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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

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

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

Phan, Thanh Luan [National Renewable Energy Labora↗
NASA NTRS2010

Optimal and Local Connectivity Between Neuron and Synapse Array in the Quantum Dot/Silicon Brain

This innovation is used to connect between synapse and neuron arrays using nanowire in quantum dot and metal in CMOS (complementary metal oxide semiconductor) technology to enable the density of a brain-like connection in hardware. The hardware implementation combines three technologies: 1. Quantum dot and nanowire-based compact synaptic cell (50x50 sq nm) with inherently low parasitic capacitance (hence, low dynamic power approx.l0(exp -11) watts/synapse), 2. Neuron and learning circuits implemented in 50-nm CMOS technology, to be integrated with quantum dot and nanowire synapse, and 3. 3D stacking approach to achieve the overall numbers of high density O(10(exp 12)) synapses and O(10(exp 8)) neurons in the overall system. In a 1-sq cm of quantum dot layer sitting on a 50-nm CMOS layer, innovators were able to pack a 10(exp 6)-neuron and 10(exp 10)-synapse array; however, the constraint for the connection scheme is that each neuron will receive a non-identical 10(exp 4)-synapse set, including itself, via its efficacy of the connection. This is not a fully connected system where the 100x100 synapse array only has a 100-input data bus and 100-output data bus. Due to the data bus sharing, it poses a great challenge to have a complete connected system, and its constraint within the quantum dot and silicon wafer layer. For an effective connection scheme, there are three conditions to be met: 1. Local connection. 2. The nanowire should be connected locally, not globally from which it helps to maximize the data flow by sharing the same wire space location. 3. Each synapse can have an alternate summation line if needed (this option is doable based on the simple mask creation). The 10(exp 3)x10(exp 3)-neuron array was partitioned into a 10-block, 10(exp 2)x10(exp 3)-neuron array. This building block can be completely mapped within itself (10,000 synapses to a neuron).

Duong, Tuan A.↗
DOE OSTI2022

Shape‐Dependent Multi‐Weight Magnetic Artificial Synapses for Neuromorphic Computing

Abstract In neuromorphic computing, artificial synapses provide a multi‐weight (MW) conductance state that is set based on inputs from neurons, analogous to the brain. Herein, artificial synapses based on magnetic materials that use a magnetic tunnel junction (MTJ) and a magnetic domain wall (DW) are explored. By fabricating lithographic notches in a DW track underneath a single MTJ, 3–5 stable resistance states that can be repeatably controlled electrically using spin‐orbit torque are achieved. The effect of geometry on the synapse behavior is explored, showing that a trapezoidal device has asymmetric weight updates with high controllability, while a rectangular device has higher stochasticity, but with stable resistance levels. The device data is input into neuromorphic computing simulators to show the usefulness of application‐specific synaptic functions. Implementing an artificial neural network (NN) applied to streamed Fashion‐MNIST data, the trapezoidal magnetic synapse can be used as a metaplastic function for efficient online learning. Implementing a convolutional NN for CIFAR‐100 image recognition, the rectangular magnetic synapse achieves near‐ideal inference accuracy, due to the stability of its resistance levels. This work shows MW magnetic synapses are a feasible technology for neuromorphic computing and provides design guidelines for emerging artificial synapse technologies.

Leonard, Thomas↗
DOE OSTI2024

Enhanced read resolution in reconfigurable memristive synapses for Spiking Neural Networks

Abstract The synapse is a key element circuit in any memristor-based neuromorphic computing system. A memristor is a two-terminal analog memory device. Memristive synapses suffer from various challenges including high voltage, SET or RESET failure, and READ margin issues that can degrade the distinguishability of stored weights. Enhancing READ resolution is very important to improving the reliability of memristive synapses. Usually, the READ resolution is very small for a memristive synapse with a 4-bit data precision. This work considers a step-by-step analysis to enhance the READ current resolution or the read current difference between two resistance levels for a current-controlled memristor-based synapse. An empirical model is used to characterize the $${\hbox {HfO}}_{2}$$ HfO 2 based memristive device. $$1\textrm{st}$$ 1 st and $$2\textrm{nd}$$ 2 nd stage device of our proposed synapse design can be scaled to enhance the READ current margin up to $$\sim$$ ∼ 4.3 $$\times$$ × and $$\sim$$ ∼ 21%, respectively. Moreover, READ current resolution can be enhanced with run-time adaptation techniques such as READ voltage scaling and body biasing. The READ voltage scaling and body biasing can improve the READ current resolution by about 46% and 15%, respectively. TENNLab’s neuromorphic computing framework is leveraged to evaluate the effect of READ current resolution on classification, control, and reservoir computing applications. Higher READ current resolution shows better accuracy than lower resolution even when facing different levels of read noise.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Isochronic development of cortical synapses in primates and mice

