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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Machine Learning-Driven Reliability Estimation of PV Inverters Considering Alert-Ambient Variability

Weather-induced spatio-temporal degradation limits outdoor PV inverter lifetime and reliability, necessitating advanced data analysis. This study employs a top-down, data-driven approach utilizing multiple machine learning (ML) algorithms to estimate inverter reliability in a 1.4 MW PV power plant, considering factors such as irradiance, humidity, temperature, time of day, and weather conditions. An extensive alert dataset from 17 identical inverters, including alert types, propagation, and frequency, reveals significant correlations with environmental factors and inverter output power, enabling the construction of a performance reliability model. Dual-stage supervised-ML models are evaluated for accuracy, with the ‘classification-regression’ model by an artificial neural network (ANN) tested on the averaged “Alert-Ambient” dataset, which is outperformed by ‘clustering-regression’ models using random forest (RF) and K-Nearest Neighbors (KNN) on individual inverter datasets. K-means clustering applies principal component analysis to reduce dimensions, achieving improved accuracy beyond the 80% achieved by ANN on the averaged dataset. Second-stage regression estimates inverter reliability with a mean square error of 0.0195 on the averaged dataset and as low as 0.002 on individual inverter datasets using RF. Furthermore, these findings highlight the method's suitability for estimating PV inverter output reliability under ambient conditions, essential for digital twin development and related applications.

14 SOLAR ENERGY↗
DOE OSTI2023

A New Method for the Evaluation of Majority and Minority Carrier Contact Resistivity of Polysilicon on Oxide Contacts

In this contribution we present a novel technique for characterizing the majority and minority carrier contact resistivity in polysilicon on oxide passivating contacts. Traditionally, contact resistivity is measured through the Transfer Length Method (TLM). This method presents difficulties when measuring the minority carrier contact due to the presence of a blocking diode which prevents current flow between the pads. Our novel method is performed by creating a unipolar device which has the same contact on both sides (either symmetric n-type or symmetric p-type) and metalizing the device with a grid on one side, and a full metal contact on the back (the same pattern that will be used in a final cell). We then measure the resistance across the device at increasing illumination. Since the resistivity of the wafer is a function of carrier density, when increasing illumination, the wafer resistivity decreases. We can then fit modeling equations to the measured resistivity and extrapolate the fit to infinite illumination where only the contact resistivity is measured to accurately measure both the minority and majority carrier contact resistivity.

current measurement↗
DOE OSTI2020

Electron-electron interactions in low-dimensional Si:P delta layers

Scientists have long studied the physics of highly disordered conducting systems, seeking to understand the multitude of quantum phenomena that govern how electrons move through material systems. Recently, research into silicon-based quantum computing has made disordered conducting systems, such as Si:P monolayers embedded in isotopically pure Si, technically relevant. Consequently, applying and advancing the theoretical frameworks developed to describe electron behavior in disordered systems is a necessary objective in this field of research. This study investigates key components of dopant-based Si quantum computing devices: embedded regions of highly doped delta layers (δ layers). We examine the transport behavior and the electron-electron interaction (EEI) physics in embedded Si:P δ layers by means of self-consistent magnetotransport measurements. Parameters associated with the electronic transport offer a meaningful quantitative characterization of δ-layer quality and dopant diffusion. In addition, by examining EEI behaviors in a set of samples with embedded Si:P δ layers produced with different PH3 exposure procedures prior to Si encapsulation, we show how details of material synthesis affect the dimensionality of charge carrier interactions in embedded Si:P δ layers. Furthermore, the relationship between δ-layer confinement and EEI screening lengths is established here. This understanding will help validate important models used for device simulation and design and lead to improvements in the control of electrostatic gating of and tunneling transport through Si:P single atom transistors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Multi-Electron Transfer at H-Terminated p-Si Electrolyte Interfaces: Large Photovoltages under Inversion Conditions

