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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantum Efficiency Gain in 2D Perovskite Photo and X‐Ray Detectors

Abstract The perovskite polycrystalline thin film detector fabricated by solution method is a promising low‐cost, scalable technology for radiation imaging, but its thin volume limits the sensing efficiency for high‐energy X‐ray photons. This work reports 2D perovskite thin film photo‐diodes with a detection gain when sensing visible and X‐ray photons. Detailed power and temperature‐dependent device characterizations reveal a charge multiplication effect to be responsible for the observed high gain. This is caused by a disparity in electron and hole transport, where electron transport is retarded by a trap/de‐trap process via shallow trap states, whereas the hole transport is fast enough to produce a photoconductive gain in satisfying the charge neutrality. The 2D perovskite made with butylamine spacers is also found to exhibit a larger efficiency gain than those made with phenylethylamines because of the higher likelihood of forming shallow traps in the former. The thin film diodes feature a high temporal response over 1 MHz due to the fast charge collection across a thin volume, and the discovery provides device physics mechanisms in connection to material structure‐function relationship for future optoelectronics design that can boost the efficiency of X‐ray sensing and dim light detection.

2D perovskites↗
DOE OSTI2022

Proton Storage in Metallic H 1.75 MoO 3 Nanobelts through the Grotthuss Mechanism

The proton, as the cationic form of the lightest element-H, is regarded as most ideal charge carrier in "rocking chair " batteries. However, current research on proton batteries is still at its infancy, and they usually deliver low capacity and suffer from severe acidic corrosion. In this work, electrochemically activated metallic H 1.75 MoO 3 nanobelts are developed as a stable electrode for proton storage. The electrochemically pre-intercalated protons not only bond directly with the terminal O 3 site via strong O-H bonds but also interact with the oxygens within the adjacent layers through hydrogen bonding, forming a hydrogen-bonding network in H 1.75 MoO 3 nanobelts and enabling a diffusion-free Grotthuss mechanism as a result of its ultralow activation energy of ~0.02 eV. To the best of our knowledge, this is the first reported inorganic electrode exhibiting Grotthuss mechanism-based proton storage. Additionally, the proton intercalation into MoO 3 with formation of H 1.75 MoO 3 induces strong Jahn-Teller electron-phonon coupling, rendering a metallic state. As a consequence, the H 1.75 MoO 3 shows an outstanding fast charging performance and maintains a capacity of 111 mAh/g at 2500 C, largely outperforming the state-of-art battery electrodes. More importantly, a symmetric proton ion full cell based on H 1.75 MoO 3 was assembled and delivered an energy density of 14.7 Wh/kg at an ultrahigh power density of 12.7 kW/kg, which outperforms those of fast charging supercapacitors and lead-acid batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Unconventional solitonic high-temperature superfluorescence from perovskites

Fast thermal dephasing limits macroscopic quantum phenomena to cryogenic conditions and hinders their use at ambient temperatures. For electronic excitations in condensed media, dephasing is mediated by thermal lattice motion. Therefore, taming the lattice influence is essential for creating collective electronic quantum states at high temperatures. Although there are occasional reports of high-T c quantum effects across different platforms, it is unclear which lattice characteristics and electron–lattice interactions lead to macroscopically coherent electronic states in solids. Here we studied intensity fluctuations in the macroscopic polarization during the emergence of superfluorescence in a lead halide perovskite and showed that spontaneously synchronized polaronic lattice oscillations accompany collective electronic dipole emission. We further developed an effective field model and theoretically confirmed that exciton–lattice interactions lead to a new electronically and structurally entangled coherent extended solitonic state beyond a critical polaron density. The analysis shows a phase transition with two processes happening in tandem: incoherent disordered polaronic lattice deformations establish an order, while macroscopic quantum coherence among excitons simultaneously emerges. Recombination of excitons in this state culminates in superfluorescence at high temperatures. Our study establishes fundamental connections between the transient superfluorescence process observed after the impulsive excitation of perovskites and general equilibrium phase transitions achieved by thermal cooling. By identifying various electron–lattice interactions in the perovskite structure and their respective role in creating collectively coherent electronic effects in solids, our work provides unprecedented insight into the design and development of new materials that exhibit high-temperature macroscopic quantum phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2023

