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Enantiomers, or molecule pairs that are mirror images of each other, make up more than half of FDA-approved drugs in use today, including those used in treatments for cancer, neurologic diseases and arthritis. Separating enantiomers is critical for drug manufacturing because the effect of each molecule in the pair can be very different—for example, one enantiomer might cure a headache while its mirror-image could cause a headache.

Faster and more accurate separations would help with the overall drug discovery and screening process, but by their very nature, enantiomers—which have identical compositions and only differ by not being superimposable (think left hand and right hand)—are notoriously difficult to separate.

An effort by a group of researchers at the University of Illinois Urbana-Champaign to find an efficient, sustainable way to perform these critical enantiomer separations is the focus of a new study published in the Journal of the American Chemical Society.

A trio of scientists from the Georgia Institute of Technology, Université de Lyon, and Arizona State University, respectively, has found that a likely reason flat pancake-like volcanoes form on Venus’ surface is the planet has an elastic lithosphere and volcanoes that emit dense lava.

In their paper published in the Journal of Geophysical Research: Planets, M. E. Borrelli, C. Michaut, and J. G. O’Rourke describe how they used data collected by NASA’s Magellan mission in the 1990s, to simulate how one such flat-topped could have come about and what they learned by doing so.

Planetary scientists have been wondering for many years how the oddly shaped volcanic domes came to exist on the surface of Venus. With their flat shapes and steep sides, they are unlike any volcanoes seen on Earth—they look much more like pancakes than cones. To learn more, the research trio took a unique approach. They attempted to simulate how just one of them might have come about.

As the digital world demands greater data storage and faster access times, magnetic memory technologies have emerged as a promising frontier. However, conventional magnetic memory devices have an inherent limitation: they use electric currents to generate the magnetic fields necessary to reverse their stored magnetization, leading to energy losses in the form of heat.

This inefficiency has pushed researchers to explore approaches that could further reduce in magnetic memories while maintaining or even enhancing their performance.

Multiferroic materials, which exhibit both ferroelectric and ferromagnetic properties, have long been considered potential game changers for next-generation memory devices.

Narcissism has become the armchair diagnosis of the decade. Social media is awash with people flinging the label around. Everyone’s ex seems to be a narcissist, some of our parents are under suspicion, and that office villain? They definitely tick the box, too.

The accuracy of these rampant diagnoses warrants scepticism. But the reality is narcissists do exist. At its extreme, narcissism is a rare mental health diagnosis, known as narcissistic personality disorder. But narcissism also describes a cluster of personality traits, which we all display to varying degrees.

For those of us who have been in close quarters with someone high in narcissistic traits, we rarely walk away unscathed. And we may be left with lingering questions. For example, what made them this way?

Is artificial intelligence (AI) capable of suggesting appropriate behaviour in emotionally charged situations? A team from the University of Geneva (UNIGE) and the University of Bern (UniBE) put six generative AIs — including ChatGPT — to the test using emotional intelligence (EI) assessments typically designed for humans. The outcome: these AIs outperformed average human performance and were even able to generate new tests in record time. These findings open up new possibilities for AI in education, coaching, and conflict management. The study is published in Communications Psychology.