Field and Satellite Observations of the Formation and Distribution of Arctic Atmospheric Bromine Above a Rejuvenated Sea Ice Cover

Recent drastic reduction of the older perennial sea ice in the Arctic Ocean has resulted in a vast expansion of younger and saltier seasonal sea ice. This increase in the salinity of the overall ice cover could impact tropospheric chemical processes. Springtime perennial ice extent in 2008 and 2009 broke the half-century record minimum in 2007 by about one million km2. In both years seasonal ice was dominant across the Beaufort Sea extending to the Amundsen Gulf, where significant field and satellite observations of sea ice, temperature, and atmospheric chemicals have been made. Measurements at the site of the Canadian Coast Guard Ship Amundsen ice breaker in the Amundsen Gulf showed events of increased bromine monoxide (BrO), coupled with decreases of ozone (O3) and gaseous elemental mercury (GEM), during cold periods in March 2008. The timing of the main event of BrO, O3, and GEM changes was found to be consistent with BrO observed by satellites over an extensive area around the site. Furthermore, satellite sensors detected a doubling of atmospheric BrO in a vortex associated with a spiral rising air pattern. In spring 2009, excessive and widespread bromine explosions occurred in the same region while the regional air temperature was low and the extent of perennial ice was significantly reduced compared to the case in 2008. Using satellite observations together with a Rising-Air-Parcel model, we discover a topographic control on BrO distribution such that the Alaskan North Slope and the Canadian Shield region were exposed to elevated BrO, whereas the surrounding mountains isolated the Alaskan interior from bromine intrusion

Experimental investigation on the applicability of FBRM in the control of batch cooling crystallization

Master'sMASTER OF ENGINEERIN

Formation and Characterization of Transversely Modulated Nanostructures in Metallic Thin Films using Epitaxial Control

This thesis describes a fundamental investigation into the formation, characterization, and modeling of epitaxially-controlled self-assembly at the nanoscale. The presence of coherent nanophases and the clamping effect from an epitaxial substrate enables the formation of transversely modulated nanostructures (TMNS) resulting in improved functionality, which was previously observed through increased piezoelectric response in BiFeO3. The ability to fabricate high quality epitaxial films presents opportunity to investigate coherent phase decomposition in other material systems with multifunctional response. The research herein aims to extend the concept of nanoscale self assembly in metallic systems, including Ag-Si and Pd-PdH. First, the effect of annealing a Ag-Si couple was examined, and ordered, nanoscale Ag crystallites were observed along the interface with the epitaxial Si wafer. It is demonstrated that Ag foil can be used in place of doped Ag paste (commonly used in solar cell metallization) to achieve TMNS at the interface. It was proved that annealing the Ag-Si couple in air is necessary for the self-assembly reaction to take place, as doing so prevents bulk diffusion and eutectic melting. Electron backscatter diffraction was used to verify the epitaxial relation between the Ag nanostructures and Si crystal. A method to fabricate ordered, nanoscale PdH precipitates in epitaxial Pd thin films via high temperate gas phase hydrogenation was established. Epitaxial Pd films were deposited via e-beam deposition and a V buffer layer was necessary to induce epitaxy. This novel self-assembled nanostructure may enable hysteresis-less absorption and desorption, thus improving functionality with regard to hydrogen sensing and storage. The epitaxial Pd film was characterized before and after hydrogenation with x-ray diffraction and atomic force microscopy to determine composition and nanostructure of the film. A thermodynamic model was developed to demonstrate the possibility to control or eliminate thermodynamic hysteresis via balance of elastic interaction between the coherent interfaces of metal and metal-hydride phases and the film-substrate interface. This model can be extended to other metal-hydride systems which demonstrate coherent phase decomposition

On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds

Fifth generation (5G) mobile communication systems have entered the stage of commercial development, providing users with new services and improved user experiences as well as offering a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified for stimulating the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed

Artificial Neural Networks in Agriculture

Modern agriculture needs to have high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those derived from artificial intelligence methods. Artificial neural networks (ANNs) are one of the most popular tools of this kind. They are widely used in solving various classification and prediction tasks, for some time also in the broadly defined field of agriculture. They can form part of precision farming and decision support systems. Artificial neural networks can replace the classical methods of modelling many issues, and are one of the main alternatives to classical mathematical models. The spectrum of applications of artificial neural networks is very wide. For a long time now, researchers from all over the world have been using these tools to support agricultural production, making it more efficient and providing the highest-quality products possible

