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Categories: Energy: Alternative Fuels, Mathematics: Modeling

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A joint research team in computer science, economics, and geography has developed an artificial intelligence (AI) technology to measure grid-level economic development within six-square-kilometer regions. This AI technology is applicable in regions with limited statistical data (e.g., North Korea), supporting international efforts to propose policies for economic growth and poverty reduction in underdeveloped countries. The research team plans to make this technology freely available for use to contribute to the United Nations' Sustainable Development Goals (SDGs).

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Mathematics, histopathology and genomics converge to confirm that the most aggressive clear cell renal cell carcinomas display low levels of intratumour heterogeneity, i.e. they contain fewer distinct cell types. The study supports the hypothesis that it would be advisable to apply therapeutic strategies to maintain high levels of cellular heterogeneity within the tumour in order to slow down the evolution of the cancer and improve human survival.  

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Hydrogen is a building block for the energy transition. To obtain it with the help of solar energy, researchers have developed new high-performance nanostructures. The material holds a world record for green hydrogen production with sunlight.

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Researchers have demonstrated the use of AI-selected natural images and AI-generated synthetic images as neuroscientific tools for probing the visual processing areas of the brain. The goal is to apply a data-driven approach to understand how vision is organized while potentially removing biases that may arise when looking at responses to a more limited set of researcher-selected images.

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A new AI model that optimizes the use of renewables and other energy sources outperforms traditional power restoration techniques for islanded microgrids, a new paper shows. 

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Salt batteries can store summer heat to be used in winter, but which salt works best for the purpose?

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Engineers have achieved a world first by manufacturing the first back-contact micrometric photovoltaic cells.

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Tandem solar cells based on perovskite semiconductors convert sunlight to electricity more efficiently than conventional silicon solar cells. In order to make this technology ready for the market, further improvements with regard to stability and manufacturing processes are required. Researchers have succeeded in finding a way to predict the quality of the perovskite layers and consequently that of the resulting solar cells: Assisted by Machine Learning and new methods in Artificial Intelligence (AI), it is possible assess their quality from variations in light emission already in the manufacturing process.

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Biological materials are made of individual components, including tiny motors that convert fuel into motion. This creates patterns of movement, and the material shapes itself with coherent flows by constant consumption of energy. Such continuously driven materials are called 'active matter'. The mechanics of cells and tissues can be described by active matter theory, a scientific framework to understand shape, flows, and form of living materials. The active matter theory consists of many challenging mathematical equations. Scientists have now developed an algorithm, implemented in an open-source supercomputer code, that can for the first time solve the equations of active matter theory in realistic scenarios. These solutions bring us a big step closer to solving the century-old riddle of how cells and tissues attain their shape and to designing artificial biological machines.

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Scientists have leveraged artificial intelligence models to enhance dam operations.

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Energy researchers posit hydrogen fuel can potentially be a cost-competitive and environmentally friendly alternative to gasoline and diesel, and that supplying hydrogen for transportation in the greater Houston area can be profitable today.

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As power generation from sources like solar and wind increases, along with the introduction of devices such as heat pumps and batteries, a new optimization tool will help the UK plan for a greener electricity network.   The researchers developed an algorithm to model how these smaller networks distributed electricity -- factoring in how local grids could become unbalanced by adding too many heat pumps in a single area or generating more electricity than the grid could accept.  

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A team of researchers looked back at a model that predicted nuclear power would expand dramatically in order to assess the efficacy of energy policies implemented today.

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Engineers enhance hydrogen fuel cell durability via tungsten oxide coating.

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Electrochemical catalysts used in water splitting often show poor performance due to low electrical conductance of (oxy)hydroxide species produced in situ. To overcome this challenge, researchers have now designed an electrode with Schottky Junction formed at the interface of metallic Ni-W5N4 and semiconducting NiFeOOH. The proposed electrode shows excellent catalytic activity and can facilitate industrial seawater splitting continuously for 10 days.

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An innovative approach to artificial intelligence (AI) enables reconstructing a broad field of data, such as overall ocean temperature, from a small number of field-deployable sensors using low-powered 'edge' computing, with broad applications across industry, science and medicine.

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Researchers have identified the potential environmental risks of using ammonia as a zero-carbon fuel in order to develop an engineering roadmap to a sustainable ammonia economy.

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A floating, solar-powered device that can turn contaminated water or seawater into clean hydrogen fuel and purified water, anywhere in the world, has been developed by researchers.

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Deep within every piece of magnetic material, electrons dance to the invisible tune of quantum mechanics. Their spins, akin to tiny atomic tops, dictate the magnetic behavior of the material they inhabit. This microscopic ballet is the cornerstone of magnetic phenomena, and it's these spins that a team of researchers has learned to control with remarkable precision, potentially redefining the future of electronics and data storage.

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In the same way that chatbots sometimes 'hallucinate,' or make things up, machine learning models designed for scientific applications can sometimes present misleading or downright false results. Researchers now present a new statistical technique for safely using AI predictions to test scientific hypotheses.