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New carbon nanotube-based foam guarantees superior safety in opposition to concussions — ScienceDaily


Developed by College of Wisconsin-Madison engineers, a light-weight, ultra-shock-absorbing foam may vastly enhance helmets designed to guard individuals from robust blows.

The brand new materials displays 18 instances larger particular power absorption than the froth at present utilized in U.S. navy fight helmet liners, in addition to having a lot better energy and stiffness, which may permit it to supply improved influence safety.

Bodily forces from an influence can inflict trauma within the mind, inflicting a concussion. However helmet supplies which might be higher at absorbing and dissipating this kinetic power earlier than it reaches the mind may assist mitigate, and even stop, concussions and different traumatic mind accidents.

The researchers’ {industry} associate, helmet producer Workforce Wendy, is experimenting with the brand new materials in a helmet liner prototype to research its efficiency in real-world situations.

“This new materials holds super potential for power absorption and thus influence mitigation, which in flip ought to considerably decrease the probability of mind damage,” says Ramathasan Thevamaran, a UW-Madison professor of engineering physics who led the analysis.

The group detailed its advance in a research printed not too long ago within the journal Excessive Mechanics Letters.

The brand new materials is an architected, vertically aligned carbon nanotube foam. To create it, the researchers began with carbon nanotubes — carbon cylinders only one atom thick in every layer — as the fundamental constructing blocks.

Carbon nanotubes have already got distinctive mechanical properties, and to additional improve their efficiency, the researchers designed a fabric with distinctive structural options throughout a number of size scales. The fabric’s novel structure consists of quite a few micrometer-scale cylinder constructions, every made from many carbon nanotubes.

Discovering the brand new foam’s final optimum design parameters — such because the thickness of the cylinders, their internal diameter and the hole between adjoining cylinders — was no small job. The researchers systematically carried out experiments the place they different every parameter and studied all of the potential combos.

“So we took a number of totally different thicknesses, after which examined that with each diameter measurement and each potential hole, and so forth,” Thevamaran says. “Altogether, we checked out 60 totally different combos and carried out three assessments on every pattern, so 180 experiments went into this research.”

They uncovered a transparent winner. Cylinders with a thickness of 10 micrometers or much less, organized shut to one another, produced a foam with the most effective shock-absorbing properties.

“I anticipated the general properties to enhance resulting from our interactive structure, however I used to be shocked by how dramatically the properties had been enhanced when the cylinders had been 10 micrometers thick,” Thevamaran says. “It was resulting from an uncommon measurement impact that emerged within the process-structure-property relations. The impact was very pronounced, and it turned out to be fairly advantageous for the properties we had been focusing on.”

As well as, the brand new materials can stay robustly shock-absorbing at each very excessive and really low temperatures due to its carbon nanotube constructing blocks, making it helpful for functions in a variety of maximum environments.

The researchers, together with Komal Chawla, UW-Madison postdoctoral analysis affiliate, and graduate college students Abhishek Gupta and Abhijeet S. Bhardwaj, are patenting their innovation via the Wisconsin Alumni Analysis Basis. The university-industry collaboration was a part of the UW¬-Madison-led PANTHER program, an interdisciplinary analysis initiative that’s growing options to allow higher detection and prevention of traumatic mind accidents.

Grants from the U.S. Workplace of Naval Analysis (N000142112044) and the Military Analysis Workplace (W911NF2010160) supported the analysis.

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