How can electrons can split into fractions of themselves?
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Updates every hour. Last Updated: 25-Apr-2025 23:08 ET (26-Apr-2025 03:08 GMT/UTC)
MIT physicists have taken a key step toward solving the puzzle of what leads electrons to split into fractions of themselves. Their solution sheds light on the conditions that give rise to exotic electronic states in graphene and other two-dimensional systems.
Genes aren’t the sole driver instructing cells to build multicellular structures, tissues, and organs. In a new paper published in Nature Communications, USC Stem Cell scientist Leonardo Morsut and Caltech computational biologist Matt Thomson characterize the influence of another important developmental driver: cell density, or how loosely or tightly cells are packed into a given space. In both computational models and laboratory experiments, the team of scientists used cell density as an effective tool for controlling how mouse cells pattern themselves into complex structures. The research represents progress towards the big picture goal of engineering synthetic tissues. Synthetic tissues could have endless medical applications, ranging from testing potential drugs or therapies to providing grafts or transplants for patients.
A speed record has been broken using nanoscience, which could lead to a host of new advances, including improved battery charging, biosensing, soft robotics and neuromorphic computing. Scientists have discovered a way to make ions move more than ten times faster in mixed organic ion-electronic conductors. These conductors combine the advantages of the ion signaling used by many biological systems, including the human body, with the electron signaling used by computers. The new development speeds up ion movement in these conductors by using molecules that attract and concentrate ions into a separate nanochannel creating a type of tiny “ion superhighway.”
Phosphorus, a nutrient in soil essential for sustaining most forms of life, is increasingly disappearing from land as it is washed into waterways throughout the United States, according to a new study led by researchers at Penn State.
Can artificial intelligence-powered tools help enrich child development and learning? That question is the crux of a series of research projects led by Zhen Bai, an assistant professor of computer science at the University of Rochester and the Biggar Family Fellow in Data Science at the Goergen Institute for Data Science. From tools to help parents of deaf and hard-of-hearing (DHH) children learn American Sign Language (ASL) to interactive games that demystify machine learning, Bai aims to help children benefit from AI and understand how it is impacting them.
Researchers at New York University have devised a mathematical approach to predict the structures of crystals—a critical step in developing many medicines and electronic devices—in a matter of hours using only a laptop, a process that previously took a supercomputer weeks or months. Their novel framework is published in the journal Nature Communications.