Tag Archives: Australia

Is it time to invest in a ‘brain chip’ company?

This story take a few twists and turns. First, ‘brain chips’ as they’re sometimes called would allow, theoretically, computers to learn and function like human brains. (Note: There’s another type of ‘brain chip’ which could be implanted in human brains to help deal with diseases such as Parkinson’s and Alzheimer’s. *Today’s [June 26, 2015] earlier posting about an artificial neuron points at some of the work being done in this areas.*)

Returning to the ‘brain ship’ at hand. Second, there’s a company called BrainChip, which has one patent and another pending for, yes, a ‘brain chip’.

The company, BrainChip, founded in Australia and now headquartered in California’s Silicon Valley, recently sparked some investor interest in Australia. From an April 7, 2015 article by Timna Jacks for the Australian Financial Review,

Former mining stock Aziana Limited has whet Australian investors’ appetite for science fiction, with its share price jumping 125 per cent since it announced it was acquiring a US-based tech company called BrainChip, which promises artificial intelligence through a microchip that replicates the neural system of the human brain.

Shares in the company closed at 9¢ before the Easter long weekend, having been priced at just 4¢ when the backdoor listing of BrainChip was announced to the market on March 18.

Creator of the patented digital chip, Peter Van Der Made told The Australian Financial Review the technology has the capacity to learn autonomously, due to its composition of 10,000 biomimic neurons, which, through a process known as synaptic time-dependent plasticity, can form memories and associations in the same way as a biological brain. He said it works 5000 times faster and uses a thousandth of the power of the fastest computers available today.

Mr Van Der Made is inviting technology partners to license the technology for their own chips and products, and is donating the technology to university laboratories in the US for research.

The Netherlands-born Australian, now based in southern California, was inspired to create the brain-like chip in 2004, after working at the IBM Internet Security Systems for two years, where he was chief scientist for behaviour analysis security systems. …

A June 23, 2015 article by Tony Malkovic on phys.org provide a few more details about BrainChip and about the deal,

Mr Van der Made and the company, also called BrainChip, are now based in Silicon Valley in California and he returned to Perth last month as part of the company’s recent merger and listing on the Australian Stock Exchange.

He says BrainChip has the ability to learn autonomously, evolve and associate information and respond to stimuli like a brain.

Mr Van der Made says the company’s chip technology is more than 5,000 faster than other technologies, yet uses only 1/1,000th of the power.

“It’s a hardware only solution, there is no software to slow things down,” he says.

“It doesn’t executes instructions, it learns and supplies what it has learnt to new information.

“BrainChip is on the road to position itself at the forefront of artificial intelligence,” he says.

“We have a clear advantage, at least 10 years, over anybody else in the market, that includes IBM.”

BrainChip is aiming at the global semiconductor market involving almost anything that involves a microprocessor.

You can find out more about the company, BrainChip here. The site does have a little more information about the technology,

Spiking Neuron Adaptive Processor (SNAP)

BrainChip’s inventor, Peter van der Made, has created an exciting new Spiking Neural Networking technology that has the ability to learn autonomously, evolve and associate information just like the human brain. The technology is developed as a digital design containing a configurable “sea of biomimic neurons’.

The technology is fast, completely digital, and consumes very low power, making it feasible to integrate large networks into portable battery-operated products, something that has never been possible before.

BrainChip neurons autonomously learn through a process known as STDP (Synaptic Time Dependent Plasticity). BrainChip’s fully digital neurons process input spikes directly in hardware. Sensory neurons convert physical stimuli into spikes. Learning occurs when the input is intense, or repeating through feedback and this is directly correlated to the way the brain learns.

Computing Artificial Neural Networks (ANNs)

The brain consists of specialized nerve cells that communicate with one another. Each such nerve cell is called a Neuron,. The inputs are memory nodes called synapses. When the neuron associates information, it produces a ‘spike’ or a ‘spike train’. Each spike is a pulse that triggers a value in the next synapse. Synapses store values, similar to the way a computer stores numbers. In combination, these values determine the function of the neural network. Synapses acquire values through learning.

In Artificial Neural Networks (ANNs) this complex function is generally simplified to a static summation and compare function, which severely limits computational power. BrainChip has redefined how neural networks work, replicating the behaviour of the brain. BrainChip’s artificial neurons are completely digital, biologically realistic resulting in increased computational power, high speed and extremely low power consumption.

The Problem with Artificial Neural Networks

Standard ANNs, running on computer hardware are processed sequentially; the processor runs a program that defines the neural network. This consumes considerable time and because these neurons are processed sequentially, all this delayed time adds up resulting in a significant linear decline in network performance with size.

BrainChip neurons are all mapped in parallel. Therefore the performance of the network is not dependent on the size of the network providing a clear speed advantage. So because there is no decline in performance with network size, learning also takes place in parallel within each synapse, making STDP learning very fast.

A hardware solution

BrainChip’s digital neural technology is the only custom hardware solution that is capable of STDP learning. The hardware requires no coding and has no software as it evolves learning through experience and user direction.

The BrainChip neuron is unique in that it is completely digital, behaves asynchronously like an analog neuron, and has a higher level of biological realism. It is more sophisticated than software neural models and is many orders of magnitude faster. The BrainChip neuron consists entirely of binary logic gates with no traditional CPU core. Hence, there are no ‘programming’ steps. Learning and training takes the place of programming and coding. Like of a child learning a task for the first time.

