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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Giant Apparent Optical Circular Dichroism in Thin Films of Bismuth-Based Hybrid Organic-Inorganic Metal Halide Semiconductor Through Preferred Orientation

Introducing chirality into organic/inorganic hybrid materials can impart chiroptical properties such as circular dichroism. The ability to tune chiroptical properties in self-assembled materials can have important implications for spintronic and optoelectronic applications. Here, a chiral organic cation, (R/S)-4-methoxy-a-methylbenzylammonium, is incorporated to synthesize the bismuth-based hybrid organic-inorganic metal halide semiconductor, (R/S-MeOMePMA)BiI4. Thin films of this Bi-based compound demonstrate large chiroptical responses, with circular dichroism anisotropy (gCD) values up to ˜0.1, close to the highest value observed in another chiral metal-halide semiconductor, (R-MBA2CuCl4). Detailed investigation reveals that this large gCD in (R/S-MeOMePMA)BiI4 is caused by the apparent CD effect. Careful selection of deposition conditions and the concomitant thin-film orientation enables the control of gCD, with maximum value observed when its thin film has a well-crystallized preferred (001) orientation parallel to the substrate. The results support a growing body of evidence that low symmetry plays an important role in achieving unusually large gCD in these chiral metal-halide materials and provides design rules for achieving large chiroptical response via morphology control.

chiroptic response↗
DOE OSTI2025

(NH 3 (CH 2 ) 7 NH 3 ) 2 Sn 3 I 10 , a Vacancy-Ordered Three-Dimensional Tin(II) Perovskite-Derived Semiconductor

Ordering vacancies in hybrid Sn(II) halide semiconductors provides a strategy for preventing uncontrolled oxidation and formation of mobile holes. In this study, we report the structure and optical and electronic properties of (NH 3 (CH 2 ) 7 NH 3 ) 2 Sn 3 I 10 , a vacancy-ordered perovskite derivative with three-dimensional inorganic connectivity. The crystal structure resembles that of a Dion–Jacobson layered perovskite derivative, but with [SnI 5 ] square pyramids bridging the layers. UV–vis diffuse reflectance spectroscopy reveals a sharp onset of light absorption at 1.86(1) eV with the photoluminescence emission maximum at 1.90(1) eV. However, the maximum excitation occurs from 3.42 to 3.81 eV (325 to 370 nm), revealing a significant Stokes shift of 1.3 eV. The electronic properties determined from dark and time-resolved microwave conductivity measurements reveal a minimum carrier mobility of 4.3 × 10 –2 cm 2 V –1 s –1 and a maximum carrier density of 5.96 × 10 16 cm –3 , a uniquely low value for a hybrid Sn(II) halide semiconductor. The transport behavior in combination with first-principles calculations of the electronic band structure and dielectric permittivity suggest polaron-mediated electronic transport, yet the photogenerated carriers have a fast and fluence-dependent nonradiative recombination rate, suggestive of localized “defect-like” states at the band edge. The observed photoluminescence is most consistent with single-ion-like behavior of an asymmetric Sn(II) environment. Together, these results suggest that defect ordering presents a strategy for the reduction of mobile charge carriers at equilibrium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

Electronic states of semiconductor-metal-semiconductor quantum-well structures

Quantum-size effects are calculated in thin layered semiconductor-metal-semiconductor structures using an ideal free-electron model for the metal layer. The results suggest new quantum-well structures having device applications. Structures with sufficiently high-quality interfaces should exhibit effects such as negative differential resistance due to tunneling between allowed states. Similarly, optical detection by intersubband absorption may be possible. Ultrathin metal layers are predicted to behave as high-density dopant sheets.

Huberman, M. L.↗
NASA NTRS1978

Semiconductor heterostructure

A technique for fabricating a semiconductor heterostructure by growth of a ternary semiconductor on a binary semiconductor substrate from a melt of the ternary semiconductor containing less than saturation of at least one common ingredient of both the binary and ternary semiconductors wherein in a single temperature step the binary semiconductor substrate is etched, a p-n junction with specific device characteristics is produced in the binary semiconductor substrate by diffusion of a dopant from the melt and a region of the ternary semiconductor of precise conductivity type and thickness is grown by virtue of a change in the melt characteristics when the etched binary semiconductor enters the melt.

