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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

Unveiling the nature of Ga-based chalcogenides for electrical switching selectors

Three-dimensional phase-change memory with stackable crossbar architecture is a promising technology to meet the urgent demands for high-density storage and rapid information processing in the era of explosive data growth. The performance depends strongly on the properties of ovonic threshold switching (OTS) selectors, which control the on/off states of memory units. Amorphous GaS serves as an outstanding OTS material, distinguished by its sizable mobility gap and high crystallization temperature, while the underlying mechanism continues to be inadequately comprehended. Here, in this work, we systematically studied the structural and electronic properties of amorphous Ga-X (X = S/Se/Te) using first-principles calculations. The results show that Ga atoms adopt tetrahedral motifs, while S/Se/Te atoms predominantly exhibit the structure of a distorted triangular pyramid. This structural arrangement is ascribed to the substantial dative bonds formed by the lone-pair electrons of the anions and the vacant sp3 orbitals around Ga atoms. Large mobility gaps (e.g., GaS: 2.43 eV, GaSe: 1.76 eV, GaTe: 1.26 eV) and distinct mid-gap states (e.g., ∼0.66 eV above valence band tail) ensure that these three chalcogenide glasses can be switched on under an external electric field while effectively suppressing leakage current without a bias, and the defect electronic states originate from short, robust Ga-Ga bonds due to the formation of distorted chain-like local structures. Our research elucidates the mechanisms of amorphous Ga-X as OTS materials, enriching the spectrum of electrical switching selectors by incorporating III-VI chalcogenides. This inclusion offers novel opportunities for the refinement and optimization of high-density integrated memory systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Reduced Geometry for the NB5 Velocity Selector Shielding Box

This report details the reduced NB5 velocity selector shielding box that has been isolated from the complete HFIR CGH model in order to speed up detailed calculations of the velocity selector shielding. This shielding model is intended for outsourcing shielding optimization calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Vertical 2T-nC FeRAM Demonstration: BEOL Read Transistor for 4F 2 Memory Strings and Two-Terminal Selector Design for Polarization Disturb Mitigation

In this work, we demonstrate a vertical 2T-nC FeRAM with a back-end-of-line (BEOL) read transistor (T R ) for 4F 2 string and propose a selector design to mitigate polarization disturb in passive capacitor crossbar arrays. Key contributions include: 1) successful integration and operation composed of a Si MOSFET write transistor (T W ), 3-layer cylindrical ferroelectric capacitors, and Si-doped In 2 O 3 BEOL T R , demonstrating the feasibility of 4F 2 2T−nC string; 2) introducing nonlinearity into the capacitor stack to suppress ferroelectric voltage drop under inhibition biases while maintaining sufficient write voltage, reducing disturbance; 3)modeling and experimental validation of inserting a metalsemiconductor (a-Si)-metal (MSM) selector into the capacitor in mitigating the disturb, particularly achieving 9x reduction of disturb after 10 6 cycles in the V W /2 scheme.

42 ENGINEERING↗
DOE OSTI2024

Nitrogen: A promising doping strategy for high-performance ovonic threshold switching selectors

The Ovonic Threshold Switching (OTS) selector serves as an essential component in the development of three-dimensional high-density memory integration technology. Nevertheless, the state-of-the-art high-performance OTS materials usually contain toxic elements such as arsenic (As), posing significant risks to both environmental and human health. Nitrogen (N), which belongs to the same group as arsenic (As), has emerged as a highly promising alternative for As doping. However, the underlying mechanisms that govern N-based OTS materials have not yet been extensively investigated. In this study, we delve into the effects of N doping on the structural, bonding, and electronic properties of amorphous GeSe (a-GeNSe) by ab initio molecular dynamics simulations to bridge the knowledge gap. Our findings indicate that upon N doping in a-GeSe, the formation of robust Ge-N bonds, along with N-centered tetrahedral and triangular structures, resulting in the sluggish atomic movement that enhances the thermal stability and endurance of a-GeNSe. The OTS characteristics are significantly influenced by the material’s electronic band structure, and thus the relatively slow performance drift can be attributed to the stabilization of mid-gap states, a result of N doping which effectively slows down the aging process of chalcogenide glass. Moreover, the increased mobility gap in a-GeNSe raises the threshold voltage (V th ), making it more compatible with commercially available phase-change memory materials. Furthermore, our findings reveal the extensive impact of the N element on a typical OTS material and offer valuable perspectives for alternative doping strategies that could potentially supplant As practices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Monte Carlo simulation analysis for radiation damage on Glidcop Al-15 caused by 17-20 MeV/u heavy ions

