Lifeboat Foundation

Scientists specializing in chemical and environmental engineering at the University of California, Riverside have discovered two types of bacteria in the soil capable of breaking down a class of stubborn “forever chemicals,” giving hope for low-cost biological cleanup of industrial pollutants.

Assistant Professor Yujie Men and her team at the Bourns College of Engineering have found that these bacteria are able to eradicate a specific subgroup of per-and poly-fluoroalkyl substances, known as PFAS, particularly those that contain one or more chlorine atoms within their chemical structure. Their findings were published in the scientific journal, Nature Water.

Unhealthful forever chemicals persist in the environment for decades or much longer because of their unusually strong carbon-to-fluorine bonds. Remarkably, the UCR team found that the bacteria cleave the pollutant’s chlorine-carbon bonds, which starts a chain of reactions that destroy the forever chemical structures, rendering them harmless.

The discovery of the Higgs Boson in 2012 represented a major turning point for particle physics marking the completion of what is known as the standard model of particle physics. Yet, the standard model can’t answer every question in physics, thus, since this discovery at the Large Hadron Collider (LHC) physicists have searched for physics beyond the standard model and to determine what shape future physics will take.

A paper in The European Physical Journal H by Robert Harlander and Jean-Philippe Martinez of the Institute for Theoretical Particle Physics and Cosmology, RWTH Aachen University, Germany, and Gregor Schiemann from the Faculty of Humanities and Cultural Studies, Bergische Universität Wuppertal, Germany, considers the idea that particle physics may be on the verge of a new era of discovery and understanding in particle physics. The paper also considers the implications of the many possible scenarios for the future of high-energy physics.

“Over the last century, the concept of the particle has emerged as fundamental in the field of physics,” Martinez said. “It has undergone a significant evolution across time, which has opened up new ways for particle observation, and thus for the discovery of new particles. Currently, observing a particle requires its on-shell production.”

Credit: Hyundai Motor Group.

During a press conference held yesterday in Seoul, South Korea, Hyundai Motor Group revealed plans for a new generation of high-tech cars incorporating nanoscale features, which it hopes to begin mass producing by 2025–2026.

Continue reading “Hyundai to use nanotechnology in cars from 2025–2026” »

Now that’s something mach can use.

MIT researchers have recently developed a portable desalination unit that can remove particles and salts to turn seawater into drinking water.

Continue reading “MIT Scientists Turn Seawater to Drinking Water With the Push of a Button” »

Newton’s first law of motion says that particles move in straight lines unless influenced by a force but a new experiment shows that the quantum version of that assumption fails for quantum particles of light.

By Karmela Padavic-Callaghan

The digital devices that we rely on so heavily in our day-to-day and professional lives today—smartphones, tablets, laptops, fitness trackers, etc.—use traditional computational technology. Traditional computers rely on a series of mathematical equations that use electrical impulses to encode information in a binary system of 1s and 0s. This information is transmitted through quantitative measurements called “bits.”

Unlike traditional computing, quantum computing relies on the principles of quantum theory, which address principles of matter and energy on an atomic and subatomic scale. With quantum computing, equations are no longer limited to 1s and 0s, but instead can transmit information in which particles exist in both states, the 1 and the 0, at the same time.

Quantum computing measures electrons or photons. These subatomic particles are known as quantum bits, or ” qubits.” The more qubits are used in a computational exercise, the more exponentially powerful the scope of the computation can be. Quantum computing has the potential to solve equations in a matter of minutes that would take traditional computers tens of thousands of years to work out.

Teams of physicists worldwide have been trying to detect dark matter, an elusive type of matter that does not emit, absorb, or reflect light. Due to its lack of interactions with electromagnetic forces, this matter is very difficult to observe directly, thus most researchers are instead searching for signals originating from its interactions with other particles in its surroundings.

The PandaX experiment is a research effort dedicated to the search of dark matter using data collected by the Particle and Astrophysical xenon detector, situated at the China Jinping Underground Laboratory (CJPL) in Sichuan, in China. In a recent paper published in Physical Review Letters, the researchers involved in this large-scale experiment published the results of their most recent search for light dark matter (i.e., weakly interacting massive particles with masses below 1 GeV).

“Currently, strong constraints exist for heavy mass dark matter candidates derived from null results in direct detection experiments using xenon detectors,” Yue Meng, Qing Lin and Ning Zhou told Tech Xplore, on behalf of the PandaX collaboration. “However, traditional searches are not sensitive to light mass dark matter (less than GeV/c2) due to the detection energy threshold. Using an ionization-only signal (S2-only) to search for light mass dark matter can reduce the energy threshold from ~1 keV to 0.1 keV. Previous S2-only data analyses in xenon detectors were unable to model the background, which prevented effective and sensitive searches for light mass dark matter.”

A new type of particle called the strange pentaquark has been found using the Large Hadron Collider. The particle could help researchers catalogue the states of exotic matter and figure out how fundamental particles stick together.

By Leah Crane

Originally developed nearly a century ago by physicists studying neutron diffusion, Monte Carlo simulations are mathematical models that use random numbers to simulate different kinds of events. As a simple example of how they work, imagine you have a pair of six-sided dice, and you’d like to determine the probability of the dice landing on any given number.

“You take your dice, and you repeat the same exercise of throwing them on the table, and you look at the outcome,” says Susanna Guatelli, associate professor of physics at the University of Wollongong in Australia.

By repeating the dice-throwing experiment and recording the number of times your dice land on each number, you can build a “probability distribution”—a list giving you the likelihood your dice will land on each possible outcome.