Hovel, Harold John↗
NASA NTRS1979

Semiconductor structure

A technique for fabricating a semiconductor heterostructure by growth of a ternary semiconductor on a binary semiconductor substrate from a melt of the ternary semiconductor containing less than saturation of at least one common ingredient of both the binary and ternary semiconductors wherein in a single temperature step the binary semiconductor substrate is etched, a p-n junction with specific device characteristics is produced in the binary semiconductor substrate by diffusion of a dopant from the melt and a region of the ternary semiconductor of precise conductivity type and thickness is grown by virtue of a change in the melt characteristics when the etched binary semiconductor enters the melt.

Hovel, Harold J.↗
DOE OSTI2025

Defect modeling in semiconductors: the role of first principles simulations and machine learning

Abstract Point defects in semiconductors dictate their electronic and optical properties. Vacancies, interstitials, substitutional defects, and defect complexes can form in the semiconductor lattice and significantly impact its performance in applications such as solar absorption, light emission, electronics, and catalysis. Understanding the nature and energetics of point defects is essential for the design and optimization of next-generation semiconductor technologies. Here, we provide a comprehensive overview of the current state of research on point defects in semiconductors, focusing on the application of density functional theory (DFT) and machine learning (ML) in accelerating the prediction and understanding of defect properties. DFT has been instrumental in accurately calculating defect formation energies, charge transition levels, and other defect-related properties such as carrier recombination rates and lifetimes, and ion migration barriers. ML techniques, particularly neural networks, have emerged as powerful tools for enabling rapid prediction of defect properties at DFT-accuracy in order to overcome the expense of using large supercells and advanced functionals. We begin this article with a discussion of different types of point defects and complexes, their impact on semiconductor properties, and the experimental and DFT approaches typically used for their characterization. Through multiple case studies, we explore how DFT has been successfully applied to understand defect behavior across a variety of semiconductors, and how ML approaches integrated with DFT can efficiently predict defect properties and facilitate the discovery of new materials with tailored defect behavior. Overall, the advent of ‘DFT+ML’ promises to drive advancements in semiconductor technology, catalysis, and renewable energy applications, paving the way for the development of high-performance semiconductors which are defect-tolerant or have desirable dopability.

Rahman, Md Habibur (ORCID:000000027705984X)↗
NASA NTRS1983

Semiconductor photoelectrochemistry

Semiconductor photoelectrochemical reactions are investigated. A model of the charge transport processes in the semiconductor, based on semiconductor device theory, is presented. It incorporates the nonlinear processes characterizing the diffusion and reaction of charge carriers in the semiconductor. The model is used to study conditions limiting useful energy conversion, specifically the saturation of current flow due to high light intensity. Numerical results describing charge distributions in the semiconductor and its effects on the electrolyte are obtained. Experimental results include: an estimate rate at which a semiconductor photoelectrode is capable of converting electromagnetic energy into chemical energy; the effect of cell temperature on the efficiency; a method for determining the point of zero zeta potential for macroscopic semiconductor samples; a technique using platinized titanium dioxide powders and ultraviolet radiation to produce chlorine, bromine, and iodine from solutions containing their respective ions; the photoelectrochemical properties of a class of layered compounds called transition metal thiophosphates; and a technique used to produce high conversion efficiency from laser radiation to chemical energy.

Buoncristiani, A. M.↗
NASA NTRS1977

Semiconductor sensors

A semiconductor sensor adapted to detect with a high degree of sensitivity small magnitudes of a mechanical force, presence of traces of a gas or light. The sensor includes a high energy gap (i.e., .about. 1.0 electron volts) semiconductor wafer. Mechanical force is measured by employing a non-centrosymmetric material for the semiconductor. Distortion of the semiconductor by the force creates a contact potential difference (cpd) at the semiconductor surface, and this cpd is determined to give a measure of the force. When such a semiconductor is subjected to illumination with an energy less than the energy gap of the semiconductors, such illumination also creates a cpd at the surface. Detection of this cpd is employed to sense the illumination itself or, in a variation of the system, to detect a gas. When either a gas or light is to be detected and a crystal of a non-centrosymmetric material is employed, the presence of gas or light, in appropriate circumstances, results in a strain within the crystal which distorts the same and the distortion provides a mechanism for qualitative and quantitative evaluation of the gas or the light, as the case may be.

