Tag Archives: New Jersey Institute of Technology (NJIT)

Brainy and brainy: a novel synaptic architecture and a neuromorphic computing platform called SpiNNaker

I have two items about brainlike computing. The first item hearkens back to memristors, a topic I have been following since 2008. (If you’re curious about the various twists and turns just enter  the term ‘memristor’ in this blog’s search engine.) The latest on memristors is from a team than includes IBM (US), École Politechnique Fédérale de Lausanne (EPFL; Swizterland), and the New Jersey Institute of Technology (NJIT; US). The second bit comes from a Jülich Research Centre team in Germany and concerns an approach to brain-like computing that does not include memristors.

Multi-memristive synapses

In the inexorable march to make computers function more like human brains (neuromorphic engineering/computing), an international team has announced its latest results in a July 10, 2018 news item on Nanowerk,

Two New Jersey Institute of Technology (NJIT) researchers, working with collaborators from the IBM Research Zurich Laboratory and the École Polytechnique Fédérale de Lausanne, have demonstrated a novel synaptic architecture that could lead to a new class of information processing systems inspired by the brain.

The findings are an important step toward building more energy-efficient computing systems that also are capable of learning and adaptation in the real world. …

A July 10, 2018 NJIT news release (also on EurekAlert) by Tracey Regan, which originated by the news item, adds more details,

The researchers, Bipin Rajendran, an associate professor of electrical and computer engineering, and S. R. Nandakumar, a graduate student in electrical engineering, have been developing brain-inspired computing systems that could be used for a wide range of big data applications.

Over the past few years, deep learning algorithms have proven to be highly successful in solving complex cognitive tasks such as controlling self-driving cars and language understanding. At the heart of these algorithms are artificial neural networks – mathematical models of the neurons and synapses of the brain – that are fed huge amounts of data so that the synaptic strengths are autonomously adjusted to learn the intrinsic features and hidden correlations in these data streams.

However, the implementation of these brain-inspired algorithms on conventional computers is highly inefficient, consuming huge amounts of power and time. This has prompted engineers to search for new materials and devices to build special-purpose computers that can incorporate the algorithms. Nanoscale memristive devices, electrical components whose conductivity depends approximately on prior signaling activity, can be used to represent the synaptic strength between the neurons in artificial neural networks.

While memristive devices could potentially lead to faster and more power-efficient computing systems, they are also plagued by several reliability issues that are common to nanoscale devices. Their efficiency stems from their ability to be programmed in an analog manner to store multiple bits of information; however, their electrical conductivities vary in a non-deterministic and non-linear fashion.

In the experiment, the team showed how multiple nanoscale memristive devices exhibiting these characteristics could nonetheless be configured to efficiently implement artificial intelligence algorithms such as deep learning. Prototype chips from IBM containing more than one million nanoscale phase-change memristive devices were used to implement a neural network for the detection of hidden patterns and correlations in time-varying signals.

“In this work, we proposed and experimentally demonstrated a scheme to obtain high learning efficiencies with nanoscale memristive devices for implementing learning algorithms,” Nandakumar says. “The central idea in our demonstration was to use several memristive devices in parallel to represent the strength of a synapse of a neural network, but only chose one of them to be updated at each step based on the neuronal activity.”

Here’s a link to and a citation for the paper,

Neuromorphic computing with multi-memristive synapses by Irem Boybat, Manuel Le Gallo, S. R. Nandakumar, Timoleon Moraitis, Thomas Parnell, Tomas Tuma, Bipin Rajendran, Yusuf Leblebici, Abu Sebastian, & Evangelos Eleftheriou. Nature Communications volume 9, Article number: 2514 (2018) DOI: https://doi.org/10.1038/s41467-018-04933-y Published 28 June 2018

This is an open access paper.

