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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$_x$Ti$_{1-x}$O3 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$_x$Ti$_{1-x}$O3 thin films. 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.

Perovskite oxides such as LaFeO$_3$ 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 \textit{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 osciallations 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 LaFeO$_3$ samples on Nb-doped SrTiO$_3$ 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 LaFeO$_3$ film samples. These capabilities set the stage for real-time processing of RHEED data during growth to enable machine learning-accelerated film synthesis., Comment: 8 pages, 7 figures; Supplemental materials available on Zenodo at DOI: 10.5281/zenodo.14649215

The spontaneous bending of core-shell nanowires through asymmetric shell deposition has implications for sensors, enabling both parallel fabrication and creating advantageous out-of-plane nanowire sensor geometries. This study investigates the impact of shell deposition geometry on the shell distribution and bending of GaAs-InP core-shell nanowires. Scanning and transmission electron microscopy methods are employed to quantify nanowire twisting and bending. A practical analytical electron tomography reconstruction technique is developed for characterizing the nanowire shell distribution, which utilizes the hexagonal nanowire shape to reconstruct two-dimensional cross-sections along the nanowire length. The study reveals that the orientation of the phosphorus beam with respect to the nanowire side facets induces significant variations in nanowire bending and twisting. The findings demonstrate the important role of crystallographic orientation during core-shell nanowire synthesis for engineering the shape of bent nanowire sensors., Comment: Corresponding author Ryan B. Lewis --> rlewis@mcmaster.ca

The iterative bleaching extends multiplexity (IBEX) Knowledge-Base is a central portal for researchers adopting IBEX and related 2D and 3D immunofluorescence imaging methods. The design of the Knowledge-Base is modeled after efforts in the open-source software community and includes three facets: a development platform (GitHub), static website, and service for data archiving. The Knowledge-Base facilitates the practice of open science throughout the research life cycle by providing validation data for recommended and non-recommended reagents, e.g., primary and secondary antibodies. In addition to reporting negative data, the Knowledge-Base empowers method adoption and evolution by providing a venue for sharing protocols, videos, datasets, software, and publications. A dedicated discussion forum fosters a sense of community among researchers while addressing questions not covered in published manuscripts. Together, scientists from around the world are advancing scientific discovery at a faster pace, reducing wasted time and effort, and instilling greater confidence in the resulting data.

We present a method whereby the finite element method is used to train physics-informed neural networks that are suitable for surrogate modeling. The method is based on a custom convolutional operation called stencil convolution which leverages the inverse isoparametric map of the finite element method. We demonstrate the performance of the method in several training and testing scenarios with linear boundary-value problems of varying geometries. The resulting neural networks show reasonable accuracy when tested on unseen geometries that are similar to those used for training. Furthermore, when the number of training geometries is increased the testing errors systematically decrease, demonstrating that the neural networks learn how to generalize as the training set becomes larger. Further extending the method to allow for variable boundary conditions, properties, and body forces will lead to a general-purpose surrogate modeling framework that can leverage existing finite element codes for training.

Dense arrays of semiconductor quantum dots are currently employed in highly efficient quantum dot lasers for data communications and other applications. Traditionally, the electronic properties of such quantum nanostructures have been treated as isolated objects, with the degree of hybridization between neighboring quantum dots and the wetting layer left unexplored. Here, we use atom probe tomography and transmission electron microscopy to uncover the three-dimensional composition profile of a high-density ensemble of epitaxial InAs/GaAs quantum dots. The sub-nanometer compositional data is used to construct the 3D local band structure and simulate the electronic eigenstates within the dense quantum dot ensemble using finite element method. This in situ electronic simulation reveals a high degree of hybridization between neighboring quantum dots and the wetting layer, in stark contrast to the usual picture of isolated quantum nanostructures. The simulated transition energies are compared with low temperature photoluminescence. This work has important applications for quantum dot laser design and paves the way to engineering ensemble effects in quantum dot lasers and other quantum nanostructures., Comment: 26 pages, 10 figures

The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microstructural order. Our present understanding is typically derived from laborious manual analysis of imaging and spectroscopy data, which is difficult to scale, challenging to reproduce, and lacks the ability to reveal latent associations needed for mechanistic models. Here, we demonstrate a multi-modal machine learning (ML) approach to describe order from electron microscopy analysis of the complex oxide La$_{1-x}$Sr$_x$FeO$_3$. We construct a hybrid pipeline based on fully and semi-supervised classification, allowing us to evaluate both the characteristics of each data modality and the value each modality adds to the ensemble. We observe distinct differences in the performance of uni- and multi-modal models, from which we draw general lessons in describing crystal order using computer vision., Comment: 30 pages, 5 figures, 2 tables

Perovskite oxides hetero-structures are host to a large number of interesting phenomena such as ferroelectricity and 2D-superconductivity. Ferroelectric perovskite oxides have been of significant interest due to their possible use in MOSFETs and FRAM. SrHfO$_3$ (SHO) is a perovskite oxide with pseudo-cubic lattice parameter of 4.1 $\mathring{A}$ that previous DFT calculations suggest can be stabilized in a ferroelectric P4mm phase, similar to STO, when stabilized with sufficient compressive strain. Additionally, it is insulating, possesses a large band gap, and a high dielectric constant, making it an ideal candidate for oxide electronic devices. In this work, SHO films were grown by hybrid molecular beam epitaxy with a tetrakis(ethylmethylamino)hafnium(IV) source on GdScO$_3$ and TbScO$_3$ substrates. Equilibrium and strained SHO phases were characterized using X-ray diffraction, X-ray absorption spectroscopy, and scanning transmission electron microscopy to determine the perovskite phase of the strained films, with the results compared to density functional theory models of phase stability versus strain. Contrary to past reports, we find that compressively-strained SrHfO$_3$ undergoes octahedral tilt distortions and most likely takes on the I4/mcm phase with the a$^0$a$^0$c$^-$ tilt pattern., Comment: 36 pages, 11 figures

