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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Accurate Quantification of Si/SiGe Interface Profiles via Atom Probe Tomography

Pulsed laser atom probe tomography (APT) has enabled the investigation of semiconducting materials at sub-nm length scales and 10 ppm chemical sensitivity. This has enabled APT to be the best technique for nanoscale detection of dopant distributions and low levels of chemical segregation at interfaces, which are both important for semiconductor processing; however, the accuracy of measured interfacial profiles is typically compromised by aberrations. Interfacial profiles in APT data will vary with respect to different interfacial combinations, especially when the evaporation field between two materials is drastically different. Here, the ability of APT to measure SiGe/Si/SiGe interfacial profiles is tested with an 8 nm Si well embedded in SiGe. The APT measurements are compared to those measured using scanning transmission electron microscopy (STEM) to evaluate reconstruction and post-reconstruction processing methods to appropriately measure interfacial profiles using APT. Without post-APT reconstruction processing, the measured Si/SiGe interfacial widths between APT and STEM match poorly, but after applying the z-redistribution algorithm, the interfacial profiles are in good agreement. These results indicate that APT can be used to accurately identify SiGe/Si/SiGe interfacial profiles after application of the z-redistribution algorithm, which will greatly impact the synergy between growth and characterization of semiconductor devices using Si/SiGe interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Physics‐Informed Machine Learning for Inverse Design of Optical Metamaterials

Optical metamaterials manipulate light through various confinement and scattering processes, offering unique advantages like high performance, small form factor and easy integration with semiconductor devices. However, designing metasurfaces with suitable optical responses for complex metamaterial systems remains challenging due to the exponentially growing computation cost and the ill‐posed nature of inverse problems. To expedite the computation for the inverse design of metasurfaces, a physics‐informed deep learning (DL) framework is used. A tandem DL architecture with physics‐based learning is used to select designs that are scientifically consistent, have low error in design prediction, and accurate reconstruction of optical responses. The authors focus on the inverse design of a representative plasmonic device and consider the prediction of design for the optical response of a single wavelength incident or a spectrum of wavelength in the visible light range. The physics‐based constraint is derived from solving the electromagnetic wave equations for a simplified homogenized model. The model converges with an accuracy up to 97% for inverse design prediction with the optical response for the visible light spectrum as input, and up to 96% for optical response of single wavelength of light as input, with optical response reconstruction accuracy of 99%.

Sarkar, Sulagna↗
DOE OSTI2015

Assessing a mini-application as a performance proxy for a finite element method engineering application

The performance of a large-scale, production-quality science and engineering application (‘app’) is often dominated by a small subset of the code. Even within that subset, computational and data access patterns are often repeated, so that an even smaller portion can represent the performance-impacting features. If application developers, parallel computing experts, and computer architects can together identify this representative subset and then develop a small mini-application (‘miniapp’) that can capture these primary performance characteristics, then this miniapp can be used to both improve the performance of the app as well as provide a tool for co-design for the high-performance computing community. However, a critical question is whether a miniapp can effectively capture key performance behavior of an app. This study provides a comparison of an implicit finite element semiconductor device modeling app on unstructured meshes with an implicit finite element miniapp on unstructured meshes. The goal is to assess whether the miniapp is predictive of the performance of the app. Finally, single compute node performance will be compared, as well as scaling up to 16,000 cores. Results indicate that the miniapp can be reasonably predictive of the performance characteristics of the app for a single iteration of the solver on a single compute node.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2025

Measurement of Contact Resistivity In Symmetric Polycrystalline Si/SiO x /Monocrystalline Si Test Structures Using Variable Light Illumination

While different methods exist to determine the contact resistivity in semiconductor devices, these methods are limited to measurement of the majority carrier contacts. The measurement of p‐ or n‐type contacts on n‐ or p‐type crystalline silicon, respectively, is challenging due to the blocking diode formed by the p–n junction. In this article, we address this problem for tunneling oxide passivating contacts used in high‐efficiency Si solar cells. We propose a universal method to extract contact resistivity on symmetric test structures with polycrystalline silicon on SiO x (poly‐Si/SiO x ) passivating contacts under illumination, both for p–n and high–low‐junction passivated contacts. In this method, we demonstrate that the total contact resistance of each cell grid finger to the base wafer is governed by its effective contact area, defined by the transfer length extending from both sides of the finger. Therefore, the grid contact resistance of a poly‐Si contact depends on the ratio of the doped poly‐Si sheet resistance to the tunneling contact resistivity.

