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The development of efficient hydrogen storage technologies is crucial for the transition to sustainable energy solutions. Hydrogen, known for its versatility and clean energy potential, can be produced from renewable sources. Solid-state hydrogen storage materials, such as magnesium hydride (MgH2), are considered promising due to their high storage capacity and availability. However, despite decades of
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Quantum physics and quantum chemistry have long relied on stochastic methods like Monte Carlo simulations to study strongly interacting systems. However, these methods face challenges when sign oscillations occur, leading to inaccurate results. A recent breakthrough by an international team of researchers from Germany, Turkey, the U.S., China, South Korea, and France introduces the new
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Building design methods play a crucial role in ensuring the safety and integrity of structures. The traditional approach focuses on improving connectivity between components to redistribute loads in case of component failure. However, this method can lead to progressive collapse after large initial failures, as evidenced by incidents like the Champlain Towers collapse. In response,
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Prions are abnormal, infectious agents that trigger the misfolding of normal cellular proteins, leading to a group of neurodegenerative diseases known as prion diseases. These conditions, which include Creutzfeldt-Jakob disease in humans and mad cow disease in animals, are fatal and currently lack effective treatments. The conversion of a normal prion protein (PrPC) into a
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A groundbreaking study conducted by researchers at the University of Illinois Urbana-Champaign has redefined the way diffusion is understood and calculated in multicomponent alloys. By introducing the concept of “kinosons” as individual contributions to diffusion, the team has harnessed the power of machine learning to transform the traditional approach to modeling. Published in the prestigious
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