ROBOTICS
Autonomous realignment and self-healing in multilayer soft electronic devices
By combining two dynamic polymers, researchers present a new method for achieving autonomous realignment and self-healing in multilayered soft electronic devices and robots, according to a new study. Like human skin, self-healing polymers allow soft electronic and robotic devices to recover autonomously from various forms of damage. Such devices are often multilayered and embedded with conductive or dielectric materials to achieve functional properties while also maintaining the soft mechanical properties of the self-healing polymer matrix. However, self-healing devices often require manual realignment of individual layers after damage to properly align different functional components within the polymer, as even slightly misaligned layers can limit the functional recovery of a device. Achieving autonomous realignment and self-healing in complex, multilayered soft devices has remained a challenge. Here, Christopher Cooper and colleagues demonstrate an autonomous self-healing of multilayered soft electronic devices by combining two orthogonal self-healing polymers with identical dynamic hydrogen-bonding interactions but with immiscible polymer backbones. According to Cooper et al., composition gradients between the two polymers enable interlayer adhesion between the otherwise immiscible layers while enabling self-recognition and healing of different functional layers. To test the design, the authors fabricated thin film devices with conductive, dielectric, and magnetic particles and demonstrate their ability to functionally self-heal after mechanical damage to 96% of their initial capacitance. What’s more, Cooper et al. showed that the approach could also be used to magnetically guide the self-assembly of soft robots and underwater circuits.
JOURNAL
Science
ARTICLE TITLE
Autonomous alignment and healing in multilayer soft electronics using immiscible dynamic polymers
ARTICLE PUBLICATION DATE
2-Jun-2023
Layers of self-healing electronic skin realign autonomously when cut
The advance presages a new era of robots and prosthetics wrapped in self-healing synthetic materials imbued with human-like sense of touch
Peer-Reviewed Publicationby Andrew Myers
Human skin is amazing. It senses temperature, pressure, and texture. It’s able to stretch and spring back, time and again. And it provides a barrier between the body and bad things in the world—bacteria, viruses, toxins, ultraviolet radiation and more. Engineers are, accordingly, keen to create synthetic skin. They imagine robots and prosthetic limbs that have skin-like qualities—not the least of which is skin’s remarkable ability to heal.
“We’ve achieved what we believe to be the first demonstration of a multi-layer, thin film sensor that automatically realigns during healing. This is a critical step toward mimicking human skin, which has multiple layers that all re-assemble correctly during the healing process,” said Chris Cooper, a Ph.D. candidate at Stanford University who, along with postdoctoral researcher Sam Root, is co-author of a new study in Science announcing the advance.
Layering is critical to mimicking skin’s many qualities. “It is soft and stretchable. But if you puncture it, slice it, or cut it— each layer will selectively heal with itself to restore the overall function,” Root says. “Just like real skin.”
Skin, too, is formed of layers. It has just evolved immune mechanisms that rebuild the tissue with the original layered structure through a complex process involving molecular recognition and signaling.
“With true ‘skin’ the layers should realign naturally and autonomously,” Cooper says.
Root says the team, led by Professor Zhenan Bao at Stanford University, might be able to create multi-tiered synthetic skin with individually functional layers as thin as a micron each, perhaps less. Thin enough that a stack of 10 or more layers would be no thicker than a sheet of paper. “One layer might sense pressure, another temperature, and yet another tension,” says Root. The material of different layers can be engineered to sense thermal, mechanical, or electrical changes.
A Novel Approach
“We reported the first multi-layer self-healing synthetic electronic skin in 2012 in Nature Nanotechnology,” says Bao. “There has been a lot of interest around the world in pursuing multi-layer synthetic skin since then.” What sets their current work apart is that the layers self-recognize and align with like layers during the healing process, restoring functionality layer by layer as they heal. Existing self-healing synthetic skins must be realigned manually—by humans. Even a slight misalignment in layers might compromise functional recovery.
The secret is in the materials. The backbone of each layer is formed of long molecular chains connected periodically by dynamic hydrogen bonds, similar to those holding the double-helix of DNA strands together, that allow the material to stretch repeatedly without tearing. Rubber and latex are two well-known natural polymers, but there are countless synthetic polymers, too. The key is to design polymer molecular structures and choose the right combination for each layer—first layer of one polymer, the second of another and so forth.
The researchers used PPG (polypropylene glycol) and PDMS (polydimethylsiloxane, better known as silicone). Both have rubber-like electrical and mechanical properties and biocompatibility and can be mixed with nano- or microparticles to enable electric conductivity. Critically, the chosen polymers and their respective composites are immiscible — they do not mix with one another yet, due to the hydrogen bonding, they adhere to one another well to create a durable, multilayer material.