Abstract The neotenous, or delayed, development of primate neurons, particularly human ones, is thought to underlie primate-specific abilities like cognition. We tested whether synaptic development follows suit—would synapses, in absolute time, develop slower in longer-lived, highly cognitive species like non-human primates than in shorter-lived species with less human-like cognitive abilities, e.g., the mouse? Instead, we find that excitatory and inhibitory synapses in the maleMus musculus(mouse) andRhesus macaque(primate) cortex form at similar rates, at similar times after birth. Primate excitatory and inhibitory synapses and mouse excitatory synapses also prune in such an isochronic fashion. Mouse inhibitory synapses are the lone exception, which are not pruned and instead continuously added throughout life. The monotony of synaptic development clocks across species with disparate lifespans, experiences, and cognitive abilities argues that such programs are likely orchestrated by genetic events rather than experience.

Science & Technology - Other Topics↗
DOE OSTI2021

A domain wall-magnetic tunnel junction artificial synapse with notched geometry for accurate and efficient training of deep neural networks

Inspired by the parallelism and efficiency of the brain, several candidates for artificial synapse devices have been developed for neuromorphic computing, yet a nonlinear and asymmetric synaptic response curve precludes their use for backpropagation, the foundation of modern supervised learning. Spintronic devices—which benefit from high endurance, low power consumption, low latency, and CMOS compatibility—are a promising technology for memory, and domain-wall magnetic tunnel junction (DW-MTJ) devices have been shown to implement synaptic functions such as long-term potentiation and spike-timing dependent plasticity. In this work, we propose a notched DW-MTJ synapse as a candidate for supervised learning. Using micromagnetic simulations at room temperature, we show that notched synapses ensure the non-volatility of the synaptic weight and allow for highly linear, symmetric, and reproducible weight updates using either spin transfer torque (STT) or spin–orbit torque (SOT) mechanisms of DW propagation. We use lookup tables constructed from micromagnetics simulations to model the training of neural networks built with DW-MTJ synapses on both the MNIST and Fashion-MNIST image classification tasks. Accounting for thermal noise and realistic process variations, the DW-MTJ devices achieve classification accuracy close to ideal floating-point updates using both STT and SOT devices at room temperature and at 400 K. Our work establishes the basis for a magnetic artificial synapse that can eventually lead to hardware neural networks with fully spintronic matrix operations implementing machine learning.

42 ENGINEERING↗
NASA NTRS1995

Cationic influences upon synaptic transmission at the hair cell-afferent fiber synapse of the frog