Also they’ve got a couple of very nice introductory paragraphs which I’m including here, (from the June 28, 2018 paper in Nature Communications; Note: Links have been removed),

The human brain with less than 20 W of power consumption offers a processing capability that exceeds the petaflops mark, and thus outperforms state-of-the-art supercomputers by several orders of magnitude in terms of energy efficiency and volume. Building ultra-low-power cognitive computing systems inspired by the operating principles of the brain is a promising avenue towards achieving such efficiency. Recently, deep learning has revolutionized the field of machine learning by providing human-like performance in areas, such as computer vision, speech recognition, and complex strategic games1. However, current hardware implementations of deep neural networks are still far from competing with biological neural systems in terms of real-time information-processing capabilities with comparable energy consumption.

One of the reasons for this inefficiency is that most neural networks are implemented on computing systems based on the conventional von Neumann architecture with separate memory and processing units. There are a few attempts to build custom neuromorphic hardware that is optimized to implement neural algorithms2,3,4,5. However, as these custom systems are typically based on conventional silicon complementary metal oxide semiconductor (CMOS) circuitry, the area efficiency of such hardware implementations will remain relatively low, especially if in situ learning and non-volatile synaptic behavior have to be incorporated. Recently, a new class of nanoscale devices has shown promise for realizing the synaptic dynamics in a compact and power-efficient manner. These memristive devices store information in their resistance/conductance states and exhibit conductivity modulation based on the programming history6,7,8,9. The central idea in building cognitive hardware based on memristive devices is to store the synaptic weights as their conductance states and to perform the associated computational tasks in place.

The two essential synaptic attributes that need to be emulated by memristive devices are the synaptic efficacy and plasticity. …

It gets more complicated from there.

Now onto the next bit.


At a guess, those capitalized N’s are meant to indicate ‘neural networks’. As best I can determine, SpiNNaker is not based on the memristor. Moving on, a July 11, 2018 news item on phys.org announces work from a team examining how neuromorphic hardware and neuromorphic software work together,

A computer built to mimic the brain’s neural networks produces similar results to that of the best brain-simulation supercomputer software currently used for neural-signaling research, finds a new study published in the open-access journal Frontiers in Neuroscience. Tested for accuracy, speed and energy efficiency, this custom-built computer named SpiNNaker, has the potential to overcome the speed and power consumption problems of conventional supercomputers. The aim is to advance our knowledge of neural processing in the brain, to include learning and disorders such as epilepsy and Alzheimer’s disease.

A July 11, 2018 Frontiers Publishing news release on EurekAlert, which originated the news item, expands on the latest work,

“SpiNNaker can support detailed biological models of the cortex–the outer layer of the brain that receives and processes information from the senses–delivering results very similar to those from an equivalent supercomputer software simulation,” says Dr. Sacha van Albada, lead author of this study and leader of the Theoretical Neuroanatomy group at the Jülich Research Centre, Germany. “The ability to run large-scale detailed neural networks quickly and at low power consumption will advance robotics research and facilitate studies on learning and brain disorders.”

The human brain is extremely complex, comprising 100 billion interconnected brain cells. We understand how individual neurons and their components behave and communicate with each other and on the larger scale, which areas of the brain are used for sensory perception, action and cognition. However, we know less about the translation of neural activity into behavior, such as turning thought into muscle movement.

Supercomputer software has helped by simulating the exchange of signals between neurons, but even the best software run on the fastest supercomputers to date can only simulate 1% of the human brain.

“It is presently unclear which computer architecture is best suited to study whole-brain networks efficiently. The European Human Brain Project and Jülich Research Centre have performed extensive research to identify the best strategy for this highly complex problem. Today’s supercomputers require several minutes to simulate one second of real time, so studies on processes like learning, which take hours and days in real time are currently out of reach.” explains Professor Markus Diesmann, co-author, head of the Computational and Systems Neuroscience department at the Jülich Research Centre.