Software ‘neurons’, to compromise for limited processing power, are simplified to a point where they do not resemble any of the features of a biological neuron. This is due to the sequential nature of computers, whereby all data has to pass through a central processor in chunks of 16, 32 or 64 bits. In contrast, the brain’s network is parallel and processes the equivalent of millions of data bits simultaneously.

A significantly faster technology

Performing emulation in digital hardware has distinct advantages over software. As software is processed sequentially, one instruction at a time, Software Neural Networks perform slower with increasing size. Parallel hardware does not have this problem and maintains the same speed no matter how large the network is. Another advantage of hardware is that it is more power efficient by several orders of magnitude.

The speed of the BrainChip device is unparalleled in the industry.

For large neural networks a GPU (Graphics Processing Unit) is ~70 times faster than the Intel i7 executing a similar size neural network. The BrainChip neural network is faster still and takes far fewer CPU (Central Processing Unit) cycles, with just a little communication overhead, which means that the CPU is available for other tasks. The BrainChip network also responds much faster than a software network accelerating the performance of the entire system.

The BrainChip network is completely parallel, with no sequential dependencies. This means that the network does not slow down with increasing size.

Endorsed by the neuroscience community

A number of the world’s pre-eminent neuroscientists have endorsed the technology and are agreeing to joint develop projects.

BrainChip has the potential to become the de facto standard for all autonomous learning technology and computer products.

Patented

BrainChip’s autonomous learning technology patent was granted on the 21st September 2008 (Patent number US 8,250,011 “Autonomous learning dynamic artificial neural computing device and brain inspired system”). BrainChip is the only company in the world to have achieved autonomous learning in a network of Digital Neurons without any software.

A prototype Spiking Neuron Adaptive Processor was designed as a ‘proof of concept’ chip.

The first tests were completed at the end of 2007 and this design was used as the foundation for the US patent application which was filed in 2008. BrainChip has also applied for a continuation-in-part patent filed in 2012, the “Method and System for creating Dynamic Neural Function Libraries”, US Patent Application 13/461,800 which is pending.

Van der Made doesn’t seem to have published any papers on this work and the description of the technology provided on the website is frustratingly vague. There are many acronyms for processes but no mention of what this hardware might be. For example, is it based on a memristor or some kind of atomic ionic switch or something else altogether?

It would be interesting to find out more but, presumably, van der Made, wishes to withhold details. There are many companies following the same strategy while pursuing what they view as a business advantage.

* Artificial neuron link added June 26, 2015 at 1017 hours PST.

Nanoscale imaging gets rough

Smooth is easier than rough when imaging at the nanoscale according to a June 17, 2015 Northwestern University news release by Megan Fellman (also on EurekAlert),

A multi-institutional team of scientists has taken an important step in understanding where atoms are located on the surfaces of rough materials, information that could be very useful in diverse commercial applications, such as developing green energy and understanding how materials rust.

Researchers from Northwestern University, Brookhaven National Laboratory, Lawrence Berkeley National Laboratory and the University of Melbourne, Australia, have developed a new imaging technique that uses atomic resolution secondary electron images in a quantitative way to determine the arrangement of atoms on the surface.

Many important processes take place at surfaces, ranging from the catalysis used to generate energy-dense fuels from sunlight and carbon dioxide to how bridges and airplanes corrode, or rust. Every material interacts with the world through its surface, which is often different in both structure and chemistry from the bulk of the material.

The real focus of the work is on corrosion, according to the news release,

“We are excited by the possibilities of applying our imaging technique to corrosion and catalysis problems,” said Laurence Marks, a co-author of the paper and a professor of materials science and engineering at Northwestern’s McCormick School of Engineering and Applied Science. “The cost of corrosion to industry and the military is enormous, and we do not understand everything that is taking place. We must learn more, so we can produce materials that will last longer.”

To understand these processes and improve material performance, it is vital to know how the atoms are arranged on surfaces. While there are many good methods for obtaining this information for rather flat surfaces, most currently available tools are limited in what they can reveal when the surfaces are rough.

Scanning electron microscopes are widely used to produce images of many different materials, and roughness of the surface is not that important. Until very recently, instruments could not obtain clear atomic images of surfaces until a group at Brookhaven managed in 2011 to get the first images that seemed to show the surfaces very clearly. However, it was not clear to what extent they really were able to image the surface, as there was no theory for the imaging and many uncertainties.

The new work has answered all these questions, Marks said, providing a definitive way of understanding the surfaces in detail. What was needed was to use a carefully controlled sample of strontium titanate and perform a large range of different types of imaging to unravel the precise details of how secondary electron images are produced.

“We started this work by investigating a well-studied material,” said Jim Ciston, a staff scientist at Lawrence Berkeley National Laboratory and the lead author of the paper, who obtained the experimental images. “This new technique is so powerful that we had to revise much of what was already thought to be well-known. This is an exciting prospect because the surface of every material can act as its own nanomaterial coating, which can greatly change the chemistry and behavior.”

“The beauty of the technique is that we can image surface atoms and bulk atoms simultaneously,” said Yimei Zhu, a scientist at Brookhaven National Laboratory. “Currently, no existing methods can achieve that.”

