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Having the right tool for the job makes the job a lot easier, less expensive and faster. Chemical engineering researchers have now developed a virtual laboratory that can be used to determine the artificial intelligence AI tools best dzting for addressing various chemical synthesis challenges in flow chemistry systems.
My team focused on the hardware challenges with our Artificial Chemist project. Fossil dating virtual lab work we're publishing now is focused on addressing the autonomous decision-making challenges. Abolhasani's work stems from his observation that: A there are a lot of different AI tools available; B it's not always datinh which tool is the best fit for any given material synthesis problem; and C whichever tool is selected, it will always need to be fine-tuned based on the chemistry problem.
Not just identifying the best material, but the best way of producing that material so that it has the best possible combination of characteristics. And the best AI model architecture is going to vary depending on the material and the complexity of lag challenge. So Abolhasani and his collaborators took an AI-driven approach to finding the best AI tool for each material synthesis problem.
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The researchers ran 1, experiments using their automated Artificial Chemist platform and used those experimental data points to train the virtual experimental platform. For the work reported in the new paper, the virtual laboratory simulated more virtua,experiments, assessing more than AI-guided decision-making strategies. If those experiments were run in the real world, even using automated systems and microscale volumes of material, the experiments would have taken 7.
Abolhasani's team did it in about a month. Ultimately, we think that these AI-driven tools will be able to operate quickly enough to adjust operations as needed in real time. Materials provided by North Carolina State University. Original written by Matt Shipman.
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Note: Content may be edited for style and length. Science News. Journal Reference : Robert W. Epps, Amanda A. Volk, Kristofer G. Reyes, Milad Abolhasani. Accelerated AI development for autonomous materials synthesis in flow. Chemical Science; DOI: ScienceDaily, 22 March North Carolina State University.]
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