The Facility for Rare Isotope Beams (FRIB) SRF linear heavy-ion accelerator is designed to accelerate all ions up to uranium to a maximum beam power of 400 kW. Several beam intercepting devices (BIDs) are essential to the successful operation of the accelerator, including a low power charge selector (LPCS) made of copper containing 0.15% precipitated aluminum oxide by weight called Glidcop Al-15. As FRIB ramps up the primary beam power beyond the current 20 kW level, the charge selector must withstand higher radiation damage rates, typically measured in displacements per atom (dpa). Significant beam induced radiation damage including significant deformation, like swelling, blistering, and cracking has been observed on a recently removed LPCS. We also observed physical features up to about 5.5 mm wide and appear to be deeper than the projected range of any ions. This paper presents the results of Monte Carlo simulations carried out using the Particle and Heavy Ion Transport code System (PHITS), quantifying the total damage dose and ion concentration, etc. Simulating an accurate irradiation history is essential to determining the scope of post irradiation examination (PIE) work.

Fletcher, Ethan [Michigan State U.]↗
DOE OSTI2024

A Platform for Ultra-Fast Proton Probing of Matter in Extreme Conditions

Recent developments in ultrashort and intense laser systems have enabled the generation of short and brilliant proton sources, which are valuable for studying plasmas under extreme conditions in high-energy-density physics. However, developing sensors for the energy selection, focusing, transport, and detection of these sources remains challenging. This work presents a novel and simple design for an isochronous magnetic selector capable of angular and energy selection of proton sources, significantly reducing temporal spread compared to the current state of the art. The isochronous selector separates the beam based on ion energy, making it a potential component in new energy spectrum sensors for ions. Analytical estimations and Monte Carlo simulations validate the proposed configuration. Due to its low temporal spread, this selector is also useful for studying extreme states of matter, such as proton stopping power in warm dense matter, where short plasma stagnation time (<100 ps) is a critical factor. The proposed selector can also be employed at higher proton energies, achieving final time spreads of a few picoseconds. This has important implications for sensing technologies in the study of coherent energy deposition in biology and medical physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Structure, bonding and electronic characteristics of amorphous Se

Ovonic threshold switching (OTS) selector can effectively improve the storage density and suppress the leakage current of advanced phase-change memory. As a prototypical OTS material, amorphous GeSe is widely investigated. But the attentions paid to amorphous Se (i.e., the functional constituent in amorphous GeSe) is very limited up to now. Here, in this work, we have explored the structure, bonding and electronic characteristics of amorphous Se using ab initio molecular dynamics simulations. The results reveal that the Se atoms in amorphous Se tend to form the 2-coordinated configurations, and they connect with each other to form the long chains. The fraction of vibrational density of state located in high frequency range is relatively large, and the formation energy of Se-Se bond is as large as 4.44 eV, hinting that the Se-Se bonds in chains possess a high stability. In addition, the mid-gap state related to the OTS behavior is also found in the amorphous Se despite of the small proportion. Our findings enrich the knowledge of the amorphous Se, which contributes to the applications of Se-based OTS selectors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Revealing the structure and electronic characteristics of Te-rich threshold switching materials for high-density integration

