48,316 research outputs found

    Quantification of interfacial polymerization covalent organic framework membrane physicochemical composition and performance

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    Forty percent of the world suffers from water scarcity and a lack of safe drinking water due to record population growth, accelerated development, and climate change, making it essential to start emphasizing sustainable and efficient water treatment technologies. Pressure driven membrane systems are a promising technology that can be used effectively to recycle freshwater, seawater, municipal wastewater effluent or industrial water to potable quality. Commercial membrane products typically consist of an asymmetric thin-film composite (TFC) structure: a polymeric thin active layer supported by an ultrafiltration membrane and a thick fiber backing. While this structure allows reverse osmosis (RO) and nanofiltration (NF) membrane systems to remove a wide range of water contaminants with no chemical additives or thermal input, the relatively limited polymeric surface chemistry currently available restricts the range of water permeability and solute selectivity achieved. An alternative to conventional polymeric membrane materials are two-dimensional covalent organic frameworks (COFs). 2D COFs have a crystalline structure created by strong covalent bonds made through synthetic reactions of organic building units. This structure provides a well-organized layer, reducing surface roughness, with pore size control based on chosen building units, allowing the user more control over membrane performance. Utilizing the up-scalable TFC structure formation of commercial membrane products, an ultrathin COF film can form on an ultrafiltration membrane support by interfacial polymerization (IP), creating a novel NF TFC membrane. This research presents a robust analysis of IP COF NF membranes, utilizing novel materials characterization techniques to quantify film composition and structure. Key material properties of COF films are assessed including modularity, crystallinity, and chemical stability. The impact of COF monomer selection was assessed through a comparative analysis of three imine-linked COF films, ultimately showing that COF building units significantly influence membrane performance. The performance of these three materials illuminated critical questions about the IP COF membrane configuration, motivating an in-depth analysis to quantify the degree of COF formation. Using Rutherford backscattering spectrometry (RBS) and heavy counterion probe solutions, COF material properties were obtained and lead to the realization that IP COF films were made up of small platelets rather than large sheets. This experimental method provided pathways to understand other material characteristics of the COF films, including oxidation tolerance, an important parameter for a water treatment application. A key takeaway from each of these studies is although the COF formation and performance is not ideal, the resulting films still exhibit properties that when controlled will result in extraordinary attributes for the next generation of membrane materials.LimitedAuthor requested closed access (OA after 2yrs) in Vireo ETD syste

    Meso-scale FDM material layout design strategies under manufacturability constraints and fracture conditions

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    In the manufacturability-driven design (MDD) perspective, manufacturability of the product or system is the most important of the design requirements. In addition to being able to ensure that complex designs (e.g., topology optimization) are manufacturable with a given process or process family, MDD also helps mechanical designers to take advantage of unique process-material effects generated during manufacturing. One of the most recognizable examples of this comes from the scanning-type family of additive manufacturing (AM) processes; the most notable and familiar member of this family is the fused deposition modeling (FDM) or fused filament fabrication (FFF) process. This process works by selectively depositing uniform, approximately isotropic beads or elements of molten thermoplastic material (typically structural engineering plastics) in a series of pre-specified traces to build each layer of the part. There are many interesting 2-D and 3-D mechanical design problems that can be explored by designing the layout of these elements. The resulting structured, hierarchical material (which is both manufacturable and customized layer-by-layer within the limits of the process and material) can be defined as a manufacturing process-driven structured material (MPDSM). This dissertation explores several practical methods for designing these element layouts for 2-D and 3-D meso-scale mechanical problems, focusing ultimately on design-for-fracture. Three different fracture conditions are explored: (1) cases where a crack must be prevented or stopped, (2) cases where the crack must be encouraged or accelerated, and (3) cases where cracks must grow in a simple pre-determined pattern. Several new design tools, including a mapping method for the FDM manufacturability constraints, three major literature reviews, the collection, organization, and analysis of several large (qualitative and quantitative) multi-scale datasets on the fracture behavior of FDM-processed materials, some new experimental equipment, and the refinement of a fast and simple g-code generator based on commercially-available software, were developed and refined to support the design of MPDSMs under fracture conditions. The refined design method and rules were experimentally validated using a series of case studies (involving both design and physical testing of the designs) at the end of the dissertation. Finally, a simple design guide for practicing engineers who are not experts in advanced solid mechanics nor process-tailored materials was developed from the results of this project.U of I OnlyAuthor's request

