Search NASA⌕ Search

SEARCH · Search NASA

Results for “reflection high-energy electron diffraction (RHEED)”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

17 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Predicting Pulsed-Laser Deposition SrTiO 3 Homoepitaxy Growth Dynamics Using High-Speed Reflection High-Energy Electron Diffraction

Pulsed-laser deposition (PLD) is a powerful technique for growing complex oxides with controlled stoichiometry. To understand growth dynamics therein, it is common to leverage in situ spectroscopies, such as reflection high-energy electron diffraction (RHEED), to monitor surface crystallinity. Most commercial systems rely on video-rate cameras operating at 60-120 Hz that lack sufficient temporal resolution to capture growth dynamics at practical deposition frequencies. Here, a high-speed platform to record in situ dynamics via RHEED at >500 Hz is implemented. An open-source analysis package is designed to fit diffraction spots to 2D Gaussians, allowing single-pulse surface reconstruction kinetics extraction. Using homoepitaxially deposited (001)-oriented SrTiO 3 as a model system, we demonstrate how high-speed RHEED can provide real-time insight into growth processes obscured by slower acquisition systems. By fitting the single-pulse intensity to a set of exponential functions, we observe changes in the characteristic decay time and mechanism correlated to the substrate step width and surface termination. We observe distinct surface effects, with diffraction intensity decaying on lower-energy TiO 2 -terminated surfaces and stabilizing on SrO- or mixed-terminated surfaces. Similarly, using an exponential model, the extracted characteristic time of adatom deposition decreases with increased density of bonding sites associated with mixed termination and narrower step widths. Ultimately, this work shows how increasing RHEED temporal resolution can uncover new insights into growth processes, with practical implications for the design and control of PLD processes. This experimental platform provides new capabilities to enable data-driven machine learning analysis and autonomous control systems to enhance the complexity and fecundity of PLD.

(SrO)↗
DOE OSTI2025

Machine-learning-enabled on-the-fly analysis of RHEED patterns during thin film deposition by molecular beam epitaxy

Thin film deposition is a fundamental technology for the discovery, optimization, and manufacturing of functional materials. Deposition by molecular beam epitaxy (MBE) typically employs reflection high-energy electron diffraction (RHEED) as a real-time in situ probe of the growing film. However, the state-of-the-art for RHEED analysis during deposition requires human observation. Here, we present an approach using machine learning (ML) methods to monitor, analyze, and interpret RHEED images on-the-fly during thin film deposition. In the analysis workflow, RHEED pattern images are collected at one frame per second and featurized using a pretrained deep convolutional neural network. The feature vectors are then statistically analyzed to identify changepoints; these changepoints can be related to changes in the deposition mode from initial film nucleation to a transition regime, smooth film deposition, and in some cases, an additional transition to a rough, islanded deposition regime. The feature vectors are additionally analyzed via graph analysis and community classification. The graph is quantified as a stabilization plot, and we show that inflection points in the stabilization plot correspond to changes in the growth regime. The full RHEED analysis workflow is termed RHAAPsody and includes data transfer and output to a visual dashboard. We demonstrate the functionality of RHAAPsody by analyzing the precaptured RHEED images from epitaxial depositions of anatase TiO2 on SrTiO3(001) and show that the analysis workflow can be executed in less than 1 s. Our approach shows promise as one component of ML-enabled real-time feedback control of the MBE deposition process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In-situ quantification of the surface roughness for facile fabrications of atomically smooth thin films

Here in this work we present an in-situ technique to quantify the layer-by-layer roughness of thin films and heterostructures by measuring the spectral profile of the reflection high-energy electron diffraction (RHEED). The characteristic features of the diffraction spot, including the vertical to lateral size ratio c/b and the asymmetrical ratio c 1 /c 2 along the vertical direction, are found to be quantitatively dependent on the surface roughness. The quantitative relationships between them are established and discussed for different incident angles of high-energy electrons. As an example, the surface roughnesses of LaCoO 3 films grown at different temperatures are obtained using such an in-situ technique, which are confirmed by the ex-situ atomic force microscopy. Moreover, the in-situ measured layer-by-layer roughness oscillations of two LaCoO 3 films are demonstrated, revealing drastically different information from the intensity oscillations. The experiments assisted with the in-situ technique demonstrate an outstanding high resolution down to similar to ~0.1 Å. Therefore, the new quantitative RHEED technique with real-time feedbacks significantly escalates the thin film synthesis efficiency, especially for achieving atomically smooth surfaces and interfaces. It opens up new prospects for future generations of thin film growth, such as the artificial intelligence-assisted thin film growth.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Au assisted smooth ultrathin epitaxial ZnO film grown by pulsed laser deposition on sapphire(0001)