Here, photovoltages for hydrogen terminated p-Si(111) in an acetonitrile electrolyte were quantified with methyl viologen [1,1'-(CH 3 ) 2 -4,4'-bipyridinium](PF 6 ) 2 , abbreviated MV 2+ , and [Ru(bpy) 3 ](PF 6 ) 2 , where bpy is 2,2'-bipyridine, that respectively undergo two and three one-electron transfer reductions. The reduction potentials, E°, of the two MV 2+ reductions occurred at energies within the forbidden bandgap, while the three [Ru(bpy) 3 ] 2+ reductions occurred within the continuum of conduction band states. Bandgap illumination resulted in reduction that were more positive than that measured with a degenerately doped n + -Si demonstrative of a photovoltage, Vph, that increased in the order: MV 2+/+ (260 mV) < MV +/0 (400 mV) < Ru 2+/+ (530 mV) ~ Ru +/0 (540 mV) ~ Ru 0/– (550 mV). Pulsed 532 nm excitation generated electron-hole pairs whose dynamics were nearly constant under depletion conditions and increased markedly as the potential was raised or lowered. A long wavelength absorption feature assigned to conduction band electrons provided additional evidence for the presence of an inversion layer. Collectively, the data reveal that the most optimal photovoltage, as well at the longest electron-hole pair lifetime and the highest surface electron concentration, occur when E° lies energetically within the unfilled conduction band states where an inversion layer is present. The bell-shaped dependence for electron-hole pair recombination with the surface potential was predicted by the time-honored SRH model providing a clear indication that this interface provides access to all four bias conditions, i.e., accumulation, flat band, depletion, and inversion. The implications of these findings for photocatalysis applications and solar energy conversion are discussed.

14 SOLAR ENERGY↗
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 OSTI2020

Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition

Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.

Hanson, Joshua↗
DOE OSTI2022

Carrier capture and emission by substitutional carbon impurities in GaN vertical diodes

A model was developed for the operation of a GaN pn junction vertical diode which includes rate equations for carrier capture and thermally activated emission by substitutional carbon impurities and carrier generation by ionizing radiation. The model was used to simulate the effect of ionizing radiation on the charge state of carbon. These simulations predict that with no applied bias, carbon is negatively charged in the n-doped layer, thereby compensating n-doping as experimentally observed in diodes grown by metal-organic chemical vapor deposition. With reverse bias, carbon remains negative in the depletion region, i.e., compensation persists in the absence of ionization but is neutralized by exposure to ionizing radiation. This increases charge density in the depletion region, decreases the depletion width, and increases the capacitance. The predicted increase in capacitance was experimentally observed using a pulsed 70 keV electron beam as the source of ionization. In additional confirming experiments, the carbon charge-state conversion was accomplished by photoionization using sub-bandgap light or by the capture of holes under forward bias.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A Gauss’s law analysis of redox active adsorbates on semiconductor electrodes: The charging and faradaic currents are not independent

A detailed framework for modeling and interpreting the data in totality from a cyclic voltammetric measurement of adsorbed redox monolayers on semiconductor electrodes has been developed. A three-layer model consisting of the semiconductor space-charge layer, a surface layer, and an electrolyte layer is presented that articulates the interplay between electrostatic, thermodynamic, and kinetic factors in the electrochemistry of a redox adsorbate on a semiconductor. Expressions are derived that describe the charging and faradaic current densities individually, and an algorithm is demonstrated that allows for the calculation of the total current density in a cyclic voltammetry measurement as a function of changes in the physical properties of the system (e.g., surface recombination, dielectric property of the surface layer, and electrolyte concentration). The most profound point from this analysis is that the faradaic and charging current densities can be coupled. That is, the common assumption that these contributions to the total current are always independent is not accurate. Their interrelation can influence the interpretation of the charge-transfer kinetics under certain experimental conditions. More generally, this work not only fills a long-standing knowledge gap in electrochemistry but also aids practitioners advancing energy conversion/storage strategies based on redox adsorbates on semiconductor electrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A 3D simulation comparison of carrier transport in green and blue c-plane multi-quantum well nitride light emitting diodes

