Lifeboat Foundation

Researchers have used a novel near-infrared light imaging technique to capture the first cross-sectional images of carbon dioxide in the exhaust plume of a commercial jet engine. This new state-of-the-art technology could help accelerate turbine combustion research aimed at developing engines and aviation fuels that are more environmentally friendly.

“This approach, which we call chemical species tomography, provides real-time spatially resolved information for carbon dioxide emissions from a large-scale commercial engine,” said research team leader Michael Lengden from the University of Strathclyde in the U.K. “This information has not been available before at this industrial scale and is a big improvement over the current industry-standard emissions measurement, which involves taking gas from the exhaust to a gas analyzer system in a different location.”

The researchers report the new research in Applied Optics. Chemical species tomography works much like the X-ray-based CT scans used in medicine, except that it uses near-infrared laser light tuned to the absorption wavelength of a target molecule and requires very fast imaging speeds to capture the dynamic processes of combustion.

Microprocessors in smartphones, computers, and data centers process information by manipulating electrons through solid semiconductors, but our brains have a different system. They rely on the manipulation of ions in liquid to process information.

Inspired by the brain, researchers have long been seeking to develop “ionics” in an aqueous solution. While ions in water move slower than electrons in semiconductors, scientists think the diversity of ionic species with different physical and chemical properties could be harnessed for richer and more diverse information processing.

Ionic computing, however, is still in its early days. To date, labs have only developed individual ionic devices such as ionic diodes and transistors, but no one has put many such devices together into a more complex circuit for computing until now.

The universe’s first stars, known as population III, could have had masses up to 250 times greater than that of the Sun. We may now have proof of them.

Astronomers now believe they have discovered ancient chemical remnants of the universe’s first stars, according to new research published in The Astrophysical Journal.

For decades scientists have been diligently looking for direct evidence of these ‘first generation’ stars believed to have formed when the Earth was a modest 100 million years old. The discovery could improve our understanding of how matter in the universe evolved into what it is today, including us. Commons.

Including decaffeinated and instant ones.

A new study conducted by Australian scientists suggests that consuming two to three cups of decaffeinated, ground, and instant coffee can lower the risk of developing cardiovascular disease and dying early.

“In this large, observational study, ground, instant, and decaffeinated coffee were associated with equivalent reductions in the incidence of cardiovascular disease and death from cardiovascular disease or any cause,” says study author Professor Peter Kistler of the Baker Heart and Diabetes Research Institute in a media release.

Continue reading “Drinking 2 to 3 cups of coffee per day could have a surprising effect on longevity” »

The 100 MW Dalian Flow Battery Energy Storage Peak-shaving Power Station, with the largest power and capacity in the world so far, was connected to the grid in Dalian, China, on September 29, and it will be put into operation in mid-October.

This energy storage project is supported technically by Prof. Li Xianfeng’s group from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences. And the system was built and integrated by Rongke Power Co. Ltd.

The Dalian Flow Battery Energy Storage Peak-shaving Power Station was approved by the Chinese National Energy Administration in April 2016. As the first national, large-scale chemical energy storage demonstration project approved, it will eventually produce 200 megawatts (MW)/800 megawatt-hours (MWh) of electricity.

Personalized Bio-Engineered Human Hearts For All — Dr. Doris A. Taylor, Ph.D., CEO, Organamet Bio Inc.

Dr. Doris A. Taylor, Ph.D. is Chief Executive Officer of Organamet Bio Inc. (https://organametbio.com/) an early phase start-up committed to saving lives and reducing the cost of healthcare for those with heart disease. Organamet has a goal is to make personalized bio-engineered human hearts, available to all who need them, within 5 years, increasing availability and access to hearts, decreasing or eliminating need for immunosuppression, reducing total lifetime transplant costs, and improving quality of life.

Continue reading “Dr. Doris A. Taylor, Ph.D. — CEO, Organamet Bio Inc. — Personalized Bio-Engineered Human Hearts” »

Advancements in 3D printing have made it easier for designers and engineers to customize projects, create physical prototypes at different scales, and produce structures that can’t be made with more traditional manufacturing techniques. But the technology still faces limitations—the process is slow and requires specific materials which, for the most part, must be used one at a time.

Researchers at Stanford have developed a method of 3D printing that promises to create prints faster, using multiple types of resin in a single object. Their design, published recently in Science Advances, is 5 to 10 times faster than the quickest high-resolution printing method currently available and could potentially allow researchers to use thicker resins with better mechanical and electrical properties.

Continue reading “New 3D printing method promises faster printing with multiple materials” »

Every summer, weather forecasters blast news about African dust plumes crossing the southern United States. And to most people, it’s just dust, but to researchers at Texas A&M University, it’s much more.

Researchers have developed a new method called isotope-resolved chemical mass balance to identify dust participles using isotopic measurements. Their new research builds off previous studies where they identified and quantified the dust by determining the elemental composition.

The study was recently published in Environmental Science & Technology.

PRESS RELEASE — There has been a lot of buzz about quantum computers and for good reason. The futuristic computers are designed to mimic what happens in nature at microscopic scales, which means they have the power to better understand the quantum realm and speed up the discovery of new materials, including pharmaceuticals, environmentally friendly chemicals, and more. However, experts say viable quantum computers are still a decade away or more. What are researchers to do in the meantime?

A new Caltech-led study in the journal Science describes how machine learning tools, run on classical computers, can be used to make predictions about quantum systems and thus help researchers solve some of the trickiest physics and chemistry problems. While this notion has been shown experimentally before, the new report is the first to mathematically prove that the method works.

“Quantum computers are ideal for many types of physics and materials science problems,” says lead author Hsin-Yuan (Robert) Huang, a graduate student working with John Preskill, the Richard P. Feynman Professor of Theoretical Physics and the Allen V. C. Davis and Lenabelle Davis Leadership Chair of the Institute for Quantum Science and Technology (IQIM). “But we aren’t quite there yet and have been surprised to learn that classical machine learning methods can be used in the meantime. Ultimately, this paper is about showing what humans can learn about the physical world.”