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                    <title>Phys.org - latest science and technology news stories</title>
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            <description>Phys.org internet news portal provides the latest news on science including: Physics, Nanotechnology, Life Sciences, Space Science, Earth Science, Environment, Health and Medicine.</description>

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                    <title>&#039;Don&#039;t scare the cat!&#039; Engineers find smarter way to measure quantum systems</title>
                    <description>UNSW Sydney engineers have riffed on the famous Schrödinger&#039;s cat analogy to demonstrate a more efficient way to eliminate errors in quantum computing.</description>
                    <link>https://phys.org/news/2026-06-dont-cat-smarter-quantum.html</link>
                    <category>Quantum Physics</category>                    <pubDate>Wed, 03 Jun 2026 14:40:07 EDT</pubDate>
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                    <title>Teaching thermodynamic laws to AI unlocks a polymer modeling challenge</title>
                    <description>For more than half a century, materials scientists have struggled with how to simulate the complexity of polymer materials. An individual chain can comprise tens of thousands of atoms, a melt or composite contains billions, and the properties engineers actually care about, such as how an adhesive grips a surface, how a self-assembling block copolymer locks into a nanostructure, or how a biopolymer film stretches without tearing, emerge only over length and time scales that forcible atomistic simulation cannot reach.</description>
                    <link>https://phys.org/news/2026-05-thermodynamic-laws-ai-polymer.html</link>
                    <category>Polymers</category>                    <pubDate>Tue, 26 May 2026 19:20:07 EDT</pubDate>
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                    <title>A roadmap for safer, explainable protein-design AI</title>
                    <description>Protein language models are artificial intelligence tools which help engineer proteins with useful properties, including completely new structures never seen before in nature.</description>
                    <link>https://phys.org/news/2026-05-roadmap-safer-protein-ai.html</link>
                    <category>Biotechnology</category>                    <pubDate>Mon, 11 May 2026 13:20:06 EDT</pubDate>
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                    <title>Super transformer aims to bring order to biology&#039;s data under one AI model</title>
                    <description>Modern biology is awash in data. Scientists can sequence DNA, track gene activity cell-by-cell, map proteins in space, and image tissues at microscopic resolution. However, it is a struggle to put all that information together to form a cohesive view.</description>
                    <link>https://phys.org/news/2026-05-super-aims-biology-ai.html</link>
                    <category>Biotechnology</category>                    <pubDate>Tue, 05 May 2026 13:40:06 EDT</pubDate>
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                    <title>DNA-reading AI reconstructs ancestry in minutes, matching top statistical methods</title>
                    <description>Researchers at the University of Oregon have developed an artificial intelligence tool that can read genetic code the way large language models like ChatGPT read text. Scanning the genome for biological mutation patterns, the computer model traces pairs of genes back in time to their last common ancestor.</description>
                    <link>https://phys.org/news/2026-05-dna-ai-reconstructs-ancestry-minutes.html</link>
                    <category>Biotechnology</category>                    <pubDate>Mon, 04 May 2026 16:20:06 EDT</pubDate>
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                    <title>AI tackles one of math&#039;s most brutal problems: Inverse PDEs</title>
                    <description>Penn Engineers have developed a new way to use AI to solve inverse partial differential equations (PDEs), a particularly challenging class of mathematical problems with broad implications for understanding the natural world.</description>
                    <link>https://phys.org/news/2026-05-ai-tackles-math-brutal-problems.html</link>
                    <category>Mathematics</category>                    <pubDate>Fri, 01 May 2026 11:20:05 EDT</pubDate>
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                    <title>Developing countries are writing AI laws they cannot enforce</title>
                    <description>Imagine that a government builds a five-star airport without any roads leading to it. The terminal is immaculate, the runway is regulation length—but there is simply no way to get there.</description>
                    <link>https://phys.org/news/2026-04-countries-ai-laws.html</link>
                    <category>Political science</category>                    <pubDate>Wed, 29 Apr 2026 14:40:05 EDT</pubDate>
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                    <title>AI speeds chemists&#039; search for better disinfectants</title>
                    <description>Chemists and computer scientists tapped AI to find new disinfectants to combat the growing threat of dangerous &quot;superbugs.&quot; Their computational-experimental framework for developing quaternary ammonium compounds, or QACs, to kill bacteria yielded 11 new QACs that show activity against antimicrobial-resistant bacteria.</description>
                    <link>https://phys.org/news/2026-04-ai-chemists-disinfectants.html</link>
                    <category>Biochemistry</category>                    <pubDate>Wed, 29 Apr 2026 11:40:02 EDT</pubDate>
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                    <title>AI slashes the time needed to design better heat-harvesting devices</title>