The concentrations of inorganic cations (K+, Na+, and Ca2+) bathing the isolated frog labyrinth were varied in order to assess their role in influencing and mediating synaptic transmission at the hair cell-afferent fiber synapse. Experiments employed intracellular recordings of synaptic activity from VIIIth nerve afferents. Recordings were digitized continuously at 50 kHz, and excitatory postsynaptic potentials were detected and parameters quantified by computer algorithms. Particular attention was focused on cationic effects upon excitatory postsynaptic potential frequency of occurrence and excitatory postsynaptic potential amplitude, in order to discriminate between pre- and postsynaptic actions. Because the small size of afferents preclude long term stable recordings, alterations in cationic concentrations were applied transiently and their peak effects on synaptic activity were assessed. Increases in extracellular K+ concentration of a few millimolar produced a large increase in the frequency of occurrence of excitatory postsynaptic potentials with little change in amplitude, indicating that release of transmitter from the hair cell is tightly coupled to its membrane potential. Increasing extracellular Na+ concentration resulted in an increase in excitatory postsynaptic potential amplitude with no significant change in excitatory postsynaptic potential frequency of occurrence, suggesting that the transmitter-gated subsynaptic channel conducts Na+ ions. Decreases in extracellular Ca2+ concentration had little effect upon excitatory postsynaptic potential frequency, but increased excitatory postsynaptic potential frequency and amplitude. These findings suggest that at higher concentrations Ca2+ act presynaptically to prevent transmitter release and postsynaptically to prevent Na+ influx during the generation of the excitatory postsynaptic potential. The influences of these ions on synaptic activity at this synapse are remarkably similar to those reported at the vertebrate neuromuscular junction. The major differences between these two synapses are the neurotransmitters and the higher resting release rate and higher sensitivity of release to increased K+ concentrations of the hair cells over that of motor nerve terminals. These differences reflect the functional roles of the two synapses: the motor nerve terminal response in an all-or-nothing signal consequent from action potential invasion, while the hair cell releases transmitter in a graded fashion, proportionate to the extent of stereocilial deflection. Despite these differences between the two junctions, the similar actions of these elemental cations upon synaptic function at each implies that these ions may participate similarly in the operations of other synapses, independent of the neurotransmitter type.(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗
DOE OSTI2025

Integrated multi-omic characterizations of the synapse reveal RNA processing factors and ubiquitin ligases associated with neurodevelopmental disorders

The molecular composition of the excitatory synapse is incompletely defined due to its dynamic nature across developmental stages and neuronal populations. To address this gap, we apply proteomic mass spectrometry to characterize the synapse in multiple biological models including the fetal human brain and hiPSC-derived neurons. To prioritize the identified proteins, we develop an orthogonal multi-omic screen of genomic, transcriptomic, interactomic, and structural data. This data-driven framework identifies proteins with key molecular features intrinsic to the synapse, including characteristic patterns of biophysical interactions and cross-tissue expression. The multi-omic analysis captures synaptic proteins across developmental stages and experimental systems, including 493 synaptic candidates supported by proteomics. We further investigate three such proteins that are associated with neurodevelopmental disorders – the CUL3 E3 ubiquitin ligase, the DDX3X and YBX1 nucleic-acid binding proteins – by mapping their networks of physically interacting synapse proteins or transcripts. Our study demonstrates the potential of an integrated multi-omic approach to systematically and more comprehensively resolve the synaptic architecture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

(Bi 0.2 Sb 0.8 ) 2 Te 3 based dynamic synapses with programmable spatio-temporal dynamics

Neuromorphic computing has recently emerged as a promising paradigm to overcome the von-Neumann bottleneck and enable orders of magnitude improvement in bandwidth and energy efficiency. However, existing complementary metal-oxide-semiconductor (CMOS) digital devices, the building block of our computing system, are fundamentally different from the analog synapses, the building block of the biological neural network—rendering the hardware implementation of the artificial neural networks (ANNs) not scalable in terms of area and power, with existing CMOS devices. In addition, the spatiotemporal dynamic, a crucial component for cognitive functions in the neural network, has been difficult to replicate with CMOS devices. Here, we present the first topological insulator (TI) based electrochemical synapse with programmable spatiotemporal dynamics, where long-term and short-term plasticity in the TI synapse are achieved through the charge transfer doping and ionic gating effects, respectively. We also demonstrate basic neuronal functions such as potentiation/depression and paired-pulse facilitation with high precision (>500 states per device), as well as a linear and symmetric weight update. We envision that the dynamic TI synapse, which shows promising scaling potential in terms of energy and speed, can lead to the hardware acceleration of truly neurorealistic ANNs with superior cognitive capabilities and excellent energy efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Synapse-specific catecholaminergic modulation of neuronal glutamate release

Norepinephrine in vertebrates and its invertebrate analog, octopamine, regulate the activity of neural circuits. We find that, when hungry,Drosophilalarvae switch activity in type II octopaminergic motor neurons (MNs) to high-frequency bursts, which coincide with locomotion-driving bursts in type I glutamatergic MNs that converge on the same muscles. Optical quantal analysis across hundreds of synapses simultaneously reveals that octopamine potentiates glutamate release by tonic type Ib MNs, but not phasic type Is MNs, and occurs via the G q -coupled octopamine receptor (OAMB). OAMB is more abundant in type Ib terminals and acts through diacylglycerol and its target Unc13A, a key component of the glutamate release machinery. Potentiation varies significantly—by up to 1,000%—across synapses of a single Ib axon, with synaptic Unc13A levels determining both release probability and potentiation. We propose that a dual molecular mechanism—an upstream neuromodulator receptor and a downstream transmitter release controller—fine-tunes catecholaminergic modulation so that strong tonic synapses exhibit large potentiation, while weaker tonic and all phasic synapses maintain consistency, yielding a sophisticated regulation of locomotor behavior.

