Lifeboat Foundation

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The universe is going to end. But of all the possible ends of the universe vacuum decay would have to be the most thorough — because it could totally rewrite the laws of physics. Today I hope to help you understand exactly how terrified you should be.

Continue reading “How Vacuum Decay Would Destroy The Universe” »

Carl knox / ozgrav, ARC centre of excellence for gravitational wave discovery, swinburne university of technology.

The specific event they observed and analyzed is so rare that it has only been seen three other times throughout history.

Scientists have created, synthesized, and analyzed a new class of fluorophores, which are luminous chemical compounds. These are the new bullet systems based on cyanopyrazine. According to research, the inclusion of cyanogroup compounds in fluorophores considerably boosts the efficiency of organic light-emitting diodes (OLED). This indicates they can be utilized to develop new materials to improve the brightness of smartphone, computer, and television screens. The researchers’ findings were recently published in the journal Dyes and Pigments.

The research was led by Egor Verbitskiy, the director of the Postovsky Institute of Organic Synthesis Ural Branch of RAS and a member of the Laboratory of Medical Chemistry and Advanced Organic Materials at the Ural Federal University. He states that physicists were aware that introducing cyanogroups to fluorophores can enhance the OLEDs’ properties and overall efficiency.

An analysis of star clusters suggests that some of them are apparently defying the known laws of physics, leaving experts baffled.

Walking can boost not only your own energy but also, potentially, the energy of your wearable electronic devices. Osaka Metropolitan University scientists made a significant advance toward self-charging wearable devices with their invention of a dynamic magnifier-enhanced piezoelectric vibration energy harvester that can amplify power generated from impulsive vibrations, such as from a human walking, by about 90 times, while remaining as small as currently developed energy harvesters. The results were published in Applied Physics Letters.

These days, people carry multiple electronic devices such as smartphones, and wearable devices are expected to become increasingly widespread in the near future. The resulting demand for more efficient recharging of these devices has increased the attention paid to energy harvesting, a technology that converts energy such as heat and light into electricity that can power small devices. One form of energy harvesting called vibration energy harvesting is deemed highly practical given that it can transform the kinetic energy from vibration into electricity and is not affected by weather or climate.

A research team led by Associate Professor Takeshi Yoshimura from the Graduate School of Engineering at Osaka Metropolitan University has developed a microelectromechanical system (MEMS) piezoelectric vibration energy harvester that is only approximately 2 cm in diameter with a U-shaped metal component called a dynamic magnifier. Compared with conventional harvesters, the new harvester allows for an increase of about 90 times in the power converted from impulsive vibrations, which can be generated by the human walking motion.

“Thermal issues are currently one of the biggest bottlenecks that are plaguing any kind of microelectronics,” says team lead Srabanti Chowdhury, professor of electrical engineering at Stanford University. “We asked ourselves, ‘Can we perform device cooling at the very material level without paying a penalty in electrical performance?’”

Indeed, they could. The engineers grew a heat-wicking diamond layer right on top of individual transistors—their hottest points—as well as on their sides. Heat flowed through the diamond to a heat sink on the back of the device. With this technique, the researchers achieved temperatures 100 degrees Celsius lower without any degradation of the device’s electrical properties. They will report their findings in San Francisco at the IEEE International Electron Device Meeting in December.

They demonstrated their technique on gallium nitride (GaN) high-electron-mobility transistors, or HEMTs. GaN is the go-to alternative to silicon for high-frequency applications, as it can sustain higher electric fields and responds more quickly to electric field changes. GaN also breaks down at a higher temperature than silicon. But not high enough: “If you go by the physics of the material, you see what its potential is, and we’re nowhere close to that today,” says Chowdhury. Keeping GaN HEMTs cool as devices shrink and frequencies grow will allow them to live up to their physics-promised potential.

Workshop supported by the Imperial College Physics of Life Network of Excellence.

https://www.imperial.ac.uk/physics-of-life/

Continue reading “Physics of Emergent Behaviour III: from origin of life to multicellularity, 2nd July 2021 (part 2)” »

An algorithm that already predicts how proteins fold might also shed light on the physical principles that dictate this folding.

Proteins control every cell-level aspect of life, from immunity to brain activity. They are encoded by long sequences of compounds called amino acids that fold into large, complex 3D structures. Computational algorithms can model the physical amino-acid interactions that drive this folding [1]. But determining the resulting protein structures has remained challenging. In a recent breakthrough, a machine-learning model called AlphaFold [2] predicted the 3D structure of proteins from their amino-acid sequences. Now James Roney and Sergey Ovchinnikov of Harvard University have shown that AlphaFold has learned how to predict protein folding in a way that reflects the underlying physical amino-acid interactions [3]. This finding suggests that machine learning could guide the understanding of physical processes too complex to be accurately modeled from first principles.

Predicting the 3D structure of a specific protein is difficult because of the sheer number of ways in which the amino-acid sequence could fold. AlphaFold can start its computational search for the likely structure from a template (a known structure for similar proteins). Alternatively, and more commonly, AlphaFold can use information about the biological evolution of amino-acid sequences in the same protein family (proteins with similar functions that likely have comparable folds). This information is helpful because consistent correlated evolutionary changes in pairs of amino acids can indicate that these amino acids directly interact, even though they may be far in sequence from each other [4, 5]. Such information can be extracted from the multiple sequence alignments (MSAs) of protein families, determined from, for example, evolutionary variations of sequences across different biological species.

Kathryn Tunyasuvunakool grew up surrounded by scientific activities carried out at home by her mother—who went to university a few years after Tunyasuvunakool was born. One day a pendulum hung from a ceiling in her family’s home, Tunyasuvunakool’s mother standing next to it, timing the swings for a science assignment. Another day, fossil samples littered the dining table, her mother scrutinizing their patterns for a report. This early exposure to science imbued Tunyasuvunakool with the idea that science was fun and that having a career in science was an attainable goal. “From early on I was desperate to go to university and be a scientist,” she says.

Tunyasuvunakool fulfilled that ambition, studying math as an undergraduate, and computational biology as a graduate student. During her PhD work she helped create a model that captured various elements of the development of a soil-inhabiting roundworm called Caenorhabditis elegans, a popular organism for both biologists and physicists to study. She also developed a love for programming, which, she says, lent itself naturally to a jump into software engineering. Today Tunyasuvunakool is part of the team behind DeepMind’s AlphaFold—a protein-structure-prediction tool. Physics Magazine spoke to her to find out more about this software, which recently won two of its makers a Breakthrough Prize, and about why she’s excited for the potential discoveries it could enable.

All interviews are edited for brevity and clarity.