From the start of a synthetic chemist's training, experiments are conducted based on recipes
from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist …

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

Conspectus We must accelerate the pace at which we make technological advancements to
address climate change and disease risks worldwide. This swifter pace of discovery requires …

Many properties of nanoparticles are governed by their shape, size, polydispersity and
surface chemistry. To apply nanoparticles in chemical sensing, medical diagnostics …

We report the development of an open-source experimental design via Bayesian
optimization platform for multi-objective reaction optimization. Using high-throughput …

The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …

This review paper delves into synergistic integration of artificial intelligence (AI) and
machine learning (ML) with high-throughput experimentation (HTE) in the field of …

Autonomous process optimization involves the human intervention-free exploration of a
range process parameters to improve responses such as product yield and selectivity …

Artificial intelligence-guided closed-loop experimentation has emerged as a promising
method for optimization of objective functions,, but the substantial potential of this …

Many applications of inorganic nanoparticles (NPs), including photocatalysis, photovoltaics,
chemical and biochemical sensing, and theranostics, are governed by NP optical properties …