New-to-me and wow, what a collection of enthusiasm and expertise. It’s the Wood Database! https://www.wood-database.com/ . This is a collection of information about wood — almost 600 species according to the front page, with tons of articles, a wood identification guide, and more. Just wow.
Dalhousie University: Dal researchers’ chance discovery could help extend battery life by replacing tape that causes self‑discharge. ‘”In commercial battery cells there is tape — like Scotch tape — that holds the electrodes together and there is a chemical decomposition of this tape, which creates a molecule that leads to the self-discharge,” says Michael Metzger, an assistant professor and the Herzberg-Dahn chair and in the Department of Physics and Atmospheric Science.’
UC San Diego: Nanoengineers Develop a Predictive Database for Materials. “Nanoengineers at the University of California San Diego’s Jacobs School of Engineering have developed an AI algorithm that predicts the structure and dynamic properties of any material—whether existing or new—almost instantaneously. Known as M3GNet, the algorithm was used to develop… a database of more than 31 million yet-to-be-synthesized materials with properties predicted by machine learning algorithms.”
MIT News: Is it topological? A new materials database has the answer. “In 2007, researchers predicted the first electronic topological insulators — materials in which electrons that behave in ways that are ‘topologically protected,’ or persistent in the face of certain disruptions. Since then, scientists have searched for more topological materials with the aim of building better, more robust electronic devices. Until recently, only a handful of such materials were identified, and were therefore assumed to be a rarity. Now researchers at MIT and elsewhere have discovered that, in fact, topological materials are everywhere, if you know how to look for them.”
Phys .org: Automatic database creation for materials discovery: Innovation from frustration. “A collaboration between the University of Cambridge and Argonne has developed a technique that generates automatic databases to support specific fields of science using AI and high-performance computing. Searching through reams of scientific literature for bits and bytes of information to support an idea or find the key to solving a specific problem has long been a tedious affair for researchers, even after the dawn of data-driven discovery.”
PRWeb: ASM International Launches Online Access to World’s Largest Archive of Inorganic Materials Data (PRESS RELEASE). “The ASM Materials Platform for Data Science (MPDS) is the world’s largest and most comprehensive repository of inorganic materials data comprised of phase diagrams, crystal structures, and a broad range of properties – physical, mechanical, electrical, optical, magnetic, to name a few. This massive data archive contains more than 1 million experimental and calculated data properties that allow users to dive deep into highly technical materials information that are now easily accessible in one place. In addition, utilizing concise searching technology, MPDS offers effective progressive data discovery of the massive data repository.” Searching appears to be free, while getting detailed search result information appears to be paywalled.
Phys .org: Can I mix those chemicals? There’s an app for that!. “Improperly mixed chemicals cause a shocking number of fires, explosions, and injuries in laboratories, businesses, and homes each year. A new open source computer program called ChemStor developed by engineers at the University of California, Riverside, can prevent these dangerous situations by telling users if it is unsafe to mix certain chemicals.”
NewsMaker: Using Big Databases to find Superconductors of the Future (PRESS RELEASE). “Superconductors are materials that conduct electricity with virtually no resistance. Superconducting materials have improved the field of magnetic resonance imaging (MRI) and have led to the development of particle colliders that can be used for research related to splitting atoms. Currently available superconducting materials can only perform at extremely low temperatures. If researchers can find superconducting materials that work at ambient temperature, electricity could be conducted over large distances without energy loss. Current approaches to searching for these materials are somewhat random, and results strongly depend on researcher’s intuition, experience and luck. Materials scientist Yoshihiko Takano of Japan’s National Institute for Materials Science and colleagues have shown that sifting through an inorganic materials database using specific search parameters can provide a more systematic way to finding superconducting materials.”
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