This image is pretty and I’m pretty sure it’s an illustration and not a real photodetection system. Regardless, an Oct. 21, 2020 news item on Nanowerk describes the research into producing a real 3D hemispheric photodetector for biomedical imaging (Note: A link has been removed),
Purdue University innovators are taking cues from nature to develop 3D photodetectors for biomedical imaging.
The researchers used some architectural features from spider webs to develop the technology. Spider webs typically provide excellent mechanical adaptability and damage-tolerance against various mechanical loads such as storms.
“We employed the unique fractal design of a spider web for the development of deformable and reliable electronics that can seamlessly interface with any 3D curvilinear surface,” said Chi Hwan Lee, a Purdue assistant professor of biomedical engineering and mechanical engineering. “For example, we demonstrated a hemispherical, or dome-shaped, photodetector array that can detect both direction and intensity of incident light at the same time, like the vision system of arthropods such as insects and crustaceans.”
The Purdue technology uses the structural architecture of a spider web that exhibits a repeating pattern. This work is published in Advanced Materials (“Fractal Web Design of a Hemispherical Photodetector Array with Organic-Dye-Sensitized Graphene Hybrid Composites”).
Lee said this provides unique capabilities to distribute externally induced stress throughout the threads according to the effective ratio of spiral and radial dimensions and provides greater extensibility to better dissipate force under stretching. Lee said it also can tolerate minor cuts of the threads while maintaining overall strength and function of the entire web architecture.
“The resulting 3D optoelectronic architectures are particularly attractive for photodetection systems that require a large field of view and wide-angle antireflection, which will be useful for many biomedical and military imaging purposes,” said Muhammad Ashraful Alam, the Jai N. Gupta Professor of Electrical and Computer Engineering.
Alam said the work establishes a platform technology that can integrate a fractal web design with system-level hemispherical electronics and sensors, thereby offering several excellent mechanical adaptability and damage-tolerance against various mechanical loads.
“The assembly technique presented in this work enables deploying 2D deformable electronics in 3D architectures, which may foreshadow new opportunities to better advance the field of 3D electronic and optoelectronic devices,” Lee said.
To just solve a puzzle or play a game, artificial intelligence can require software running on thousands of computers. That could be the energy that three nuclear plants produce in one hour.
A team of engineers has created hardware that can learn skills using a type of AI that currently runs on software platforms. Sharing intelligence features between hardware and software would offset the energy needed for using AI in more advanced applications such as self-driving cars or discovering drugs.
“Software is taking on most of the challenges in AI. If you could incorporate intelligence into the circuit components in addition to what is happening in software, you could do things that simply cannot be done today,” said Shriram Ramanathan, a professor of materials engineering at Purdue University.
AI hardware development is still in early research stages. Researchers have demonstrated AI in pieces of potential hardware, but haven’t yet addressed AI’s large energy demand.
As AI penetrates more of daily life, a heavy reliance on software with massive energy needs is not sustainable, Ramanathan said. If hardware and software could share intelligence features, an area of silicon might be able to achieve more with a given input of energy.
Ramanathan’s team is the first to demonstrate artificial “tree-like” memory in a piece of potential hardware at room temperature. Researchers in the past have only been able to observe this kind of memory in hardware at temperatures that are too low for electronic devices.
The results of this study are published in the journal Nature Communications.
The hardware that Ramanathan’s team developed is made of a so-called quantum material. These materials are known for having properties that cannot be explained by classical physics. Ramanathan’s lab has been working to better understand these materials and how they might be used to solve problems in electronics.
Software uses tree-like memory to organize information into various “branches,” making that information easier to retrieve when learning new skills or tasks.
The strategy is inspired by how the human brain categorizes information and makes decisions.
“Humans memorize things in a tree structure of categories. We memorize ‘apple’ under the category of ‘fruit’ and ‘elephant’ under the category of ‘animal,’ for example,” said Hai-Tian Zhang, a Lillian Gilbreth postdoctoral fellow in Purdue’s College of Engineering. “Mimicking these features in hardware is potentially interesting for brain-inspired computing.”
The team introduced a proton to a quantum material called neodymium nickel oxide. They discovered that applying an electric pulse to the material moves around the proton. Each new position of the proton creates a different resistance state, which creates an information storage site called a memory state. Multiple electric pulses create a branch made up of memory states.
