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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

Self Driving Labs (SDLs) that combine automation of experimental procedures with autonomous decision making are gaining popularity as a means of increasing the throughput of scientific workflows. The task of identifying quantities of supplied colored pigments that match a target color, the color matching problem, provides a simple and flexible SDL test case, as it requires experiment proposal, sample creation, and sample analysis, three common components in autonomous discovery applications. We present a robotic solution to the color matching problem that allows for fully autonomous execution of a color matching protocol. Our solution leverages the WEI science factory platform to enable portability across different robotic hardware, the use of alternative optimization methods for continuous refinement, and automated publication of results for experiment tracking and post-hoc analysis.

Fires and burning are the chief causes of particulate matter (PM2.5), a key measurement of air quality in communities and cities worldwide. This work develops a live fire tracking platform to show active reported fires from over twenty cities in the U.S., as well as predict their smoke paths and impacts on the air quality of regions within their range. Specifically, our close to real-time tracking and predictions culminates in a digital twin to protect public health and inform the public of fire and air quality risk. This tool tracks fire incidents in real-time, utilizes the 3D building footprints of Austin to simulate smoke outputs, and predicts fire incident smoke falloffs within the complex city environment. Results from this study include a complete fire and smoke digital twin model for Austin. We work in cooperation with the City of Austin Fire Department to ensure the accuracy of our forecast and also show that air quality sensor density within our cities cannot validate urban fire presence. We additionally release code and methodology to replicate these results for any city in the world. This work paves the path for similar digital twin models to be developed and deployed to better protect the health and safety of citizens., Comment: 8 pages, 8 figures, conference

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.

Language models are not accurate in numerical problems. Their architecture does not allow for anything less than a probabilistic next word. This paper introduces ComputeGPT: an approach of creating a chat model able to answer computational problems through running on-demand code. ComputeGPT converts each question to relevant code, runs the code, and returns the computed answer as part of the chat. We combine this approach with a local browser-based Python interpretation and fine-tuned prompts in order to achieve state-of-the-art efficiency on numerical problems and provide a suitable front-end and safe environment for the code to be executed in., Comment: 12 pages, 2 figures

There are 1.1 million English learner (EL) students in California, representing 18 percent of the statewide student population (California Department of Education [CDE], 2021b). Following some background on California's standards-aligned instructional materials and on the state's EL student population, this brief summarizes California findings from a nationwide survey on teachers' perceptions of their instructional materials for EL students. The brief highlights teachers' views on the adequacy of their instructional materials for their EL students, how they address any inadequacies, whether the materials help them to provide culturally relevant instruction, and what value they place on particular elements of the materials. Finally, the discussion section of the brief includes implications for improving materials and for strengthening professional learning.

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

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.

This knowledge brief is part of a continuing series designed to inform California education leaders about key policy issues related to teachers and teaching in the Golden State. The brief outlines the current policy environment surrounding math instruction in California, summarizes California information from a nationwide teacher survey on teachers' experiences with professional learning during the 2019/20 school year, and highlights options for instructional supports for California math teachers.

This knowledge brief is part of a continuing series designed to inform California education leaders about new research findings on key state policy topics. To better understand the reopening planning process and other issues related to education during the pandemic, WestEd conducted telephone interviews with County Office of Education (COE) leaders from five different counties about how school closures due to COVID-19 impacted their work with districts and schools. The five COE leaders who were interviewed for this brief represent different corners of the state: Tehama, Tulare, Orange, Napa, and Placer counties. Across these counties, common themes emerged throughout the interviews around how COVID-19 has impacted COE work with schools and districts. Most notably, the school closures have changed how COEs and local educational agencies (LEAs) collaborate and communicate with each other, with their students and their families, and with service providers. To place these findings from California in a national context, the authors of this brief also analyzed data from RAND's 2020 American Educator Panels, the American School Leader Panel (ASLP) and the American Teacher Panel (ATP) surveys. Although responses from California teachers cannot yet be isolated in these data, the ASLP and ATP results are among the first large-scale survey data releases to include responses to COVID-related questions, providing a glimpse into how school leaders and teachers in the United States are viewing the issues that WestEd researchers discussed with COE leaders.

