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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. 

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 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. 

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. 

4d transition metal oxides have emerged as promising materials for numerous applications including high mobility electronics. SrNbO3 is one such candidate material, serving as a good donor material in interfacial oxide systems and exhibiting high electron mobility in ultrathin films. However, its synthesis is challenging due to the metastable nature of the d1 Nb4+ cation and the limitations in the delivery of refractory Nb. To date, films have been grown primarily by pulsed laser deposition (PLD), but development of a means to grow and stabilize the material via molecular beam epitaxy (MBE) would enable studies of interfacial phenomena and multilayer structures that may be challenging by PLD. To that end, SrNbO3 thin films were grown using hybrid MBE for the first time using a tris(diethylamido)(tert-butylimido) niobium precursor for Nb and an elemental Sr source on GdScO3 substrates. Varying thicknesses of insulating SrHfO3 capping layers were deposited using a hafnium tert-butoxide precursor for Hf on top of SrNbO3 films to preserve the metastable surface. Grown films were transferred in vacuo for x-ray photoelectron spectroscopy to quantify elemental composition, density of states at the Fermi energy, and Nb oxidation state. Ex situ studies by x-ray absorption near edge spectroscopy and scanning transmission electron microscopy illustrate that the SrHfO3 capping plays an important role in preserving the crystalline quality of the material and the Nb 4d1 metastable charge state under atmospheric conditions.