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A team of engineers, dentists, and biologists from the University of Pennsylvania developed a microscopic robotic cleaning crew. With two types of robotic systems -- one designed to work on surfaces and the other to operate inside confined spaces -- the scientists showed that robots with catalytic activity could ably destroy biofilms, sticky amalgamations of bacteria enmeshed in a protective scaffolding. Such robotic biofilm-removal systems could be valuable in a wide range of potential applications, from keeping water pipes and catheters clean to reducing the risk of tooth decay, endodontic infections, and implant contamination.

The work, published in Science Robotics, was led by Hyun (Michel) Koo of the School of Dental Medicine and Edward Steager of the School of Engineering and Applied Science.

"This was a truly synergistic and multidisciplinary interaction," says Koo. "We're leveraging the expertise of microbiologists and clinician-scientists as well as engineers to design the best microbial eradication system possible. This is important to other biomedical fields facing drug-resistant biofilms as we approach a post-antibiotic era."

"Treating biofilms that occur on teeth requires a great deal of manual labor, both on the part of the consumer and the professional," adds Steager. "We hope to improve treatment options as well as reduce the difficulty of care."

Biofilms can arise on biological surfaces, such as on a tooth or in a joint or on objects, like water pipes, implants, or catheters. Wherever biofilms form, they are notoriously difficult to remove, as the sticky matrix that holds the bacteria provides protection from antimicrobial agents.

In previous work, Koo and colleagues have made headway at breaking down the biofilm matrix with a variety of outside-the-box methods. One strategy has been to employ iron-oxide-containing nanoparticles that work catalytically, activating hydrogen peroxide to release free radicals that can kill bacteria and destroy biofilms in a targeted fashion.

Serendipitously, the Penn Dental Medicine team found that groups at Penn Engineering led by Steager, Vijay Kumar, and Kathleen Stebe were working with a robotic platform that used very similar iron-oxide nanoparticles as building blocks for microrobots. The engineers control the movement of these robots using a magnetic field, allowing a tether-free way to steer them.

Together, the cross-school team designed, optimized, and tested two types of robotic systems, which the group calls catalytic antimicrobial robots, or CARs, capable of degrading and removing biofilms. The first involves suspending iron-oxide nanoparticles in a solution, which can then be directed by magnets to remove biofilms on a surface in a plow-like manner. The second platform entails embedding the nanoparticles into gel molds in three-dimensional shapes. These were used to target and destroy biofilms clogging enclosed tubes.

Both types of CARs effectively killed bacteria, broke down the matrix that surrounds them, and removed the debris with high precision. After testing the robots on biofilms growing on either a flat glass surface or enclosed glass tubes, the researchers tried out a more clinically relevant application: Removing biofilm from hard-to-reach parts of a human tooth.

The CARs were able to degrade and remove bacterial biofilms not just from a tooth surface but from one of the most difficult-to-access parts of a tooth, the isthmus, a narrow corridor between root canals where biofilms commonly grow.

"Existing treatments for biofilms are ineffective because they are incapabale of simultaneously degrading the protective matrix, killing the embedded bacteria, and physically removing the biodegraded products," says Koo. "These robots can do all three at once very effectively, leaving no trace of biofilm whatsoever."

By plowing away the degraded remains of the biofilm, Koo says, the chance of it taking hold and re-growing decreases substantially. The researchers envision precisely directing these robots to wherever they need to go to remove biofilms, be it the inside of a cathether or a water line or difficult-to-reach tooth surfaces.

"We think about robots as automated systems that take actions based on actively gathered information," says Steager. In this case, he says, "the motion of the robot can be informed by images of the biofilm gathered from microcameras or other modes of medical imaging."

To move the innovation down the road to clinical application, the researchers are receiving support from the Penn Center for Health, Devices, and Technology, an initiative supported by Penn's Perelman School of Medicine, Penn Engineering, and the Office of the Vice Provost for Research. Penn Health-Tech, as it's known, awards select interdisciplinary groups with support to create new health technologies, and the robotic platforms project was one of those awarded support in 2018.

"The team has a great clinical background on the dental side and a great technical background on the engineering side," says Victoria Berenholz, executive director of Penn Health-Tech. "We're here to round them out on the business side. They have really done a fantastic job on the project."

Purdue University researchers and experts in brain-inspired computing think part of the answer may be found in magnets. The researchers have developed a process to use magnetics with brain-like networks to program and teach devices such as personal robots, self-driving cars and drones to better generalize about different objects.

"Our stochastic neural networks try to mimic certain activities of the human brain and compute through a connection of neurons and synapses," said Kaushik Roy, Purdue's Edward G. Tiedemann Jr. Distinguished Professor of Electrical and Computer Engineering. "This allows the computer brain to not only store information but also to generalize well about objects and then make inferences to perform better at distinguishing between objects."

Roy presented the technology during the annual German Physical Sciences Conference earlier this month in Germany. The work also appeared in the Frontiers in Neuroscience.

The switching dynamics of a nano-magnet are similar to the electrical dynamics of neurons. Magnetic tunnel junction devices show switching behavior, which is stochastic in nature.

The stochastic switching behavior is representative of a sigmoid switching behavior of a neuron. Such magnetic tunnel junctions can be also used to store synaptic weights.

The Purdue group proposed a new stochastic training algorithm for synapses using spike timing dependent plasticity (STDP), termed Stochastic-STDP, which has been experimentally observed in the rat's hippocampus. The inherent stochastic behavior of the magnet was used to switch the magnetization states stochastically based on the proposed algorithm for learning different object representations.

