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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electron mobility of SnO 2 from first principles

The transparent conducting oxide SnO 2 is a wide bandgap semiconductor that is easily n-type doped and widely used in various electronic and optoelectronic applications. Experimental reports of the electron mobility of this material vary widely depending on the growth conditions and doping concentrations. In this work, we calculate the electron mobility of SnO 2 from first principles to examine the temperature and doping concentration dependence and to elucidate the scattering mechanisms that limit transport. We include both electron–phonon scattering and electron-ionized impurity scattering to accurately model scattering in a doped semiconductor. Furthermore, we find a strongly anisotropic mobility that favors transport in the direction parallel to the c-axis. At room temperature and intrinsic carrier concentrations, the low-energy polar-optical phonon modes dominate scattering, while ionized-impurity scattering dominates above 10 18 cm −3 .

36 MATERIALS SCIENCE↗
DOE OSTI2023

Theory and Simulation of Metal–Insulator–Semiconductor (MIS) Photoelectrodes

A metal–insulator–semiconductor (MIS) structure is an attractive photoelectrode-catalyst architecture for promoting photoelectrochemical reactions, such as the formation of H 2 by proton reduction. The metal catalyzes the generation of H 2 using electrons generated by photon absorption and charge separation in the semiconductor. The insulator layer between the metal and the semiconductor protects the latter element from photo-corrosion and, also, significantly impacts the photovoltage at the metal surface. Understanding how the insulator layer determines the photovoltage and what properties lead to high photovoltages is critical to the development of MIS structures for solar-to-chemical energy conversion. Herein, we present a continuum model for charge-carrier transport from the semiconductor to the metal with an emphasis on mechanisms of charge transport across the insulator. The polarization curves and photovoltages predicted by this model for a Pt/HfO 2 /p-Si MIS structure at different HfO 2 thicknesses agree well with experimentally measured data. The simulations reveal how insulator properties (i.e., thickness and band structure) affect band bending near the semiconductor/insulator interface and how tuning them can lead to operation closer to the maximally attainable photovoltage, the flat-band potential. This phenomenon is understood by considering the change in tunneling resistance with insulator properties. The model shows that the best MIS performance is attained with highly symmetric semiconductor/insulator band offsets (e.g., BeO, MgO, SiO 2 , HfO 2 , or ZrO 2 deposited on Si) and a low to moderate insulator thickness (e.g., between 0.8 and 1.5 nm). Beyond 1.5 nm, the density of filled interfacial trap sites is high and significantly limits the photovoltage and the solar-to-chemical conversion rate. These conclusions are true for photocathodes and photoanodes. This understanding provides critical insight into the phenomena enhancing and limiting photoelectrode performance and how this phenomenon is influenced by insulator properties. The study gives guidance toward the development of next-generation insulators for MIS structures that achieve high performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2006

Metal-Ferroelectric-Semiconductor Field-Effect Transistor NAND Gate Switching Time Analysis

Previous research investigated the modeling of a N Wga te constructed of Metal-Ferroelectric- Semiconductor Field-Effect Transistors (MFSFETs) to obtain voltage transfer curves. The NAND gate was modeled using n-channel MFSFETs with positive polarization for the standard CMOS n-channel transistors and n-channel MFSFETs with negative polarization for the standard CMOS p-channel transistors. This paper investigates the MFSFET NAND gate switching time propagation delay, which is one of the other important parameters required to characterize the performance of a logic gate. Initially, the switching time of an inverter circuit was analyzed. The low-to-high and high-to-low propagation time delays were calculated. During the low-to-high transition, the negatively polarized transistor pulls up the output voltage, and during the high-to-low transition, the positively polarized transistor pulls down the output voltage. The MFSFETs were simulated by using a previously developed model which utilized a partitioned ferroelectric layer. Then the switching time of a 2-input NAND gate was analyzed similarly to the inverter gate. Extension of this technique to more complicated logic gates using MFSFETs will be studied.