Les Allen, who led the theoretical and modeling aspects of the new imaging technique in Melbourne, said, “We now have a sophisticated understanding of what the images mean. It now will be full steam ahead to apply them to many different types of problems.”

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

Surface determination through atomically resolved secondary-electron imaging by J. Ciston, H. G. Brown, A. J. D’Alfonso, P. Koirala, C. Ophus, Y. Lin, Y. Suzuki, H. Inada, Y. Zhu, L. J. Allen, & L. D. Marks. Nature Communications 6, Article number: 7358 doi:10.1038/ncomms8358 Published 17 June 2015

This paper is open access.

Animation: art and science

Being in the process of developing an art/science piece involving poetry and visual metaphors as realized through video, I was quite fascinated to read about someone else’s process and issues in Stephen Curry’s and Drew Berry’s June 9, 2015 joint post on the Guardian science blogs (Note: Links have been removed),

Yesterday [June 8, 2015] I [Stephen Curry] was trying to figure out why it seems to be so difficult to connect to the biological molecules that we are made of – proteins, DNA and such like. My piece might have ended on a frustrated note but I have no wish to be negative, especially since the problem has only arisen because animators like Drew Berry are now able to use the results of structural biology to make quite exquisite movies of the molecules of life at work inside the cells of our bodies. As I was working though my difficulties, I wrote to ask Berry how he approached the task of representing molecular complexity in ways that would make sense to people. This is his considered and insightful reply:

“The goal of my [Drew Berry] work is to show non-experts – the general public aged 4 to 99, students of biology, journalists and politicians, and so on – what is being discovered in biology, in a format that is accessible, meaningful, and engaging. I hope that my work provides some sense of what biologists and medical researchers are discovering and thinking about, to provide the public with a framework of understanding to discuss these important new discoveries and the impact it will have on us as a society as we head into the future.

These passages, in particular, caught my attention as they are descriptive of the art and the science inherent in Berry’s work,

… I should avoid overstating how accurately I have depicted the reality of the molecular world. It is vastly messier, random and crowded, and it’s physical nature is unimaginably alien to our normal perception of the world around us. That said, my work is not intended to be a lab-bench-calculated model for research use, it is an impressionistic, artist-generated crude sketch of phenomena and structures science is measuring and discovering at the molecular scale.

… I would then assert that the animations are firmly founded on real data and are as accurate as I can possibly make them, while making them watchable and interpretable to a human audience. By far the largest portion of my time is spent conducting broad ranging literature reviews of the topic I am working on, gathering the fragments of data scattered throughout the journals, and holistically reconstructing what currently we know and do not know. Wherever data and models are available, I incorporate them directly into the construction of the animation, including molecular structures, dynamics simulations, speed measurements, and so on. My work is most akin to a ‘review’ paper in the literature, presented in visual form.

Here is one of the problems Berry and other animators struggle with,

… I am friends with the dozen or so people who are at the top of the game at creating biomedical animations (most have a PhD scientific background) and we all struggle with the problem of having a molecule arrive at a particular location from the thick molecular soup of the cytoplasm and not look directed. I can make the molecule wander around in a Brownian type manner, but for story telling and visual explanations, I need it to get to a certain point and do it’s thing at a certain time to move the story along. This can make it look determined and directed.

Berry also discusses the unexpected,

An unexpected outcome I stumbled across more than a decade ago is that the public loves it when ‘real time’ speeds are displayed and the structures and reactions are derived from research data. This takes a lot of time to build, but then the animations have a remarkable longevity of use and strongly resonate with the audience.

For the last excerpt from this essay, I include Berry’s description of one of his most challenging projects and the video he produced,

The most heavily researched and technically challenging animation I have ever built is the kinetochore which can be seen in the video below . The kinetochore is a gigantic structure that assembles on chromosomes just after they have been duplicated and helps them to be pulled apart during cell division (mitosis). It has about 200 proteins of which I depicted about 50. I gathered data from more than 180 scientific papers with everything built as accurately as possible with hundreds of little scientific details built into the structure and dynamics.”

There are more illustrations and one more video embedded along with more from Berry in the essay, which includes these biographical details (Note: Links have been removed),

Drew Berry is the Biomedical Animations Manager at the Walter and Eliza Hall Institute of Medical Research in Melbourne, Australia. @Stephen_Curry is a professor of structural biology at Imperial College [London, UK].

Memristor, memristor, you are popular

Regular readers know I have a long-standing interest in memristor and artificial brains. I have three memristor-related pieces of research,  published in the last month or so, for this post.

First, there’s some research into nano memory at RMIT University, Australia, and the University of California at Santa Barbara (UC Santa Barbara). From a May 12, 2015 news item on ScienceDaily,

RMIT University researchers have mimicked the way the human brain processes information with the development of an electronic long-term memory cell.

Researchers at the MicroNano Research Facility (MNRF) have built the one of the world’s first electronic multi-state memory cell which mirrors the brain’s ability to simultaneously process and store multiple strands of information.

The development brings them closer to imitating key electronic aspects of the human brain — a vital step towards creating a bionic brain — which could help unlock successful treatments for common neurological conditions such as Alzheimer’s and Parkinson’s diseases.

