Tags: undergraduate research

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  1. Phase Transforming Cellular Material Simulator

    27 Aug 2018 | | Contributor(s):: Gavin Carter, Yunlan Zhang, Kristiaan William Hector, Pablo Daniel Zavattieri

    Cellular material that exhibits phase transformations provide a variety of applications from the construction of medical casts to car bumpers. Materials with multiple phases are able to experience a multitude of loading and unloading forces. How the materials reacts is in part due to its...

  2. Phase Transforming Cellular Materials (Spherical Shells)

    27 Aug 2018 | | Contributor(s):: Valeria Grillo, ASHLEY MIN, Gavin Carter, Yunlan Zhang, Kristiaan William Hector, David Restrepo Arango, Chidubem Nuela Enebechi, Pablo Daniel Zavattieri, Nilesh Mankame

    “Phase transforming cellular materials (PXCMs) are a class of materials whose unit cells exhibit multiple configurations (metastable or bistable) [1]. The geometrical structure of the PXCM can change to increase the energy absorbed. The hysteretic nature of the PXCM makes the potential...

  3. AFM And EBSD Cross-Comparison Analysis Tool

    14 Aug 2018 | | Contributor(s):: Andrew Martin Krawec, John Blendell, Matthew John Michie

    Ceramic and semiconductor research is limited in its ability to create holistic representations of data in concise, easily-accessible file formats or visual data representations. These materials are used in everyday electronics, and optimizing their electrical and physical properties is...

  4. Developing a machine learning tool to optimize thermal transport

    14 Aug 2018 | | Contributor(s):: Adam Sandor Garrett, proycho, Xiulin Ruan, creynolds

    The purpose of this tool is to optimize SiGe super-lattices to have the lowest possible thermal conductivity. This poster describes the processes used in the tool and how it impacts thermoelectrics.

  5. Radiation Induced Segregation in Fe-Cr-Al Alloys

    14 Aug 2018 | | Contributor(s):: Timothy Joe Pownell, Janelle P Wharry, Priyam Vivek Patki

    This poster represents the results a summer long research project conducted by Timothy Pownell at the Purdue Nuclear Engineering Department. Specifically, the poster details the results and tool that were developed from data on Radiation Induced Segregation of the prospective cladding material...

  6. Building Nanohub Tool "Optical Properties of Single Coaxial Nanowires -LDOS and Purcell Factor"

    14 Aug 2018 | | Contributor(s):: Sulaiman Abdul-Hadi, Amartya Dutta, Melissa P Cardona, Chen Yang

    My project was to build a simulation tool for Nanohub.org. The tool that I made is called “Optical Properties of Single Coaxial Nanowires -LDOS and Purcell Factor”, or NWLDOS.

  7. Powder Compaction and Unloading Simulation Poster

    08 Aug 2018 | | Contributor(s):: Jesse Lee Hoffman, Isabel Bojanini, Melanie Hacopian, Vidal Lopez, Caroline Baker, Marcial Gonzalez

    This poster shows the development process of a tool that simulates the mechanical behavior of a binary mixture during compaction and unloading.

  8. Predicting and Optimizing Solar Cell Performance with Material/Surface Characteristics

    08 Aug 2018 | | Contributor(s):: Yiheng Zhu, Allison Perna, Peter Bermel

    Renewable energy sources have begun replacing fossil fuels at the utility scale. In particular, photovoltaics has grown rapidly in recent years. To further improve solar technology in terms of cost and efficiency and promote adoption, researchers often seek material and device level...

  9. The Exciton Spectra Simulator of Photosynthetic Protein-pigment Complex

    08 Aug 2018 | | Contributor(s):: Qifeng Chen, Yongbin Kim, Lyudmila V. Slipchenko

        The solar energy is one of the most successful alternative energy sources because of its unlimited availability and environmental friendliness. However, the energy transfer rate in artificial solar devices is significantly lower than the energy transfer rate in plants and...

