In this pulsed laser deposition setup, an invisible laser emanating from outside the scene to the right, strikes targets in the lower and upper left, creating plasma plumes. The stream of atoms and particles from the plumes form an ultrathin film on the surface of the sample in the upper right.
Pictured on the left, human vision of the pulsed laser deposition plasma plumes. On the right, images from movies of the interpretation of the plasma plumes by AI, which can predict film growth characteristics.
Newswise — In a game-changing study, Oak Ridge National Laboratory scientists developed a deep learning model — a type of artificial intelligence that mimics human brain function — to analyze high-speed videos of plasma plumes during a process called pulsed laser deposition, or PLD.
The PLD technique uses powerful laser pulses to vaporize a target material, creating a cloud-like stream of atoms and particles — the plasma plume — which then settles onto a target surface to form ultrathin films. This method is crucial for creating advanced materials used in electronics and energy technologies.
"We've taught AI to do what expert scientists have always done intuitively — assess the plasma plume to check if the color, shape, size and brightness look the same as they did the last time a good sample was made," said ORNL’s Sumner Harris, the lead author of the study. "This not only automates quality control but also reveals unexpected insights into how these microscopic particles behave during film formation."
This innovation builds on ORNL’s previous development of an autonomous PLD system that accelerates materials discovery tenfold, promising to transform materials synthesis monitoring and further streamline the creation of next-generation materials. — Scott Gibson
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