Ovonic threshold switching (OTS) selectors play an important role in the integration of advanced three-dimensional memory. Selectors based on tellurium (Te)-containing materials exhibit significant promise due to their low threshold voltages and superior consistency. Here we have theoretically studied the structure and electronic properties of a typical OTS material, amorphous GeTe 6 , to explore the switching mechanisms using ab initio molecular dynamics simulations. The results indicate that Ge atoms tend to bond with Te atoms, forming stable chemical bonds. The Te-centered clusters are predominantly in the form of distorted octahedrons, while the Ge-centered clusters are in the form of both octahedrons and tetrahedrons. Notably, the proportion of tetrahedrons within the 4-coordinated Ge-centered clusters reaches an impressive 66.9%. These tetrahedrons are randomly dispersed throughout the simulated cell, leading to a stable amorphous configuration. The mid-gap state observed in the mobility bandgap originates from the atomic chain composed of both over-coordinated Ge and Te atoms. It is the inherent stability of the chemical environment within amorphous GeTe 6 that enables it to maintain its amorphous phase under a repeated threshold voltage, a characteristic that distinguishes it from non-OTS materials, such as amorphous tellurium. Furthermore, our findings provide an in-depth understanding of the structure and electronic characteristics of amorphous GeTe 6 , which can promote the design and application of the Te-rich threshold switching materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Double-sided electron energy analyzer for measurement of non-Maxwellian electron energy distributions

Here, a double-sided electron energy analyzer is developed for studies of magnetic reconnection. It can measure electron energy distribution functions along two directions opposite to each other at the same time. Each side is composed of a floating reference grid, an energy selector grid, and a collector plate. The voltage of the selector grid is swept from –40 to 0 V with respect to the reference grid with a frequency of 1 MHz. This fast sweeping is required to resolve sub-Alfvénic changes in plasma quantities of the Magnetic Reconnection Experiment, where the typical Alfvénic time is a few microseconds. The reliability of the energy analyzer is checked in Maxwellian plasmas away from the reconnection region. In this case, the electron temperature computed from the electron energy distribution function agrees with measurements of a reference triple Langmuir probe. When it is located near the reconnection region, the temperatures of the tail electron population from both sides, facing into the electron flow and facing away from it, exceed the bulk electron temperature measured by the Langmuir probe by a factor of about 2.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System (CYDRES)

The DOE CYDRES project is driven by the urgent need to address critical research gaps in the domain of cyber-physical security of smart buildings, including Grid-interactive Efficient Buildings (GEBs). CYDRES, a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms. CYDRES consists of five key modules: a multi-layer network analyzer, an Automatic Fault Detection, Diagnosis, and Prognosis (AFDDP) framework, an intelligent mode selector, a cyber-resilient control framework, and a situation awareness platform. The Network Analyzer employs a data-driven framework that includes a protocol state learning tool and a CRF (Conditional Random Field) command validator. In Hardware-In-the-Loop (HIL) testbeds, it achieved 100% detection accuracy with a false alarm rate of 3%, validating its efficacy in identifying selected cyber-attacks. The AFDDP framework leverages pattern matching, PCA (Principal Component Analysis)-based strategies, and a DBN (Dynamic Bayesian Network)-based fault diagnosis approach to pinpoint the causes of physical system abnormalities using Building Automation System (BAS) data. In HIL experiments, the AFDDP module attained a detection accuracy of over 95% with a false alarm rate below 7%. Additionally, the fault detector utilized machine learning (Random Forest) and deep learning (Multi-Layer Perceptron) methods with acoustic sensor data to achieve a 100% fault detection accuracy in Heating, Ventilation, and Air-Conditioning (HVAC) equipment. The Mode Selector offered real-time impact analysis, allowing immediate actions to protect BASs in the face of emerging threats. The cyber-resilient control framework included an adaptive Model Predictive Control (MPC) and a measurement compensator, reducing temperature violations by up to 94% and improving the total demand flexibility by up to 70% in HIL experiments. Such HIL experiments covered a cyber-attack case and a physical fault case, showcasing CYDRES’ efficiency in maintaining operational continuity during threats. The situation awareness platform in Grafana enhanced real-time threat detection and response visualization, augmenting the operational awareness for building operators. CYDRES demonstrated high technical effectiveness in various test scenarios, particularly in HIL environments. The project's phased development approach ensured efficient use of resources, highlighting its practical feasibility and readiness for commercialization. By enhancing the security and resilience of building operations, CYDRES represents a significant advance in mitigating risks associated with cyber-physical systems, thereby enhancing public confidence in the safety of modern building infrastructure. Future directions for the project include expanding testing protocols, refining AFDDP methodologies, exploring more comprehensive resilient control strategies, and testing in real commercial buildings.

