West LA Times

Computational microscopy has seen significant advancements over the past 25 years, allowing researchers to visualize extremely small and ultrafast phenomena. UCLA physicist John Miao has been a key figure in developing the foundational methods that have driven this field forward. In a recent single-author review article, Miao offers a comprehensive overview of computational microscopy and its potential for future developments, such as determining the three-dimensional atomic structures of small elements like carbon, nitrogen, and oxygen.

In 1999, Jianwei “John” Miao, then a graduate student at the State University of New York, Stony Brook, demonstrated with his colleagues that computational algorithms could reveal details previously impossible to capture with conventional microscopes. They expanded on X-ray crystallography to apply it to structures lacking uniform patterns found in crystals. The algorithm reconstructs images from diffraction patterns created when electromagnetic beams pass through samples.

Miao's approach is likened to a "killer app" for microscopes, unlocking their full potential by combining diffraction and computation to replace traditional objective lenses. Over the years, this method has been integrated into various types of microscopes, advancing computational microscopy to achieve unparalleled resolution and precision.

As a professor at UCLA College, Miao authored the first comprehensive review of computational microscopy published in Nature. His article highlights innovative developments and multidisciplinary applications while outlining future directions for the field.

“Spinoza found ultimate happiness in discovering truth in nature,” said Miao. “That philosophy is always on my mind. Each of us has only one life to live, and I am committed to seeking truth and addressing profound scientific problems.”

Miao's work focuses on two related methods: coherent diffractive imaging (CDI) and ptychography. CDI uses synchronized beams for rapid event capture while ptychography provides detailed images across larger fields of view despite being slower.

The review also explores new frontiers opened by these techniques across various scientific disciplines. Researchers have used them to reveal biological structures, capture magnetic phenomena on ultrafast timescales, inspect microchips nondestructively, and observe batteries charging in real-time.

Miao expects further breakthroughs as artificial intelligence accelerates phase information extraction from diffraction patterns. He anticipates advancements will allow scientists real-time views of studied phenomena and determine atomic structures of high-tech materials.

“Physics, chemistry, materials science... every field stands to benefit,” Miao stated. “The future is cross-disciplinary.”

In his review, Miao acknowledges support from organizations including the National Science Foundation’s STROBE center where he serves as deputy director.