He continues, “There is a huge gap between the energy consumption of the brain and today’s supercomputers. Neuromorphic (brain-inspired) computing allows us to investigate how close we can get to the energy efficiency of the brain using electronics.”

Developed over the past 15 years and based on the structure and function of the human brain, SpiNNaker — part of the Neuromorphic Computing Platform of the Human Brain Project — is a custom-built computer composed of half a million of simple computing elements controlled by its own software. The researchers compared the accuracy, speed and energy efficiency of SpiNNaker with that of NEST–a specialist supercomputer software currently in use for brain neuron-signaling research.

“The simulations run on NEST and SpiNNaker showed very similar results,” reports Steve Furber, co-author and Professor of Computer Engineering at the University of Manchester, UK. “This is the first time such a detailed simulation of the cortex has been run on SpiNNaker, or on any neuromorphic platform. SpiNNaker comprises 600 circuit boards incorporating over 500,000 small processors in total. The simulation described in this study used just six boards–1% of the total capability of the machine. The findings from our research will improve the software to reduce this to a single board.”

Van Albada shares her future aspirations for SpiNNaker, “We hope for increasingly large real-time simulations with these neuromorphic computing systems. In the Human Brain Project, we already work with neuroroboticists who hope to use them for robotic control.”

Before getting to the link and citation for the paper, here’s a description of SpiNNaker’s hardware from the ‘Spiking neural netowrk’ Wikipedia entry, Note: Links have been removed,

Neurogrid, built at Stanford University, is a board that can simulate spiking neural networks directly in hardware. SpiNNaker (Spiking Neural Network Architecture) [emphasis mine], designed at the University of Manchester, uses ARM processors as the building blocks of a massively parallel computing platform based on a six-layer thalamocortical model.[5]

Now for the link and citation,

Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model by
Sacha J. van Albada, Andrew G. Rowley, Johanna Senk, Michael Hopkins, Maximilian Schmidt, Alan B. Stokes, David R. Lester, Markus Diesmann, and Steve B. Furber. Neurosci. 12:291. doi: 10.3389/fnins.2018.00291 Published: 23 May 2018

As noted earlier, this is an open access paper.

Getting a more complete picture of aerosol particles at the nanoscale

What is in the air we breathe? In addition to the gases we learned about in school there are particles, not just the dust particles you can see, but micro- and nanoparticles too and scientists would like to know more about them.

An August 23, 2017 news item on Nanowerk features work which may help scientists in their quest,

They may be tiny and invisible, says Xiaoji Xu, but the aerosol particles suspended in gases play a role in cloud formation and environmental pollution and can be detrimental to human health.

Aerosol particles, which are found in haze, dust and vehicle exhaust, measure in the microns. One micron is one-millionth of a meter; a thin human hair is about 30 microns thick.

The particles, says Xu, are among the many materials whose chemical and mechanical properties cannot be fully measured until scientists develop a better method of studying materials at the microscale as well as the much smaller nanoscale (1 nm is one-billionth of a meter).

Xu, an assistant professor of chemistry, has developed such a method and utilized it to perform noninvasive chemical imaging of a variety of materials, as well as mechanical mapping with a spatial resolution of 10 nanometers.

The technique, called peak force infrared (PFIR) microscopy, combines spectroscopy and scanning probe microscopy. In addition to shedding light on aerosol particles, Xu says, PFIR will help scientists study micro- and nanoscale phenomena in a variety of inhomogeneous materials.

The lower portion of this image by Xiaoji Xu’s group shows the operational scheme of peak force infrared (PFIR) microscopy. The upper portion shows the topography of nanoscale PS-b-PMMA polymer islands on a gold substrate. (Image courtesy of Xiaoji Xu)

An August 22, 2017 Lehih University news release by Kurt Pfitzer (also on EurekAlert), which originated the news item, explains the research in more detail (Note: A link has been removed),

“Materials in nature are rarely homogeneous,” says Xu. “Functional polymer materials often consist of nanoscale domains that have specific tasks. Cellular membranes are embedded with proteins that are nanometers in size. Nanoscale defects of materials exist that affect their mechanical and chemical properties.