  10. Deep Machine Learning for Machine Performance and Damage Prediction

    08 Aug 2018 | | Contributor(s):: Elijah Reber, Nickolas D Winovich, Guang Lin

    Deep learning has provided opportunities for advancement in many fields. One such opportunity is being able to accurately predict real world events. Ensuring proper motor function and being able to predict energy output is a valuable asset for owners of wind turbines. In this paper, we look at...

  11. Computational Catalysis with Density Functional Theory

    08 Aug 2018 | | Contributor(s):: Kevin Greenman, Peilin Liao

    Heterogeneous catalysis is used in a significant portion of production processes in the industrialized world, which makes maximizing the efficiency of catalysts a high priority. However, the immense number of candidates for new catalysts precludes the possibility of testing all of them by...

  12. Grain Boundary Motion Analysis

    08 Aug 2018 | | Contributor(s):: Jeremy Seiji Marquardt, Xiaorong Cai, Marisol Koslowski

        Grain growth is a mechanism to relax residual stresses in thin films. These grains grow out of the thin film surface and are known as whiskers. These whiskers can cause short circuits, so developing scalable and cost effective solutions would increase the reliability and...

  13. GUI for the Surface Evolver - Polycrystalline Grain Growth

    08 Aug 2018 | | Contributor(s):: Kevin K Ngo, Lucas Darby Robinson

    This poster summarizes how the the online simulation tool, GUI for the Surface Evolver, was created as well as how it will impact research in polycrystalline grain growth. Polycrystalline grains have surface energies and tensions associated with them that cause grain boundaries to move...

  14. Débora Jimena Mendoza Silva

    Chemistry Undergradute Student

    https://nanohub.org/members/201649

  15. Understanding Powder Compaction Using Single Particle Measurement

    23 Oct 2017 | | Contributor(s):: Wentao Chen, Ankit Agarwal, Marcial Gonzalez

    Powder compaction is the process of transforming granular media into a solid body with a high relative density (low porosity) and a unique anisotropic microstructure. It is critical to understand the physical mechanisms of the compaction process in order to identify powder properties and optimal...

  16. Quantum Dot Lab - A Novel Visualization Tool using Jupyter

    09 Oct 2017 | | Contributor(s):: Khaled Aboumerhi

    As semiconductor devices scale down into the nano regime, deep understanding of quantum mechanical properties of nano-structures become increasingly essential. Quantum dots are famous examples of such nano-structures. Quantum dots have attracted a lot of attention over the last two decades due...

  17. Modelling of Phase Transforming Cellular Material (PXCM)

    28 Aug 2017 | | Contributor(s):: Chidubem Nuela Enebechi, Yunlan Zhang, David Restrepo Arango, Pablo Daniel Zavattieri, Nilesh Mankame

    Phase transforming cellular materials (PXCMs) are a new class of materials that can go through large deformation and return to their original configuration. Currently, there are reliable cellular materials that can resist large deformation, for example, honey comb; however, when these materials...

  18. Electronic and Thermoelectric Characterization of Materials from Ab Initio Calculations

    15 Aug 2017 | | Contributor(s):: Gustavo Javier, David M Guzman, Austin Jacob Zadoks, Alejandro Strachan

    We present the Optimized Workflow for Electronic and Thermoelectric Properties (OWETP) python notebook, which uses Density Functional Theory (DFT) as implemented in the Quantum Espresso code for electronic properties of materials. The OWETP python notebook also enables connecting to the...

  19. Analytical Solution of Microbes Interacting with Surfaces

    14 Aug 2017 | | Contributor(s):: Junyuan Li, Vaseem Shaik, Arezoo Ardekani

    The biological or medical related problems are among the most heated topics in scientific field. There is a rising interest in studying the behavior of microbes and their interactions with flow. In order to explore the velocity fields, pressures and forces around the microbes, the solution of...

  20. Applying Machine Learning to Computational Chemistry: Can We Predict Molecular Properties Faster without Compromising Accuracy?

    14 Aug 2017 | | Contributor(s):: Hanjing Xu, Pradeep Kumar Gurunathan

    Non-covalent interactions are crucial in analyzing protein folding and structure, function of DNA and RNA, structures of molecular crystals and aggregates, and many other processes in the fields of biology and chemistry. However, it is time and resource consuming to calculate such interactions...