System for recording and analysis of reflection high-energy electron diffraction patterns

Guryanov, G.; Демидов, В Н; Korneeva, N. P.; Petrov, V. N.; Samsonenko, Yu. B.; Tsyrlin, G. É.

doi:10.1134/1.1258761

Cited by 8 publications

(3 citation statements)

References 6 publications

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“…Given the proliferation of RHEED systems in growth chambers worldwide and the wealth of static and dynamic information that can be obtained about the surface from analysis of RHEED data, toolkits to analyze the entire RHEED image sequence should be developed. In the 1990s, systems to record, store, and analyze the data were developed, 17,18 and at present, though the common commercially available RHEED systems 19 are perfectly capable of recording the entire image sequence at appropriate capture rates and high resolutions, most routine analysis of acquired data sets is still limited to either averaging the intensity of one or several diffraction spots (thus yielding a single timevarying intensity plot) or producing a few static images of RHEED diffraction patterns at particular times, e.g., at the start, middle and at the end of the deposition. Thus, the majority of information in the acquired RHEED image sequence is discarded, along with the static and dynamic information on surface properties contained therein.…”

mentioning

confidence: 99%

“…Given the proliferation of RHEED systems in growth chambers worldwide and the wealth of static and dynamic information that can be obtained about the surface from analysis of RHEED data, toolkits to analyze the entire RHEED image sequence should be developed. In the 1990s, systems to record, store, and analyze the data were developed, , and at present, though the common commercially available RHEED systems are perfectly capable of recording the entire image sequence at appropriate capture rates and high resolutions, most routine analysis of acquired data sets is still limited to either averaging the intensity of one or several diffraction spots (thus yielding a single time-varying intensity plot) or producing a few static images of RHEED diffraction patterns at particular times, e.g. , at the start, middle and at the end of the deposition.…”

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confidence: 99%

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Big-Data Reflection High Energy Electron Diffraction Analysis for Understanding Epitaxial Film Growth Processes

et al. 2014

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Reflection high energy electron diffraction (RHEED) has by now become a standard tool for in situ monitoring of film growth by pulsed laser deposition and molecular beam epitaxy. Yet despite the widespread adoption and wealth of information in RHEED images, most applications are limited to observing intensity oscillations of the specular spot, and much additional information on growth is discarded. With ease of data acquisition and increased computation speeds, statistical methods to rapidly mine the data set are now feasible. Here, we develop such an approach to the analysis of the fundamental growth processes through multivariate statistical analysis of a RHEED image sequence. This approach is illustrated for growth of La(x)Ca(1-x)MnO(3) films grown on etched (001) SrTiO(3) substrates, but is universal. The multivariate methods including principal component analysis and k-means clustering provide insight into the relevant behaviors, the timing and nature of a disordered to ordered growth change, and highlight statistically significant patterns. Fourier analysis yields the harmonic components of the signal and allows separation of the relevant components and baselines, isolating the asymmetric nature of the step density function and the transmission spots from the imperfect layer-by-layer (LBL) growth. These studies show the promise of big data approaches to obtaining more insight into film properties during and after epitaxial film growth. Furthermore, these studies open the pathway to use forward prediction methods to potentially allow significantly more control over growth process and hence final film quality.

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mentioning

confidence: 99%

“…Given the proliferation of RHEED systems in growth chambers worldwide and the wealth of static and dynamic information that can be obtained about the surface from analysis of RHEED data, toolkits to analyze the entire RHEED image sequence should be developed. In the 1990s, systems to record, store, and analyze the data were developed, , and at present, though the common commercially available RHEED systems are perfectly capable of recording the entire image sequence at appropriate capture rates and high resolutions, most routine analysis of acquired data sets is still limited to either averaging the intensity of one or several diffraction spots (thus yielding a single time-varying intensity plot) or producing a few static images of RHEED diffraction patterns at particular times, e.g. , at the start, middle and at the end of the deposition.…”

mentioning

confidence: 99%

Big-Data Reflection High Energy Electron Diffraction Analysis for Understanding Epitaxial Film Growth Processes

et al. 2014

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“…Despite the relative wealth of information contained in RHEED patterns and the near universality of the presence of RHEED in both commercial and academic MBE chambers, the analysis of RHEED is typically limited to a quantitative analysis of a few static images taken before, during, and after the growth and/or the mean intensity collected of a few pre-determined specular or diffraction spots over the course of a growth. Although systems that allow users to take video of the evolution of RHEED patterns have been developed and are commercially available [11,12], video is rarely used in RHEED analysis beyond the analysis of a few static frames and the majority of the information contained within goes unused.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Analysis of Perovskite Oxides Grown by Molecular Beam Epitaxy

Provence,

Thapa,

Paudel

et al. 2020

Preprint

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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 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 SrTiO3 growths, heteroepitaxial SrTiO3 grown on scandate substrates, BaSnO3 films grown on SrTiO3 substrates, and LaNiO3 films grown on LaAlO3 substrates. 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 over growth processes and film quality.

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Incorporation of InAs nanostructures in a silicon matrix: growth, structure and optical properties

Cirlin

Polyakov

Petrov

et al. 2001

Materials Science and Engineering: B

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System for recording and analysis of reflection high-energy electron diffraction patterns

Cited by 8 publications

References 6 publications

Big-Data Reflection High Energy Electron Diffraction Analysis for Understanding Epitaxial Film Growth Processes

Big-Data Reflection High Energy Electron Diffraction Analysis for Understanding Epitaxial Film Growth Processes

Machine Learning Analysis of Perovskite Oxides Grown by Molecular Beam Epitaxy

Incorporation of InAs nanostructures in a silicon matrix: growth, structure and optical properties

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