“PFIR microscopy represents a fundamental breakthrough that will enable multiple innovations in areas ranging from the study of aerosol particles to the investigation of heterogeneous and biological materials,” says Xu.

Xu and his group recently reported their results in an article titled “Nanoscale simultaneous chemical and mechanical imaging via peak force infrared microscopy.” The article was published in Science Advances, a journal of the American Association for the Advancement of Science, which also publishes Science magazine.

The article’s lead author is Le Wang, a Ph.D. student at Lehigh. Coauthors include Xu and Lehigh Ph.D. students Haomin Wang and Devon S. Jakob, as well as Martin Wagner of Bruker Nano in Santa Barbara, Calif., and Yong Yan of the New Jersey Institute of Technology.

“PFIR microscopy enables reliable chemical imaging, the collection of broadband spectra, and simultaneous mechanical mapping in one simple setup with a spatial resolution of ~10 nm,” the group wrote.

“We have investigated three types of representative materials, namely, soft polymers, perovskite crystals and boron nitride nanotubes, all of which provide a strong PFIR resonance for unambiguous nanochemical identification. Many other materials should be suited as well for the multimodal characterization that PFIR microscopy has to offer.

“In summary, PFIR microscopy will provide a powerful analytical tool for explorations at the nanoscale across wide disciplines.”

Xu and Le Wang also published a recent article about the use of PFIR to study aerosols. Titled “Nanoscale spectroscopic and mechanical characterization of individual aerosol particles using peak force infrared microscopy,” the article appeared in an “Emerging Investigators” issue of Chemical Communications, a journal of the Royal Society of Chemistry. Xu was featured as one of the emerging investigators in the issue. The article was coauthored with researchers from the University of Macau and the City University of Hong Kong, both in China.

PFIR simultaneously obtains chemical and mechanical information, says Xu. It enables researchers to analyze a material at various places, and to determine its chemical compositions and mechanical properties at each of these places, at the nanoscale.

“A material is not often homogeneous,” says Xu. “Its mechanical properties can vary from one region to another. Biological systems such as cell walls are inhomogeneous, and so are materials with defects. The features of a cell wall measure about 100 nanometers in size, placing them well within range of PFIR and its capabilities.”

PFIR has several advantages over scanning near-field optical microscopy (SNOM), the current method of measuring material properties, says Xu. First, PFIR obtains a fuller infrared spectrum and a sharper image—6-nm spatial resolution—of a wider variety of materials than does SNOM. SNOM works well with inorganic materials, but does not obtain as strong an infrared signal as the Lehigh technique does from softer materials such as polymers or biological materials.

“Our technique is more robust,” says Xu. “It works better with soft materials, chemical as well as biological.”

The second advantage of PFIR is that it can perform what Xu calls point spectroscopy.

“If there is something of interest chemically on a surface,” Xu says, “I put an AFM [atomic force microscopy] probe to that location to measure the peak-force infrared response.

“It is very difficult to obtain these spectra with current scattering-type scanning near-field optical microscopy. It can be done, but it requires very expensive light sources. Our method uses a narrow-band infrared laser and costs about $100,000. The existing method uses a broadband light source and costs about $300,000.”

A third advantage, says Xu, is that PFIR obtains a mechanical as well as a chemical response from a material.

“No other spectroscopy method can do this,” says Xu. “Is a material rigid or soft? Is it inhomogeneous—is it soft in one area and rigid in another? How does the composition vary from the soft to the rigid areas? A material can be relatively rigid and have one type of chemical composition in one area, and be relatively soft with another type of composition in another area.

“Our method simultaneously obtains chemical and mechanical information. It will be useful for analyzing a material at various places and determining its compositions and mechanical properties at each of these places, at the nanoscale.”