PFPO plasma scenarios for exploration of long pulse operation in ITER

Long Pulse Scenarios (LPS) in ITER foreseen during the Pre-Fusion Power Operation (PFPO) phase of the ITER Research Plan (IRP) are assessed using 1.5D transport simulations within the ASTRA framework. Such assessment is required to predict the operational space for LPS operation in PFPO, as well as to evaluate which physics processes for LPS operation during Fusion Power Operation (FPO) could be studied during PFPO. An important aspect in the development of LPSs in PFPO is to minimize lifetime consumption of the Central Solenoid (CS) for these scenarios. The maximum pulse length achievable for LPSs in PFPO with no consumption of CS lifetime (currents in CS coils $⩽$30 kA per turn) has been assessed for a range of heating schemes and heating mixes, confinement regimes (L-mode and H-mode) and for helium and hydrogen plasmas. The operational space of LPS and pulse length has been explored through density scans with the Heating and Current Drive mix required for the FPO Q $⩾$ 5 steady-state plasma scenario (namely Neutral Beam Injection and Electron Cyclotron Heating) including acceptable shine through losses on the first wall for both helium and hydrogen plasmas. Fast particle physics aspects that are common between FPO plasmas and LPS PFPO H-mode plasmas at low densities are studied including MHD stability analysis with the KINX code and non-perturbative critical gradient model based on high-n Toroidal Alfven Eigenmodes (TAE) stability kinetic ballooning code HINST calculations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

First high-power helicon results from DIII-D

Abstract More than 0.6 MW of rf power at 476 MHz has been coupled to DIII-D plasmas by launching helicon (whistler) waves with a traveling-wave antenna (comb-line) in the fast-wave polarization (Van Compernolle et al 2021 Nucl. Fusion 61 116034) which resulted in the observation of electron heating of the core plasma with single-pass absorption based on ray-tracing in L-mode discharges. The coupling performance of the 1.5 m wide 30-element comb-line traveling-wave antenna has been consistent with expectations based on the 2015–2016 experiments on DIII-D with a low-power 12-element prototype (Pinsker et al 2018 Nucl. Fusion 58 106007). The conditioning process that was necessary to carry out high-power experiments is discussed; rf-specific impurities have not been observed. Parametric decay instabilities have been observed and are being investigated as a potential edge absorption mechanism (Porkolab et al 2023 AIP Conf. Proc. 2984 070004).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Understanding Proton Movement in [Fe-Fe] Hydrogenases

Nature uses specialized metalloenzymes to carry out small molecule activation reactions, including CO 2 fixation, O 2 activation, and proton reduction, with unparalleled efficiency, rates, and selectivity. The latter reactions are performed by hydrogenases, protein metallo-complexes that interconverts H 2 to protons and electrons (H 2 oxidation) and the reverse reaction (H 2 production) with incredibly low energy input and amazingly fast kinetics. Reproducing both the activity and efficiency of metalloenzymes in sustainable anthropogenic systems remains one of the “holy grails” of inorganic chemistry. However, identifying the precise molecular components responsible for these desirable properties has been challenging in the natural metalloenzymes, hindering efforts to develop analogous processes in synthetic compounds. Considering the inherent complexity of a metalloenzyme and the many interactions, both strong and weak, that contribute to the function of an enzyme, we have elected to model natural metalloenzymes on a biochemical platform. Towards this end, we have a developed structural, functional, and mechanistic mimic of the [Ni-Fe] hydrogenases within a robust protein scaffold, rubredoxin, to understand the influence of the secondary coordination environment on the metal center. This involved preparing a series of three rubredoxin constructs containing a single point mutation at Val positions and making the NMR chemical shift assignments for the paramagnetic (nickel-substituted) and non-paramagnetic (zinc-substituted) form. These physical studies were complemented with in silico molecular dynamic studies on proteins with [Fe-S] clusters to engineer new proton channels to test in vitro . To assist our search for new natural metalloprotein scaffolds within the vast number of sequenced genomes, we created a neural network-based program to identify proteins with specific metal-binding sites. These computational and physical studies with metalloenzymes provide direct insight into the fundamental chemical principles driving the natural systems and offer design principles for developing catalysts that utilize analogous principles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Data reduction through optimized scalar quantization for more compact neural networks