The explosion of artificial intelligence, possible end of Moore's law, dawn of quantum computing and continued exponential growth of data communications traffic have brought new urgency to the need for laser integration on the diversified Si platform. While diode lasers on III-V platforms have long powered internet data communications and other optoelectronic technologies, direct integration with Si remains problematic. A paradigm-shifting solution requires exploring new and unconventional materials and integration approaches. In this work, we show that a sub-10-nm ultra-thin Si$_{1-x}$Ge$_x$ buffer layer fabricated by an oxidative solid-phase epitaxy process can facilitate extraordinarily efficient strain relaxation. The Si$_{1-x}$Ge$_x$ layer is formed by ion implanting Ge into Si(111) and selectively oxidizing Si atoms in the resulting ion-damaged layer, precipitating a fully strain-relaxed Ge-rich layer between the Si substrate and surface oxide. The efficient strain relaxation results from the high oxidation temperature, producing a periodic network of dislocations at the substrate interface, coinciding with modulations of the Ge content in the Si$_{1-x}$Ge$_x$ layer and indicating the presence of defect-mediated diffusion of Si through the layer. The epitaxial growth of high-quality GaAs is demonstrated on this ultra-thin Si$_{1-x}$Ge$_x$ layer, demonstrating a promising new pathway for integrating III-V lasers directly on the Si platform., Comment: 16 pages, 5 figures

Iterative Bleaching Extends multipleXity (IBEX) is a versatile method for highly multiplexed imaging of diverse tissues. Based on open science principles, we created the IBEX Knowledge-Base, a resource for reagents, protocols and more, to empower innovation., Comment: 8 pages, 1 figure, 9 references

Obtaining insight into the constituents of dark matter and their interactions with normal matter has inspired a wide range of experimental efforts. Several approaches, particularly those involving searches for ultralight bosonic dark matter (UBDM) fields, involve the use of quantum systems or measurements performed at the limits imposed by quantum mechanics. While a classical treatment of UBDM and its detectors is satisfactory, a fully quantum description would assist in developing future detection strategies. Here, we present an open quantum systems approach that accomplishes this while providing intuition into the quantum nature of the detection process itself. Furthermore, we apply the quantum theory of optical coherence to characterize the statistical properties of the UBDM field. Using representative examples, we show that this theoretical treatment has implications in uncovering signatures of the cosmological production mechanism of the UBDM field and its galactic merger history. By adapting tools from quantum optics, this work will help facilitate the creation of novel methods to extract astrophysically relevant information from correlation measurements.

The large spin-orbit coupling in iridium oxides plays a significant role in driving novel physical behaviors, including emergent phenomena in the films and heterostructures of perovskite and Ruddlesden-Popper iridates. In this work, we study the role of epitaxial strain on the electronic behavior of thin SrIrO$_3$ films. We find that compressive epitaxial strain leads to metallic transport behavior, but a slight tensile strain shows gapped behavior. Temperature-dependent resistivity measurements are used to examine different behaviors in films as a function of strain. We find Kondo contributions to the resistivity, with stronger effects in films that are thinner and under less compressive epitaxial strain. These results show the potential to tune SrIrO$_3$ into Kondo insulating states and open possibilities for a quantum critical point that can be controlled with strain in epitaxial films., Comment: 13 pages, 4 figures

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.

We characterized the dosimetric properties of a clinical linear accelerator configured to deliver ultra-high dose rate (UHDR) irradiation to mice and cell-culture FLASH radiobiology experiments. UHDR electron beams were controlled by a microcontroller and relay interfaced with the respiratory gating system. We produced beam collimators with indexed stereotactic mouse positioning devices to provide anatomically specific preclinical treatments. Treatment delivery was monitored directly with an ionization chamber, and charge measurements were correlated with radiochromic film at the entry surface of the mice. The setup for conventional (CONV) dose rate irradiation was similar but the source-to-surface distance was longer. Monte Carlo simulations and film dosimetry were used to characterize beam properties and dose distributions. The mean electron beam energies before the flattening filter were 18.8 MeV (UHDR) and 17.7 MeV (CONV), with corresponding values at the mouse surface of 17.2 MeV and 16.2 MeV. The charges measured with an external ion chamber were linearly correlated with the mouse entrance dose. Use of relay gating for pulse control initially led to a delivery failure rate of 20% ($+/-$ 1 pulse); adjustments to account for the linac latency improved this rate to <1/20. Beam field sizes for two anatomically specific mouse collimators (4x4 $cm^2$ for whole-abdomen and 1.5x1.5 $cm^2$ for unilateral lung irradiation) were accurate within <5% and had low radiation leakage (<4%). Normalizing the dose at the center of the mouse (~0.75 cm depth) produced UHDR and CONV doses to the irradiated volumes with >95% agreement. We successfully configured a clinical linear accelerator for increased output and developed a robust preclinical platform for anatomically specific irradiation, with highly accurate and precise temporal and spatial dose delivery, for both CONV and UHDR applications., Comment: Jinghui Wang and Stavros Melemenidis are co-first authors, and Emil Sch\"uler and Peter G. Maxim are co-senior/co-corresponding authors

DNA looping is important in DNA condensation and regulation. One method for forming a DNA loop, thought to be used by the condensing agent protamine, is bind-and-bend. In bind-and-bend, molecules bind all along the DNA, each creating a bend in the DNA. Eventually, enough bending leads to the formation of a loop. Here, we adapt theory for DNA bending by cations to create a simple bind-and-bend model. To test the model, we simulate bending and looping by the condensing agent protamine and compare the output of the simulation to experimental data. The model captures several interesting features of the data including: the curvature of the DNA due to both protamine-induced bending and thermal fluctuations, the small circumference of the loops (200-300 bp), the bias in the location where the loop forms, and the emergence of multi-looped flower structures. The model leads to insight into where protamine binds, how it bends DNA, and how it creates one or more DNA loops. More broadly, the model could be useful in understanding the compaction of nucleic acids or polyelectrolytes., Comment: 27 pages, 13 figures