California public schools enroll some 1.2 million students who are classified as English learners (ELs), representing a little more than 19 percent of the statewide student population. Given the size of this population and given the state's efforts over the last decade to recommend to districts materials lists for high-quality, standards-aligned materials for all students, education leaders need to understand teachers' perceptions of the quality and suitability of materials available for use with their EL students. This information can help inform the provision of differentiated supports that meet the needs of schools, teachers, and learners across the Golden State. This brief, produced by the CA Analysis for Learning & Engagement (CALE) project, summarizes survey data about California teachers' views of and experience instructional materials in relation to their EL students. It draws from a survey that included items about subject-matter materials in general, along with items about the cultural relevance and linguistic appropriateness of the materials, digital materials, and teachers' modification of materials for EL students. To place California's results in a national context, the authors also compared California's subject-specific teacher responses to those of teachers in other states who responded to the same survey.

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.

Satellite imagery analytics have numerous human development and disaster response applications, particularly when time series methods are involved. For example, quantifying population statistics is fundamental to 67 of the 231 United Nations Sustainable Development Goals Indicators, but the World Bank estimates that over 100 countries currently lack effective Civil Registration systems. To help address this deficit and develop novel computer vision methods for time series data, we present the Multi-Temporal Urban Development SpaceNet (MUDS, also known as SpaceNet 7) dataset. This open source dataset consists of medium resolution (4.0m) satellite imagery mosaics, which includes 24 images (one per month) covering >100 unique geographies, and comprises >40,000 km2 of imagery and exhaustive polygon labels of building footprints therein, totaling over 11M individual annotations. Each building is assigned a unique identifier (i.e. address), which permits tracking of individual objects over time. Label fidelity exceeds image resolution; this "omniscient labeling" is a unique feature of the dataset, and enables surprisingly precise algorithmic models to be crafted. We demonstrate methods to track building footprint construction (or demolition) over time, thereby directly assessing urbanization. Performance is measured with the newly developed SpaceNet Change and Object Tracking (SCOT) metric, which quantifies both object tracking as well as change detection. We demonstrate that despite the moderate resolution of the data, we are able to track individual building identifiers over time. This task has broad implications for disaster preparedness, the environment, infrastructure development, and epidemic prevention., Comment: 8 pages, 10 figures, 3 tables

RarePlanes is a unique open-source machine learning dataset that incorporates both real and synthetically generated satellite imagery. The RarePlanes dataset specifically focuses on the value of synthetic data to aid computer vision algorithms in their ability to automatically detect aircraft and their attributes in satellite imagery. Although other synthetic/real combination datasets exist, RarePlanes is the largest openly-available very-high resolution dataset built to test the value of synthetic data from an overhead perspective. Previous research has shown that synthetic data can reduce the amount of real training data needed and potentially improve performance for many tasks in the computer vision domain. The real portion of the dataset consists of 253 Maxar WorldView-3 satellite scenes spanning 112 locations and 2,142 km^2 with 14,700 hand-annotated aircraft. The accompanying synthetic dataset is generated via AI.Reverie's simulation platform and features 50,000 synthetic satellite images simulating a total area of 9331.2 km^2 with ~630,000 aircraft annotations. Both the real and synthetically generated aircraft feature 10 fine grain attributes including: aircraft length, wingspan, wing-shape, wing-position, wingspan class, propulsion, number of engines, number of vertical-stabilizers, presence of canards, and aircraft role. Finally, we conduct extensive experiments to evaluate the real and synthetic datasets and compare performances. By doing so, we show the value of synthetic data for the task of detecting and classifying aircraft from an overhead perspective., Comment: To appear in WACV 2021 - 11 pages