Raw data generation for several existing and planned large physics experiments now exceeds TB/s rates, generating untenable data sets in very little time. Those data often demonstrate high dimensionality while containing limited information. Meanwhile, Machine Learning algorithms are now becoming an essential part of data processing and data analysis. Those algorithms can be used offline for post processing and post data analysis, or they can be used online for real time processing providing ultra low latency experiment monitoring. Both use cases would benefit from data throughput reduction while preserving relevant information: one by reducing the offline storage requirements by several orders of magnitude and the other by allowing ultra fast online inferencing with low complexity Machine Learning models. Moreover, reducing the data source throughput also reduces material cost, power and data management requirements. In this work we demonstrate optimized nonuniform scalar quantization for data source reduction. This data reduction allows lower dimensional representations while preserving the relevant information of the data, thus enabling high accuracy Tiny Machine Learning classifier models for online fast inferences. We demonstrate this approach with an initial proof of concept targeting the CookieBox, an array of electron spectrometers used for angular streaking, that was developed for LCLS-II as an online beam diagnostic tool. We used the Lloyd-Max algorithm with the CookieBox dataset to design an optimized nonuniform scalar quantizer. Optimized quantization lets us reduce input data volume by 69% with no significant impact on inference accuracy. When we tolerate a 2% loss on inference accuracy, we achieved 81% of input data reduction. Finally, the change from a 7-bit to a 3-bit input data quantization reduces our neural network size by 38%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Electronic Spin Relaxation and Clustering in High-Pressure High-Temperature Synthesized Microcrystalline Diamond Particles with Reduced Nitrogen Content

The negatively charged nitrogen-vacancy (NV – ) color center in diamonds is widely studied because of numerous applications of this unique quantum system in sensing and quantum information sciences. While substitutional nitrogen is required to form the NV – centers in diamond, it also yields other paramagnetic defects─primarily the neutrally charged substitutional nitrogen centers (P1)─that decrease NV – spin coherence, which in turn degrades performance in applications. Herein, we investigate high-pressure high-temperature synthesized diamond microparticles (ca. 140–185 μm) having lower─ranging from 3 to 38 ppm─than the typical nitrogen content of type 1b diamond ( ca. 100 ppm and higher) typically used for the production of fluorescent diamond particles with NV – centers. A suite of electron paramagnetic resonance, optically detected magnetic resonance, and nuclear magnetic resonance methods are used to characterize spin properties of P1 and NV – centers in the particles. Upon decreasing the nitrogen content from 29 to 3 ppm, the ensemble NV – T 2 relaxation time increased by about 3-fold as measured directly in the Hahn Echo experiment at magnetic field of 1.2 T. Analysis of electronic relaxation of P1 centers revealed the existence of at least two distinct populations of P1 centers, consisting of fast and slower relaxing spins and allowed for an estimation of local concentrations. Even with <10 ppm nitrogen contents, the analysis indicated a highly heterogeneous distribution of P1 centers, suggesting the possibility of P1 spin clustering even at low nitrogen concentrations. The combined data demonstrate that the particles prepared from HPHT diamond with a low nitrogen content offer improved spin properties that are beneficial for NV – sensing applications.

Carbon↗
DOE OSTI2021

VLBI Data Processing on Coronal Radio-sounding Experiments of Mars Express

The ESA’s Mars Express solar corona experiments were performed at two solar conjunctions in the years 2015 and 2017 by a number of radio telescopes in the European VLBI Network. This paper presents the methods to measure the frequency and phase fluctuations of the spacecraft radio signal, and the applications to study the characteristics of the plasma turbulence effects on the signal at a single station and at multiple stations via cross correlation. The power spectra of the frequency fluctuations observed between 4.9 and 76.3 R {sub s} have a power-law shape close to a Kolmogorov spectrum over the frequency interval ν {sub lo} < ν < ν {sub up}, where the nominal value of ν {sub lo} is set to 3 mHz and ν {sub up} is in the range of 0.03–0.15 Hz. The rms of the frequency fluctuations is presented as a function of the heliocentric distance. Furthermore, we analyze the variations of the electron column density fluctuations at solar offsets 4.9 R {sub s} and 9.9 R {sub s} and the cross-correlation products between the VLBI stations. The power density of the differential fluctuations between different stations decreases at ν < 0.01 Hz. Finally, the fast flow speeds of solar wind >700 km s{sup -1} are derived from the cross correlation of frequency fluctuations at ν < 0.01 Hz. The fast flow speeds of solar wind correspond to the high heliolatitude of the coronal region that the radio rays passed. The VLBI observations and analysis methods can be used to study the electron column density fluctuations and the turbulence at multiple spatial points in the inner solar wind by providing multiple lines of sight between the Earth and the spacecraft.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Modeling the Simultaneous Dropout of Energetic Electrons and Protons by Magnetopause Shadowing

