In a study published recently in Advanced Intelligent Systems, researchers from Queen Mary University of London have made significant advancements in the field of bionics with the development of a new type of electric variable-stiffness artificial muscle that possesses self-sensing capabilities. This innovative technology has the potential to revolutionize soft robotics and medical applications.

Muscle contraction hardening is not only essential for enhancing strength but also enables rapid reactions in living organisms. Taking inspiration from nature, the team of researchers at QMUL’s School of Engineering and Materials Science has successfully created an artificial muscle that seamlessly transitions between soft and hard states while also possessing the remarkable ability to sense forces and deformations.

Dr. Ketao Zhang, a Lecturer at Queen Mary and the lead researcher, explains the importance of variable stiffness technology in artificial muscle-like actuators. “Empowering robots, especially those made from flexible materials, with self-sensing capabilities is a pivotal step towards true bionic intelligence,” says Dr. Zhang.

The cutting-edge artificial muscle developed by the researchers exhibits flexibility and stretchability similar to natural muscle, making it ideal for integration into intricate soft robotic systems and adapting to various geometric shapes. With the ability to withstand over 200% stretch along the length direction, this flexible actuator with a striped structure demonstrates exceptional durability.

By applying different voltages, the artificial muscle can rapidly adjust its stiffness, achieving continuous modulation with a stiffness change exceeding 30 times. Its voltage-driven nature provides a significant advantage in terms of response speed over other types of artificial muscles. Additionally, this novel technology can monitor its deformation through resistance changes, eliminating the need for additional sensor arrangements and simplifying control mechanisms while reducing costs.

The fabrication process for this self-sensing artificial muscle is simple and reliable. Carbon nanotubes are mixed with liquid silicone using ultrasonic dispersion technology and coated uniformly using a film applicator to create the thin layered cathode, which also serves as the sensing part of the artificial muscle. The anode is made directly using a soft metal mesh cut, and the actuation layer is sandwiched between the cathode and the anode. After the liquid materials cure, a complete self-sensing variable-stiffness artificial muscle is formed.

The potential applications of this flexible variable stiffness technology are vast, ranging from soft robotics to medical applications. The seamless integration with the human body opens up possibilities for aiding individuals with disabilities or patients in performing essential daily tasks. By integrating the self-sensing artificial muscle, wearable robotic devices can monitor a patient’s activities and provide resistance by adjusting stiffness levels, facilitating muscle function restoration during rehabilitation training.

“While there are still challenges to be addressed before these medical robots can be deployed in clinical settings, this research represents a crucial stride towards human-machine integration,” highlights Dr. Zhang. “It provides a blueprint for the future development of soft and wearable robots.”

The groundbreaking study conducted by researchers at Queen Mary University of London marks a significant milestone in the field of bionics. With their development of self-sensing electric artificial muscles, they have paved the way for advancements in soft robotics and medical applications.

BSD are psychiatric conditions that typically emerge in young adulthood, often severely disrupting lives and requiring intensive treatments. Mania risk has remained challenging for clinicians to predict; the ability to do so would aid in directing treatments to at-risk patients sooner.

The researchers, led by Adriane M. Soehner, PhD, at the University of Pittsburgh, built on previous research showing that heightened reward motivation and sleep-circadian rhythm disruption are associated with mania/hypomania onset. Brain imaging studies have also shown that BSD is associated with elevated reward expectancy activation in the left ventrolateral prefrontal cortex, a key reward- and salience-processing hub.

For the current study, Dr. Soehner and colleagues clustered these markers together; they hypothesized that a signature of increased mania risk would be marked by elevated reward sensitivity, impulsivity, and sleep-circadian characteristics. Young adult participants, who did not have a diagnosis of BSD, completed assessments and underwent functional magnetic resonance imaging. About half the participants also underwent follow-up assessments at six and 12 months.

Three “profiles” emerged from the sample: one healthy, one at moderate risk, and one at high risk. Individuals at high risk had elevated mania symptoms at baseline compared to the other two groups. Over the 12-month follow-up interval, mania symptoms in both the high-risk and moderate-risk groups exceeded the healthy group.

