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Perovskite oxides such as LaFeO3 are a well-studied family of materials that possess a wide range of useful and novel properties. Successfully synthesizing perovskite oxide samples usually requires a significant number of growth attempts and a detailed film characterization on each sample to find the optimal growth window of a material. The most common real-time in situ diagnostic technique available during molecular beam epitaxy (MBE) synthesis is reflection high-energy electron diffraction (RHEED). Conventional use of RHEED allows a highly experienced operator to determine growth rate by monitoring intensity oscillations and make some qualitative observations during growth, such as recognizing the sample has become amorphous or recognizing that large islands have formed on the surface. However, due to a lack of theoretical understanding of the diffraction patterns, finer, more precise levels of observations are challenging. To address these limitations, we implement new data analytics techniques in the growth of three LaFeO3 samples on Nb-doped SrTiO3 by MBE. These techniques improve our ability to perform unsupervised machine learning using principal component analysis (PCA) and k-means clustering by using drift correction to overcome sample or stage motion during growth and intensity transformations that highlight more subtle features in the images such as Kikuchi bands. With this approach, we enable the first demonstration of PCA and k-means across multiple samples, allowing for quantitative comparison of RHEED videos for two LaFeO3 film samples. These capabilities set the stage for real-time processing of RHEED data during growth to enable machine learning-accelerated film synthesis. 

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. 

Perovskite oxide heterostructures host a large number of interesting phenomena such as ferroelectricity, which are often driven by octahedral distortions in the crystal that may induce polarization. SrHfO3 (SHO) is a perovskite oxide with a pseudocubic lattice parameter of 4.08 Å that previous density functional theory (DFT) calculations suggest can be stabilized in a ferroelectric P4mm phase when stabilized with sufficient compressive strain. Additionally, it is insulating and possesses a large band gap and a high dielectric constant, making it an ideal candidate for oxide electronic devices. To test the viability of epitaxial strain as a driver of ferroic phase transitions, SHO films were grown by hybrid molecular beam epitaxy (hMBE) with a tetrakis(ethylmethylamino)hafnium(IV) source on GdScO3 and TbScO3 substrates. Strained SHO phases were characterized using X-ray diffraction, X-ray absorption spectroscopy, and scanning transmission electron microscopy to determine the space group of the strained films, with the results compared to those of DFT-optimized models of phase stability versus strain. Contrary to past reports, we find that compressively strained SrHfO3 undergoes octahedral tilt distortions without associated ferroelectric polarization and most likely takes on the I4/mcm phase with the a0a0c– tilt pattern. 

Abstract This study compares the growth cycles and spatial distribution of dust cloud for titania and carbonaceous dusty nanoparticles in capacitively coupled radiofrequency plasmas, with and without the presence of a weak magnetic field of approximately 500 Gauss. Findings on cycle time, growth rate, and spatial distribution of dust cloud are discussed. The growth of nanoparticles in these plasmas is cyclic, with particles reaching their maximum size and subsequently moving out of the plasma, followed by the generation of a new particle growth cycle. The presence of the magnetic field speeds up the growth cycle in both plasma. The magnetic field also makes the spatial distribution of the two dust cloud different from each other. Langmuir probe measurement of the background plasma parameters such as electron temperature and floating potential reveal radial variations in floating potential but not electron temperature. Furthermore, the magnetic field changes the radial variation of floating potential. These measurements, however, are not sufficient to explain why the two dust clouds appear differently. It is possible that the differences occur due to a gradient in the radial distribution of the magnetic field. 

