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With new optical device, engineers can fine tune the color of light

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Home > Press > With new optical device, engineers can fine tune the color of light

Shanhui Fan (Image credit: Rod Searcey)
Shanhui Fan (Image credit: Rod Searcey)

Abstract:
Among the first lessons any grade school science student learns is that white light is not white at all, but rather a composite of many photons, those little droplets of energy that make up light, from every color of the rainbow – red, orange, yellow, green, blue, indigo, violet.

With new optical device, engineers can fine tune the color of light


Stanford, CA | Posted on April 23rd, 2021

Now, researchers at Stanford University have developed an optical device that allows engineers to change and fine-tune the frequencies of each individual photon in a stream of light to virtually any mixture of colors they want. The result, published April 23 in Nature Communication, is a new photonic architecture that could transform fields ranging from digital communications and artificial intelligence to cutting-edge quantum computing.

“This powerful new tool puts a degree of control in the engineer’s hands not previously possible,” said Shanhui Fan, a professor of electrical engineering at Stanford and senior author of the paper.

The clover-leaf effect

The structure consists of a low-loss wire for light carrying a stream of photons that pass by like so many cars on a busy throughway. The photons then enter a series of rings, like the off-ramps in a highway cloverleaf. Each ring has a modulator that transforms the frequency of the passing photons – frequencies which our eyes see as color. There can be as many rings as necessary, and engineers can finely control the modulators to dial in the desired frequency transformation.

Among the applications that the researchers envision include optical neural networks for artificial intelligence that perform neural computations using light instead of electrons. Existing methods that accomplish optical neural networks do not actually change the frequencies of the photons, but simply reroute photons of a single frequency. Performing such neural computations through frequency manipulation could lead to much more compact devices, say the researchers.

“Our device is a significant departure from existing methods with a small footprint and yet offering tremendous new engineering flexibility,” said Avik Dutt, a post-doctoral scholar in Fan’s lab and second author of the paper.

Seeing the light

The color of a photon is determined by the frequency at which the photon resonates, which, in turn, is a factor of its wavelength. A red photon has a relatively slow frequency and a wavelength of about 650 nanometers. At the other end of the spectrum, blue light has a much faster frequency with a wavelength of about 450 nanometers.

A simple transformation might involve shifting a photon from a frequency of 500 nanometers to, say, 510 nanometers – or, as the human eye would register it, a change from cyan to green. The power of the Stanford team’s architecture is that it can perform these simple transformations, but also much more sophisticated ones with fine control.

To further explain, Fan offers an example of an incoming light stream comprised of 20 percent photons in the 500-nanometer range and 80 percent at 510 nanometers. Using this new device, an engineer could fine-tune that ratio to 73 percent at 500 nanometers and 27 percent at 510 nanometers, if so desired, all while preserving the total number of photons. Or the ratio could 37 and 63 percent, for that matter. This ability to set the ratio is what makes this device new and promising. Moreover, in the quantum world, a single photon can have multiple colors. In that circumstance, the new device actually allows changing of the ratio of different colors for a single photon.

“We say this device allows for ‘arbitrary’ transformation but that does not mean ‘random,'” said Siddharth Buddhiraju, who was a graduate student in Fan’s lab during the research and is first author of the paper and who now works at Facebook Reality Labs. “Instead, we mean that we can achieve any linear transformation that the engineer requires. There is a great amount of engineering control here.”

“It’s very versatile. The engineer can control the frequencies and proportions very accurately and a wide variety of transformations are possible,” Fan added. “It puts new power in the engineer’s hands. How they will use it is up to them.”

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Additional authors include postdoctoral scholars Momchil Minkov, now at Flexcompute, and Ian A. D. Williamson, now at Google X.

This research was supported by the U.S. Air Force Office of Scientific Research.