Dr. Soehner said of the findings, “Here, we identified neurobehavioral profiles based on reward sensitivity, impulsivity, and sleep-circadian characteristics that help distinguish those with elevated mania vulnerability. These characteristics, in combination, may help detect mania risk and provide targets to guide and monitor early interventions.”

Cameron Carter, MD, Editor of Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, said of the work, “New findings such as these highlight our emerging ability to combine neurobiological and clinical measures to identify groups of patients at highest risk for serious mental health problems such as mania, allowing for early identification and intervention for those at highest risk. Future research is needed to show that this can lead to reduced suffering and better outcomes in individuals identified in this way.”

“Our newly-devised model stretches the galaxy formation time by a several billion years, making the universe 26.7 billion years old, and not 13.7 as previously estimated,” says author Rajendra Gupta, adjunct professor of physics in the Faculty of Science at the University of Ottawa.

For years, astronomers and physicists have calculated the age of our universe by measuring the time elapsed since the Big Bang and by studying the oldest stars based on the redshift of light coming from distant galaxies. In 2021, thanks to new techniques and advances in technology, the age of our universe was thus estimated at 13.797 billion years using the Lambda-CDM concordance model.

However, many scientists have been puzzled by the existence of stars like the Methuselah that appear to be older than the estimated age of our universe and by the discovery of early galaxies in an advanced state of evolution made possible by the James Webb Space Telescope. These galaxies, existing a mere 300 million years or so after the Big Bang, appear to have a level of maturity and mass typically associated with billions of years of cosmic evolution. Furthermore, they’re surprisingly small in size, adding another layer of mystery to the equation.

Zwicky’s tired light theory proposes that the redshift of light from distant galaxies is due to the gradual loss of energy by photons over vast cosmic distances. However, it was seen to conflict with observations. Yet Gupta found that “by allowing this theory to coexist with the expanding universe, it becomes possible to reinterpret the redshift as a hybrid phenomenon, rather than purely due to expansion.”

In addition to Zwicky’s tired light theory, Gupta introduces the idea of evolving “coupling constants,” as hypothesized by Paul Dirac. Coupling constants are fundamental physical constants that govern the interactions between particles. According to Dirac, these constants might have varied over time. By allowing them to evolve, the timeframe for the formation of early galaxies observed by the Webb telescope at high redshifts can be extended from a few hundred million years to several billion years. This provides a more feasible explanation for the advanced level of development and mass observed in these ancient galaxies.

Moreover, Gupta suggests that the traditional interpretation of the “cosmological constant,” which represents dark energy responsible for the accelerating expansion of the universe, needs revision. Instead, he proposes a constant that accounts for the evolution of the coupling constants. This modification in the cosmological model helps address the puzzle of small galaxy sizes observed in the early universe, allowing for more accurate observations.

Need for safe, flexible bioelectronic devices

Implanted bioelectronic devices are playing a critical role in these treatments, but there are a number of challenges that have stalled their widespread adoption. These devices require specialized components for signal acquisition, processing, data transmission, and powering. Up to now, achieving these capabilities in an implanted device has entailed using numerous rigid and non-biocompatible components that can lead to tissue disruption and patient discomfort. Ideally, these devices need to be biocompatible, flexible, and stable in the long term in the body. They also must be fast and sensitive enough to record rapid, low-amplitude biosignals, while still being able to transmit data for external analysis.

Columbia researchers invent first stand-alone, flexible, fully organic bioelectronic device

Columbia Engineering researchers announced today that they have developed the first stand-alone, conformable, fully organic bioelectronic device that can not only acquire and transmit neurophysiologic brain signals, but can also provide power for device operation. This device, about 100 times smaller than a human hair, is based on an organic transistor architecture that incorporates a vertical channel and a miniaturized water conduit demonstrating long-term stability, high electrical performance, and low-voltage operation to prevent biological tissue damage. The findings are outlined in a new study, published today in Nature Materials.

