Thermometry of Silicon Nanoparticles

Current thermometry techniques lack the spatial resolution required to see the temperature gradients in typical, highly-scaled modern transistors. As a step toward addressing this problem, we have measured the temperature dependence of the volume plasmon energy in silicon nanoparticles from room temperature to 1250$^\circ$C, using a chip-style heating sample holder in a scanning transmission electron microscope (STEM) equipped with electron energy loss spectroscopy (EELS). The plasmon energy changes as expected for an electron gas subject to the thermal expansion of silicon. Reversing this reasoning, we find that measurements of the plasmon energy provide an independent measure of the nanoparticle temperature consistent with that of the heater chip's macroscopic heater/thermometer to within the 5\% accuracy of the chip thermometer's calibration. Thus silicon has the potential to provide its own, high-spatial-resolution thermometric readout signal via measurements of its volume plasmon energy. Furthermore, nanoparticles in general can serve as convenient nanothermometers for \emph{in situ} electron microscopy experiments.Comment: 6 pages, 3 figure

Electron beam-induced current imaging with two-angstrom resolution.

An electron microscope's primary beam simultaneously ejects secondary electrons (SEs) from the sample and generates electron beam-induced currents (EBICs) in the sample. Both signals can be captured and digitized to produce images. The off-sample Everhart-Thornley detectors that are common in scanning electron microscopes (SEMs) can detect SEs with low noise and high bandwidth. However, the transimpedance amplifiers appropriate for detecting EBICs do not have such good performance, which makes accessing the benefits of EBIC imaging at high-resolution relatively more challenging. Here we report lattice-resolution imaging via detection of the EBIC produced by SE emission (SEEBIC). We use an aberration-corrected scanning transmission electron microscope (STEM), and image both microfabricated devices and standard calibration grids

Designing wheelchair-based movement games

People using wheelchairs have access to fewer sports and other physically stimulating leisure activities than nondisabled persons, and often lead sedentary lifestyles that negatively influence their health. While motion- based video games have demonstrated great potential of encouraging physical activity among nondisabled players, the accessibility of motion-based games is limited for persons with mobility disabilities, thus also limiting access to the potential health benefits of playing these games. In our work, we address this issue through the design of wheelchair-accessible motion-based game controls. We present KINECTWheels, a toolkit designed to integrate wheelchair movements into motion-based games. Building on the toolkit, we developed Cupcake Heaven, a wheelchair-based video game designed for older adults using wheelchairs, and we created Wheelchair Revolution, a motion-based dance game that is accessible to both persons using wheelchairs and nondisabled players. Evaluation results show that KINECTWheels can be applied to make motion-based games wheelchair-accessible, and that wheelchair-based games engage broad audiences in physically stimulating play. Through the application of the wheelchair as an enabling technology in games, our work has the potential of encouraging players of all ages to develop a positive relationship with their wheelchair

Tree-level electron-photon interactions in graphene

Graphene's low-energy electronic excitations obey a 2+1 dimensional Dirac Hamiltonian. After extending this Hamiltonian to include interactions with a quantized electromagnetic field, we calculate the amplitude associated with the simplest, tree-level Feynman diagram: the vertex connecting a photon with two electrons. This amplitude leads to analytic expressions for the 3D angular dependence of photon emission, the photon-mediated electron-hole recombination rate, and corrections to graphene's opacity $\pi \alpha$ and dynamic conductivity $\pi e^2/2 h$ for situations away from thermal equilibrium, as would occur in a graphene laser. We find that Ohmic dissipation in perfect graphene can be attributed to spontaneous emission.Comment: 5 pages, 3 figure

Large object segmentation with region priority rendering

The Address Recalculation Pipeline is a hardware architecture designed to reduce the end-to-end latency suffered by immersive Head Mounted Display virtual reality systems. A demand driven rendering technique known as priority rendering was devised for use in conjunction with the address recalculation pipeline. Using this technique, different sections of a scene can be updated at different rates, resulting in reductions to the rendering load.Further reductions can potentially be achieved by allowing for the segmenting of large objects. However in doing so a tearing problem surfaces, which has to be overcome before large object segmentation can be used effectively in priority rendering. This paper demonstrates a way of organizing virtual world objects for priority rendering, as well as a method to hide scene tearing artefacts due to object segmentation

Electron tomography at 2.4 {\AA} resolution

Transmission electron microscopy (TEM) is a powerful imaging tool that has found broad application in materials science, nanoscience and biology(1-3). With the introduction of aberration-corrected electron lenses, both the spatial resolution and image quality in TEM have been significantly improved(4,5) and resolution below 0.5 {\AA} has been demonstrated(6). To reveal the 3D structure of thin samples, electron tomography is the method of choice(7-11), with resolutions of ~1 nm^3 currently achievable(10,11). Recently, discrete tomography has been used to generate a 3D atomic reconstruction of a silver nanoparticle 2-3 nm in diameter(12), but this statistical method assumes prior knowledge of the particle's lattice structure and requires that the atoms fit rigidly on that lattice. Here we report the experimental demonstration of a general electron tomography method that achieves atomic scale resolution without initial assumptions about the sample structure. By combining a novel projection alignment and tomographic reconstruction method with scanning transmission electron microscopy, we have determined the 3D structure of a ~10 nm gold nanoparticle at 2.4 {\AA} resolution. While we cannot definitively locate all of the atoms inside the nanoparticle, individual atoms are observed in some regions of the particle and several grains are identified at three dimensions. The 3D surface morphology and internal lattice structure revealed are consistent with a distorted icosahedral multiply-twinned particle. We anticipate that this general method can be applied not only to determine the 3D structure of nanomaterials at atomic scale resolution(13-15), but also to improve the spatial resolution and image quality in other tomography fields(7,9,16-20).Comment: 27 pages, 17 figure

Smart observation of management impacts on peatlands function (SmartBog)

Peatlands are an important ecosystem due to their role in carbon sequestration as well as other ecosystem services including; climate regulation and water regulation. Peatlands cover a small fraction (~3 %) of the terrestrial surface. Nevertheless, they account for approximately one-third of global Soil Organic Carbon stock. In Ireland, peatlands cover ~21% of the land area and account for between 50-75% of the total SOC stock. However, much of this area has been degraded through anthropogenic activities such as drainage and peat extraction. Therefore, there is a need to develop a system to identify management-related impacts on peatland function. The system will directly support rehabilitation and conservation activities, aiding identification of candidate sites for rewetting and restoration. Both high-resolution satellite data (Copernicus Sentinel-2) and very high-resolution aerial photography will be used. Peatlands will be delineated using the Derived Irish Peat map (DIPM2) in both datasets. Semi-automatic object-based image analysis and machine learning-based techniques will be used to extract the extent of drains on Irish peatlands. Furthermore, a multi-scale approach will be implemented to generate Normalized Difference Vegetation Index maps. NDVI will be generated from both in-situ and remote sensors (Sentinel-2/Aerial imagery). Overall, the outputs generated from these datasets (LULC, drainage and NDVI maps) will be integrated into a GIS framework. The main aim of this study is to assess the impact of anthropogenic management of peatlands, using GIS, Earth Observation and Machine Learning (ML)