High quality ZnO has applications in photonics and electronics. Literature has shown that continuous, but rough ZnO film can be grown on sapphire substrate by pulsed laser deposition (PLD). In this work, ZnO and Au were co-deposited by PLD on sapphire(0001) substrates from a single ZnO target overlaid with an Au strip that serves as a catalyst. The reflection high-energy electron diffraction (RHEED) patterns show paired double stripes from sample of ZnO-Au where the difference of in-plane lattice parameters between ZnO and Au is 11.4 %. The two-dimensional (2D) reciprocal space maps constructed from azimuthal RHEED (ARHEED) patterns reveal parallel epitaxial relationship between ZnO and Au in the continuous ZnO-Au film on sapphire substrate. Transmission electron microscopy (TEM) cross section images and energy dispersive spectroscopy maps show a minute amount of Au nanocrystals distributed in the entire ultrathin ZnO film. Atomic force microscopy shows the root-mean-square roughness of the surface of ultrathin ZnO film with Au is in the sub-nm range. The ARHEED and TEM results show that a couple of atomic percentages of Au co-deposited with ZnO catalyzes the growth of smooth ultrathin epitaxial ZnO film.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine learning analysis of perovskite oxides grown by molecular beam epitaxy

Reflection high-energy electron diffraction (RHEED) is a ubiquitous in situ molecular beam epitaxial (MBE) characterization tool. Although RHEED can be a powerful means for crystal surface structure determination, it is often used as a static qualitative surface characterization method at discrete intervals during a growth. A full analysis of RHEED data collected during the entirety of MBE growths is made possible using principle component analysis (PCA) and $\textit{k}$-means clustering to examine significant boundaries that occur in the temporal clusters grouped from RHEED data and identify statistically significant patterns. This process is applied to data from homoepitaxial SrTiO 3 growths, heteroepitaxial SrTiO 3 grown on scandate substrates, BaSnO 3 films grown on SrTiO 3 substrates, and LaNiO 3 films grown on SrTiO 3 substrates. We report this analysis may provide additional insights into the surface evolution and transitions in growth modes at precise times and depths during growth, and that video archival of an entire RHEED image sequence may be able to provide more insight and control overgrowth processes and film quality.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Machine-learning-assisted analysis of transition metal dichalcogenide thin-film growth

In situ reflective high-energy electron diffraction (RHEED) is widely used to monitor the surface crystalline state during thin-film growth by molecular beam epitaxy (MBE) and pulsed laser deposition. With the recent development of machine learning (ML), ML-assisted analysis of RHEED videos aids in interpreting the complete RHEED data of oxide thin films. The quantitative analysis of RHEED data allows us to characterize and categorize the growth modes step by step, and extract hidden knowledge of the epitaxial film growth process. In this study, we employed the ML-assisted RHEED analysis method to investigate the growth of 2D thin films of transition metal dichalcogenides (ReSe2) on graphene substrates by MBE. Principal component analysis (PCA) and K-means clustering were used to separate statistically important patterns and visualize the trend of pattern evolution without any notable loss of information. Using the modified PCA, we could monitor the diffraction intensity of solely the ReSe2 layers by filtering out the substrate contribution. These findings demonstrate that ML analysis can be successfully employed to examine and understand the film-growth dynamics of 2D materials. Further, the ML-based method can pave the way for the development of advanced real-time monitoring and autonomous material synthesis techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Self-driving thin film laboratory: autonomous epitaxial atomic-layer synthesis via real-time computer vision analysis of electron diffraction

