Nov. 15, 2013 – Professor Barry Goodell’s recent research provides a link to Middle Age weaponry. He aims to discover a process that would incorporate carbon nanomaterials into steel to produce a hybrid of biobased carbon and metal that could greatly enhance the strength of steel products.
Along the way, Goodell and his team hope to uncover the secret behind an ancient steel used to make sword blades. Damascus steel, which was manufactured in the area that is now Syria as far back as A.D. 900, was known for its exceptional strength and sharp blade, while also being able to bend without breaking. While sword smiths have been able to replicate the steel’s distinctive wavy pattern, the exact manufacturing process was lost about 300 years ago.
Recent studies on museum pieces revealed that those ancient blades contained carbon nanotubes, which explains the steel’s famed properties. Similar processes developed by Goodell’s team could hold the key to many modern advancements, ranging from lighter weight vehicles to more wear-resistant engine parts.
Hoping to replicate the long-lost technologies, Goodell and his team experiment with heating pieces of iron and steel with carbonized wood fibers to study how the carbon nanotubes were generated within the steel — a key part of the Damascus puzzle. “We now know that the carbon nanotubes are part of the secret to why the swords were legendarily sharp,” said Goodell.
Once the secret is revealed, Goodell says it has the potential for wide-ranging benefits. The steel could make cars lighter for better fuel efficiency while also maintaining strength for safety. Reactors for energy production could run at three times the temperature of current reactors, resulting in more efficient energy output. Among the many possible applications, Goodell says, the steel could also be used to produce stronger turbines and more durable car parts.
Goodell and three other faculty members — Scott Renneckar, associate professor of sustainable biomaterials; Alan Druschitz, associate professor of materials science and engineering; and Xinwei Deng, assistant professor of statistics — are leading the project.