Within the remote sensing domain, a diverse set of acquisition modalities exist, each with their own unique strengths and weaknesses. Yet, most of the current literature and open datasets only deal with electro-optical (optical) data for different detection and segmentation tasks at high spatial resolutions. optical data is often the preferred choice for geospatial applications, but requires clear skies and little cloud cover to work well. Conversely, Synthetic Aperture Radar (SAR) sensors have the unique capability to penetrate clouds and collect during all weather, day and night conditions. Consequently, SAR data are particularly valuable in the quest to aid disaster response, when weather and cloud cover can obstruct traditional optical sensors. Despite all of these advantages, there is little open data available to researchers to explore the effectiveness of SAR for such applications, particularly at very-high spatial resolutions, i.e. <1m Ground Sample Distance (GSD). To address this problem, we present an open Multi-Sensor All Weather Mapping (MSAW) dataset and challenge, which features two collection modalities (both SAR and optical). The dataset and challenge focus on mapping and building footprint extraction using a combination of these data sources. MSAW covers 120 km^2 over multiple overlapping collects and is annotated with over 48,000 unique building footprints labels, enabling the creation and evaluation of mapping algorithms for multi-modal data. We present a baseline and benchmark for building footprint extraction with SAR data and find that state-of-the-art segmentation models pre-trained on optical data, and then trained on SAR (F1 score of 0.21) outperform those trained on SAR data alone (F1 score of 0.135)., Comment: To appear in CVPR EarthVision Proceedings, 10 pages, 7 figures

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

Identification of road networks and optimal routes directly from remote sensing is of critical importance to a broad array of humanitarian and commercial applications. Yet while identification of road pixels has been attempted before, estimation of route travel times from overhead imagery remains a novel problem, particularly for off-nadir overhead imagery. To this end, we extract road networks with travel time estimates from the SpaceNet MVOI dataset. Utilizing the CRESIv2 framework, we demonstrate the ability to extract road networks in various observation angles and quantify performance at 27 unique nadir angles with the graph-theoretic APLS_length and APLS_time metrics. A minimal gap of 0.03 between APLS_length and APLS_time scores indicates that our approach yields speed limits and travel times with very high fidelity. We also explore the utility of incorporating all available angles during model training, and find a peak score of APLS_time = 0.56. The combined model exhibits greatly improved robustness over angle-specific models, despite the very different appearance of road networks at extremely oblique off-nadir angles versus images captured from directly overhead., Comment: 4 pages, 5 figures. To appear at the 2020 IEEE International Geoscience and Remote Sensing Symposium

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

We explore the Bi-surfactant-directed self-assembly and structure of InAs quantum dots grown on GaAs(110) by molecular beam epitaxy. The addition of a Bi flux during InAs deposition changes the InAs growth mode from two-dimensional (2D) Frank-van der Merwe to Stranski-Krastanov, resulting in the formation of three-dimensional (3D) InAs islands on the surface. Furthermore, exposing static InAs 2D layers to Bi induces a rearrangement of the strained layer into 3D islands. We explore the effect of varying the InAs thickness and Bi flux for these two growth approaches, observing a critical thickness for 3D island formation in both cases. Characterization of (110) InAs quantum dots with high-resolution transmission electron microscopy reveals that larger islands grown by the Stranski-Krastanov mode are plastically relaxed, while small islands grown by the on-demand approach are coherent. Strain relaxation along the [1-10] direction is achieved by 90 degree pure-edge dislocations with dislocation lines running along [001]. In contrast, strain relief along [001] is by 60 degree misfit dislocations. This behaviour is consistent with observations of planar (In,Ga)As/GaAs(110) layers. These results illustrate how surfactant Bi can provoke and control quantum dot formation where it normally does not occur.