A May 11, 2015 RMIT University news release, which originated the news item, reveals more about the researchers’ excitement and about the research,

“This is the closest we have come to creating a brain-like system with memory that learns and stores analog information and is quick at retrieving this stored information,” Dr Sharath said.

“The human brain is an extremely complex analog computer… its evolution is based on its previous experiences, and up until now this functionality has not been able to be adequately reproduced with digital technology.”

The ability to create highly dense and ultra-fast analog memory cells paves the way for imitating highly sophisticated biological neural networks, he said.

The research builds on RMIT’s previous discovery where ultra-fast nano-scale memories were developed using a functional oxide material in the form of an ultra-thin film – 10,000 times thinner than a human hair.

Dr Hussein Nili, lead author of the study, said: “This new discovery is significant as it allows the multi-state cell to store and process information in the very same way that the brain does.

“Think of an old camera which could only take pictures in black and white. The same analogy applies here, rather than just black and white memories we now have memories in full color with shade, light and texture, it is a major step.”

While these new devices are able to store much more information than conventional digital memories (which store just 0s and 1s), it is their brain-like ability to remember and retain previous information that is exciting.

“We have now introduced controlled faults or defects in the oxide material along with the addition of metallic atoms, which unleashes the full potential of the ‘memristive’ effect – where the memory element’s behaviour is dependent on its past experiences,” Dr Nili said.

Nano-scale memories are precursors to the storage components of the complex artificial intelligence network needed to develop a bionic brain.

Dr Nili said the research had myriad practical applications including the potential for scientists to replicate the human brain outside of the body.

“If you could replicate a brain outside the body, it would minimise ethical issues involved in treating and experimenting on the brain which can lead to better understanding of neurological conditions,” Dr Nili said.

The research, supported by the Australian Research Council, was conducted in collaboration with the University of California Santa Barbara.

Here’s a link to and a citation for this memristive nano device,

Donor-Induced Performance Tuning of Amorphous SrTiO3 Memristive Nanodevices: Multistate Resistive Switching and Mechanical Tunability by  Hussein Nili, Sumeet Walia, Ahmad Esmaielzadeh Kandjani, Rajesh Ramanathan, Philipp Gutruf, Taimur Ahmed, Sivacarendran Balendhran, Vipul Bansal, Dmitri B. Strukov, Omid Kavehei, Madhu Bhaskaran, and Sharath Sriram. Advanced Functional Materials DOI: 10.1002/adfm.201501019 Article first published online: 14 APR 2015

© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

This paper is behind a paywall.

The second published piece of memristor-related research comes from a UC Santa Barbara and  Stony Brook University (New York state) team but is being publicized by UC Santa Barbara. From a May 11, 2015 news item on Nanowerk (Note: A link has been removed),

In what marks a significant step forward for artificial intelligence, researchers at UC Santa Barbara have demonstrated the functionality of a simple artificial neural circuit (Nature, “Training and operation of an integrated neuromorphic network based on metal-oxide memristors”). For the first time, a circuit of about 100 artificial synapses was proved to perform a simple version of a typical human task: image classification.

A May 11, 2015 UC Santa Barbara news release (also on EurekAlert)by Sonia Fernandez, which originated the news item, situates this development within the ‘artificial brain’ effort while describing it in more detail (Note: A link has been removed),

“It’s a small, but important step,” said Dmitri Strukov, a professor of electrical and computer engineering. With time and further progress, the circuitry may eventually be expanded and scaled to approach something like the human brain’s, which has 1015 (one quadrillion) synaptic connections.

For all its errors and potential for faultiness, the human brain remains a model of computational power and efficiency for engineers like Strukov and his colleagues, Mirko Prezioso, Farnood Merrikh-Bayat, Brian Hoskins and Gina Adam. That’s because the brain can accomplish certain functions in a fraction of a second what computers would require far more time and energy to perform.

… As you read this, your brain is making countless split-second decisions about the letters and symbols you see, classifying their shapes and relative positions to each other and deriving different levels of meaning through many channels of context, in as little time as it takes you to scan over this print. Change the font, or even the orientation of the letters, and it’s likely you would still be able to read this and derive the same meaning.

In the researchers’ demonstration, the circuit implementing the rudimentary artificial neural network was able to successfully classify three letters (“z”, “v” and “n”) by their images, each letter stylized in different ways or saturated with “noise”. In a process similar to how we humans pick our friends out from a crowd, or find the right key from a ring of similar keys, the simple neural circuitry was able to correctly classify the simple images.

“While the circuit was very small compared to practical networks, it is big enough to prove the concept of practicality,” said Merrikh-Bayat. According to Gina Adam, as interest grows in the technology, so will research momentum.

“And, as more solutions to the technological challenges are proposed the technology will be able to make it to the market sooner,” she said.

Key to this technology is the memristor (a combination of “memory” and “resistor”), an electronic component whose resistance changes depending on the direction of the flow of the electrical charge. Unlike conventional transistors, which rely on the drift and diffusion of electrons and their holes through semiconducting material, memristor operation is based on ionic movement, similar to the way human neural cells generate neural electrical signals.

“The memory state is stored as a specific concentration profile of defects that can be moved back and forth within the memristor,” said Strukov. The ionic memory mechanism brings several advantages over purely electron-based memories, which makes it very attractive for artificial neural network implementation, he added.