Phillips, Thomas A.↗
NASA NTRS2008

SiC JFET Transistor Circuit Model for Extreme Temperature Range

A technique for simulating extreme-temperature operation of integrated circuits that incorporate silicon carbide (SiC) junction field-effect transistors (JFETs) has been developed. The technique involves modification of NGSPICE, which is an open-source version of the popular Simulation Program with Integrated Circuit Emphasis (SPICE) general-purpose analog-integrated-circuit-simulating software. NGSPICE in its unmodified form is used for simulating and designing circuits made from silicon-based transistors that operate at or near room temperature. Two rapid modifications of NGSPICE source code enable SiC JFETs to be simulated to 500 C using the well-known Level 1 model for silicon metal oxide semiconductor field-effect transistors (MOSFETs). First, the default value of the MOSFET surface potential must be changed. In the unmodified source code, this parameter has a value of 0.6, which corresponds to slightly more than half the bandgap of silicon. In NGSPICE modified to simulate SiC JFETs, this parameter is changed to a value of 1.6, corresponding to slightly more than half the bandgap of SiC. The second modification consists of changing the temperature dependence of MOSFET transconductance and saturation parameters. The unmodified NGSPICE source code implements a T(sup -1.5) temperature dependence for these parameters. In order to mimic the temperature behavior of experimental SiC JFETs, a T(sup -1.3) temperature dependence must be implemented in the NGSPICE source code. Following these two simple modifications, the Level 1 MOSFET model of the NGSPICE circuit simulation program reasonably approximates the measured high-temperature behavior of experimental SiC JFETs properly operated with zero or reverse bias applied to the gate terminal. Modification of additional silicon parameters in the NGSPICE source code was not necessary to model experimental SiC JFET current-voltage performance across the entire temperature range from 25 to 500 C.

Neudeck, Philip G.↗
NASA NTRS2001

A Hydrodynamic Theory for Spatially Inhomogeneous Semiconductor Lasers: Numerical Results - 2

We present numerical results of the diffusion coefficients (DCs) in the coupled diffusion model derived in the preceding paper for a semiconductor quantum well. These include self and mutual DCs in the general two-component case, as well as density- and temperature-related DCs under the single-component approximation. The results are analyzed from the viewpoint of free Fermi gas theory with many-body effects incorporated. We discuss in detail the dependence of these DCs on densities and temperatures in order to identify different roles played by the free carrier contributions including carrier statistics and carrier-LO phonon scattering, and many-body corrections including bandgap renormalization and electron-hole (e-h) scattering. In the general two-component case, it is found that the self- and mutual- diffusion coefficients are determined mainly by the free carrier contributions, but with significant many-body corrections near the critical density. Carrier-LO phonon scattering is dominant at low density, but e-h scattering becomes important in determining their density dependence above the critical electron density. In the single-component case, it is found that many-body effects suppress the density coefficients but enhance the temperature coefficients. The modification is of the order of 10% and reaches a maximum of over 20% for the density coefficients. Overall, temperature elevation enhances the diffusive capability or DCs of carriers linearly, and such an enhancement grows with density. Finally, the complete dataset of various DCs as functions of carrier densities and temperatures provides necessary ingredients for future applications of the model to various spatially inhomogeneous optoelectronic devices.

Li, Jianzhong↗
DOE OSTI2021

Investigation of GaAs surface treatments for ZnSe growth by molecular beam epitaxy without a buffer layer

Atomically clean and smooth surfaces are critical prerequisite for the epitaxial regrowth of dissimilar semiconductors. Using ZnSe/GaAs as a model system, epitaxial regrowth without a buffer layer after thermal cleaning with various As-fluxes, atomic Ga flux, and atomic hydrogen treatments to the GaAs substrates and the surfaces were investigated in this work via in-situ Auger electron spectroscopy (AES). The ZnSe epilayers grown on the pre-treated GaAs surfaces without a buffer layer were characterized by X-ray diffraction (XRD), photoluminescence (PL) and atomic force microscopy (AFM) to evaluate the effectiveness of the surface treatment methods. It was found that a high quality ZnSe layer can be achieved by atomic hydrogen surface treatment at 300°C without requiring GaAs buffer layer growth, which reveals a path for epitaxy growth avoiding high temperature treatments.

42 ENGINEERING↗
DOE OSTI2021

Impact of Photon Recycling, Grain Boundaries, and Nonlinear Recombination on Energy Transport in Semiconductors

Energy carrier transport and recombination in semiconductors can be directly monitored with optical microscopy, revealing key insights into fundamental photophysics and informs efficient optoelectronic device design. Oftentimes, energy transport is measured by monitoring a time-resolved expanding carrier profile after optical excitation under a focused laser beam. Although this approach has gained widespread adoption, the presence of competing dynamic processes, such as diffusion and photon recycling, has made it difficult to accurately extract and understand important semiconductor properties. Here, we develop and apply a new framework for modeling energy transport in both excitonic and free carrier semiconductors. Here, we demonstrate that processes such as nonlinear recombination and photon recycling can have a significant impact on the apparent energy carrier profiles, especially for excitonic materials with short radiative lifetimes. Additionally, we find that film microstructure can lead to unique transport profiles that strongly depends on material boundary behavior and the difference between feature size and diffusion length. Here, these findings provide a deeper understanding of energy transport in semiconducting materials and provide new strategies for the design and optimization of electronic and optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2003

Basic Equations for the Modeling of Gallium Nitride (gan) High Electron Mobility Transistors (hemts)