Electromechanical and biological evaluations of 0.94Bi0.5Na0.5TiO3–0.06BaTiO3 as a lead-free piezoceramic for implantable bioelectronics

Smart implantable electronic medical devices are being developed to deliver healthcare that is more connected, personalised, and precise. Many of these implantables rely on piezoceramics for sensing, communication, energy autonomy, and biological stimulation, but the piezoceramics with the strongest piezoelectric coefficients are almost exclusively lead-based. In this article, we evaluate the electromechanical and biological characteristics of a lead-free alternative, 0.94Bi0.5Na0.5TiO3–0.06BaTiO3 (BNT-6BT), manufactured via two synthesis routes: the conventional solid-state method (PIC700) and tape casting (TC-BNT-6BT). The BNT-6BT materials exhibited soft piezoelectric properties, with d33 piezoelectric coefficients that were inferior to commonly used PZT (PIC700: 116 pC/N; TC-BNT-6BT: 121 pC/N; PZT-5A: 400 pC/N). The material may be viable as a lead-free substitute for soft PZT where moderate performance losses up to 10 dB are tolerable, such as pressure sensing and pulse-echo measurement. No short-term harmful biological effects of BNT-6BT were detected and the material was conducive to the proliferation of MC3T3-E1 murine preosteoblasts. BNT-6BT could therefore be a viable material for electroactive implants and implantable electronics without the need for hermetic sealing

A Quantitative Study of Drug Recrystallization in Drug-In-Adhesive Transdermal Patches Using Vibrational Spectroscopy

Drug-in-adhesive (DIA) transdermal patches are an important type of transdermal drug delivery system (TDDS). The drugs used in the DIA system are frequently present in metastable forms, such as amorphous solids or supercooled liquids. These drug states are thermodynamically unstable and tend to undergo recrystallization. Recrystallization of the active pharmaceutical ingredient can adversely affect the efficacy of transdermal products. This dissertation demonstrates a systematic approach to quantify the crystalline content of the API in DIA systems. This approach uses a novel method of preparing calibration standards and a spectroscopic method to reliably predict crystalline content in DIA patches. Spectroscopic tools, including Raman spectroscopy and near-infrared spectroscopy (NIRS), were used to determine the crystallinity of drug in transdermal patches rapidly and non-destructively with a limit of detection comparable to that of the conventional solid-state characterization techniques. Sample representativeness, analytical capability, and method suitability were integrated to form a systematic approach for crystallization quantification. The multivariate methods were validated via a fit-for-purpose approach. The results of this work demonstrated that a reliable crystalline content quantification method can be developed using vibrational spectroscopy for DIA transdermal patches. The quantitative spectroscopic methods are potential tools for supporting formulation development and physical stability evaluation of transdermal products in the pharmaceutical industry

