All Categories (1-20 of 117)

1. Antibody Engineers - Antibody Hackathon

   15 Jul 2022 |

2. USC Summer Undergraduate Research Experience (SURE) Opportunities and NanoResearch Efforts

   30 Jun 2022 | | Contributor(s):: Andrea Armani

   Prof. Armani presents nano-research opportunities for USC's Summer Undergraduate Research Experience (SURE) program.

3. MATE ROV Competiton

   30 Jun 2022 | | Contributor(s):: Jill Zande

   The MATE ROV Competition is an underwater robotics (aka remotely operated vehicle or ROV) challenge that engages a global community of learners each year.

4. URE Experience - DFT Thermoelectric Calculations

   15 Apr 2022 | | Contributor(s):: Gustavo Javier

   Gustavo discusses his experience in the 2015 NCN URE program and his work to develop a thermoelectric simulation for the nanoHBU tool DFT Material Properties Simulator . Gustavo Javier now teaches high school physics in the Los Angeles area.The DFT Material Properties Simulator can compute...

5. LAMMPS Data File Generator Tool Demo

   15 Apr 2022 | | Contributor(s):: Carlos Miguel Patiño

   A quick demonstration of the nanoHUB tool LAMMPS Data-File Generator. This was developed as part of the 2017 NCN URE program.

6. SCME and URE Program – It’s about the Students!

   28 Oct 2020 | | Contributor(s):: Matthias Pleil, The Micro Nano Technology - Education Center

   This session will be talking about his 2021 MEMS workshop and the upcoming URE opportunities at the University of New Mexico.

7. Bandgap Manipulation of Armchair Graphene nanoribbon

   01 Sep 2020 | | Contributor(s):: Lance Fernandes

   Bandgap Manipulation is very important for various applications. Optical Devices need smaller Bandgap where as Diode's need larger Bandgap. Armchair graphene Nanoribbon (AGNR) has a special property where if the numbers of atoms are multiple of three or multiple of three plus one, they are...

8. Illustrative Mathematical Concepts

   29 Jul 2020 | | Contributor(s):: Hae Ji Kwon, David R. Ely

   Illustrates mathematical concepts and their applications

9. 3 min. Research Talk: Identifying the Dimensionality of Crystal Structures

   12 Feb 2020 | | Contributor(s):: Franco Vera

   Today, researchers worldwide have identified over 100,000 distinct bulk materials. The underlying dimensionality of these materials is not always clear however, and as such researchers have sought to identify stable, lower dimensional materials derived from the bulk parent structures. A team of...

10. PhysiCell: Extracellular Matrix Modeling

    10 Dec 2019 | | Contributor(s):: John Metzcar, Ben Duggan, Daniel Matthew Murphy, Paul Macklin

    An extracellular matrix model developed in PhysiCell.

11. 3 min Research Talk: Hierarchical Material Optimization using Neural Networks

    29 Oct 2019 | | 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.

12. Hierarchical material optimization

    28 Oct 2019 | | Contributor(s):: Miguel Arcilla Cuaycong

    Assembles all possible configurations of a structural level in a Hierarchical Material.

13. 3 min. Research Talk: The Agrivoltaic Simulation tool

    23 Oct 2019 | | 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.

14. Image Analysis of a Vesicle to Calculate the Bending Modulus

    10 Oct 2019 | | Contributor(s):: Pheobe Jane Appel, Charlie Lin, Vivek Narsimhan

    The cell membrane is an essential component of living cells; the dynamics of the membrane will provide insight into how a biological cell will react to mechanical strain.  Membrane mechanics are important in a variety of cellular processes like secretion, trafficking, signaling, and storage....

15. 3 min Research Talk: Web-based Machine Learning Tool for Material Discovery and Property Prediction

    26 Sep 2019 | | 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.

16. 3 min Research Talk: Plasmonic Core-Multishell Nanowires for Optical Applications

    26 Sep 2019 | | 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.

17. 3 min Research Talk: Using Machine Learning for Materials Discovery and Property Prediction

    26 Sep 2019 | | 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...

18. Agrivoltaic Simulation

    23 Sep 2019 | | Contributor(s):: Hans Torsina, Allison Perna, Peter Bermel

            With the continually increasing food and energy demands which require sustainability, novel solutions in which agrivoltaic (agrophotovoltaic) is a part of are pushed to solve local land shortages and increase land productivity. Compared to...

19. Machine Learning for Property Prediction and Materials Discovery

    20 Sep 2019 | | Contributor(s):: Mackinzie S Farnell, Nicolae C Iovanac, Brett Matthew Savoie

    Machine learning displays excellent potential for generating material property predictions and discovering novel compounds with desirable properties; however, it can be prohibitively costly to obtain data to train machine learning models. This barrier can be overcome by training models to...

20. Web-based Machine Learning Tool for Material Discovery and Property Prediction

    20 Aug 2019 | | Contributor(s):: Bryan Arciniega, Mackinzie S Farnell, Nicolae C Iovanac, Brett Matthew Savoie

    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...