Tags: computational materials science

Description

Computational materials science is the application of computational methods alone or in conjunction with experimental techniques to discover new materials and investigate existing materials such as: metals, ceramics, composites, semiconductors, nanostructures, 2D materials, metamaterials, polymers, liquid crystals, surfactants, emulsions, polymer nanocomposites, nanocrystal superlattices and nanoparticles.

All Categories (41-60 of 187)

  1. Gas Diffusion Coefficient in Metal Organic Frameworks

    28 May 2019 | | Contributor(s):: Julian Chinonso Umeh, Thomas A Manz

    Calculates gas self diffusion coefficient in metal organic frameworks

  2. Chris Jones

    https://nanohub.org/members/221455

  3. 3 min Research Talk: Analysis of Radiation Induced Segregation in Fe-Cr-Al Alloys

    31 Jan 2019 | | Contributor(s):: Timothy Joe Pownell

    This presentation gives an overview of the results and tool that were developed from data on Radiation Induced Segregation of the prospective cladding material Fe-Cr-Al.

  4. 3 min Research Talk: AFM And EBSD Cross-Comparison Analysis Tool

    31 Jan 2019 | | Contributor(s):: Andrew Martin Krawec

    This talk describes an approach to analyzing the crystal structure using data collected from AFM and EBSD scans to build an accurate image of the crystal structure and orientation in the ceramic

  5. 3 min Research Talk: Predicting and Optimizing Solar Cell Performance with Material/Surface Characteristics

    31 Jan 2019 | | Contributor(s):: Yiheng Zhu

    Photovoltaic simulation tools can be utilized to predict device performance before fabrication and experimentation, streamline research processes, and interpret experimental results. Therefore, we developed ContourPV, which simulates various combinations of values of different device...

  6. Ionization Potential of Small Molecules Using DFT

    27 Aug 2018 | | Contributor(s):: Alejandro Strachan

    Use DFT simulations to explore the ionization potential (energy required to remove an electron) in atoms and small molecules. Disclaimer: While very powerful, DFT makes well known approximations and the results obtained in this module are approximate. 

  7. Scaffolding Simulations in a Rate Processes of Materials Course

    16 Aug 2018 | | Contributor(s):: Susan P Gentry

    This learning resource describes a set of programming assignments that are used in a Rate Processes of Materials course. The assignments are designed around the pedagogical principle of scaffolding, in which students are given initial support structures that are gradually removed. The...

  8. Mostopha Muhammad Labib

    https://nanohub.org/members/203896

  9. Bibek Jung Karki

    https://nanohub.org/members/193307

  10. Akshat Saraf

    Chemistry PhD Student at Georg August Universität GöttingenUsing computational chemistry to better inform electrochemical experiments

    https://nanohub.org/members/190860

  11. Rajan Khadka

    Bsc in Applied Physics, Kathmandu University, Dhulikhel, NepalMS in Material Science, Missouri State University, Springfield, Missouri

    https://nanohub.org/members/189499

  12. AIDA: A tool for exhaustive enumeration of solutions to the quantized Frank-Bilby equation

    08 Jan 2018 | | Contributor(s):: Ali Sangghaleh, Michael J. Demkowicz

    We present a tool called Arrangement of Interface Dislocation Arrays (AIDA) for enumerating all dislocation networks that satisfy the quantized Frank-Bilby equation for any interface between cubic crystals with a single-atom basis, i.e. FCC/FCC, BCC/BCC, and FCC/BCC interfaces. The set of...

  13. shigueru emilio nagata

    I’m MSc. Physics from National University of Engineering. I’m a researcher in materials science. I research mechanical properties and electronic structure with density functional theory and...

    https://nanohub.org/members/188255

  14. Dibya Prakash Rai

    https://nanohub.org/members/187116

  15. Anter A El-azab

    Dr. El-Azab is a professor of Materials Science and Engineering at Purdue University. His research interests are in the broad area of microstructure science. His current research includes mesoscale...

    https://nanohub.org/members/186519

  16. Phase Transforming Cellular Materials Simulator

    07 Jun 2017 | | Contributor(s):: Yunlan Zhang, Chidubem Nuela Enebechi, Kristiaan William Hector, Gavin Carter, ASHLEY MIN, Valeria Grillo, David Restrepo, Nilesh Mankame, Pablo Daniel Zavattieri

    The tool will predict mechanical behavior of PXCMs given the the response of the unit cell

  17. High Throughput DFT Calculation Resources

    16 Jun 2017 | | Contributor(s):: Austin Jacob Zadoks, Karthik Guda Vishnu, Sam Reeve, David M Guzman, Alejandro Strachan

    Python functions / libraries / other resources useful for running High Throughput (query-based) DFT calculations on nanoHUB

  18. Daryl Chrzan

    Daryl C. Chrzan is a Professor of Materials Science at the University of California, Berkeley, and holds a joint appointment at Lawrence Berkeley National Laboratory, where he is a member of the...

    https://nanohub.org/members/179730

  19. Spin Transport Modeling Tool

    21 Aug 2017 | | Contributor(s):: Onur Dincer, Azad Naeemi

    Calculates spin transport parameters in nanoscale metallic interconnects.

  20. Comparing the Operation of p-i-n vs. p-n Junction Diodes Using PN Junction Lab in ABACUS

    22 Aug 2017 | | Contributor(s):: André Schleife, Materials Science and Engineering at Illinois

    In this activity, students use the PN Junction Lab simulation tool in ABACUS on nanoHUB to simulate different p-i-n or p-n diode structures.  Plots of hole concentration and electric field as a function of position, along with the gand structure with and without applied bias, will be...