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Tom Abate
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@stanford

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With a zap of light, system switches objects’ colors and patterns: “Programmable matter” technique could enable product designers to churn out prototypes with ease

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Home > Press > With a zap of light, system switches objects’ colors and patterns: “Programmable matter” technique could enable product designers to churn out prototypes with ease

A new system uses UV light projected onto objects coated with light-activated dye to alter the reflective properties of the dye, creating images in minutes. CREDIT
Image courtesy of Michael Wessley, Stefanie Mueller, et al
A new system uses UV light projected onto objects coated with light-activated dye to alter the reflective properties of the dye, creating images in minutes. CREDIT
Image courtesy of Michael Wessley, Stefanie Mueller, et al

Abstract:
When was the last time you repainted your car? Redesigned your coffee mug collection? Gave your shoes a colorful facelift?

With a zap of light, system switches objects’ colors and patterns: “Programmable matter” technique could enable product designers to churn out prototypes with ease


Cambridge, MA | Posted on May 6th, 2021

You likely answered: never, never, and never. You might consider these arduous tasks not worth the effort. But a new color-shifting “programmable matter” system could change that with a zap of light.

MIT researchers have developed a way to rapidly update imagery on object surfaces. The system, dubbed “ChromoUpdate” pairs an ultraviolet (UV) light projector with items coated in light-activated dye. The projected light alters the reflective properties of the dye, creating colorful new images in just a few minutes. The advance could accelerate product development, enabling product designers to churn through prototypes without getting bogged down with painting or printing.

ChromoUpdate “takes advantage of fast programming cycles — things that wouldn’t have been possible before,” says Michael Wessley, the study’s lead author and a postdoc in MIT’s Computer Science and Artificial Intelligence Laboratory.

The research will be presented at the ACM Conference on Human Factors in Computing Systems this month. Wessely’s co-authors include his advisor, Professor Stefanie Mueller, as well as postdoc Yuhua Jin, recent graduate Cattalyya Nuengsigkapian ’19, MNG ’20, visiting master’s student Aleksei Kashapov, postdoc Isabel Qamar, and Professor Dzmitry Tsetserukou of the Skolkovo Institute of Science and Technology.

ChromoUpdate builds on the researchers’ previous programmable matter system, called PhotoChromeleon. That method was “the first to show that we can have high-resolution, multicolor textures that we can just reprogram over and over again,” says Wessely. PhotoChromeleon used a lacquer-like ink comprising cyan, magenta, and yellow dyes. The user covered an object with a layer of the ink, which could then be reprogrammed using light. First, UV light from an LED was shone on the ink, fully saturating the dyes. Next, the dyes were selectively desaturated with a visible light projector, bringing each pixel to its desired color and leaving behind the final image. PhotoChromeleon was innovative, but it was sluggish. It took about 20 minutes to update an image. “We can accelerate the process,” says Wessely.

They achieved that with ChromoUpdate, by fine-tuning the UV saturation process. Rather than using an LED, which uniformly blasts the entire surface, ChromoUpdate uses a UV projector that can vary light levels across the surface. So, the operator has pixel-level control over saturation levels. “We can saturate the material locally in the exact pattern we want,” says Wessely. That saves time — someone designing a car’s exterior might simply want to add racing stripes to an otherwise completed design. ChromoUpdate lets them do just that, without erasing and reprojecting the entire exterior.

This selective saturation procedure allows designers to create a black-and-white preview of a design in seconds, or a full-color prototype in minutes. That means they could try out dozens of designs in a single work session, a previously unattainable feat. “You can actually have a physical prototype to see if your design really works,” says Wessely. “You can see how it looks when sunlight shines on it or when shadows are cast. It’s not enough just to do this on a computer.”

That speed also means ChromoUpdate could be used for providing real-time notifications without relying on screens. “One example is your coffee mug,” says Wessely. “You put your mug in our projector system and program it to show your daily schedule. And it updates itself directly when a new meeting comes in for that day, or it shows you the weather forecast.”