42 ENGINEERING↗
DOE OSTI2026

An efficient explicit implementation of a near-optimal quantum algorithm for simulating linear dissipative differential equations

We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator as a weighted sum of Hamiltonian evolutions, thereby emulating a dissipative problem by mixing various time scales. We introduce an efficient encoding of the LCHS into a quantum circuit based on a simple coordinate transformation that turns the dependence on the summation index into a trigonometric function. Classically, this method is equivalent to the use of a highly accurate Fejér-Clenshaw-Curtis quadrature formula. Quantumly, this significantly simplifies block-encoding of a dissipative problem and allows one to perform an exponential number of Hamiltonian simulations by a single Quantum Signal Processing (QSP) circuit. The resulting LCHS circuit has high success probability and the selector scales logarithmically with the number of terms in the LCHS sum and linearly with time. Careful analysis of error convergence proves that this method is more efficient than other LCHS circuits that have recently appeared in the literature. We verify the quantum circuit and its scaling by simulating it on a digital emulator of fault-tolerant quantum computers and, as a test problem, solve the advection-diffusion equation. The proposed algorithm can be used for simulating a wide class of nonunitary initial-value problems including the Liouville equation with added dissipation and linear embeddings of nonlinear systems, such as the Koopman-von Neumann and Carleman embeddings.

Novikau, I [Lawrence Livermore National Laboratory↗
DOE OSTI2023

Accelerating matrix-centric graph processing on GPUs through bit-level optimizations

Even though it is well known that binary values are common in graph applications (e.g., adjacency matrix), how to leverage the phenomenon for efficiency has not yet been adequately explored. This paper presents a systematic study on how to unlock the potential of the bit-level optimizations of graph computations that involve binary values. It proposes a two-level representation named Bit-Block Compressed Sparse Row (B2SR) and presents a series of optimizations to the graph operations on B2SR by the intrinsics of modern GPUs. It additionally introduces Deep Reinforcement Learning (DRL) as an efficient way to best configure the bit-level optimizations on the fly. Additionally, the DQN-based adaptive tile size selector with dedicated model training can reach 68% prediction accuracy. Evaluations on NVIDIA Pascal and Volta GPUs show that the optimizations bring up to 40× and 6555× for essential GraphBLAS kernels SpMV and SpGEMM, respectively, making GraphBLAS-based BFS accelerate up to 433×, SSSP, PR, and CC up to 35×, and TC up to 52×.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Incident beamline design for a modern cold triple axis spectrometer at the High Flux Isotope Reactor

A modern cold triple axis spectrometer is being planned for the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory. Here, we describe the design of an incident beamline that will put a flux of ~ 10 8 $\frac {n}{cm^{2}s}$ on a sample with an area of 2 cm X 2 cm. It takes current physical constraints at HFIR into account and it can accommodate both single and multiplexed analyzer-detector secondary spectrometers and large superconducting magnets. The proposed incident beamline includes a multi-channel guide with horizontal focusing, a neutron velocity selector, components to facilitate an incident beam polarization option, and a double-focusing pyrolytic graphite monochromator. Here, this work describes the process of optimizing the guide system and monochromator and summarizes the expected performance of the incident beamline for non-polarized operation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Ferroelectric capacitors and field-effect transistors as in-memory computing elements for machine learning workloads

Abstract This study discusses the feasibility of Ferroelectric Capacitors (FeCaps) and Ferroelectric Field-Effect Transistors (FeFETs) as In-Memory Computing (IMC) elements to accelerate machine learning (ML) workloads. We conducted an exploration of device fabrication and proposed system-algorithm co-design to boost performance. A novel FeCap device, incorporating an interfacial layer (IL) and$$\text {Hf}_{0.5}\text {Zr}_{0.5}\text {O}_2$$ Hf 0.5 Zr 0.5 O 2 (HZO), ensures a reduction in operating voltage and enhances HZO scaling while being compatible with CMOS circuits. The IL also enriches ferroelectricity and retention properties. When integrated into crossbar arrays, FeCaps and FeFETs demonstrate their effectiveness as IMC components, eliminating sneak paths and enabling selector-less operation, leading to notable improvements in energy efficiency and area utilization. However, it is worth noting that limited capacitance ratios in FeCaps introduced errors in multiply-and-accumulate (MAC) computations. The proposed co-design approach helps in mitigating these errors and achieves high accuracy in classifying the CIFAR-10 dataset, elevating it from a baseline of 10% to 81.7%. FeFETs in crossbars, with a higher on-off ratio, outperform FeCaps, and our proposed charge-based sensing scheme achieved at least an order of magnitude reduction in power consumption, compared to prevalent current-based methods.