Gallium nitride (GaN) is a most promising wide band-gap semiconductor for use in high-power microwave devices. It has functioned at 320 C, and higher values are well within theoretical limits. By combining four devices, 20 W has been developed at X-band. GaN High Electron Mobility Transistors (HEMTs) are unique in that the two-dimensional electron gas (2DEG) is supported not by intentional doping, but instead by polarization charge developed at the interface between the bulk GaN region and the AlGaN epitaxial layer. The polarization charge is composed of two parts: spontaneous and piezoelectric. This behavior is unlike other semiconductors, and for that reason, no commercially available modeling software exists. The theme of this document is to develop a self-consistent approach to developing the pertinent equations to be solved. A Space Act Agreement, "Effects in AlGaN/GaN HEMT Semiconductors" with Silvaco Data Systems to implement this approach into their existing software for III-V semiconductors, is in place (summer of 2002).

Freeman, Jon C.↗
DOE OSTI2025

Applications of Federated Learning in Semiconductor Manufacturing [Poster]

As semiconductor manufacturers explore advanced data analytics and modeling techniques and data hungry machine learning models increase in popularity due to their accuracy in solving generalized problems and ability to learn complex relationships, federated learning emerges as a privacy preserving machine learning technique for preserving data privacy and ensuring intellectual property protection. Federated Learning is a machine learning technique focused on training models using distributed data that never needs to be centrally stored, allowing the use of advanced machine learning techniques without compromising data privacy, and in the semiconductor manufacturing industry advanced machine learning techniques can reduce cost and time, but maintaining data privacy is essential to maintaining a competitive advantage. This paper systematically reviews existing literature on applications of federated learning in the semiconductor manufacturing industry with a focus on identifying common themes, algorithms, and gaps within the literature to drive future research directions. The findings reveal five key themes, including improvements in quality assurance, virtual models, privacy preservation, reliable data practices, and emerging trends and developments. By identifying key themes in literature on federated learning and semiconductor manufacturing and analyzing gaps and discussed methodologies, this study highlights several potential future research directions to expand the application of federated learning techniques in the semiconductor manufacturing domain.

42 ENGINEERING↗
DOE OSTI2025

Photon counting with intensified charge coupled device (ICCD) – I. In-depth detector characterization

While the adsorption properties of transition metal catalysts have been widely studied, leading to the discovery of various scaling relations, descriptors of catalytic activity, and well-established computational models, a similar understanding of semiconductor catalysts has not yet been achieved. In this work, we present a high-throughput density functional theory investigation into the adsorption properties of 5 oxides of interest to the photocatalytic CO 2 reduction reaction: TiO 2 (rutile and anatase), SrTiO 3 , NaTaO 3 , and CeO 2 . Using a systematic approach, we exhaustively identify unique surfaces and construct adsorption structures to undergo geometry optimizations. We then perform a data-driven analysis, which reveals the presence of weak adsorption energy scaling relations, the propensity of adsorbates of interest to interact with oxygen surface sites, and the importance of slab deformation upon adsorption. Our findings are presented in the context of experimental observations and in comparison to previously studied classes of catalysts, such as pure metals and tellurium-containing semiconductors, and reinforce the need for a comprehensive approach to the study of site-specific surface phenomena on semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Systematic computational study of oxide adsorption properties for applications in photocatalytic CO 2 reduction

While the adsorption properties of transition metal catalysts have been widely studied, leading to the discovery of various scaling relations, descriptors of catalytic activity, and well-established computational models, a similar understanding of semiconductor catalysts has not yet been achieved. In this work, we present a high-throughput density functional theory investigation into the adsorption properties of 5 oxides of interest to the photocatalytic CO 2 reduction reaction: TiO 2 (rutile and anatase), SrTiO 3 , NaTaO 3 , and CeO 2 . Using a systematic approach, we exhaustively identify unique surfaces and construct adsorption structures to undergo geometry optimizations. We then perform a data-driven analysis, which reveals the presence of weak adsorption energy scaling relations, the propensity of adsorbates of interest to interact with oxygen surface sites, and the importance of slab deformation upon adsorption. Our findings are presented in the context of experimental observations and in comparison to previously studied classes of catalysts, such as pure metals and tellurium-containing semiconductors, and reinforce the need for a comprehensive approach to the study of site-specific surface phenomena on semiconductors.

