Graphene is a one-atom-thick planar sheet of sp2-bonded carbon atoms that are densely packed in a honeycomb crystal lattice. The term Graphene was coined as a combination of graphite and the suffix -ene by Hanns-Peter Boehm, who described single-layer carbon foils in 1962. Graphene is most easily visualized as an atomic-scale chicken wire made of carbon atoms and their bonds. The crystalline or "flake" form of graphite consists of many graphene sheets stacked together.
Learn more about quantum dots from the many resources on this site, listed below. More information on Graphene can be found here.
Fun with Carbon Nanostructures using Crystal Viewer 2.3.4
02 Nov 2021 | | Contributor(s):: Tanya Faltens
Quick tutorial/demonstration on how to create carbon nanostructures (buckyballs, graphene sheets, and carbon nanotubes) using Crystal Viewer 2.3.4.
Fusing Light With Heat: Polaritons for Nanoscale Thermal Transport & Sensing
07 Oct 2021 | | Contributor(s):: Thomas Beechem
Light exhibits a wave nature. Phonons do too. Within the infrared portion of the spectrum, these differing “waves” can interact to form hybrid energy carriers called polaritons. Polaritons, in turn, provide fundamental advantages for optical functionality and...
IWCN 2021: Recursive Open Boundary and Interfaces Method for Material Property Predictions
14 Jul 2021 | | Contributor(s):: James Charles, Sabre Kais, Tillmann Christoph Kubis
In this presentation, we show that assuming periodicity elevates a small perturbation of a periodic cell into a strong impact on the material property prediction. Periodic boundary conditions can be applied on truly periodic systems only. More general systems should apply an open boundary...
Gr-ResQ Tutorial II: Tool Demonstration and Training
04 Jun 2021 | | Contributor(s):: Mitisha Surana
Gr-ResQ (Graphene Rescue) Tool Tutorial & Training
03 Jun 2021 | | Contributor(s):: Mitisha Surana
This hands-on tutorial will introduce users to the Gr-ResQ (‘graphene rescue’) platform. Gr-ResQ is (i) an open, crowd-sourced database of recipes and characterization of graphene synthesized by chemical vapor deposition, (ii) a set of analysis tools that enable users to analyze the...
Gr-ResQ Tutorial I: Introduction and Framework
Gr-ResQ Tutorial III: Machine Learning and Beyound
FDNS21: Van der Waals Epitaxy of Atomically Thin Metal Oxide
20 May 2021 | | Contributor(s):: Lili Cai
FDNS21: Artificial van der Waals Crystals
27 Apr 2021 | | Contributor(s):: Cheol-Joo Kim
FDNS21: Predictive Models in Materials Making, 2D, 3D, 2.1D
27 Apr 2021 | | Contributor(s):: Boris I Yakobson
FDNS21: Conversion of Large-area AB-stacked Bilayer Graphene to F-diamane
27 Apr 2021 | | Contributor(s):: Rod Ruoff
FDNS21: Conversion of Metal Oxide Films to 2D Metal Chalcogenide Films
27 Apr 2021 | | Contributor(s):: Judy Cha
Mar 30 2021
MNT-EC Spring Development Workshop: CVD Synthesis and Image Analysis
Mar 23 2021
U-Net Convolutional Neural Networks for Image Segmentation: Application to Scanning Electron Microscopy Images of Graphene
01 Feb 2021 | | Contributor(s):: Aagam Rajeev Shah
This tutorial introduces you to U-Net, a popular convolutional neural network commonly developed for image segmentation in biomedicine. Using an assembled data set, you will learn how to create and train a U-Net neural network, and apply it to segment scanning electron microscopy images of...
Unsupervised Clustering Methods for Image Segmentation: Application to Scanning Electron Microscopy Images of Graphene
27 Jan 2021 | | Contributor(s):: Aagam Rajeev Shah
This tutorial will introduce you to some basic image segmentation techniques driven by unsupervised machine learning techniques such as the Gaussian mixture model and k-means clustering. You will learn how to implement k-means clustering and template matching, and use these to segment a...
SEM Image Segmentation Workshop
12 Jan 2021 | | Contributor(s):: Aagam Rajeev Shah, Darren K Adams, Mitisha Surana, Ricardo Toro, Sameh H Tawfick, Elif Ertekin
This tool introduces users to machine learning used to segment microscopy images
"Turning Fruit Juice into Graphene Quantum Dots" Supplementary Lesson Plans: Going Atomic
15 Nov 2020 | | Contributor(s):: Susan P Gentry, Rachel Altovar
Expanding on the pre-existing resource on nanoHUB: “Turning Fruit Juice into Graphene Quantum Dots” this resource expands on the concepts in the experimental guide to give a comprehensive overview of materials pertaining to concepts and ideas within the...
MODULE 3 - Structures: "Turning Fruit Juice into Graphene Quantum Dots" Supplementary Lesson Plans: Going Atomic
In MODULE 3- Structures in the "Turning Fruit Juice into Graphene Quantum Dots" Supplementary Lesson Plans, crystal structures and systems are investigated. This module relates back to graphene and how its structure relates back to its unique properties in comparison to other forms of...
MODULE 1 - Graphene: "Turning Fruit Juice into Graphene Quantum Dots" Supplementary Lesson Plans: Going Atomic
13 Nov 2020 | | Contributor(s):: Susan P Gentry, Rachel Altovar
The first module in "Turning Fruit Juice into Graphene Quantum Dots" Supplementary Lesson Plans, explores the material, graphene, how it was discovered, and the unique properties that it has. The activity paired with this lesson plan re-creates the famous "sticky-tape"...