14 SOLAR ENERGY↗
DOE OSTI2023

OFraMP: a fragment-based tool to facilitate the parametrization of large molecules

Abstract An Online tool for Fragment-based Molecule Parametrization (OFraMP) is described. OFraMP is a web application for assigning atomic interaction parameters to large molecules by matching sub-fragments within the target molecule to equivalent sub-fragments within the Automated Topology Builder (ATB, atb.uq.edu.au) database. OFraMP identifies and compares alternative molecular fragments from the ATB database, which contains over 890,000 pre-parameterized molecules, using a novel hierarchical matching procedure. Atoms are considered within the context of an extended local environment (buffer region) with the degree of similarity between an atom in the target molecule and that in the proposed match controlled by varying the size of the buffer region. Adjacent matching atoms are combined into progressively larger matched sub-structures. The user then selects the most appropriate match. OFraMP also allows users to manually alter interaction parameters and automates the submission of missing substructures to the ATB in order to generate parameters for atoms in environments not represented in the existing database. The utility of OFraMP is illustrated using the anti-cancer agent paclitaxel and a dendrimer used in organic semiconductor devices. Graphical abstract OFraMP applied to paclitaxel (ATB ID 35922).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Empirical correlations between the arrhenius' parameters of impurities' diffusion coefficients in CdTe crystals

Understanding of self- and dopant-diffusion in semiconductor devices is essential to our being able to assure the formation of well-defined doped regions. In this paper, we compare obtained in the literature up to date the Arrhenius’ parameters (D=D 0 exp(–ΔE a /kT)) of point-defect diffusion coefficients and the I-VII groups impurities in CdTe crystals and films. We found that in the diffusion process there was a linear dependence between the pre-exponential factor, D 0 , and the activation energy, ΔE a , of different species: This was evident in the self-diffusivity and isovalent impurity Hg diffusivity as well as for the dominant IIIA and IVA groups impurities and Chlorine, except for the fast diffusing elements (e.g., Cu and Ag), chalcogens O, S, and Se, halogens I and Br as well as the transit impurities Mn, Co, Fe. As a result, reasons of the lack of correspondence of the data to compensative dependence are discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A review of high order strong stability preserving two-derivative explicit, implicit, and IMEX methods

High order strong stability preserving time discretizations ensure the nonlinear non-inner-product strong stability properties of spatial discretizations suited for the stable simulation of hyperbolic PDEs in a wide variety of application areas including fluid dynamics, magnetohydrodynamics, semiconductor devices, electromagnetics, and astrophysics. Over the past decade multiderivative time-stepping have been increasingly used for the time-evolution hyperbolic PDEs, so that the strong stability properties of these methods have become important. In this work we review sufficient conditions for a two-derivative multistage method to preserve the strong stability properties of spatial discretizations in a forward Euler and different conditions on the second derivative. In particular we present the strong stability preserving theory for explicit and implicit two-derivative Runge–Kutta schemes, including a special condition on the second derivative under which these implicit methods may be unconditionally strong stability preserving. This special condition is natural for the stiff component of wide range of plasma physics problems, and can be useful in the context of strong stability preserving implicit-explicit multi-derivative Runge–Kutta schemes, where the time-step restriction is then independent of the stiff term. Lastly, we present the strong stability preserving theory for implicit-explicit multi-derivative general linear methods, and some novel second and third order methods where the time-step restriction is independent of the stiff term.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2027

Low thermal budget dopant activation in shallow junctions of implanted Si via Tunable plasma enhanced annealing

Low thermal budget (LTB) annealing has become increasingly critical for shallow junctions as semiconductor devices are scaled down. Plasma Enhanced Annealing (PEA) has emerged as a promising LTB annealing process, however its mechanisms remain unclear. In this study, arsenic and boron implanted silicon wafers were subjected to helium or argon ion bombardment generated by annealing plasmas under controlled ion energies and doses in a home-built annealing reactor. The structural and electrical changes were characterized by four-point probe measurements, secondary ion mass spectrometry, Raman spectroscopy and spectroscopic ellipsometry. A pronounced reduction in sheet resistance, accompanied by a decrease in the damage layer thickness demonstrates the surface selective annealing capability of PEA process. Comparative studies using He and Ar plasmas and related ion bombardment reveal a dependence of activation efficacy on both ion species and the dopant implantation profile. Furthermore, a multi-step annealing mechanism is proposed, consisting of an initial (low dose) structural recovery stage followed by the generation of “extended” defects and concluded at large doses by an enhanced dopant activation. The proposed annealing kinetics are thought to be controlled by ion flux, dose and energy. Finally, these results highlight PEA as an effective, surface-selective, LTB approach for shallow-dopant activation and near surface annealing, and provide mechanistic insights into PEA processes.