Characterisation of highly active nuclear waste simulants

Nuclear power is a non-carbon emitting energy resource generating 18% of electricity to the UK. As with any type of industrial process the waste management strategy is an important step to define considering the environmental, economic and political factors. However, the nuclear industry faces ongoing challenges to underpin a well-defined waste treatment strategy due to the high heat load and the radioactive nature of the products produced. Reprocessing of spent nuclear fuel produces a highly active liquor (HAL) waste stream. HAL is currently stored in a number of highly active storage tanks (HASTs). Within the HASTs, solid materials are known to have precipitated from the HAL over time. Particle simulants provide a route for understanding the physical behaviour, it is the synthesis of the particle simulants and the characterisation of these solid-liquid systems that are the interest of this study. An understanding of the HAL waste properties is required for its safe transport, storage and eventual disposal of the HASTs are to be safely emptied and decommissioned. Collaboration with the National Nuclear Laboratory (NNL), at Sellafield UK, provided the opportunity to manufacture the HAL simulants, caesium phosphomolybdate (CPM) and zirconium molybdate (ZM), on larger scale. Manipulation of the aspect ratio of ZM particles is also investigated. The initial step of the synthesis produces spherical CPM which leads to the production of cubic ZM, the final step requires the addition of an organic additive, citric acid, where cuboidal zirconium citratomolybdate (ZMCA) is formed. Molecular modelling analysis revealed growth inhibition of the {2 0 0}, {-2 0 0}, {0 2 0} and {0 -2 0} faces, due to greater number of Zr sites for citratomolybdate complex affiliation. Distinct particle properties are established for CPM, ZM and ZMCA and compared to a common oxide particle material titanium dioxide (TiO2). The results of this study highlight the influence of key aspects of the HAL particulates, such as size and shape, on relevant solid-liquid properties such as sedimentation and rheology. The influence of bulk liquid properties such as electrolyte concentration and pH were also investigated. Sedimentation behaviour was characterised by fitting the experimental data to the Richardson-Zaki model, yielding a fitting parameter n (cognate to particle size and shape) and thus demonstrated a settling relationship with particle shape, sphere > cubic > cuboidal. The rheological behaviour explored was categorised into four groups: (i) flow behaviour data was fitted to a simplified Cross model yielding two parameters K (related to viscosity) and n (extent of shear-thinning); (ii) dependency of viscosity on particle volume fraction was characterised using the Krieger-Dougherty model yielding fitting parameter [µ] (particle’s contribution to suspension viscosity) and maximum packing fraction m, this demonstrated the relationship, cuboidal > sphere > cube; (iii) yield stress was characterised using an empirical model derived by Heymann et al (2002) yielding a fitting parameter σ^* (cognate to particle shape and size) and demonstrating a relationship, sphere > cuboidal > cubic; (iv) characterisation of compressive yield stress demonstrated the relationship, cuboidal > cubic > sphere. The results indicate various possible behaviours within the tanks which may impact the storage, remobilisation and pipeline transport of this class of nuclear waste. Ultimately, it is of importance to establish the effect of solid-liquid properties on the behaviour of HAL for current processing, post operational clean out (POCO) and life-time assessment

Investigation of freezing properties of polar statospheric cloud particles with optical microscopy

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Chemistry, 1997.Includes bibliographical references (leaves 96-100).by Huey Pin Ng.M.S

A framework for malicious host fingerprinting using distributed network sensors

Numerous software agents exist and are responsible for increasing volumes of malicious traffic that is observed on the Internet today. From a technical perspective the existing techniques for monitoring malicious agents and traffic were not developed to allow for the interrogation of the source of malicious traffic. This interrogation or reconnaissance would be considered active analysis as opposed to existing, mostly passive analysis. Unlike passive analysis, the active techniques are time-sensitive and their results become increasingly inaccurate as time delta between observation and interrogation increases. In addition to this, some studies had shown that the geographic separation of hosts on the Internet have resulted in pockets of different malicious agents and traffic targeting victims. As such it would be important to perform any kind of data collection over various source and in distributed IP address space. The data gathering and exposure capabilities of sensors such as honeypots and network telescopes were extended through the development of near-realtime Distributed Sensor Network modules that allowed for the near-realtime analysis of malicious traffic from distributed, heterogeneous monitoring sensors. In order to utilise the data exposed by the near-realtime Distributed Sensor Network modules an Automated Reconnaissance Framework was created, this framework was tasked with active and passive information collection and analysis of data in near-realtime and was designed from an adapted Multi Sensor Data Fusion model. The hypothesis was made that if sufficiently different characteristics of a host could be identified; combined they could act as a unique fingerprint for that host, potentially allowing for the re-identification of that host, even if its IP address had changed. To this end the concept of Latency Based Multilateration was introduced, acting as an additional metric for remote host fingerprinting. The vast amount of information gathered by the AR-Framework required the development of visualisation tools which could illustrate this data in near-realtime and also provided various degrees of interaction to accommodate human interpretation of such data. Ultimately the data collected through the application of the near-realtime Distributed Sensor Network and AR-Framework provided a unique perspective of a malicious host demographic. Allowing for new correlations to be drawn between attributes such as common open ports and operating systems, location, and inferred intent of these malicious hosts. The result of which expands our current understanding of malicious hosts on the Internet and enables further research in the area