In dusty plasma environments, the 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 band gap semiconductor, as dusty plasma nanoparticles. The resultant particles exhibited a spherical morphology and reached a maximum homogeneous radius of 230 $\pm$ 17 nm after an elapsed time of 70 seconds. 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 a new 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 after 70 seconds exhibited an amorphous structure. However, annealing treatments at temperatures of 400 $^\circ$C and 800 $^\circ$C induced crystallization, yielding anatase and rutile phases, respectively. Notably, annealing at 600 $^\circ$C resulted in a mixed phase of anatase and rutile. These findings open new avenues for a rapid and controlled growth technique of titanium dioxide as dusty plasma., Comment: 8 pages, 5 figures

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., Comment: 29 pages, 7 figures

The United States has introduced a special humanitarian parole process for Ukrainian citizens in response to Russia 2022 invasion of Ukraine. To qualify for parole, Ukrainian applicants must have a sponsor in the United States. In collaboration with HIAS, a refugee resettlement agency involved in the parole process, we deployed RUTH (Refugees Uniting Through HIAS), a novel algorithmic matching system that is driven by the relocation preferences of refugees and the priorities of US sponsors. RUTH adapts Thakral Multiple-Waitlist Procedure (MWP) that combines the main FIFO queue with location-specific FIFO queues to effectively manage the preferences of refugees and the supply of community sponsors. RUTH also incorporates various feasibility considerations, such as community capacity religious, and medical needs. The adapted mechanism is envy-free, efficient, and strategy-proof for refugees. Our analysis shows diverse refugee location preferences, not fully explained by observables, highlighting the challenge of predicting preferences directly from them. We use our data for two counterfactual simulations. First, we consider the effects of increased waiting times for refugees on the quality of their matches. We find that with a periodic Top Trading Cycles algorithm, increasing period length from 24 days to 80 days improves the average rank of a refugees match from 3.20 to 2.44. Second, we estimate the arrival rates of sponsors in each location that would be consistent with a long-run steady state. We find that more desirable locations (regarding refugee preferences) require the highest arrival rates, suggesting that preferences might be a useful indicator for investments in sponsorship capacity. Our study highlights the potential for preference-based algorithms such as RUTH to improve the efficiency and fairness of other rapidly deployed humanitarian parole processes., Comment: In Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO23), October 30-November 1, 2023, Boston, MA, USA. 34 pages, including an appendix

Methodologies for training machine learning potentials (MLPs) to quantum-mechanical simulation data have recently seen tremendous progress. Experimental data has a very different character than simulated data, and most MLP training procedures cannot be easily adapted to incorporate both types of data into the training process. We investigate a training procedure based on Iterative Boltzmann Inversion that produces a pair potential correction to an existing MLP, using equilibrium radial distribution function data. By applying these corrections to a MLP for pure aluminum based on Density Functional Theory, we observe that the resulting model largely addresses previous overstructuring in the melt phase. Interestingly, the corrected MLP also exhibits improved performance in predicting experimental diffusion constants, which are not included in the training procedure. The presented method does not require auto-differentiating through a molecular dynamics solver, and does not make assumptions about the MLP architecture. The results suggest a practical framework of incorporating experimental data into machine learning models to improve accuracy of molecular dynamics simulations.

Breakthroughs extending nanostructure engineering beyond what is possible with current fabrication techniques will be crucial for enabling next-generation nanotechnologies. Nanoepitaxy of strain-engineered bent nanowire heterostructures presents a promising platform for realizing bottom-up and scalable fabrication of nanowire devices. The synthesis of these structures requires the selective asymmetric deposition of lattice-mismatched shells-a complex growth process which is not well understood. We present the nanoepitaxial growth of GaAs-InP core-shell bent nanowires and connecting nanowire pairs to form nano-arches. Compositional analysis of nanowire cross-sections reveals the critical role of adatom diffusion in the nanoepitaxial growth process, which leads to two distinct growth regimes: indium-diffusion limited growth and phosphorous-limited growth. The highly controllable phosphorous-limited growth mode is employed to synthesize connected nanowire pairs and quantify the role of flux shadowing on the shell growth process. These results provide important insight into three-dimensional nanoepitaxy and enable new possibilities for nanowire device fabrication.

Purpose: Thoracic radiographs are commonly used to evaluate patients with confirmed or suspected thoracic pathology. Proper patient positioning is more challenging in canine and feline radiography than in humans due to less patient cooperation and body shape variation. Improper patient positioning during radiograph acquisition has the potential to lead to a misdiagnosis. Asymmetrical hemithoraces are one of the indications of obliquity for which we propose an automatic classification method. Approach: We propose a hemithoraces segmentation method based on Convolutional Neural Networks (CNNs) and active contours. We utilized the U-Net model to segment the ribs and spine and then utilized active contours to find left and right hemithoraces. We then extracted features from the left and right hemithoraces to train an ensemble classifier which includes Support Vector Machine, Gradient Boosting and Multi-Layer Perceptron. Five-fold cross-validation was used, thorax segmentation was evaluated by Intersection over Union (IoU), and symmetry classification was evaluated using Precision, Recall, Area under Curve and F1 score. Results: Classification of symmetry for 900 radiographs reported an F1 score of 82.8% . To test the robustness of the proposed thorax segmentation method to underexposure and overexposure, we synthetically corrupted properly exposed radiographs and evaluated results using IoU. The results showed that the models IoU for underexposure and overexposure dropped by 2.1% and 1.2%, respectively. Conclusions: Our results indicate that the proposed thorax segmentation method is robust to poor exposure radiographs. The proposed thorax segmentation method can be applied to human radiography with minimal changes., Comment: Submitted to SPIE Journal of Medical Imaging

