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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Stacked-mosaic amplifier and diode delivery concept for kJ-class inertial fusion energy laser driver

We report on a laser amplifier architecture designed as a modular element for scaling to multi-megajoule laser facilities intended for inertial fusion energy (IFE) power plants. This kilojoule-class module features a stacked mosaic of gain media integrated with a diode delivery system for efficient optical pumping of the mosaic-structured gain medium, enabling high-repetition-rate operation at high wall plug efficiencies, necessary for an IFE driver. Details of a diode delivery system capable of pumping the mosaic architecture are presented. Comprehensive numerical modeling demonstrates that the stacked-mosaic approach reduces transverse gain by five orders of magnitude compared to a conventional full-aperture Yb:YAG based amplifier, substantially suppressing transverse amplified spontaneous emission (TASE) and enabling enhanced longitudinal energy extraction. Detailed analysis of thermal management and wavefront distortion in a 4 × 4 mosaic array indicates that temperature gradients and thermally induced aberrations are effectively controlled using gas cooling and commercially available phase-plate and deformable mirror technologies. We further discuss the applicability of a stacked-mosaic architecture to direct-drive IFE schemes, where broad spectral bandwidth is critical, and its compatibility with frequency conversion modules for up-conversion to blue wavelengths. Finally, an example point design for a 10 kJ, 10 Hz Yb:YAG module operating at 175 K with wall-plug efficiency exceeding 10 % is presented, underscoring the feasibility of this approach for next-generation high-energy lasers for IFE drivers. The results establish the stacked-mosaic amplifier as a scalable, robust platform not only for IFE but also for a broad range of advanced scientific and industrial laser applications.

Lasers↗
DOE OSTI2025

Field-resilient supercurrent diode in a multiferroic Josephson junction

The research on supercurrent diodes has surged rapidly due to their potential applications in electronic circuits at cryogenic temperatures. To unlock this functionality, it is essential to find supercurrent diodes that can work consistently at zero magnetic field and under ubiquitous stray fields generated in electronic circuits. However, a supercurrent diode with robust field tolerance is currently lacking. Here, we demonstrate a field-resilient supercurrent diode by incorporating a 2D multiferroic material into a Josephson junction, and observed a pronounced supercurrent diode effect at zero magnetic field. More importantly, the supercurrent rectification persists over a wide and bipolar magnetic field range beyond industrial standards for field tolerance. By theoretically modeling a multiferroic Josephson junction, we unveil that the interplay between spin-orbit coupling and multiferroicity underlies the unusual field resilience of the observed diode effect. This work introduces multiferroic Josephson junctions as a new field-resilient superconducting device for cryogenic electronics.

Yang, Hung-Yu [Univ. of California, Los Angeles, C↗
DOE OSTI2023

Capacitance–voltage modeling of mid-wavelength infrared nBn detectors

Capacitance–voltage measurements are a powerful technique to determine doping profiles of semiconductor pn junctions and Schottky barrier diodes. The measurements were recently extended to III-V-based mid-wavelength nBn infrared detectors, and absorber doping densities have been extracted using the widely accepted Schottky approximation, where the potential drop across the device is assumed to be across the depleting absorber layer. However, this approach is limited to when the absorber region of the nBn is under high reverse bias and thus is only able to extract the absorber region doping profile. Here, we introduce a semi-analytical model that is capable of extracting barrier dopant polarity, doping concentration, and thickness, as well as contact and absorber layer doping concentrations, all from a capacitance–voltage measurement. Rather than solely considering the potential drop across the depleting layers, it considers the potential drop across the accumulating layer as well. This negative charge accumulation occurs for the contact and absorber layers in the case of reverse and forward biases, respectively. This allows for a single model to be applied to a capacitance–voltage curve at forward and reverse biases and it can provide regions of bias where the absorber transitions from depletion to accumulation. We compare the agreement of the semianalytical model with modeling results from commercially available finite element method software and experimental capacitance–voltage data. Finally, we show that the method is consistent with the Schottky approximation of extracting absorber doping densities at high reverse bias and discuss the model's limitations.