“We can build up many thousands of memory states in the material by taking advantage of quantum mechanical effects. The material stays the same. We are simply shuffling around protons,” Ramanathan said.
Through simulations of the properties discovered in this material, the team showed that the material is capable of learning the numbers 0 through 9. The ability to learn numbers is a baseline test of artificial intelligence.
The demonstration of these trees at room temperature in a material is a step toward showing that hardware could offload tasks from software.
“This discovery opens up new frontiers for AI that have been largely ignored because implementing this kind of intelligence into electronic hardware didn’t exist,” Ramanathan said.
The material might also help create a way for humans to more naturally communicate with AI.
“Protons also are natural information transporters in human beings. A device enabled by proton transport may be a key component for eventually achieving direct communication with organisms, such as through a brain implant,” Zhang said.
Here’s a link to and a citation for the published study,
Perovskite neural trees by Hai-Tian Zhang, Tae Joon Park, Shriram Ramanathan. Nature Communications volume 11, Article number: 2245 (2020) DOI: https://doi.org/10.1038/s41467-020-16105-y Published: 07 May 2020
A new addition to your wardrobe may soon help you turn on the lights and music – while also keeping you fresh, dry, fashionable, clean and safe from the latest virus that’s going around.
Purdue University researchers have developed a new fabric innovation that allows wearers to control electronic devices through clothing.
“It is the first time there is a technique capable to transform any existing cloth item or textile into a self-powered e-textile containing sensors, music players or simple illumination displays using simple embroidery without the need for expensive fabrication processes requiring complex steps or expensive equipment,” said Ramses Martinez, an assistant professor in the School of Industrial Engineering and in the Weldon School of Biomedical Engineering in Purdue’s College of Engineering.
The technology is featured in the July 25  edition of Advanced Functional Materials.
“For the first time, it is possible to fabricate textiles that can protect you from rain, stains, and bacteria while they harvest the energy of the user to power textile-based electronics,” Martinez said. “These self-powered e-textiles also constitute an important advancement in the development of wearable machine-human interfaces, which now can be washed many times in a conventional washing machine without apparent degradation.
Martinez said the Purdue waterproof, breathable and antibacterial self-powered clothing is based on omniphobic triboelectric nanogeneragtors (RF-TENGs) – which use simple embroidery and fluorinated molecules to embed small electronic components and turn a piece of clothing into a mechanism for powering devices. The Purdue team says the RF-TENG technology is like having a wearable remote control that also keeps odors, rain, stains and bacteria away from the user.
“While fashion has evolved significantly during the last centuries and has easily adopted recently developed high-performance materials, there are very few examples of clothes on the market that interact with the user,” Martinez said. “Having an interface with a machine that we are constantly wearing sounds like the most convenient approach for a seamless communication with machines and the Internet of Things.”
The technology is being patented through the Purdue Research Foundation Office of Technology Commercialization. The researchers are looking for partners to test and commercialize their technology.
Their work aligns with Purdue’s Giant Leaps celebration of the university’s global advancements in artificial intelligence and health 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.
A July 25, 2019 news item on Nanowerk provides a description of Moore`s Law and some ‘watery’ research that may upend it,
Moore’s law – which says the number of components that could be etched onto the surface of a silicon wafer would double every two years – has been the subject of recent debate. The quicker pace of computing advancements in the past decade have led some experts to say Moore’s law, the brainchild of Intel co-founder Gordon Moore in the 1960s, no longer applies. Particularly of concern, next-generation computing devices require features smaller than 10 nanometers – driving unsustainable increases in fabrication costs.
Biology creates features at sub-10nm scales routinely, but they are often structured in ways that are not useful for applications like computing. A Purdue University group has found ways of transforming structures that occur naturally in cell membranes to create other architectures, like parallel 1nm-wide line segments, more applicable to computing.
Inspired by biological cell membranes, Purdue researchers in the Claridge Research Group have developed surfaces that act as molecular-scale blueprints for unpacking and aligning nanoscale components for next-generation computers. The secret ingredient? Water, in tiny amounts.
“Biology has an amazing tool kit for embedding chemical information in a surface,” said Shelley Claridge, a recently tenured faculty member in chemistry and biomedical engineering at Purdue, who leads a group of nanomaterials researchers. “What we’re finding is that these instructions can become even more powerful in nonbiological settings, where water is scarce.”
