Lifeboat Foundation

However, Hassabis’ true breakthrough came just a month ago, when he and two colleagues from DeepMind won the Nobel Prize in Chemistry for their development of AlphaFold, an AI tool capable of predicting the structure of the 200 million known proteins. This achievement would have been nearly impossible without AI, and solidifies Hassabis’ belief that AI is set to become one of the main drivers of scientific progress in the coming years.

Hassabis — the son of a Greek-Cypriot father and a Singaporean mother — reflects on the early days of DeepMind, which he founded in 2010, when “nobody was working on AI.” Over time, machine learning techniques such as deep learning and reinforcement learning began to take shape, providing AI with a significant boost. In 2017, Google scientists introduced a new algorithmic architecture that enabled the development of AGI. “It took several years to figure out how to utilize that type of algorithm and then integrate it in hybrid systems like AlphaFold, which includes other components,” he explains.

“During our first years, we were working in a theoretical space. We focused on games and video games, which were never an end in themselves. It gave us a controlled environment in which to operate and ask questions. But my passion has always been to use AI to accelerate scientific understanding. We managed to scale up to solving a real-world problem, such as protein folding,” recalls the engineer and neuroscientist.

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Research on moscovium and nihonium shows they are more reactive than flerovium and subject to notable relativistic effects, broadening our understanding of superheavy elements and their potential uses.

An international team led by scientists from GSI/FAIR in Darmstadt, Johannes Gutenberg University Mainz, and the Helmholtz Institute Mainz has successfully determined the chemical properties of the artificially produced superheavy elements moscovium and nihonium (elements 115 and 113).

Continue reading “The Periodic Table Just Got Wilder: Scientists Unveil the Secrets of the Heaviest Element Ever — Moscovium” »

In an era where AI and data are driving the scientific revolution, quantum computing technology is emerging as another game-changer in the development of new drugs and new materials.

Dr. Hyang-Tag Lim’s research team at the Center for Quantum Technology at the Korea Institute of Science and Technology (KIST) has implemented a quantum computing algorithm that can estimate interatomic bond distances and ground state energies with chemical accuracy using fewer resources than conventional methods, and has succeeded in performing accurate calculations without the need for additional quantum error mitigation techniques.

The work is published in the journal Science Advances.

A large number of 2D materials like graphene can have nanopores—small holes formed by missing atoms through which foreign substances can pass. The properties of these nanopores dictate many of the materials’ properties, enabling the latter to sense gases, filter out seawater, and even help in DNA sequencing.

“The problem is that these 2D materials have a wide distribution of nanopores, both in terms of shape and size,” says Ananth Govind Rajan, Assistant Professor at the Department of Chemical Engineering, Indian Institute of Science (IISc). “You don’t know what is going to form in the material, so it is very difficult to understand what the property of the resulting membrane will be.”

Machine learning models can be a powerful tool to analyze the structure of nanopores in order to uncover tantalizing new properties. But these models struggle to describe what a nanopore looks like.

Using various telescopes, an international team of astronomers has conducted a comprehensive study of a double-lined spectroscopic binary known as HD 34736. The study, published November 6 in the Monthly Notices of the Royal Astronomical Society, delivers important insights into the properties of this system.

So far, the majority of binaries have been detected by Doppler shifts in their spectral lines, hence these systems are called spectroscopic binaries. Observations show that in some spectroscopic binaries, spectral lines from both stars are visible, and these lines are alternately double and single. These systems are known as double-lined spectroscopic binaries (SB2).

HD 34,736 is an SB2 system consisting of two chemically peculiar late B-type stars, located some 1,215 light years away. Previous observations of HD 34,736 have found that the system has an extraordinarily strong magnetic field exceeding 4.5 kG. The effective temperatures of the primary and secondary star were found to be 13,700 and 11,500 K, respectively.

More than 4 million people in the U.S. have glaucoma, a group of eye diseases that can damage the optic nerve and lead to vision loss. It’s the second-leading cause of blindness worldwide and there’s currently no cure, but there’s a way to help prevent vision loss through early detection and treatment.

The two main treatment options, however, are inefficient and have downsides. Medicated eyedrops are noninvasive but can’t be absorbed for full effectiveness. Repeated injections into the eye can lead to infections or inflammation, not to mention patient discomfort.

Researchers at Binghamton University are exploring several new glaucoma treatments that would be less invasive. In a study recently published in the Journal of Materials Chemistry B, Assistant Professor Qianbin Wang and Ph.D. student Dorcas Matuwana from the Thomas J. Watson College of Engineering and Applied Science’s Department of Biomedical Engineering shared their findings for drug-carrying liposomes that could be activated in the eye using near-infrared light.

DGIST and UNIST researchers have discovered a new quantum state, the exciton-Floquet synthesis state, enabling real-time quantum information control in two-dimensional semiconductors.

A research team led by Professor Jaedong Lee from the Department of Chemical Physics at DGIST (President Kunwoo Lee) has unveiled a groundbreaking quantum state and an innovative mechanism for extracting and manipulating quantum information through exciton and Floquet states.

Collaborating with Professor Noejung Park from UNIST’s Department of Physics (President Chongrae Park), the team has, for the first time, demonstrated the formation and synthesis process of exciton and Floquet states, which arise from light-matter interactions in two-dimensional semiconductors. This study captures quantum information in real-time as it unfolds through entanglement, offering valuable insights into the exciton formation process in these materials, thereby advancing quantum information technology.

A team of researchers from Jilin University, NYU Abu Dhabi’s Smart Materials Lab, and the Center for Smart Engineering Materials, led by Professor of Chemistry Pance Naumov, has developed a new crystalline material that can harvest water from fog without any energy input.

The design of the novel type of smart crystals, which the researchers named Janus crystals, is inspired by desert plants and animals, which can survive in arid conditions. Desert beetles and lizards, for example, have evolved to develop surface structures that have both hydrophilic and hydrophobic areas and effectively capture moisture from the air. Water is attracted to the hydrophilic areas and droplets are accumulated and transported through the hydrophobic areas.

The findings are presented in the paper titled “Efficient Aerial Water Harvesting with Self-Sensing Dynamic Janus Crystals,” recently published in the Journal of the American Chemical Society.

Astronomers at the University of Toronto (U of T) have discovered the first pairs of white dwarf and main sequence stars—” dead” remnants and “living” stars—in young star clusters. Described in a new study published in The Astrophysical Journal, this breakthrough offers new insights into an extreme phase of stellar evolution, and one of the biggest mysteries in astrophysics.

Scientists can now begin to bridge the gap between the earliest and final stages of binary star systems—two stars that orbit a shared center of gravity—to further our understanding of how stars form, how galaxies evolve, and how most elements on the periodic table were created. This discovery could also help explain cosmic events like supernova explosions and gravitational waves, since binaries containing one or more of these compact dead stars are thought to be the origin of such phenomena.

Most stars exist in binary systems. In fact, nearly half of all stars similar to our sun have at least one companion star. These paired stars usually differ in size, with one star often being more massive than the other. Though one might be tempted to assume that these stars evolve at the same rate, more massive stars tend to live shorter lives and go through the stages of stellar evolution much faster than their lower mass companions.