Science & Technology - Other Topics↗
DOE OSTI2023

Unveiling the structure and electronic characteristics of amorphous GeS for high performance threshold switching

Ovonic threshold switching selectors are widely studied owing to the essential application in high density phase-change memory. Amorphous GeS is proposed as a potential candidate for the excellent performance. However, the knowledge of amorphous GeS is still insufficient up to date. Here, we have studied the structure and electronic characteristics of GeS in the amorphization process, by using ab initio molecular dynamics simulations. The results indicate that the amorphous GeS is mainly made up of Ge–S bonds. The Ge- and S-centered clusters are dominantly in the form of octahedral structures in liquid GeS. Furthermore, during the amorphization process, most of Ge-centered clusters become highly coordinated octahedrons while a small number of Ge-centered clusters change to tetrahedrons, and the S-centered clusters deviate from the octahedral structure gradually. In addition, the large bandgap and the relatively small mid-gap states in amorphous GeS lead to a high switching voltage.

42 ENGINEERING↗
DOE OSTI2025

Harnessing ferro-valleytricity in pentalayer rhombohedral graphene for memory and compute

Two-dimensional materials with multiple degrees of freedom, including spin, valleys, and orbitals, open up an exciting avenue for engineering multifunctional devices. Beyond spintronics, these degrees of freedom can lead to novel quantum effects such as valley-dependent Hall effects and orbital magnetism, which could revolutionize next-generation electronics. However, achieving independent control over valley polarization and orbital magnetism has been a challenge due to the need for large electric fields. A recent breakthrough involving pentalayer rhombohedral graphene has demonstrated the ability to individually manipulate anomalous Hall signals and orbital magnetic hysteresis, forming what is known as a valley-magnetic quartet. Here, we leverage the electrically tunable ferro-valleytricity of pentalayer rhombohedral graphene to develop nonvolatile memory and in-memory computation applications. We propose an architecture for a dense, scalable, and selector-less nonvolatile memory array that harnesses the electrically tunable ferro-valleytricity. In our designed array architecture, nondestructive read and write operations are conducted by sensing the valley state through two different pairs of terminals, allowing for independent optimization of read/write peripheral circuits. The power consumption of our PRG-based array is remarkably low, with only ∼6 nW required per write operation and ∼2.3 nW per read operation per cell. This consumption is orders of magnitude lower than that of the majority of state-of-the-art cryogenic memories. Additionally, we engineer in-memory computation by implementing majority logic operations within our proposed nonvolatile memory array without modifying the peripheral circuitry. In conclusion, our framework presents a promising pathway toward achieving ultra-dense cryogenic memory and in-memory computation capabilities.

2D materials↗
DOE OSTI2023

PyTorch Circuit-Aware Bit-Cell Modeling

SAND2024-08549O PyTorch Circuit-Aware Bit-Cell Modeling, a Python library, demonstrates circuit-aware training for analog machine learning accelerators. Built upon PyTorch, this software provides hardware-aware versions of common neural network layers to mitigate non-ideal behavior from novel hardware. The software provides accurate forward and backward pass estimates for hardware-mapped neural networks that are implemented in crossbars (arrays) that contain a non-linear transistor selector device. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Bennett, Christopher↗
DOE OSTI2025

FLORIS Wake Map [SWR-25-71]

The FLORIS Wake Map repository is a set of tools for creating maps of cluster wake impacts based on NREL's FLORIS software and modeling tool (https://github.com/nrel/floris). The floriswakemap package comprises two main modules: the wake_map module, dedicated to the WakeMap class, and the area_selector module, dedicated to the AreaSelector class. The WakeMap class is used to generate maps of wake impacts on both new and existing clusters, while the AreaSelector class provides selections of candidate areas for new developments based on an instantiated WakeMap object.

Sinner, Michael (Misha) [National Renewable Energy↗