Both polymers have the advantage that when warmed they soften and flow, but solidify as they cool. Thus, by warming the synthetic skin, the researchers were able to speed the healing process. At room temperature, healing can take as long as a week, but when heated to just 70°C (158°F), the self-alignment and healing happen in about 24 hours. The two materials were carefully designed to have similar viscous and elastic responses to external stress over an appropriate temperature range.
“Skin is slow to heal, too. I cut my finger the other day and it was still healing four or five days later,” Cooper says. “For us, the most important part is that it heals to recover functions without our input or effort.”
A Step Further
With a successful prototype, the researchers then took things a step further, working with Professor Renee Zhao at Stanford University, adding magnetic materials to their polymer layers, allowing the synthetic skin to not only heal but also to self-assemble from separate pieces. “Combining with magnetic field-guided navigation and induction heating,” says Zhao, “we may be able to build reconfigurable soft robots that can change shape and sense their deformation on demand.” (Watch the video.)
“Our long-term vision is to create devices that can recover from extreme damage. For example, imagine a device that when torn into pieces and ripped apart, could reconstruct itself autonomously,” Cooper says, showing a short video of several pieces of stratified synthetic skin immersed in water. Drawn together magnetically, the pieces inch toward one another, eventually reassembling. As they heal, their electrical conductivity returns, and an LED attached atop the material glows to prove it.
Among their next steps, the researchers will work to make the layers as thin as possible and toward creating layers of varying function. The current prototype was engineered to sense pressure, and additional layers engineered to sense changes in temperature or strain could be included.
In terms of future vision, the team imagines, potentially, robots that could be swallowed in pieces and then self-assemble inside the body to perform non-invasive medical treatments. Other applications include multi-sensory, self-healing electronic skins that form-fit to robots and provide them with a sense of touch.
Ph.D. Candidate Christopher B. Cooper and postdoctoral scholar Samuel E. Root are members of the Bao Group and co-lead authors of this research. Other Stanford co-authors include postdoctoral scholar Lukas Michalek; graduate student Shuai Wu; postdoctoral scholar Jian-Cheng Lai; postdoctoral scholar Muhammad Khatib; Ph.D. Candidate Solomon T. Oyakhire; Renee Zhao, Assistant Professor of Mechanical Engineering and, by courtesy, of Materials Science and Engineering; Jian Qin, Assistant Professor of Chemical Engineering; and Zhenan Bao, K. K. Lee Professor and Professor, by courtesy, of Materials Science and Engineering and of Chemistry. Bao, Qin, & Zhao are members of Stanford Bio-X and the Wu Tsai Neurosciences Institute. Bao and Zhao are also members of the Stanford Cardiovascular Institute and the Wu Tsai Human Performance Alliance. Bao is also a member of the Maternal & Child Health Research Institute (MCHRI), an affiliate of the Precourt Institute for Energy and the Stanford Woods Institute for the Environment, and faculty fellow of Sarafan ChEM-H.
This work was supported by Army Research Office Materials Design Program; National Science Foundation; Department of Defense, National Defense Science & Engineering Graduate Fellowship Program; Walter Benjamin Fellowship Program, Deutsche Forschungsgemeinschaft; and TomKat Center Fellowship for Translational Research at Stanford University. Part of this work was performed at the Stanford Nano Shared Facilities, supported by the National Science Foundation. Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, for SAXS experiments was supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences. This work used Expanse computing resources at the San Diego Supercomputer Center through allocation MAT220035 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support program, which is supported by National Science Foundation grants.
The eWEAR-TCCI awards for science writing is a project commissioned by the Wearable Electronics Initiative (eWEAR) at Stanford University and made possible by funding through eWEAR industrial affiliates program member Shanda Group and the Tianqiao and Chrissy Chen Institute (TCCI®).
Pieces of synthetic skin are drawn together magnetically; electrical conductivity returns as they heal, and the LED lights.
CREDIT
Bao Group, Stanford U.
JOURNAL
Science
METHOD OF RESEARCH
Experimental study
SUBJECT OF RESEARCH
Not applicable
ARTICLE TITLE
Autonomous alignment and healing in multilayer soft electronics using immiscible dynamic polymers
ARTICLE PUBLICATION DATE
2-Jun-2023
Newborn baby inspires sensor design that simulates human touch
Researchers find potential key to high-sensitivity, broad-range sensors after inventing device to measure baby’s weight
Peer-Reviewed PublicationUNIVERSITY PARK, Pa. — As we move into a world where human-machine interactions are becoming more prominent, pressure sensors that are able to analyze and simulate human touch are likely to grow in demand.
One challenge facing engineers is the difficulty in making the kind of cost-effective, highly sensitive sensor necessary for applications such as detecting subtle pulses, operating robotic limbs, and creating ultrahigh-resolution scales. However, a team of researchers has developed a sensor capable of performing all of those tasks.
