Scientists just successfully created synthetic polymers at the atomic scale. If scalable, it could enhance polymer fabrication methods and lead to better polymer-based products.

For polymers, we remain dependent on nature by harvesting materials from vegetable and animal sources.

Latex or natural rubber, cellulose, silk, and wool are all naturally-occurring polymers that were and are still widely used.

DNA is also an organic polymer, though we have yet to figure out how to harness its full potential.

It wasn’t until the early 1900s that we started synthesizing polymers from petroleum oil.

Today, we can’t even imagine our modern life without all the plastic products based on synthetic polymers.

The world produces about 140 million tons per year of nylon, polyester, epoxy, Teflon, polyethylene, and other synthetic polymers.

However, although we’ve been making them for decades, we still don’t know much about the microscopic nature of synthetic polymers.

Read More: New Biodegradable Plastic Polymer Found by Researchers

Taking a Peek at Synthetic Polymer Atoms

Until today, to have a look at individual atoms in polymers, you had to use computer simulations or illustrations.

Now, new research from the Lawrence Berkeley National Laboratory (Berkeley Lab) and the University of California Berkeley (UC Berkeley), has changed that.

In a world first, the team of materials scientists led by Professor Nitash Balsara“adapted a powerful electron-based imaging technique to obtain an image of atomic-scale structure in a synthetic polymer.”

This process could help devise better fabrication methods of synthetic polymers and incorporate them more effectively into materials and devices.

At Berkeley Lab’s Molecular Foundry, the team designed a peptoid polymer, a synthetic polymer that mimics natural peptides.

They then tested a sample of the peptoid polymer with the adapted imaging technique they call Cryogenic Electron Microscopy.

Along with computer simulations and sorting techniques, the cryogenic electron microscope identified 35 arrangements of crystal structures in the peptoid polymer sample. Professor Balsara describes these structures as “the most perfect polymer molecules we could make.”

Images of individual atoms in the sample were too blurry with a resolution of “about 2 angstroms, which is two-tenths of a nanometer (billionth of a meter), or about double the diameter of a hydrogen atom.”

They enhanced the resolution thanks to sorting methods first designed to image the structure of proteins at the atomic scale.

“We took advantage of technology that the protein-imaging folks had developed and extended it to human-made, soft materials. Only when we sorted them and averaged them did that blurriness become clear. Before these high-resolution images, the arrangement and variation of the different types of crystal structures was unknown,” said Nitash Balsara, UC Berkeley’s professor of chemical and biomolecular engineering.

For even higher resolution, the team is planning on using AI algorithm-based sorting methods.

“We should be able to determine the atomic-scale structure of a wide variety of synthetic polymers such as commercial polyethylene and polypropylene, leveraging rapid developments in areas such as artificial intelligence, using [machine learning].”

After proteins and synthetic polymers, what other molecular structures can we use this imaging technique for?

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