Source of the paper "Automatic extraction of materials and properties from superconductors scientific literature"
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Updated
Dec 7, 2022 - TeX
Source of the paper "Automatic extraction of materials and properties from superconductors scientific literature"
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
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 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.
Transport solver for a two-terminal superconducting junction for probing a tight-binding mean-field structure
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/
Tools for general Tight Binding systems
Implementation of SuperDiff: Diffusion Models for Conditional Generation of Hypothetical New Families of Superconductors
A term paper discussing the history, developments and applications of High Temperature 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
Repository for the publication "Leveraging composition-based energy material descriptors for machine learning models"
Material parsers and other tools, scripts Initially developed for Grobid Superconductor
Notes for anyone who is interested in quickly familiarizing themselves with superconductors from a materials science perspective
Workflow for generating formulas of chemically novel superconductors
The critical temperature of a superconductor is predicted using XGBoost algorithm.
Source of the short paper titled "Proposal of Automatic Extraction Framework of Superconductors related Information from Scientific literature"
Predicting critical temperature of Superconductors using multiple linear regression and XGBoost methods
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