Why memristors make good artificial synapses

An international team of researchers has worked out why a ferroelectric memristor does a good job at mimicking an important function of the brain. The brain learns by reconfiguring the strengths of the connections (synapses) between neurons and in a process that is called synaptic plasticity – and researchers are keen on creating artificial brains that learn in a similar way. Vincent Garcia and colleagues at CNRS, Thales, and several universities in France, the US and Switzerland have studied synapses that are based on ferroelectric tunnel junctions (FTJs) that adhere to a biological learning rule called spike-timing-dependent plasticity (STDP). Each FTJ measures less than one micron across and comprises a thin ferroelectric layer sandwiched between two electrodes. The FTJs operate as memristors, whereby the resistance of the layer can be tuned using voltage pulses similar to those in neurons. If the resistance is low the synaptic connection will be strong, and if the resistance is high the connection will be weak. This capacity to adapt its resistance enables the synapse to learn. While FTPs are used as artificial synapses in many laboratories, exactly how they function was not well understood. Now, Garcia and colleagues claim to be the first to have developed a physical model that describes how the artificial synapses work. Using a combination of experimental measurements they have shown that changes in the resistance of the FTJs are brought about by the nucleation-dominated reversal of ferromagnetic domains. Writing in Nature Communications, the team says it was able to simulate the behaviour of an artificial neural network based on an array of FTJs and show that it should be capable of learning to recognise patterns. Garcia and colleagues now plan to use the FTPs to develop a camera that can perform real-time shape recognition. There is more about artificial neural networks in “Smarter machines” (subscription required).

Graphene oxide turns seawater to drinking water

Graphene-oxide sieves have turned seawater into drinking water. Over the past five years, a team at the University of Manchester in the UK has studied using graphene and graphene oxide as a way of removing salt from seawater, with the aim to replace current, energy-intensive methods. While plain graphene is just a single layer of carbon atoms, graphene oxide (GO) is covered with molecules such as hydroxyl groups. As graphene is impermeable to gases and liquids, holes have to be drilled through to create a sieve. “But if the hole size is larger than one nanometre, the salts go through the hole,” explains team member Rahul Nair, “You have to make a membrane with a very uniform less-than-one-nanometre hole size to make it useful for desalination. It is a really challenging job.” In contrast, GO is permeable and easier to make. Nair and colleagues have previously found that GO can remove small nanoparticles, organic molecules and large salts, however, as with graphene, common salt (sodium chloride) has proven more difficult because it is smaller. Now, the researchers have demonstrated that walls of epoxy resin on either side of the GO membrane prevent it’s natural expansion in water, and this has allowed them to create a sieve with only 7.8 Å spacing, rather than 9.8 Å. These tiny pores through the membrane mean that water molecules can still penetrate but salt cannot. The group hopes the current work, presented in Nature Nanotechnology, may lead to a cheap and efficient method for producing clean drinking water from seawater.

Surface tension of water can be much greater than previously thought

The surface tension of water can be much higher than the currently accepted value. That is the surprising conclusion of Ines Hauner and Daniel Bonn of the University of Amsterdam and colleagues in the Netherlands, France and Australia, who measured the surface tension of newly created water–air interfaces. They found that at times up to about 1 ms after the new interface is created, the surface tension of the water can be as much as 25% greater than the accepted room-temperature value of 72.75 mN/m. This could have important implications for industrial processes such as inkjet printing, which rely on the rapid formation of tiny droplets – a process that is governed by surface tension. The team made its discovery using a high-speed camera to watch the release of water droplets from a tap. This involves the formation of a liquid neck on which the drops hangs before breaking away – and by analysing this process on a sub-millisecond timescale, the researchers were able to calculate the surface tension. The study is described in The Journal of Physical Chemistry Letters.

 

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