“For example, many different configurations of ionic profiles result in a continuum of memory states and hence analog memory functionality,” he said. “Ions are also much heavier than electrons and do not tunnel easily, which permits aggressive scaling of memristors without sacrificing analog properties.”

This is where analog memory trumps digital memory: In order to create the same human brain-type functionality with conventional technology, the resulting device would have to be enormous — loaded with multitudes of transistors that would require far more energy.

“Classical computers will always find an ineluctable limit to efficient brain-like computation in their very architecture,” said lead researcher Prezioso. “This memristor-based technology relies on a completely different way inspired by biological brain to carry on computation.”

To be able to approach functionality of the human brain, however, many more memristors would be required to build more complex neural networks to do the same kinds of things we can do with barely any effort and energy, such as identify different versions of the same thing or infer the presence or identity of an object not based on the object itself but on other things in a scene.

Potential applications already exist for this emerging technology, such as medical imaging, the improvement of navigation systems or even for searches based on images rather than on text. The energy-efficient compact circuitry the researchers are striving to create would also go a long way toward creating the kind of high-performance computers and memory storage devices users will continue to seek long after the proliferation of digital transistors predicted by Moore’s Law becomes too unwieldy for conventional electronics.

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

Training and operation of an integrated neuromorphic network based on metal-oxide memristors by M. Prezioso, F. Merrikh-Bayat, B. D. Hoskins, G. C. Adam, K. K. Likharev,    & D. B. Strukov. Nature 521, 61–64 (07 May 2015) doi:10.1038/nature14441

This paper is behind a paywall but a free preview is available through ReadCube Access.

The third and last piece of research, which is from Rice University, hasn’t received any publicity yet, unusual given Rice’s very active communications/media department. Here’s a link to and a citation for their memristor paper,

2D materials: Memristor goes two-dimensional by Jiangtan Yuan & Jun Lou. Nature Nanotechnology 10, 389–390 (2015) doi:10.1038/nnano.2015.94 Published online 07 May 2015

This paper is behind a paywall but a free preview is available through ReadCube Access.

Dexter Johnson has written up the RMIT research (his May 14, 2015 post on the Nanoclast blog on the IEEE [Institute of Electrical and Electronics Engineers] website). He linked it to research from Mark Hersam’s team at Northwestern University (my April 10, 2015 posting) on creating a three-terminal memristor enabling its use in complex electronics systems. Dexter strongly hints in his headline that these developments could lead to bionic brains.

For those who’d like more memristor information, this June 26, 2014 posting which brings together some developments at the University of Michigan and information about developments in the industrial sector is my suggestion for a starting point. Also, you may want to check out my material on HP Labs, especially prominent in the story due to the company’s 2008 ‘discovery’ of the memristor, described on a page in my Nanotech Mysteries wiki, and the controversy triggered by the company’s terminology (there’s more about the controversy in my April 7, 2010 interview with Forrest H Bennett III).

Changing the vibration of gold nanodisks (acoustic tuning) with light

A May 7, 2015 news item on phys.org describes research that could have a major impact on photonics applications,

In a study that could open doors for new applications of photonics from molecular sensing to wireless communications, Rice University [Texas, US] scientists have discovered a new method to tune the light-induced vibrations of nanoparticles through slight alterations to the surface to which the particles are attached.

n a study published online this week in Nature Communications, researchers at Rice’s Laboratory for Nanophotonics (LANP) used ultrafast laser pulses to induce the atoms in gold nanodisks to vibrate. These vibrational patterns, known as acoustic phonons, have a characteristic frequency that relates directly to the size of the nanoparticle. The researchers found they could fine-tune the acoustic response of the particle by varying the thickness of the material to which the nanodisks were attached.

A May 7, 2015 Rice University news release (also on EurekAlert), which originated the news item, expands on the theme (Note: A link has been removed),

Our results point toward a straightforward method for tuning the acoustic phonon frequency of a nanostructure in the gigahertz range by controlling the thickness of its adhesion layer,” said lead researcher Stephan Link, associate professor of chemistry and in electrical and computer engineering.

Light has no mass, but each photon that strikes an object imparts a miniscule amount of mechanical motion, thanks to a phenomenon known as radiation pressure. A branch of physics known as optomechanics has developed over the past decade to study and exploit radiation pressure for applications like gravity wave detection and low-temperature generation.

Link and colleagues at LANP specialize in another branch of science called plasmonics that is devoted to the study of light-activated nanostructures. Plasmons are waves of electrons that flow like a fluid across a metallic surface.

When a light pulse of a specific wavelength strikes a metal particle like the puck-shaped gold nanodisks in the LANP experiments, the light energy is converted into plasmons. These plasmons slosh across the surface of the particle with a characteristic frequency, in much the same way that each phonon has a characteristic vibrational frequency.

The study’s first author, Wei-Shun Chang, a postdoctoral researcher in Link’s lab, and graduate students Fangfang Wen and Man-Nung Su conducted a series of experiments that revealed a direct connection between the resonant frequencies of the plasmons and phonons in nanodisks that had been exposed to laser pulses.

“Heating nanostructures with a short light pulse launches acoustic phonons that depend sensitively on the structure’s dimensions,” Link said. “Thanks to advanced lithographic techniques, experimentalists can engineer plasmonic nanostructures with great precision. Based on our results, it appears that plasmonic nanostructures may present an interesting alternative to conventional optomechanical oscillators.”