Abstract Magnetopause shadowing (MPS) effect could drive a concurrent dropout of radiation belt electrons and ring current protons. However, its relative role in the dropout of both plasma populations has not been well quantified. In this work, we study the simultaneous dropout of MeV electrons and 100s keV protons during an intense geomagnetic storm in May 2017. A radial diffusion model with an event‐specific last closed drift shell is used to simulate the MPS loss of both populations. The model well captures the fast shadowing loss of both populations at L * > 4.6, while the loss at L * < 4.6, possibly due to the electromagnetic ion cyclotron wave scattering, is not captured. The observed butterfly pitch angle distributions of electron fluxes in the initial loss phase are well reproduced by the model. The initial proton losses at low pitch angles are underestimated, potentially also contributed by other mechanisms such as field line curvature scattering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Radiation-induced transients on solid and molten Li and K iodides

The study, quantification, and monitoring of iodine in nuclear power generation systems have been paramount due to its environmental and health implications. Thorough speciation and transport studies strengthened the development and deployment of water reactors, which are now required for the new generation of Molten Salt Reactors (MSR), where the fuel and coolant are a complex liquid system of suitable halides. The speciation, radiation-induced chemistry, and transport of iodine (I-127, I-129 and I-131) under extreme conditions of temperature and ionizing radiation are among the challenges for the future implementation of MSR’s. In aqueous systems, the triiodide-iodine-iodide (I3--I2-I-) equilibrium is strongly dependent on the conditions of the medium. In molten iodides and chlorides, the triiodide detection (and its disproportionation) poses challenges due to the extreme conditions of temperature and radiation, but studies have shown a dependence on temperature, absorbed dose and salt composition. Through absorption spectroscopy techniques (diffuse reflectance and high-temperature UV-Vis), as well as resonance (Electron Paramagnetic Resonance) it is possible to identify primary transients induced by ionizing radiation trapped in the solid phase (Solid-state radiolysis), and steady-state main absorption components with a fast-acquisition real-time spectroscopy. The presence of heterogeneous phase (colloids), viscosity changes, and gas evolution are among the observed processes. A specific case of study is speciation in the presence of Ni. A corrosion product with magnetic properties due to unpaired electrons in its electronic structure. Ferromagnetic materials are monitored in solidified salts to identify aggregation and phase separation. Comparative studies of eutectic mixtures of LiI-KI and LiCl-KCl with known addition of dopants will be presented, with a perspective of radiation chemistry and its possible implications in complex systems.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Multi-scale time-resolved electron diffraction: A case study in moiré materials

Ultrafast-optical-pump — structural-probe measurements, including ultrafast electron and x-ray scattering, provide direct experimental access to the fundamental timescales of atomic motion, and are thus foundational techniques for studying matter out of equilibrium. High-performance detectors are needed in scattering experiments to obtain maximum scientific value from every probe particle. Here we deploy a hybrid pixel array direct electron detector to perform ultrafast electron diffraction experiments on a WSe 2 /MoSe 2 2D heterobilayer, resolving the weak features of diffuse scattering and moiré superlattice structure without saturating the zero order peak. Enabled by the detector’s high frame rate, we show that a chopping technique provides diffraction difference images with signal-to-noise at the shot noise limit. Finally, we demonstrate that a fast detector frame rate coupled with a high repetition rate probe can provide continuous time resolution from femtoseconds to seconds, enabling us to perform a scanning ultrafast electron diffraction experiment that maps thermal transport in WSe 2 /MoSe 2 and resolves distinct diffusion mechanisms in space and time.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fast Single-Quantum Measurement with a Multi-Amplifier Sensing Charge-Coupled Device

A novel readout architecture that uses multiple non-destructive floating-gate amplifiers to achieve sub-electron readout noise in a thick, fully-depleted silicon detector is presented. This Multi-Amplifier Sensing Charge-Coupled Device (MAS-CCD) can perform multiple independent charge measurements with each amplifier; measurements with multiple amplifiers can then be combined to further reduce the readout noise. The readout speed of this detector scales roughly linearly with the number of amplifiers without requiring segmentation of the active area. The performance of this detector is demonstrated, emphasizing the ability to resolve individual quanta and the ability to combine measurements across amplifiers to reduce readout noise. The unprecedented low noise and fast readout of the MAS-CCD make it a unique technology for astronomical observations, quantum imaging, and low-energy interacting particles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Total Recycling of Copper Cable Scrap and Production of Carbon Using Fast Microwave Technology

