A research team from Peking University and Peking University Shenzhen Graduate School have used artificial intelligence (AI) to quickly and accurately predict the properties of materials that could improve solar energy devices. Their algorithms were able to predictic important properties such as: conduction band minimum (CBM), valence band maximum (VBM), and bandgap of halide perovskites.

This work provides valuable insights into the rational design of halide perovskites with tailored properties. These findings can impulse the discovery of better-performing solar materials, paving the way for more affordable and efficient solar panels.

Deep in the heart of Tanzania’s Udzungwa Mountains, a trio of Rice University researchers, including ecophysiologist Andrea Rummel, graduate student Annie Finneran and junior Caroline Pollan, embarked on an ambitious summer field study to understand how human impacts are reshaping forest ecosystems. Armed with bat detectors, camera traps, soil sampling kits and a passion for ecological discovery, they worked alongside Tanzanian scientists to track the interplay between biodiversity, conservation and nutrient cycling in one of Africa’s most biologically rich yet vulnerable landscap

A mechanical artwork designed in 1775 to depict the eruption of Italy’s Mount Vesuvius has been brought to life for the first time — 250 years after it was conceived — thanks to modern technology and the ingenuity of two University of Melbourne engineering students.

This research paves the way for point-of-care cortisol testing and diagnoses.

A team of UC Merced researchers has shown that tiny artificial cells can accurately keep time, mimicking the daily rhythms found in living organisms. Their findings shed light on how biological clocks stay on schedule despite the inherent molecular noise inside cells.

This study examined whether machine learning could predict the risk and contributing factors of no-shows and late cancellations in primary care practices.