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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Heterogenous Integration of Boron-Doped p -Diamond with Monolayer n -MoS 2 for PN Junctions Operating at Room Temperature

Diamond has tremendous potential for power electronics, due to its superior thermal conductivity, large electric field strength, and high carrier mobilities. However, the absence of a reliable room temperature n-type transport has impeded any advancements in diamond-based electronics. Here, we circumvent this bottleneck by integrating n-type two-dimensional (2D) monolayers of molybdenum disulfide (MoS 2 ) with boron doped p-type single crystal diamond and demonstrate 2D/3D heterostructure-based PN junction diodes that operate at room temperature with excellent rectification characteristics. Our diodes achieve a maximum forward current density (J D ) of ∼4000 A/cm 2 , an ideality factor (η) value of ∼3.7, and a rectification ratio (RR) of 10 6 . We find that the origin of current rectification stems from the interlayer recombination of majority carriers driven by direct tunnelling (DT) and Fowler Nordheim (FN) tunnelling mechanisms. In conclusion, our demonstration can open new avenues for diamond-based power electronics through its integration with 2D materials.

2D/3D integration↗
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↗
DOE OSTI2023

Steady-state junction current distribution in p-n GaN diodes measured using low-energy electron microscopy (LEEM)

Here, we report on the measurement of the lateral distribution of the junction current of an electrical biased p-n GaN diode by electron emission microscopy using a low-energy electron microscope. The vacuum level at the surface of the diode was lowered by deposition of cesium to achieve negative electron affinity, allowing overflow electrons at the surface of the biased diodes to be emitted and their spatial distribution imaged. The results were compared to the literature, and a good match with analytical solutions by Joyce and Wemple was obtained.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Exploring transport mechanisms in atomic precision advanced manufacturing enabled pn junctions

We investigate the different transport mechanisms that can occur in pn junction devices made using atomic precision advanced manufacturing at temperatures ranging from cryogenic to room temperature. We first elucidate the potential cause of the anomalous behavior observed in the forward-bias response of these devices in recent cryogenic temperature measurements, which deviates from the theoretical response of a silicon Esaki diode. These anomalous behaviors include current suppression at low voltages in the forward-bias response and a much lower valley voltage at cryogenic temperatures than theoretically expected for a silicon diode. To investigate the potential causes of these anomalies, we studied the effects of a few possible transport mechanisms, including band-to-band tunneling, bandgap narrowing, potential impact of non-Ohmic contacts, band quantization, impact of leakage, and inelastic trap-assisted tunneling, through semi-classical simulations. We find that a combination of two sets of band-to-band tunneling (BTBT) parameters can qualitatively approximate the shape of the tunneling current at low bias. This can arise from band quantization and realignment due to the strong potential confinement in δ-layers. We also find that the lower-than-theoretically-expected valley voltage can be attributed to modifications in the electronic band structure within the δ-layer regions, leading to a significant bandgap narrowing induced by the high density of dopants. Finally, we extend our analyses to room temperature operation and predict that trap-assisted tunneling (TAT) facilitated by phonon interactions may become significant, leading to a complex superposition of BTBT and TAT transport mechanisms in the electrical measurements.

band gap↗
DOE OSTI2025

High-speed tunable generation of random number distributions using actuated perpendicular magnetic tunnel junctions

Perpendicular magnetic tunnel junctions (pMTJs) actuated by nanosecond pulses are emerging as promising devices for true random number generation (TRNG) due to their intrinsic stochastic behavior and high throughput. In this work, we demonstrate the tunability and quality of random number distributions generated by pMTJs operating at a frequency of 104 MHz. First, changing the pulse amplitude is used to systematically vary the probability bias. The variance of the resulting bitstreams closely matches the expected binomial distribution, demonstrating consistency with an underlying sequence of Bernoulli trials. Second, the quality of uniform distributions of 8-bit random numbers generated with a probability bias of 0.5 is considered. A reduced chi-square analysis of these data shows that only two XOR operations are sufficient to achieve this distribution with p-values greater than 0.05. Finally, we show that there is a correlation between long-term probability bias variations and pMTJ resistance. These findings suggest that variations in the characteristics of the pMTJ underlie the observed variation of probability bias. In conclusion, our results highlight the potential of stochastically actuated pMTJs for high-speed, tunable TRNG applications, showing the importance of the stability of pMTJ device characteristics in achieving reliable, long-term performance.