dopant activation↗
DOE OSTI2024

Solution of the Schrödinger equation for quasi-one-dimensional materials using helical waves

We formulate and implement a spectral method for solving the Schrödinger equation, as it applies to quasi-one-dimensional materials and structures. This allows for computation of the electronic structure of important technological materials such as nanotubes (of arbitrary chirality), nanowires, nanoribbons, chiral nanoassemblies, nanosprings and nanocoils, in an accurate, efficient and systematic manner. Our work is motivated by the observation that one of the most successful methods for carrying out electronic structure calculations of bulk/crystalline systems — the plane-wave method — is a spectral method based on eigenfunction expansion. Our scheme avoids computationally onerous approximations involving periodic supercells often employed in conventional plane-wave calculations of quasi-one-dimensional materials, and also overcomes several limitations of other discretization strategies, e.g., those based on finite differences and atomic orbitals. The basis functions in our method — called helical waves (or twisted waves) — are eigenfunctions of the Laplacian with symmetry adapted boundary conditions, and are expressible in terms of plane waves and Bessel functions in helical coordinates. We describe the setup of fast transforms to carry out discretization of the governing equations using our basis set, and the use of matrix-free iterative diagonalization to obtain the electronic eigenstates. Miscellaneous computational details, including the choice of eigensolvers, use of a preconditioning scheme, evaluation of oscillatory radial integrals and the imposition of a kinetic energy cutoff are discussed. We have implemented these strategies into a computational package called HelicES (Helical Electronic Structure). We demonstrate the utility of our method in carrying out systematic electronic structure calculations of various quasi-one-dimensional materials through numerous examples involving nanotubes, nanoribbons and nanowires. We also explore the convergence properties of our method, and assess its accuracy and computational efficiency by comparison against reference finite difference, transfer matrix method and plane-wave results. We anticipate that our method will find applications in computational nanomechanics and multiscale modeling, for carrying out transport calculations of interest to the field of semiconductor devices, and for the discovery of novel chiral phases of matter that are of relevance to the burgeoning quantum hardware industry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Friction and wear behavior of nitrogen-doped ZnO thin films deposited via MOCVD under dry contact

Most researches on doped ZnO thin films are tilted toward their applications in optoelectronics and semiconductor devices. Research on their tribological properties is still unfolding. In this work, nitrogen-doped ZnO thin films were deposited on 304 L stainless steel substrate from a combination of zinc acetate and ammonium acetate precursor by MOCVD technique. Compositional and structural studies of the films were done using Rutherford Backscattering Spectroscopy (RBS) and X-ray Diffraction (XRD). The frictional behavior of the thin film coatings was evaluated using a ball-on-flat configuration in reciprocating sliding under dry contact condition. After friction test, the flat and ball counter-face surfaces were examined to assess the wear dimension and failure mechanism. In conclusion, both friction behavior and wear (in the ball counter-face) were observed to be dependent on the crystallinity and thickness of the thin film coatings.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Recent progress in degradation and stabilization of organic solar cells

Stability is of paramount importance in organic semiconductor devices, especially in organic solar cells (OSCs). Serious degradation in air limits wide applications of these flexible, light-weight and low-cost power-generation devices. Studying the stability of organic solar cells will help us understand degradation mechanisms and further improve the stability of these devices. There are many investigations into the efficiency and stability of OSCs. The efficiency and stability of devices even of the same photoactive materials are scattered in different papers. In particular, the extrinsic degradation that mainly occurs near the interface between the organic layer and the cathode is a major stability concern. In the past few years, researchers have developed many new cathodes and cathode buffer layers, some of which have astonishingly improved the stability of OSCs. In this review article, we discuss the recent developments of these materials and summarize recent progresses in the study of the degradation/stability of OSCs, with emphasis on the extrinsic degradation/stability that is related to the intrusion of oxygen and water. The review provides detailed insight into the current status of research on the stability of OSCs and seeks to facilitate the development of highly-efficient OSCs with enhanced stability.

