Physics-informed machine learning connects atomic structure with ion transport and electrolyte stability, accelerating better sodium- and lithium-ion batteries.
Electrochemistry stands at the intersection of materials science, chemistry, and physics, driving transformative advances in sustainable energy conversion, ...
A cobalt aluminum nanolaminate has shattered the usual tradeoff between strength and flexibility, emerging up to 10 times ...
A sea worm’s metal-like jaws may represent an entirely new class of natural material. In the classic guessing game “20 ...
An ancient sea worm may hold the secret to a whole new category of natural materials. Its jaws combine proteins and metal ...
A study reveals that gold possesses an unexpected "self-defense" system at the atomic level that prevents oxygen from ...
Fusion advances, AI demand, and improved plasma containment bring commercial clean energy significantly closer to practical ...
Leading scientists from around the world who study the structure and reactions of rare atomic nuclei not found in nature will ...
Tech Xplore on MSN
With machine learning, researchers embrace the atomic-scale complexity of batteries
For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National ...
Specialized technical teams from the Syrian Atomic Energy Commission (SAEC) completed the safe containment and transfer of a ...
Researchers have demonstrated a technique allowing them to fabricate oxide twistronic materials at much larger sizes, while ...
A layered crystal that combines high electrical conductivity with low thermal conductivity, offering an efficient solid-state ...
一些您可能无法访问的结果已被隐去。
显示无法访问的结果