Researchers Gaopei Pan and Fakher F. Assaad from the University of Goettingen have delved into the complex world of heavy fermion systems, using advanced computational techniques to better understand these unique materials. Their work, published in t
Unraveling Heavy Fermion Mysteries for Next-Gen Energy Materials Read More »
In a significant stride towards democratizing advanced imaging techniques, a team of researchers from University College London, led by Dr. Silvia Cipiccia, has successfully demonstrated the potential of laboratory X-ray sources for high-resolution,
Lab X-rays unlock nano-imaging potential for energy research Read More »
In the realm of energy research, a team from the Swiss Federal Institute of Technology in Lausanne (EPFL) has been delving into the potential impacts of Local Electricity Communities (CELs) in Switzerland. These communities, set to become operational
Swiss Study Reveals Local Electricity Communities’ Potential and Pitfalls Read More »
Researchers from the University of Colorado Boulder, led by Ana Maria Rey, have introduced a novel approach to simulate and control topological superconductors using photon-mediated interactions. This work, published in the journal Nature Physics, co
Researchers from the University of Illinois at Urbana-Champaign and the University of Science and Technology of China have developed a new system aimed at improving the quality of information gathered through vehicular mobile crowdsensing. This techn
QUIDS: Revolutionizing Smart Cities with Vehicular Data Crowdsourcing Read More »
In the realm of cancer treatment, a team of researchers from the Technical University of Darmstadt, Germany, led by Jeannette Jansen, is revisiting the potential of very heavy ions for precision radiotherapy. The team, which includes Olga Sokol, Yola
Reviving Heavy Ions: Neon’s Potential in Cancer Radiotherapy” (66 characters) Read More »
In the realm of energy journalism, a recent study from researchers at Facebook Reality Labs, including Vincent T. Lee, Tanfer Alan, Sung Kim, Ecenur Ustun, Amr Suleiman, Ajit Krisshna, Tim Balbekov, Armin Alaghi, and Richard Newcombe, has shed light
Wearable AI’s Power Puzzle: A Holistic Approach to Energy Efficiency” (69 characters) Read More »
In the rapidly evolving landscape of energy storage, a team of researchers from the University of Toronto, including Jiayang Yang, Chunhui Zhao, Martin Guay, and Zhixing Cao, has developed a novel approach to enhance the management of lithium-ion bat
Toronto Team’s AI Framework Revolutionizes Battery Management Read More »
Researchers from the University of Cambridge, led by Ruifeng Tan, have developed a new machine learning model called the Pretrained Battery Transformer (PBT) to predict the cycle life of lithium-ion batteries (LIBs). This research, published in Natur
Revolutionary AI Model Predicts Lithium-Ion Battery Life with Unprecedented Accuracy Read More »
Researchers Philipp Plamper, Hanna Köpcke, and Anika Groß from the University of Potsdam have conducted a comprehensive survey on spatio-temporal knowledge graphs (STKGs), a topic of growing interest in various domains, including energy and environme
Unlocking Energy Insights: Spatio-Temporal Knowledge Graphs Pave the Way Read More »
