A recent study published in National Science Review has revealed new insights into the global riverine carbon cycle. This study constructed global maps of riverine dissolved organic carbon (DOC) concentration, along with its radiocarbon (Δ¹⁴C) and stable carbon isotope (δ¹³C) signatures, based on a comprehensive global database and machine learning approaches. It systematically elucidates the sources, spatial distribution, and age characteristics of riverine DOC, quantifies the contributions of different endmembers, and reveals how its age and origin are dynamically regulated by climate conditions, hydrological processes, and soil properties. The results show that soil carbon residence time plays a key role in determining the age of dissolved organic matter transported by global rivers. In particular, warming-induced permafrost thaw is accelerating the release of long-preserved “old carbon” into river systems. Once mobilized, this aged carbon can be transported downstream and participate in aquatic biogeochemical processes, potentially enhancing carbon cycle feedbacks to the climate system.

PPPL researchers have identified a novel mechanism in which expanding plasmas rapidly self-magnetize through the Weibel instability, generating magnetic fields strong enough to alter heat transport. The finding, supported by first-principles simulations, has direct implications for inertial fusion research and for understanding how magnetic fields arise in astrophysical plasmas.

Boundary states in topological states of matter are determined by bulk topological invariants. The conventional bulk–boundary correspondence typically maps a single invariant to a specific boundary mode, which complicates the description of systems hosting multiple coexisting topological phases. Now, writing in the journal National Science Review, researchers proposed a unified characterization of strong, weak, and higher-order topological boundary states in two-dimensional Floquet systems using three complementary one-dimensional winding numbers, offering new insights into the prediction and manipulation of complex topological phases.

The Laureates of the prestigious 2026 Blavatnik Awards for Young Scientists in Israel are announced today by the Blavatnik Family Foundation, the Israel Academy of Sciences and Humanities, and The New York Academy of Sciences.  Each Laureate will receive US$100,000 in prize money. The Blavatnik Awards for Young Scientists in Israel are the largest unrestricted prizes available to scientists across Israel aged 42 or younger. Now in their ninth year in Israel, the Blavatnik Awards recognize research with the potential to transform lives, advance scientific understanding, and address global challenges across disciplines. The three Laureates are: Sergey N. Semenov, PhD, a chemist at the Weizmann Institute of Science, Uri Ben-David, PhD, a cancer biologist at Tel Aviv University, and Paz Beniamini, PhD, an astrophysicist at the Open University of Israel.

Finding and developing new molecules is one of the great research endeavours of modern chemistry. From the development of new drugs to the creation of more sustainable materials, everything depends on finding new combinations of atoms with useful properties. Now, a research team from the Universitat Rovira i Virgili (URV) has developed an artificial intelligence tool capable of generating millions of new molecules which, although still unknown to science, comply with the laws of chemistry and could therefore be realistic possibilities. The research results have been published in the journal Nature Machine Intelligence.

A research team led by Professor Denver Li Danfeng of CityUHK has discovered magnetic-field-induced re-entrant superconductivity in infinite-layer nickelates, where superconductivity re-emerges at high fields. The breakthrough challenges conventional understanding and opens new directions for next-generation superconducting materials.