Wessely hopes to keep improving the technology. At present, the light-activated ink is specialized for smooth, rigid surfaces like mugs, phone cases, or cars. But the researchers are working toward flexible, programmable textiles. “We’re looking at methods to dye fabrics and potentially use light-emitting fibers,” says Wessely. “So, we could have clothing — t-shirts and shoes and all that stuff — that can reprogram itself.”

The researchers have partnered with a group of textile makers in Paris to see how ChomoUpdate can be incorporated into the design process.

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This research was funded, in part, by Ford.

Written by Daniel Ackerman, MIT News Office

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Abby Abazorius
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Graphene key for novel hardware security

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Home > Press > Graphene key for novel hardware security

A team of Penn State researchers has developed a new hardware security device that takes advantage of microstructure variations to generate secure keys. CREDIT
Jennifer McCann,Penn State
A team of Penn State researchers has developed a new hardware security device that takes advantage of microstructure variations to generate secure keys. CREDIT
Jennifer McCann,Penn State

Abstract:
As more private data is stored and shared digitally, researchers are exploring new ways to protect data against attacks from bad actors. Current silicon technology exploits microscopic differences between computing components to create secure keys, but artificial intelligence (AI) techniques can be used to predict these keys and gain access to data. Now, Penn State researchers have designed a way to make the encrypted keys harder to crack.

Graphene key for novel hardware security


University Park, PA | Posted on May 10th, 2021

Led by Saptarshi Das, assistant professor of engineering science and mechanics, the researchers used graphene — a layer of carbon one atom thick — to develop a novel low-power, scalable, reconfigurable hardware security device with significant resilience to AI attacks. They published their findings in Nature Electronics today (May 10).

“There has been more and more breaching of private data recently,” Das said. “We developed a new hardware security device that could eventually be implemented to protect these data across industries and sectors.”

The device, called a physically unclonable function (PUF), is the first demonstration of a graphene-based PUF, according to the researchers. The physical and electrical properties of graphene, as well as the fabrication process, make the novel PUF more energy-efficient, scalable, and secure against AI attacks that pose a threat to silicon PUFs.

The team first fabricated nearly 2,000 identical graphene transistors, which switch current on and off in a circuit. Despite their structural similarity, the transistors’ electrical conductivity varied due to the inherent randomness arising from the production process. While such variation is typically a drawback for electronic devices, it’s a desirable quality for a PUF not shared by silicon-based devices.

After the graphene transistors were implemented into PUFs, the researchers modeled their characteristics to create a simulation of 64 million graphene-based PUFs. To test the PUFs’ security, Das and his team used machine learning, a method that allows AI to study a system and find new patterns. The researchers trained the AI with the graphene PUF simulation data, testing to see if the AI could use this training to make predictions about the encrypted data and reveal system insecurities.

“Neural networks are very good at developing a model from a huge amount of data, even if humans are unable to,” Das said. “We found that AI could not develop a model, and it was not possible for the encryption process to be learned.”

This resistance to machine learning attacks makes the PUF more secure because potential hackers could not use breached data to reverse engineer a device for future exploitation, Das said. Even if the key could be predicted, the graphene PUF could generate a new key through a reconfiguration process requiring no additional hardware or replacement of components.

“Normally, once a system’s security has been compromised, it is permanently compromised,” said Akhil Dodda, an engineering science and mechanics graduate student conducting research under Das’s mentorship. “We developed a scheme where such a compromised system could be reconfigured and used again, adding tamper resistance as another security feature.”

With these features, as well as the capacity to operate across a wide range of temperatures, the graphene-based PUF could be used in a variety of applications. Further research can open pathways for its use in flexible and printable electronics, household devices and more.

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Paper co-authors include Dodda, Shiva Subbulakshmi Radhakrishnan, Thomas Schranghamer and Drew Buzzell from Penn State; and Parijat Sengupta from Purdue University. Das is also affiliated with the Penn State Department of Materials Science and Engineering and the Materials Research Institute.

