Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: chemistry – Page 6

The willingness of the 4f orbitals of lanthanide metals to participate in chemical reactions is as rare as their presence in Earth’s crust. A recent study, however, witnessed the 4f orbital in a cerium-based compound actively participate in bond formation, triggering a unique chemical reaction.

The researchers observed that a cerium-containing cyclic complex formed a 4f-covalent interaction, leading to a ring-opening isomerization from cyclopropene to allene. The findings are published in Nature Chemistry.

Lanthanides are heavy, rare-earth , occupying positions 57 through 71 in the —from lanthanum to lutetium—and are widely used in modern technologies ranging from electronics to clean energy. In nature, these elements are usually found together in their ore form and separating them using current methods is extremely challenging and energy-intensive. Understanding how these elements bond or interact with other atoms at an electronic level could help us to distinguish between lanthanides and design effective separation strategies.

Read more | >

In every scientific discovery in the movies, a scientist observes something unexpected, scratches the side of his or her forehead and says “hmmmmm.” In just such a moment in real life, scientists from Canada observed unexpected flashes of curved green light from a red light-emitting polymer above its surface. The flashes were reminiscent of the colored arcs that auroras take above Earth’s poles, providing a clue as to their provenance.

Their resulting investigation of the new phenomenon could find applications towards understanding the failures of polymer materials and more. Their work has been published in Physical Review Letters.

Jun Gao, a professor and chair of Engineering Physics at the Engineering Physics and Astronomy Department at Queen’s University in Ontario, Canada, and graduate student Dongze Wang were investigating the performance of semiconductors called polymer light-emitting electrochemical cells, or PLECs.

Read more | >

As artificial intelligence (AI) continues to advance, researchers at POSTECH (Pohang University of Science and Technology) have identified a breakthrough that could make AI technologies faster and more efficient.

Professor Seyoung Kim and Dr. Hyunjeong Kwak from the Departments of Materials Science & Engineering and Semiconductor Engineering at POSTECH, in collaboration with Dr. Oki Gunawan from the IBM T.J. Watson Research Center, have become the first to uncover the hidden operating mechanisms of Electrochemical Random-Access Memory (ECRAM), a promising next-generation technology for AI. Their study is published in the journal Nature Communications.

As AI technologies advance, data processing demands have exponentially increased. Current computing systems, however, separate data storage (memory) from data processing (processors), resulting in significant time and due to data transfers between these units. To address this issue, researchers developed the concept of in-memory computing.

Read more | >

A U of A engineering researcher is using sunlight and semiconductor catalysts to produce hydrogen by splitting apart water molecules into their constituent elements.

“The process to form the semiconductor, called thermal condensation polymerization, uses cheap and Earth-abundant materials, and could eventually lead to a more efficient, economical path to clean energy than existing ,” says project lead Karthik Shankar of the Department of Electrical and Computer Engineering, an expert in the field of photocatalysis.

In a collaboration between the U of A and the Technical University of Munich, results of the research were published in the Journal of the American Chemical Society.

Read more | >

It’s obvious when a dog has been poorly trained. It doesn’t respond properly to commands. It pushes boundaries and behaves unpredictably. The same is true with a poorly trained artificial intelligence (AI) model. Only with AI, it’s not always easy to identify what went wrong with the training.

Research scientists globally are working with a variety of AI models that have been trained on experimental and theoretical data. The goal: to predict a material’s properties before taking the time and expense to create and test it. They are using AI to design better medicines and industrial chemicals in a fraction of the time it takes for experimental trial and error.

But how can they trust the answers that AI models provide? It’s not just an academic question. Millions of investment dollars can ride on whether AI model predictions are reliable.

Read more | >

The resuspension of seafloor sediments—triggered by human activities such as bottom trawling as well as natural processes like storms and tides—can significantly increase the release of carbon dioxide (CO2) into the atmosphere. When these sediments are exposed to oxygen-rich seawater, large-scale oxidation of pyrite occurs.

This reaction plays a much greater role in CO2 emissions than previously assumed, exceeding the contribution from the of . A new study, published in Communications Earth & Environment, provides the first quantitative evidence of this effect in the western Baltic Sea.

“Fine-grained, muddy sediments are important reservoirs of organic carbon and pyrite,” says lead author Habeeb Thanveer Kalapurakkal, a Ph.D. student in the Benthic Biogeochemistry working group at GEOMAR.

Read more | >

A study conducted by CNRS researchers describes a new method of recycling silicone waste (caulk, sealants, gels, adhesives, cosmetics, etc.). It has the potential to significantly reduce the sector’s environmental impacts.

This is the first universal recycling process that brings any type of used silicone material back to an earlier state in its where each molecule has only one silicon atom. And there is no need for the currently used to design new silicones. Moreover, since it is chemical and not mechanical recycling, the reuse of the material can be carried out infinitely.

The associated study is published in Science.

Read more | >

Quantum computers promise to speed calculations dramatically in some key areas such as computational chemistry and high-speed networking. But they’re so different from today’s computers that scientists need to figure out the best ways to feed them information to take full advantage. The data must be packed in new ways, customized for quantum treatment.

Read more | >

MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected. The new framework sheds light on how scientists could fuse strategies from different methods to improve existing AI models or come up with new ones.

For instance, the researchers used their framework to combine elements of two different algorithms to create a new image-classification that performed 8% better than current state-of-the-art approaches.

The periodic table stems from one key idea: All these algorithms learn a specific kind of relationship between data points. While each algorithm may accomplish that in a slightly different way, the core mathematics behind each approach is the same.

Read more | >