Cao, Huanqi↗
DOE OSTI2025

Mg vacancy and impurity-limited MgO single crystal thermal conductivity

Magnesium oxide (MgO) exhibits one of the highest thermal conductivities among oxides and is widely used as a dielectric material and substrate in semiconductor devices, in refractory applications, and as a promising filler in thermal interface materials for electronics. Its high thermal conductivity may be sensitive to impurity and defects, yet this influence is still uncertain. Here, in this study, the impact of the common impurities, i.e., Al, Ca, Ti, V, Fe, Si, B, Nb, Zr, Na, and K, as well as Mg and O vacancies on phonon scattering and thermal conductivity of MgO is studied using a fully first-principles T-matrix framework. It is found that B, Nb, and Zr impurities, along with Mg vacancies, lead to exceptionally strong reductions in thermal conductivity. By contrast, O vacancies and other impurities have modest to minimal impacts. Leveraging the T-matrix results, we reassess the perturbative, mass-only formalism whose use is pervasive in the literature and show that neglecting bond disorder does not necessarily lead to underestimation: for all transition-metal impurities studied, bond perturbations partially cancel mass disorder, causing the traditional perturbative model to overestimate scattering. We propose a simple modified perturbative expression that incorporates both mass and bond disorder and closely reproduces the T-matrix trends. Our predicted low-temperature trends by including phonon-impurity and phonon-boundary scattering match reasonably well with experiments. This work provides an in-depth study of impurity- and vacancy-limited thermal conductivity of MgO and suggests that reported “high-purity” MgO values have likely not yet reached the intrinsic upper limit, which may be substantially higher.

36 - MATERIALS SCIENCE↗
DOE OSTI2019

Novel high-energy ion implantation facility using a 15 MV Tandem Van de Graaff accelerator

The implantation depths required for the development and fabrication of future generations of silicon carbide (SiC) semiconductor devices require ion energies that are well above the capabilities of most conventional ion implanters. To generate implantation profiles that extend from more than 10 μm to the surface of the wafer, a wide range of energy ions (kV to 10 s of MeV) is required. We developed a novel multi-energy implantation system that satisfies these requirements using heavy ion beams from one of the Brookhaven National Laboratory’s two 15 MV Tandem Van de Graaff accelerators. This system is described, including the dosimetry approach and the available ion species and intensities. Finally, an example of a measured implantation profiles in SiC is shown and compared to simulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Atomic worlds: Current state and future of atom probe tomography in geoscience

Atom Probe Microscopy(APM)is rapidly finding new applications within the geosciences. Historically connectedwithmaterials science, and semiconductor device applications, recent years have seen an excitingtrend as APM hasproveda useful tool for nanoscale geochemistry, as itoffersunique capabilities when compared withthe suite of conventional geoanalytical techniques. The ability to characterize 3D nanoscale chemistry with isotopic sensitivityhas uncoveredintricate details of complex trace element distributions within a varietyof minerals and has opened the door to nanoscale isotope geochemistry. Already these advances are having an impact on long-standing questions within geochronology, planetary science and many other fields of research. As this trend gathers pace, we present here a brief summary of the current statusof APM geoscience applications and discuss the likely future directions in this developingresearch space.

58 GEOSCIENCES↗
DOE OSTI2018

Increased fracture depth range in controlled spalling of (100)-oriented germanium via electroplating

Controlled spalling in (100)-oriented germanium using a nickel stressor layer shows promise for semiconductor device exfoliation and kerfless wafering. Demonstrated spall depths of 7-60 um using DC sputtering to deposit the stressor layer are appropriate for the latter application but spall depths < 5 um may be required to minimize waste for device applications. This work investigates the effect of tuning both electroplating current density and electrolyte chemistry on the residual stress in the nickel and on the achievable spall depth range for the Ni/Ge system as a lower-cost, higher-throughput alternative to sputtering. By tuning current density and electrolyte phosphorous concentration, it is shown that electroplating can successfully span the same range of spalled thicknesses as has previously been demonstrated by sputtering and can reach sufficiently high stresses to enter a regime of thickness (<7 um) appropriate to minimize substrate consumption for device applications.

14 SOLAR ENERGY↗