Tag Archives: polydimethylsiloxane (PDMS)

Precise knee motion tracking in wearable device with boron nitride nanotubes

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A July 2, 2025 news item on Nanowerk announces research that employs boron nitride nanotubes in a device for monitoring joint health, Note: Links have been removed,

A research team from the University of Oxford and University College London has developed a wearable device that can track joint torque with precision, potentially transforming the way clinicians and patients monitor joint health.

Reported in Nano-Micro Letters (“AI-Enabled Piezoelectric Wearable for Joint Torque Monitoring”), the new technology integrates advanced materials and artificial intelligence to provide real-time data from everyday movements.

The device relies on boron nitride nanotubes (BNNTs) embedded in a soft polymer called polydimethylsiloxane (PDMS). These nanotubes possess exceptional mechanical strength and piezoelectric properties, meaning they generate electrical signals in response to movement or pressure. When worn on the knee, the composite material responds to joint motion by producing signals that can be interpreted to measure torque—the rotational force exerted on the joint.

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Caption: Artificial intelligence-enabled wearable device with boron nitride nanotubes (BNNTs)-based piezoelectric film for accurate joint torque sensing. Inverse-designed structure optimizes biomechanical compatibility for enhanced knee motion tracking. High-sensitivity BNNTs/polydimethylsiloxane composite enables precise and dynamic knee motion signal detection. Lightweight neural network processes complex signals for accurate torque, angle, and load estimation. Real-time monitoring system provides instant knee torque assessment for daily use. Credit: Jinke Chang, Jinchen Li, Jiahao Ye, Bowen Zhang, Jianan Chen, Yunjia Xia, Jingyu Lei, Tom Carlson, Rui Loureiro, Alexander M. Korsunsky, Jin-Chong Tan, Hubin Zhao.

A July 7, 2025 Shanghai Jiao Tong University Journal Center press release on EurekAlert provides information about the research in bullet point form,

In the pursuit of more effective and accessible solutions for joint health monitoring, researchers are constantly seeking innovative ways to enhance the capabilities of wearable devices. A recent article published in Nano-Micro Letters, authored by Professor Jin-Chong Tan and Professor Hubin Zhao from the University of Oxford and University College London, presents a groundbreaking AI-enabled piezoelectric wearable device for accurate joint torque sensing, leveraging the unique properties of boron nitride nanotubes (BNNTs).

Why This Research Matters

  • Enhanced Joint Health Monitoring: Traditional methods for assessing joint torque are often confined to laboratory settings or require complex setups, limiting their feasibility for real-world applications. This new wearable device offers a portable, non-invasive solution for continuous joint torque monitoring, crucial for evaluating joint health, guiding interventions, and monitoring rehabilitation progress.
  • High Sensitivity and Accuracy: The device’s high-sensitivity BNNTs/polydimethylsiloxane composite enables precise and dynamic knee motion signal detection, while the lightweight neural network processes complex signals for accurate torque, angle, and load estimation, providing reliable data for joint health assessment.
  • Low-Cost and Accessible Solution: The compatibility of the materials and design with low-power, resource-limited settings makes this wearable device a cost-effective and accessible solution for diverse populations across regions with varying levels of development, potentially revolutionizing joint health monitoring on a global scale.

Innovative Design and Mechanisms

  • Boron Nitride Nanotubes and Polydimethylsiloxane: BNNTs are highlighted as ideal materials for constructing high-performance piezoelectric sensors due to their exceptional mechanical strength, thermal stability, and intrinsic piezoelectric properties. The uniform dispersion of BNNTs in a PDMS matrix results in a highly sensitive piezoelectric film capable of capturing complex knee motion signals.
  • Inverse Design Structure: The wearable device employs an inverse-designed structure with a negative Poisson’s ratio, precisely matched to the biomechanics of the knee joint. This unique design ensures optimal biomechanical compatibility, enhancing motion tracking fidelity and enabling detailed sensing of complex loading conditions during knee movements.
  • Artificial Intelligence Integration: The integration of a lightweight on-device artificial neural network allows for real-time processing and analysis of the complex piezoelectric signals generated during movement. The AI algorithm accurately extracts targeted signals and maps them to corresponding physical characteristics, such as torque, angle, and loading, providing valuable insights into joint health.

Applications and Future Outlook

  • Joint Health Monitoring: This wearable device can continuously monitor joint torque, offering valuable data for the evaluation of joint health and early detection of potential issues. It can be particularly beneficial for individuals with musculoskeletal conditions, the elderly, and athletes, enabling timely interventions and personalized rehabilitation plans.
  • Rehabilitation and Injury Prevention: By providing real-time torque assessment and risk assessment of joint injury, the device can play a crucial role in rehabilitation programs, ensuring safe and effective recovery. It can also help in preventing injuries by alerting users to potentially harmful joint movements or excessive torque.
  • Future Research Directions: Future research should focus on further optimizing the sensing materials, device design, and AI algorithms to enhance the performance, accuracy, and adaptability of the wearable device. Exploring additional complementary modalities and integrating the device with wearable robotics or exoskeletons could further expand its applications and utility in various fields.