The trained synaptic weights, encoded deterministically in the magnetization state of the nano-magnets, are then used during inference. Advantageously, use of high-energy barrier magnets (30-40KT where K is the Boltzmann constant and T is the operating temperature) not only allows compact stochastic primitives, but also enables the same device to be used as a stable memory element meeting the data retention requirement. However, the barrier height of the nano-magnets used to perform sigmoid-like neuronal computations can be lowered to 20KT for higher energy efficiency.

"The big advantage with the magnet technology we have developed is that it is very energy-efficient," said Roy, who leads Purdue's Center for Brain-inspired Computing Enabling Autonomous Intelligence. "We have created a simpler network that represents the neurons and synapses while compressing the amount of memory and energy needed to perform functions similar to brain computations."

Roy said the brain-like networks have other uses in solving difficult problems as well, including combinatorial optimization problems such as the traveling salesman problem and graph coloring. The proposed stochastic devices can act as "natural annealer," helping the algorithms move out of local minimas.

Their work aligns with Purdue's Giant Leaps celebration, acknowledging the university's global advancements in artificial intelligence as part of Purdue's 150th anniversary. It is one of the four themes of the yearlong celebration's Ideas Festival, designed to showcase Purdue as an intellectual center solving real-world issues.

Roy has worked with the Purdue Research Foundation Office of Technology Commercialization on patented technologies that are providing the basis for some of the research at C-BRIC. They are looking for partners to license the technology.

Making objects invisible is no longer the stuff of fantasy but a fast-evolving science. 'Invisibility cloaks' using metamaterials[2] -- engineered materials that can bend rays of light around an object to make it undetectable -- now exist, and are beginning to be used to improve the performance of satellite antennas and sensors. Many of the proposed metamaterials, however, only work at limited wavelength ranges such as microwave frequencies.

Now, Kotaro Kajikawa and Yusuke Kobayashi of Tokyo Tech's Department of Electrical and Electronic Engineering report a way of making a cylinder invisible without a cloak for monochromatic illumination at optical frequency -- a broader range of wavelengths including those visible to the human eye.

They firstly explored what happens when a light wave hits an imaginary cylinder with an infinite length. Based on a classical electromagnetic theory called Mie scattering[3], they visualized the relationship between the light-scattering efficiency of the cylinder and the refractive index [4]. They looked for a region indicating very low scattering efficiency, which they knew would correspond to the cylinder's invisibility.

After identifying a suitable region, they determined that invisibility would occur when the refractive index of the cylinder ranges from 2.7 to 3.8. Some useful natural materials fall within this range, such as silicon (Si), aluminum arsenide (AlAs) and germanium arsenide (GaAs), which are commonly used in semiconductor technology.

Thus, in contrast to the difficult and costly fabrication procedures often associated with exotic metamaterial coatings, the new approach could provide a much simpler way to achieve invisibility.

The researchers used numerical modeling based on the Finite-Difference Time-Domain (FDTD) method to confirm the conditions for achieving invisibility.  By taking a close look at the magnetic field profiles, they inferred that "the invisibility stems from the cancellation of the dipoles generated in the cylinder."

Although rigorous calculations of the scattering efficiency have so far only been possible for cylinders and spheres, Kajikawa notes there are plans to test other structures, but these would require much more computing power.

To verify the current findings in practice, it should be relatively easy to perform experiments using tiny cylinders made of silicon and germanium arsenide. Kajikawa says: "We hope to collaborate with research groups who are now focusing on such nanostructures. Then, the next step would be to design novel optical devices."

Potential optoelectronic applications may include new kinds of detectors and sensors for the medical and aerospace industries.

[1] Optical frequency: A region of the electromagnetic spectrum that includesultraviolet, visible and infrared light.

[2] Metamaterials: Specially engineered materials designed to have advantageouselectromagnetic properties. Many recent advances in optical cloaking are based on John Pendry's pioneering work on metamaterials.

[3] Mie scattering: A description of the scattering of light particles that have adiameter larger than the wavelength of the incident light. It is named after Germanphysicist Gustav Mie (1868-1957), who published a seminal paper on the scatteringof light by gold colloids in 1908.

[4]Refractive index: A measure of how fast light propagates through a material.

In a new study, the researchers tested bacteria commonly found inside homes on samples of drywall coated with antimicrobial, synthetic latex paints. Within 24 hours, all bacteria died except for Bacillus timonensis, a spore-forming bacterium. Most bacilli are commonly inhabit soil, but many are found in indoor environments.

"If you attack bacteria with antimicrobial chemicals, then they will mount a defense," said Northwestern's Erica Hartmann, who led the study. "Bacillus is typically innocuous, but by attacking it, you might prompt it to develop more antibiotic resistance."

Bacteria thrive in warm, moist environments, so most die on indoor surfaces, which are dry and cold, anyway. This makes Hartmann question the need to use antimicrobial paints, which may only be causing bacteria to become stronger.

Spore-forming bacteria, such as Bacillus, protect themselves by falling dormant for a period of time. While dormant, they are highly resistant to even the harshest conditions. After those conditions improve, they reactivate.

"When it's in spore form, you can hit it with everything you've got, and it's still going to survive," said Hartmann, assistant professor of civil and environmental engineering in Northwestern's McCormick School of Engineering. "We should be judicious in our use of antimicrobial products to make sure that we're not exposing the more harmless bacteria to something that could make them harmful."

The study was published online on April 13 in the journal Indoor Air.

One problem with antimicrobial products -- such as these paints -- is that they are not tested against more common bacteria. Manufacturers test how well more pathogenic bacteria, such as E. coli or Staphylococcus, survive but largely ignore the bacteria that people (and the products they use) would more plausibly encounter.

"E. coli is like the 'lab rat' of the microbial world," Hartmann said. "It is way less abundant in the environment than people think. We wanted to see how the authentic indoor bacteria would respond to antimicrobial surfaces because they don't behave the same way as E. coli."