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Contacts:
Megan Lakatos
814-865-5544

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Tiny, Wireless, Injectable Chips Use Ultrasound to Monitor Body Processes

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Home > Press > Tiny, Wireless, Injectable Chips Use Ultrasound to Monitor Body Processes

Chips shown in the tip of a hypodermic needle. Chen Shi/Columbia Engineering
Chips shown in the tip of a hypodermic needle. Chen Shi/Columbia Engineering

Abstract:
Columbia Engineers develop the smallest single-chip system that is a complete functioning electronic circuit; implantable chips visible only in a microscope point the way to developing chips that can be injected into the body with a hypodermic needle to monitor medical conditions.

Tiny, Wireless, Injectable Chips Use Ultrasound to Monitor Body Processes


New York, NY | Posted on May 12th, 2021

Widely used to monitor and map biological signals, to support and enhance physiological functions, and to treat diseases, implantable medical devices are transforming healthcare and improving the quality of life for millions of people. Researchers are increasingly interested in designing wireless, miniaturized implantable medical devices for in vivo and in situ physiological monitoring. These devices could be used to monitor physiological conditions, such as temperature, blood pressure, glucose, and respiration for both diagnostic and therapeutic procedures.

To date, conventional implanted electronics have been highly volume-inefficient—they generally require multiple chips, packaging, wires, and external transducers, and batteries are often needed for energy storage. A constant trend in electronics has been tighter integration of electronic components, often moving more and more functions onto the integrated circuit itself.

Researchers at Columbia Engineering report that they have built what they say is the world’s smallest single-chip system, consuming a total volume of less than 0.1 mm3. The system is as small as a dust mite and visible only under a microscope. In order to achieve this, the team used ultrasound to both power and communicate with the device wirelessly. The study was published online May 7 in Science Advances.

Chips shown in the tip of a hypodermic needle.

Chen Shi/Columbia Engineering

“We wanted to see how far we could push the limits on how small a functioning chip we could make,” said the study’s leader Ken Shepard, Lau Family professor of electrical engineering and professor of biomedical engineering. “This is a new idea of ‘chip as system’—this is a chip that alone, with nothing else, is a complete functioning electronic system. This should be revolutionary for developing wireless, miniaturized implantable medical devices that can sense different things, be used in clinical applications, and eventually approved for human use.”

The team also included Elisa Konofagou, Robert and Margaret Hariri Professor of Biomedical engineering and professor of radiology, as well as Stephen A. Lee, PhD student in the Konofagou lab who assisted in the animal studies.

The design was done by doctoral student Chen Shi, who is the first author of the study. Shi’s design is unique in its volumetric efficiency, the amount of function that is contained in a given amount of volume. Traditional RF communications links are not possible for a device this small because the wavelength of the electromagnetic wave is too large relative to the size of the device. Because the wavelengths for ultrasound are much smaller at a given frequency because the speed of sound is so much less than the speed of light, the team used ultrasound to both power and communicate with the device wirelessly. They fabricated the “antenna” for communicating and powering with ultrasound directly on top of the chip.

The chip, which is the entire implantable/injectable mote with no additional packaging, was fabricated at the Taiwan Semiconductor Manufacturing Company with additional process modifications performed in the Columbia Nano Initiative cleanroom and the City University of New York Advanced Science Research Center (ASRC) Nanofabrication Facility.

Shepard commented, “This is a nice example of ‘more than Moore’ technology—we introduced new materials onto standard complementary metal-oxide-semiconductor to provide new function. In this case, we added piezoelectric materials directly onto the integrated circuit to transducer acoustic energy to electrical energy.”

Konofagou added, “Ultrasound is continuing to grow in clinical importance as new tools and techniques become available. This work continues this trend.”

The team’s goal is to develop chips that can be injected into the body with a hypodermic needle and then communicate back out of the body using ultrasound, providing information about something they measure locally. The current devices measure body temperature, but there are many more possibilities the team is working on.

