All models are wrong, but some are useful.

-- George Box

The following are some handy summaries from my research on nanomaterials by means of molecular simulations (e.g., molecular dynamics MD), machine learning (ML), computational mechanics (CM), and other interesting stuff like coding and technology. I hope it will be helpful for beginners in nanomaterials and computer simulations.

• MD contains:
  • polymer molecules generation for molecular dynamics simulations
  • nanosystem build-up, for example, polymer-grafted nanopores or nanoparticles
  • molecular dynamics simulations using Gromacs
  • other related contents
    
    
• CM includes:
  • continuum level by finite element method (FEM) or meshfree method (RKPM)
  • nanoscale level by molecular dynamics (MD) modeling
    
    
• ML is about:
  • machine learning or deep learning and their application in materials science field
  • forward problems like structure-property relationships
  • inverse problems, e.g., polymer design from desired properties
    
    
• Other:
  • programing
  • computer graphics (scientific drawings)
  • technology
  • other fun stuff

• [MD-010] Polymer Trajectory Analysis (structure and hydration) using Gromacs

• [MD-009] Coarse Grained Simulation of Bottlebrush Polymers using a Bead-Spring Model by Lammps

• [MD-008] VMD for MD Trajectory Visualization

• [MD-007] Post-analysis of MD Simulations

• [MD-006] Nanobuilder-3: Generation of Soft-soft Nanosystems for MD Simulations

• [MD-005] Nanobuilder-2: Generation of Hard-soft Nanosystem for MD Simulations

• [MD-004] Nanobuilder-1: Generation of Hard-soft Nanosystem for MD Simulations

• [MD-003] MD Simulations of Polymers in Solution by Gromacs

• [MD-002] Preparation of Topology and Coordinate Files for MD simulations in Gromacs

• [MD-001] Drawing Molecules for Molecular Simulations

• [CM-005] Microstructure Evolution of Semicrystalline Polymers in Deformation

• [CM-004] Microstructure Evolution of Amorphous Polymers in Deformation

• [CM-003] Computational Modeling of Viscoelastic Materials: part 2

• [CM-002] Computational Modeling of Viscoelastic Materials: part 1

• [CM-001] Nanocrystalline Materials: System Generation and Molecular Simulation using Lammps

• [ML-003] Reinforcement Learning: an Introduction

• [ML-002] Molecular Generation Towards Inverse Material Design using RNN

• [ML-001] Recurrent Neural Networks (RNNs) Learn the Constitutive Law of Viscoelasticity

• [Other-006] Scientific Plotting using Xmgrace and gnuplot

• [Other-005] HPC Cluster Login from a Local Computer

• [Other-004] Blender-for-Science-3: Deform Objects and Render Animations

• [Other-003] Blender-for-Science-2: Load Molecules into Blender for Rendering

• [Other-002] Blender-for-Science-1: Build Graphene Sheet, Carbon Nanotube and Fullerene

• [Other-001] Combining Python coding with Bash scripting