                    <description>From wearable technology to industrial heat recovery, thermoelectric generators which convert waste heat into electricity have an enormous range of potential applications. So far, however, designing high-performing versions of these devices has remained a painstaking task.</description>
                    <link>https://phys.org/news/2026-04-ai-slashes-harvesting-devices.html</link>
                    <category>General Physics</category>                    <pubDate>Tue, 28 Apr 2026 08:10:02 EDT</pubDate>
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                    <title>AI for molecular simulations may not need built-in physics to deliver strong results</title>
                    <description>Simulating how atoms and molecules move over time is a central challenge in computational chemistry and materials science. Classical machine learning approaches to molecular dynamics (MD) encode fundamental physical principles directly into their model architectures, most notably energy conservation and equivariance, the requirement that predicted forces remain consistent regardless of how a molecule is oriented in space. These so-called inductive biases have long been considered essential for reliable, physically meaningful MD models. But are they truly indispensable?</description>
                    <link>https://phys.org/news/2026-04-ai-molecular-simulations-built-physics.html</link>
                    <category>Analytical Chemistry</category>                    <pubDate>Wed, 22 Apr 2026 17:50:03 EDT</pubDate>
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                    <title>Low-cost robotic chemistry system can be built and deployed in any lab</title>
                    <description>In a paper just out in Nature Synthesis, researchers led by Prof. Timothy Noël of the University of Amsterdam&#039;s Van &#039;t Hoff Institute for Molecular Sciences presented a breakthrough in autonomous laboratory systems for synthesis optimization. With an estimated cost of a mere $5,000, a versatile, modular design and the option for &quot;human in the loop&quot; analytics, RoboChem Flex caters to all synthesis laboratories, large or small. The paper provides all the information to build their own system.</description>
                    <link>https://phys.org/news/2026-04-robotic-chemistry-built-deployed-lab.html</link>
                    <category>Analytical Chemistry</category>                    <pubDate>Mon, 13 Apr 2026 19:40:02 EDT</pubDate>
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                    <title>AI pragmatists: How language teachers are navigating AI with nuance</title>
                    <description>A pervasive narrative has taken hold in education: generative AI (genAI) is an unstoppable force, and educators must adapt or be left behind.</description>
                    <link>https://phys.org/news/2026-04-ai-pragmatists-language-teachers-nuance.html</link>
                    <category>Education</category>                    <pubDate>Sat, 11 Apr 2026 18:00:01 EDT</pubDate>
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                    <title>Bridging AI- and experimental-led materials discovery with better database architecture</title>
                    <description>Materials databases lie at the heart of future data-driven discovery in energy-related fields, say researchers from Tohoku University. In an article published in the journal Precision Chemistry, they have examined how different types of databases, both computational and experimental, work together to support modern artificial intelligence (AI) tools used in materials science.</description>
                    <link>https://phys.org/news/2026-04-bridging-ai-experimental-materials-discovery.html</link>
                    <category>Analytical Chemistry</category>                    <pubDate>Thu, 09 Apr 2026 22:40:04 EDT</pubDate>
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                    <title>Useful quantum computers could be built with as few as 10,000 qubits, team finds</title>
                    <description>Quantum computers of the future may be closer to reality thanks to new research from Caltech and Oratomic, a Caltech-linked start-up company. Theorists and experimentalists teamed up to develop a new approach for reducing the errors that riddle today&#039;s rudimentary quantum computers. Whereas these machines were previously thought to require millions of qubits to work properly (qubits being the quantum equivalent to 1&#039;s and 0&#039;s in classical computers), the new results indicate that a fully realized quantum computer could be built with as few as 10,000 to 20,000 qubits. The need for fewer qubits means that quantum computers could, in theory, be operational by the end of the decade.</description>
                    <link>https://phys.org/news/2026-04-quantum-built-qubits-team.html</link>
                    <category>Quantum Physics</category>                    <pubDate>Wed, 01 Apr 2026 14:20:04 EDT</pubDate>
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                    <title>Designing proteins by their motion, not just their shape</title>
                    <description>Proteins are far more than nutrients we track on a food label. Present in every cell of our bodies, they work like nature&#039;s molecular machines. They walk, stretch, bend, and flex to do their jobs, pumping blood, fighting disease, building tissue, and many other jobs too small for the eye to see. Their power doesn&#039;t come from shape alone, but from how they move.</description>
                    <link>https://phys.org/news/2026-03-proteins-motion.html</link>
                    <category>Biotechnology</category>                    <pubDate>Fri, 27 Mar 2026 11:20:04 EDT</pubDate>
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                    <title>Mapping 3D-super-enhancers with machine learning to pinpoint regulators of cell identity</title>