Physics↗
DOE OSTI2022

Unraveling the Correlation between Raman and Photoluminescence in Monolayer MoS 2 through Machine‐Learning Models

Abstract 2D transition metal dichalcogenides (TMDCs) with intense and tunable photoluminescence (PL) have opened up new opportunities for optoelectronic and photonic applications such as light‐emitting diodes, photodetectors, and single‐photon emitters. Among the standard characterization tools for 2D materials, Raman spectroscopy stands out as a fast and non‐destructive technique capable of probing material's crystallinity and perturbations such as doping and strain. However, a comprehensive understanding of the correlation between photoluminescence and Raman spectra in monolayer MoS 2 remains elusive due to its highly nonlinear nature. Here, the connections between PL signatures and Raman modes are systematically explored, providing comprehensive insights into the physical mechanisms correlating PL and Raman features. This study's analysis further disentangles the strain and doping contributions from the Raman spectra through machine‐learning models. First, a dense convolutional network (DenseNet) to predict PL maps by spatial Raman maps is deployed. Moreover, a gradient boosted trees model (XGBoost) with Shapley additive explanation (SHAP) to bridge the impact of individual Raman features in PL features is applied. Last, a support vector machine (SVM) to project PL features on Raman frequencies is adopted. This work may serve as a methodology for applying machine learning to characterizations of 2D materials.

Lu, Ang‐Yu↗
DOE OSTI2024

Decoupling excitons from high-frequency vibrations in organic molecules

The coupling of excitons in π-conjugated molecules to high-frequency vibrational modes, particularly carbon–carbon stretch modes (1,000–1,600 cm -1 ) has been thought to be unavoidable. These high-frequency modes accelerate non-radiative losses and limit the performance of light-emitting diodes, fluorescent biomarkers and photovoltaic devices. Here, by combining broadband impulsive vibrational spectroscopy, first-principles modelling and synthetic chemistry, we explore exciton–vibration coupling in a range of π-conjugated molecules. We uncover two design rules that decouple excitons from high-frequency vibrations. First, when the exciton wavefunction has a substantial charge-transfer character with spatially disjoint electron and hole densities, we find that high-frequency modes can be localized to either the donor or acceptor moiety, so that they do not significantly perturb the exciton energy or its spatial distribution. Second, it is possible to select materials such that the participating molecular orbitals have a symmetry-imposed non-bonding character and are, thus, decoupled from the high-frequency vibrational modes that modulate the π-bond order. We exemplify both these design rules by creating a series of spin radical systems that have very efficient near-infrared emission (680–800 nm) from charge-transfer excitons. We show that these systems have substantial coupling to vibrational modes only below 250 cm -1 , frequencies that are too low to allow fast non-radiative decay. This enables non-radiative decay rates to be suppressed by nearly two orders of magnitude in comparison to π-conjugated molecules with similar bandgaps. Our results show that losses due to coupling to high-frequency modes need not be a fundamental property of these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Reconfigurable Planar Capacitor Sensor for Thru the Jacket Dielectric Constant Measurement of Cable Insulation

Planar capacitor sensors have been proposed to measure the aging-related dielectric constant variation of the jacket or insulation materials of cables. Although capacitor sensors have been used to monitor the aging of cable insulation by removing the jacket, through the jacket measurement of cable insulation dielectric constant variation is difficult because once the sensor is placed on the jacket it would either measure the aging of the jacket or that of the jacket and insulation together. A reconfigurable sensor along with innovative cable-specific models could be used to determine the jacket and insulation aging using the same sensor. For the proposed novel reconfigurable sensor, the electric field penetration depth is changed by activating and deactivating PIN diode switches. In one instance, the sensor measures the dielectric constant variation of the jacket, while in the next, it measures the dielectric constant variation of both the jacket and the insulation. Here, by leveraging previously developed capacitance estimation models from large-scale finite element simulations for a specific cable, these two sets of measurement data are used to evaluate the aging-related dielectric constant variation of the insulation. Experimental data from aged cable specimens are presented to demonstrate the operation of the sensor.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Progress toward absolute calibrations of DC x-ray sources from 1 keV to >30 keV for Z diagnostics applications

Numerous x-ray diagnostics at the Z facility, time-resolved and time-integrated, would benefit from a local calibrated x-ray source. For many years, Z has used low-power Manson x-ray sources to provide some characterization information for components of Z diagnostics below 30 keV. More recently, we have acquired TruFocus x-ray sources, which operate at voltages up to 100 kV depending on the anode material and model. These DC sources have demonstrated good stability and repeatability. Absolute calibrations of either sources or detectors usually involve another calibrated detector from another source, which has not been readily available locally. Therefore, we have adopted the strategy of characterizing a sensitive semiconductor diode detector by controlling or inferring the active volume. This characterized detector is then used to scale the Manson x-ray spectral shape as measured by an Amptek energy-resolving detector. Here, the result agrees well with the modeled source spectrum. We can apply this technique to the TruFocus as well.