Magnetic tunnel junctions↗
DOE OSTI2021

Structural basis for Clostridium perfringens enterotoxin targeting of claudins at tight junctions in mammalian gut

The bacterium Clostridium perfringens causes severe, sometimes lethal gastrointestinal disorders in humans, including enteritis and enterotoxemia. Type F strains produce an enterotoxin (CpE) that causes the third most common foodborne illness in the United States. CpE induces gut breakdown by disrupting barriers at cell–cell contacts called tight junctions (TJs), which are formed and maintained by claudins. Targeted binding of CpE to specific claudins, encoded by its C-terminal domain (cCpE), loosens TJ barriers to trigger molecular leaks between cells. Cytotoxicity results from claudin-bound CpE complexes forming pores in cell membranes. In mammalian tissues, ~24 claudins govern TJ barriers—but the basis for CpE’s selective targeting of claudins in the gut was undetermined. We report the structure of human claudin-4 in complex with cCpE, which reveals that enterotoxin targets a motif conserved in receptive claudins and how the motif imparts high-affinity CpE binding to these but not other subtypes. The structural basis of CpE targeting is supported by binding affinities, kinetics, and half-lives of claudin–enterotoxin complexes and by the cytotoxic effects of CpE on claudin-expressing cells. By correlating the binding residence times of claudin–CpE complexes we determined to claudin expression patterns in the gut, we uncover that the primary CpE receptors differ in mice and humans due to sequence changes in the target motif. These findings provide the molecular and structural element CpE employs for subtype-specific targeting of claudins during pathogenicity of C. perfringens in the gut and a framework for new strategies to treat CpE-based illnesses in domesticated mammals and humans.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

All-MOCVD-grown gallium nitride diodes with ultra-low resistance tunnel junctions

In this work, we carefully investigate three important effects including postgrowth activation annealing, delta (δ) dose and magnesium (Mg) buildup delay as well as experimentally demonstrate their influence on the electrical properties of GaN homojunction p–n diodes with a tunnel junction (TJ). The diodes were monolithically grown by metalorganic chemical vapor deposition (MOCVD) in a single growth step. By optimizing the annealing parameters for Mg activation, δ-dose for both donors and acceptors at TJ interfaces, and p + -GaN layer thickness, a significant improvement in tunneling properties is achieved. For the TJs embedded within the continuously-grown, all-MOCVD GaN diode structures, ultra-low voltage penalties of 158 mV and 490 mV are obtained at current densities of 20 A cm –2 and 100 A cm –2 , respectively. The diodes with the engineered TJs show a record-low differential resistivity of 1.6 × 10 –4 Ω cm 2 at 5 kA cm –2 .

42 ENGINEERING↗
DOE OSTI2024

Magnetic tunnel junction random number generators applied to dynamically tuned probability trees driven by spin orbit torque

Abstract Perpendicular magnetic tunnel junction (pMTJ)-based true-random number generators (RNGs) can consume orders of magnitude less energy per bit than CMOS pseudo-RNGs. Here, we numerically investigate with a macrospin Landau–Lifshitz-Gilbert equation solver the use of pMTJs driven by spin–orbit torque to directly sample numbers from arbitrary probability distributions with the help of a tunable probability tree. The tree operates by dynamically biasing sequences of pMTJ relaxation events, called ‘coinflips’, via an additional applied spin-transfer-torque current. Specifically, using a single, ideal pMTJ device we successfully draw integer samples on the interval [0, 255] from an exponential distribution based on p -value distribution analysis. In order to investigate device-to-device variations, the thermal stability of the pMTJs are varied based on manufactured device data. It is found that while repeatedly using a varied device inhibits ability to recover the probability distribution, the device variations average out when considering the entire set of devices as a ‘bucket’ to agnostically draw random numbers from. Further, it is noted that the device variations most significantly impact the highest level of the probability tree, with diminishing errors at lower levels. The devices are then used to draw both uniformly and exponentially distributed numbers for the Monte Carlo computation of a problem from particle transport, showing excellent data fit with the analytical solution. Finally, the devices are benchmarked against CMOS and memristor RNGs, showing faster bit generation and significantly lower energy use.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Optimization of Application-Driven Development of In Vitro Neuromuscular Junction Models