The recycling of cable scrap, particularly from discarded electrical wiring, is gaining significant attention due to the rising demand for copper and the need for sustainable management of electronic waste. Traditionally, mechanical and thermal processings have been used to recover copper and plastic from cables. However, these approaches are often energy-intensive, time-consuming, and costly in terms of equipment and labor. In this study, we present a simple and effective method for recovering materials from cable scrap using a domestic microwave oven. Cable pieces (2–2.5 cm long) were exposed to 700 W of microwave irradiation under rotation for 30 s, enabling the rapid and efficient separation of high-quality copper metal from the core wire, and activated carbon from the carbonized plastic sheath. Microwaves facilitate this process through Ohmic heating, which induces electrical resistance in the metal, generating heat that mechanically loosens the metal and carbonized plastic components. The process demonstrates high efficiency, achieving an 80% reduction in energy consumption compared to conventional processings. This fast and energy-efficient method shows strong potential for scaling up to industrial recycling, offering a cost-effective and environmentally friendly way to recover high-quality materials for further use or repurposing.

Bourlinos, Athanasios B. (ORCID:0000000256165993)↗
DOE OSTI2022

$\mathrm{SIM}$-$\mathrm{STEM}$ $\mathrm{Lab}$: Incorporating Compressed Sensing Theory for Fast STEM Simulation

We report recently it has been shown that precise dose control and an increase in the overall acquisition speed of atomic resolution scanning transmission electron microscope (STEM) images can be achieved by acquiring only a small fraction of the pixels in the image experimentally and then reconstructing the full image using an inpainting algorithm. In this paper, we apply the same inpainting approach (a form of compressed sensing) to simulated, sub-sampled atomic resolution STEM images. We find that it is possible to significantly sub-sample the area that is simulated, the number of g-vectors contributing the image, and the number of frozen phonon configurations contributing to the final image while still producing an acceptable fit to a fully sampled simulation. Here we discuss the parameters that we use and how the resulting simulations can be quantifiably compared to the full simulations. As with any Compressed Sensing methodology, care must be taken to ensure that isolated events are not excluded from the process, but the observed increase in simulation speed provides significant opportunities for real time simulations, image classification and analytics to be performed as a supplement to experiments on a microscope to be developed in the future

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Real-time plasma monitoring framework for advanced plasma control and ML-research in DIII-D

Real-time and adaptive plasma control is crucial for robust tokamak operation, requiring sensitivity and tolerance measurements of the plasma state. This paper presents the implementation of an integrated real-time plasma monitoring framework on the DIII-D tokamak to support advanced control approaches, including machine-learning (ML) methods. The system is built on the SHIELD framework, a high-performance modular architecture that provides a unified pipeline for integrating diverse diagnostics. The framework leverages high-bandwidth digitizers, fast numerical processing, and deterministic, low-latency interconnects to stream high-fidelity data from diagnostics such as electron cyclotron emission (ECE), beam emission spectroscopy (BES), CO interferometers, and a visible tangential divertor camera (TangTV). The system’s validity is demonstrated through direct comparisons of real-time and offline data. Furthermore, we present two key applications of the developed plasma monitoring system with ML-based plasma control strategies, including real-time divertor detachment and active Alfvén Eigenmode control. As a result, this work presents a robust and scalable approach for integrating high-frequency, multidimensional diagnostics into advanced control algorithms for future fusion devices.

AI/ML↗
DOE OSTI2023

A fine pore-preserved deep neural network for porosity analytics of a high burnup U-10Zr metallic fuel

Abstract U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel system to design future fast reactors. To address the above issues, we introduce a workflow to process and analyze multi-source Scanning Electron Microscope (SEM) image data. Moreover, an encoder-decoder-based, deep fully convolutional network is proposed to segment pores accurately by integrating the residual unit and the densely-connected units. Two SEM 250 × field of view image datasets with different formats are utilized to evaluate the new proposed model’s performance. Sufficient comparison results demonstrate that our method quantitatively outperforms two popular deep fully convolutional networks. Furthermore, we conducted experiments on the third SEM 2500 × field of view image dataset, and the transfer learning results show the potential capability to transfer the knowledge from low-magnification images to high-magnification images. Finally, we use a pre-trained network to predict the pores of SEM images in the whole cross-sectional image and obtain quantitative porosity analysis. Our findings will guide the SEM microscopy data collection efficiently, provide a mechanistic understanding of the U-10Zr fuel system and bridge the gap between advanced characterization to fuel system design.

36 MATERIALS SCIENCE↗