Crystal spectroscopy↗
DOE OSTI2024

Slope Efficiency and Voltage Reduction at High Current Densities in AlInGaAs Diode Lasers

Here, the slope efficiency and drive voltage of broad area AlInGaAs laser diodes near 865 nm is observed to decrease significantly under quasi-CW pulsed operation at currents well above threshold, in a manner that cannot be explained by thermal effects or carrier leakage over heterojunction barriers. Simulations show that the slope efficiency reduction is explicable by increased free carrier absorption in the waveguide region. Empirical formulas are presented to represent these effects in a closed analytic form suitable for use in simulators for diode-pumped laser systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Landfill Emissions of Methane Inferred from Unmanned Aerial Vehicle and Mobile Ground Measurements

Municipal solid waste landfills are significant sources of atmospheric methane, the second most important greenhouse gas after carbon dioxide. Large emissions of methane from landfills contribute not only to global climate change, but also to local ozone formation due to the enhancement of radical chain lengths in atmospheric reactions of volatile organic compounds and nitrogen oxides. Several advanced techniques were deployed to measure methane emissions from two landfills in the Southeast Michigan ozone nonattainment area during the Michigan–Ontario Ozone Source Experiment (MOOSE). These techniques included mobile infrared cavity ringdown spectrometry, drone-mounted meteorological sensors and tunable diode laser spectrometry, estimation of total landfill emissions of methane based on flux plane measurements, and Gaussian plume inverse modeling of distributed methane emissions in the presence of complex landfill terrain. The total methane emissions measured at the two landfills were of the order of 500 kg/h, with an uncertainty of around 50%. The results indicate that both landfill active faces and leaking gas collection systems are important sources of methane emissions.

Olaguer, Eduardo P.↗
DOE OSTI2021

Magnetic skyrmion diode: Unidirectional skyrmion motion via symmetry breaking of potential energy barriers

In this work, we realize a magnetic skyrmion diode operated by a unidirectional skyrmion transport that flows in only one direction, which is highly significant for information processing in spintronic and nanoelectronic devices. We easily control the skyrmion transport by engineering asymmetric shapes of geometric structures. Here, we present a simple method to describe the underlying mechanism behind the unidirectional skyrmion transport by characterizing the topography of potential energy surfaces from a purely geometric perspective. Our approach enables a deeper physical insight into skyrmion transport manipulation and efficient design of skyrmion-based devices in geometric structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

A far‐red‐emitting (Gd,Y) 3 (Ga,Al) 5 O 12 :Mn 2+ ceramic phosphor with enhanced thermal stability for plant cultivation

Abstract As for plants, far‐red (FR) light with wavelength from 700 nm to 740 nm is critical for processes of photosynthesis and photomorphogenesis. Light‐controlled development depends on light to control cell differentiation, structural and functional changes, and finally converge into the formation of tissues and organs. Phosphor converted FR emission under LED excitation is a cost‐effective and high‐efficient way to provide artificial FR light source. With the aim to develop an efficient FR phosphor that can promote the plant growth, a series of gadolinium yttrium gallium garnet (GYGAG) transparent ceramic phosphors co‐doped with Mn 2+ and Si 4+ have been fabricated via chemical co‐precipitation method, followed sintered in O 2 and hot isostatic pressing in this work. Under UV excitation, the phosphor exhibited two bright and broadband red emission spectra due to Mn 2+ : 4 T 1 → 6 A 1 spin‐forbidden transition, and one of which located in the right FR region. And then, Ce 3+ ions were co‐doped as the activator to enhance the absorption at blue light region and the emission of Mn 2+ . It turns out that the emission band of GYGAG transparent ceramic phosphors matches well with the absorption band of phytochrome P FR , which means they are promising to be applied in plant cultivation light‐emitting diodes (LEDs) for modulating plant growth. Besides, the thermal stability of this material was investigated systematically, and an energy transferring model involves defects was also proposed to explain the phenomenon of abnormal temperature quenching.

