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DOE OSTI2024

Localized Conduction Channels in Memristors

Since the early 2000s, the impending end of Moore’s scaling, as the physical limits to shrinking transistors have been approached, has fueled interest in improving the functionality and efficiency of integrated circuits by employing memristors or two-terminal resistive switches. Formation (or avoidance) of localized conducting channels in many memristors, often called “filaments”, has been established as the basis for their operation. While we understand some qualitative aspects of the physical and thermodynamic origins of conduction localization, there are not yet quantitative models that allow us to predict when they will form or how large they will be. Here, in this work, we compile observations and explanations of channel formation that have appeared in the literature since the 1930s, show how many of these seemingly unrelated pieces fit together, and outline what is needed to complete the puzzle. This understanding will be a necessary predictive component for the design and fabrication of post-Moore’s-era electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Efficient Probabilistic Computing with Stochastic Perovskite Nickelates

Probabilistic computing has emerged as a viable approach to solve hard optimization problems. Devices with inherent stochasticity can greatly simplify their implementation in electronic hardware. In this report we demonstrate intrinsic stochastic resistance switching controlled via electric fields in perovskite nickelates doped with hydrogen. The ability of hydrogen ions to reside in various metastable configurations in the lattice leads to a distribution of transport gaps. With experimentally characterized p-bits, a shared-synapse p-bit architecture demonstrates highly parallelized and energy-efficient solutions to optimization problems such as integer factorization and Boolean satisfiability. The results introduce perovskite nickelates as scalable potential candidates for probabilistic computing and showcase the potential of light-element dopants in next-generation correlated semiconductors.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Electron Doping-Induced Metal–Insulator Transition in LaNiO 3 and Memory Devices

LaNiO 3 (LNO) is the only rare-earth nickelate that does not undergo a temperature-driven insulator-metal transition. Here, we report the successful deposition of epitaxial LNO thin films on LaAlO 3 substrates by a chemical solution deposition method. We report a metal-insulator transition driven by electron doping from hydrogen using catalytic Pd electrodes. A series of in-plane devices with LNO thin films and Pd-Au as the two working terminals were designed and fabricated by photolithography. Further, we report their resistance switching behavior and synaptic multiresistance states under voltage pulses. The results demonstrate the universality of electron doping-driven phase transitions in the rare-earth nickelates and their relevance to emerging memory and computing technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Integration of CeO 2 -Based Memristor with Vertically Aligned Nanocomposite Thin Film: Enabling Selective Conductive Filament Formation for High-Performance Electronic Synapses

The CeO 2 -based memristor has attracted significant attention due to its intrinsic resistive switching (RS) properties, large on/off ratio, and great plasticity, making it a promising candidate for artificial synapses. However, significant challenges such as high power consumption and poor device reliability hinder its broad application in neuromorphic microchips. To tackle these issues, in this work, we design a novel bilayer (BL) memristor by integrating a CeO 2 -based memristor with a Co-CeO 2 vertically aligned nanocomposite (VAN) layer and compare it with the single layer (SL) memristor. Preliminary electrical testing reveals that the BL memristor offers a reduced set/reset voltage (~67% lower), a higher on/off ratio (~5 × 10 2 ), enhanced device reliability, and improved device-to-device variation compared to the SL memristor. Insight from COMSOL simulation, coupled with microstructural analysis, provides a comprehensive elucidation on how the VAN layer facilitates the selective conductive filament (CF) formation. Subsequently, the plasticity of the BL memristor is evaluated through long-term potentiation/depression (LTP/LTD), paired-pulse facilitation (PPF), and spike-time-dependent plasticity (STDP). The spiking neural network (SNN) built upon the BL memristor achieves remarkable accuracy (~94%) after only 12 iterations, underscoring its potential for high-performance neural networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Dielectric-Engineered Monolayer MoS 2 Memtransistors for Brain-Inspired Computing with High Recognition Accuracy

