GDSHelpers is an open-source package for automatized pattern generation for nano-structuring.
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Updated
May 25, 2022 - Python
GDSHelpers is an open-source package for automatized pattern generation for nano-structuring.
Simulate the magnetic response of 2D superconductors
Superconductors material dataset
Grobid module for superconductor material and properties extraction
Tools for general Tight Binding systems
Spectral Solver for the Ginzburg-Landau equation
Material parsers and other tools, scripts Initially developed for Grobid Superconductor
Desktop app for lithography learning available for Windows, macOS, and Linux
Training a GAN using superconductivity data
Superconductivity is a phenomenon where a charge can move through a material without any resistance. This allows electricity to be conducted at maximum efficiency. TensorFlow was used to make an accurate Neural Network.
A term paper discussing the history, developments and applications of High Temperature Superconductors
Implementation of Diffusion Models for Conditional Generation of Hypothetical New Families of Superconductors
Staging-area for automatically collected experimental data for the SuperCon database with a curation interface with enhanced-document viewer and curation-ready interface
A research paper detailing the model building process of principal component regression using mathematical notation and a demonstration using the superconductivity dataset from the UCI machine learning repository.
Predicting critical temperature of Superconductors using multiple linear regression and XGBoost methods
Notes for anyone who is interested in quickly familiarizing themselves with superconductors from a materials science perspective
Topological Superconductors - Notebooks for an introductory course
Tools designed to extract Resonant Frequency & Coupling Quality Factor for Microwave Kinetic Inductance Detector Simulations using a Sonnet .csv data file.
A website to quickly plot PPMS data and find the Critical current (Ic) of an IV curve. deployed at https://share.streamlit.io/iamashwin99/jj-ic-finder/main/app.py and https://jj-ic-finder.herokuapp.com/
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