Qiu, Xuting↗
DOE OSTI2023

Effects of fast and thermal neutron irradiation on Ga-polar and N-polar GaN diodes

Studies of the radiation tolerance and electrical behavior of gallium nitride (GaN) based devices are important for the next generation of high-power and high-voltage electronics that may be subjected to harsh environments such as nuclear reactor and fusion facilities, particle accelerators, and post-denotation environments. Here, in this work, we study the behavior of Ga-polar and N-polar GaN Schottky diodes before and after exposure to fast and thermal + fast neutrons. Temperature-dependent current–voltage (I–V) and circular transmission line method (CTLM) measurements were used to study the electrical characteristics. A strong reduction in reverse leakage current and an increase in differential resistance in forward bias were observed after neutron irradiation. Thermionic emission (TE), Frenkel–Poole (FP) emission, and Fowler–Nordheim (FN) tunneling models were used to explain the forward and reverse I–V characteristics pre- and post-irradiation. The study confirms that Ga-polar and N-polar GaN Schottky diodes exhibit different electrical responses to fast and thermal neutron irradiations. The reverse bias characteristics of N-polar diodes are less affected after the fast neutron irradiation compared to Ga-polar diodes, while in the forward bias region, the electrical behavior after fast and thermal neutron irradiations is similar in Ga-polar and N-polar diodes. The results indicate that the role of orientation should be considered in the design of GaN-based radiation-tolerant electronics.

42 ENGINEERING↗
DOE OSTI2022

Simulation of GaN-based light emitting diodes incorporating composition fluctuation effects

III-Nitride light emitting diodes (LEDs) are widely used in a range of high efficiency lighting and display applications, which has enabled significant energy savings in the last decade. Despite the wide application of GaN LEDs, transport mechanisms across InGaN/GaN heterostructures in these devices are not well explained. Fixed polarization sheet charges at InGaN/GaN interfaces lead to large interface dipole charges, which create large potential barriers to overcome. One-dimensional models for transport across such heterostructures predict turn-on voltages that are significantly higher than that found in real devices. As a result, conventional models for transport cannot predict the performance of new designs such as for longer wavelength LEDs or for multi-quantum well LEDs. In this work, we show that incorporating low and high indium compositions within quantum wells at the submicrometer scale can provide an accurate prediction of the characteristics of GaN/InGaN light emitting diodes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

End-Use Savings Shapes Upgrade Package Documentation: LED Lighting, HP-RTU and ASHP-Boiler

Building on the successfully completed effort to calibrate and validate the U.S. Department of Energy's ResStock and ComStock models over the past 3 years, the objective of this work is to produce national data sets that empower analysts working for federal, state, utility, city, and manufacturer stakeholders to answer a broad range of analysis questions. The goal of this work is to develop energy efficiency, electrification, and demand flexibility end-use load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) upgrade measures, or upgrades. "Measures" refers to energy efficiency variables that can be applied to buildings during modeling. An end-use savings shape is the difference in energy consumption between a baseline building and a building with an energy efficiency, electrification, or demand flexibility upgrade applied. It results in a time-series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step. ComStock is a highly granular, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The baseline model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology and results of the baseline model are discussed in the final technical report of the End-Use Load Profiles project. This documentation focuses on an upgrade package of three end-use savings shapes upgrades - Light Emitting Diode (LED) Lighting, Heat Pump Rooftop Unit (RTU) (HP-RTU), and Air-Source Heat Pump (ASHP) Boiler, which we will refer to collectively as the "Interior Lighting and Heat Pump" package. More details on the individual upgrades can be found on the ComStock Measures Documentation page. An upgrade package applies two or more EUSS upgrades to a single building model simulation. Since ComStock is a bottom-up physics-based model, an upgrade package will go beyond aggregating or summing the individual upgrade results and produce novel results by simulating interactions between the upgrades. For example, pairing an envelope upgrade with an electrification upgrade would likely result in higher savings results than the sum of these upgrades individually, and the size of the heating, ventilating, and air conditioning (HVAC) equipment may be reduced if the envelope upgrade reduces the loads significantly.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Realizing a topological diode effect on the surface of a topological Kondo insulator

Introducing the concept of topology into material science has sparked a revolution from classic electronic and optoelectronic devices to topological quantum devices. The latter has potential for transferring energy and information with unprecedented efficiency. Here, we demonstrate a topological diode effect on the surface of a three-dimensional material, SmB 6 , a candidate topological Kondo insulator. The diode effect is evidenced by pronounced rectification and photogalvanic effects under electromagnetic modulation and radiation at radio frequency. Our experimental results and modeling suggest that these prominent effects are intimately tied to the spatially inhomogeneous formation of topological surface states (TSS) at the intermediate temperature. This work provides a manner of breaking the mirror symmetry (in addition to the inversion symmetry), resulting in the formation of pn-junctions between puddles of metallic TSS. Further, this effect paves the way for efficient current rectifiers or energy-harvesting devices working down to radio frequency range at low temperature, which could be extended to high temperatures using other topological insulators with large bulk gap.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, G. C.↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, Chris↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, Chris↗