Archive for the ‘information science’ category: Page 4

Nov 28, 2022

Researchers publish 31,618 molecules with potential for energy storage in batteries

Posted by in categories: chemistry, information science, robotics/AI, supercomputing

Scientists from the Dutch Institute for Fundamental Energy Research (DIFFER) have created a database of 31,618 molecules that could potentially be used in future redox-flow batteries. These batteries hold great promise for energy storage. Among other things, the researchers used artificial intelligence and supercomputers to identify the molecules’ properties. Today, they publish their findings in the journal Scientific Data.

In recent years, chemists have designed hundreds of molecules that could potentially be useful in flow batteries for energy storage. It would be wonderful, researchers from DIFFER in Eindhoven (the Netherlands) imagined, if the properties of these molecules were quickly and easily accessible in a database. The problem, however, is that for many molecules the properties are not known. Examples of molecular properties are redox potential and water solubility. Those are important since they are related to the power generation capability and energy density of redox flow batteries.

To find out the still-unknown properties of molecules, the researchers performed four steps. First, they used a and smart algorithms to create thousands of virtual variants of two types of molecules. These molecule families, the quinones and aza aromatics, are good at reversibly accepting and donating electrons. That is important for batteries. The researchers fed the computer with backbone structures of 24 quinones and 28 aza-aromatics plus five different chemically relevant side groups. From that, the computer created 31,618 different molecules.

Nov 28, 2022

Machine-Learning Model Reveals Protein-Folding Physics

Posted by in categories: biological, information science, physics, robotics/AI

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.

Nov 28, 2022

AI invents millions of materials that don’t yet exist

Posted by in categories: information science, robotics/AI

UC San Diego nanoengineering professor Shyue Ping Ong described M3GNet as “an AlphaFold for materials”, referring to the breakthrough AI algorithm built by Google’s DeepMind that can predict protein structures.

“Similar to proteins, we need to know the structure of a material to predict its properties,” said Professor Ong.

“We truly believe that the M3GNet architecture is a transformative tool that can greatly expand our ability to explore new material chemistries and structures.”

Continue reading “AI invents millions of materials that don’t yet exist” »

Nov 28, 2022

The Friedmann equations, and how they are related to protests in China

Posted by in categories: biotech/medical, government, information science

NEW DELHI: Among all the protests that have erupted across China following the strict quarantine measures enforced by the government for Covid-19, one form that has stood out is the display of a physics equation.

In images widely being circulated on social media, students of Beijing’s Tsinghua University can be seen holding sheets on which is written one of the Friedmann equations.

What these equations have to do with the subject of the protests is open to speculation. Many on social media have suggested that it is a play on the words “free man”. Another view is that it symbolises a free and “open” China, because the Friedmann equations describe an “open” (expanding) universe.

Continue reading “The Friedmann equations, and how they are related to protests in China” »

Nov 28, 2022

Completing Einstein’s Theories — A Particle Physics Breakthrough

Posted by in categories: information science, particle physics

Osaka University researchers show the relativistic contraction of an electric field produced by fast-moving charged particles, as predicted by Einstein’s theory, which can help improve radiation and particle physics research.

Over a century ago, one of the most renowned modern physicists, Albert Einstein, proposed the ground-breaking theory of special relativity. Most of everything we know about the universe is based on this theory, however, a portion of it has not been experimentally demonstrated until now. Scientists from Osaka University’s Institute of Laser Engineering utilized ultrafast electro-optic measurements for the first time to visualize the contraction of the electric field surrounding an electron beam traveling at near the speed of light and demonstrate the generation process.

According to Einstein’s theory of special relativity, one must use a “Lorentz transformation” that combines space and time coordinates in order to accurately describe the motion of objects passing an observer at speeds near the speed of light. He was able to explain how these transformations resulted in self-consistent equations for electric and magnetic fields.

