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

Material parsers and other tools, scripts Initially developed for Grobid Superconductor

Spectral Solver for the Ginzburg-Landau equation

Desktop app for lithography learning available for Windows, macOS, and Linux

Implementation of Diffusion Models for Conditional Generation of Hypothetical New Families of Superconductors

Training a GAN using superconductivity data

Staging-area for automatically collected experimental data for the SuperCon database with a curation interface with enhanced-document viewer and curation-ready interface

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

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.

Machine-Learning Predictions of Critical Temperatures from Chemical Compositions of Superconductors

Notes for anyone who is interested in quickly familiarizing themselves with superconductors from a materials science perspective

Predicting critical temperature of Superconductors using multiple linear regression and XGBoost methods

Tools designed to extract Resonant Frequency & Coupling Quality Factor for Microwave Kinetic Inductance Detector Simulations using a Sonnet .csv data file.

Topological Superconductors - Notebooks for an introductory course