Skip to content Skip to navigation

Research & Ideas

Search this site

An ability to sort microparticles by shape could improve human health

The new technique repurposes a common tool in biology that can help separate red blood cells from white blood cells or human cells from microbial cells.

Illustration of squares and circles

Researchers created a shape-sorter to help identify and isolate microparticles. | Illustration by Kevin Craft

Engineers want to design microparticles for all sorts of applications, but there’s one big problem: So far, materials scientists have had no reliable way to identify and sort microparticles by shape.

If they could, it could make it much easier to deliver drugs deep inside the body or create ultrapure crystals that use light in new ways.

Now, Stanford engineers may have solved that problem. In a recent work published in Nature Materials, H. Tom Soh, a professor of electrical engineering and of radiology, and former postdoctoral scholar Peter Mage describe how they borrowed a hardware tool from biology and a software technique from atmospheric research. Combining these two technologies, they created a system that can sort several thousand microparticles each second — based purely on shape — and they think far greater efficiencies are possible.

“This will be super useful for materials scientists in many areas of research,” said Soh, who sees applications in fields stretching from pharmaceuticals to biomedical imaging.

The new technique repurposes a familiar biological tool called the fluorescence-activated cell sorter, or FACS, which itself was invented at Stanford in the 1960s. Biologists use FACS to separate living cells from one another — red blood cells from white, human from microbial or virus, and so forth. FACS works by feeding cells one by one through a laser beam. Sensors read identifiable patterns of light scattering off the cells.

Biologists have it easy when it comes to cell sorting, explained Mage, who is now a scientist in the biotech industry. That’s because biologists can tag cells with fluorescent molecules that serve as biological barcodes to identify specific cell types. There is no meaningful way to identify particle shape using fluorescent labels, which attach themselves to molecules found only on living cells. So, until now, FACS has been useless for materials science, and shape-sorting has been a roadblock to scientific advancement.

“Imagine staring into a thick solution of millions of invisible microparticles smaller than specks of dust and being asked to isolate one particular shape by hand,” Mage said. “It’s virtually impossible.”

And, in a field where shape is everything, materials scientists were left empty-handed until Soh and Mage discovered that, under laser light, microparticles act like tiny lenses and mirrors, reflecting, refracting and diffracting light in equally distinct ways based on their physical shape.

So, unlike biologists, materials scientists don’t need fluorescence to tag microparticles, not when each shape has its own light-scattering signature. But to make FACS practical for sorting non-biological materials, they needed a way to predict how the scattering signatures would arise for different shapes.

They found the answer in a software technique that atmospheric scientists use to study the interaction of light and water in clouds. Over the last three years, Mage and Soh have used their hybrid system to analyze and catalog the scattering signatures of variously shaped micro- and nanoparticles. The particle identifier works on complex mixtures containing diverse sizes and materials. It can discriminate particles that are nearly identical in shape and is not fooled by particle orientation. The team has even developed a scatter-pattern toolkit that can accommodate the signatures of new sizes, shapes and materials yet to be developed.

Light-based shape identification is only the first step in their technique. The second step is to rapidly sort particles of a desired shape from solutions containing many shapes. In the biological world, FACS accomplishes this by applying a small electrical charge to a droplet encapsulating each cell. The Stanford group used the same technique to direct particles into shape-based collection points.

There is a lower size limit to the effectiveness of the technique. The researchers studied microparticles ranging from as large as 20 micrometers, nearly the width of a human hair, to as small as 500 nanometers, the size of an E. coli bacterial cell. They think they can improve the sophistication of their software so that the system could sort even smaller particles. Eventually, however, they expect that the hardware will bump up against a fundamental limit because the tiniest nanoparticles would scatter light uniformly regardless of shape, make sorting impossible.

Even so, the technique provides a new and needed capability for shape-sorting microparticles for applications ranging from drug delivery to exotic low-power display technologies. The Stanford technique works with any of the several different types of FACS devices now being used in biological research. It’s the new software that teaches the hardware new tricks.

“We purposely designed our system to work with off-the-shelf FACS to reduce the barriers to its adoption and use in materials sciences,” Soh said.

Contributing authors include professor Craig Hawker, project scientist Andrew T. Csordas and project scientist Daniel Klinger of the University of California, Santa Barbara; professor Samir Mitragotri and graduate student Tyler Brown of Harvard University; and Stanford project scientist Michael Eisenstein.

Financial support was provided by the Defense Advanced Research Projects Administration.