An Innovative Take on Filtering Carbon Dioxide Through CryoCapture

Overview (Air Mover): Carbon dioxide plays an important role in the earth's ecosystem; the lives of many organisms are based on the balancing of this gas. Plants and animals need it for survival however, an excess of carbon dioxide can also end the organism’s life. The production of the gas mostly comes from the combustion of fossil fuel, power plants, big industries, vehicles, and processes involving natural gasses. One of the most known issues of carbon dioxide pollution is global warming. The greenhouse gas essentially traps heat in the atmosphere, increasing the global temperature. The methodology provided is an innovative solution towards the creation of an environmentally friendly carbon dioxide filter. Current air filtration systems are restricted to industrial environments limiting the ability to filter the air. Due to the large noise and low range of operation of axial fans the filtration systems need controlled environments for longevity. The paper presents a versatile air mover that can be mounted onto multiple surfaces due to its low profile and bracket mounts. Furthermore, the usage of a diagonal fan inside of a PVC pipe allows for a durable system that can operate at high efficiency and low noise. The main challenge in designing the air mover was figuring out how to quantify the scalability of the device and what parameters could be changed in order to make the device more viable. The designs most prominent feature are the inclusion of a modular enclosure that can be adapted to multiple areas and environments while withstanding harsh conditions due to the PVC piping that can be coated with a diagonal fan for high volumetric flow rates and pressure differential for versatility in environments the device is placed in as well as efficiency. Overview (Carbon Storer): The Civil and Environmental Engineering team is responsible for finding a cost effective and sustainable way to transport, store and recycle the carbon caught in the air from the Carbon Catcher designed by the other engineering teams. In the team’s design, the Carbon Catcher will reduce the harmful emissions in the air by capturing CO2, store it and then utilize it in another industry which will reduce the need to mine for more raw materials which would thus further reduce the pollution emitted into the environment. Our plan is to recycle the carbon emitted from a factory and utilize it in CO2 dry ice. It's the Civil and Environmental Engineers’ job to find a way to connect a sustainable solution with a solution that improves the public’s quality of life. There are many industries that pollute immense amounts from the mining of raw material or the emission of pollutants. The team wants to show industries that the economic solution can also be the sustainable solution. Overview (Membrane) The team’s solution focuses on the use of cryogenic carbon capture, a method in which the selective freezing points of the gaseous components of air are used to separate out carbon dioxide. For this process, the team will be utilizing a 4 step filtration process. First, the flue gas will be run through a particulate filter to catch all macroscopic particles that may be present within the air. Afterwards, the gas is then passed through a dehumidifier where a majority of water content will be extracted. Following this, The gas was then run through a long pipe and progressively cool it down to the freezing point of carbon dioxide. Finally, the filtered gas is extracted, and a bubbler is used to separate the solid carbon dioxide. The carbon dioxide is then compressed and recycled around the feed pipe to help in the cooling process. Along the process of this design, the team encountered problems finding the optimum materials for temperatures this low. As well, coming up with a way to eliminate heat transfer from the outside posed a huge problem. Through the experience, the team was able to gain a greater view of what benefits and drawbacks must be balanced, along with the economic interest that comes with designing an efficient process. Unlike how most designs are focused, It was understood that using a membrane only provided so much creativity when it came to filtration. As a result, the team researched other successful methods and arrived at utilizing cryogenics to filter. Goal Research to provide a single solution to remove levels of carbon dioxide in the immediate atmosphere, transport it to a storage mechanism, and find a way to recycle it. Powerful research is required to ensure effective methodologies, material usage, and flexible scalability of the overall device. This particular team seeks to find an alternative separation process to membrane filtration, the efficacy of which has not been demonstrated beyond the scale of a laboratory

eleanor: An open-source tool for extracting light curves from the TESS Full-Frame Images