Until recently, the electrical efficiency of green nitride light-emitting diodes (LEDs) was considerably lower than that of blue LEDs. This is particularly surprising as one would expect a reduced forward voltage with increasing emission wavelength. In this paper, we theoretically investigated the impact of the number of quantum wells on the forward voltage of III-nitride LEDs with x = 0.15 (blue) and x = 0.24 (green) In x Ga1–xN QWs. The simulated dependence of current density (J) on applied diode bias (V) shows a significant increase of 1.9 V in the forward voltage between one and five quantum well (QW) c-plane green LED structures. Artificially turning off the polarization fields in the simulation does not entirely suppress this effect. Due to the large band offsets in the green LED multiple QW stack, simulations indicate a sequential band filling of the QW sequence. Furthermore, this mechanism should not be limited to c-plane LEDs and could also be present in nonpolar or semipolar devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Identification of localized radiation damage in power MOSFETs using EBIC imaging

The rapidly increasing use of electronics in high-radiation environments and the continued evolution in transistor architectures and materials demand improved methods to characterize the potential damaging effects of radiation on device performance. Here, electron-beam-induced current is used to map hot-carrier transport in model metal-oxide semiconductor field-effect transistors irradiated with a 300 KeV focused He + beam as a localized line spanning across the gate and bulk Si. By correlating the damage to the electronic properties and combining these results with simulations, the contribution of spatially localized radiation damage on the device characteristics is obtained. Furthermore, this identified damage, caused by the He + beam, is attributed to localized interfacial P b centers and delocalized positive fixed-charges, as surmised from simulations. Comprehension of the long-term interaction and mobility of radiation-induced damage are key for future design of rad-hard devices.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Spatial BCS-BEC crossover in superconducting $\textit{p–n}$ junctions

Here, we present a theory of superconducting $\textit{p–n}$ junctions. To this end, we consider a two band model of doped bulk semiconductors with attractive interactions between the charge carriers and derive the superconducting order parameter, the quasiparticle density of states, and the chemical potential as a function of the semiconductor gap $Δ_0$ and the doping level ε. We verify previous results for the quantum phase diagram for a system with constant density of states in the conduction and valence band, which show BCS-superconductor to Bose-Einstein-condensation (BEC) and BEC-to-insulator transitions as a function of doping level and the size of the band gap. Then, we extend this formalism to a density of states which is more realistic for 3D systems and derive the corresponding quantum phase diagram, where we find that a BEC phase can only exist for small band gaps $Δ_0 < Δ ^{\ast}_0$. For larger band gaps, we find rather a direct transition from an insulator to a BCS phase. Next, we apply this theory to study the properties of superconducting $\textit{p–n}$ junctions. We derive the spatial variation of the superconducting order parameter along the $\textit{p–n}$ junction. As the potential difference across the junction leads to energy band bending, we find a spatial crossover between a BCS and BEC condensate, as the density of charge carriers changes across the $\textit{p–n}$ junction. For the two-dimensional system, we find two possible regimes, when the bulk is in a BCS phase, a BCS-BEC-BCS junction with a single BEC layer in the space charge region, and a BCS-BEC-I-BEC-BCS junction with two layers of BEC condensates separated by an insulating layer. In three dimensions we find that there can also be a conventional BCS-I-BCS junction for semiconductors with band gaps exceeding $Δ^{\ast}_0$. Thus, we find that there can be BEC layers in the well controlled setting of doped semiconductors, where the doping level can be varied to change and control the thickness of BEC and insulator layers, making Bose-Einstein condensates thereby possibly accessible to experimental transport and optical studies in solid-state materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

New Radiation Tolerant LGAD for High Energy Physics

Low Gain Avalanche Detectors (LGADS) have recently been studied for applications in high energy physics. However, radiation hardness remains a problem. Here, we propose new LGAD process flow that allows for the creation of a very steep born profile in the multiapplication region, reducing the fractional acceptor removal and resulting performance degradation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

