Tag Archives: Swiss Federal Institute of Technology in Lausanne

Identifying performance problems in nanoresonators

Use of nanoelectromechanical systems (NEMS) can now be maximised due to a technique developed by researchers at the Commissariat a l’Energie Atomique (CEA) and the University of Grenoble-Alpes (France). From a March 7, 2016 news item on ScienceDaily,

A joint CEA / University of Grenoble-Alpes research team, together with their international partners, have developed a diagnostic technique capable of identifying performance problems in nanoresonators, a type of nanodetector used in research and industry. These nanoelectromechanical systems, or NEMS, have never been used to their maximum capabilities. The detection limits observed in practice have always been well below the theoretical limit and, until now, this difference has remained unexplained. Using a totally new approach, the researchers have now succeeded in evaluating and explaining this phenomenon. Their results, described in the February 29 [2016] issue of Nature Nanotechnology, should now make it possible to find ways of overcoming this performance shortfall.

A Feb. 29, 2016 CEA press release, which originated the news item, provides more detail about NEMS and about the new technique,

NEMS have many applications, including the measurement of mass or force. Like a tiny violin string, a nanoresonator vibrates at a precise resonant frequency. This frequency changes if gas molecules or biological particles settle on the nanoresonator surface. This change in frequency can then be used to detect or identify the substance, enabling a medical diagnosis, for example. The extremely small dimensions of these devices (less than one millionth of a meter) make the detectors highly sensitive.

However, this resolution is constrained by a detection limit. Background noise is present in addition to the wanted measurement signal. Researchers have always considered this background noise to be an intrinsic characteristic of these systems (see Figure 2 [not reproduced here]). Despite the noise levels being significantly greater than predicted by theory, the impossibility of understanding the underlying phenomena has, until now, led the research community to ignore them.

The CEA-Leti research team and their partners reviewed all the frequency stability measurements in the literature, and identified a difference of several orders of magnitude between the accepted theoretical limits and experimental measurements.

In addition to evaluating this shortfall, the researchers also developed a diagnostic technique that could be applied to each individual nanoresonator, using their own high-purity monocrystalline silicon resonators to investigate the problem.

The resonant frequency of a nanoresonator is determined by the geometry of the resonator and the type of material used in its manufacture. It is therefore theoretically fixed. By forcing the resonator to vibrate at defined frequencies close to the resonant frequency, the CEA-Leti researchers have been able to demonstrate a secondary effect that interferes with the resolution of the system and its detection limit in addition to the background noise. This effect causes slight variations in the resonant frequency. These fluctuations in the resonant frequency result from the extreme sensitivity of these systems. While capable of detecting tiny changes in mass and force, they are also very sensitive to minute variations in temperature and the movements of molecules on their surface. At the nano scale, these parameters cannot be ignored as they impose a significant limit on the performance of nanoresonators. For example, a tiny change in temperature can change the parameters of the device material, and hence its frequency. These variations can be rapid and random.

The experimental technique developed by the team makes it possible to evaluate the loss of resolution and to determine whether it is caused by the intrinsic limits of the system or by a secondary fluctuation that can therefore by corrected. A patent has been applied for covering this technique. The research team has also shown that none of the theoretical hypotheses so far advanced to explain these fluctuations in the resonant frequency can currently explain the observed level of variation.

The research team will therefore continue experimental work to explore the physical origin of these fluctuations, with the aim of achieving a significant improvement in the performance of nanoresonators.

The Swiss Federal Institute of Technology in Lausanne, the Indian Institute of Science in Bangalore, and the California Institute of Technology (USA) have also participated in this study. The authors have received funding from the Leti Carnot Institute (NEMS-MS project) and the European Union (ERC Consolidator Grant – Enlightened project).

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

Frequency fluctuations in silicon nanoresonators by Marc Sansa, Eric Sage, Elizabeth C. Bullard, Marc Gély, Thomas Alava, Eric Colinet, Akshay K. Naik, Luis Guillermo Villanueva, Laurent Duraffourg, Michael L. Roukes, Guillaume Jourdan & Sébastien Hentz. Nature Nanotechnology (2016) doi:10.1038/nnano.2016.19 Published online 29 February 2016

This paper is behind a paywall.