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About Columbia Engineering
Columbia Engineering, based in New York City, is one of the top engineering schools in the U.S. and one of the oldest in the nation. Also known as The Fu Foundation School of Engineering and Applied Science, the School expands knowledge and advances technology through the pioneering research of its more than 220 faculty, while educating undergraduate and graduate students in a collaborative environment to become leaders informed by a firm foundation in engineering. The School’s faculty are at the center of the University’s cross-disciplinary research, contributing to the Data Science Institute, Earth Institute, Zuckerman Mind Brain Behavior Institute, Precision Medicine Initiative, and the Columbia Nano Initiative. Guided by its strategic vision, “Columbia Engineering for Humanity,” the School aims to translate ideas into innovations that foster a sustainable, healthy, secure, connected, and creative humanity.

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Graphene key for novel hardware security

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A team of Penn State researchers has developed a new hardware security device that takes advantage of microstructure variations to generate secure keys. CREDIT
Jennifer McCann,Penn State
A team of Penn State researchers has developed a new hardware security device that takes advantage of microstructure variations to generate secure keys. CREDIT
Jennifer McCann,Penn State

Abstract:
As more private data is stored and shared digitally, researchers are exploring new ways to protect data against attacks from bad actors. Current silicon technology exploits microscopic differences between computing components to create secure keys, but artificial intelligence (AI) techniques can be used to predict these keys and gain access to data. Now, Penn State researchers have designed a way to make the encrypted keys harder to crack.

Graphene key for novel hardware security


University Park, PA | Posted on May 10th, 2021

Led by Saptarshi Das, assistant professor of engineering science and mechanics, the researchers used graphene — a layer of carbon one atom thick — to develop a novel low-power, scalable, reconfigurable hardware security device with significant resilience to AI attacks. They published their findings in Nature Electronics today (May 10).

“There has been more and more breaching of private data recently,” Das said. “We developed a new hardware security device that could eventually be implemented to protect these data across industries and sectors.”

The device, called a physically unclonable function (PUF), is the first demonstration of a graphene-based PUF, according to the researchers. The physical and electrical properties of graphene, as well as the fabrication process, make the novel PUF more energy-efficient, scalable, and secure against AI attacks that pose a threat to silicon PUFs.

The team first fabricated nearly 2,000 identical graphene transistors, which switch current on and off in a circuit. Despite their structural similarity, the transistors’ electrical conductivity varied due to the inherent randomness arising from the production process. While such variation is typically a drawback for electronic devices, it’s a desirable quality for a PUF not shared by silicon-based devices.

After the graphene transistors were implemented into PUFs, the researchers modeled their characteristics to create a simulation of 64 million graphene-based PUFs. To test the PUFs’ security, Das and his team used machine learning, a method that allows AI to study a system and find new patterns. The researchers trained the AI with the graphene PUF simulation data, testing to see if the AI could use this training to make predictions about the encrypted data and reveal system insecurities.

“Neural networks are very good at developing a model from a huge amount of data, even if humans are unable to,” Das said. “We found that AI could not develop a model, and it was not possible for the encryption process to be learned.”

This resistance to machine learning attacks makes the PUF more secure because potential hackers could not use breached data to reverse engineer a device for future exploitation, Das said. Even if the key could be predicted, the graphene PUF could generate a new key through a reconfiguration process requiring no additional hardware or replacement of components.

“Normally, once a system’s security has been compromised, it is permanently compromised,” said Akhil Dodda, an engineering science and mechanics graduate student conducting research under Das’s mentorship. “We developed a scheme where such a compromised system could be reconfigured and used again, adding tamper resistance as another security feature.”

With these features, as well as the capacity to operate across a wide range of temperatures, the graphene-based PUF could be used in a variety of applications. Further research can open pathways for its use in flexible and printable electronics, household devices and more.

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Paper co-authors include Dodda, Shiva Subbulakshmi Radhakrishnan, Thomas Schranghamer and Drew Buzzell from Penn State; and Parijat Sengupta from Purdue University. Das is also affiliated with the Penn State Department of Materials Science and Engineering and the Materials Research Institute.

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