Fast but error-prone AI assists in solving a decades-old fluid mechanics problem in five weeks
An AI assistant helped University of Colorado Boulder researchers solve a mathematical problem that had challenged their lab for a year and a half, though it made subtle errors along the way.
An AI assistant helped University of Colorado Boulder researchers solve a mathematical problem that had challenged their lab for a year and a half, though it made subtle errors along the way.
The short version
- The breakthrough could improve how scientists study nanoparticles—tiny particles about 1,000 times thinner than a human hair—but it reveals both the promise and limitations of AI as a scientific research partner.
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- The new study, published in the Journal of Fluid Mechanics , details the solution to a decades-old fluid mechanics problem and explains how researchers combined AI with human expertise to reach the answer.
What happened
The research was led by Ankur Gupta, an assistant professor of chemical and biological engineering, and his graduate student, Arkava Ganguly, who spent a year and a half working on the problem. The paper focuses on electrophoresis, the movement of charged particles in an electric field.
Why it matters
More than a century ago, the Polish physicist Marian Smoluchowski showed that the speed of particles is typically independent of their size and shape.
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