Nov 27, 2022

Robotics Breakthrough Builds Anything

Posted by in categories: information science, robotics/AI, transportation

MIT researchers have devised an algorithm using voxels robotics devices to build anything from houses to planes to cars and even other robots by using a grid system that transfers knowledge to determine when to build what, and when to build other robot builders. New Google Deepmind video game artificial intelligence develops agents that can talk, listen, ask questions, navigate, search and retrieve information, control things, and do a range of other intelligent tasks in real-time. New Non-invasive brain computer interface device transmits information through optic nerve to compete with Neuralink BCI.

Tech News Timestamps:
0:00 Robotics Breakthrough Builds Anything — Even Robots.
2:44 New Google Deepmind Video Game AI
5:25 New Neuralink BCI Competitor.

Continue reading “Robotics Breakthrough Builds Anything” »

Nov 27, 2022

Groundbreaking New Technology Allows People To Listen to Music Through Touch

Posted by in categories: information science, media & arts, neuroscience

A ground-breaking prototype developed by experts from the Department of Electronics at the University of Malaga and members of the R&D group “Electronics for Instrumentation and Systems,” will allow those with hearing loss to listen to music through the sense of touch.

It consists of an audio-tactile algorithm that transforms monophonic music into tangible stimuli based on vibration utilizing “tactile illusions.” According to the researchers, “It’s like ‘hacking’ the nervous system to receive a different response to the real stimulus sent.”

Continue reading “Groundbreaking New Technology Allows People To Listen to Music Through Touch” »

Nov 26, 2022

How To Increase Longevity | Prof. Matt Kaeberlein

Posted by in categories: biotech/medical, genetics, information science, life extension

No questions concerning plasma dilution or E5, but a good interview with chapters.

Professor Matt Kaeberlein discusses the Dog Aging Project, longevity, Rapamycin, mTOR, and if we can ‘solve aging’

Continue reading “How To Increase Longevity | Prof. Matt Kaeberlein” »

Nov 26, 2022

A Boiling Cauldron: Cybersecurity Trends, Threats, And Predictions For 2023

Posted by in categories: cybercrime/malcode, information science, internet, quantum physics

By Chuck Brooks

There are many other interesting trends to look out for in 2023. These trends will include the expansion of use of a Software Bill of Materials (SBOM), the integration of more 5G networks to bring down latency of data delivery, more Deep Fakes being used for fraud, low code for citizen coding, more computing at the edge, and the development of initial stages of the implementation of quantum technologies and algorithms.

When all is said and done, 2023 will face a boiling concoction of new and old cyber-threats. It will be an especially challenging year for all those involved trying to protect their data and for geopolitical stability.

Continue reading “A Boiling Cauldron: Cybersecurity Trends, Threats, And Predictions For 2023” »

Nov 26, 2022

Fluxonium qubits bring the creation of a quantum computer closer

Posted by in categories: computing, information science, quantum physics

Russian scientists from University of Science and Technology MISIS and Bauman Moscow State Technical University were one of the first in the world to implement a two-qubit operation using superconducting fluxonium qubits. Fluxoniums have a longer life cycle and a greater precision of operations, so they are used to make longer algorithms. An article on research that brings the creation of a quantum computer closer to reality has been published in npj Quantum Information.

One of the main questions in the development of a universal quantum computer is about . Namely, which quantum objects are the best to make processors for quantum computers: electrons, photons, ions, superconductors, or other “quantum transistors.” Superconducting qubits have become one of the most successful platforms for quantum computing during the past decade. To date, the most commercially successful superconducting qubits are transmons, which are actively investigated and used in the quantum developments of Google, IBM and other world leading laboratories.

The main task of a qubit is to store and process information without errors. Accidental noise and even mere observation can lead to the loss or alteration of data. The stable operation of often requires extremely low ambient temperatures—close to zero Kelvin, which is hundreds of times colder than the temperature of open space.

Page 4 of 22212345678Last