Bi-containing III-V semiconductors constitute an exciting class of metastable compounds with wide-ranging potential optoelectronic and electronic applications. However, the growth of III-V-Bi alloys requires group-III-rich growth conditions, which pose severe challenges for planar growth. In this work, we exploit the naturally-Ga-rich environment present inside the metallic droplet of a self-catalyzed GaAs nanowire to synthesize metastable GaAs/GaAs$_{1-\text{x}}$Bi$_{\text{x}}$ axial nanowire heterostructures with high Bi contents. The axial GaAs$_{1-\text{x}}$Bi$_{\text{x}}$ segments are realized with molecular beam epitaxy by first enriching only the vapor-liquid-solid (VLS) Ga droplets with Bi, followed by exposing the resulting Ga-Bi droplets to As$_2$ at temperatures ranging from 270 to 380$\,^{\circ}$C to precipitate GaAs$_{1-\text{x}}$Bi$_{\text{x}}$ only under the nanowire droplets. Microstructural and elemental characterization reveals the presence of single crystal zincblende GaAs$_{1-\text{x}}$Bi$_{\text{x}}$ axial nanowire segments with Bi contents up to (10$\pm$2)$\%$. This work illustrates how the unique local growth environment present during the VLS nanowire growth can be exploited to synthesize heterostructures with metastable compounds.

In this paper, the controlled production of high quality metal-free diamond nanoparticles is demonstrated. Milling with tempered steel is shown to leave behind iron oxide contamination which is difficult to remove. Milling with SiN alleviates this issue but generates more non diamond carbon. Thus the choice of milling materials is critically determined by the acceptable contaminants in the ultimate application. The removal of metal impurities, present in all commercially available nanoparticles, will open new possibilities towards the production of customised diamond nanoparticles, covering the most demanding quantum applications.

III-V nanowires are comprehensively studied because of their suitability for optoelectronic quantum technology applications. However, their small dimensions and the spatial separation of carriers from the wire surface render electrical contacting difficult. Systematically studying ohmic contact formation by diffusion to $n$-doped GaAs nanowires, we provide a set of optimal annealing parameters for Pd/Ge/Au ohmic contacts. We reproducibly achieve low specific contact resistances of $\sim2\times10^{-7}\,\Omega\text{cm}^2$ at room temperature becoming an order of magnitude higher at $T\simeq4.2\,$K. We provide a phenomenological model to describe contact resistances as a function of diffusion parameters. Implementing a transfer-matrix method, we numerically study the influence of the Schottky barrier on the contact resistance. Our results indicate that contact resistances can be predicted using various barrier shapes but further insights into structural properties would require a full microscopic understanding of the complex diffusion processes., Comment: 11 pages, 10 figures

We present a novel two-step approach for the selective area growth (SAG) of GaAs nanowires (NWs) by molecular beam epitaxy which has enabled a detailed exploration of the NW diameter evolution. In the first step, the growth parameters are optimized for the nucleation of vertically-oriented NWs. In the second step, the growth parameters are chosen to optimize the NW shape, allowing NWs with a thin diameter (45 nm) and an untapered morphology to be realized. This result is in contrast to the commonly observed thick, inversely tapered shape of SAG NWs. We quantify the flux dependence of radial vapour-solid (VS) growth and build a model that takes into account diffusion on the NW sidewalls to explain the observed VS growth rates. Combining this model for the radial VS growth with an existing model for the droplet dynamics at the NW top, we achieve full understanding of the diameter of NWs over their entire length and the evolution of the diameter and tapering during growth. We conclude that only the combination of droplet dynamics and VS growth results in an untapered morphology. This result enables NW shape engineering and has important implications for doping of NWs.