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

Localized Excitons in NbSe 2 -MoSe 2 Heterostructures

Neutral and charged excitons (trions) in atomically thin materials offer important capabilities for photonics, from ultrafast photodetectors to highly efficient light-emitting diodes and lasers. Recent studies of van der Waals (vdW) heterostructures comprised of dissimilar monolayer materials have uncovered a wealth of optical phenomena that are predominantly governed by interlayer interactions. Here, we examine the optical properties in NbSe 2 -MoSe 2 vdW hetero- structures, which provide an important model system to study metal–semiconductor interfaces, a common element in optoelectronics. Through low-temperature photoluminescence (PL) microscopy, we discover a sharp emission feature, L1, that is localized at the NbSe 2 -capped regions of MoSe 2 . L1 is observed at energies below the commonly studied MoSe 2 excitons and trions and exhibits temperature- and power-dependent PL consistent with exciton localization in a confining potential. This PL feature is robust, observed in a variety of samples fabricated with different stacking geometries and cleaning procedures. Using first-principles calculations, we reveal that the confinement potential required for exciton localization naturally arises from the in-plane band bending due to the changes in the electron affinity between pristine MoSe 2 and NbSe 2 -MoSe 2 heterostructure. Here, we discuss the implications of our studies for atomically thin optoelectronics devices with atomically sharp interfaces and tunable electronic structures.

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

Conjugated polyelectrolyte-based ternary exciton funnels via liposome scaffolds

There is great interest in developing inexpensive, molecular light-harvesting systems capable of efficiently converting photon energy to chemical potential energy. It is highly desirable to do so using self-assembly and in a manner that supports environmentally benign processing. A critical consideration in any such assembly is the ability to absorb a substantial fraction of the solar emission spectrum and to be able to efficiently move excited states through the space to a functional interface. We have previously shown that aqueous inter-conjugated polyelectrolyte (CPE) complexes can act as ultrafast and efficient energy-transfer antennae. Here we demonstrate formation of a hierarchically assembled, aqueous system based on an inter-CPE exciton donor/acceptor network and a lipid vesicle scaffold. Using a model small-molecule organic semiconductor embedded in the vesicle membrane, we form a ternary exciton funnel that is oriented towards the membrane interior. We show that, although energy transfer is efficient, the assembly morphology depends sensitively on preparation conditions and relative ionic stoichiometry. We propose several approaches towards stabilizing such aqueous assemblies. Furthermore, this work highlights a path to formation of an aqueous, panchromatic light-harvesting system, whose functional complexity can be systematically increased with modularity.

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

Millimeter-Wave Imaging Technology Development for Real-Time 2D and 3D Fusion Plasma Diagnostics

Including a one year No-Cost Extension, The University of California, Davis has been funded since 2020 to advance innovative millimeter-wave diagnostics for fusion plasma research. This work includes: (1) Developing and applying cutting-edge System-on-Chip millimeter wave Integrated Circuit (IC) technology for Electron Cyclotron Emission Imaging (ECEI) and Microwave Imaging Reflectometry (MIR) on the DIII-D tokamak and the NSTX-U spherical tokamak. (2) Development of radiation-hardened millimeter-wave chip for diagnostics in harsh environments, utilizing wide bandgap Gallium Nitride (GaN) semiconductors. (3) Integrating forward-modeling synthetic diagnostics to enable advanced, real-time plasma prediction and feedback control. Originally planned as a three-year program (2020–2023), the project was granted a one-year no-cost extension, extending its duration through the end of 2024.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Machine-learned impurity level prediction for semiconductors: the example of Cd-based chalcogenides

The ability to predict the likelihood of impurity incorporation and their electronic energy levels in semiconductors is crucial for controlling its conductivity, and thus the semiconductor's performance in solar cells, photodiodes, and optoelectronics. The difficulty and expense of experimental and computational determination of impurity levels makes a data-driven machine learning approach appropriate. In this work, we show that a density functional theory-generated dataset of impurities in Cd-based chalcogenides CdTe, CdSe, and CdS can lead to accurate and generalizable predictive models of defect properties. By converting any semiconductor + impurity system into a set of numerical descriptors, regression models are developed for the impurity formation enthalpy and charge transition levels. These regression models can subsequently predict impurity properties in mixed anion CdX compounds (where X is a combination of Te, Se and S) fairly accurately, proving that although trained only on the end points, they are applicable to intermediate compositions. We make machine-learned predictions of the Fermi-level-dependent formation energies of hundreds of possible impurities in 5 chalcogenide compounds, and we suggest a list of impurities which can shift the equilibrium Fermi level in the semiconductor as determined by the dominant intrinsic defects. Machine learning predictions for the dominating impurities compare well with DFT predictions, revealing the power of machine-learned models in the quick screening of impurities likely to affect the optoelectronic behavior of semiconductors.

36 MATERIALS SCIENCE↗
NASA NTRS1986

Exact solution of three-dimensional transport problems using one-dimensional models

Several parameters of certain three-dimensional semiconductor devices including diodes, transistors, and solar cells can be determined without solving the actual boundary-value problem. The recombination current, transit time, and open-circuit voltage of planar diodes are emphasized here. The resulting analytical expressions enable determination of the surface recombination velocity of shallow planar diodes. The method involves introducing corresponding one-dimensional models having the same values of these parameters.

Misiakos, K.↗