    Drug delivery systems based on 2-oxazoline/2-oxazine amphiphilic gradient copolymers

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    Poly(2-oxazoline)s and, recently, also poly(2-oxazine)s have gained increasing attention for biomedical applications. The homopolymerization of these two cyclic imino ether monomers through cationic ring-opening polymerization have been extensively reported. On the other side not so much data have been published about the copolymerization of these two different monomers. We demonstrate with this study that the statistical copolymerization of 2-oxazines with 2oxazolines monomers can lead with a single step reaction to the synthesis of amphiphilic gradient copolymers. We report for the first time the statistical copolymerization of 2-npropyl-2-oxazine (nPrOzi) and 2-nbutyl-2-oxazine (nBuOzi) with 2-methyl-2-oxazoline (MeOx) or 2-ethyl-2-oxazoline (EtOx). These resulting gradient copolymers are the combination of the structural modularity of poly(2-oxazoline)s with the surprisingly biological properties of poly(2-oxazine)s. In all copolymerizations was found that nPrOzi and nBuOzi showed a higher interaction in the copolymeritazion than in the homopolymerization. This behavior was explained on the basis of a kinetic study revealing that a combination of electronic and steric effects reverse the monomer incorporation in the statistical copolymerization compared to the homopolymerizations. For all gradient copolymers, prepared with different molar ratios, we studied the self-assembly properties in an aqueous environment as well as the thermoresponsive characteristics, as a confirmation of their potential as stimuli-responsive nonionic surfactants for various applications, especially biomedical

    A Protocol for Cast-as-Intended Verifiability with a Second Device

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    Numerous institutions, such as companies, universities, or non-governmental organizations, employ Internet voting for remote elections. Since the main purpose of an election is to determine the voters' will, it is fundamentally important to ensure that the final election result correctly reflects the voters' votes. To this end, modern secure Internet voting schemes aim for what is called end-to-end verifiability. This fundamental security property ensures that the correctness of the final result can be verified, even if some of the computers or parties involved are malfunctioning or corrupted. A standard component in this approach is so called cast-as-intended verifiability which enables individual voters to verify that the ballots cast on their behalf contain their intended choices. Numerous approaches for cast-as-intended verifiability have been proposed in the literature, some of which have also been employed in real-life Internet elections. One of the well established approaches for cast-as-intended verifiability is to employ a second device which can be used by voters to audit their submitted ballots. This approach offers several advantages - including support for flexible ballot/election types and intuitive user experience - and it has been used in real-life elections, for instance in Estonia. In this work, we improve the existing solutions for cast-as-intended verifiability based on the use of a second device. We propose a solution which, while preserving the advantageous practical properties sketched above, provides tighter security guarantees. Our method does not increase the risk of vote-selling when compared to the underlying voting protocol being augmented and, to achieve this, it requires only comparatively weak trust assumptions. It can be combined with various voting protocols, including commitment-based systems offering everlasting privacy

    Fourier Coefficients of Weight Zero Mixed False Modular Forms

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    In this paper we employ the Circle Method to give exact formulae for Fourier coefficients of an infinite family of weight zero mixed false modular forms using and extending the techniques of Bringmann and Nazaroglu as well as Rademacher. To do so we additionally provide a bound on a Kloosterman sum of modulus kk.Comment: 53 pages, 3 figures, 1 table; Comments welcome

    Concept Graph Neural Networks for Surgical Video Understanding

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    We constantly integrate our knowledge and understanding of the world to enhance our interpretation of what we see. This ability is crucial in application domains which entail reasoning about multiple entities and concepts, such as AI-augmented surgery. In this paper, we propose a novel way of integrating conceptual knowledge into temporal analysis tasks via temporal concept graph networks. In the proposed networks, a global knowledge graph is incorporated into the temporal analysis of surgical instances, learning the meaning of concepts and relations as they apply to the data. We demonstrate our results in surgical video data for tasks such as verification of critical view of safety, as well as estimation of Parkland grading scale. The results show that our method improves the recognition and detection of complex benchmarks as well as enables other analytic applications of interest

