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Categories: Energy: Fossil Fuels, Mathematics: Statistics

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By studying how bubbles form in a drop of biodiesel, researchers can help future engines get the most energy out of the fuel.

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Researchers have recast diffusion in multicomponent alloys as a sum of individual contributions, called 'kinosons.' Using machine learning to compute the statistical distribution of the individual contributions, they were able to model the alloy and calculate its diffusivity orders of magnitude more efficiently than computing whole trajectories.

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Artificial intelligence (AI) computer programs that process MRI results show differences in how the brains of men and women are organized at a cellular level, a new study shows. These variations were spotted in white matter, tissue primarily located in the human brain's innermost layer, which fosters communication between regions.

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A special review examines highly-cited papers in statistical ecology. The review, which covers a century of research, details how models and concepts have evolved alongside increasing computational power.

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Physicists and computer scientists have recently expanded the modern theory of the thermodynamics of computation. By combining approaches from statistical physics and computer science, the researchers introduce mathematical equations that reveal the minimum and maximum predicted energy cost of computational processes that depend on randomness, which is a powerful tool in modern computers.

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Coal phase-out is necessary to solve climate change, but can have negative impacts on workers and local communities dependent on coal for their livelihoods. Researchers have studied government plans for coal phase-out around the world and discovered that more than half of such plans include monetary compensation to affected parties. This planned compensation globally amounts to USD 200 billion, but it excludes China and India, the two largest users of coal that currently do not have phase-out plans. The study shows that if China and India decide to phase out coal as fast as needed to reach the Paris climate targets and pay similar compensation, it would cost upwards of USD 2 trillion.

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Researchers have developed a chemical process using plasma that could create sustainable jet fuel from methane gas emitted from landfills, potentially creating a low-carbon aviation industry.

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Elucidating the relationship between the sequences of non-coding regulatory elements and their target genes is key to understanding gene regulation and its variation between plant species and ecotypes. Now, an international research team developed deep learning models that link gene sequence data with mRNA copy number for several plant species and predicted the regulatory effect of gene sequence variation.

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The first health impact study of coal train pollution centers on the San Francisco Bay Area, with scientists finding communities near passing coal trains suffer worse health outcomes.

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International shipping does not want to be a climate bad guy and is aiming to be emission-free by 2050. A new tool can help shipowners who are searching for green solutions.

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Scientists are using computer simulations and laboratory experiments to see if depleted oil and natural gas reservoirs can be used for storing carbon-free hydrogen fuel. Hydrogen is an important clean fuel: It can be made by splitting water using solar or wind power, it can be used to generate electricity and power heavy industry, and it could be used to power fuel-cell-based vehicles. Additionally, hydrogen could be stored for months and used when energy needs outpace the supply delivered by renewable energy sources.

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Researchers have developed a new method to predict the financial impacts climate change will have on agriculture, which can help support food security and financial stability for countries increasingly prone to climate catastrophes.

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Scientists have developed an automated workflow that could accelerate the discovery of new pharmaceutical drugs and other useful products. The new automated approach could analyze chemical reactions in real time and identify new chemical-reaction products much faster than current laboratory methods.

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Researchers show that using magnetic fields can boost electrocatalysis for sustainable fuel production by enhancing the movement of the reactants, which improves the efficiency of energy-related reactions.

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A new way to make an important ingredient for plastics, adhesives, carpet fibers, household cleaners and more from natural gas could reduce manufacturing costs in a post-petroleum economy by millions of dollars, thanks to a new chemical reactor.

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Scientists have demonstrated the selective conversion of carbon dioxide (CO2) into methanol using a cascade reaction strategy. The two-part process is powered by sunlight, occurs at room temperature and at ambient pressure, and employs a recyclable organic reagent that's similar to a catalyst found in natural photosynthesis.

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In order to limit the increase in global average temperature to 1.5 C, it is essential to drastically reduce carbon dioxide emissions in the atmosphere. This would mean not exploiting most of the existing coal, conventional gas and oil energy resources in regions around the world, according to new research. The study presents the atlas of unburnable oil in the world, a world map designed with environmental and social criteria that warns which oil resources should not be exploited to meet the commitments of the Paris Agreement signed in 2015 to mitigate the effects of climate change.

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Neural networks have been powering breakthroughs in artificial intelligence, including the large language models that are now being used in a wide range of applications, from finance, to human resources to healthcare. But these networks remain a black box whose inner workings engineers and scientists struggle to understand. Now, a team has given neural networks the equivalent of an X-ray to uncover how they actually learn.

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Quantum sensor technology promises even more precise measurements of physical quantities. A team has now compared the signals of up to 91 quantum sensors with each other and thus successfully eliminated the noise caused by interactions with the environment. Correlation spectroscopy can be used to increase the precision of sensor networks.

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A team of scientists has devised means for classical computing to mimic a quantum computing with far fewer resources than previously thought. The scientists' results show that classical computing can be reconfigured to perform faster and more accurate calculations than state-of-the-art quantum computers.