Artificial intelligence accelerates the development of advanced heat-dissipating polymers
Peer-Reviewed Publication
Updates every hour. Last Updated: 20-Dec-2025 13:11 ET (20-Dec-2025 18:11 GMT/UTC)
A machine learning method developed by researchers from Institute of Science Tokyo, the Institute of Statistical Mathematics, and other institutions accurately predicts liquid crystallinity of polymers with 96% accuracy. They screened over 115,000 polyimides and selected six candidates with a high probability of exhibiting liquid crystallinity. Upon successful synthesis and experimental analyses, these liquid crystalline polyimides demonstrated thermal conductivities up to 1.26 W m⁻1 K⁻1, accelerating the discovery of efficient thermal materials for next-generation electronics.
Large language models such as ChatGPT recognise widespread myths about the human brain better than many educators. However, if false assumptions are embedded into a lesson scenario, artificial intelligence (AI) does not reliably correct them. These were the findings of an international study that included psychologists from Martin Luther University Halle-Wittenberg (MLU). The researchers attribute this behaviour to the fundamental nature of AI models: they act as people pleasers. However, this problem can be solved by a simple trick. The study was published in the journal “Trends in Neuroscience and Education”.
Recently, Professor Yanyan Jiang's research team at Shandong University has developed an innovative "carbon precursor pre-coordination" strategy for precisely regulate the single-atom coordination environments in carbon-supported nanozymes. By using carbon dots as carriers and mimicking the active sites of natural CuZn-SOD and Mn-SOD enzymes, they successfully synthesized highly antioxidative CuMn-CDs using only a household microwave oven. The team conducted a systematic investigation into the antioxidant mechanisms of CuMn-CDs, demonstrating their capability to effectively scavenge free radicals present in cigarette smoke and alleviate lung tissue damage in smoking mouse models. Furthermore, the successful syntheis of various other bimetallic single-atom nanozymes confirmed the universal applicability of this strategy.
A team led by Simon Haas has developed a technology to decode how immune cells talk to each other – revealing how our bodies respond to infections, how miscommunication can trigger autoimmune diseases, and why some people don’t respond to immunotherapies. The study was published in “Nature Methods.”
A piece of GSI/FAIR’s cutting-edge research is scheduled to be launched into space next year: the Biophysics department will be involved in one of the next scientific missions on the International Space Station (ISS) with a highly innovative research project. The “HippoBox” project was successfully reviewed by the German Space Agency at DLR and recently selected for participation in the CELLBOX-4 mission on the ISS. The aim of the project is to use brain organoids (“mini-brains”) to investigate neuroplastic changes in a specific area of the brain, the hippocampus – a question that is highly relevant for the medical preparation of future long-term missions in space.
Large metal surfaces coated with precisely formed nanostructures have so far remained in the realm of fantasy. The obstacle standing in the way of their production seemed fundamental, as it resulted from the presence of crystal grains in metals: their boundaries disrupted the growth of the nanostructures. At the Institute of Nuclear Physics of the PAS, using titanium and its oxide by way of example, it has been proven that this obstacle can be overcome.