Chemists routinely optimize reactions to maximize the yield of their desired products, but understanding why those reactions work can require laborious experiments that track reactions through time. Researchers at the University of Tokyo have developed a method to extract hidden information on reaction speeds from yield data obtained during reaction optimization using machine learning together with rate equations developed by chemists. Concentration-dependent yield analysis (CYAN) uses machine learning to expand the yield data from reaction optimization experiments, then uses this information to calculate how quickly the different steps of a reaction occur. This gives chemists a tool to understand, improve and design complex high-yield chemical reactions. 

The high O–H bond strength of common alcohols prevents their direct hydrogen atom transfer (HAT) activation. By leveraging the β-silicon effect in α-silyl alcohols, the research group of Professor Xiao Shen at Wuhan University weaken the O–H bond to enable redox-neutral, photoinduced homolysis using thioxanthone. The resulting alkoxy radicals undergo Brook rearrangement to carbon radicals, which are intercepted by nickel catalysis for enantioconvergent cross-couplings with acyl chlorides and aryl bromides. This protocol tolerates substrates inert under classical SET/PCET conditions and establishes direct HAT as a versatile platform.

Researchers at Zhejiang University have developed AtomDiT, a machine learning framework that builds a digital twin of dislocations from a single high-resolution electron micrograph. The twin simultaneously reveals dislocation type and position, local stress, and chemical fields. Demonstrated across metals and alloys, including dual-phase systems and hydrogen-segregated grain boundaries, AtomDiT uncovers how stress and chemistry govern dislocation motion, offering a new route to understanding crystal deformation and damage.

Efficient amide bond synthesis is essential for biology, medicine and materials chemistry. However, conventional approaches often require expensive or harsh reagents. In a new study, researchers demonstrated that dichloromethane, a widely used solvent, can serve as an effective coupling reagent for direct synthesis of amides from carboxylic acids and amines. The approach has broad scope, produces relatively benign byproducts, and is practical for scale-up, offering a potentially simpler strategy for amide synthesis.

ICFO researchers have applied a spin rephasing mechanism to store quantum light in a solid-state quantum memory. The work, published in Physical Review Letters, achieves the longest storage time to date for single photons in this kind of memory, marking a significant enabling step towards the quantum internet.

Researchers have developed a laser-assisted method that rapidly detects tiny amounts of CEACAM-5, a colorectal cancer biomarker, in blood. The technique enhances antibody–antigen interactions and achieves detection even at low concentrations within minutes. The researchers also identified nanoscale CEACAM-5 aggregates that may enhance the method’s sensitivity.

Activated carbon and biochar are widely studied for removing pollutants from water, but new research suggests that the materials doing the cleaning may also create an overlooked transport pathway for contaminants.

Twistronics has become a new alchemy of materials. By choosing atomically thin layers, stacking them and changing their relative angle, researchers can create electronic behavior absent from the original ingredients.

Now, in two back-to-back papers publishing in Science on September 24, an international collaboration provides both the building blocks and a guide to that vast search. The first maps the electronic structures and topology of nearly 9,000 two-dimensional entries, whether topological or not. The second identifies more than 1,600 candidates for twisting, with different electronic starting points that could enable entirely new kinds of quantum simulators.

“Every new family of twisted materials gives us a chance to ask a different question about quantum matter. We want to move beyond the few platforms we know and explore the enormous range of physics that other layers and other twists could make possible,” said B. Andrei Bernevig, a Princeton professor of physics and coauthor of both studies.