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

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

We leveraged the power of ChatGPT and Bayesian optimization in the development of a
multi-AI-driven system, backed by seven large language model-based assistants and …

The synthesis of crystalline polyphenylene covalent organic frameworks (COFs) was
accomplished by linking fluorinated tris (4-acetylphenyl) benzene building units using aldol …

Predicting, monitoring, and optimizing the performance and health of a battery system
entails a variety of complex variables as well as unpredictability in given conditions. Data …

The recent rise of computational, data-driven research has significant potential to accelerate
materials discovery. Automated workflows and materials databases are being rapidly …

Metal-organic frameworks (MOFs) are a new class of nanoporous materials that are widely
used in various emerging fields due to their large specific surface area, high porosity and …

Disease X is a hypothetical unknown disease that has the potential to cause an epidemic or
pandemic outbreak in the future. Nanosensors are attractive portable devices that can swiftly …

Reaction optimization is challenging and traditionally delegated to domain experts who
iteratively propose increasingly optimal experiments. Problematically, the reaction …

The global scenario of water shortage and pollution has necessitated the use of advanced
water treatment and desalination technologies. Solar interfacial evaporation has shown …