In work just published in Chem, sister journal to Cell, the group has found that stripes of lipids can unpack and order flexible gold nanowires with diameters of just 2 nm, over areas corresponding to many millions of molecules in the template surface.
“The real surprise was the importance of water,” Claridge said. “Your body is mostly water, so the molecules in your cell membranes depend on it to function. Even after we transform the membrane structure in a way that’s very nonbiological and dry it out, these molecules can pull enough water out of dry winter air to do their job.”
Their work aligns with Purdue’s Giant Leaps celebration, celebrating the global advancements in sustainability as part of Purdue’s 150th anniversary. Sustainability 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.
The research team is working with the Purdue Research Foundation Office of Technology Commercialization to patent their work. They are looking for partners for continued research and to take the technology to market. [emphasis mine]
I wonder how close they are to taking this work to market. Usually they say it will be five to 10 years but perhaps we’ll see water-based computers in the near future. In the meantime, here’s a link to and a citation for the paper,
I think this is the first time I’ve seen one of these projects not being funded by the military, which explains why the researchers are more interested in using these hummingbird robots for observing wildlife and for rescue efforts in emergency situations. Still, they do acknowledge theses robots could also be used in covert operations.
What can fly like a bird and hover like an insect?
Your friendly neighborhood hummingbirds. If drones had this combo, they would be able to maneuver better through collapsed buildings and other cluttered spaces to find trapped victims.
Purdue University researchers have engineered flying robots that behave like hummingbirds, trained by machine learning algorithms based on various techniques the bird uses naturally every day.
This means that after learning from a simulation, the robot “knows” how to move around on its own like a hummingbird would, such as discerning when to perform an escape maneuver.
Artificial intelligence, combined with flexible flapping wings, also allows the robot to teach itself new tricks. Even though the robot can’t see yet, for example, it senses by touching surfaces. Each touch alters an electrical current, which the researchers realized they could track.
“The robot can essentially create a map without seeing its surroundings. This could be helpful in a situation when the robot might be searching for victims in a dark place — and it means one less sensor to add when we do give the robot the ability to see,” said Xinyan Deng, an associate professor of mechanical engineering at Purdue.
Drones can’t be made infinitely smaller, due to the way conventional aerodynamics work. They wouldn’t be able to generate enough lift to support their weight.
But hummingbirds don’t use conventional aerodynamics – and their wings are resilient. “The physics is simply different; the aerodynamics is inherently unsteady, with high angles of attack and high lift. This makes it possible for smaller, flying animals to exist, and also possible for us to scale down flapping wing robots,” Deng said.
Researchers have been trying for years to decode hummingbird flight so that robots can fly where larger aircraft can’t. In 2011, the company AeroVironment, commissioned by DARPA, an agency within the U.S. Department of Defense, built a robotic hummingbird that was heavier than a real one but not as fast, with helicopter-like flight controls and limited maneuverability. It required a human to be behind a remote control at all times.
Deng’s group and her collaborators studied hummingbirds themselves for multiple summers in Montana. They documented key hummingbird maneuvers, such as making a rapid 180-degree turn, and translated them to computer algorithms that the robot could learn from when hooked up to a simulation.
Further study on the physics of insects and hummingbirds allowed Purdue researchers to build robots smaller than hummingbirds – and even as small as insects – without compromising the way they fly. The smaller the size, the greater the wing flapping frequency, and the more efficiently they fly, Deng says.
The robots have 3D-printed bodies, wings made of carbon fiber and laser-cut membranes. The researchers have built one hummingbird robot weighing 12 grams – the weight of the average adult Magnificent Hummingbird – and another insect-sized robot weighing 1 gram. The hummingbird robot can lift more than its own weight, up to 27 grams.
Designing their robots with higher lift gives the researchers more wiggle room to eventually add a battery and sensing technology, such as a camera or GPS. Currently, the robot needs to be tethered to an energy source while it flies – but that won’t be for much longer, the researchers say.
The robots could fly silently just as a real hummingbird does, making them more ideal for covert operations. And they stay steady through turbulence, which the researchers demonstrated by testing the dynamically scaled wings in an oil tank.
