Unlocking new horizons for advanced imaging and photonics
Peer-Reviewed Publication
Updates every hour. Last Updated: 22-Aug-2025 13:11 ET (22-Aug-2025 17:11 GMT/UTC)
Millions of years ago, during periods known as “Snowball Earth,” when much of the planet was covered in ice, some of our ancient cellular ancestors could have waited out the deep freeze in pools of melted ice that dotted the planet’s icy surface, according to a new study.
New research from DTU in Denmark could change the way the food industry manufactures dairy based yoghurt—making it both more cost-effective and more sustainable. Researchers have developed a simple yet powerful method that has the potential to reduce the use of expensive bacterial cultures by up to 80%, while also extending shelf life.
Rechargeable zinc (Zn)-ion batteries (RZIBs) with hydrogel electrolytes (HEs) have gained significant attention in the last decade owing to their high safety, low cost, sufficient material abundance, and superb environmental friendliness, which is extremely important for wearable energy storage applications. Given that HEs play a critical role in building flexible RZIBs, it is urgent to summarize the recent advances in this field and elucidate the design principles of HEs for practical applications. This review systematically presents the development history, recent advances in the material fundamentals, functional designs, challenges, and prospects of the HEs-based RZIBs. Firstly, the fundamentals, species, and flexible mechanisms of HEs are discussed, along with their compatibility with Zn anodes and various cathodes. Then, the functional designs of hydrogel electrolytes in harsh conditions are comprehensively discussed, including high/low/wide-temperature windows, mechanical deformations (e.g., bending, twisting, and straining), and damages (e.g., cutting, burning, and soaking). Finally, the remaining challenges and future perspectives for advancing HEs-based RZIBs are outlined.
Every query typed into a large language model (LLM), such as ChatGPT, requires energy and produces CO2 emissions. Emissions, however, depend on the model, the subject matter, and the user. Researchers have now compared 14 models and found that complex answers cause more emissions than simple answers, and that models that provide more accurate answers produce more emissions. Users can, however, to an extent, control the amount of CO2 emissions caused by AI by adjusting their personal use of the technology, the researchers said.