Self-driving laboratories (SDLs) promise an accelerated application of the scientific method.
Through the automation of experimental workflows, along with autonomous experimental …

We envision" AI scientists" as systems capable of skeptical learning and reasoning that
empower biomedical research through collaborative agents that integrate AI models and …

This paper proposes an approach to automate chemistry experiments using robots by
translating natural language instructions into robot-executable plans, using large language …

Efficient synthesis recipes are needed to streamline the manufacturing of complex materials
and to accelerate the realization of theoretically predicted materials. Often, the solid-state …

This paper provides a simulated laboratory for making use of Reinforcement Learning (RL)
for chemical discovery. Since RL is fairly data intensive, training agentson-the-fly'by taking …

The material acceleration platform, empowered by robotics and artificial intelligence, is a
transformative approach for expediting material discovery processes across diverse …

This paper provides a simulated laboratory for making use of reinforcement learning (RL) for
material design, synthesis, and discovery. Since RL is fairly data intensive, training agents …

The development of novel polymer-based nanocomposites necessitates the experimental
preparation and characterization of numerous compositions to identify optimal formulations …

Automated air-displacement pipettes have become a standard equipment for the transfer of
liquids in laboratory settings. However, these tools fail to perform accurate and precise …

Aliquoting of biological samples refers to the process of dividing a larger biological sample
into smaller, representative portions known as aliquots. This procedure is commonly …