Abstract Molecular beam epitaxy (MBE), a workhorse of the semiconductor industry, has progressed rapidly in the last few decades in the development of novel materials. Recent developments in condensed matter and materials physics have seen the rise of many novel quantum materials that require ultra-clean and high-quality samples for fundamental studies and applications. Novel oxide-based quantum materials synthesized using MBE have advanced the development of the field and materials. In this review, we discuss the recent progress in new MBE techniques that have enabled synthesis of complex oxides that exhibit ‘quantum’ phenomena, including superconductivity and topological electronic states. We show how these techniques have produced breakthroughs in the synthesis of 4d and 5d oxide films and heterostructures that are of particular interest as quantum materials. These new techniques in MBE offer a bright future for the synthesis of ultra-high quality oxide quantum materials. 

In dusty plasma environments, spontaneous growth of nanoparticles from reactive gases has been extensively studied for over three decades, primarily focusing on hydrocarbons and silicate particles. Here, we introduce the growth of titanium dioxide, a wide bandgap semiconductor, as dusty plasma nanoparticles. The resultant particles exhibited a spherical morphology and reached a maximum monodisperse radius of 235 ± 20 nm after growing for 70 s. The particle grew linearly, and the growth displayed a cyclic behavior; that is, upon reaching their maximum radius, the largest particles fell out of the plasma, and the next growth cycle immediately followed. The particles were collected after being grown for different amounts of time and imaged using scanning electron microscopy. Further characterization was carried out using energy dispersive x-ray spectroscopy, x-ray diffraction, and Raman spectroscopy to elucidate the chemical composition and crystalline properties of the maximally sized particles. Initially, the as-grown particles exhibited an amorphous structure after 70 s. However, annealing treatments at temperatures of 400 and 800 °C induced crystallization, yielding anatase and rutile phases, respectively. Annealing at 600 °C resulted in a mixed phase of anatase and rutile. These findings open avenues for a rapid and controlled growth of titanium dioxide via dusty plasma. 

Iron and nickel-based perovskite oxides have proven promising for the oxygen evolution reaction (OER) in alkaline environments, as their catalytic overpotentials rival precious metal catalysts when the band alignment is tuned through substitutional doping or alloying. Here, we report the engineering of band alignment in LaFeO3/LaNiO3 (LFO/LNO) heterostructures via interfacial doping that yields greatly enhanced catalytic performance. The 0.2 eV offset (VBO) between the Fermi level in metallic LNO and the valence band in semiconducting LFO that we predict using density functional theory makes LFO a p-type semiconductor, resulting in significantly lower barriers for hole transport through LFO compared to the intrinsic material. Experimental band alignment measured with in situ x-ray photoelectron spectroscopy of epitaxial LFO/LNO heterostructures confirms these predictions, producing a measured VBO of 0.3(1) eV. Furthermore, OER catalytic measurements on these samples in the alkaline solution show an increase in catalytic current density by a factor of ∼275 compared to LFO grown on n-type Nb-doped SrTiO3. These results demonstrate the power of tuning band alignments through interfacial band engineering for improved catalytic performance of oxides. 

Transition metal spinel oxides comprised of earth-abundant Mn and Co have long been explored for their use in catalytic reactions and energy storage. However, understanding functional properties can be challenging due to differences in sample preparation and the ultimate structural properties of the materials. Epitaxial thin film synthesis provides a novel means of producing precisely controlled materials to explore the variations reported in the literature. In this work, MnxCo3−xO4 samples from x = 0 to x = 1.28 were synthesized through molecular beam epitaxy and characterized to develop a material properties map as a function of stoichiometry. Films were characterized via in situ x-ray photoelectron spectroscopy, x-ray diffraction, scanning transmission electron microscopy, and polarized K-edge x-ray absorption spectroscopy. Mn cations within this range were found to be octahedrally coordinated, in line with an inverse spinel structure. Samples largely show mixed Mn3+ and Mn4+ character with evidence of phase segregation tendencies with the increasing Mn content and increasing Mn3+ formal charge. Phase segregation may occur due to structural incompatibility between cubic and tetragonal crystal structures associated with Mn4+ and Jahn–Teller active Mn3+ octahedra, respectively. Our results help in explaining the reported differences across samples in these promising materials for renewable energy technologies.