Two-dimensional transition metal dichalcogenides (2D-TMDs)-based memtransistors have emerged as promising candidates for neuromorphic hardware due to their exceptional ability to emulate synaptic behavior. However, many existing 2D-TMDs memtransistors rely on polycrystalline channels with grain boundaries or defects introduced through postgrowth treatments, raising concerns about material integrity and the preservation of intrinsic properties. Here, in this work, we demonstrate a monocrystalline monolayer MoS 2 memtransistor fabricated on a silicon nitride (SiN X ) substrate, achieving a large resistive switching ratio of 10 4 , a dynamic range exceeding 90, along with highly linear and symmetric weight updates, minimal cycle-to-cycle variability, and low device-to-device variability. These attributes are critical for enabling high-performance neuromorphic hardware. Based on experimental data, we further show that these artificial synapses enable a recognition accuracy of more than 97% on the MNIST handwritten digits data set. Our findings present a straightforward approach to realizing 2D-TMDs memtransistors through dielectric engineering, offering a promising platform for next-generation neuromorphic computing systems.

2D TMDs↗

DOE OSTI2020

Time- and strain-dependent nanoscale structural degradation in phase change epitaxial strontium ferrite films

Topotactic phase transition between metallic, perovskite SrFeO 3 and insulating, Brownmillerite SrFeO 2.5 has been extensively studied due to the potential applications in resistive switching devices for neuromorphic computing. However, its practical utilization as memristors has been hindered by the structural instability of SrFeO 3 , which is often ascribed to the generation of oxygen vacancies to form SrFeO 3-δ . Here we reveal the dominating defects generated in SrFeO 3 epitaxial thin films are atomic scale gaps as a result of interfacial strain. Our correlated time- and strain-dependent measurements show that tensile strained SrFeO 3 films form vertical, nanoscale gaps that are SrO-rich, which are accountable for the observed metal-to-insulator transition over time. While compressively strained or small lattice mismatched SrFeO 3 films mainly yield horizontal gaps with a smaller impact on the in-plane transport. The atomic scale origin of such defects and their impact on device performance need to be further understood in order to integrate phase change materials in oxide electronics.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A caloritronics-based Mott neuristor

Abstract Machine learning imitates the basic features of biological neural networks at a software level. A strong effort is currently being made to mimic neurons and synapses with hardware components, an approach known as neuromorphic computing. While recent advances in resistive switching have provided a path to emulate synapses at the 10 nm scale, a scalable neuron analogue is yet to be found. Here, we show how heat transfer can be utilized to mimic neuron functionalities in Mott nanodevices. We use the Joule heating created by current spikes to trigger the insulator-to-metal transition in a biased VO 2 nanogap. We show that thermal dynamics allow the implementation of the basic neuron functionalities: activity, leaky integrate-and-fire, volatility and rate coding. This approach could enable neuromorphic hardware to take full advantage of the rapid advances in memristive synapses, allowing for much denser and complex neural networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Physics for neuromorphic computing

Neuromorphic computing takes inspiration from the brain to create energy-efficient hardware for information processing, capable of highly sophisticated tasks. Systems built with standard electronics achieve gains in speed and energy by mimicking the distributed topology of the brain. Scaling-up such systems and improving their energy usage, speed and performance by several orders of magnitude requires a revolution in hardware. Here, we discuss how including more physics in the algorithms and nanoscale materials used for data processing could have a major impact in the field of neuromorphic computing. We review striking results that leverage physics to enhance the computing capabilities of artificial neural networks, using resistive switching materials, photonics, spintronics and other technologies. We discuss the paths that could lead these approaches to maturity, towards low-power, miniaturized chips that could infer and learn in real time.

device physics↗

DOE OSTI2025

Electrolytic gold plating, stripping, and ion transport dynamics through a solid-state iodide perovskite

