Single electron tunneling detected by electrostatic force

Journal ArticleSingle electron tunneling events between a specially fabricated scanning probe and a conducting surface are demonstrated. The probe is an oxidized silicon atomic force microscope tip with an electrically isolated metallic dot at its apex. A voltage applied to the silicon tip produces an electrostatic force on the probe, which depends upon the charge on the metallic dot. Single electron tunneling events are observed in both the electrostatic force amplitude and phase signal. Electrostatic modeling of the probe response to single tunneling events is in good agreement with measured results

Modeling and experimental investigation of cantilever dynamics in force detected single electron tunneling

Journal ArticleThe dynamic response of a voltage biased oscillating cantilever probe is investigated through experimental and theoretical analysis as it approaches a dielectric surface. When the tip reaches the appropriate gap single electron tunneling events are detected between the metallic tip and the surface. The tunneling events cause a decrease of the electrostatic force and force gradient acting between tip and sample

Coherence properties of infrared thermal emission from heated metallic nanowires

Coherence properties of the infrared thermal radiation from individual heated nanowires are investigated as function of nanowire dimensions. Interfering the thermally induced radiation from a heated nanowire with its image in a nearby moveable mirror, well-defined fringes are observed. From the fringe visibility, the coherence length of the thermal emission radiation from the narrowest nanowires was estimated to be at least 20 um which is much larger than expected from a classical blackbody radiator. A significant increase in coherence and emission efficiency is observed for smaller nanowires.Comment: 4 pages,figures include

Quantification of Carbon Sequestration in Urban Forests

Vegetation, trees in particular, sequester carbon by absorbing carbon dioxide from the atmosphere. However, the lack of efficient quantification methods of carbon stored in trees renders it difficult to track the process. We present an approach to estimate the carbon storage in trees based on fusing multi-spectral aerial imagery and LiDAR data to identify tree coverage, geometric shape, and tree species -- key attributes to carbon storage quantification. We demonstrate that tree species information and their three-dimensional geometric shapes can be estimated from aerial imagery in order to determine the tree's biomass. Specifically, we estimate a total of $52,000$ tons of carbon sequestered in trees for New York City's borough Manhattan

Urban Forests for Carbon Sequestration and Heat Island Mitigation

Urban forests serve both as a carbon sequestration pool and heat island mitigation tool. Climate change will increase the frequency and severity of urban heat islands. Thus, new urban planning strategies demand our attention. Based on multimodal, remotely sensed data, we map the tree density, its carbon sequestered, and its impact on urban heat islands for Long Island, NY and Dallas, TX. Using local climate zones we investigate concepts of urban planning through optimized tree planting and adjusting building designs to mitigate urban heat islands

S3RP: Self-Supervised Super-Resolution and Prediction for Advection-Diffusion Process

We present a super-resolution model for an advection-diffusion process with limited information. While most of the super-resolution models assume high-resolution (HR) ground-truth data in the training, in many cases such HR dataset is not readily accessible. Here, we show that a Recurrent Convolutional Network trained with physics-based regularizations is able to reconstruct the HR information without having the HR ground-truth data. Moreover, considering the ill-posed nature of a super-resolution problem, we employ the Recurrent Wasserstein Autoencoder to model the uncertainty.Comment: 9 pages, 8 figure

Carbon Sequestration and Urban Heat Island Mitigation by Urban Forests

Nature-based carbon sequestration is one of the most straightforward ways to extract and to store carbon dioxide from the atmosphere. Urban forests hold the promise of optimized carbon storage and temperature reduction in cities. Remote sensing imagery can identify tree location and size, classify trees based on their species, and track tree health. Using multi- and hyperspectral overhead imagery, green vegetation can be separated from various land use types. Moreover, through further refinement of models by texture and contextual information, trees can get spatially separated from bushes and grass covered surfaces. While spectral-based tree identification can achieve accuracy of 90%, additional deep learning models using even noisy labeled data can further improve tree identification models. Once trees are identified in two-dimensional remote sensing images, allometric models allow to extract tree height and tree growth based on climate data, topography, and soil properties. The biomass of the trees is calculated for tree species using geometrical and phenological models. The carbon stored in trees can be quantified at individual tree level. Furthermore, the models allow to identify areas densely covered by trees to pinpoint bare land where further trees may be planted. Exploiting land surface temperature maps from satellite thermal measurements of, e.g., the Sentinel or Landsat missions, urban heat island can be mapped out at city scale. Urban heat islands may vary based on season and weather conditions; areas persistently warmer when compared to average city temperature background can be identified from time series of data. The correlation of local temperature, tree cover, and land perviousness helps to identify local climate zones. It also may refine and re-evaluate the definition of Local Climate Zones (LCZ). We employ the PAIRS geospatial information platform to demonstrate a scalable solution for tree delineation, carbon sequestration, and urban heat island identification for three global cities: Madrid, New York City, and Dallas, TX

Single-electron quantum dot in Si/SiGe with integrated charge-sensing

Single-electron occupation is an essential component to measurement and manipulation of spin in quantum dots, capabilities that are important for quantum information processing. Si/SiGe is of interest for semiconductor spin qubits, but single-electron quantum dots have not yet been achieved in this system. We report the fabrication and measurement of a top-gated quantum dot occupied by a single electron in a Si/SiGe heterostructure. Transport through the quantum dot is directly correlated with charge-sensing from an integrated quantum point contact, and this charge-sensing is used to confirm single-electron occupancy in the quantum dot.Comment: 3 pages, 3 figures, accepted version, to appear in Applied Physics Letter