    The impact of innovative technologies in construction activities on concrete debris recycling in China : a system dynamics-based analysis

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    As construction activities become more intensive in developing countries, increasing improperly managed construction and demolition waste (CDW) brings serious environmental impacts. Recycling is a beneficial way to dispose of CDW that reduces environmental impact and brings economic benefits, especially for concrete. China is the country that generates the most CDW in the world, but its domestic recycling rate is much lower than that of developed countries. While the efficient technologies in developed regions have helped them to achieve a well-established recycling industry, whether these innovative technologies can be used to improve the concrete debris recycling targets in developing regions is unclear. This study examines whether innovations currently widely used in construction activities and materials can have a positive effect on the recycling of End-of-Life concrete materials in China. Results from modeling system dynamics imply that the introduction of innovative technologies in the recycling system of concrete debris can probably contribute to CO2 reduction (3.6% reduction) and economic benefits (2.6 times increase, but mainly from landfill charges and fines) from 2022 to 2030. Prefabrication and 3D printing significantly impact recycled concrete production and CDW recycling, and they are recommended as a priority for promotion. In contrast, carbonation is not suggested for application due to its minor role. Nevertheless, since the market share of innovative technologies and the basic CDW recycling rates are currently low in China, fluctuations in their usage are hardly to have a substantial positive impact. We suggest that financial support from the government is needed for upcycling by recyclers and technology providers to improve the base recycling rate in order for innovative technologies to make an effective contribution to the sustainable construction industry, creating a win–win situation for both the economy and the environment of the recycling system

    Composing games into complex institutions

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    Game theory is used by all behavioral sciences, but its development has long centered around tools for relatively simple games and toy systems, such as the economic interpretation of equilibrium outcomes. Our contribution, compositional game theory, permits another approach of equally general appeal: the high-level design of large games for expressing complex architectures and representing real-world institutions faithfully. Compositional game theory, grounded in the mathematics underlying programming languages, and introduced here as a general computational framework, increases the parsimony of game representations with abstraction and modularity, accelerates search and design, and helps theorists across disciplines express real-world institutional complexity in well-defined ways. Relative to existing approaches in game theory, compositional game theory is especially promising for solving game systems with long-range dependencies, for comparing large numbers of structurally related games, and for nesting games into the larger logical or strategic flows typical of real world policy or institutional systems.Comment: ~4000 words, 6 figure

    Advancing Model Pruning via Bi-level Optimization

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    The deployment constraints in practical applications necessitate the pruning of large-scale deep learning models, i.e., promoting their weight sparsity. As illustrated by the Lottery Ticket Hypothesis (LTH), pruning also has the potential of improving their generalization ability. At the core of LTH, iterative magnitude pruning (IMP) is the predominant pruning method to successfully find 'winning tickets'. Yet, the computation cost of IMP grows prohibitively as the targeted pruning ratio increases. To reduce the computation overhead, various efficient 'one-shot' pruning methods have been developed, but these schemes are usually unable to find winning tickets as good as IMP. This raises the question of how to close the gap between pruning accuracy and pruning efficiency? To tackle it, we pursue the algorithmic advancement of model pruning. Specifically, we formulate the pruning problem from a fresh and novel viewpoint, bi-level optimization (BLO). We show that the BLO interpretation provides a technically-grounded optimization base for an efficient implementation of the pruning-retraining learning paradigm used in IMP. We also show that the proposed bi-level optimization-oriented pruning method (termed BiP) is a special class of BLO problems with a bi-linear problem structure. By leveraging such bi-linearity, we theoretically show that BiP can be solved as easily as first-order optimization, thus inheriting the computation efficiency. Through extensive experiments on both structured and unstructured pruning with 5 model architectures and 4 data sets, we demonstrate that BiP can find better winning tickets than IMP in most cases, and is computationally as efficient as the one-shot pruning schemes, demonstrating 2-7 times speedup over IMP for the same level of model accuracy and sparsity.Comment: Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022
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