Emerging materials science platforms with the ability to make autonomous decisions on the fly are fundamentally changing the outlook and protocols for materials optimization and discovery. Because AI-driven self-navigating schemes can effectively reduce the total number of iterations needed to arrive at the "answer" (i.e. the best stochiometric composition for a desired physical property, optimum materials processing parameters, etc.) by significant margins, they have the potential to revolutionize materials and chemical manufacturing processes at large in research laboratory settings as well as in industrial plants. Here, we demonstrate a successful implementation of real-time closed-loop autonomous navigation of a multi-dimensional materials synthesis parameter space for fabricating phase-pure epitaxial films of a metastable phase of a functional oxide in a combinatorial pulsed laser deposition chamber. Sequential epitaxial growth iterations in search of the optimized recipe to stabilize the desired crystal phase were performed using frame-by-frame quantitative computer vision analysis of reflection high-energy electron diffraction (RHEED) images of the unit-cell level film being deposited. The autonomous scheme regularly resulted in > 30-fold reduction in the number of required experiments compared to a comprehensive mapping of the parameter space. The real-time workflow developed here can be readily extended to a variety of thin film synthesis platforms opening the door for self-driving atomic-level materials design as well as autonomous optimization of semiconductor manufacturing.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Delayed Shutters For Dual-Beam Molecular Epitaxy

System of shutters for dual-molecular-beam epitaxy apparatus delays start of one beam with respect to another. Used in pulsed-beam equipment for deposition of low-dislocation layers of InAs on GaAs substrates, system delays application of arsenic beam with respect to indium beam to assure proper stoichiometric proportions on newly forming InAs surface. Reflectance high-energy electron diffraction (RHEED) instrument used to monitor condition of evolving surface of deposit. RHEED signal used to time pulsing of molecular beams in way that minimizes density of defects and holds lattice constant of InAs to that of GaAs substrate.

Grunthaner, Frank J.↗
NASA NTRS1990

Multiple reflection high-energy electron diffraction beam intensity measurement system

A video-based analysis system for reflection high-energy electron diffraction (RHEED) is described which simultaneously measures the intensities and profiles of multiple diffraction beams. This system is used to record real-time RHEED intensity oscillations for layer-by-layer epitaxial growth. Fast Fourier transform analysis of the oscillation data is used to directly determine the growth rate and to accurately obtain phase information about the oscillations. This system is demonstrated and compared to other methods of recording RHEED oscillation data.

Resh, J. S.↗
NASA NTRS1992

Reflection high-energy electron diffraction study of growth and interface formation of the Ga(1-x)In(x)Sb/InAs strained-layer superlattices

Reflection high-energy electron diffraction (RHEED) during molecular beam epitaxy is used to study the growth and interface formation of the Ga(1-x)In(x)Sb/InAs (x is not greater than 0.4) strained-layer superlattices (SLSs) on GaSb(100) substrates. A number of surface atomic structures were observed in the growth of the SLS: a (1 x 3) phase from the InAs epilayer surface, a (2 x 3) phase, a (2 x 4) phase, and diffuse (1 x 1)-like phases from the InAs epilayer surface. It is suggested that the long-range order quality of the interface of Ga(1-x)In(x)Sb on InAs may be better than that of the interface of InAs on Ga(1-x)In(x)Sb, but the abruptness of the interfaces would still be compatible. The RHEED intensity variations in the formation of the interfaces are discussed in terms of interface chemical reactions.

Fan, W. C.↗
NASA NTRS1990

Narrow bandgap semiconducting silicides: Intrinsic infrared detectors on a silicon chip

