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Computational Catalysis with Density Functional Theory
08 Aug 2018 | Contributor(s):: Kevin Greenman, Peilin Liao
Heterogeneous catalysis is used in a significant portion of production processes in the industrialized world, which makes maximizing the efficiency of catalysts a high priority. However, the immense number of candidates for new catalysts precludes the possibility of testing all of them by...
Computational Catalysis with DFT
01 Aug 2018 | Contributor(s):: Kevin Greenman, Peilin Liao
DFT tool for studying heterogeneous catalysis
High Pressure DFT Data
20 Feb 2018 | Contributor(s):: Austin Zadoks, Sam Reeve, Karthik Guda Vishnu, Alejandro Strachan
Query and retrieve elastic constants and phase stability data from high-pressure DFT calculations
Dibya Prakash Rai
Using DFT to Predict the Equilibrium Lattice Parameter and Bulk Modulus of Crystalline Materials
23 Aug 2017 | Contributor(s):: André Schleife, Materials Science and Engineering at Illinois
This activity guides users through the use of DFT calculations with Quantum ESPRESSO in nanoHUB to calculate the total energy of a crystal structure. By varying the volume of the structure, and calculating the associated energies, the equilibirum structure can be found. Users are...
Using DFT to Simulate the Band Structure and Density of States of Crystalline Materials
In this activity, DFT is used to simulate the band structure and density of states of several crystalline semiconductors. Users are instructed in how to use the Bilbao Crystallographic Server to select a path through the Brillouin zone for each structure.This activity is adapted from an...
Computer Modeling Module: Chemical Reaction Simulation using SIESTA
23 Aug 2017 | | Contributor(s):: Lan Li
This activity guides students through a module using the SIESTA DFT tool that is housed within the MIT Atomic Scale Modeling Toolkit on nanoHUB. Instructional videos, background reading, reminders and the assignment are included.Learning outcomes:Get familiar with SIESTA tool and activation...
2016 IMECE Tutorials on Phonon Transport Modeling
04 Jan 2017 | | Contributor(s):: Alan McGaughey, Xiulin Ruan
Advances in theoretical methodologies and computational power in the last fifteen years have enabled the prediction of phonon properties with high resolution and fidelity. Notably, the use of molecular dynamics simulations, lattice dynamics calculations, density functional theory calculations,...
Fundamentals of Phonon Transport Modeling L4: Anharmonic Lattice dynamics, First Principles
Part of the 2016 IMECE Tutorial: Fundamentals of Phonon Transport Modeling: Formulation, Implementation, and Applications.
Machine learned approximations to Density Functional Theory Hamiltonians - Towards High-Throughput Screening of Electronic Structure and Transport in Materials
13 Dec 2016 | | Contributor(s):: Ganesh Krishna Hegde
We present results from our recent work on direct machine learning of DFT Hamiltonians. We show that approximating DFT Hamiltonians accurately by direct learning is feasible and compare them to existing semi-empirical approaches to the problem. The technique we have proposed requires little...
OQMD: The Open Quantum Materials Database
03 Nov 2016 |
Posted by Tanya Faltens
GGA-PBE Prediction of TiC Bulk Modulus
31 Oct 2016 |
Posted by David M Guzman
Si band structure sequence
30 Oct 2016 |
Posted by Tanya Faltens
NEMO5 and 2D Materials: Tuning Bandstructures, Wave Functions and Electrostatic Screening
19 Oct 2016 | | Contributor(s):: Tillmann Christoph Kubis
In this talk, I will briefly discuss the MLWF approach and compare it to DFT and atomistic tight binding. Initial results using the MLWF approach for 2D material based devices will be discussed and compared to experiments. These results unveil systematic band structure changes as functions of the...
Jun 26 2016
nanoHUB Materials Simulation Workshop
Introduction to Computational Modeling - Input Parameters for SIESTA Simulation
16 Jun 2016 | | Contributor(s):: Lan Li
This instructional video is part 2 in a two part series. It explains how to set up input parameters for the SIESTA simulation tool.