Drug discovery has always been a numbers game with brutal odds.

North Carolina State University Now Runs the Largest Academic Self-Driving Lab Ecosystem in the US.

Solid sampling at the sub-milligram and milligram scale remains a major bottleneck for high-throughput chemistry or material sciences, as existing approaches rely on manual handling or slow deterministic microsampling that do not readily scale.

Here we present STORMS, an automated STOchastic Robotic MicroSampling system that enables fast, reliable and parallel sampling of solid materials at sub-milligram and milligram masses. 

Polymer–solvent systems exhibit complex solvation behaviours encompassing a diverse range of phenomena, including swelling, gelation, and dispersion. Accurate interpretation is often hindered by subjectivity, particularly in manual rapid screening assessments. While computer vision models hold significant promise to replace the reliance on human evaluation for inference, their adoption is limited by the lack of domain-specific datasets tailored, in our case, to polymer–solvent systems.

A first example of diglycolamide flow synthesis was developed, showcasing algorithm-accelerated reaction optimization and its potential to accelerate ligand discovery and enable autonomous, AIcontrolled manufacturing of critical materials. The increasing demand for manufacturing rare-earth elements (REEs) as critical materials has intensified research on sustainable synthesis of advanced extractants such as diglycolamides (DGAs).

Screening powder properties such as flowability, compressibility, and particle geometry is crucial for controlling ceramic processing, particularly in automated workflows that demand high reproducibility. Sacrificial templating for porous ceramics is well suited to automation because it is prone to variability arising from manual handling.

At the University of Liverpool, AI-powered robots are transforming lab work.

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.

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