Build atomistic structures of carbon nanotubes with the possibility to add functional groups (OH, COOH, COO-) and assigns generalized Amber (GAFF) parameters to them.

CNTT, also spelled C-entity, is an acronym for Carbon Nano Tube Tool. It's a tool for computing, displaying and manipulating properties of carbon nanotubes.

Calculation of intersubband plasmons in doped carbon nanotubes.

Electrostatic-Quantum Transport framework based on nonequilibrium Green's function method for modeling field effect transistors (FETs)

An old Fortran program for generating carbon nanotube coordinates.

Simulation for the conduction between carbon nanotubes (CNTs) in a random network field effect transistor

Associated repository for the "Should we be building Space Elevators to reduce cost to access space?" 15 minute discourse podcast on YouTube!

Code to generate randomised initial periodic molecular structure with 2 molecule types for MD simulations

The main objective in this analysis will be to use deep learning algorithms to predict atomic coordinates of carbon nanotubes. Using the carbon nanotubes dataset from the UCI Machine Learning data repository.

Ansys Mechanical APDL files for mesh generation and simulation of carbon reinforced composites

A Blender Python add-on for generating graphene sheets and carbon nanotubes (CNTs) with customizable chirality, geometry, and atomic properties. This tool allows users to create accurate 3D atomic models directly in Blender, ideal for visualization, simulation preparation, or educational use.

Monte Carlo simulation of exciton diffusion in carbon nanotube networks

This repository contains source code and PCB designs for a switch matrix to measure carbon nanotube field-effect transistors.

A cutting-edge approach to accelerating Carbon Nanotube (CNT) growth via a human-AI hybrid system that leverages advanced generative AI techniques and feedback loops.

An open source with graphical user interface (GUI) for choosing a minimal sensor set out of analyte-sensor screening data, that preserves both accuracy and minimal sensor number.