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.
Angelo Giovanni Oñate Soto
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...
Citrine Tools for Materials Informatics
05 Dec 2019 | | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan
Jupyter notebooks for sequential learning in the context of materials design. Run your own models, explore various methods and adapt the notebooks to your needs.
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.
Aug 12 2019
ICANM2019:7th International Conference & Exhibition on Advanced & Nano Materials
Jun 16 2019
Hands-on workshop: Introduction to using nanoHUB’s free online computational materials simulations for undergraduate education
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.
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
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...
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.
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...
Mostopha Muhammad Labib
Bibek Jung Karki
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...
Dibya Prakash Rai
Anter A El-azab
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