Work done during the final report period is presented. The main technical objective was to achieve epitaxial growth on silicon of two semiconducting silicides, ReSi2 and CrSi2. ReSi2 thin films were grown on (001) silicon wafers by vacuum evaporation of rhenium onto hot substrates in ultrahigh vacuum. The preferred epitaxial relationship was found to be ReSi2(100)/Si(001) with ReSi2(010) parallel to Si(110). The lattice matching consists of a common unit mesh of 120 A(sup 2) area, and a mismatch of 1.8 percent. Transmission electron microscopy revealed the existence of rotation twins corresponding to two distinct but equivalent azimuthal orientations of the common unit mesh. MeV He(+) backscattering spectrometry revealed a minimum channeling yield of 2 percent for an approximately 1,500 A thick film grown at 650 C. Although the lateral dimension of the twins is on the order of 100 A, there is a very high degree of alignment between the ReSi2(100) and the Si(001) planes. Highly oriented films of CrSi2 were grown on (111) silicon substrates, with the matching crystallographic faces being CrSi2(001)/Si(111). The reflection high-energy electron diffraction (RHEED) patterns of the films consist of sharp streaks, symmetrically arranged. The predominant azimuthal orientation of the films was determined to be CrSi2(210) parallel to Si(110). This highly desirable heteroepitaxial relationship has been obtained previously by others; it may be described with a common unit mesh of 51 A(sup 2) and mismatch of 0.3 percent. RHEED also revealed the presence of limited film regions of a competing azimuthal orientation, CrSi2(110) parallel to Si(110). A channeling effect for MeV He(+) ions was not found for this material. Potential commercial applications of this research may be found in silicon-integrated infrared detector arrays. Optical characterizations showed that semiconducting ReSi2 is a strong absorber of infrared radiation, with the adsorption constant increasing above 2 x 10(exp 4) cm(sup -1) for photon energies above 0.2 eV. CrSi2 is of potential utility for detection at photon energies above approximately 0.3 eV.

Mahan, John E.↗
DOE OSTI2024

Advances in Molecular Beam Epitaxy Growth of Ultra-Wide Bandgap Ga2O3 Based Alloys

Gallium oxide (Ga2O3) is an emerging ultra-wide bandgap semiconductor material that has attracted attention for its potential to outperform existing SiC and GaN based devices operating at high breakdown voltages and high temperature. Isovalent alloying of In and Al in Ga2O3 provides the ability to engineer bandgap energy and strain of the material. Alloying with Al increases the bandgap energy and the theoretically achievable Baliga's figure of merit, a key measure of a material's ultimate performance limits for high power switching devices. Alloying with In introduces compressive strain and can be used to counteract the tensile strain of Al incorporation. The resulting (AlxGa1-x-yIny)2O3 alloy can be lattice-matched to commercially available Ga2O3 wafers and has a tunable bandgap energy greater than that of Ga2O3, 4.76 eV. Such lattice-matched material can be grown arbitrarily thick without the detrimental effects of elastic strain and relaxation, making it suitable for high voltage diodes and transistors. However, efforts to synthesize isovalent alloys are complicated by their tendency to phase separate into corundum Al2O3 or bixbyite In2O3. Literature reports of the quaternary (AlxGa1-x-yIny)2O3 are limited to <1% unintentional indium incorporation in In-catalyzed (AlxGa1-x)2O3. The primary limitation to quaternary growth is the limited incorporation of indium at elevated growth temperatures. This limited incorporation is due to both the volatility of indium oxide and Al and Ga cation exchange reactions which replace indium in In2O3. We report on the development of a novel high-throughput molecular beam epitaxy (MBE) technique to screen the growth conditions for the ternary alloy (InyGa1-y)2O3, and the application of these findings to the first successful synthesis of phase pure monoclinic (AlxGa1-x-yIny)2O3 by MBE. By leveraging the unique sub-oxide chemistry of Ga2O3 and in-situ monitoring of crystal properties by reflection high-energy electron diffraction (RHEED), a cyclical growth and etch-back method is developed and applied to rapidly characterize the (InyGa1-y)2O3 growth space. This cyclical method provides approximately 10x increase in experimental throughput and up to 46x improvement in Ga2O3 substrate utilization. Appropriate growth conditions for monoclinic (InyGa1- y)2O3 are identified by machine learning analysis of RHEED patterns and targeted growths are characterized ex-situ to confirm improved In incorporation. These growth conditions are then combined with established (AlxGa1-x)2O3 growth conditions to grow quaternary (AlxGa1-x-yIny)2O3 with Al mole fractions ranging from 1.4% - 24.4% and In mole fractions ranging from 3.1% to 15.5%. The chemical and optical properties of the alloys are investigated by XRD, XPS, and spectroscopic ellipsometry. A lattice-matched (AlxGa1-x-yIny)2O3 alloy is examined by 4D-STEM and the chemical and physical uniformity of Al and In incorporation are discussed.

alloy↗
NASA NTRS1986

Arsenic-induced intensity oscillations in reflection high-energy electron diffraction measurements

A technique of arsenic-induced RHEED intensity oscillations has been used to accurately measure arsenic incorporation rates as a function of substrate temperature during the homoepitaxial growths of both GaAs and InAs by molecular beam epitaxy (MBE). Measurements were made at growth temperatures from 350 to 650 C and at arsenic fluxes of 0.1 to 10.0 monolayer/s. The method measures only the arsenic actually incorporated into the growing film and does not include the arsenic lost in splitting the arsenic tetramers or lost by evaporation from the sample.

