Triboelectric nanogenerator (TENG) technology can harvest low-frequency and low-power energy. However, there is limited research on harvesting energy from secondary effluents using TENG. Now, researchers have developed a droplet-based electricity generator system capable of harvesting energy from treated municipal wastewater. Using TENG technology, the system converts low-frequency energy from secondary effluents into usable electricity while simultaneously supporting wastewater treatment processes. The findings highlight a promising low-carbon pathway for sustainable wastewater resource recovery and energy utilization.

Genetically engineered cyanobacteria developed at Institute of Science Tokyo (Science Tokyo), Japan, produce sulfated polysaccharides using sunlight and carbon dioxide. By transferring an entire gene cluster responsible for the production of a sulfated polysaccharide, the researchers enabled a non-producing cyanobacterial strain to produce such a polysaccharide. The research demonstrates a sustainable route for manufacturing biomaterials using photosynthesis, expanding the possibilities for synthetic biology and green chemistry applications.

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.