All posts by Margot Knight

Carbon black: Using old tires to make longer lasting batteries

Old disused tires can be utilised to help make batteries that last longer and also have long-term stability.

Researchers at the Department of Energy’s Oak Ridge National Laboratory (ORNL) believe that lithium-ion batteries, storing wind and solar energy and powering plug-in electric vehicles, could be developed at a lower cost, both financially and to the environment, by developing a better anode made from a substance found in recycled tires.

An anode is a negatively charged electrode used as a host for storing lithium during charging.

The substance, recovered from discarded tires, is carbon black.

Modifying its microstructural characteristics is the solution to developing a better anode, says the team led by Parans Paranthaman and Amit Naskar.


“This technology addresses the need to develop an inexpensive, environmentally benign carbon composite anode material with high-surface area, higher-rate capability and long-term stability,” Naskar said.

“Using waste tires for products such as energy storage is very attractive not only from the carbon materials recovery perspective but also for controlling environmental hazards caused by waste tire stock piles,” Paranthaman added.

Outlined in a paper published in the journal RSC Advances, the ORNL technique uses a proprietary pretreatment to recover pyrolytic carbon black material.


The material is similar to graphite but man-made.

The researchers produced a small, laboratory-scale battery with a reversible capacity that is higher than what is possible with commercial graphite materials.

After 100 cycles, the capacity measures nearly 390 milliamp hours per gram of carbon anode, exceeding the best properties of commercial graphite which researchers say is due to the unique microstructure of the carbon black material.

“This kind of performance is highly encouraging, especially in light of the fact that the global battery market for vehicles and military applications is approaching $78 billion and the materials market is expected to hit $11 billion in 2018,” Paranthaman commented.

Weak spots: Helping to predict injuries before they happen

New research from Washington University in the US may one day be used to prevent injuries after repair surgery on knees, shoulders and other tissues, and could even predict problems before they become an issue.

Using their algorithms, the researchers can identify weak spots in muscles, tendons and bones that are prone to tearing or breaking.

Senior investigator and professor of orthopaedic surgery Stavros Thomopoulos said: “Tendons are constantly stretching as muscles pull on them, and bones also bend or compress as we carry out everyday activities.”

He added: “Small cracks or tears can result from these loads and lead to major injuries. Understanding how these tears and cracks develop over time therefore is important for diagnosing and tracking injuries.”

By stretching tissues and tracking the results as their shapes changed or became distorted, Thomopoulos and the team could visualize and predict spots where tissues are weakened.

John J. Boyle, the paper’s first author and a graduate student in biomedical engineering, explains: “If you imagine stretching Silly Putty or a swimming cap with a picture on it, as you pull, the picture becomes distorted. This allows us to track how the material responds to an external force.”

By combining mechanical engineering with image-analysis techniques, Boyle was able to create the algorithms and then test them in different materials as well as in animal models.

The research showed that one of the two new algorithms is 1,000 times more accurate than older methods at quantifying large stretches near tiny tears and cracks. The second algorithm has the ability to predict where they are likely to form.

Professor of mechanical engineering and co-senior investigator on the study Guy Genin commented: “This extra accuracy is critical for quantifying large strains.

“Commercial algorithms that estimate strain often are much less sensitive, and they are prone to detecting noise that can arise from the algorithm itself rather than from the material being examined.

“The new algorithms can distinguish the noise from true regions of large strains.”


Genin added that, while the current study helps with understanding injury and stress on human tissue, the algorithms could also help engineers to identify vulnerable parts of buildings and other structures. According to Genin, our muscles and bones are influenced by the same strains that affect those structures.

He continued: “Whether it’s a bridge or a tendon, it’s vital to understand the ways that physical forces cause structures and tissues to deform so that we can identify the onset of failures and eventually predict them.”

Current imaging techniques, such as MRI and ultrasound, lack the required clarity and resolution so only once the team can get better images of the body’s tissues, will patients be able to see the new algorithms in action.

The group applied for a provisional patent earlier this year. Their research is available online in the Journal of the Royal Society Interface.