During its two year prime mission the Transiting Exoplanet Survey Satellite (TESS) will perform a time-series photometric survey covering over 80% of the sky. This survey comprises observations of 26 24 x 96 degree sectors that are each monitored continuously for approximately 27 days. The main goal of TESS is to find transiting planets around 200,000 pre-selected stars for which fixed aperture photometry is recorded every two minutes. However, TESS is also recording and delivering Full-Frame Images (FFIs) of each detector at a 30 minute cadence. We have created an open-source tool, eleanor, to produce light curves for objects in the TESS FFIs. Here, we describe the methods used in eleanor to produce light curves that are optimized for planet searches. The tool performs background subtraction, aperture and PSF photometry, decorrelation of instrument systematics, and cotrending using principal component analysis. We recover known transiting exoplanets in the FFIs to validate the pipeline and perform a limited search for new planet candidates in Sector 1. Our tests indicate that eleanor produces light curves with significantly less scatter than other tools that have been used in the literature. Cadence-stacked images, and raw and detrended eleanor light curves for each analyzed star will be hosted on MAST, with planet candidates on ExoFOP-TESS as Community TESS Objects of Interest (CTOIs). This work confirms the promise that the TESS FFIs will enable the detection of thousands of new exoplanets and a broad range of time domain astrophysics.Comment: 21 pages, 13 figures, 2 tables, Accepted to PAS

Robust Free-Space Optical Communication Utilizing Polarization

Free-space optical (FSO) communication can be subject to various types of distortion and loss as the signal propagates through non-uniform media. In experiment and simulation, we demonstrate that the state of polarization and degree of polarization of light passed though underwater bubbles, causing turbulence, is preserved. Our experimental setup serves as an efficient, low cost alternative approach to long distance atmospheric or underwater testing. We compare our experimental results with those of simulations, in which we model underwater bubbles, and separately, atmospheric turbulence. Our findings suggest potential improvements in polarization based FSO communication schemes.Comment: 13 pages, 5 figure

Photoaffinity labelling displacement assay using multiple recombinant protein domains

The development and optimisation of a photoaffinity labelling (PAL) displacement assay is presented, where a highly efficient PAL probe was used to report on the relative binding affinities of compounds to specific binding sites in multiple recombinant protein domains in tandem. The N- and C-terminal bromodomains of BRD4 were used as example target proteins. A test set of 264 compounds annotated with activity against the bromodomain and extra-terminal domain (BET) family in ChEMBL were used to benchmark the assay. The pIC50 values obtained from the assay correlated well with orthogonal TR‑FRET data, highlighting the potential of this highly accessible PAL biochemical screening platform

The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for cloud-based processing of Earth satellite imagery with practical applications to aid in natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework allows batches of analytics, scanning for new data, to be applied to data as it flows in. In the Matsu Wheel, the data only need to be accessed and preprocessed once, regardless of the number or types of analytics, which can easily be slotted into the existing framework. The Matsu Wheel system provides a significantly more efficient use of computational resources over alternative methods when the data are large, have high-volume throughput, may require heavy preprocessing, and are typically used for many types of analysis. We also describe our preliminary Wheel analytics, including an anomaly detector for rare spectral signatures or thermal anomalies in hyperspectral data and a land cover classifier that can be used for water and flood detection. Each of these analytics can generate visual reports accessible via the web for the public and interested decision makers. The result products of the analytics are also made accessible through an Open Geospatial Compliant (OGC)-compliant Web Map Service (WMS) for further distribution. The Matsu Wheel allows many shared data services to be performed together to efficiently use resources for processing hyperspectral satellite image data and other, e.g., large environmental datasets that may be analyzed for many purposes

Automated LC-MS analysis and data extraction for high-throughput chemistry

High-throughput experimentation for chemistry and chemical biology has emerged as a highly impactful technology, particularly when applied to Direct-to-Biology. Analysis of the rich datasets which come from this mode of experimentation continues to be the rate-limiting step to reaction optimisation and the submission of compounds for biological assay. We present PyParse, an automated, accurate and accessible program for data extraction from high-throughput chemistry and provide real-life examples of situations in which PyParse can provide dramatic improvements in the speed and accuracy of analysing plate data. This software package has been made available through GitHub repository under an open-source Apache 2.0 licence, to facilitate the widespread adoption of high-throughput chemistry and enable the creation of standardised chemistry datasets for reaction prediction