sparks-baird / self-driving-lab-demo
Software and instructions for setting up and running a self-driving lab (autonomous experimentation) demo using dimmable RGB LEDs, an 8-channel spectrophotometer, a microcontroller, and an adaptive design algorithm, as well as extensions to liquid- and solid-based color matching demos.
☆76Updated last week
Alternatives and similar repositories for self-driving-lab-demo
Users that are interested in self-driving-lab-demo are comparing it to the libraries listed below
Sorting:
- Honegumi (骨組み) is an interactive "skeleton code" generator for API tutorials focusing on optimization packages.☆52Updated last week
- A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.☆41Updated 9 months ago
- Encode/decode a crystal structure to/from a grayscale PNG image for direct use with image-based machine learning models such as Palette.☆37Updated last year
- AlabOS: Managing the workflows in the Autonomous lab☆43Updated last month
- ☆40Updated last year
- Agent-based sequential learning software for materials discovery☆62Updated last year
- Microcourses hosted by the Acceleration Consortium for self-driving lab topics.☆30Updated last month
- ☆124Updated last month
- The Wren sits on its Roost in the Aviary.☆55Updated last month
- 3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)☆41Updated 2 years ago
- Application of Large Language Models (LLM) for computational materials science - visit jan-janssen.com/LangSim☆63Updated 6 months ago
- Python package to interact with high-dimensional representations of the chemical elements☆43Updated last week
- Codebase to drive the Perovskite Automated Spin Coat Assembly Line (PASCAL) in the Fenning research group.☆15Updated last month
- Active Learning for Machine Learning Potentials☆55Updated last year
- The materials for the Spring Mathematics in Materials course at the UTK MSE☆49Updated last year
- Deep learning framework for atomistic image data☆34Updated 4 months ago
- hierachical automation of the natural sciences☆20Updated 3 months ago
- train and use graph-based ML models of potential energy surfaces☆91Updated 3 weeks ago
- Strategies for the Construction of Neural-Network Based Machine-Learning Potentials (MLPs)☆28Updated 4 years ago
- ☆60Updated 5 months ago
- ☆33Updated 7 months ago
- ☆21Updated 4 years ago
- Generative materials benchmarking metrics, inspired by guacamol and CDVAE.☆38Updated 11 months ago
- Code for automated fitting of machine learned interatomic potentials.☆76Updated last week
- An overview of literature that discusses the use of machine learning for atomistic simulations☆45Updated 2 years ago
- FTCP code☆34Updated last year
- A public repository collecting links to state of the art QA and evaluation sets for various ML and LLM applications☆92Updated 10 months ago
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆81Updated 3 weeks ago
- A python library for calculating materials properties from the PES☆87Updated last week
- Software for evaluating pareto-optimal synthesis pathways☆25Updated 11 months ago