One of the current challenges in the chemical industry is to find methods that facilitate the optimisation of catalysts capable of enabling the development of new chemical processes. Catalyst optimisation is usually based on trial-and-error testing, in which the properties of the catalyst are improved through a slow and routine process aimed at identifying the best combinations of ligand and metal, which are its basic components. Once the catalyst has been optimised, its properties are fixed and adapted to the specific requirements of a particular chemical process.

A highly interesting alternative to this method is to design a catalyst that contains a ligand whose properties can be modulated through the application of an external stimulus. These properties, known as “switchable”, are much easier to modulate and therefore to adapt to the specific needs of each reaction. Over the past four years, the Organometallic Chemistry and Homogeneous Catalysis Group (QOMCAT) at the Universitat Jaume I has designed a series of multisensitive catalysts capable of adapting their properties through the application of electrochemical, light-based, chemical and supramolecular stimuli.

Formaldehyde, a highly toxic chemical, must be converted into value-added products. A recent paper by researchers from Chonnam National University presents an engineered enzyme system that converts the highly toxic formaldehyde into L-glyceraldehyde, a valuable chiral compound, with high selectivity and conversion efficiency in a sustainable, one-pot, water-based process. This technology can help better manage environmental pollutants, supporting greener chemical manufacturing.

researchers discovered that by using a ruthenium-catalysedsemi-hydrogenation process, PET waste could be depolymerised into a valuable chemical, ethyl-4-hydroxymethyl benzoate (EHMB). 

Remarkably, EHMB serves as a key intermediate for synthesising several important compounds, including the blockbuster anticancer drug Imatinib, Tranexamic acid, the base for medication that helps the blood to clot, and the insecticide Fenpyroximate. 

For the first time worldwide, we have achieved remote, real-time control of fusion plasma using a digital twin running on a supercomputer located about 1,000 km away (round-trip network path ~2,000 km).

In magnetic confinement fusion power, sustaining and precisely controlling plasma at temperatures exceeding 100 million ℃ over long durations is essential. Yet “predicting-while-controlling” has been challenging due to model accuracy limits, computation speed, and unresolved physics. Our team has developed a system that applies data assimilation, continuously updating the predictive model with real-time measurements to improve accuracy and using accelerated parallel prediction to determine optimal unrehearsed control actions.

A research team from Kyoto University, the National Institute for Fusion Science (NIFS), the National Institutes for Quantum Science and Technology (QST), and the Institute of Statistical Mathematics (ISM), has connected the Large Helical Device (LHD) in Toki, Gifu, Japan to the new “Plasma Simulator” supercomputer in Rokkasho, Aomori, jointly procured by NIFS and QST, via the high-quality, high-bandwidth academic network SINET6. By exclusively using more than 20,000 Central Processing Unit (CPU) cores and minimizing communication latency, the team has realized real-time predictive control of LHD from a remote supercomputer. This approach — linking a large experimental facility and a large computing system over a ~2,000 km network loop — can serve as a foundation for real-time control beyond fusion.