Bayesian Optimization (BO) links Gaussian Process (GP) surrogates with sequential design toward optimizing expensive-to-evaluate black-box functions. Example design heuristics, or so-called acquisition functions, like expected improvement (EI), balance exploration and exploitation to furnish global solutions under stringent evaluation budgets. However, they fall short when solving for robust optima, meaning a preference for solutions in a wider domain of attraction. Robust solutions are useful when inputs are imprecisely specified, or where a series of solutions is desired. A common mathematical programming technique in such settings involves an adversarial objective, biasing a local solver away from ``sharp'' troughs. Here we propose a surrogate modeling and active learning technique called robust expected improvement (REI) that ports adversarial methodology into the BO/GP framework. After describing the methods, we illustrate and draw comparisons to several competitors on benchmark synthetic exercises and real problems of varying complexity., Comment: 27 pages, 17 figures, 1 table

We present the first experimental observation of K$_{\beta}$ emission from highly charged Mg ions at solid density, driven by intense x-rays from a free electron laser. The presence of K$_{\beta}$ emission indicates the $n=3$ atomic shell is relocalized for high charge states, providing an upper constraint on the depression of the ionization potential. We explore the process of state relocalization in dense plasmas from first principles using finite-temperature density functional theory alongside a wavefunction localization metric, and find excellent agreement with experimental results., Comment: 22 pages, 13 figures

Quantum dot (QD) growth on high ($c_{3v}$) symmetry GaAs{111} surfaces holds promise for efficient entangled photon sources. Unfortunately, homoepitaxy on GaAs{111} surfaces suffers from surface roughness/defects and InAs deposition does not natively support Stranski-Krastanov (SK) QD growth. Surfactants have been identified as effective tools to alter the epitaxial growth process of III-V materials, however, their use remains unexplored on GaAs{111}. Here, we investigate Bi as a surfactant in III-As molecular beam epitaxy (MBE) on GaAs(111)A substrates, demonstrating that Bi can eliminate surface defects/hillocks in GaAs and (Al,Ga)As layers, yielding atomically-smooth hillock-free surfaces with RMS roughness values as low as 0.13 nm. Increasing Bi fluxes are found to result in smoother surfaces and Bi is observed to increase adatom diffusion. The Bi surfactant is also shown to trigger a morphological transition in InAs/GaAs(111)A films, directing the 2D InAs layer to rearrange into 3D nanostructures, which are promising candidates for high-symmetry quantum dots. The desorption activation energy ($U_{Des}$) of Bi on GaAs(111)A was measured by reflection high energy electron diffraction (RHEED), yielding $U_{Des}$ = 1.7 $\pm$ 0.4 eV. These results illustrate the potential of Bi surfactants on GaAs(111)A and will help pave the way for GaAs(111)A as a platform for technological applications including quantum photonics., Comment: 9 pages, 4 figures

We present a novel dual-DBA allocation, with a fast P4-enabled scheduler to provide low latency upstream grant allocations. We show latency reduction of 37% and 43%, respectively, compared to standard and virtual PONs

We provide a real-time demonstration of a low-latency PON DBA mechanism, optimised for virtual PONs. Our implementation mixes P4 programmable data plane and software-based virtual DBA to provide efficient fast-track allocation for low latency applications

GaAs-based nanowires are among the most promising candidates for realizing a monolithical integration of III-V optoelectronics on the Si platform. To realize their full potential for applications as light absorbers and emitters, it is crucial to understand their interaction with light governing the absorption and extraction efficiency, as well as the carrier recombination dynamics determining the radiative efficiency. Here, we study the spontaneous emission of zincblende GaAs/(Al,Ga)As core/shell nanowire arrays by $\mu$-photoluminescence spectroscopy. These ordered arrays are synthesized on patterned Si(111) substrates using molecular beam epitaxy, and exhibit an exceptionally low degree of polytypism for interwire separations exceeding a critical value. We record emission spectra over more than five orders of excitation density for both steady-state and pulsed excitation to identify the nature of the recombination channels. An abrupt Mott transition from excitonic to electron-hole-plasma recombination is observed, and the corresponding Mott density is derived. Combining these experiments with simulations and additional direct measurements of the external quantum efficiency using a perfect diffuse reflector as reference, we are able to extract the internal quantum efficiency as a function of carrier density and temperature as well as the extraction efficiency of the nanowire array. The results vividly document the high potential of GaAs/(Al,Ga)As core/shell nanowires for efficient light emitters integrated on the Si platform. Furthermore, the methodology established in this work can be applied to nanowires of any other materials system of interest for optoelectronic applications.

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 of 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, Mn$_{x}$Co$_{3-x}$O$_{4}$ 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 Mn$^{3+}$ and Mn$^{4+}$ character with evidence of phase segregation tendencies with increasing Mn content and increasing Mn$^{3+}$ formal charge. Phase segregation may occur due to structural incompatibility between cubic and tetragonal crystal structures associated with Mn$^{4+}$ and Jahn-Teller active Mn$^{3+}$ octahedra, respectively. Our results help to explain the reported differences across samples in these promising materials for renewable energy technologies., Comment: 25 pages, 8 figures; Supplemental info and figures, 9 pages