The pronounced electrochemical reactivity between halide perovskites and metal electrodes can introduce mobile extrinsic metal ions which can cause device instability or enable novel functionalities. Here we systematically investigate the kinetics of gold cation (Au + ) migration in indium tin oxide (ITO)/methylammonium lead triiodide (MAPbI 3 )/Au model devices under long-term potentiostatic biasing. Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) analyses reveal that Au + ions, electrochemically generated at the Au anode, traverse the perovskite layer with diffusion coefficients on the order of 10 −11 to 10 −10 cm 2 s −1 and are subsequently reduced at the cathode as Au 0 clusters, resembling metal plating behavior in electrolytic cells and solid-state batteries during charging. Furthermore, reversing the applied bias strips the plated Au 0 , revealing reversibility suitable for bipolar resistive switching devices and providing direct evidence of the electrochemical and ionic nature of Au transport within the perovskite matrix. Quantitatively determining diffusion coefficients and ion concentrations provides foundational inputs for future drift-diffusion modelling opportunities and allows us to relate our findings to implications on long term operation of devices like photovoltaic modules. These results clearly demonstrate the solid-state electrochemical nature of perovskite devices, highlight methods to be more quantitative about ion transport properties, provide and emphasize the importance of disentangling electro-, photo-, photoelectrochemical processes for understanding device performance and unlocking new functionalities.

14 SOLAR ENERGY↗

DOE OSTI2026

Electronic Origin of Delicate Antiferromagnetism in Fe 𝑥 ⁢NbS 2

Among the family of intercalated transition-metal dichalcogenides (TMDs), Fe 𝑥 ⁢NbS 2 is found to possess unique current-induced resistive switching behaviors, tunable antiferromagnetic states, and a commensurate charge order, all of which are tied to a critical Fe doping of 𝑥 𝑐 = 1/3. However, the electronic origin of such extreme stoichiometry sensitivities remains unclear. Combining angle-resolved photoemission spectroscopy (ARPES) with density functional theory (DFT) calculations, we identify and characterize a dramatic eV-scale electronic restructuring that occurs across the 𝑥𝑐. Moment-carrying Fe 3⁢𝑑 𝑧 2 electrons manifest as narrow bands within 200 meV of the Fermi level, distinct from other transition metal intercalated TMD magnets. These states strongly hybridize with itinerant electrons in the TMD layer and rapidly lose coherence above 𝑥 𝑐 due to correlation-driven effects. This sudden quasiparticle decoherence collapses the Fe-Nb hybridization, which explicitly suppresses the out-of-plane effective Fe-Fe exchange interaction, driving the transformation of the magnetic ground state from an antiferromagnetic stripe phase to a zigzag phase. Furthermore, these observations resemble the exceptional electronic and magnetic sensitivity of strongly correlated systems, and demonstrate that quantifying orbital-specific hybridization via ARPES offers an alternative pathway to evaluate effective magnetic exchange in metallic magnets, complementing inelastic neutron and resonant x-ray scattering probes.

Angle-resolved photoemission spectroscopy↗

DOE OSTI2023

Field orientation dependent magnetic phases in the Weyl semimetal Co 3 ⁢Sn 2 ⁢S 2

Magnetism plays a key role in the emergence of topological phenomena in the Weyl semimetal Co 3 ⁢Sn 2 ⁢S 2 , which exhibits ferromagnetic interactions along the c-axis of the crystal and antiferromagnetic (AFM) interactions within the ab plane. Extensive studies on the temperature dependence of the magnetism with the magnetic field along the c-axis have uncovered a number of magnetic phases. Currently, the nature and origins of the reported magnetic phases are under debate. Here, in this work, we report on magnetic field orientation effects on the magnetism in Co 3 ⁢Sn 2 ⁢S 2 . The shape of the hysteresis loop of the Hall resistance at a fixed temperature is found to change from rectangular to bow tie-like as the magnetic field is tilted from the c-axis toward the ab plane, resembling that reported for magnetic fields along the c-axis as the temperature approaches the Curie temperature from below. Unlike their temperature-dependent counterparts, the newly observed bow tie-like hysteresis loops show exchange bias. Our results showcase the contribution of the in-plane AFM interactions to the magnetism in Co 3 ⁢Sn 2⁢ S 2 and demonstrate a new way to tune its magnetic phases. They also shed light on the temperature-dependent magnetic phases occurring in the magnetic field along the c-axis of the crystal.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Discovery of Charge Order in the Transition Metal Dichalcogenide Fe x NbS 2