The selective area growth of Ga-assisted GaAs nanowires (NWs) with a high vertical yield on Si(111) substrates is still challenging. Here, we explore different surface preparations and their impact on NW growth by molecular beam epitaxy. We show that boiling the substrate in ultrapure water leads to a significant improvement in the vertical yield of NWs (realizing 80%) grown on substrates patterned by electron-beam lithography (EBL). Tentatively, we attribute this improvement to a reduction in atomic roughness of the substrate in the mask opening. On this basis, we transfer our growth results to substrates processed by a technique that enables the efficient patterning of large arrays, nano imprint lithography (NIL). In order to obtain hole sizes below 50 nm, we combine the conventional NIL process with an indirect pattern transfer (NIL-IPT) technique. Thereby, we achieve smaller hole sizes than previously reported for conventional NIL and growth results that are comparable to those achieved on EBL patterned substrates.

We investigate the optical properties of InAs quantum dots grown by molecular beam epitaxy on GaAs(110) using Bi as a surfactant. The quantum dots are synthesized on planar GaAs(110) substrates as well as on the {110} sidewall facets of GaAs nanowires. At 10 K, neutral excitons confined in these quantum dots give rise to photoluminescence lines between 1.1 and 1.4 eV. Magneto-photoluminescence spectroscopy reveals that for small quantum dots emitting between 1.3 and 1.4 eV, the electron-hole coherence length in and perpendicular to the (110) plane is on the order of 5 and 2 nm, respectively. The quantum dot photoluminescence is linearly polarized, and both binding and antibinding biexcitons are observed, two findings that we associate with the strain in the (110) plane This strain leads to piezoelectric fields and to a strong mixing between heavy and light hole states, and offers the possibility to tune the degree of linear polarization of the exciton photoluminescence as well as the sign of the binding energy of biexcitons.

Surface energies play a dominant role in the self-assembly of three dimensional (3D) nanostructures. In this letter, we show that using surfactants to modify surface energies can provide a means to externally control nanostructure self-assembly, enabling the synthesis of novel hierarchical nanostructures. We explore Bi as a surfactant in the growth of InAs on the {1-10} sidewall facets of GaAs nanowires. The presence of surface Bi induces the formation of InAs 3D islands by a process resembling the Stranski-Krastanov mechanism, which does not occur in the absence of Bi on these surfaces. The InAs 3D islands nucleate at the corners of the {1-10} facets above a critical shell thickness and then elongate along <110> directions in the plane of the nanowire sidewalls. Exploiting this growth mechanism, we realize a series of novel hierarchical nanostructures, ranging from InAs quantum dots on single {1-10} nanowire facets to zig-zag shaped nanorings completely encircling nanowire cores. Photoluminescence spectroscopy and cathodoluminescence spectral line scans reveal that small surfactant-induced InAs 3D islands behave as optically active quantum dots. This work illustrates how surfactants can provide an unprecedented level of external control over nanostructure self-assembly., Comment: 12 pages, 4 figures

In strained heteroepitaxy, two-dimensional (2D) layers can exhibit a critical thickness at which three-dimensional (3D) islands self-assemble, relieving misfit strain at the cost of an increased surface area. Here we show that such a morphological phase transition can be induced on-demand using surfactants. We explore Bi as a surfactant in the growth of InAs on GaAs(110), and find that the presence of surface Bi induces Stranski-Krastanov growth of 3D islands, while growth without Bi always favors 2D layer formation. Exposing a static two monolayer thick InAs layer to Bi rapidly transforms the layer into 3D islands. Density functional theory calculations reveal that Bi reduces the energetic cost of 3D island formation by modifying surface energies. These 3D nanostructures behave as optically active quantum dots. This work illustrates how surfactants can enable quantum dot self-assembly where it otherwise would not occur.

This brief documents the expansion of instructional specialist staffing in U.S. public school districts. We use data from the National Center of Education Statistics' annual Common Core of Data to chart staffing trends in public school districts between 1997-98 and 2012-13. The number of instructional specialists per 1,000 U.S students doubled during that period, and the proportion of districts employing no specialists declined from nearly 20% to 7%. We suggest that specialists are poised to play a pivotal "professional sense-making" role as schools work to implement new instructional standards in the classroom. [This paper was published in "Education Researcher" v44 n6 p359-364 Aug-Sep 2015 (EJ1073976).]