Gatos, Harry C.↗
NASA NTRS1998

Semiconductor apparatus utilizing gradient freeze and liquid-solid techniques

Transition metals of Group VIII (Co, Rh and Ir) have been prepared as semiconductor compounds with the general formula TSb.sub.3. The skutterudite-type crystal lattice structure of these semiconductor compounds and their enhanced thermoelectric properties results in semiconductor materials which may be used in the fabrication of thermoelectric elements to substantially improve the efficiency of the resulting thermoelectric device. Semiconductor materials having the desired skutterudite-type crystal lattice structure may be prepared in accordance with the present invention by using vertical gradient freezing techniques and/or liquid phase sintering techniques. Measurements of electrical and thermal transport properties of selected semiconductor materials prepared in accordance with the present invention, demonstrated high Hall mobilities (up to 1200 cm.sup.2.V.sup.-1.s.sup.-1) and good Seebeck coefficients (up to 150 .mu.VK.sup.-1 between 300.degree. C. and 700.degree. C.). Optimizing the transport properties of semiconductor materials prepared from elemental mixtures Co, Rh, Ir and Sb resulted in a substantial increase in the thermoelectric figure of merit (ZT) at temperatures as high as 400.degree. C. for thermoelectric elements fabricated from such semiconductor materials.

Fleurial, Jean-Pierre↗
DOE OSTI2024

High-purity germanium semiconductor modeling in the detector response function toolkit

In this study, we have extended the detector response function toolkit (DRiFT) to provide modeling capabilities of semiconductor sensors. DRiFT provides realistic nuclear instrumentation response by post-processing Monte-Carlo N-particle (MCNP®) radiation transport outputs. MCNP® is capable of modeling radiation transport in complex environments, but has limited detector physics and readout electronics modeling capabilities. Semiconductor detector response can be calculated with a high-fidelity for a flexible range of environments by utilizing MCNP® to simulate radiation interactions inside of detector volumes, and then using DRiFT to model charge transport and signal formation in the semiconductor, as well as the readout electronics. DRiFT models charge transport in the semiconductor, the preamplifier, shaping amplifier, pulse pile-up, and electronic noise to generate detector response. The semiconductor application in DRiFT can model a range of semiconductor materials, shapes, and sizes; and is demonstrated here for a large volume coaxial high-purity germanium (HPGe) detector. Here, we compare detector response functions of a coaxial HPGe detector with measurement of 60 Co, 133 Ba, and 137 Cs at varying count rates, and we conduct a parameter study to demonstrate the effect of changing parameters in the DRiFT simulation. The HPGe detector response function shows excellent agreement with measurements of difference sources with varying dead times and count rates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1999

Validity of the Relation Between Spontaneous and Stimulated Emissions in Semiconductors

The Einstein relation between spontaneous emission and absorption was originally derived for a system consists of a two-state subsystem representing matter and harmonic fields representing radiation. The derivation is based on the detailed balance between these two subsystems under thermal equilibrium. The relationship was later investigated in connection with the interactions between radiation field and solids or semiconductors. The simple derivation dose not hold for semiconductors in general. In certain limiting cases, simple relation was obtained. The validity of this relation is important not only because of its fundamental role connecting two of the most fundamental optical processes in semiconductors, but mostly also because of its wide use as a practical method to measure the optical gain of a semiconductor. The validity of this relation for semiconductors has been an issue of controversial for some time. In this paper we numerically examine the validity of this relationship for several different lineshapes including Lorentzian, Gaussian, Sech, and a convoluted double Lorentzians (CDL). We find out that at relatively low density above transparency level, all first three lineshapes violate the Einstein relation. The relation is approximately valid at high density. At very high density, the validity of the Einstein relation holds well for all three lineshapes. The reason behind this observation is explained. The CDL lineshape has been shown analytically to obey the Einstein relationship previously. We show that for a 2D semiconductor with parabolic bands, the CDL lineshape can be integrated analytically. This analytic lineshape is compared with a simple Lorentzian lineshape.

Ning, Cun-Zheng↗
NASA NTRS1977

Semiconductor ohmic contact

A semiconductor device has one surface of P type conductivity material having a wide energy bandgap and a large crystal lattice parameter. Applied to the P type surface of the semiconductor device is a degenerate region of semiconductor material, preferably a group III-V semiconductor material, having a narrower energy bandgap. The degenerate region is doped with tin to increase the crystal lattice of the region to more closely approximate the crystal lattice of the one surface of the semiconductor device. The degenerate region is compensatingly doped with a P type conductivity modifier. An electrical contact is applied to one surface of the degenerate region forming an ohmic contact with the semiconductor device.

Hawrylo, Frank Zygmunt↗
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↗