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Categories: Computer Science: General, Energy: Fossil Fuels

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Researchers have developed an easy-to-use optical chip that can configure itself to achieve various functions. The positive real-valued matrix computation they have achieved gives the chip the potential to be used in applications requiring optical neural networks.

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Researchers have demonstrated a type of quantum eraser. The physicists show that they can pinpoint and correct for mistakes in quantum computing systems known as 'erasure' errors. 

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Artificial intelligence (AI) comes with promises of helping coders code faster, drivers drive safer, and making daily tasks less time-consuming. But a recent study demonstrates that the tool, when adopted widely, could have a large energy footprint, which in the future may exceed the power demands of some countries.

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A team of computer scientists has created a neural network that can explain how it reaches its predictions. The work reveals what accounts for the functionality of neural networks--the engines that drive artificial intelligence and machine learning--thereby illuminating a process that has largely been concealed from users.   

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A fundamental discovery about the Fischer Tropsch process, a catalytic reaction used in industry to convert coal, natural gas or biomass to liquid fuels, could someday allow for more efficient fuel production. Researchers discovered previously unknown self-sustained oscillations in the Fischer Tropsch process. They found that unlike many catalytic reactions which have one steady state, this reaction periodically moves back and forth from a high to a low activity state. The discovery means that these well-controlled oscillatory states might be used in the future to control the reaction rate and the yields of desired products.

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Whether you’re battling foes in a virtual arena or collaborating with colleagues across the globe, lag-induced disruptions can be a major hindrance to seamless communication and immersive experiences. That’s why researchers have developed new technology to make data transfer over optical fiber communication faster and more efficient.

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Big data and artificial intelligence (AI) are being used to model hidden patterns in nature, not just for one bird species, but for entire ecological communities across continents. And the models follow each species’ full annual life cycle, from breeding to fall migration to non-breeding grounds, and back north again during spring migration.

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For reasons of food security and economic incentive, farmers continuously seek to maximize their marketable crop yields. As plants grow inconsistently, at the time of harvesting, there will inevitably be variations in quality and size of individual crops. Finding the optimal time to harvest is therefore a priority for farmers. A new approach making heavy use of drones and artificial intelligence demonstrably improves this estimation by carefully and accurately analyzing individual crops to assess their likely growth characteristics.

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Researchers developed the first AI to date that can intelligently design robots from scratch by compressing billions of years of evolution into mere seconds. It's not only fast but also runs on a lightweight computer and designs wholly novel structures from scratch — without human-labeled, bias-filled datasets.

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At the core of uncovering extreme events such as floods is the physics of fluids – specifically turbulent flows. Researchers leveraged a computer-vision deep learning technique and adapted it for nonlinear analysis of extreme events in wall-bounded turbulent flows, which are pervasive in numerous physics and engineering applications and impact wind and hydrokinetic energy, among others. Results show the technique employed can be invaluable for accurately identifying the sources of extreme events in a completely data-driven manner.

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Chemical engineers have designed a fuel that ignites only with the application of electric current. Since it doesn't react to flames and cannot start accidental fires during storage or transport, it is a 'safe' liquid fuel.

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Scientists unveil exciting possibilities for the development of highly efficient quantum devices.

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Researchers have developed a novel superconducting qubit architecture that can perform operations between qubits with much higher accuracy than scientists have yet been able to achieve. This architecture, which utilizes a relatively new type of superconducting qubit called fluxonium, is scalable and could be used to someday build a large-scale quantum computer.

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Boosting virtual screening with machine learning allowed for a 10-fold time reduction in the processing of 1.56 billion drug-like molecules. Researchers teamed up with industry and supercomputers to carry out one of the world's largest virtual drug screens.

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A research team has successfully developed a new method that can prevent the crossover of large fuel molecules and suppress the degradation of electrodes in advanced fuel cell technology using methanol or formic acid. The successful sieving of the fuel molecules is achieved via selective proton transfers due to steric hindrance on holey graphene sheets that have chemical functionalization and act as proton-exchange membranes.

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New physics-based self-learning machines could replace the current artificial neural networks and save energy.

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As renewable energy sources like wind and solar ramp up, they can be used to sustainably generate hydrogen fuel. But implementing such a strategy on a large scale requires land and water dedicated to this purpose.

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Scientists have shown that their steerable lung robot can autonomously maneuver the intricacies of the lung, while avoiding important lung structures.

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Scientists and industry leaders worldwide are looking for answers on how to make aviation sustainable by 2050 and choosing a viable sustainable fuel is a major sticking point. Aerospace engineers took a full inventory of the options to make a data-driven assessment about how they stack up in comparison. He reviewed over 300 research projects from across different sectors, not just aerospace, to synthesize the ideas and draw conclusions to help direct the dialogue about sustainable aviation toward a permanent solution.

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Building on work in human-computer interaction that aims to incorporate sustainability and reuse into the field, researchers introduce 'garbatrage,' a framework for prototype builders centered around repurposing underused devices.