A fourth advantage of PFIR is its size, says Xu.

“We use a table-top laser to get infrared spectra. Ours is a very compact light source, as opposed to the much larger sizes of competing light sources. Our laser is responsible for gathering information concerning chemical composition. We get mechanical information from the AFM [atomic force microscope]. We integrate the two types of measurements into one device to simultaneously obtain two channels of information.”

Although PFIR does not work with liquid samples, says Xu, it can measure the properties of dried biological samples, including cell walls and protein aggregates, achieving a 10-nm spatial resolution without staining or genetic modification.

This looks like very exciting work.

Here are links and citations for both studies mentioned in the news release (the most recently published being cited first),

Nanoscale simultaneous chemical and mechanical imaging via peak force infrared microscopy by Le Wang, Haomin Wang, Martin Wagner, Yong Yan, Devon S. Jakob, and Xiaoji G. Xu. Science Advances 23 Jun 2017: Vol. 3, no. 6, e1700255 DOI: 10.1126/sciadv.1700255

Nanoscale spectroscopic and mechanical characterization of individual aerosol particles using peak force infrared microscopy by Le Wang, Dandan Huang, Chak K. Chan, Yong Jie Li, and Xiaoji G. Xu. Chem. Commun., 2017,53, 7397-7400 DOI: 10.1039/C7CC02301D First published on 16 Jun 2017

The June 23, 2017 paper is open access while the June 16, 2017 paper is behind a paywall.

US Army offers course on nanotechnology

As you might expect, the US Army course on nanotechnology stresses the importance of nanotechnology for the military, according to a June 16, 2016 news item on Nanowerk,

If there is one lesson to glean from Picatinny Arsenal’s new course in nanomaterials, it’s this: never underestimate the power of small.

Nanotechnology is the study of manipulating matter on an atomic, molecular, or supermolecular scale. The end result can be found in our everyday products, such as stained glass [This is a reference to the red glass found in churches from the Middle Ages. More about this later in the posting], sunscreen, cellphones, and pharmaceutical products.

Other examples are in U.S. Army items such as vehicle armor, Soldier uniforms, power sources, and weaponry. All living things also can be considered united forms of nanotechnology produced by the forces of nature.

“People tend to think that nanotechnology is all about these little robots roaming around, fixing the environment or repairing damage to your body, and for many reasons that’s just unrealistic,” said Rajen Patel, a senior engineer within the Energetics and Warheads Manufacturing Technology Division, or EWMTD.

The division is part of the U.S. Army Armament Research, Development and Engineering Center or ARDEC.

A June 15, 2016 ARDEC news release by Cassandra Mainiero, which originated the news item, expands on the theme,

“For me, nanotechnology means getting materials to have these properties that you wouldn’t expect them to have.” [Patel]

The subject can be separated into multiple types (nanomedicine, nanomachines, nanoelectronics, nanocomposites, nanophotonics and more), which can benefit areas, such as communications, medicine, environment remediation, and manufacturing.

Nanomaterials are defined as materials that have at least one dimension in the 1-100 nm range (there are 25,400,000 nanometers in one inch.) To provide some size perspective: comparing a nanometer to a meter is like comparing a soccer ball to the earth.

Picatinny’s nanomaterials class focuses on nanomaterials’ distinguishing qualities, such as their optical, electronic, thermal and mechanical properties–and teaches how manipulating them in a weapon can benefit the warfighter [soldier].

While you could learn similar information at a college course, Patel argues that Picatinny’s nanomaterial class is nothing like a university class.

This is because Picatinny’s nanomaterials class focuses on applied, rather than theoretical nanotechnology, using the arsenal as its main source of examples.

“We talk about things like what kind of properties you get, how to make materials, places you might expect to see nanotechnology within the Army,” explained Patel.

The class is taught at the Armament University. Each class lasts three days. The last one was held in February.