University of Waterloo researchers use 2.5M (virtual) neurons to simulate a brain

I hinted about some related work at the University of Waterloo earlier this week in my Nov. 26, 2012 posting (Existential risk) about a proposed centre at the University of Cambridge which would be tasked with examining possible risks associated with ‘ultra intelligent machines’.  Today (Science (magazine) published an article about SPAUN (Semantic Pointer Architecture Unified Network) [behind a paywall])and its ability to solve simple arithmetic and perform other tasks as well.

Ed Yong writing for Nature magazine (Simulated brain scores top test marks, Nov. 29, 2012) offers this description,

Spaun sees a series of digits: 1 2 3; 5 6 7; 3 4 ?. Its neurons fire, and it calculates the next logical number in the sequence. It scrawls out a 5, in legible if messy writing.

This is an unremarkable feat for a human, but Spaun is actually a simulated brain. It contains2.5 millionvirtual neurons — many fewer than the 86 billion in the average human head, but enough to recognize lists of numbers, do simple arithmetic and solve reasoning problems.

Here’s a video demonstration, from the University of Waterloo’s Nengo Neural Simulator home page,

The University of Waterloo’s Nov. 29, 2012 news release offers more technical detail,

… The model captures biological details of each neuron, including which neurotransmitters are used, how voltages are generated in the cell, and how they communicate. Spaun uses this network of neurons to process visual images in order to control an arm that draws Spaun’s answers to perceptual, cognitive and motor tasks. …

“This is the first model that begins to get at how our brains can perform a wide variety of tasks in a flexible manner—how the brain coordinates the flow of information between different areas to exhibit complex behaviour,” said Professor Chris Eliasmith, Director of the Centre for Theoretical Neuroscience at Waterloo. He is Canada Research Chair in Theoretical Neuroscience, and professor in Waterloo’s Department of Philosophy and Department of Systems Design Engineering.

Unlike other large brain models, Spaun can perform several tasks. Researchers can show patterns of digits and letters the model’s eye, which it then processes, causing it to write its responses to any of eight tasks.  And, just like the human brain, it can shift from task to task, recognizing an object one moment and memorizing a list of numbers the next. [emphasis mine] Because of its biological underpinnings, Spaun can also be used to understand how changes to the brain affect changes to behaviour.

“In related work, we have shown how the loss of neurons with aging leads to decreased performance on cognitive tests,” said Eliasmith. “More generally, we can test our hypotheses about how the brain works, resulting in a better understanding of the effects of drugs or damage to the brain.”

In addition, the model provides new insights into the sorts of algorithms that might be useful for improving machine intelligence. [emphasis mine] For instance, it suggests new methods for controlling the flow of information through a large system attempting to solve challenging cognitive tasks.

Laura Sanders’ Nov. 29, 2012 article for ScienceNews suggests that there is some controversy as to whether or not SPAUN does resemble a human brain,

… Henry Markram, who leads a different project to reconstruct the human brain called the Blue Brain, questions whether Spaun really captures human brain behavior. Because Spaun’s design ignores some important neural properties, it’s unlikely to reveal anything about the brain’s mechanics, says Markram, of the Swiss Federal Institute of Technology in Lausanne. “It is not a brain model.”

Personally, I have a little difficulty seeing lines of code as ever being able to truly simulate brain activity. I think the notion of moving to something simpler (using fewer neurons as the Eliasmith team does) is a move in the right direction but I’m still more interested in devices such as the memristor and the electrochemical atomic switch and their potential.

Blue Brain Project

Memristor and artificial synapses in my April 19, 2012 posting

Atomic or electrochemical atomic switches and neuromorphic engineering briefly mentioned (scroll 1/2 way down) in my Oct. 17, 2011 posting.

ETA Dec. 19, 2012: There was an AMA (ask me anything) session on Reddit with the SPAUN team in early December, if you’re interested, you can still access the questions and answers,

We are the computational neuroscientists behind the world’s largest functional brain model