A new study published in the journal Nature Geoscience [1] by researchers at the IBS Center for Climate Physics (ICCP) at Pusan National University in South Korea shows that the Antarctic ice sheet became more sensitive to climate forcing following a major shift in Earth’s ice age cycles about one million years ago, providing new insight into how ice sheets respond to long-term climate change.

This study introduced a simplified soil vapor transport scheme into the Community Land Model version 5 (CLM5). Under extremely dry surface conditions, upward liquid water movement becomes very weak or nearly ceases. As a result, near-surface soil layers may dry too slowly in models, leading to unrealistic wet biases.

As a growing share of total power output comes from wind turbines, sudden spikes in power generation from unpredictable changes in atmospheric conditions is becoming an increasingly urgent and potentially dangerous threat to grid stability. Using a 20 km-wide wind farm as a giant physics experiment, researchers have now developed a framework to predict the risk of power fluctuations for individual turbines, farms, and the whole grid, based on existing geospatial data. Their model will help establish the risk profile of existing and future developments, providing a powerful tool to ensure reliable and sustainable power generation for plant operators, grid engineers, and energy planners.

Discovering new catalysts is one of the central challenges in developing clean-energy technologies such as green hydrogen production. Yet catalyst discovery has traditionally remained confined within individual material families, limiting researchers’ ability to transfer knowledge across chemically distinct systems.

A research team led by Director HYEON Taeghwan of the Center for Nanoparticle Research within the Institute for Basic Science (IBS) has developed an artificial intelligence (AI) framework that discovers catalysts in a fundamentally new way — by combining knowledge across different catalyst families.

Researchers from The University of Osaka created stable cobalt-based honeycomb structures inside a layered material and observed ferromagnetic-like ordering at low temperatures. By introducing a small amount of cobalt into NaSbO₃, the team demonstrated a new platform to study Kitaev materials using abundant 3d transition metals, potentially supporting future cost-effective quantum technologies.

A new review synthesizes a decade of research into one of the most promising materials for water purification, biochar–hydrogel composites, and concludes that their effectiveness is governed by a single, critical factor: the chemistry of their surfaces. The work, led by corresponding author Dr. Dong Hee Kang at Morgan State University, provides a unified framework for understanding how these materials function and a clear roadmap for designing more robust and efficient filters to tackle global water contamination.

Biochar, a carbon-rich material made from pyrolyzed biomass, and hydrogels, water-absorbing polymer networks, are powerful on their own. When combined, they create a synergistic adsorbent with enhanced capabilities. This review analyzes the extensive body of literature to demonstrate that the true power of these composites comes from their surface functional groups—specific chemical moieties like carboxyl, hydroxyl, and amine groups that act as molecular-scale "hooks" to capture contaminants. The hydrogel matrix not only adds its own functional groups but also makes the biochar’s reactive sites more accessible, explaining why the composite consistently outperforms its individual components.

Tiny sound waves inside the Sun unmask evidence of systematic changes in the solar activity cycle over the last 40 years – with implications for predicting space weather.

Scientists at the University of California, Riverside are making breakthroughs in understanding how quantum wave functions move across ultra-thin materials — research that could eventually improve solar energy technologies and help lay the groundwork for new forms of quantum computing.

A team at Polytechnique Montréal has opened the door to a new generation of photonic chips that could cut the electricity use of data centres and generative AI systems. The work is published today in Science Advances, part of the Science family of journals.