Lifeboat Foundation

Low-energy nuclear fusion reactions are influenced by the migration of neutrons and protons between fusing nuclei and their isospin compositions. Research conducted using high-performance computational models has shown the importance of isospin dynamics and nuclear shapes, particularly in asymmetric, neutron-rich systems, revealing significant implications for nuclear physics and potential energy applications.

Low-Energy Nuclear Fusion

Low-energy nuclear fusion reactions can potentially provide clean energy. In stars, low-energy fusion reactions during the stages of carbon and oxygen burning are critical to stellar evolution. These reactions also offer valuable insights into the exotic processes occurring in the inner crust of neutron stars as they accumulate matter. However, scientists do not fully understand the underlying dynamics governing these reactions.

Mindfulness training may cause altered states of consciousness, including disembodiment and unity, according to a University of Cambridge study. While often positive, these experiences can sometimes be unsettling. Awareness and open communication about these potential side effects are essential for both teachers and students.

A new study from the University of Cambridge suggests that participants in mindfulness training may undergo altered states of consciousness, experiencing sensations of disembodiment and unity.

The team says that while these experiences can be very positive, that is not always the case. Mindfulness teachers and students need to be aware that they can be a side-effect of training, and students should feel empowered to share their experiences with their teacher or doctor if they have any concerns.

Optical spectrometers are versatile instruments that can produce light and measure its properties over specific portions of the electromagnetic spectrum. These instruments can have various possible applications; for instance, aiding the diagnosis of medical conditions, the analysis of biological systems, and the characterization of materials.

Conventional spectrometer designs often integrate advanced optical components and complex underlying mechanisms. As a result, they are often bulky and expensive, which significantly limits their use outside of specialized facilities, such as hospitals, laboratories and research institutes.

In recent years, some electronics engineers have thus been trying to develop more compact and affordable optical spectrometers that could be easier to deploy on a large-scale. These devices are typically either developed following the same principle underpinning the functioning of conventional larger spectrometers or via the use of arrayed broadband photodetectors, in conjunction with computational algorithms.

Space storms could soon be forecast with greater accuracy than ever before thanks to a big leap forward in our understanding of exactly when a violent solar eruption may hit Earth.

Artificial intelligence (AI) has grown rapidly in the last few years, and with that increase, industries have been able to automate and improve their efficiency in operations.

A feature article published in AIChE Journal identifies the challenges and benefits of using Intelligence Augmentation (IA) in process safety systems.

Contributors to this work are Dr. Faisal Khan, professor and chemical engineering department head at Texas A&M University, Dr. Stratos Pistikopoulos, professor and director of the Energy Institute, Drs. Rajeevan Arunthavanathan, Tanjin Amin, and Zaman Sajid from the Mary Kay O’Connor Safety Center.

The concept of short-range order (SRO)—the arrangement of atoms over small distances—in metallic alloys has been underexplored in materials science and engineering. But the past decade has seen renewed interest in quantifying it, since decoding SRO is a crucial step toward developing tailored high-performing alloys, such as stronger or heat-resistant materials.

Understanding how atoms arrange themselves is no easy task and must be verified using intensive lab experiments or computer simulations based on imperfect models. These hurdles have made it difficult to fully explore SRO in metallic alloys.

But Killian Sheriff and Yifan Cao, graduate students in MIT’s Department of Materials Science and Engineering (DMSE), are using machine learning to quantify, atom by atom, the complex chemical arrangements that make up SRO. Under the supervision of Assistant Professor Rodrigo Freitas, and with the help of Assistant Professor Tess Smidt in the Department of Electrical Engineering and Computer Science, their work was recently published in Proceedings of the National Academy of Sciences.

A team of researchers, affiliated with UNIST has made a significant breakthrough in developing an eco-friendly dry electrode manufacturing process for lithium-ion batteries (LIBs). The new process, which does not require the use of harmful solvents, enhances battery performance while promoting sustainability.

The findings of this research have been published in the July 2024 issue of Chemical Engineering Journal.

Led by Professor Kyeong-Min Jeong in the School of Energy and Chemical Engineering at UNIST, the research team has introduced a novel solvent-free dry electrode process using polytetrafluoroethylene (PTFE) as a binder. This innovative approach addresses the challenges associated with traditional wet-electrode manufacturing methods, which often result in non-uniform distribution of binders and conductive materials, leading to performance degradation.

Pallets are everywhere, but training robots to stack them with goods takes forever. Fixing that could be a tangible win for commercial AI-powered robots.

Tesla has secured an absurdly large contract to provide over 15 GWh of Megapack to California’s Intersect Power.

The Megapack has become the go-to, posterchild product for large-scale energy storage around the globe.

It’s by far Tesla’s fastest-growing product and enabled the company to deploy a record of 9.4 GWh of energy storage last quarter – more than twice the last record.