The canonical technique for nonlinear modeling of spatial/point-referenced data is known as kriging in geostatistics, and as Gaussian Process (GP) regression for surrogate modeling and statistical learning. This article reviews many similarities shared between kriging and GPs, but also highlights some important differences. One is that GPs impose a process that can be used to automate kernel/variogram inference, thus removing the human from the loop. The GP framework also suggests a probabilistically valid means of scaling to handle a large corpus of training data, i.e., an alternative to so-called ordinary kriging. Finally, recent GP implementations are tailored to make the most of modern computing architectures such as multi-core workstations and multi-node supercomputers. We argue that such distinctions are important even in classically geostatistical settings. To back that up, we present out-of-sample validation exercises using two, real, large-scale borehole data sets involved in the mining of gold and other minerals. We pit classic kriging against the modern GPs in several variations and conclude that the latter can more economical (fewer human and compute resources), more accurate and offer better uncertainty quantification. We go on to show how the fully generative modeling apparatus provided by GPs can gracefully accommodate left-censoring of small measurements, as commonly occurs in mining data and other borehole assays., Comment: 35 pages, 13 figures

Transition metal oxides have generated significant interest for their potential as catalysts for the oxygen evolution reaction (OER) in alkaline environments. Iron and nickel-based perovskite oxides have proven particularly promising, with catalytic over-potentials rivaling precious metal catalysts when the alignment of the valence band relative to the OER reaction potential is tuned through substitutional doping or alloying. Here we report that engineering of band alignment in LaFeO$_{3}$/LaNiO$_{3}$ (LFO/LNO) heterostructures via interfacial doping yields greatly enhanced catalytic performance. Using density functional theory modeling, we predict a 0.2 eV valence band offset (VBO) between metallic LNO and semiconducting LFO that significantly lowers the barrier for hole transport through LFO compared to the intrinsic material and make LFO a p-type semiconductor. Experimental band alignment measurements using in situ X-ray photoelectron spectroscopy of epitaxial LFO/LNO heterostructures agree quite well with these predictions, producing a measured VBO of 0.3(1) eV. OER catalytic measurements on the same samples in alkaline solution show an increase in catalytic current density by a factor of ~275 compared to LFO grown on n-type Nb-doped SrTiO$_{3}$. These results demonstrate the power of tuning band alignments through interfacial band engineering for improved catalytic, Comment: 13 pages, 5 figures; Supplemental info: 5 pages, 5 figures

While many physical processes are non-equilibrium in nature, the theory and modeling of such phenomena lag behind theoretical treatments of equilibrium systems. The diversity of powerful theoretical tools available to describe equilibrium systems has inspired strategies that map non-equilibrium systems onto equivalent equilibrium analogs so that interrogation with standard statistical mechanical approaches is possible. In this work, we revisit the mapping from the non-equilibrium random sequential addition process onto an equilibrium multi-component mixture via the replica method, allowing for theoretical predictions of non-equilibrium structural quantities. We validate the above approach by comparing the theoretical predictions to numerical simulations of random sequential addition., Comment: 32 pages, 3 figures

Nanocrystalline MnFe$_{2}$O$_{4}$ has shown promise as a catalyst for the oxygen reduction reaction (ORR) in alkaline solutions, but the material has been lightly studied as highly ordered thin film catalysts. To examine the role of surface termination and Mn and Fe site occupancy, epitaxial MnFe$_{2}$O$_{4}$ and Fe$_{3}$O$_{4}$ spinel oxide films were grown on (001) and (111) oriented Nb:SrTiO$_{3}$ perovskite substrates using molecular beam epitaxy and studied as electrocatalysts for the oxygen reduction reaction (ORR). HRXRD and XPS show synthesis of pure phase materials while STEM and RHEED analysis demonstrate island-like growth of (111) surface terminated pyramids on both (001) and (111) oriented substrates, consistent with the literature and attributed to lattice mismatch between the spinel films and perovskite substrate. Cyclic voltammograms under an N$_{2}$ atmosphere revealed distinct redox features for Mn and Fe surface termination based on comparison of MnFe$_{2}$O$_{4}$ and Fe$_{3}$O$_{4}$. Under O$_{2}$ atmosphere, electrocatalytic reduction of oxygen was observed at both Mn and Fe redox features; however, diffusion limited current was only achieved at potentials consistent with Fe reduction. This result contrasts with that of nanocrystalline MnFe$_{2}$O$_{4}$ reported in the literature where diffusion limited current is achieved with Mn-based catalysis. This difference is attributed to a low density of Mn surface termination, as determined by the integration of current from CVs collected under N$_{2}$, in addition to low conductivity through the MnFe$_{2}$O$_{4}$ film due to the degree of inversion. Such low densities are attributed to the synthetic method and island-like growth pattern and highlight challenges in studying ORR catalysis with single-crystal spinel materials., Comment: 26 pages, 10 figures; 16 supplemental figures

4d transition metal oxides have emerged as promising materials for numerous applications including high mobility electronics. SrNbO$_{3}$ 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 d$^{1}$ Nb$^{4+}$ 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, SrNbO$_{3}$ thin films were grown using hybrid MBE for the first time using a tris(diethalamido)(tert-butylimido) niobium precursor for Nb and an elemental Sr source on GdScO$_{3}$ substrates. Varying thicknesses of insulating SrHfO$_{3}$ capping layers were deposited using a hafnium tert-butoxide precursor for Hf on top of SrNbO$_{3}$ 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 spectra illustrates the SrHfO$_{3}$ capping plays an important role in preserving the Nb 4d$^{1}$ metastable charge state in atmospheric conditions., Comment: 11 pages, 5 figures; 3 pages of supplemental information

