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Browsing by Author "Wen, Chengyuan"

Now showing 1 - 4 of 4
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    Computational Studies of Polyetherimides: Beyond All-Atom Molecular Dynamics Simulations
    Wen, Chengyuan (Virginia Tech, 2020-01-24)
    Polyetherimides are an important class of engineering thermoplastics used in a broad range of industries and applications because of their high heat resistance and stability, high strength and moduli, excellent electrical properties over a wide range of temperatures and frequencies, good processability, good adhesive properties, and chemical stability. All-atom molecular dynamics (MD) simulation is a useful tool to study polymers, but the accessible length and time scales are limited. In this thesis, we explore several computational methods that go beyond all-atom MD simulations to investigate polyetherimides. First, we have developed a transferable coarse-grained MD model of polyetherimides that captures their mechanical and thermal expansion properties. Our results show that in order to make the model transferable, it is critical to include an entropic correction term in the coarse-grained force field and require the coarse-grained model to capture the thermal expansion property of polyetherimides. Secondly, we have constructed a predictive model of the glass transition temperature (Tg) for polyimides by using machine-learning algorithms to analyze existing data on Tg reported in the literature. The predictive model is validated by comparing its predictions to experimental data not used in the training process of the model. We further demonstrate that the diffusion coefficients of small gas molecules can be quickly computed with all-atom MD simulations and used to determine Tg. Finally, we have developed a Monte Carlo (MC) program to model the polymerization process of branched polyetherimides and to compute their molecular weight distribution for a wide range of systems, including fully reacted, partially reacted, stoichiometric, and nonstoichiometric ones. The MC results are compared to the predictions of the Flory-Stockmayer theory of branched polymers and an excellent agreement is found below the gel point of the system under consideration. Above the gel point, the Flory- Stockmayer theory starts to fail but the MC method can still be used to quickly determine the molecular weight distribution of branched polyetherimides under very general conditions.
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    Hadoop Project for IDEAL in CS5604
    Cadena, Jose; Chen, Mengsu; Wen, Chengyuan (Virginia Tech, 2015-05-11)
    The Integrated Digital Event Archive and Library (IDEAL) system addresses the need for combining the best of digital library and archive technologies in support of stakeholders who are remembering and/or studying important events. It leverages and extends the capabilities of the Internet Archive to develop spontaneous event collections that can be permanently archived as well as searched and accessed. IDEAL connects the processing of tweets and web pages, combining informal and formal media to support building collections on chosen general or specific events. Integrated services include topic identification, categorization (building upon special ontologies being devised), clustering, and visualization of data, information, and context. The objective for the course is to build a state-of-the-art information retrieval system in support of the IDEAL project. Students were assigned to eight teams, each of which focused on a different part of the system to be built. These teams were Solr, Classification, Hadoop, Noise Reduction, LDA, Clustering, Social Networks, and NER. As the Hadoop team, our focus is on making the information retrieval system scalable to large datasets by taking advantage of the distributed computing capabilities of the Apache Hadoop framework. We design and put in place a general schema for storing and updating data stored in our Hadoop cluster. Throughout the project, we coordinate with other teams to help them make use of readily available machine learning software for Hadoop, and we also provide support for using MapReduce. We found that different teams were able to easily integrate their results in the design we developed and that uploading these results into a data store for communication with Solr can be done, in the best cases, in a few minutes. We conclude that Hadoop is an appropriate framework for the IDEAL project; however, we also recommend exploring the use of the Spark framework.
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    Molecular Weight Distribution of Branched Polymers: Comparison between Monte Carlo Simulation and Flory-Stockmayer Theory
    Wen, Chengyuan; Odle, Roy; Cheng, Shengfeng (MDPI, 2023-04-04)
    It is challenging to predict the molecular weight distribution (MWD) for a polymer with a branched architecture, though such information will significantly benefit the design and development of branched polymers with desired properties and functions. A Monte Carlo (MC) simulation method based on the Gillespie algorithm is developed to quickly compute the MWD of branched polymers formed through step-growth polymerization, with a branched polyetherimide from two backbone monomers (4,4′-bisphenol A dianhydride and m-phenylenediamine), a chain terminator (phthalic anhydride), and a branching agent (tris[4-(4-aminophenoxy)phenyl] ethane) as an example. This polymerization involves four reactions that can be all reduced to a condensation reaction between an amine group and a carboxylic anhydride group. A comparison between the MC simulation results and the predictions of the Flory-Stockmayer theory on MWD shows that the rates of the reactions are determined by the concentrations of the functional groups on the monomers involved in each reaction. It further shows that the Flory-Stockmayer theory predicts MWD well for systems below the gel point but starts to fail for systems around or above the gel point. However, for all the systems, the MC method can be used to reliably predict MWD no matter if they are below or above the gel point. Even for a macroscopic system, a converging distribution can be quickly obtained through MC simulations on a system of only a few hundred to a few thousand monomers that have the same molar ratios as in the macroscopic system.
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    Xeditor: Inferring and Applying XML Consistency Rules
    Wen, Chengyuan (Virginia Tech, 2019-12)
    XML files are frequently used by developers when building Web applications or Java EE applications. However, maintaining XML files is challenging and time-consuming because the correct usage of XML entities is always domain-specific and rarely well documented. Also, the existing compilers and program analysis tools seldom examine XML files. In this thesis, we developed a novel approach to XML file debugging called Xeditor where we extract XML consistency rules from open-source projects and use these rules to detect XML bugs. There are two phases in Xeditor: rule inference and application. To infer rules, Xeditor mines XML-based deployment descriptors in open-source projects, extracting XML entity pairs that frequently co-exist in the same files and refer to the same string literals. Xeditor then applies association rule mining to the extracted pairs. For rule application, given a program commit, Xeditor checks whether any updated XML file violates the inferred rules; if so, Xeditor reports the violation and suggests an edit for correction?. Our evaluation shows that Xeditor inferred rules with high precision (83%). For injected XML bugs, Xeditor detected rule violations and suggested changes with 74.6% precision, 50% recall. More importantly, Xeditor identified 31 really erroneous XML updates in version history, 17 of which updates were fixed by developers in later program commits. This observation implies that by using Xeditor, developers would have avoided introducing errors when writing XML files. Finally, we compared Xeditor with a baseline approach that suggests changes based on frequently co-changed entities, and found Xeditor to outperform the baseline for both rule inference and rule application.