MLSPICE: Machine Learning based SPICE Modeling Platform for Power Magnetics

Electrical power converters are critical to a wide range of applications ranging from renewable integration to transportation electrification, and can be a key factor determining the size, weight, and efficiency of energy conversion systems. Magnetic components are typically the largest and least efficient components in power electronics. While there have been major strides in the modeling and analysis of power semiconductor devices and circuit simulations, the necessary advances in the design of power magnetics have lagged. In this project, we have transformed the modeling and design of power magnetics with machine learning enabled methods and catalyze simultaneous disruptive improvements for ML-based power electronics design tools. A fully automated open-source machine learning based magnetics modeling platform – the MagNet project - with innovations in full stack have been developed to greatly accelerate the design process and provide new insights to magnetic material and geometry design. The ARPA-E funded MagNet platform contains three major building blocks: 1) a ML-Integrated Data Acquisition System (MIDAS): a highly automated data acquisition testbed which is capable of measuring a large number of magnetic cores with a wide range of electrical circuit excitations; 2) a ML-integrated Core Loss Model (MICLM): a machine-learning trained modeling method for modeling the core loss and saturation effects of magnetic materials for arbitrary excitation waveforms; 3) ML-guided Magnetics SPICE Simulation Tool (PMSPICE): a fully integrated CAD tool which can simulate the magnetics in SPICE. It can help the designers to quickly model the linear and non-linear characteristics of magnetic components and evaluate their behavior in SPICE simulations. The developed MagNet system has fully demonstrated the proposed performance target and has been open sourced to the entire power electronics community to advance the modeling and design of power magnetics from many different angles.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Accelerated Scaling to Rapid Open-Air Fabrication of Durable Perovskite Solar Modules

The goals of this SETO project (DE-EE0008559, Accelerated Scaling to Rapid Open-Air Fabrication of Durable Perovskite Solar modules) are to address the principal challenges towards the successful commercialization of perovskite solar modules utilizing scalable, high-throughput open-air spray deposition. The successful outcome of the project will provide the foundation of an all open-air spray deposited perovskite solar module with hole transport layer (HTL), perovskite, electron transport layer (ETL), and barrier layer development while establishing a fundamental understanding of perovskite device behavior under accelerated aging conditions. Through this program, we have made significant progress towards a commercializable pathway for perovskites. (1) We’ve demonstrated the successful open-air deposition of perovskite and transport layer materials. These deposition methods were chosen for their inherent scalability, and open-air processing enables a significant reduction in processing costs. These methods are also compatible with high throughputs, demonstrating the fastest perovskite film deposition at these performance levels. (2) Development of a unique all-fiber laser scribing procedure provides a high-performance, low-cost method for further improvements in scalability. (3) Our group has also placed a unique emphasis on device stability. The development of testing standards for perovskite modules is required to thoroughly evaluate potential candidates for commercialization, and we’ve taken inspiration from current industry standards to provide an honest insight into the performance and reliability of our devices. (4) An extensive cost model detailing the specific contributions of each device layer and production component provides the most thorough evaluation of any perovskite technology against conventional silicon and compound semiconductor solar devices. The cost model is a critical advancement that will provide the foundation for evaluating the levelized cost of energy (LCOE) of this technology.

14 SOLAR ENERGY↗
DOE OSTI2023

Physically realistic, parametric model for excitonic critical point parabolic band oscillators

Critical point parabolic band (CPPB) oscillators are often useful to model the optical response of semiconductor materials, such as hybrid organic–inorganic lead halide-based perovskites, to incident photons in the form of the complex dielectric function (ε=ε1+iε2) spectra. Some models of ε using CPPB oscillators are not guaranteed Kramers–Kronig (KK) consistent (and therefore not physically realistic), may have excess or arbitrary parameter values, or may require prohibitively long computational time when used to fit ellipsometric spectra. For excitonic CPPBs, commonly used to describe the optical response of hybrid organic–inorganic lead halide-based perovskite materials, a physically realistic, parametric model of ε is developed from the KK relationship between ε1 and ε2 for a number of CPPB oscillators with an Urbach tail below the lowest direct transition. This parametric model is shown to produce the same line shape reported from previous works accurately and more quickly than other available KK-consistent CPPB models.

Physics↗