The robot requires only two motors and can control each wing independently of the other, which is how flying animals perform highly agile maneuvers in nature.
“An actual hummingbird has multiple groups of muscles to do power and steering strokes, but a robot should be as light as possible, so that you have maximum performance on minimal weight,” Deng said.
Robotic hummingbirds wouldn’t only help with search-and-rescue missions, but also allow biologists to more reliably study hummingbirds in their natural environment through the senses of a realistic robot.
“We learned from biology to build the robot, and now biological discoveries can happen with extra help from robots,” Deng said. Simulations of the technology are available open-source at https://github.com/ purdue-biorobotics/flappy.
Early stages of the work, including the Montana hummingbird experiments in collaboration with Bret Tobalske’s group at the University of Montana, were financially supported by the National Science Foundation.
The researchers have three paper on arxiv.org for open access peer review,
Learning Extreme Hummingbird Maneuvers on Flapping Wing Robots Fan Fei, Zhan Tu, Jian Zhang, and Xinyan Deng Purdue University, West Lafayette, IN, USA https://arxiv.org/abs/1902.0962
Biological studies show that hummingbirds can perform extreme aerobatic maneuvers during fast escape. Given a sudden looming visual stimulus at hover, a hummingbird initiates a fast backward translation coupled with a 180-degree yaw turn, which is followed by instant posture stabilization in just under 10 wingbeats. Consider the wingbeat frequency of 40Hz, this aggressive maneuver is carried out in just 0.2 seconds. Inspired by the hummingbirds’ near-maximal performance during such extreme maneuvers, we developed a flight control strategy and experimentally demonstrated that such maneuverability can be achieved by an at-scale 12- gram hummingbird robot equipped with just two actuators. The proposed hybrid control policy combines model-based nonlinear control with model-free reinforcement learning. We use model-based nonlinear control for nominal flight control, as the dynamic model is relatively accurate for these conditions. However, during extreme maneuver, the modeling error becomes unmanageable. A model-free reinforcement learning policy trained in simulation was optimized to ‘destabilize’ the system and maximize the performance during maneuvering. The hybrid policy manifests a maneuver that is close to that observed in hummingbirds. Direct simulation-to-real transfer is achieved, demonstrating the hummingbird-like fast evasive maneuvers on the at-scale hummingbird robot.
Acting is Seeing: Navigating Tight Space Using Flapping Wings Zhan Tu, Fan Fei, Jian Zhang, and Xinyan Deng Purdue University, West Lafayette, IN, USA https://arxiv.org/abs/1902.0868
Wings of flying animals can not only generate lift and control torques but also can sense their surroundings. Such dual functions of sensing and actuation coupled in one element are particularly useful for small sized bio-inspired robotic flyers, whose weight, size, and power are under stringent constraint. In this work, we present the first flapping-wing robot using its flapping wings for environmental perception and navigation in tight space, without the need for any visual feedback. As the test platform, we introduce the Purdue Hummingbird, a flapping-wing robot with 17cm wingspan and 12 grams weight, with a pair of 30-40Hz flapping wings driven by only two actuators. By interpreting the wing loading feedback and its variations, the vehicle can detect the presence of environmental changes such as grounds, walls, stairs, obstacles and wind gust. The instantaneous wing loading can be obtained through the measurements and interpretation of the current feedback by the motors that actuate the wings. The effectiveness of the proposed approach is experimentally demonstrated on several challenging flight tasks without vision: terrain following, wall following and going through a narrow corridor. To ensure flight stability, a robust controller was designed for handling unforeseen disturbances during the flight. Sensing and navigating one’s environment through actuator loading is a promising method for mobile robots, and it can serve as an alternative or complementary method to visual perception.
Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and Animals Fan Fei, Zhan Tu, Yilun Yang, Jian Zhang, and Xinyan Deng Purdue University, West Lafayette, IN, USA https://arxiv.org/abs/1902.0962
Insects and hummingbirds exhibit extraordinary flight capabilities and can simultaneously master seemingly conflicting goals: stable hovering and aggressive maneuvering, unmatched by small scale man-made vehicles. Flapping Wing Micro Air Vehicles (FWMAVs) hold great promise for closing this performance gap. However, design and control of such systems remain challenging due to various constraints. Here, we present an open source high fidelity dynamic simulation for FWMAVs to serve as a testbed for the design, optimization and flight control of FWMAVs. For simulation validation, we recreated the hummingbird-scale robot developed in our lab in the simulation. System identification was performed to obtain the model parameters. The force generation, open- loop and closed-loop dynamic response between simulated and experimental flights were compared and validated. The unsteady aerodynamics and the highly nonlinear flight dynamics present challenging control problems for conventional and learning control algorithms such as Reinforcement Learning. The interface of the simulation is fully compatible with OpenAI Gym environment. As a benchmark study, we present a linear controller for hovering stabilization and a Deep Reinforcement Learning control policy for goal-directed maneuvering. Finally, we demonstrate direct simulation-to-real transfer of both control policies onto the physical robot, further demonstrating the fidelity of the simulation.
This research comes from Purdue University (US) and the December announcement seemed particularly timely since battery-powered gifts are popular at Christmas but since it could be many years before this work is commercialized, you may want to tuck it away for future reference. Also, readers familiar with memristors might see a resemblance to the memory cells mentioned in the following excerpt. From a December 13, 2018 news item on Nanowerk,
The more objects we make “smart,” from watches to entire buildings, the greater the need for these devices to store and retrieve massive amounts of data quickly without consuming too much power.
Millions of new memory cells could be part of a computer chip and provide that speed and energy savings, thanks to the discovery of a previously unobserved functionality in a material called molybdenum ditelluride.
The two-dimensional material stacks into multiple layers to build a memory cell. Researchers at Purdue University engineered this device in collaboration with the National Institute of Standards and Technology (NIST) and Theiss Research Inc.
Chip-maker companies have long called for better memory technologies to enable a growing network of smart devices. One of these next-generation possibilities is resistive random access memory, or RRAM for short.
In RRAM, an electrical current is typically driven through a memory cell made up of stacked materials, creating a change in resistance that records data as 0s and 1s in memory. The sequence of 0s and 1s among memory cells identifies pieces of information that a computer reads to perform a function and then store into memory again.
A material would need to be robust enough for storing and retrieving data at least trillions of times, but materials currently used have been too unreliable. So RRAM hasn’t been available yet for widescale use on computer chips.
Molybdenum ditelluride could potentially last through all those cycles. “We haven’t yet explored system fatigue using this new material, but our hope is that it is both faster and more reliable than other approaches due to the unique switching mechanism we’ve observed,” Joerg Appenzeller, Purdue University’s Barry M. and Patricia L. Epstein Professor of Electrical and Computer Engineering and the scientific director of nanoelectronics at the Birck Nanotechnology Center.
Molybdenum ditelluride allows a system to switch more quickly between 0 and 1, potentially increasing the rate of storing and retrieving information. This is because when an electric field is applied to the cell, atoms are displaced by a tiny distance, resulting in a state of high resistance, noted as 0, or a state of low resistance, noted as 1, which can occur much faster than switching in conventional RRAM devices.
“Because less power is needed for these resistive states to change, a battery could last longer,” Appenzeller said.
In a computer chip, each memory cell would be located at the intersection of wires, forming a memory array called cross-point RRAM.
Appenzeller’s lab wants to explore building a stacked memory cell that also incorporates the other main components of a computer chip: “logic,” which processes data, and “interconnects,” wires that transfer electrical signals, by utilizing a library of novel electronic materials fabricated at NIST.
“Logic and interconnects drain battery too, so the advantage of an entirely two-dimensional architecture is more functionality within a small space and better communication between memory and logic,” Appenzeller said.
The work received financial support from the Semiconductor Research Corporation through the NEW LIMITS Center (led by Purdue University), NIST, the U.S. Department of Commerce and the Material Genome Initiative.
Billions of objects ranging from smartphones and watches to buildings, machine parts and medical devices have become wireless sensors of their environments, expanding a network called the “internet of things.”
As society moves toward connecting all objects to the internet — even furniture and office supplies — the technology that enables these objects to communicate and sense each other will need to scale up.
Researchers at Purdue University and the University of Virginia have developed a new fabrication method that makes tiny, thin-film electronic circuits peelable from a surface. The technique not only eliminates several manufacturing steps and the associated costs, but also allows any object to sense its environment or be controlled through the application of a high-tech sticker.
