Shan-Zhu / ML-Carbon_SupercapacitorLinks
Using machine learning to predict the performance of supercapacitors.
☆11Updated 5 years ago
Alternatives and similar repositories for ML-Carbon_Supercapacitor
Users that are interested in ML-Carbon_Supercapacitor are comparing it to the libraries listed below
Sorting:
- code package with elemental property dictionary that trains a model based on training dataset and gives prediction on new perovskite comp…☆27Updated 7 years ago
- Python interface to the SISSO (Sure Independence Screening and Sparsifying Operator) method.☆57Updated last year
- Modules for cross validation, evaluation and plot of SISSO☆16Updated 5 years ago
- Simulates molecular adsorption and diffusion on nanoporous materials.☆18Updated 9 months ago
- LAMMPS plugins for thermal conductivity and density of states calculation☆48Updated 6 years ago
- A MATLAB program for simulating film growth using Kinetic Monte Carlo.☆15Updated 4 years ago
- A script to build reference datasets for training neural network potentials from given LAMMPS trajectories.☆40Updated last week
- Quantum-Wise VNL Application for Perovskite Building and Machine Learning☆10Updated 5 years ago
- RMD_digging is aimed to provide pre-processing and post-processing tools for the reactive molecular dynamics (ReaxFF) simulations based o…☆46Updated 3 months ago
- [MGE Advances 2025] Offical implement of BgoFace☆17Updated last month
- AIM (Adsorption Integrated Modules) is a collection of MATLAB based GUI modules for adsorption isotherm based fixed bed process modelling☆12Updated 2 weeks ago
- Tools for auto-generating the battery-materials database.☆47Updated 3 years ago
- Comparative Analysis of Machine Learning Approaches on the Prediction of the Electronic Properties of Perovskite: A Case Study of the ABX…☆23Updated 3 years ago
- Expanded dataset of mechanical properties and observed phases of multi-principal element alloys☆36Updated 3 years ago
- A collection of notebooks in support of the publication "A Database of Experimentally Measured Lithium Solid Electrolyte Conductivities E…☆22Updated last year
- Machine Learning for Catalyst Design and Discovery☆17Updated 6 years ago
- We developed a novel method, MOF-CGCNN, to efficiently and accurately predict the methane the volumetric uptakes at 65 bar for MOFs. Two …☆19Updated 3 years ago
- This is the code for the paper 'Machine learning-enabled high-entropy alloy discovery'☆75Updated last year
- A high performace ReaxFF/AIMD trajectory analysis tool based on graph theory.☆62Updated this week
- materialsvirtuallab / Data-driven-First-Principles-Methods-for-the-Study-and-Design-of-Alkali-Superionic-ConductorsJupyter notebooks and data for our Chemistry of Materials article "Data-driven First Principles Methods for the Study and Design of Alkal…☆12Updated 4 years ago
- Predict the band gap energy for inorganic materials☆19Updated last year
- Code to help you get started using machine learning in materials science☆17Updated 6 years ago
- Microkinetic models for electrochemical CO stripping and hydrogen oxidation☆14Updated 4 years ago
- an automatic reaction network generator for reactive molecular dynamics simulation☆91Updated last week
- Python scripts for dealing with molecular dynamics script for LAMMPS☆17Updated 2 years ago
- LAMMPS scripts to simulate uniaxial tensile test of a graphene Sample☆34Updated 5 years ago
- MatDesign: a programming-free AI platform to predict and design materials☆72Updated 2 months ago
- ☆25Updated last month
- Kinetic Monte Carlo of Systems (KMCOS): lattice based kinetic Monte Carlo with a python front-end and Fortran back-end.☆23Updated 2 months ago
- PoreBlazer (v4.0) source code, examples, and geometric properties of porous materials calculated for the subset of 12,000 structures from…☆54Updated last year