Science & Technology - Other Topics↗
NASA NTRS2000

Changes in ribbon synapses and rough endoplasmic reticulum of rat utricular macular hair cells in weightlessness

This study combined ultrastructural and statistical methods to learn the effects of weightlessness on rat utricular maculae. A principle aim was to determine whether weightlessness chiefly affects ribbon synapses of type II cells, since the cells communicate predominantly with branches of primary vestibular afferent endings. Maculae were microdissected from flight and ground control rat inner ears collected on day 13 of a 14-day spaceflight (F13), landing day (R0) and day 14 postflight (R14) and were prepared for ultrastructural study. Ribbon synapses were counted in hair cells examined in a Zeiss 902 transmission electron microscope. Significance of synaptic mean differences was determined for all hair cells contained within 100 section series, and for a subset of complete hair cells, using SuperANOVA software. The synaptic mean for all type II hair cells of F13 flight rats increased by 100%, and that for complete cells by 200%. Type I cells were less affected, with synaptic mean differences statistically insignificant in complete cells. Synapse deletion began within 8 h upon return to Earth. Additionally, hair cell laminated rough endoplasmic reticulum of flight rats was reversibly disorganized on R0. Results support the thesis that synapses in type II hair cells are uniquely affected by altered gravity. Type II hair cells may be chiefly sensors of gravitational and type I cells of translational linear accelerations.

short duration↗
DOE OSTI2023

Photothermally Activated Artificial Neuromorphic Synapses

Biological nervous systems rely on the coordination of billions of neurons with complex, dynamic connectivity to enable the ability to process information and form memories. In turn, artificial intelligence and neuromorphic computing platforms have sought to mimic biological cognition through software-based neural networks and hardware demonstrations utilizing memristive circuitry with fixed dynamics. Here, to incorporate the advantages of tunable dynamic software implementations of neural networks into hardware, we develop a proof-of-concept artificial synapse with adaptable resistivity. This synapse leverages the photothermally induced local phase transition of VO 2 thin films by temporally modulated laser pulses. Such a process quickly modifies the conductivity of the film site-selectively by a factor of 500 to “activate” these neurons and store “memory” by applying varying bias voltages to induce self-sustained Joule heating between electrodes after activation with a laser. These synapses are demonstrated to undergo a complete heating and cooling cycle in less than 120 ns.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Determinants of synapse diversity revealed by super-resolution quantal transmission and active zone imaging

Neural circuit function depends on the pattern of synaptic connections between neurons and the strength of those connections. Synaptic strength is determined by both postsynaptic sensitivity to neurotransmitter and the presynaptic probability of action potential evoked transmitter release (P r ). Whereas morphology and neurotransmitter receptor number indicate postsynaptic sensitivity, presynaptic indicators and the mechanism that sets P r remain to be defined. To address this, we developed QuaSOR, a super-resolution method for determining P r from quantal synaptic transmission imaging at hundreds of glutamatergic synapses at a time. We mapped the P r onto super-resolution 3D molecular reconstructions of the presynaptic active zones (AZs) of the same synapses at the Drosophila larval neuromuscular junction (NMJ). We find that P r varies greatly between synapses made by a single axon, quantify the contribution of key AZ proteins to P r diversity and find that one of these, Complexin, suppresses spontaneous and evoked transmission differentially, thereby generating a spatial and quantitative mismatch between release modes. Transmission is thus regulated by the balance and nanoscale distribution of release-enhancing and suppressing presynaptic proteins to generate high signal-to-noise evoked transmission.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

An Interface–Type Memristive Device for Artificial Synapse and Neuromorphic Computing