Eventually, these stickers could also facilitate wireless communication. …
“We could customize a sensor, stick it onto a drone, and send the drone to dangerous areas to detect gas leaks, for example,” said Chi Hwan Lee, Purdue assistant professor of biomedical engineering and mechanical engineering.
Most of today’s electronic circuits are individually built on their own silicon “wafer,” a flat and rigid substrate. The silicon wafer can then withstand the high temperatures and chemical etching that are used to remove the circuits from the wafer.
But high temperatures and etching damage the silicon wafer, forcing the manufacturing process to accommodate an entirely new wafer each time.
Lee’s new fabrication technique, called “transfer printing,” cuts down manufacturing costs by using a single wafer to build a nearly infinite number of thin films holding electronic circuits. Instead of high temperatures and chemicals, the film can peel off at room temperature with the energy-saving help of simply water.
“It’s like the red paint on San Francisco’s Golden Gate Bridge – paint peels because the environment is very wet,” Lee said. “So in our case, submerging the wafer and completed circuit in water significantly reduces the mechanical peeling stress and is environmentally-friendly.”
A ductile metal layer, such as nickel, inserted between the electronic film and the silicon wafer, makes the peeling possible in water. These thin-film electronics can then be trimmed and pasted onto any surface, granting that object electronic features.
Putting one of the stickers on a flower pot, for example, made that flower pot capable of sensing temperature changes that could affect the plant’s growth.
Lee’s lab also demonstrated that the components of electronic integrated circuits work just as well before and after they were made into a thin film peeled from a silicon wafer. The researchers used one film to turn on and off an LED light display.
“We’ve optimized this process so that we can delaminate electronic films from wafers in a defect-free manner,” Lee said.
This technology holds a non-provisional U.S. patent. The work was supported by the Purdue Research Foundation, the Air Force Research Laboratory (AFRL-S-114-054-002), the National Science Foundation (NSF-CMMI-1728149) and the University of Virginia.
Dexter Johnson provides some context in his July 25, 2018 posting on the Nanoclast blog (on the IEEE [Institute of Electronic and Electrical Engineers] website), Note: A link has been removed,
The Internet of Things (IoT), the interconnection of billions of objects and devices that will be communicating with each other, has been the topic of many futurists’ projections. However, getting the engineering sorted out with the aim of fully realizing the myriad visions for IoT is another story. One key issue to address: How do you get the electronics onto these devices efficiently and economically?
A team of researchers from Purdue University and the University of Virginia has developed a new manufacturing process that could make equipping a device with all the sensors and other electronics that will make it Internet capable as easily as putting a piece of tape on it.
… this new approach makes use of a water environment at room temperature to control the interfacial debonding process. This allows clean, intact delamination of prefabricated thin film devices when they’re pulled away from the original wafer.
The use of mechanical peeling in water rather than etching solution provides a number of benefits in the manufacturing scheme. Among them are simplicity, controllability, and cost effectiveness, says Chi Hwan Lee, assistant professor at Purdue University and coauthor of the paper chronicling the research.
If you have the time, do read Dexter’s piece. He always adds something that seems obvious in retrospect but wasn’t until he wrote it.
A professor in the Purdue College of Engineering examined the potential use of various materials in nuclear reactors in an extensive review article in the journal Progress in Materials Science.
The article, titled “Radiation Damage in Nanostructured Materials,” was led by Xinghang Zhang, a professor of materials engineering. It will be published in the July issue of the journal.
Zhang said there is a significant demand for advanced materials that can survive high temperature and high doses of radiation. These materials contain significant amount of internal changes, called defect sinks, which are too small to be seen with the naked eye, but may form the next generation of materials used in nuclear reactors.
“Nanostructured materials with abundant internal defect sinks are promising as these materials have shown significantly improved radiation tolerance,” he said. “However, there are many challenges and fundamental science questions that remain to be solved before these materials can have applications in advanced nuclear reactors.”
The 100-page article, which took two years to write, focuses on metallic materials and metal-ceramic compounds and reviews types of internal material defects on the reduction of radiation damage in nanostructured materials.
Under the extreme radiation conditions, a large number of defects and their clusters are generated inside materials, and such significant microstructure damage often leads to degradation of the mechanical and physical properties of the materials
The article discusses the usage of a combination of defect sink networks to collaboratively improve the radiation tolerance of nanomaterials, while pointing out the need to improve the thermal and radiation stabilities of the defect sinks.