                    <description>Scientists usually study the molecular machinery that controls gene expression from the perspective of a linear, two-dimensional genome—even though DNA and its bound proteins function in three dimensions (3D). To better understand how key components of this machinery, such as super-enhancers, regulate genes in this 3D reality, scientists at St. Jude Children&#039;s Research Hospital have developed a new algorithm called BOUQUET.</description>
                    <link>https://phys.org/news/2026-03-3d-super-machine-cell-identity.html</link>
                    <category>Cell &amp; Microbiology</category>                    <pubDate>Mon, 09 Mar 2026 16:00:08 EDT</pubDate>
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                    <title>With Evo 2, AI can model and design the genetic code for all domains of life</title>
                    <description>The DNA foundation model Evo 2 has been published in the journal Nature. Trained on the DNA of over 100,000 species across the entire tree of life, Evo 2 can identify patterns in gene sequences across disparate organisms that experimental researchers would need years to uncover. The machine learning model can accurately identify disease-causing mutations in human genes and is capable of designing new genomes that are as long as the genomes of simple bacteria.</description>
                    <link>https://phys.org/news/2026-03-evo-ai-genetic-code-domains.html</link>
                    <category>Biotechnology</category>                    <pubDate>Wed, 04 Mar 2026 11:00:01 EST</pubDate>
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                    <title>Courtship is complicated, even in fruit flies</title>
                    <description>Love is in the air for the vinegar fly. Drosophila melanogaster has long been a model for understanding how brains translate sensory information into courtship behavior. Male flies perform a multitude of romantic actions—orienting, tapping, chasing and singing—directed toward eligible females.</description>
                    <link>https://phys.org/news/2026-02-courtship-complicated-fruit-flies.html</link>
                    <category>Ecology</category>                    <pubDate>Mon, 23 Feb 2026 12:40:04 EST</pubDate>
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                    <title>AI-based technology can detect gender violence from the voice</title>
                    <description>A research team at Universidad Carlos III de Madrid (UC3M) has developed technology using advanced machine learning techniques that detects signs of gender violence from paralinguistic characteristics of the voice such as tone, rhythm, and intensity. This innovative method helps to recognize situations of psychological stress or trauma while preserving the privacy of the speakers, which could have major implications for telephone helplines and telemedicine services.</description>
                    <link>https://phys.org/news/2026-02-ai-based-technology-gender-violence.html</link>
                    <category>Social Sciences</category>                    <pubDate>Thu, 19 Feb 2026 11:10:29 EST</pubDate>
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                    <title>Rolling out the carpet for spin qubits with new chip architecture</title>
                    <description>Researchers at QuTech in Delft, The Netherlands, have developed a new chip architecture that could make it easier to test and scale up quantum processors based on semiconductor spin qubits. The platform, called QARPET (Qubit-Array Research Platform for Engineering and Testing) and reported in Nature Electronics, allows hundreds of qubits to be characterized within the same test-chip under the same operating conditions used in quantum computing experiments.</description>
                    <link>https://phys.org/news/2026-02-carpet-qubits-chip-architecture.html</link>
                    <category>Condensed Matter</category>                    <pubDate>Thu, 12 Feb 2026 05:00:10 EST</pubDate>
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                    <title>Five ways quantum technology could shape everyday life</title>
                    <description>The unveiling by IBM of two new quantum supercomputers and Denmark&#039;s plans to develop &quot;the world&#039;s most powerful commercial quantum computer&quot; mark just two of the latest developments in quantum technology&#039;s increasingly rapid transition from experimental breakthroughs to practical applications.</description>
                    <link>https://phys.org/news/2026-02-ways-quantum-technology-everyday-life.html</link>
                    <category>Quantum Physics</category>                    <pubDate>Tue, 10 Feb 2026 19:00:01 EST</pubDate>
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                    <title>Keeping long-term climate simulations stable and accurate with a new AI approach</title>
                    <description>Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving models while retaining their accuracy. The approach retains physics-based models to simulate large-scale atmospheric dynamics, while harnessing deep learning to emulate cloud and convection processes that are too small to be resolved directly. In practice, however, many hybrid AI-physics models are unreliable. When simulations extend over months or years, small errors can accumulate and cause the model to become unstable.</description>
                    <link>https://phys.org/news/2026-02-term-climate-simulations-stable-accurate.html</link>
                    <category>Earth Sciences</category>                    <pubDate>Sat, 07 Feb 2026 08:00:15 EST</pubDate>
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                    <title>Pittsburgh study links dark roofs and roads to higher heat and social vulnerability</title>
                    <description>Cities are increasingly becoming the epicenter of climate-related risks, with research showing that impervious surfaces (e.g., roofs, streets, sidewalks, parking lots) are a major driver of urban climate impacts because they disrupt the natural surface energy balance, increase stormwater runoff, and intensify urban heat island effects.</description>