The Fe intercalated transition metal dichalcogenide (TMD), Fe 1/3 NbS 2 , exhibits remarkable resistance switching properties and highly tunable spin ordering phases due to magnetic defects. We conduct synchrotron x-ray scattering measurements on both underintercalated ( x = 0.32 ) and overintercalated ( x = 0.35 ) samples. We discover a new charge order phase in the overintercalated sample, where the excess Fe atoms lead to a zigzag antiferromagnetic order. The agreement between the charge and magnetic ordering temperatures, as well as their intensity relationship, suggests a strong magnetoelastic coupling as the mechanism for the charge ordering. In conclusion, our results reveal the first example of a charge order phase among the intercalated TMD family and demonstrate the ability to stabilize charge modulation by introducing electronic correlations, where the charge order is absent in bulk 2H - NbS 2 compared to other pristine TMDs.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Graphite-Embedded High-Performance Insulated Metal Substrate for Wide-Bandgap Power Modules

Emerging wide-bandgap (WBG) semiconductor devices such as silicon carbide (SiC) metal–oxide semiconductor field-effect transistors (MOSFETs) and gallium nitride high-electron-mobility transistors can handle high power in reduced semiconductor areas better than conventional Si-based devices owing to superior material properties. With increased power loss density in a WBG-based converter and reduced die size in power modules, thermal management of power devices must be optimized for high performance. Here, we present a graphite-embedded insulated metal substrate (thermally-annealed-pyrolytic-graphite-embedded insulated metal substrate—IMSwTPG) designed for WBG power modules. Theoretical thermal performance analysis of graphite-embedded metal cores is presented, with design details for IMSwTPG with embedded graphite to replace a direct-bonded copper (DBC) substrate. The proposed IMSwTPG is compared with an aluminum nitride-based DBC substrate using finite-element thermal analysis for steady-state and transient thermal performance. The solutions’ thermal performances are compared under different coolant temperature and thermal loading conditions, and the proposed substrate's electrical performance is validated with static and dynamic characterization. Using graphite-embedded substrates, junction-to-case thermal resistance of SiC MOSFETs can be reduced up to 17%, and device current density can be increased by 10%, regardless of the thermal management strategy used to cool the substrate. Reduced transient thermal impedance of up to 40% of dies owing to increased heat capacity is validated in transient thermal simulations and experiments. The half-bridge power module's electrical performance is evaluated for on -state resistance, switching performance, and switching loss at three junction temperature conditions. The proposed substrate solution has minimal impact on conduction and switching performance of SiC MOSFETs.

42 ENGINEERING↗

DOE OSTI2023

Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials

The Abisko project aims to develop an energy-efficient spiking neural network (SNN) computing architecture and software system capable of autonomous learning and operation. The SNN architecture explores novel neuromorphic devices that are based on resistive-switching materials, such as memristors and electrochemical RAM. Equally important, Abisko uses a deep codesign approach to pursue this goal by engaging experts from across the entire range of disciplines: materials, devices and circuits, architectures and integration, software, and algorithms. Here, the key objectives of our Abisko project are threefold. First, we are designing an energy-optimized high-performance neuromorphic accelerator based on SNNs. This architecture is being designed as a chiplet that can be deployed in contemporary computer architectures and we are investigating novel neuromorphic materials to improve its design. Second, we are concurrently developing a productive software stack for the neuromorphic accelerator that will also be portable to other architectures, such as field-programmable gate arrays and GPUs. Third, we are creating a new deep codesign methodology and framework for developing clear interfaces, requirements, and metrics between each level of abstraction to enable the system design to be explored and implemented interchangeably with execution, measurement, a model, or simulation. As a motivating application for this codesign effort, we target the use of SNNs for an analog event detector for a high-energy physics sensor.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Two-Dimensional Silk Crystal Films as Matrix Layer for High-Performance Microelectronics

