NCN Undergraduate Research Experience 2019 - 3 Minute Research Talks

Category

Workshops

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Abstract

As part of each student's undergraduate research experience, each student gave a 3 minute presentation describing their research work.

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Cite this work

Researchers should cite this work as follows:

  • (2019), "NCN Undergraduate Research Experience 2019 - 3 Minute Research Talks," https://nanohub.org/resources/31335.

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Time

Location

Rawls 1062, Purdue University, West Lafayette, IN

Tags

NCN URE 2019

NCN URE 2019 group image

In This Workshop

  1. 3 min Research Talk: Web-based Machine Learning Tool for Material Discovery and Property Prediction

    26 Sep 2019 | Online Presentations | Contributor(s): Bryan Arciniega

    This model allows the end-user to increase their knowledge on a scarce data set by using a data-rich property set. We also investigate the effect of chemical representation and autoencoder type on property prediction and compound generation.

  2. 3 min Research Talk: Plasmonic Core-Multishell Nanowires for Optical Applications

    26 Sep 2019 | Online Presentations | Contributor(s): Raheem Carless

    ED lights and technology are being used more often in today’s society. Compared to traditional illumination they are far more reliable and efficient, in the sense that they last longer, are environmentally friendly, and most importantly, they reduce energy waste.

  3. 3 min Research Talk: Using Machine Learning for Materials Discovery and Property Prediction

    26 Sep 2019 | Online Presentations | Contributor(s): Mackinzie S Farnell

    Machine Learning models present a transformative method of optimization and prediction in science and engineering research. In the chemical sciences, unsupervised deep learning models such as autoencoders have shown to be useful for property prediction and material...

  4. 3 min. Research Talk: The Agrivoltaic Simulation tool

    23 Oct 2019 | Online Presentations | Contributor(s): Hans Torsina

    The Agrivoltaic Simulation tool will calculate based on the solar panel parameters, geometries, patterns, and tracking system to provide outputs of contour shadowmaps, solar and electrical power output plots, along with input-output tables.

  5. 3 min Research Talk: Hierarchical Material Optimization using Neural Networks

    29 Oct 2019 | Online Presentations | Contributor(s): Miguel Arcilla Cuaycong

    In this presentation, we sought to use a neural network (NN) to identify optimal arrangements of four different constituents in a tape spring to be used as snapping mechanisms in phase transforming cellular material that can dissipate energy.