                    <link>https://phys.org/news/2026-02-pittsburgh-links-dark-roofs-roads.html</link>
                    <category>Environment</category>                    <pubDate>Thu, 05 Feb 2026 16:15:34 EST</pubDate>
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                    <title>Philadelphia communities help AI machine learning get better at spotting gentrification</title>
                    <description>Over the last several decades, urban planners and municipalities have sought to identify and better manage the socioeconomic dynamics associated with rapid development in established neighborhoods. The term &quot;gentrification&quot; has been lingua franca for generations of urbanites who have seen their communities change and property values, and commensurate taxes, shift in ways that can make it difficult for longtime residents to stay. But identifying its unmanaged creep can be a challenge, particularly in densely populated areas, as its visual hallmarks—such as new facades, mixes in building materials and changes in building heights—present differently in different cities and regions.</description>
                    <link>https://phys.org/news/2026-02-philadelphia-communities-ai-machine-gentrification.html</link>
                    <category>Social Sciences</category>                    <pubDate>Thu, 05 Feb 2026 14:20:06 EST</pubDate>
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                    <title>AI enables a who&#039;s who of brown bears in Alaska</title>
                    <description>A team of scientists from EPFL and Alaska Pacific University has developed an AI program that can recognize individual bears in the wild, despite the substantial changes that occur in their appearance over the summer season. This breakthrough holds significant promise for research, management, and conservation efforts. The study is published in the journal Current Biology.</description>
                    <link>https://phys.org/news/2026-01-ai-enables-brown-alaska.html</link>
                    <category>Plants &amp; Animals</category>                    <pubDate>Thu, 29 Jan 2026 11:20:04 EST</pubDate>
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                    <title>Atom-thin, content-addressable memory enables edge AI applications</title>
                    <description>Recent advances in the field of artificial intelligence (AI) have opened new exciting possibilities for the rapid analysis of data, the sourcing of information and the generation of use-specific content. To run AI models, current hardware needs to continuously move data from internal memory components to processors, which is energy-intensive and can increase the time required to tackle specific tasks.</description>
                    <link>https://phys.org/news/2026-01-atom-thin-content-memory-enables.html</link>
                    <category>Nanophysics</category>                    <pubDate>Mon, 12 Jan 2026 09:50:01 EST</pubDate>
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                    <title>Enhancing machine-learning interatomic potentials for advanced materials modeling</title>
                    <description>Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations of interatomic potentials, that are mathematical functions that express the energy of a system of atoms and are an ingredient to simulate and predict the stability and properties of materials. But machine learning by itself is not a magic wand, and many problems remain.</description>
                    <link>https://phys.org/news/2025-12-machine-interatomic-potentials-advanced-materials.html</link>
                    <category>Analytical Chemistry</category>                    <pubDate>Thu, 11 Dec 2025 15:34:12 EST</pubDate>
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                    <title>Flood disaster prediction using multi-scale deep learning and neuro-fuzzy inference</title>
                    <description>A new algorithmic framework that can predict flooding could help save lives and reduce the devastation as climate change drives more intense and unpredictable rainfall.</description>
                    <link>https://phys.org/news/2025-12-disaster-multi-scale-deep-neuro.html</link>
                    <category>Earth Sciences</category>                    <pubDate>Mon, 01 Dec 2025 21:00:01 EST</pubDate>
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                    <title>Transformer AI models outperform neural networks in stock market prediction, study shows</title>
                    <description>Like other sectors of society, artificial intelligence is fundamentally changing how investors, traders and companies make decisions in financial markets. AI models have the ability to analyze massive amounts of data while reading company filings or news headlines almost instantaneously. This is allowing for faster, more automated trading, which is making it difficult for human traders—not utilizing AI—to find an edge in the markets.</description>
                    <link>https://phys.org/news/2025-11-ai-outperform-neural-networks-stock.html</link>
                    <category>Economics &amp; Business</category>                    <pubDate>Thu, 20 Nov 2025 11:17:04 EST</pubDate>
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                    <title>Physicists unveil system to solve long-standing barrier to new generation of supercomputers</title>
                    <description>The dream of creating game-changing quantum computers—supermachines that encode information in single atoms rather than conventional bits—has been hampered by the formidable challenge known as quantum error correction.</description>
                    <link>https://phys.org/news/2025-11-physicists-unveil-barrier-generation-supercomputers.html</link>
                    <category>Quantum Physics</category>                    <pubDate>Thu, 13 Nov 2025 09:17:04 EST</pubDate>
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