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.

Educational ARES is a version of ARES OS 2.0 modified for classroom use with a Prusa MK4S 3D printer and a USB camera. Due to the generalized camera implementation, this setup is currently limited to a Windows only implementation.

Main repository for the Modular Autonomous Discovery for Science (MADSci) Framework

Codebase for controlling and managing the Acceleration Consortium (AC) Training Lab.

ARES OS 2.0 is a software suite to enable laboratory automation and fully closed-loop autonomous research.

Python library for adaptive experiment design with state-of-art ML tools

Materials Acceleration Platform Center at BAM

Accelerate 2024 Workshop on Bayesian Optimization Recipes With BayBE

A curated collection of resources for Physical AI for Science — where robotics, lab automation, and AI agents converge to accelerate scientific discovery.

WedgedSDL is a self driving lab (SDL) platform designed to discover a formula using primary colored red, yellow, and blue, food-coloring dyes for a composite dye for any given dye color. It consists of micropython, java based server, and python server API code.

Benchmark for statistically valid AI scientist systems, using audit-closed protocols, transparency logs, and sequential inference to prevent false discoveries in autonomous research agents.