Interface-type (IT) metal/oxide Schottky memristive devices have attracted considerable attention over filament-type (FT) devices for neuromorphic computing because of their uniform, filament-free, and analog resistive switching (RS) characteristics. The most recent IT devices are based on oxygen ions and vacancies movement to alter interfacial Schottky barrier parameters and thereby control RS properties. However, the reliability and stability of these devices have been significantly affected by the undesired diffusion of ionic species. Herein, a reliable interface-dominated memristive device is demonstrated using a simple Au/Nb-doped SrTiO 3 (Nb:STO) Schottky structure. The Au/Nb:STO Schottky barrier modulation by charge trapping and detrapping is responsible for the analog resistive switching characteristics. Because of its interface-controlled RS, the proposed device shows low device-to-device, cell-to-cell, and cycle-to-cycle variability while maintaining high repeatability and stability during endurance and retention tests. Furthermore, the Au/Nb:STO IT memristive device exhibits versatile synaptic functions with an excellent uniformity, programmability, and reliability. A simulated artificial neural network with Au/Nb:STO synapses achieves a high recognition accuracy of 94.72% for large digit recognition from MNIST database. These results suggest that IT resistive switching can be potentially used for artificial synapses to build next-generation neuromorphic computing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In vivo volumetric imaging of calcium and glutamate activity at synapses with high spatiotemporal resolution

Studying neuronal activity at synapses requires high spatiotemporal resolution. For high spatial resolution in vivo imaging at depth, adaptive optics (AO) is required to correct sample-induced aberrations. To improve temporal resolution, Bessel focus has been combined with two-photon fluorescence microscopy (2PFM) for fast volumetric imaging at subcellular lateral resolution. To achieve both high-spatial and high-temporal resolution at depth, we develop an efficient AO method that corrects the distorted wavefront of Bessel focus at the objective focal plane and recovers diffraction-limited imaging performance. Applying AO Bessel focus scanning 2PFM to volumetric imaging of zebrafish larval and mouse brains down to 500 µm depth, we demonstrate substantial improvements in the sensitivity and resolution of structural and functional measurements of synapses in vivo. This enables volumetric measurements of synaptic calcium and glutamate activity at high accuracy, including the simultaneous recording of glutamate activity of apical and basal dendritic spines in the mouse cortex.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Hybrid stochastic synapses enabled by scaled ferroelectric field-effect transistors

Achieving brain-like density and performance in neuromorphic computers necessitates scaling down the size of nanodevices emulating neuro-synaptic functionalities. However, scaling nanodevices results in reduction of programming resolution and emergence of stochastic non-idealities. While prior work has mainly focused on binary transitions, in this work, we leverage the stochastic switching of a three-state ferroelectric field-effect transistor to implement a long-term and short-term two-tier stochastic synaptic memory with a single device. Experimental measurements are performed on a scaled 28 nm high-k metal gate technology-based device to develop a probabilistic model of the hybrid stochastic synapse. In addition to the advantage of ultra-low programming energies afforded by scaling, our hardware–algorithm co-design analysis reveals the efficacy of the two-tier memory in comparison to binary stochastic synapses in on-chip learning tasks—paving the way for algorithms exploiting multi-state devices with probabilistic transitions beyond deterministic ones.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Neuromorphic ionic computing in droplet interface synapses

Ionic devices with memory capabilities can emulate neural functionality, enabling neuromorphic computing and biomedical applications. In this study, we report an ionic spiking synapse based on aqueous droplet interface bilayer assembly. Under stepwise triangular voltages, the device displays coupled memcapacitive-memristive behavior, showing noncrossing pinched hysteretic I-V loops. This hysteretic ion dynamics can be regulated by modifying bilayer components, reconstituting protein channels, or adjusting droplet assembly configuration. Droplet interface synapses (DIS) exhibit fundamental neuromorphic behaviors such as paired-pulse facilitation/depression, spike rate–dependent plasticity, Hebbian learning, and short-term associative learning under classical conditioning. We also used reservoir computing with DIS to implement two learning algorithms: a classification algorithm that recognizes handwritten digits and a reinforcement learning algorithm that learns to play a board game of tic-tac-toe.

Li, Zhongwu [Lawrence Livermore National Laborator↗