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

We present the open-source AiZynthFinder software that can be readily used in
retrosynthetic planning. The algorithm is based on a Monte Carlo tree search that recursively …

Artificial intelligence (AI) has undergone rapid development in recent years and has been
successfully applied to real-world problems such as drug design. In this chapter, we review …

To substantially expedite scientific discovery, research laboratories need to be further
automated. In this regard, the scientific community envisions an" artificial intelligence …

Progress in data-driven self-driving laboratories for solving materials grand challenges has
accelerated with the advent of machine learning, robotics, and automation, but they are …

Recent developments in automated flow chemistry for pharmaceutical compound synthesis
have garnered significant attention. Automation in synthesis represents a cutting-edge …

Robotic automation is proving itself indispensable in the modern Chemistry laboratory, but
adoption is slowed down by the technical challenges of implementing such systems. This …

Humankind is currently confronted with a critical challenge that determines its very
existence, not only on an individual, racial, or national level but as a whole species: the fight …

Empowered by machine learning (ML) and statistics, researchers are able to leverage a
larger amount and variety of data to facilitate research processes. Moreover, computational …

Biomass is a renewable, almost infinite reservoir of a large diversity of highly functionalized
chemicals. The conversion of biomass toward biobased platform molecules through …