The researchers, from Penn State and Hebei University of Technology in China, wanted to create a sensor that was extremely sensitive and reliably linear over a broad range of applications, had high pressure resolution, and was able to work under large pressure preloads.
“The sensor can detect a tiny pressure when large pressure is already applied,” said Huanyu “Larry” Cheng, James L. Henderson Jr. Memorial Associate Professor of Engineering Science and Mechanics at Penn State and co-author of a paper on the work published in Nature Communications. “An analogy I like to use is it’s like detecting a fly on top of an elephant. It can measure the slightest change in pressure, just like our skin does with touch.”
Cheng was inspired to develop these sensors due to a very personal experience: The birth of his second daughter.
Cheng’s daughter lost 10% of her body weight soon after birth, so the doctor asked him to weigh the baby every two days to monitor any additional loss or weight gain. Cheng tried to do this by weighing himself on a regular home weight scale and then weighing himself holding his daughter to measure the baby’s weight.
"I noticed that when I put down my daughter in her blanket, when I was no longer holding her, you didn’t see the change in weight,” Cheng said. “So, we learned that trying to use a commercial scale doesn't work, it didn’t detect the change in pressure.”
After trying many different approaches, they found that using a pressure sensor consisting of gradient micro-pyramidal structures and an ultrathin ionic layer to give a capacitive response was the most promising.
However, there was a continued issue they faced. The high sensitivity of the microstructures would decrease as the pressure increased, and the random microstructures that were templated from natural objects resulted in uncontrollable deformation and a narrow linear range. In simple terms, when pressure was applied to the sensor, it would change the sensor’s shape and therefore alter the contact area between the microstructures and throw off the readings.
To address these challenges, the scientists designed microstructure patterns that could increase the linear range without decreasing the sensitivity — they essentially made it flexible, so it could still function in the gradience of pressures that exist in the real world. Their study explored the use of a CO2 laser with a Gaussian beam to fabricate programmable structures such as gradient pyramidal microstructures (GPM) for iontronic sensors, which are soft electronics that can mimic the perception functions of human skin. This process reduces the cost and process complexity compared with photolithography, the method commonly used to prepare delicate microstructure patterns for sensors.
Cheng credits Ruoxi Yang, a graduate student in his lab and first author of the study, as the driver of this solution.
"Yang is a very smart student who introduced the idea to solve this sensor issue, which is really something like a combination of many small pieces, smartly engineered together,” Cheng said. “We know the structure must be microscale and must have a delicate design. But it is challenging to design or optimize the structure, and she worked with the laser system we have in our lab to make this possible. She has been working very hard in the past few years and was able to explore all these different parameters and be able to quickly screen throughout this parameter space to find and improve the performance.”
This optimized sensor had rapid response and recovery times and excellent repeatability, which the team tested by detecting subtle pulses, operating interactive robotic hands, and creating ultrahigh-resolution, smart weight scales and chairs. The scientists also found that the proposed fabrication approaches and design toolkit from this work could be leveraged to easily tune the pressure sensor performance for varying target applications and open opportunities to create other iontronic sensors, the range of sensors that use ionic liquids such as an ultrathin ionic layer. Along with enabling a future scale where it would be easier for parents to weigh their baby, these sensors would have other uses as well.
“We were also able to detect not only the pulse from the wrist but also from the other distal vascular structures like the eyebrow and the fingertip,” Cheng said. “In addition, we combine that with the control system to show that this is possible to use for the future of human robotic interactional collaboration. Also, we envision other healthcare uses, such as someone who has lost a limb and this sensor could be part of a system to help them control a robotic limb.”
Cheng noted other potential uses, such as sensors to measure a person’s pulse during high-stress work situations such as search-and-rescue after an earthquake or carrying out difficult, dangerous tasks in a construction site.
The research team used computer simulations and computer-aided design to help them explore ideas for these novel sensors, which Cheng notes is challenging work given all the possible sensor solutions. This electronic assistance will continue to push the research forward.
“I think in the future it is possible to further improve the model and be able to account for more complex systems and then we can certainly understand how to make even better sensors,” Cheng said.
Aside from Cheng and Yang, other authors on the study from Penn State include Ankan Dutta, Bowen Li, Naveen Tiwari, Wanqing Zhang, Zhenyuan Niu, Yuyan Gao, Daniel Erdely and Xin Xin, and from Hebei University, Tiejun Li.
JOURNAL
Nature Communications
METHOD OF RESEARCH
Experimental study
SUBJECT OF RESEARCH
Not applicable
ARTICLE TITLE
Iontronic pressure sensor with high sensitivity over ultra-broad linear range enabled by laser-induced gradient micro-pyramids
ARTICLE PUBLICATION DATE
1-Jun-2023
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