Neuromuscular junctions (NMJs) are specialized synapses responsible for signal transduction between motor neurons (MNs) and skeletal muscle tissue. Malfunction at this site can result from developmental disorders, toxic environmental exposures, and neurodegenerative diseases leading to severe neurological dysfunction. Exploring these conditions in human or animal subjects is restricted by ethical concerns and confounding environmental factors. Therefore, in vitro NMJ models provide exciting opportunities for advancements in tissue engineering. In the last two decades, multiple NMJ prototypes and platforms have been reported, and each model system design is strongly tied to a specific application: exploring developmental physiology, disease modeling, or high-throughput screening. Directing the differentiation of stem cells into mature MNs and/or skeletal muscle for NMJ modeling has provided critical cues to recapitulate early-stage development. Patient-derived inducible pluripotent stem cells provide a personalized approach to investigating NMJ disease, especially when disease etiology cannot be resolved down to a specific gene mutation. Having reproducible NMJ culture replicates is useful for high-throughput screening to evaluate drug toxicity and determine the impact of environmental threat exposures. Cutting-edge bioengineering techniques have propelled this field forward with innovative microfabrication and design approaches allowing both two-dimensional and three-dimensional NMJ culture models. Many of these NMJ systems require further validation for broader application by regulatory agencies, pharmaceutical companies, and the general research community. In this summary, we present a comprehensive review on the current state-of-art research in NMJ models and discuss their ability to provide valuable insight into cell and tissue interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Implementation of a Binary Neural Network on a Passive Array of Magnetic Tunnel Junctions

The increasing scale of neural networks and their growing application space have produced demand for more energy- and memory-efficient artificial-intelligence-specific hardware. Avenues to mitigate the main issue, the von Neumann bottleneck, include in-memory and near-memory architectures, as well as algorithmic approaches. In this report we leverage the low-power and the inherently binary operation of magnetic tunnel junctions (MTJs) to demonstrate neural network hardware inference based on passive arrays of MTJs. In general, transferring a trained network model to hardware for inference is confronted by degradation in performance due to device-to-device variations, write errors, parasitic resistance, and nonidealities in the substrate. To quantify the effect of these hardware realities, we benchmark 300 unique weight matrix solutions of a two-layer perceptron to classify the Wine dataset for both classification accuracy and write fidelity. Despite device imperfections, we achieve software-equivalent accuracy of up to 95.3% with proper tuning of network parameters in 15 x 15 MTJ arrays having a range of device sizes. The success of this tuning process shows that new metrics are needed to characterize the performance and quality of networks reproduced in mixed signal hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Sensitivity Enhancement and Random Telegraph Noise in Magnetic Tunnel Junctions with Compensated Anisotropy

We demonstrate the manipulation of perpendicular magnetic anisotropy (PMA) in magnetic tunnel junctions (MTJs) by varying the layer stacks and temperature. PMA is tuned to compensate the shape anisotropy, giving a nonhysteretic magnetic response, a noteworthy sensitivity enhancement, and a field detectability of 1.8 nT/$\sqrt{Hz}$ at 100 kHz. Such a method is further exemplified in multiple MTJs, providing a solution to obtain desired sensitivities and operating temperatures. Additionally, the electronic noise of this MTJ is revealed as a random telegraph noise (RTN) due to a generation-recombination process. In conclusion, the observed voltage-dependent RTN could potentially be applied to true random number generators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Rashba spin-orbit coupling enhanced magnetoresistance in junctions with one ferromagnet

We explain how Rashba spin-orbit coupling (SOC) in a two-dimensional electron gas (2DEG), or in a conventional s-wave superconductor, can lead to a large magnetoresistance even with one ferromagnet. However, such enhanced magnetoresistance is not generic and can be nonmonotonic and change its sign with Rashba SOC. For an in-plane rotation of magnetization, it is typically negligibly small for a 2DEG and depends on the perfect transmission which emerges from a spin-parity-time symmetry of the scattering states, while this symmetry is generally absent from the Hamiltonian of the system. The key difference from considering the normal-state magnetoresistance is the presence of the spin-dependent Andreev reflection at superconducting interfaces. In the fabricated junctions of quasi-2D van der Waals ferromagnets with conventional s-wave superconductors (Fe 0.29 ⁢TaS 2 /NbN) we find another example of enhanced magnetoresistance where the presence of Rashba SOC reduces the effective interfacial strength and is responsible for an equal-spin Andreev reflection. The observed nonmonotonic trend in the out-of-plane magnetoresistance with the interfacial barrier is an evidence for the proximity-induced equal-spin-triplet superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Controllable Reset Behavior in Domain Wall–Magnetic Tunnel Junction Artificial Neurons for Task-Adaptable Computation

Neuromorphic computing with spintronic devices has been of interest due to the limitations of CMOS-driven von Neumann computing. Domain wall–magnetic tunnel junction (DW-MTJ) devices have been shown to be able to intrinsically capture biological neuron behavior. Edgy-relaxed behavior, where a frequently firing neuron experiences a lower action potential threshold, may provide additional artificial neuronal functionality when executing repeated tasks. In this letter, we demonstrate that this behavior can be implemented in DW-MTJ artificial neurons via three alternative mechanisms: shape anisotropy, magnetic field, and current-driven soft reset. Using micromagnetics and analytical device modeling to classify the Optdigits handwritten digit dataset, we show that edgy-relaxed behavior improves both classification accuracy and classification rate for ordered datasets while sacrificing little to no accuracy for a randomized dataset. This letter establishes methods by which artificial spintronic neurons can be flexibly adapted to datasets.