Lewis, B. F.↗
DOE OSTI2023

Near surface structure of ultrathin epitaxial Ru films on graphene/amorphous SiO 2 revealed by azimuthal RHEED

Ru has been considered as an alternative metallic candidate for future local interconnects. The 2D reciprocal space map constructed from the azimuthal reflection high-energy electron diffraction patterns reveals that ultrathin Ru(0001) is epitaxially grown on transferred graphene on amorphous SiO 2 through quasi-van der Waals interaction. The in-plane and out-of-plane lattice constants are measured from streaks’ separation and intensity modulations along streaks, respectively. Weak and broad rings indicate that a low density of nanoscale polycrystals exist on the surface. In this work, The intensities of 00 and non-00 diffraction spots vs. azimuthal angles in the 2D map show a few degrees out-of-plane and in-plane angular misorientations among grains, respectively. As the film thickness decreases these angular misorientations increase. Transmission electron microscopy carried out in this study also provides precise values of lattice constant and sub-grain sizes in the films. These findings show that ultrathin Ru film is epitaxial but not exactly single crystalline.

36 MATERIALS SCIENCE↗
DOE OSTI2021

On the Development of Order and Interfaces during the Growth of Ultrathin La 2 CuO 4 Films by Molecular Beam Epitaxy

While the atomic structure of interfaces in complex oxide heterostructures created by epitaxial growth has been investigated extensively, few studies have been conducted on how interfaces form and restructure at the initial stage of film growth. The dynamic aspects of the growth behavior can strongly influence the final interfacial atomic structure, which may lead to the emergence of interface-specific properties, such as the rise of interfacial superconductivity between certain Ruddlesden-Popper oxide materials. In this report, the structural development of La2CuO 4 thin films grown by molecular beam epitaxy on a LaSrAlO 4 substrate is investigated by X-ray diffraction measurements with rapid scans over a volume of reciprocal space. This method provides far more detailed information on interface formation than traditional fixed-point measurements. The results show that the atomic structure of the interface becomes fully established after just a single unit cell of growth. Interestingly, restructuring continues to occur within the topmost half to one unit cell of the film during the deposition process. However, diffraction intensity oscillations from both reflection high-energy electron and X-ray measurements stabilize only after the growth of two unit cells, indicating that the growth front morphology continues to evolve until the start of the third unit cell. This multimodal investigation provides insights into the atomic processes taking place during layered oxide interface formation, including the dynamical rearrangement of LaO and CuO 2 layers. Such information is not only relevant to the engineering and optimization of functional layer structures but can also be critical for ultrathin films.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Deep Learning with Reflection High-Energy Electron Diffraction Images to Predict Cation Ratio in Sr 2 x Ti 2(1– x ) O 3 Thin Films

Machine learning (ML) with in-situ diagnostics offers a transformative approach to accelerate, understand, and control thin film synthesis by uncovering relationships between synthesis conditions and material properties. In this study, we demonstrate the application of deep learning to predict the stoichiometry of Sr 2x Ti 2(1–x) O 3 thin films using reflection high-energy electron diffraction images acquired during pulsed laser deposition. A gated convolutional neural network trained for regression of the Sr atomic fraction achieved accurate predictions with a small dataset of 31 samples. Explainable AI techniques revealed a previously unknown correlation between diffraction streak features and cation stoichiometry in Sr 2x Ti 2(1–x) O 3 thin films. Here, our results demonstrate how ML can be used to transform a ubiquitous in-situ diagnostic tool, that is usually limited to qualitative assessments, into a quantitative surrogate measurement of continuously valued thin film properties. Such methods are critically needed to enable real-time control, autonomous workflows, and accelerate traditional synthesis approaches.

77 NANOSCIENCE AND NANOTECHNOLOGY↗