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Like paleontologists describing a fossil, astronomers have teased out the backstory of the first directly detected gravitational waves.
Physicists of the Technische Universität Dresden introduce the first implementation of a complementary vertical organic transistor technology, which is able to operate at low voltage, with adjustable inverter properties, and a fall and rise time demonstrated in inverter and ring-oscillator circuits of less than 10 nanoseconds, respectively. With this new technology they are just a stone’s throw away from the commercialization of efficient, flexible and printable electronics of the future. Their groundbreaking findings are published in the renowned journal Nature Electronics.
Poor performance is still impeding the commercialization of flexible and printable electronics. Hence, the development of low-voltage, high-gain, and high-frequency complementary circuits is seen as one of the most important targets of research. High-frequency logic circuits, such as inverter circuits and oscillators with low power consumption and fast response time, are the essential building blocks for large-area, low power-consumption, flexible and printable electronics of the future. The research group “Organic Devices and Systems” (ODS) at the Institute of Applied Physics (IAP) at TU Dresden headed by Dr. Hans Kleemann is working on the development of novel organic materials and devices for high performance, flexible and possibly even biocompatible electronics and optoelectronics. Increasing the performance of organic circuits is one of the key challenges in their research. It was only some month ago, when Ph.D.
Astronomers have seen light from BEHIND a black hole for the first time. I explained the discovery and results to my editor, Levi. Congrats to D. Wilkins and the astronomy team!
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Continue reading “What the NEW black hole discovery tells us!” »
Astronomers have developed the most realistic model to date of planet formation in binary star systems.
The researchers, from the University of Cambridge and the Max Planck Institute for Extraterrestrial Physics, have shown how exoplanets in binary star systems – such as the ‘Tatooine’ planets spotted by NASA
Established in 1958, the National Aeronautics and Space Administration (NASA) is an independent agency of the United States Federal Government that succeeded the National Advisory Committee for Aeronautics (NACA). It is responsible for the civilian space program, as well as aeronautics and aerospace research. It’s vision is “To discover and expand knowledge for the benefit of humanity.”
Scientists have published a new, detailed radio image of the Andromeda galaxy—the Milky Way’s sister galaxy—which will allow them to identify and study the regions of Andromeda where new stars are born.
The study—which is the first to create a radio image of Andromeda at the microwave frequency of 6.6 GHz—was led by University of British Columbia physicist Sofia Fatigoni, with colleagues at Sapienza University of Rome and the Italian National Institute of Astrophysics. It was published online in Astronomy and Astrophysics.
“This image will allow us to study the structure of Andromeda and its content in more detail than has ever been possible,” said Fatigoni, a Ph.D. student in the department of physics and astronomy at UBC. “Understanding the nature of physical processes that take place inside Andromeda allows us to understand what happens in our own galaxy more clearly—as if we were looking at ourselves from the outside.”
A novel metallic compound of hydrogen, carbon, and sulfur exhibited superconductivity at a balmy 59 degrees Fahrenheit—when pressurized between a pair of diamond anvils.
Via Quanta Magazine9 months ago.
Physicists finally achieved the long-sought goal, but there’s a catch: Their compound requires crushing pressures to keep from falling apart.
Continue reading “Scientists Discover the First Room-Temperature Superconductor” »
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A study led by scientists have discovered that vanadium dioxide breaks the laws of physics, transferring electricity but not heat.
A new tool that enables thousands of tiny experiments to run simultaneously on a single polymer chip will let scientists study enzymes faster and more comprehensively than ever before.
For much of human history, animals and plants were perceived to follow a different set of rules than rest of the universe. In the 18th and 19th centuries, this culminated in a belief that living organisms were infused by a non-physical energy or “life force” that allowed them to perform remarkable transformations that couldn’t be explained by conventional chemistry or physics alone.
Scientists now understand that these transformations are powered by enzymes – protein molecules comprised of chains of amino acids that act to speed up, or catalyze, the conversion of one kind of molecule (substrates) into another (products). In so doing, they enable reactions such as digestion and fermentation – and all of the chemical events that happen in every one of our cells – that, left alone, would happen extraordinarily slowly.
Scientists hunting for elusive gravitational waves across the universe may be able to supercharge their discoveries with a new tool: artificial intelligence.
Gravitational waves are ripples in spacetime, created when a massive object is accelerated or disturbed, such as when a black hole and a neutron star collide. Theorized by Albert Einstein, their existence was confirmed in 2015 with the first gravitational wave discovery by researchers using LIGO (the advanced Laser Interferometer Gravitational-Wave Observatory). Now, just six years later, there have been at least 50 gravitational wave events detected.
The prediction of protein structures from amino acid sequence information alone, known as the “protein folding problem,” has been an important open research question for more than 50 years. In the fall of 2020, DeepMind’s neural network model AlphaFold took a huge leap forward in solving this problem, outperforming some 100 other teams in the Critical Assessment of Structure Prediction (CASP) challenge, regarded as the gold-standard accuracy assessment for protein structure prediction. The success of the novel approach is considered a milestone in protein structure prediction.
This week, the DeepMind paper Highly Accurate Protein Structure Prediction with AlphaFold was published in the prestigious scientific journal Nature. The paper introduces AlphaFold2, a completely redesigned and open-sourced model that can predict protein structures with atomic-level accuracy.
Although machine learning researchers have long sought to develop computational methods for predicting 3D protein structures from protein sequences, there had been limited progress along this path, chiefly due to the computational intractability of molecular simulation, the context-dependence of protein stability, and the difficulty of producing sufficiently accurate models for protein physics.