Chang said plasmonics experts often rely on substrates when using electron-beam lithography to pattern plasmonic structures. For example, gold nanodisks like those used in the experiments will not stick to glass slides. But if a thin substrate of titanium or chromium is added to the glass, the disks will adhere and stay where they are placed.

“The substrate layer affects the mechanical properties of the nanostructure, but many questions remain as to how it does this,” Chang said. “Our experiments explored how the thickness of the substrate impacted properties like adhesion and phononic frequency.”

Link said the research was a collaborative effort involving research groups at Rice and the University of Melbourne in Victoria, Australia.

“Wei-Shun and Man-Nung from my lab did the ultrafast spectroscopy,” Link said. “Fangfang, who is in Naomi Halas’ group here at Rice, made the nanodisks. John Sader at the University of Melbourne, and his postdoc Debadi Chakraborty calculated the acoustic modes, and Yue Zhang, a Rice graduate student from Peter Nordlander’s group at Rice simulated the optical/plasmonic properties. Bo Shuang of the Landes’ research group at Rice contributed to the analysis of the experimental data.”

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

Tuning the acoustic frequency of a gold nanodisk through its adhesion layer by Wei-Shun Chang, Fangfang Wen, Debadi Chakraborty, Man-Nung Su, Yue Zhang, Bo Shuang, Peter Nordlander, John E. Sader, Naomi J. Halas, & Stephan Link. Nature Communications 6, Article number: 7022 doi:10.1038/ncomms8022 Published 05 May 2015

This paper is behind a paywall but a free preview is available vie ReadCube Access.

Nanotechnology risk perceptions in 2015 from Australia

I haven’t stumbled across a study on the perceptions of risk and nanotechnology in quite a while.  Before commenting on this latest research from the University of Sydney, here’s a link to and a citation for this new Australian study, which is an open access paper,

Perceptions of risk from nanotechnologies and trust in stakeholders: a cross sectional study of public, academic, government and business attitudes by Adam Capon, James Gillespie, Margaret Rolfe, and Wayne Smith. BMC Public Health 2015, 15:424 Published April 26, 2015  DOI: 10.1186/s12889-015-1795-1

According to the authors, this is the first study that surveyed the general public, academics, government officials, and business people with an eye to distinguishing any differences that might exist in their attitudes,

Our study proposes to extend and develop the knowledge base regarding perceptions of risk from nanotechnology and trust by stakeholders. To do this we use a standardised questionnaire across all the stakeholders surveyed. Secondly we examine stakeholder groups beyond highly published scientists and people attending nano conferences/working in nano laboratories that had previously been surveyed to include academic, government and business stakeholders. These three groups were chosen not just for their expertise, but because they represent the interplay of stakeholders most likely to shape policy in this field. Thirdly we seek and report on views of general risk perception (to health) and for specific products (food, cosmetics and sunscreens, medicines, pesticides, tennis racquets and computers) which broadly represent Australian regulatory arms [22]. Finally we explore several trust actors (health department, scientists, journalists and politicians), all of who have the ability to shape policy.

Our study aims to test six hypotheses. First, very little targeted research has been undertaken on differing stakeholder views of risks from nanotechnology. To explore this we hypothesise that public perceptions of risks from nanotechnology will be greater than those held by ‘experts’. Second, existing studies suggest that food and health applications of nanotechnology are likely to arouse more controversy [23]. We will test the hypothesis that the public, academics, government and business respondents will all perceive a higher level of risk in nanotechnologies that penetrate or have close and prolonged contact with the body. Three, there is inconsistent evidence that increased familiarity with nanotechnology is associated with differing perceptions of nanotechnologies [24]. Our third hypothesis proposes that public self-reported familiarity with nanotechnology will be associated with a reduction in risk perception. This relationship will be found with each of the nano products in the study. Four, the public holds less trust in the government agencies with responsibility for regulating nanotechnology than that expressed by people working in nanotechnology based industries/researching nanotechnology [23]. Our fourth hypothesis tests the evidence for this proposition. We hypothesise that the trust the public vests in scientists, the health department, journalists and politicians will be less than those held by business, academic, and government respondents who have an interest in nanotechnology.

The last two hypotheses expand on hypothesis four, examining the trust of the public in greater detail. Studies have shown that the Australian public are more likely to trust scientists and scientific institutions, followed by government agencies with industry and mass media holding the least amount of trust [25],[26]. In our fifth hypothesis we test the proposition that the public will have greatest trust in scientists, followed by the health department with trust in journalists and politicians below these two. Finally, public trust in business leaders [27], science and consumer protection agencies [28] and government agencies [29] have all been associated with decreased nano risk perception. Examining other stakeholders, the greater trust that people working in nanotechnology based industries or researching nanotechnology had with scientists and government agencies, the less they perceived risk from nanotechnology [23],[30]. Our sixth hypothesis is that significant negative associations exist between the trust the public vest in scientists, health department, journalists and politicians and perceived risk of nanotechnology, both when this risk is considered to health and across all risk applications. Understanding this relationship between trust and risk perception is an important avenue for risk communication and education.

