All Categories (1-20 of 108)

1. 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...

2. 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.

3. 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.

4. 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.

5. 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....

6. 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.

7. 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.

8. 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...

9. 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...

10. 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...

11. 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...

12. Plasmonic Core-Multishell Nanowires for Optical Applications

    01 Aug 2019 | | Contributor(s):: Raheem Carless, Amartya Dutta

    LEDs are very useful in today’s society, especially when compared to conventional incandescent and fluorescent lamps. According to the US Department of Energy, by 2027 the use of LEDs could save 348 TWh of electricity, which is the equivalent...

13. Elastoplastic Response of Compacted Pharmaceutical Powder Blends: Model Development, Calibration and Validation.

    01 Aug 2019 | | Contributor(s):: Paul Beckwith, Pedro Henrique Cidreiro Martins, Marcial Gonzalez

    The compaction of granular materials is a common operation in many industrial manufacturing processes, ranging from farming to pharmaceuticals, dietary supplements to diagnostics, and many others. The operation involves combining a mixture of powdered substances into a single bonded compact, or...

14. Hierarchical Material Optimization using Neural Networks

    01 Aug 2019 | | Contributor(s):: Miguel Arcilla Cuaycong, Valeria Grillo, Kristiaan William Hector, Pablo Daniel Zavattieri

    Material structures that occur in nature are commonly made up of complex architectures arranged in a hierarchy. These hierarchical architectures are made up of different structural levels consisting of a unique arrangement of simple constituents, acting as building blocks, that satisfy a local...

15. NCN URE Communicating Science Resources

    Communicating Science Example Talks from the MOS Workshop CSW_Example_Talks.pptx (95 MB, uploaded by Tanya Faltens 49 minutes ago) Mastering Science Presentations Seminar – Tim Miller (MRS...

    https://nanohub.org/wiki/NCNURECommunicatingScienceResources

16. Structural Analysis for Molecular Dynamics Trajectories

    03 Mar 2019 | | Contributor(s):: Nicholas J Finan, Saaketh Desai, Sam Reeve, Alejandro Strachan

    This tool reads in LAMMPS trajectories and performs the following analysis: Radial Distribution Function (RDF), X-Ray Diffraction (XRD), Vibrational Density of States, and  (More to Come!). By default the tool requires trajectory files to be input by the user however there are some...

17. Ellipsoid Detection Using Matlab Image Processing

    27 Feb 2019 | | Contributor(s):: Gabrielle Kershaw, Charlie Lin, Cheng-wei Tai, Vivek Narsimhan

    The objective of this project was to create code using functions found in MATLAB Image Processing Toolbox, such as edge detection, thresholding, and morphology to isolate the desired ellipsoidal particles in images obtained from experiments. The code was to become a research tool that...

18. Analyzing Tensile Strength and Fracture Behavior in MCC and Lactose Composite Tablets

    27 Feb 2019 | | Contributor(s):: Melanie Hacopian, Marcial Gonzalez, Isabel Bojanini, Vidal Lopez, Jesse Lee Hoffman, Caroline Baker

    Tablets containing various compositions of MCC and Lactose at several relative densities were subjected to fracture and analyzed for tensile strength. Results showed that as the mass fraction of Lactose increased, tensile strength and fracture strength decreased. Analyzing the tensile strength...

19. 3 min. Research Talk: Image Analysis of a Vesicle to Calculate the Bending Modulus

    04 Feb 2019 | | Contributor(s):: Pheobe Jane Appel

20. 3 min. Research Talk: Phase Transforming Cellular Materials

    04 Feb 2019 | | Contributor(s):: Valeria Grillo