Each class includes approximately 25 students and provides an overview of nanotechnology, covering topics, such as its history, early pioneers in the field, and everyday items that rely on nanotechnology.

Additionally, the course covers how those same concepts apply at Picatinny (for electronics, sensors, energetics, robotics, insensitive munitions, and more) and the major difficulties with experimenting and manufacturing nanotechnology.

Moreover, the class involves guest talks from Picatinny engineers and scientists, such as Dan Kaplan, Christopher Haines, and Venkataraman Swaminathan as well as tours of Picatinny facilities like the Nanotechnology Center and the Explosives Research Laboratory.

It also includes lectures from guest speakers, such as Gordon Thomas from the New Jersey Institute of Technology (NJIT), who spoke about nanomaterials and diabetes research.


Relatively new, the nanomaterials class launched in January 2015. It was pioneered by Patel after he attended an instructional course on teaching at the Armament University, where he met Erin Williams, a technical training analyst at the university.

“At the Armament University, we’re always trying to think of, ‘What new areas of interest should we offer to help our workforce? What forward reaching technologies are needed?’ One topic that came up was nanotechnology,” said Williams about how the nanomaterials class originated.

“I started to do research on the subject, how it might be geared toward Picatinny, and trying to think of ways to organize the class. Then, I enrolled in the instructional course on teaching, where I just so happen to be sitting across from Dr. Rajen Patel, who not only knew about nanotechnology, but taught a few seminars at NJIT, where he did his doctorate,” explained Williams. “I couldn’t believe the coincidence! So, I asked him if he would be interested in teaching a class and he said ‘Yes!'”

“After the first [nanomaterials] class, one of the students came up to me and said ‘This was the best course I’ve ever been to on this arsenal,'” added Williams. “…This is really how Picatinny shines as a team: when you meet people and utilize your knowledge to benefit the organization.”

The success of the first nanomaterials course encouraged Patel to expand his class into specialty fields, designing a two-day nanoenergetics class taught by himself and Victor Stepanov, a senior scientist at EWMTD.

Stepanov works with nano-organic energetics (RDX, HMX, CL-20) and inorganic materials (metals.) He is responsible for creating the first nanoorganic energetic known as nano-RDX. He is involved in research aimed at understanding the various properties of nanoenergetics including sensitivity, performance, and mechanical characteristics. He and Patel teach the nanoenergetics class that was first offered last fall and due to high demand is expected to be offered annually. The next one will be held in September.

“We always ask for everyone’s feedback. And, after our first class, everyone said ‘[Picatinny] is the home of the Army’s lethality–why did we not talk about nanoenergetics?’ So, in response to the student’s feedback, we implemented that nanoenergetics course,” said Patel. “Besides, in the long run, you’ll probably replace most energetics with nano-energetics, as they have far too many advantages.”


Since all living things are a form of nanotechnology manipulated by the forces of nature, the history of nanotechnology dates back to the emergence of life. However, a more concrete example can be traced back to ancient times, when nanomaterials were manipulated to create gold and silver art such as Lycurgus Cup, a 4th century Roman glass [I’ve added more about the Lycurgus Cup later in this post].

According to Stepanov, ARDEC’s interest in nanotechnology gained significant momentum approximately 20 years ago. The initiative at ARDEC was directly tied to the emergence of advanced technologies needed for production and characterization of nanomaterials, and was concurrent with adoption of nanotechnologies in other fields such as pharmaceuticals.

In 2010, an article in The Picatinny Voice titled “Tiny particles, big impact: Nanotechnology to help warfighters” discussed Picatinny’s ongoing research on nanopowders.

It noted that Picatinny’s Nanotechnology Lab is the largest facility in North America to produce nanopowders and nanomaterials, which are used to create nanoexplosives.

It also mentioned how using nanomaterials helped to develop lightweight composites as an alternative to traditional steel.