This innovative AI-enabled piezoelectric wearable device represents a significant step forward in joint health monitoring, offering a low-cost, high-sensitivity solution with broad potential applications. Stay tuned for more groundbreaking research from Professor Jin-Chong Tan and Professor Hubin Zhao’s team as they continue to push the boundaries of wearable technology and contribute to improved joint health and rehabilitation outcomes.

Here’s a link to and a citation for the paper,

AI-Enabled Piezoelectric Wearable for Joint Torque Monitoring by Jinke Chang, Jinchen Li, Jiahao Ye, Bowen Zhang, Jianan Chen, Yunjia Xia, Jingyu Lei, Tom Carlson, Rui Loureiro, Alexander M. Korsunsky, Jin-Chong Tan & Hubin Zhao. Nano-Micro Lett. 17, 247 (2025) DOI: https://doi.org/10.1007/s40820-025-01753-w Published: 03 May 2025

This paper is open access.

Reducing microplastic pollution from when you wash your clothes with a new coating

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A January 26, 2023 University of Toronto news release (also found on EurekAlert and here but published on January 30, 2023) by Safa Jinje announced a coating the minimizes the amount of microplastic entering the water when your clothes are washed, Note: Links have been removed,

A team of University of Toronto Engineering researchers, led by Professor Kevin Golovin, have designed a solution to reduce the amount of microplastic fibres that are shed when clothes made of synthetic fabrics are washed.   

In a world swamped by fast fashion — an industry that produces a high-volume of cheaply made clothing at an immense cost to the environment — more than two-thirds of clothes are now made of synthetic fabrics. 

When clothes made from synthetic fabrics, such as nylon, polyester, acrylic and rayon, are washed in washing machines, the friction caused by cleaning cycles produces tiny tears in the fabric. These tears in turn cause microplastic fibres measuring less than 500 micrometres in length to break off and make their way down laundry drains to enter waterways.   

Once microplastics end up in oceans and freshwater lakes and rivers, the particles are difficult to remove and will take decades or more to fully break down. The accumulation of this debris in bodies of water can threaten marine life. It can also become part of the human food chain through its presence in food and tap water, with effects on human health that are not yet clear.  

Governments around the world have been looking for ways to minimize the pollution that comes from washing synthetic fabrics. One example is washing machine filters, which have emerged as a leading fix to stop microplastic fibres from entering waterways. In Ontario, legislative members have introduced a bill that would require filters in new washing machines in the province.  

“And yet, when we look at what governments around the world are doing, there is no trend towards preventing the creation of microplastic fibres in the first place,” says Golovin.  

“Our research is pushing in a different direction, where we actually solve the problem rather than putting a Band-Aid on the issue.”   

Golovin and his team have created a two-layer coating made of polydimethylsiloxane (PDMS) brushes, which are linear, single polymer chains grown from a substrate to form a nanoscale surface layer.  

Experiments conducted by the team showed that this coating can significantly reduce microfibre shedding of nylon clothing after repeated laundering. The researchers share their findings in a new paper published in Nature Sustainability. 

“My lab has been working with this coating on other surfaces, including glass and metals, for a few years now,” says Golovin. “One of the properties we have observed is that it is quite slippery, meaning it has very low friction.” 

PDMS is a silicon-based organic polymer that is found in many household products. Its presence in shampoos makes hair shiny and slippery. It is also used as a food additive in oils to prevent liquids from foaming when bottled. 

Dr. Sudip Kumar Lahiri, a postdoctoral researcher in Golovin’s lab and lead author of the study, had the idea that if they could reduce the friction that occurs during wash cycles with a PDMS-based fabric finish, then that could stop fibres from rubbing together and breaking off during laundering.  

One of the biggest challenges the researchers faced during their study was ensuring the PDMS brushes stayed on the fabric. Lahiri, who is a textile engineer by trade, developed a molecular primer based on his understanding of fabric dyes.  

Lahiri reasoned that the type of bonding responsible for keeping dyed apparel colourful after repeated washes could work for the PDMS coating as well.  

Neither the primer nor the PDMS brushes work separately to decrease the microplastic-fibre shedding. But together, they created a strong finish that reduced the release of microfibres by more than 90% after nine washes.  

“PDMS brushes are environmentally friendly because they are not derived from petroleum like many polymers used today,” says Golovin, who was awarded a Connaught New Researcher award for this work.  

“With the addition of Sudip’s primer, our coating is robust enough to remain on the garment and continue to reduce micro-fibre shedding over time.”  

Since PDMS is naturally a hydrophobic (water-repellent) material, the researchers are currently working on making the coating hydrophilic, so that coated fabrics will be better able to wick away sweat. The team has also expanded the research to look beyond nylon fabrics, including polyester and synthetic-fabric blends.  

“Many textiles are made of multiple types of fibres,” says Golovin. “We are working to formulate the correct polymer architecture so that our coating can durably adhere to all of those fibres simultaneously.” 

Here’s a link to and a citation for the paper,

Polydimethylsiloxane-coated textiles with minimized microplastic pollution by Sudip Kumar Lahiri, Zahra Azimi Dijvejin & Kevin Golovin. Nature Sustainability (2023) DOI: https://doi.org/10.1038/s41893-022-01059-4 Published: 26 January 2023

This paper is behind a paywall.