This study explores a bio-inspired approach for memristive devices by combining Keggin-type polyoxometalates (POMs)-[SiW 12 O 40 ] 4 (POM-T) and [PW 12 O 40 ] 3 (POM-P), with silk fibroin (SF) to create 2D SF–POM layers on highly ordered pyrolytic graphite (HOPG) as resistive switching layers for memristors. We propose that the ordered SF layer template 0D POMs facilitate the formation of conductive filaments, thereby enhancing the variability of the manufactured memristors. AFM analysis revealed that both SF and SF–POM layers shared similar morphologies, while SF–POM–T formed larger aggregates, likely due to the stronger acidity of POM-T, which probably caused SF to aggregate and alter its secondary structure. Scanning Kelvin probe microscopy (SKPM) revealed that POMs reduced the contact potential difference of HOPG, resulting in lower work functions. Compared to an SF device, the SF–POM–P device showed improved memristive behavior, with a larger current gap and good repeatability over multiple sweeps; whereas the SF–POM–T device did not exhibit memristor activity, likely due to acidity-induced disruption of the SF template’s order and CF formation. More importantly, SF–POM–P devices also demonstrated programmable memristive states. Finally, combining simulation-driven memristor modeling, we showcase a co-design workflow for advancing bioinspired memristors through new materials design, synthesis, and device modeling and development.

36 MATERIALS SCIENCE↗

NASA NTRS1991

Lightning protection of full authority digital electronic systems

Modern electronic systems are vulnerable to transient and they now provide safety critical functions such as full authority digital electronic control (FADEC) units for fly by wire aircraft. Of the traditional suppression technologies available diodes have gained the wider acceptance, however, they lack the current handling capacity to meet existing threat levels. The development of high speed fold back devices where, at a specified voltage, the off state resistance switches to a very low on state one has provided the equivalent to a semiconductor spark gap. The size of the technology enables it to be integrated into connectors of interconnection cables. To illustrate the performance the technology was developed to meet the Lightning Protection requirements for FADEC units within aeroengines. Work was also carried out to study switching behavior with the waveform 5, the 500 us, 10 kA pulse applied to cable assemblies. This test enabled all the switches in a connector to be fired simultaneously.

Crofts, David↗

NASA NTRS2011

Forced ion migration for chalcogenide phase change memory device

Non-volatile memory devices with two stacked layers of chalcogenide materials comprising the active memory device have been investigated for their potential as phase change memories. The devices tested included GeTe/SnTe, Ge.sub.2Se.sub.3/SnTe, and Ge.sub.2Se.sub.3/SnSe stacks. All devices exhibited resistance switching behavior. The polarity of the applied voltage with respect to the SnTe or SnSe layer was critical to the memory switching properties, due to the electric field induced movement of either Sn or Te into the Ge-chalcogenide layer. One embodiment of the invention is a device comprising a stack of chalcogenide-containing layers which exhibit phase change switching only after a reverse polarity voltage potential is applied across the stack causing ion movement into an adjacent layer and thus "activating" the device to act as a phase change random access memory device or a reconfigurable electronics device when the applied voltage potential is returned to the normal polarity. Another embodiment of the invention is a device that is capable of exhibiting more that two data states.

Campbell, Kristy A.↗

NASA NTRS2012

Forced ion migration for chalcogenide phase change memory device

Non-volatile memory devices with two stacked layers of chalcogenide materials comprising the active memory device have been investigated for their potential as phase-change memories. The devices tested included GeTe/SnTe, Ge.sub.2Se.sub.3/SnTe, and Ge.sub.2Se.sub.3/SnSe stacks. All devices exhibited resistance switching behavior. The polarity of the applied voltage with respect to the SnTe or SnSe layer was critical to the memory switching properties, due to the electric field induced movement of either Sn or Te into the Ge-chalcogenide layer. One embodiment of the invention is a device comprising a stack of chalcogenide-containing layers which exhibit phase-change switching only after a reverse polarity voltage potential is applied across the stack causing ion movement into an adjacent layer and thus "activating" the device to act as a phase-change random access memory device or a reconfigurable electronics device when the applied voltage potential is returned to the normal polarity. Another embodiment of the invention is a device that is capable of exhibiting more than two data states.

Campbell, Kristy A.↗