The more recent heightened study is due to the evolution of technology, which has allowed engineers and scientists to be more productive and made nanotechnology more ubiquitous throughout the military.

“Not too long ago making milligram quantities of nanoexplosives was challenging. Now, we have technologies that allow us make pounds of nanoexplosives per hour at low cost,” said Stepanov.

Pilot scale production of nanoexplosives is currently being performed at ARDEC, lead by Ashok Surapaneni of the Explosives Development Branch.

The broad interest in developing nanoenergetics such as nano-RDX and nano-HMX is their remarkably low initiation sensitivity.

These materials can thus be crucial in the development of safer next generation munitions that are much less vulnerable to accidental initiation.


As a result, working with nanotechnology can have various payoffs, such as enhancing the performance of military products, said Patel. For instance, by manipulating nanomaterials, an engineer could make a weapon stronger, lighter, or increase its reactivity or durability.

“Generally, if you make something more safe, you make it less powerful,” said Stepanov. “But, with nanomaterials, you can make a product more safe and, in many cases, more powerful.”

There are two basic approaches to studying nanomaterials: bottom-up (building a large object atom by atom) and top-down (deconstructing a larger material.) Both approaches have been successfully employed in the development of nanoenergetics at ARDEC.

One of the challenges with manufacturing nonmaterials can be coping with shockwaves.

A shockwave initiates an explosive as it travels through a weapon’s main fill or the booster. When a shockwave travels through an energetic charge, it can hit small regions of defects, or voids, which heat up quickly and build pressure until the explosive reaches detonation. By using nanoenergetics, one could adjust the size and quantity of the defects and voids, so that the pressure isn’t as strong and ultimately prevent accidental detonation.

Nanomaterials also are difficult to process because they tend to agglomerate (stick together) and are also prone to Ostwald Ripening, or spontaneous growth of the crystals, which is especially pronounced at the nano-scale. This effect is commonly observed with ice cream, where ice can re-crystallize, resulting in a gritty texture.

“It’s a major production challenge because if you want to process nanomaterials–if you want to coat it with some polymer for explosives–any kind of medium that can dissolve these types of materials can promote ripening and you can end up with a product which no longer has the nanomaterial that you began with,” explained Stepanov.

However, nanotechnology research continues to grow at Picatinny as the research advances in the U.S. Army.

This ongoing development and future applicability encourages Patel and Stepanov to teach the nanomaterials and nanoenergetics course at Picatinny.

“I’m interested in making things better for the warfighter,” said Patel. “Nano-materials give you so many opportunities to do so. Also, as a scientist, it’s just a fascinating realm because you always get these little interesting surprises.

“You can know all the material science and equations, but then you get in the nano-world, and there’s something like a wrinkle–something you wouldn’t expect,” Patel added.

“It satisfies three deep needs: getting the warfighter technology, producing something of value, and it’s fun. You always see something new.”

Medieval church windows and the Lycurgus Cup

The shade of red in medieval church window glass is said to have been achieved by the use of gold nanoparticles. There is a source which claims the colour is due to copper rather than gold. I have not had to time to pursue the controversy such as it is but do have November 1, 2010 posting about stained glass and medieval churches which may prove of interest.

As for the Lycurgus Cup, it’s from the 4th century (CE or AD) and is an outstanding example of Roman art and craft. The glass in the cup is dichroic (it looks green or red depending on how the light catches it). The effect was achieved with the presence of gold and silver nanoparticles in the glass. I have a more extensive description and pictures in a Sept. 21, 2010 posting.

Final note

There is an  army initiative involving an educational institution, the Massachusetts Institute of Technology (MIT). The initiative is the MIT Institute for Soldier Nanotechnologies.

Fish that suck and why they matter

That headline is misleading, these fish (remoras) surprised scientists when research challenged longheld beliefs that they used suction to cling to various surfaces  From a Feb. 12, 2015 news item on ScienceDaily,

How does the hitchhiking, flat-headed remora fish attach to surfaces so securely yet release so easily? Suction was thought to be the easy answer, but Brooke Flammang, a biologist at the New Jersey Institute of Technology (NJIT), has proved this long-held conclusion to be only partly true.

