Lifeboat Foundation

Australian scientists say they’ve made a “eureka moment” breakthrough in gas separation and storage that could radically reduce energy use in the petrochemical industry, while making hydrogen much easier and safer to store and transport in a powder.

Nanotechnology researchers, based at Deakin University’s Institute for Frontier Materials, claim to have found a super-efficient way to mechanochemically trap and hold gases in powders, with potentially enormous and wide-ranging industrial implications.

Mechanochemistry is a relatively recently coined term, referring to chemical reactions that are triggered by mechanical forces as opposed to heat, light, or electric potential differences. In this case, the mechanical force is supplied by ball milling – a low-energy grinding process in which a cylinder containing steel balls is rotated such that the balls roll up the side, then drop back down again, crushing and rolling over the material inside.

A recent study from the Singapore Centre for Environmental Life Sciences Engineering (SCELSE) at Nanyang Technological University (NTU) and published in Wa | Chemistry And Physics.

This study is intriguing since one of the results of climate change is increasing water temperatures, so removing phosphorus from such waters will prove invaluable in the future, with this study appropriately being referred to as a “future-proof” method.

Continue reading “New ‘future-proof’ method could remove phosphorus from wastewater using bacteria” »

Scientists have tested a natural chemical that could heal wounds twice as fast.

So precise.

If chemists built cars, they’d fill a factory with car parts, set it on fire, and sift from the ashes pieces that now looked vaguely car-like.

When you’re dealing with car-parts the size of atoms, this is a perfectly reasonable process. Yet chemists yearn for ways to reduce the waste and make reactions far more precise.

Continue reading “Chemists Just Rearranged Atomic Bonds in a Single Molecule For The First Time” »

Early detection and identification of pathogenic bacteria in food and water samples are essential to public health. Bacterial infections cause millions of deaths worldwide and bring a heavy economic burden, costing more than 4 billion dollars annually in the United States alone. Among pathogenic bacteria, Escherichia coli (E. coli) and other coliform bacteria are among the most common ones, and they indicate fecal contamination in food and water samples. The most conventional and frequently used method for detecting these bacteria involves culturing of the samples, which usually takes 24 hours for the final read-out and needs expert visual examination. Although some methods based on, for example, the amplification of nucleic acids, can reduce the detection time to a few hours, they cannot differentiate live and dead bacteria and present low sensitivity at low concentrations of bacteria. That is why the U.S. Environmental Protection Agency (EPA) approves no nucleic acid-based bacteria sensing method for screening water samples.

In an article recently published in ACS Photonics, a journal of the American Chemical Society (ACS), a team of scientists, led by Professor Aydogan Ozcan from the Electrical and Computer Engineering Department at the University of California, Los Angeles (UCLA), and co-workers have developed an AI-powered smart bacterial colony detection system using a thin-film transistor (TFT) array, which is a widely used technology in mobile phones and other displays.

The ultra-large imaging area of the TFT array (27 mm × 26 mm) manufactured by researchers at Japan Display Inc. enabled the system to rapidly capture the growth patterns of bacterial colonies without the need for scanning, which significantly simplified both the hardware and software design. This system achieved ~12-hour time savings compared to gold-standard culture-based methods approved by EPA. By analyzing the microscopic images captured by the TFT array as a function of time, the AI-based system could rapidly and automatically detect colony growth with a deep neural network. Following the detection of each colony, a second neural network is used to classify the bacteria species.

The question of how the chemical composition of a protein—the amino acid sequence—determines its 3D structure has been one of the biggest challenges in biophysics for more than half a century. This knowledge about the so-called “folding” of proteins is in great demand, as it contributes significantly to the understanding of various diseases and their treatment, among other things. For these reasons, Google’s DeepMind research team has developed AlphaFold, an artificial intelligence that predicts 3D structures.

A team consisting of researchers from Johannes Gutenberg University Mainz (JGU) and the University of California, Los Angeles, has now taken a closer look at these structures and examined them with respect to knots. We know knots primarily from shoelaces and cables, but they also occur on the nanoscale in our cells. Knotted proteins can not only be used to assess the quality of structure predictions but also raise important questions about folding mechanisms and the evolution of proteins.

A team of researchers from IBM Research Europe, Universidade de Santiago de Compostela and the University of Regensburg has changed the bonds between the atoms in a single molecule for the first time. In their paper published in the journal Science, the group describes their method and possible uses for it. Igor Alabugin and Chaowei Hu, have published a Perspective piece in the same journal issue outlining the work done by the team.

The current method for creating complex molecules or molecular devices, as Alagugin and Chaowei note, is generally quite challenging—they liken it to dumping a box of Legos in a washing machine and hoping that some useful connections are made. In this new effort, the research team has made such work considerably easier by using a scanning tunneling microscope (STM) to break the bonds in a molecule and then to customize the molecule by creating new bonds—a chemistry first.

Continue reading “Chemists change the bonds between atoms in a single molecule for the first time” »

High-performance, micro-sized electrochemical energy storage devices are essential for future miniaturized electronic devices, such as smart medical implants, wireless sensors, and the Internet of Things. Microbatteries (MBs) typically show higher energy density and more stable voltage output than micro-supercapacitors.

However, current MBs involve tedious construction procedures and unsatisfactory electrochemical performance. In addition, no methods exist to construct or manipulate a liquid microelectrode.

A joint research team led by Prof. Qu Liangti from Tsinghua University, Prof. Zhang Zhipan from the Beijing Institute of Technology, and Prof. Liu Feng from the Institute of Mechanics of the Chinese Academy of Sciences (IMCAS) recently proposed a dual-plating strategy to rapidly construct new zinc–bromine microbatteries (Zn–Br₂ MBs) with ultrahigh areal energy density and polarity-switchable functionality.

For his work on liquid metal batteries that could enable the long-term storage of renewable energy, MIT Professor Donald Sadoway has won the 2022 European Inventor Award, in the category for Non-European Patent Office Countries.

Sadoway is a longtime supporter and friend of MIT’s Materials Research Laboratory and is the John F. Elliott Professor of Materials Chemistry in MIT’s Department of Materials Science and Engineering.

“By enabling the large-scale storage of renewable energy, Donald Sadoway’s invention is a huge step towards the deployment of carbon-free electricity generation,” says António Campinos, President of the European Patent Office. “He has spent his career studying electrochemistry and has transformed this expertise into an invention that represents a huge step forward in the transition to green energy.”