“The field of radiation damage in nanostructured materials is an exciting and rapidly evolving arena, enriched with challenges and opportunities,” Zhang said. “The integration of extensive research effort, resources and expertise in various fields may eventually lead to the design of advanced nanomaterials with unprecedented radiation tolerance.”
Jin Li, co-author of the review article and a postdoctoral fellow in the School of Materials Engineering, said researchers with different expertise worked collaboratively on the article, which contains more than 100 pages, 100 figures and 700 references.
The team involved in the research article included researchers from Purdue, Texas A&M University, Drexel University, the University of Nebraska-Lincoln and China University of Petroleum-Beijing, as well as Sandia National Laboratory, Los Alamos National Laboratory and Idaho National Laboratory.
Here’s an image illustrating the work,
Various imperfections in nanostructures, call defect sinks, can enhance the material’s tolerance to radiation. (Photo/Xinghang Zhang)
Here’s a link to and a citation for the paper,
Radiation damage in nanostructured materials by Xinghang Zhang, Khalid Hattar, Youxing Chen, Lin Shao, Jin Li, Cheng Sun, Kaiyuan Yu, Nan Li, Mitra L.Taheri, Haiyan Wang, Jian Wang, Michael Nastasi. Progress in Materials Science Volume 96, July 2018, Pages 217-321 https://doi.org/10.1016/j.pmatsci.2018.03.002
This approach to mimicking the human brain differs from the memristor. (You can find several pieces about memrisors here including this August 24, 2017 post about a derivative, a neuristor). This approach comes from scientists at Purdue University and employs a quantum material. From an Aug. 15, 2017 news item on phys.org,
A new computing technology called “organismoids” mimics some aspects of human thought by learning how to forget unimportant memories while retaining more vital ones.
“The human brain is capable of continuous lifelong learning,” said Kaushik Roy, Purdue University’s Edward G. Tiedemann Jr. Distinguished Professor of Electrical and Computer Engineering. “And it does this partially by forgetting some information that is not critical. I learn slowly, but I keep forgetting other things along the way, so there is a graceful degradation in my accuracy of detecting things that are old. What we are trying to do is mimic that behavior of the brain to a certain extent, to create computers that not only learn new information but that also learn what to forget.”
The work was performed by researchers at Purdue, Rutgers University, the Massachusetts Institute of Technology, Brookhaven National Laboratory and Argonne National Laboratory.
Central to the research is a ceramic “quantum material” called samarium nickelate, which was used to create devices called organismoids, said Shriram Ramanathan, a Purdue professor of materials engineering.
“These devices possess certain characteristics of living beings and enable us to advance new learning algorithms that mimic some aspects of the human brain,” Roy said. “The results have far reaching implications for the fields of quantum materials as well as brain-inspired computing.”
When exposed to hydrogen gas, the material undergoes a massive resistance change, as its crystal lattice is “doped” by hydrogen atoms. The material is said to breathe, expanding when hydrogen is added and contracting when the hydrogen is removed.
“The main thing about the material is that when this breathes in hydrogen there is a spectacular quantum mechanical effect that allows the resistance to change by orders of magnitude,” Ramanathan said. “This is very unusual, and the effect is reversible because this dopant can be weakly attached to the lattice, so if you remove the hydrogen from the environment you can change the electrical resistance.”
When hydrogen is exposed to the material, it splits into a proton and an electron, and the electron attaches to the nickel, temporarily causing the material to become an insulator.
“Then, when the hydrogen comes out, this material becomes conducting again,” Ramanathan said. “What we show in this paper is the extent of conduction and insulation can be very carefully tuned.”
This changing conductance and the “decay of that conductance over time” is similar to a key animal behavior called habituation.
“Many animals, even organisms that don’t have a brain, possess this fundamental survival skill,” Roy said. “And that’s why we call this organismic behavior. If I see certain information on a regular basis, I get habituated, retaining memory of it. But if I haven’t seen such information over a long time, then it slowly starts decaying. So, the behavior of conductance going up and down in exponential fashion can be used to create a new computing model that will incrementally learn and at same time forget things in a proper way.”
