In a paper published in National Science Review, an international team of scientists propose a machine-learned protocol to efficiently and accurately monitor the chemical evolution processes using infrared spectroscopy descriptor. Illustrated with the example of C–C coupling in catalytic reactions, this introduces an intuitive strategy for fingerprinting chemical configurations to using them for assigning dynamic structural information via machine learning approach.

The chemical composition of a material alone sometimes reveals little about its properties. The decisive factor is often the arrangement of the molecules in the atomic lattice structure or on the surface of the material. Materials science utilises this factor to create certain properties by applying individual atoms and molecules to surfaces with the aid of high-performance microscopes. This is still extremely time-consuming and the constructed nanostructures are comparatively simple. Using artificial intelligence, a new research group at TU Graz now wants to take the construction of nanostructures to a new level: “We want to develop a self-learning AI system that positions individual molecules quickly, specifically and in the right orientation, and all this completely autonomously,” says Oliver Hofmann from the Institute of Solid State Physics, who heads the research group. This should make it possible to build highly complex molecular structures, including logic circuits in the nanometre range. The “Molecule arrangement through artificial intelligence” research group is receiving funding totalling 1.19 million euros from the Austrian Science Fund.

The temperature changes hour to hour and day to day, exchange rates behave no differently. Wherever studies of the variability of similar one-dimensional time series are concerned, analyses based on multifractals have managed to gain recognition. Now, these tools have been developed and successfully applied to two-dimensional cases, including the study of abstract paintings by Jackson Pollock.

Recently published research in the journal Weed Science shows promise for controlling herbicide-resistant weeds in soybean fields by using a seed impact mill at harvest. When installed on a combine, this harvest weed-seed control system (HWSC) mechanically damages weed seeds as they move through the mill to render them non-viable.

A robot capable of dynamically adjusting the flexibility of its neck has been developed and implemented to mimic the motion of a cat rubbing its head against a person (bunting). Notably, interacting with this robot could help relieve tension in humans.

Osaka Metropolitan University researchers have elucidated how a single photoreceptor in the pineal gland of zebrafish detects color.