News & Comment

A clean and non-toxic, one-step keratin crosslinking approach has been described, paving the way for greener and more sustainable hair styling.

A living catalyst transfer polymerization enables access to low dispersity polyphenylenes and ultimately to length-selective synthesis of graphene nanoribbons.

A review of Dan Egan’s book The Devil’s Element, where he explores the element that both makes plants grow and toxifies our water — phosphorus.

Voronoi domains combined with modelled vibrational sum frequency generation spectroscopy can be used to investigate surfaces, interfaces, and hydrations shells at reduced computational costs.

A series of tricopper mono-, di- and tri-hydride complexes have been prepared and studied as a models of heterogeneous copper catalysts for carbon dioxide reductions.

Near-infrared spectroscopy combined with machine learning can predict the publication years of paper books from 1851 to 2000 with an unprecedented accuracy of 2 years.

When two phenyl rings are perfectly stacked in a cyclophane structure that is bridged by three helicene linkers, they lose some of their aromatic stability, even though the overall structure — with 78 π-electrons — is aromatic.

Nitrogenases are enzymes capable of reducing atmospheric nitrogen to ammonia. By better understanding their structure and the reaction mechanism, researchers can work towards artificial mimics that may replace the need for the energy-demanding Haber–Bosch process.

A highly stable glass has been prepared by the physical vapour deposition of two materials in equal amounts.

Large language models such as GPT-4 have been approaching human-level ability across many expert domains. GPT-4 can accomplish complex tasks in chemistry purely from English instructions, which may transform the future of chemistry.

Getting the next generation to participate in chemistry will require dismantling normative approaches to education and mentoring. Inclusive pedagogy that incorporates social issues and innovative teaching with special attention to historically excluded groups are keys to unlocking the full potential of future scientists.

A review of Paul McKendrick’s book Scrubbing the Sky: Inside the Race to Cool the Planet, which looks at the chemistry, engineering and economics behind direct air capture.

A bacterial tridecasaccharide known to prevent inflammatory bowel disease has been synthesized.

Hydrogenation reactions of alkynes to cis-alkenes is typically carried out with precious metal catalysts. A new zinc complex represents a rare example of a non-transition metal able to carry out this stereoselective transformation.

Hydroxylamine is a molecule of prebiotic interest, but its estimated abundance in space is orders of magnitude greater than what we have observed. To answer this discrepancy, quantum chemical calculations are used to investigate its formation and destruction pathways.

Creating a more inclusive classroom environment starts with educating instructors about the needs of their students. Once those needs are understood, work to address them may not only benefit the small group of students for whom the intervention was intended, but the wider class too.

A thermoelectric material is presented which adopts a tungsten bronze structure with high-entropy properties but without rare-earth metals. Through entropy engineering, the Seebeck coefficient is optimized and the thermal conductivity is minimized, thereby creating the most efficient thermoelectric material of its kind.

Abundant metal copper with a catenane ligand system can effectively induce the oxygen reduction reaction, a promising alternative to typical precious-metal electrocatalysts.

A gold nanoparticle colloidal system is used to explore the effect of nanoparticle–substrate interactions on heterogeneous nucleation, providing a simple model for a complex and poorly understood physical process.

Owing to the diminishing returns of deep learning and the focus on model accuracy, machine learning for chemistry might become an endeavour exclusive to well-funded institutions and industry. Extending the focus to model efficiency and interpretability will make machine learning for chemistry more inclusive and drive methodological progress.