The researchers have developed a “neural learning model” they have termed adaptive synaptic plasticity.
“This could be really important because it’s one of the first examples of using quantum materials directly for solving a major problem in neural learning,” Ramanathan said.
The researchers used the organismoids to implement the new model for synaptic plasticity.
“Using this effect we are able to model something that is a real problem in neuromorphic computing,” Roy said. “For example, if I have learned your facial features I can still go out and learn someone else’s features without really forgetting yours. However, this is difficult for computing models to do. When learning your features, they can forget the features of the original person, a problem called catastrophic forgetting.”
Neuromorphic computing is not intended to replace conventional general-purpose computer hardware, based on complementary metal-oxide-semiconductor transistors, or CMOS. Instead, it is expected to work in conjunction with CMOS-based computing. Whereas CMOS technology is especially adept at performing complex mathematical computations, neuromorphic computing might be able to perform roles such as facial recognition, reasoning and human-like decision making.
Roy’s team performed the research work on the plasticity model, and other collaborators concentrated on the physics of how to explain the process of doping-driven change in conductance central to the paper. The multidisciplinary team includes experts in materials, electrical engineering, physics, and algorithms.
“It’s not often that a materials science person can talk to a circuits person like professor Roy and come up with something meaningful,” Ramanathan said.
Organismoids might have applications in the emerging field of spintronics. Conventional computers use the presence and absence of an electric charge to represent ones and zeroes in a binary code needed to carry out computations. Spintronics, however, uses the “spin state” of electrons to represent ones and zeros.
It could bring circuits that resemble biological neurons and synapses in a compact design not possible with CMOS circuits. Whereas it would take many CMOS devices to mimic a neuron or synapse, it might take only a single spintronic device.
In future work, the researchers may demonstrate how to achieve habituation in an integrated circuit instead of exposing the material to hydrogen gas.
Here’s a link to and a citation for the paper,
Habituation based synaptic plasticity and organismic learning in a quantum perovskite by Fan Zuo, Priyadarshini Panda, Michele Kotiuga, Jiarui Li, Mingu Kang, Claudio Mazzoli, Hua Zhou, Andi Barbour, Stuart Wilkins, Badri Narayanan, Mathew Cherukara, Zhen Zhang, Subramanian K. R. S. Sankaranarayanan, Riccardo Comin, Karin M. Rabe, Kaushik Roy, & Shriram Ramanathan. Nature Communications 8, Article number: 240 (2017) doi:10.1038/s41467-017-00248-6 Published online: 14 August 2017
Purdue University researchers are developing a nontoxic, biodegradable orthopedic implant that could be safely absorbed by the body after providing adequate support to damaged bones.
The development of the technology originated in the lab of Lia Stanciu, a professor of materials engineering at Purdue in 2009. The technology could eliminate the need for a second surgery to remove conventional hardware.
“Currently, most implants use stainless steel and titanium alloys for strength. This can cause long-term change in the mechanics of the specific region and eventual long-term deterioration,” Stanciu said. “Additionally medical operations that require an orthopedic implant must be followed-up with a second surgery to remove the implant or the accompanying hardware of the implant resulting in higher medical costs and an increased risk of complications.”
Nauman said the resorbable metal technology provides superior properties compared to conventional metals.
“The implant has high porosity, which is empty space in the material, in which optimal vascular invasion can occur. This provides a way for cells to optimally absorb the material,” he said. “Our technology is able to provide short-term fixation but eliminate the need for long-term hardware such as titanium or stainless steel that may require second surgeries to be retrieved,”
The orthopedic implant also uses manganese, which provides a better degradation rate, Stanciu added.
“Current resorbable metals are made with magnesium; however, this provides many adverse side effects to the body and degrades very quickly,” she said. “We decided to use manganese instead of magnesium. Through studies we found that we can control the degradation rates from 22 millimeters per year to 1.2 millimeters per year pretty consistently. We also saw that manganese has a very good corrosion rate over time.”
Nauman said the technology still exhibits the usual benefits associated with using biomaterials.
“With this technology we are able to tailor the surfaces such as de-alloying the surface to provide a better material for cells to grab on to and grow,” he said. “We were also able to show that we could control cell attachment proliferation, an increase of the number of cells. Our technology still has all these usual benefits in addition to controlling the degradation rates of the metals.”