tune the degree of bonding anisotropy and anharmonicity. To accomplish this work, we combined i) single-crystal growth of key material systems with tunable anisotropy, ii) in-situ high-temperature/high-pressure characterization of structure and phonons to probe bonding anisotropy and anharmonicity, including state-of-the-art inelastic X-ray scattering (IXS) and inelastic neutron scattering (INS), and iii) first-principles simulations leveraging large-scale computing to identify the fundamental origins of the observed effects, by relating atomic structure and dynamics to electronic orbital interactions. Finally, we modeled and verified the impact of the phonon behavior on thermal transport to identify new strategies for a-priori design of thermal conductivity. Our integrated collaborative approach helped to systematically unravel the effects of anisotropy and bonding anharmonicity on phonon transport, thermodynamics, and thermal properties of complex anisotropic materials.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Tuning anisotropic bonding via chemistry and pressure in layered pnictides and chalcogenides. Final Report

The overarching goal of this research program, as originally delineated in the proposal “Tuning anisotropic bonding via chemistry and pressure in layered pnictides and chalcogenides” was to develop a predictive, chemistry-driven understanding of the impact of the phonon behavior on thermal properties of bulk layered materials. At finite temperatures, atomic vibrations (phonons) strongly impact the thermodynamics, thermal and electrical transport, and phase-switching properties of functional materials. In particular, soft phonon modes and strongly anharmonic potentials can have spectacular consequences, including structural phase transitions (for example in ferroelectrics and phase-change memory materials), metal-insulator transitions, and extreme thermal resistance preventing heat propagation. Bulk materials with highly-anisotropic bonding may provide unique strategies to induce soft-phonon modes and lattice instabilities. Recently, increasingly detailed investigations of the lattice dynamics in layered materials have been made possible by the advent of first-principles phonon calculations and advanced characterization techniques based on neutron and X-ray scattering. However, due to the lack of studies in which composition and bonding character are systematically varied, there are still fundamental questions regarding the impacts of anisotropic bonding and anharmonicity on lattice stability and thermal transport. One of the major goals of this research program is therefore to address this gap by coherently tuning bonding anisotropy and anharmonicity across families of related compounds. Such approaches have revealed new strategies for exploiting structural anisotropy in quasi-1D and 2D bulk materials to obtain tailored functional properties. This project systematically explored the lattice dynamics, phase stability, and transport properties in bulk layered materials by using both composition and applied pressure to tune the degree of bonding anisotropy and anharmonicity. To accomplish this work, we combined i) single-crystal growth of key material systems with tunable anisotropy, ii) in-situ high-temperature/high-pressure characterization of structure and phonons to probe bonding anisotropy and anharmonicity, including state-of-the-art inelastic X-ray scattering (IXS) and inelastic neutron scattering (INS), and iii) first-principles simulations leveraging large-scale computing to identify the fundamental origins of the observed effects, by relating atomic structure and dynamics to electronic orbital interactions. Finally, we modeled and verified the impact of the phonon behavior on thermal transport to identify new strategies for a-priori design of thermal conductivity. Our integrated collaborative approach helped to systematically unravel the effects of anisotropy and bonding anharmonicity on phonon transport, thermodynamics, and thermal properties of complex anisotropic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Encoding multistate charge order and chirality in endotaxial heterostructures

Abstract High-density phase change memory (PCM) storage is proposed for materials with multiple intermediate resistance states, which have been observed in 1 T -TaS 2 due to charge density wave (CDW) phase transitions. However, the metastability responsible for this behavior makes the presence of multistate switching unpredictable in TaS 2 devices. Here, we demonstrate the fabrication of nanothick verti-lateral H -TaS 2 /1 T -TaS 2 heterostructures in which the number of endotaxial metallic H -TaS 2 monolayers dictates the number of resistance transitions in 1 T -TaS 2 lamellae near room temperature. Further, we also observe optically active heterochirality in the CDW superlattice structure, which is modulated in concert with the resistivity steps, and we show how strain engineering can be used to nucleate these polytype conversions. This work positions the principle of endotaxial heterostructures as a promising conceptual framework for reliable, non-volatile, and multi-level switching of structure, chirality, and resistance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Role of Oxygen on Chemical Segregation in Uncapped Ge 2 Sb 2 Te 5 Thin Films on Silicon Nitride

Germanium antimony telluride has been the most used and studied phase-change material for electronic memory due to its suitable crystallization temperature, amorphous to crystalline resistance contrast, and stability of the amorphous phase. In this paper, the segregation of Ge in a Ge 2 Sb 2 Te 5 film of 30 nm thickness during heating inside the transmission electron microscope was observed and characterized. Furthermore, Ge 2 Sb 2 Te 5 film was deposited using sputtering on a Protochips Fusion holder and left uncapped in atmosphere for about four months. Oxygen incorporated within the film played a significant role in the chemical segregation observed which resulted in amorphous Ge-O island boundaries and Sb and Te rich crystalline domains. Such composition changes can occur when the phase-change material interfaces insulating oxide layers in an integrated device and can significantly impact its electrical and thermal properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Phase transition in two-dimensional monolayer (1L)-molybdenum disulfide induced by atomic S-basal plane gliding via synchrotron X-ray monochromatic beam radiation for superior electronic performance