Transition metal oxides have long been an area of interest for water electrocatalysis through the oxygen evolution and oxygen reduction reactions. Iron oxides, such as LaFeO$_{3}$, are particularly promising due to the favorable energy alignment of the valence and conduction bands comprised of Fe$^{3+}$ cations and the visible light band gap of such materials. In this work, we examine the role of band alignment on the electrocatalytic oxygen evolution reaction (OER) in the intrinsic semiconductor LaFeO$_{3}$ by growing epitaxial films of varying thicknesses on Nb-doped SrTiO$_{3}$. Using cyclic voltammetry and electrochemical impedance spectroscopy, we find that there is a strong thickness dependence on the efficiency of electrocatalysis for OER. These measurements are understood based on interfacial band alignment in the system as confirmed by layer-resolved electron energy loss spectroscopy and electrochemical Mott-Schottky measurements. Our results demonstrate the importance of band engineering for the rational design of thin film electrocatalysts for renewable energy sources., Comment: 19 pages, 6 figures; authors Burton and Paudel contributed equally; supplement: 11 pages, 7 figures

Core-shell nanowire heterostructures form the basis for many innovative devices. When compound nanowire shells are grown by directional deposition techniques, the azimuthal position of the sources for the different constituents in the growth reactor, substrate rotation, and nanowire self-shadowing inevitably lead to sequential deposition. Here, we uncover for In$_{0.15}$Ga$_{0.85}$As/GaAs shell quantum wells grown by molecular beam epitaxy a drastic impact of this sequentiality on the luminescence efficiency. The photoluminescence intensity of shell quantum wells grown with a flux sequence corresponding to migration enhanced epitaxy, i. e. when As and the group-III metals essentially do not impinge at the same time, is more than two orders of magnitude higher than for shell quantum wells prepared with substantially overlapping fluxes. Transmission electron microscopy does not reveal any extended defects explaining this difference. Our analysis of photoluminescence transients shows that co-deposition has two detrimental microscopic effects. First, a higher density of electrically active point defects leads to internal electric fields reducing the electron-hole wave function overlap. Second, more point defects form that act as nonradiative recombination centers. Our study demonstrates that the source arrangement of the growth reactor, which is of mere technical relevance for planar structures, can have drastic consequences for the materials properties of nanowire shells. We expect that this finding holds also for other alloy nanowire shells.

Freestanding semiconductor nanowires have opened up new possibilities for semiconductor devices, enabling geometries, material combinations and strain states which were not previously possible. Along these lines, spontaneous bending in asymmetric core-shell nanowire heterostructures has recently been proposed as a means to realize previously unimagined device geometries, novel strain-gradient engineering and bottom-up device fabrication. The synthesis of these nanostructures exploits the nanowire geometry and the directionality of the shell deposition process. Here, we explore the underlying mechanisms of this bending process by modeling the evolution of nanowires during asymmetric shell deposition. We show how bending can lead to dramatic local shell thickness, curvature and strain variations along the length of the nanowire, and we elucidate the dependence of shell growth and bending on parameters such as the core and shell dimensions and materials, and angle of incidence of the deposition source. In addition, deposition shadowing by neighboring nanowires is explored. We show that shadowing can easily be employed to connect nanowire pairs, which could be used to fabricate novel nanowire sensors. Model results are compared with GaAs-InP and GaAs-(Al,In)As core-shell nanowire growth experiments. These results can be used to guide future experiments and to help pave the way to bent nanowire devices.

The high cost of density functional theory has hitherto limited the ab initio prediction of equation of state (EOS). In this article, we employ a combination of large scale computing, advanced simulation techniques, and smart data science strategies to provide an unprecedented, ab initio performance analysis of the high explosive pentaerythritol tetranitrate (PETN). Comparison to both experiment and thermochemical predictions reveals important quantitative limitations of DFT for EOS prediction, and thus the assessment of high explosives. In particular, we find DFT predicts the energy of PETN detonation products to be systematically too high relative to the unreacted neat crystalline material, resulting in an underprediction of the detonation velocity, pressure, and temperature at the Chapman-Jouguet (CJ) state. The energetic bias can be partially accounted for by high-level electronic structure calculations of the product molecules. We also demonstrate a modeling strategy for mapping chemical composition across a wide parameter space with limited numerical data, the results of which suggest additional molecular species to consider in thermochemical modeling., Comment: 16 pages, 8 figures

DNA in sperm cells must undergo an extreme compaction to almost crystalline packing levels. To produce this dense packing, DNA is condensed by protamine, a positively charged protein that loops the DNA into a toroid. Our goal is to determine the pathway and mechanism for toroid formation. We first imaged short-length (L=217-1023 nm) DNA molecules in 0-5.0 $\mu$M protamine using an atomic force microscope (AFM). At low protamine concentrations (0.2-0.6 $\mu$M), molecules dramatically condensed, folding into a flower structure. Dynamic folding measurements of the DNA using a tethered particle motion (TPM) assay revealed a corresponding, initial folding event, which was >3 loops at L=398 nm. The initial folding event was made up of smaller (<1 loop) events that had similar dynamics as protamine-induced bending. This suggests that flowers form in an initial step as protamine binds and bends the DNA. It was not until higher protamine concentrations (>2 $\mu$M) that DNA in the AFM assay formed small (<10 loop), vertically packed toroids. Taken together, these results lead us to propose a nucleation-growth model of toroid formation that includes a flower intermediate. This pathway is important in both in vivo DNA condensation and in vitro engineering of DNA nanostructures., Comment: 24 pages and 7 figures in main article, 15 pages and 9 figures in supplemental

The fundamental interactions between an edge dislocation and a random solid solution are studied by analyzing dislocation line roughness profiles obtained from molecular dynamics simulations of Fe0.70Ni0.11 Cr0.19 over a range of stresses and temperatures. These roughness profiles reveal the hallmark features of a depinning transition. Namely, below a temperature-dependent critical stress, the dislocation line exhibits roughness in two different length scale regimes which are divided by a so-called correlation length. This correlation length increases with applied stress and at the critical stress (depinning transition or yield stress) formally goes to infinity. Above the critical stress, the line roughness profile converges to that of a random noise field. Motivated by these results, a physical model is developed based on the notion of coherent line bowing over all length scales below the correlation length. Above the correlation length, the solute field prohibits such coherent line bow outs. Using this model, we identify potential gaps in existing theories of solid solution strengthening and show that recent observations of length-dependent dislocation mobilities can be rationalized., Comment: 25 pages, 12 figures