As interesting as I find methodology I’m going to skip most of it and focus on the sample size and demographics,

The surveys consisted of 1355 public, 301 academic, 19 government and 21 business responses. Gender representation of the weighted public survey population was comparable to the June 2012 Australian population estimates of approximately 50% male and female. Gender representationa for academic and business responses was more likely to be male (≈70%) while the gender of government respondents was almost evenly balanced.

Three hundred and ninety eight public respondents (30%) were categorised as having no familiarity with nanotechnology, while 528 (39%) were categorised as having some familiarity and 422 (31%) as having moderate familiarity with nanotechnology.

Amongst the academic responses, the best represented area of research (38%) was in the field of nanomaterials. Nanocharacterisation, nanofabrication, nanobiotechnology/nanomedicine, nanoscale theory/computation, nanophotonics, and nanoelectronics/nanomagnetics represented between 15% to 4% per discipline in descending order. The least represented discipline was translational nanoresearch (2%), of which half were involved in nanotoxicology and the other either in ethical or social research on risk/public attitudes/public impact or did not provide a sub specialisation. Of the business responses the greatest percentage of business involvement was in nanomaterial manufacture, importation or research (33% – 23%). Importation of products containing nanomaterials, waste collection/processing and legal issues had little representation. The highest representation of government respondents was health and safety (37%) followed by communication/social impact (26%), business development (16%) and environment (11%).

The analysis of the results is well worth reading,

The Australian public perceives greater risks from manufactured nanomaterials and shows less trust in scientists and the health department to provide protection from possible health effects than academic, business and government stakeholders in the nanotechnology sector. Food applications and cosmetics/sunscreens loom high on the list of public concerns, although medicines and pesticides are also causes of public concern. Policy makers should be aware of these risk and trust disparities and address public sentiment by treating nanotechnology applications in the higher risk areas with greater caution. Risk communication is best placed in the hands of trusted scientists.

I am a little surprised that no mention was made of the nanosunscreen situation of 2012 where a research study found that 13% (originally reported as 17%) of Australians surveyed said they didn’t use any sunscreens due to fear of nanoparticles. I have the story in my Feb. 9, 2012 posting. Be sure to read through to the end as there were a couple of updates.

Gold detection down to the nanoparticle?

It appears that detecting gold, presumably for mining purposes, isn’t as easy as one might think especially at the nanoscale. Researchers at Australia’s University of Adelaide have devised a new method according to an April 29, 2015 news item on Nanowerk (Note: A link has been removed),

University of Adelaide researchers are developing a portable, highly sensitive method for gold detection that would allow mineral exploration companies to test for gold on-site at the drilling rig.

Using light in two different processes (fluorescence and absorption), the researchers from the University’s Institute for Photonics and Advanced Sensing (IPAS), have been able to detect gold nanoparticles at detection limits 100 times lower than achievable under current methods.

An April 29, 2015 University of Adelaide news release details Australia’s interest in gold and offers a high level explanation of the need for better gold detection (Note: Links have been removed),

Australia is the world’s second largest gold producer, worth $13 billion in export earnings.

“Gold is not just used for jewellery, it is in high demand for electronics and medical applications around the world, but exploration for gold is extremely challenging with a desire to detect very low concentrations of gold in host rocks,” says postdoctoral researcher Dr Agnieszka Zuber, working on the project with Associate Professor Heike Ebendorff-Heidepriem.

“The presence of gold deep underground is estimated by analysis of rock particles coming out of the drilling holes. But current portable methods for detection are not sensitive enough, and the more sensitive methods require some weeks before results are available.

“This easy-to-use sensor will allow fast detection right at the drill rig with the amount of gold determined within an hour, at much lower cost.”

The researchers have been able to detect less than 100 parts per billion of gold in water. They are now testing using samples of real rock with initial promising results. The work is funded by the Deep Exploration Technologies Cooperative Research Centre.

The gold detection project is one of a series of projects which will be presented at the IPAS Minerals and Energy Sector Workshop today [April 29, 2015], aimed at linking resources specific research to local companies.

You can find out more about the University of Adelaide’s Institute of Photonics and Advanced Sensing here.

Building architecture inspires new light-bending material

Usually, it’s nature which inspires scientists but not this time. Instead, a building in Canberra, Australia has provided the inspiration according to a March 24, 2015 news item on Nanowerk,

Physicists inspired by the radical shape of a Canberra building have created a new type of material which enables scientists to put a perfect bend in light.

The creation of a so-called topological insulator could transform the telecommunications industry’s drive to build an improved computer chip using light.

Leader of the team, Professor Yuri Kivshar from The Australian National University (ANU) said the revolutionary material might also be useful in microscopes, antenna design, and even quantum computers.

“There has been a hunt for similar materials in photonics based on large complicated structures,” said Professor Kivshar, who is the head of the Nonlinear Physics Centre in ANU Research School of Physics and Engineering.

“Instead we used a simple, small-scale zigzag structure to create a prototype of these novel materials with amazing properties.”

The structure was inspired by the Nishi building near ANU, which consists of rows of offset zigzag walls.