42 ENGINEERING↗
DOE OSTI2022

Demonstration of >6.0-kV Breakdown Voltage in Large Area Vertical GaN p-n Diodes With Step-Etched Junction Termination Extensions

Vertical gallium nitride (GaN) p-n diodes have garnered significant interest for use in power electronics where high-voltage blocking and high-power efficiency are of concern. In this article, we detail the growth and fabrication methods used to develop a large area (1 mm 2 ) vertical GaN p-n diode capable of a 6.0-kV breakdown. We also demonstrate a large area diode with a forward pulsed current of 3.5 A, an 8.3-mΩ$\cdot$cm 2 differential specific ON-resistance, and a 5.3-kV reverse breakdown. In addition, we report on a smaller area diode (0.063 mm 2 ) that is capable of 6.4-kV breakdown with a differential specific ON-resistance of 10.2 mΩ$\cdot$cm 2 , when accounting for current spreading through the drift region at a 45° angle. Finally, the demonstration of avalanche breakdown is shown for a 0.063-mm 2 diode with a room temperature breakdown of 5.6 kV. In this work, these results were achieved via epitaxial growth of a 50-μm drift region with a very low carrier concentration of <1×10 15 cm –3 and a carefully designed four-zone junction termination extension.

42 ENGINEERING↗
DOE OSTI2021

Heavy-ion-induced displacement damage effects in magnetic tunnel junctions with perpendicular anisotropy

Here, we evaluate the resilience of CoFeB/MgO/CoFeB magnetic tunnel junctions (MTJs) with perpendicular magnetic anisotropy to displacement damage induced by heavy ion irradiation. MTJs were exposed to 3 MeV Ta 2+ ions at different levels of ion beam fluence spanning five orders of magnitude. The devices remained insensitive to beam fluences up to 10 11 ions/cm 2 , beyond which a gradual degradation in the device magnetoresistance, coercive magnetic field, and spin-transfer-torque switching voltage were observed, ending with a complete loss of magnetoresistance at very high levels of displacement damage (>0.035 displacements per atom). The loss of magnetoresistance is attributed to structural damage at the MgO interfaces, which allows electrons to scatter among the propagating modes within the tunnel barrier and reduces the net spin polarization. Ion-induced damage to the interface also reduces the perpendicular magnetic anisotropy. This study clarifies the displacement damage thresholds that lead to significant irreversible changes in the characteristics of spin-transfer-torque magnetic random access memory (STT-MRAM) and elucidates the physical mechanisms underlying the deterioration in device properties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Search for baryon junctions in e+A collisions at the electron ion collider

Constituent quarks in a nucleon are the essential elements in the standard “quark model” associated with the electric charge, spin, mass, and baryon number of a nucleon. Quantum chromodynamics (QCD) describes nucleon as a composite object containing current quarks (valence quarks and sea (anti-)quarks) and gluons. These subatomic elements and their interactions are known to contribute in complex ways to the overall nucleon spin and mass. In the early development of QCD theory in the 1970s, an alternative hypothesis postulated that the baryon number might manifest itself through a non-perturbative configuration of gluon fields forming a Y-shaped topology known as the gluon junction. In this work, we propose to test such hypothesis by measuring (i) the Regge intercept of the net-baryon distributions for e+(p)Au collisions, (ii) baryon and charge transport in the isobaric ratio between e+Ru and e+Zr collisions, and (iii) target flavor dependence of proton and antiproton yields at large rapidity, transported from the hydrogen and deuterium targets in e+p(d) collisions. Our study indicates that these measurements at the EIC can help determine what carries the baryon number.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A computational approach to complex junctions and interfaces

Molecular- and nano- junctions, surfaces, interfaces, and interfacial processes have been the subjects of this DOE supported program for about 20 years. We have investigated electronic and magnetic structure, spin-dependent charge transport, and emerging phenomena at surfaces and interfaces in a number of physical systems ranging from nano-clusters, to nanowires, to two-dimensional (2D) crystals and their interactions, to bulk matter. Eighty-four refereed papers were published [1-84], with a majority effort from the group led by the PI, and over a hundred presentations were made at international conferences. We use first-principles methods in the framework of density functional theory in conjunction with nano-equilibrium Green function techniques, semi-empirical Boltzmann transport theory, tight-binding models, and the Hubbard model and many-body wavefunction approaches. In pursuing our scientific goals, we have also developed a number of computational algorithms and computational packages.

2D materials↗