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Pittsburgh

Seda Oturak

Expert
@sedaoturak

I'm PhD candidate in Materials Informatics, learning how to effectively apply data science and machine learning methods to accelerate materials design.

data-resources-for-materials-science. A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.

448

Quantum_Espresso_Colab. This repository includes a notebook to run the open-source materials modeling package Quantum Espresso on Google Colab.

18

vae_cahn-hilliard. Generative model variational autoencoder (VAE) implementation for the predictions of phase separation in binary alloys

6

linear_elasticity_3D_fenics. Finite element modeling for linear elasticity problem in 3D by using FEniCS software

4

normalization-frc. Simple desktop application for normalization of tensile/compression test data of fiber reinforced composites

3

dcgan_cahn-hilliard. Generative model Deep Convolutional Generative Adversarial Networks (DCGAN) implementation for the predictions of phase separation in binary alloys

2

ScienceU. Material simulation tutorial on DFT for high school students to find alternative, green energy source to fossil fuels.

1

simple_digital_twin_in_materials_science. Simple Digital Twin example in materials science

1

OC22_adsorption_energy. Notebook for calculating adsorption energy from the total energies in OC22 dataset.

1

tricks_for_efficient_pytorch. Some tricks to speed up the codes written with PyTorch library.

1