Both researchers and clinicians knew there was a need for transistors that concurrently pose all of these features: low voltage of operation, biocompatibility, performance stability, conformability for in vivo operation; and high electrical performance, including fast temporal response, high transconductance, and crosstalk-free operation. Silicon-based transistors are the most established technologies, but they are not a perfect solution because they are hard, rigid, and unable to establish a very efficient ion interface with the body. ]

The team addressed these issues by introducing a scalable, self-contained, sub-micron IGT (internal-ion-gated organic electrochemical transistor) architecture, the vIGT. They incorporated a vertical channel arrangement that augments the intrinsic speed of the IGT architecture by optimizing channel geometry and permitting a high density arrangement of transistors next to each other — , 155,000of them per centimeter square.

Scalable vGITs are the fastest electrochemical transistors

The vIGTs are composed of biocompatible, commercially available materials that do not require encapsulation in biological environments and are not impaired by exposure to water or ions. The composite material of the channel can be reproducibly manufactured in large quantities and is solution-processible, making it more accessible to a broad range of fabrication processes. They are flexible and compatible with integration into a wide variety of conformable plastic substrates and have long-term stability, low inter-transistor crosstalk, and high-density integration capacity, allowing fabrication of efficient integrated circuits.

“Organic electronics are not known for their high performance and reliability,” said the study’s leader Dion Khodagholy, associate professor of electrical engineering. “But with our new vGIT architecture, we were able to incorporate a vertical channel that has its own supply of ions. This self-sufficiency of ions made the transistor to be particularly fast — in fact, they are currently the fastest electrochemical transistors.”

To push the speed of operation even further, the team used advanced nanofabrication techniques to miniaturize and densify these transistors at submicro-meter scales. Fabrication took place in the cleanroom of the Columbia Nano Initiative.

Collaborating with CUIMC clinicians

To develop the architecture, the researchers first needed to understand the challenges involved with diagnosis and treatment of patients with neurological disorders like epilepsy, as well as the methodologies currently used. They worked with colleagues at the Department of Neurology at Columbia University Irving Medical Center, in particular, with Jennifer Gelinas, assistant professor of neurology, electrical and biomedical engineering and director of the Epilepsy and Cognition Lab.

The combination of high-speed, flexibility. and low-voltage operation enables the transistors to not only be used for neural signal recording but also for data transmission as well as powering the device, leading to a fully conformable implant. The researchers used this feature to demonstrate fully soft and confirmable implants capable of recording and transmitting high resolution neural activity from both outside, on the surface of the brain, as well as inside, deep within the brain.

“This work will potentially open a wide range of translational opportunities and make medical implants accessible to a large patient demographic who are traditionally not qualified for implantable devices due to the complexity and high risks of such procedures,” said Gelinas.

“It’s amazing to think that our research and devices could help physicians with better diagnostics and could have a positive impact on patients’ quality of life,” added the study’s lead author Claudia Cea, who recently completed her PhD and will be a postdoctoral fellow at MIT this fall.

Next steps

The researchers plan next to join forces with neurosurgeons at CUIMC to validate the capabilities of vIGT-based implants in operating rooms. The team expects to develop soft and safe implants that can detect and identify various pathological brain waves caused by neurological disorders.

A research team from the Department of Energy’s Pacific Northwest National Laboratory reports that the flow battery, a design optimized for electrical grid energy storage, maintained its capacity to store and release energy for more than a year of continuous charge and discharge.

The study, just published in the journal Joule, details the first use of a dissolved simple sugar called β-cyclodextrin, a derivative of starch, to boost battery longevity and capacity. In a series of experiments, the scientists optimized the ratio of chemicals in the system until it achieved 60 percent more peak power. Then they cycled the battery over and over for more than a year, only stopping the experiment when the plastic tubing failed. During all that time, the flow battery barely lost any of its activity to recharge. This is the first laboratory-scale flow battery experiment to report more than a year of continuous use with minimal loss of capacity.

The β-cyclodextrin additive is also the first to speed the electrochemical reaction that stores and then releases the flow battery energy, in a process called homogeneous catalysis. This means the sugar does its work while dissolved in solution, rather than as a solid applied to a surface.