We present a dislocation density-based strain hardening model for single crystal copper through a systematic coarse-graining analysis of more than 200 discrete dislocation dynamics (DDD) simulations of plastic deformation under uniaxial tension. The proposed constitutive model has two components: a generalized Taylor relation connecting resolved shear stresses to dislocation densities on individual slip systems, and a generalized Kocks-Mecking model for dislocation multiplication. The DDD data strongly suggests a logarithmic dependence of flow stress on the plastic shear strain rate on each slip system, and, equivalently, an exponential dependence of the plastic shear strain rate on the resolved shear stress. Hence the proposed generalized Taylor relation subsumes the Orowan relation for plastic flow. The DDD data also calls for a correction to the Kocks-Mecking model of dislocation multiplication to account for the increase of dislocation density on slip systems with negligible plastic shear strain rate. This is accomplished by allowing the multiplication rate on each slip system to include contributions from the plastic strain rates of the two coplanar slip systems. The resulting constitutive model successfully captures the strain hardening rate dependence on the loading orientation as predicted by the DDD simulations, which is also consistent with existing experiments.

Emergent behavior at complex oxide interfaces has driven much of the research in the oxide thin film community for the past twenty years. Interfaces have been engineered for potential applications in spintronics, topological quantum computing, and high-speed electronics in cases where the bulk materials would not exhibit the desired properties. Advances in thin film growth have made the synthesis of these interfaces possible, while surface characterization tools such as X-ray photoelectron spectroscopy have been critical to understanding surface and interfacial phenomena in these materials. In this review we discuss the leading research in the oxide field over the past 5-10 years with a focus on connecting the key results to the X-ray photoelectron spectroscopy studies that enabled them. We describe how in situ integration of synthesis and spectroscopy can be used to improve the film growth process and to perform immediate experiments on specifically tailored interfacial heterostructures. These studies can include determination of interfacial intermixing, valence band alignment, and interfacial charge transfer. We also show how advances in synchrotron-based spectroscopy techniques have answered questions that cannot be addressed in a lab-based system. By further tying together synthesis and spectroscopy through in situ techniques, we conclude by discussing future opportunities in the field through the careful design of thin film heterostructures that are optimized for X-ray studies., Comment: 31 pages, 12 figures

The role of bremsstrahlung in the emission from hot accretion flows around slowly accreting supermassive black holes is not thoroughly understood. In order to appraise the importance of bremsstrahlung relative to other radiative processes, we compute spectral energy distributions (SEDs) of accretion disks around slowly accreting supermassive black holes including synchrotron radiation, inverse Compton scattering, and bremsstrahlung. We compute SEDs for (i) four axisymmetric radiative general relativistic magnetohydrodynamics (RadGRMHD) simulations of $10^{8}M_{\odot}$ black holes with accretion rates between $10^{-8}\dot{M}_{\text{Edd}}$ and $10^{-5}\dot{M}_{\text{Edd}}$, (ii) four axisymmetric RadGRMHD simulations of M87$^\ast$ with varying dimensionless spin $a_\ast$ and black hole mass, and (iii) a 3D GRMHD simulation scaled for Sgr A$^\ast$. At $10^{-8}\dot{M}_{\text{Edd}}$, most of the luminosity is synchrotron radiation, while at $10^{-5}\dot{M}_{\text{Edd}}$ the three radiative processes have similar luminosities. In most models, bremsstrahlung dominates the SED near $512\text{ keV}$. In the M87$^\ast$ models, bremsstrahlung dominates this part of the SED if $a_{\ast} = 0.5$, but inverse Compton scattering dominates if $a_{\ast}= 0.9375$. Since scattering is more variable than bremsstrahlung, this result suggests that $512\text{ keV}$ variability could be a diagnostic of black hole spin. In the appendix, we compare some bremsstrahlung formulae found in the literature., Comment: 10 pages, 5 figures, accepted for publication in ApJ

Realistic synthetic observations of theoretical source models are essential for our understanding of real observational data. In using synthetic data, one can verify the extent to which source parameters can be recovered and evaluate how various data corruption effects can be calibrated. These studies are important when proposing observations of new sources, in the characterization of the capabilities of new or upgraded instruments, and when verifying model-based theoretical predictions in a comparison with observational data. We present the SYnthetic Measurement creator for long Baseline Arrays (SYMBA), a novel synthetic data generation pipeline for Very Long Baseline Interferometry (VLBI) observations. SYMBA takes into account several realistic atmospheric, instrumental, and calibration effects. We used SYMBA to create synthetic observations for the Event Horizon Telescope (EHT), a mm VLBI array, which has recently captured the first image of a black hole shadow. After testing SYMBA with simple source and corruption models, we study the importance of including all corruption and calibration effects. Based on two example general relativistic magnetohydrodynamics (GRMHD) model images of M87, we performed case studies to assess the attainable image quality with the current and future EHT array for different weather conditions. The results show that the effects of atmospheric and instrumental corruptions on the measured visibilities are significant. Despite these effects, we demonstrate how the overall structure of the input models can be recovered robustly after performing calibration steps. With the planned addition of new stations to the EHT array, images could be reconstructed with higher angular resolution and dynamic range. In our case study, these improvements allowed for a distinction between a thermal and a non-thermal GRMHD model based on salient features in reconstructed images., Comment: 20 pages, 15 figures, accepted for publication in A&A

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 SrTiO$_{3}$ growths, heteroepitaxial SrTiO$_{3}$ grown on scandate substrates, BaSnO$_{3}$ films grown on SrTiO$_{3}$ substrates, and LaNiO$_{3}$ films grown on LaAlO$_{3}$ 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., Comment: 12 pages, 12 figures