Here, in this work, we report a novel approach to reduce the channel resistance by inducing a phase transition behavior from 2H to 1T in a monolayer MoS 2 (1L-MoS 2 ) by a synchrotron X-ray monochromatic beam (mono-beam) radiation. The effects of the biphase structure by the mono-beam on the 1L-MoS2 film were investigated using Raman spectra, photoluminescence (PL) spectra, scanning tunneling microscopy, and scanning tunneling spectroscopy, respectively. Through material characterization, we identified that the lateral sliding of S-vacancies along the S-plane in the 1L-MoS 2 is the key reason for the origin of unidirectional phase transition. The precise phase engineering triggered by the mono-beam radiation process allows the realization of field-effect transistors (FET) with 2X improvement in mobility toward a high on/off ratio (~10 8 ) and a near-ideal subthreshold swing of ~88 mV per decade. The validity of the phase engineering could be further extended for its application as a memory device, exhibiting a gate tunable conduction modulation behavior and a high resistance ratio of ~10 2 at a gate bias of 5 V with endurance of ~100 cycles. Furthermore, an artificial neural network using the synaptic weight update with accuracy of ~93 % was achieved.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Giant resistance switch in twisted transition metal dichalcogenide tunnel junctions

Resistance switching in multilayer structures are typically based on materials possessing ferroic orders. Here, in this work, we predict an extremely large resistance switching based on the relative spin–orbit splitting in twisted transition metal dichalcogenide (TMD) monolayers tunnel junctions. Because of the valence band spin splitting which depends on the valley index in the Brillouin zone, the perpendicular electronic transport through the junction depends on the relative reciprocal space overlap of the spin-dependent Fermi surfaces of both layers, which can be tuned by twisting one layer. Our quantum transport calculations reveal a switching resistance larger than 10 6 % when the relative alignment of TMDs goes from 0° to 60° and when the angle is kept fixed at 60° and the Fermi level is varied. By creating vacancies, we evaluate how inter-valley scattering affects the efficiency and find that the resistance switching remains large (10 4 %) for typical values of vacancy concentration. Not only should this resistance switching be observed at room temperature due to the large spin splitting, but our results also show how twist angle engineering and control of van der Waals heterostructures could be used for next-generation memory and electronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Design-Technology Co-Optimization for NVM-based Neuromorphic Processing Elements

An emerging use-case of machine learning (ML) is to train a model on a high-performance system and deploy the trained model on energy-constrained embedded systems. Neuromorphic hardware platforms, which operate on principles of the biological brain, can significantly lower the energy overhead of a machine learning inference task, making these platforms an attractive solution for embedded ML systems. In this paper, we present a design-technology tradeoff analysis to implement such inference tasks on the processing elements (PEs) of a Non-Volatile Memory (NVM)-based neuromorphic hardware. Through detailed circuit-level simulations at scaled process technology nodes, we show the negative impact of technology scaling on the information-processing latency, which impacts the quality-of-service (QoS) of an embedded ML system. At a finer granularity, the latency inside a PE depends on 1) the delay introduced by parasitic components on its current paths, and 2) the varying delay to sense different resistance states of its NVM cells. Based on these two observations, we make the following three contributions. First, on the technology front, we propose an optimization scheme where the NVM resistance state that takes the longest time to sense is set on current paths having the least delay, and vice versa, reducing the average PE latency, which improves the QoS. Second, on the architecture front, we introduce isolation transistors within each PE to partition it into regions that can be individually power-gated, reducing both latency and energy. Finally, on the system-software front, we propose a mechanism to leverage the proposed technological and architectural enhancements when implementing a machine-learning inference task on neuromorphic PEs of the hardware. Evaluations with a recent neuromorphic hardware architecture show that our proposed design-technology co-optimization approach improves both performance and energy efficiency of machine-learning inference tasks without incurring high cost-per-bit.

42 ENGINEERING↗
DOE OSTI2019

Intrinsic quantized anomalous Hall effect in a moiré heterostructure

The quantum anomalous Hall (QAH) effect combines topology and magnetism to produce precisely quantized Hall resistance at zero magnetic field. We report the observation of a QAH effect in twisted bilayer graphene aligned to hexagonal boron nitride. The effect is driven by intrinsic strong interactions, which polarize the electrons into a single spin- and valley-resolved moiré miniband with Chern number C = 1. In contrast to magnetically doped systems, the measured transport energy gap is larger than the Curie temperature for magnetic ordering, and quantization to within 0.1% of the von Klitzing constant persists to temperatures of several kelvin at zero magnetic field. Electrical currents as small as 1 nanoampere controllably switch the magnetic order between states of opposite polarization, forming an electrically rewritable magnetic memory.

Science & Technology - Other Topics↗
DOE OSTI2023

Recent Advancements in Reconfigurable mmWave Devices Based on Phase-Change and Metal Insulator Transition Materials

Chalcogenide Phase Change Materials (PCM) and metal insulator transition (MIT) materials are a group of materials that are capable of switching between low resistance and high resistance states. These emerging materials have been widely used in optical storage media and memory devices. Over the past recent years, there have been interests in exploiting the PCM and MIT materials, especially germanium antimony telluride (GST) alloys and vanadium dioxide (VO 2 ), for radio frequency (RF) applications. The PCM and MIT-based RF devices are expected to bridge the gap between semiconductor switches and microelectromechanical system (MEMS) switches as they combine the low insertion loss performance of MEMS technology and the small size and reliability performance of semiconductor technology. This article presents an overview of the PCM and MIT materials for RF circuits and discusses the recent advancements in reconfigurable millimeter-wave (mmWave) devices based on PCM and MIT materials in depth.

36 MATERIALS SCIENCE↗