Here’s what the building looks like,

Caption: Alex Slobozhanyuk (L) and Andrey Miroshnichenko with models of their material structures in front of the Nishi building that inspired them. Credit: Stuart Hay, ANU

Caption: Alex Slobozhanyuk (L) and Andrey Miroshnichenko with models of their material structures in front of the Nishi building that inspired them.
Credit: Stuart Hay, ANU

A March 24, 2015 Australian National University press release, which originated the news item, goes on to describe topological insulators and what makes this ‘zigzag’ approach so exciting,

Topological insulators have been initially developed for electronics, and the possibility of building an optical counterpart is attracting a lot of attention.

The original zigzag structure of the material was suggested in the team’s earlier collaboration with Dr Alexander Poddubny, from Ioffe Institute in Russia, said PhD student Alexey Slobozhanyuk.

“The zigzag structure creates a coupling throughout the material that prevents light from travelling through its centre,” Mr Slobozhanyuk said.

“Instead light is channelled to the edges of the material, where it becomes completely localised by means of a kind of quantum entanglement known as topological order.”

Fellow researcher Dr Andrew Miroshnichenko said the building inspired the researchers to think of multiple zigzags.

“We had been searching for a new topology and one day I looked at the building and a bell went off in my brain,” said fellow researcher Dr Andrey Miroshnichenko.

“On the edges of such a material the light should travel completely unhindered, surfing around irregularities that would normally scatter the light.

“These materials will allow light to be bent around corners with no loss of signal,” he said.

The team showed that the exceptional attributes of the material are related to its structure, or topology, and not to the molecules it is made from.

“In our experiment we used an array of ceramic spheres, although the initial theoretical model used metallic subwavelength particles,” said Dr Miroshnichenko.

“Even though they are very different materials they gave the same result.”

In contrast with other international groups attempting to create topological insulators with large scale structures, the team used spheres that were smaller than the wavelength of the microwaves in their successful experiments.

Dr Poddubny devised the theory when he realised there was a direct analogy between quantum Kitaev’s model of Majorana fermions and optically coupled subwavelength scatterers.

Mr Slobozhanyuk said the team could control which parts of the material surface the light is channelled to by changing the polarisation of the light.

“This opens possibilities ranging from nanoscale light sources for enhancing microscopes, highly efficient antennas or even quantum computing,” he said.

“The structure couples the two sides of the material, so they could be used as entangled qubits for quantum computing.”

It would be nice to offer a link to a published paper but I cannot find one.

Looking for nano silicon at 10 nm (nanometres)

I received this request from Greg Packer on March 17, 2015,

Dear Sir we are looking for suppliers of a small qty say 5 kilo of nano silicon 10nm for hydrogen production with water for testing of a new producť designed fòr Ìndia.If you can help please ĺet us know plus the cost we are on the Gold Coast Qld
Thanks Greg Packer. 0403159635

As the request was in a comment to a post from 2010 I’m not sure how many people would see it and so have placed it here. The Gold Coast he is referring to is in Queensland, Australia.

To be clear, I do not know Mr. Packer and am not familiar with the product or his company but if you’re selling, it never hurts to check these things out.

How geckos self-clean, even in dusty environments

An Australian research team claims a world first with regard to ‘gecko research’ according to a March 16, 2014 news item on ScienceDaily,

In a world first, a research team including James Cook University [JCU] scientists has discovered how geckos manage to stay clean, even in dusty deserts.

The process, described in Interface, a journal of the Royal Society, may also turn out to have important human applications.

JCU’s Professor Lin Schwarzkopf said the group found that tiny droplets of water on geckos, for instance from condensing dew, come into contact with hundreds of thousands of extremely small hair-like spines that cover the animals’ bodies.

A March 16, 2015 JCU press release (also on EurekAlert), which originated the news item, provides more detail,

“If you have seen how drops of water roll off a car after it is waxed, or off a couch that’s had protective spray used on it, you’ve seen the process happening,” she said. “The wax and spray make the surface very bumpy at micro and nano levels, and the water droplets remain as little balls, which roll easily and come off with gravity or even a slight wind.”

The geckos’ hair-like spines trap pockets of air and work on the same principle, but have an even more dramatic effect. Through a scanning electron microscope, tiny water droplets can be seen rolling into each other and jumping like popcorn off the skin of the animal as they merge and release energy.

Scientists were aware that hydrophobic surfaces repelled water, and that the rolling droplets helped clean the surfaces of leaves and insects, but this is the first time it has been documented in a vertebrate animal. Box-patterned geckos live in semi-arid habitats, with little rain but may have dew forming on them when the temperature drops overnight.

Professor Schwarzkopf said the process may help geckos keep clean, as the water can carry small particles of dust and dirt away from their body. “They tend to live in dry environments where they can’t depend on it raining, and this keeps process them clean,” she said.

She said there were possible applications for marine-based electronics that have to shed water quickly in use and for possible “superhydrophobic” clothing that would not get wet or dirty and would never need washing.

I’ve been reading about self-cleaning products for years now. (sigh) Where are they? Despite this momentary lapse into sighing and wailing, I am much encouraged that scientists are still trying to figure out how to create self-cleaning products.

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

Removal mechanisms of dew via self-propulsion off the gecko skin by Gregory S. Watson, Lin Schwarzkopf, Bronwen W. Cribb, Sverre Myhra, Marty Gellender, and Jolanta A. Watson.
Interface, April 2015, Volume: 12 Issue: 105 DOI: 10.1098/rsif.2014.1396 Published 11 March 2015

This paper is open access.