Hybrid oxide molecular beam epitaxy (hMBE), a thin-film deposition technique in which transition metal cations are delivered using a metal-organic precursor, has emerged as the state-of-the-art approach to the synthesis of electronic-grade complex oxide films with a stoichiometric growth window. However, numerous questions remain regarding the chemical mechanisms of the growth process and the surface properties of the resulting films. To examine these properties, thin film SrTiO$_{3}$ (STO) was prepared by hMBE using a titanium tetraisopropoxide (TTIP) precursor for Ti delivery and an elemental Sr source on annealed STO and Nb-doped STO substrates with varying TTIP:Sr flux ratios to examine the conditions for the reported stoichiometric growth window. The films were transferred in vacuo to an x-ray photoelectron spectroscopy system to study the surface elemental composition. Samples were examined using x-ray diffraction to compare our surface sensitive results with previously reported measurements of the bulk of the films in the literature. Ex situ studies by atomic force microscopy, scanning tunneling microscopy and low energy electron microscopy confirmed the presence of surface reconstructions and an Ehrlich-Schwoebel barrier consistent with an A-site SrO termination. We find that a surface exhibiting a mixture of SrO and TiO$_{2}$ termination, or a full SrO termination is necessary to obtain stoichiometric adsorption-controlled growth. These results indicate that surface Sr is necessary to maintain chemical equilibrium for stoichiometric growth during the hMBE process, which is important for the design of future interfacial systems using this technique., Comment: 37 pages, 6 figures, 10 supplemental figures

Functional soft materials, comprising colloidal and molecular building blocks that self-organize into complex structures as a result of their tunable interactions, enable a wide array of technological applications. Inverse methods provide systematic means for navigating their inherently high-dimensional design spaces to create materials with targeted properties. While multiple physically motivated inverse strategies have been successfully implemented in silico, their translation to guiding experimental materials discovery has thus far been limited to a handful of proof-of-concept studies. In this Perspective, we discuss recent advances in inverse methods for design of soft materials that address two challenges: (1) methodological limitations that prevent such approaches from satisfying design constraints and (2) computational challenges that limit the size and complexity of systems that can be addressed. Strategies that leverage machine learning have proven particularly effective, including methods to discover order parameters that characterize complex structural motifs and schemes to efficiently compute macroscopic properties from the underlying structure. We also highlight promising opportunities to improve the experimental realizability of materials designed computationally, including discovery of materials with functionality at multiple thermodynamic states, design of externally directed assembly protocols that are simple to implement in experiments, and strategies to improve the accuracy and computational efficiency of experimentally relevant models.

We report on the direct correlation between the structural and optical properties of single, as-grown core-multi-shell GaAs/In$_{0.15}$Ga$_{0.85}$As/GaAs/AlAs/GaAs nanowires. Fabricated by molecular beam epitaxy on a pre-patterned Si(111) substrate, on a row of well separated nucleation sites, it was possible to access individual nanowires in the as-grown geometry. The polytype distribution along the growth axis of the nanowires was revealed by synchrotron-based nanoprobe X-ray diffraction techniques monitoring the axial 111 Bragg reflection. For the same nanowires, the spatially-resolved emission properties were obtained by cathodoluminescence hyperspectral linescans in a scanning electron microscope. Correlating both measurements, we reveal a blueshift of the shell quantum well emission energy combined with an increased emission intensity for segments exhibiting a mixed structure of alternating wurtzite and zincblende stacking compared with the pure crystal polytypes. The presence of this mixed structure was independently confirmed by cross-sectional transmission electron microscopy., Comment: This is an author-created, un-copyedited version of an article published in Nanotechnology. IOP Publishing Ltd. is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at https://doi.org/10.1088/1361-6528/ab7590

Rare-earth based lasing action in GaN semiconductor at the telecommunication wavelength of 1.5 micron has been demonstrated at room temperature. We have reported the stimulated emission under the above bandgap excitation from Er doped GaN epilayers prepared by metal-organic chemical vapor deposition. Using the variable stripe technique, the observation of the stimulated emission has been demonstrated through characteristic features of threshold behavior of emission intensity as functions of pump intensity, excitation length, and spectral linewidth narrowing. Using the variable stripe setup, the optical gain up to 75 cm-1 has been obtained in the GaN:Er epilayers. The near infrared lasing from GaN semiconductor opens up new possibilities for extended functionalities and integration capabilities for optoelectronic devices., Comment: 9 pages, 3 figures

Core-shell GaAs-based nanowires monolithically integrated on Si constitute a promising class of nanostructures that could enable light emitters for fast inter- and intrachip optical connections. We introduce and fabricate a novel coaxial GaAs/(In,Ga)As dot-in-a-well nanowire heterostructure to reach spontaneous emission in the Si transparent region, which is crucial for applications in Si photonics. Specifically, we achieve room temperature emission at 1.27 $\mu$m in the telecommunication O band. The presence of quantum dots in the heterostructure is evidenced by a structural analysis based on scanning transmission electron microscopy. The spontaneous emission of these nanowire structures is investigated by cathodoluminescence and photoluminescence spectroscopy. Thermal redistribution of charge carriers to larger quantum dots explains the long wavelength emission achieved at room temperature. Finally, in order to demonstrate the feasibility of the presented nanowire heterostructures as electrically driven light emitters monolithically integrated on Si, a light emitting diode is fabricated exhibiting room-temperature electroluminescence at 1.26 $\mu$m., Comment: This document is the unedited Author's version of a Submitted Work that was subsequently accepted for publication in ACS Applied Nano Materials (2019), copyright (C) American Chemical Society after peer review. To access the final edited and published work see this https://doi.org/10.1021/acsanm.9b01866, the supporting information is available (free of charge) under the same link