Here’s an image of a remora clinging to a glass or plexiglass (?) wall,

Remoras stick to fast-moving sea creatures, but are also content to cling to aquarium tank walls. Courtesy: NJIT

Remoras stick to fast-moving sea creatures, but are also content to cling to aquarium tank walls. Courtesy: NJIT

A Feb. 12, 2015 NJIT press release (also on EurekAlert), which originated the news item, describes this research in the field of biomimicry,

Researchers have long studied animals like tree frogs, geckos, and spiders for their adhesive abilities, but what makes remoras unique in this group is they combine three key elements: the ability to securely fasten themselves for long periods of time; attach to different types of surfaces; release quickly without harming the surface.

Understanding the mechanics of this process could help researchers and engineers create or improve designs for any number of devices that need to stick well but then release quickly without harming the host, such as tags for tracking endangered species or bandages that really don’t hurt when you pull them off.

Using footage captured by GoPro cameras at SeaWorld’s Discovery Cove in Orlando, Flammang and NJIT researchers found that the adhesive disc on the remora’s head used to attach to sharks, rays and other pelagic hosts is actually a complex mechanism that includes a modified fin structure with teeny spikes (called lamellar spinules) that generate friction to adhere to the host. Remora head anatomy also differs from other fish in having unusually-structured blood vessels that may be the secret to how they maintain adhesion for hours at a time.

What intrigued Flammang, who studies the locomotion of fishes, integrating sensory biology, physiology, fluid dynamics, and bio-inspired robotics, is how remoras can alter the position and shape of the plates within the disc to change their position or quickly let go. She was able to observe the minute movements of remora disc components through the underwater footage provided by marine videographers.

“Remoras attach to other organisms for a variety of reasons: To find food, get protection, and find mates. Because the animals they attach to are powerful swimmers, they need a durable attachment that won’t be compromised by the host organism’s swimming, bending body. The adhesive disc the remora evolved from dorsal fin elements acts as a specialized suction cup that can bend and won’t slip,” Flammang said.

“We are applying the biomechanics of this mechanism to a robotic prototype that will be able to adhere to both rough and smooth surfaces through a variety of challenging conditions, both in water and air,” she said.

Flammang presented her research at the Society for Integrative and Comparative Biology’s annual conference in January.

“We have a lot to learn from the natural world. Being able to examine these animals up close can be very valuable to bioengineering. We are proud to support this important work,” added SeaWorld Parks & Entertainment’s Vice President of Research and Science, Dr. Judy St. Leger.

“In my lab at NJIT, we study the morphology of remoras, how they use muscular and vascular control to manipulate the disc for attachment on different surfaces, and the hydrodynamics of their approach, attachment, and release from a surface,” Flammang said. “Live remoras swim in our flow tank – a treadmill for fish – and we capture muscle activity recordings and high speed video of the fish swimming and attaching, as well as and the fluid moving around the fish and the attachment location.”

More broadly, she examines the way organisms interact with marine and aquatic environments and drive the evolutionary selection of morphology and function. She seeks to understand, for example, how different fish fins may give an advantage to certain species in a given habitat.

The two remoras (Echeneis naucrates) at SeaWorld’s Discovery Cove were valuable candidates for this study because they often attach themselves to a large acrylic panel that divides their dock-themed habitat from the park’s Grand Reef, a nearly 1million gallon tropical environment. Aquarists at Discovery Cove donned scuba gear to capture the underwater footage using a GoPro camera steadied with a suction cup arm to get the shots needed by the research team. Flammang and her colleagues then used mathematical algorithms to visualize motion that is not detected by the human eye.

There doesn’t seem to be a published paper for this work.