“This is a brand new approach to developing flow battery electrolyte,” said Wei Wang, a long-time PNNL battery researcher and the principal investigator of the study. “We showed that you can use a totally different type of catalyst designed to accelerate the energy conversion. And further, because it is dissolved in the liquid electrolyte it eliminates the possibility of a solid dislodging and fouling the system.”

What is a flow battery?

As their name suggests, flow batteries consist of two chambers, each filled with a different liquid. The batteries charge through an electrochemical reaction and store energy in chemical bonds. When connected to an external circuit, they release that energy, which can power electrical devices. Flow batteries differ from solid-state batteries in that they have two external supply tanks of liquid constantly circulating through them to supply the electrolyte, which is like the “blood supply” for the system. The larger the electrolyte supply tank, the more energy the flow battery can store.

If they are scaled up to the size of a football field or more, flow batteries can serve as backup generators for the electric grid. Flow batteries are one of the key pillars of a decarbonization strategy to store energy from renewable energy resources. Their advantage is that they can be built at any scale, from the lab-bench scale, as in the PNNL study, to the size of a city block.

Why do we need new kinds of flow batteries?

Large-scale energy storage provides a kind of insurance policy against disruption to our electrical grid. When severe weather or high demand hobble the ability to supply electricity to homes and businesses, energy stored in large-scale flow battery facilities can help minimize disruption or restore service. The need for these flow battery facilities is only expected to grow, as electricity generation increasingly comes from renewable energy sources, such as wind, solar and hydroelectric power. Intermittent power sources such as these require a place to store energy until it’s needed to meet consumer demand.

While there are many flow battery designs and some commercial installations, existing commercial facilities rely on mined minerals such as vanadium that are costly and difficult to obtain. That’s why research teams are seeking effective alternative technologies that use more common materials that are easily synthesized, stable and non-toxic.

“We cannot always dig the Earth for new materials,” said Imre Gyuk, director of energy storage research at DOE’s Office of Electricity. “We need to develop a sustainable approach with chemicals that we can synthesize in large amounts — just like the pharmaceutical and the food industries.”

The work on flow batteries is part of a large program at PNNL to develop and test new technologies for grid-scale energy storage that will be accelerated with the opening of PNNL’s Grid Storage Launchpad in 2024.

A benign ‘sugar water’ sweetens the pot for an effective flow battery

The PNNL research team that developed this new battery design includes researchers with backgrounds in organic and chemical synthesis. These skills came in handy when the team chose to work with materials that had not been used for battery research, but which are already produced for other industrial uses.

“We were looking for a simple way to dissolve more fluorenol in our water-based electrolyte,” said Ruozhu Feng, the first author of the new study. “The β-cyclodextrin helped do that, modestly, but it’s real benefit was this surprising catalytic ability.”

The researchers then worked with co-author Sharon Hammes-Schiffer of Yale University, a leading authority on the chemical reaction underlying the catalytic boost, to explain how it works.

As described in the research study, the sugar additive accepts positively charged protons, which helps balance out the movement of negative electrons as the battery discharges. The details are a bit more complicated, but it’s like the sugar sweetens the pot to allow the other chemicals to complete their chemical dance.

The study is the next generation of a PNNL-patented flow battery design first described in the journal Science in 2021. There, the researchers showed that another common chemical, called fluorenone, is an effective flow battery component. But that initial breakthrough needed improvement because the process was slow compared with commercialized flow battery technology. This new advance makes the battery design a candidate for scale up, the researchers say.

At the same time, the research team is working to further improve the system by experimenting with other compounds that are similar to β-cyclodextrin but smaller. Like honey, β-cyclodextrin addition also makes the liquid thicker, which is less than ideal for a flowing system. Nonetheless, the researchers found its benefits outweighed its drawbacks.

Understanding the complex chemistry happening inside the new flow battery design required the expertise of many scientists, including Ying Chen, Xin Zhang, Peiyuan Gao, Ping Chen, Sebastian Mergelsberg, Lirong Zhong, Aaron Hollas, Yangang Lian, Vijayakumar Murugesan, Qian Huang, Eric Walter and Yuyan Shao of PNNL, and Benjamin J. G. Rousseau and Hammes-Schiffer of Yale, in addition to Feng and Wang.