Common beans, which contain diverse bioactive molecules, have not been systematically studied for their variation in how they affect the human gut microbiome.

The design and synthesis of functional polymers, aimed at targeted properties through specific structures, have long been challenged by their complex and often nonlinear structure− property relationships. Key processes, including knowledge accumulation for predictive design and experimental refinement and validation, are traditionally labor-insensitive and timeconsuming, making it difficult to balance accuracy and efficiency.

Self-driving labs (SDLs) combine robotic automation with artificial intelligence (AI) to allow autonomous, high-throughput experimentation. However, robot manipulation in most SDL workflows operates in an open-loop manner, lacking real-time error detection and error correction. This can reduce reliability and overall efficiency.

The challenges posed by global climate change and disease risks have intensified the demand for efficient and practical materials and molecules. Traditional trial-and-error approaches are becoming increasingly inefficient and resource-intensive. The rapid advancement of artificial intelligence (AI) has opened new avenues to accelerate research and shorten development cycles.

Iridium (III) complexes are used for a wide variety of applications owing to their thermal stability, tuneable electronic properties and strong photoluminescent character. Iridium (III) complexes can be structurally altered to change the wavelengths of light they absorb and emit making them desirable for organic light emitting diodes (OLEDs) and photocatalysis.

Diverse collections of well-defined glycans are needed to investigate the molecular mechanisms by which these biomolecules mediate biological and disease processes. Several automation approaches have been introduced to accelerate the enzymatic synthesis of complex glycans. These methodologies have, however, provided only relatively simple oligosaccharides due to limitations of glycosyl transferase selectivity.

The design and discovery of porous materials have become a central theme in materials science, driven by their applications in gas storage, separation, carbon capture, and catalysis. Rapid advances in synthetic chemistry, particularly in metal–organic frameworks, porous organic cages, and conjugated microporous polymers, have enabled the generation of increasingly large and diverse material libraries.

Pharmaceuticals increasing complexity requires longer synthesis with unique processes for each step, increasing the number of experiments to develop robust sustainable processes. The time to develop these processes is getting shorter, and automation can support the growing need to efficiently perform more experiments.

Advances in high-throughput instrumentation and laboratory automation are revolutionizing materials synthesis by enabling the rapid generation of large libraries of novel materials.

The development of automated experimental facilities and the digitization of experimental data have introduced numerous opportunities to radically advance chemical laboratories.