Electronic synapses; nanotube forests; better TB tests through video game.
Neural network synapses
In a development that could potentially be used as a basis for the hardware implementation of artificial neural networks, Moscow Institute of Physics and Technology (MIPT) researchers have created prototypes of electronic synapses based on ultra-thin films of hafnium oxide (HfO2).
The team made the HfO2-based memristors measuring just 40×40 nm2, which exhibit properties similar to biological synapses using newly developed technology. The memristors were integrated in matrices, which in the future may be used to design computers that function similar to biological neural networks.
Memristors (resistors with memory) devices are able to change their state (conductivity) depending on the charge passing through them, and therefore have a memory of their history. In this case, the researchers used devices based on thin-film hafnium oxide, a material that is already used in the production of modern processors, which means that this new lab technology could, if required, easily be used in industrial processes, they said.
In a simpler version, memristors are promising binary non-volatile memory cells, in which information is written by switching the electric resistance – from high to low and back again. The team is trying to demonstrate much more complex functions of memristors, and prove that they behave similar to biological synapses.
Given that synapses are the key to learning and memory, this is also why this system forms the basis of the concept of convolutional neural networks in computing architectures.
The researchers reminded that a synapse is point of connection between neurons, the main function of which is to transmit a signal from one neuron to another. Each neuron may have thousands of synapses, i.e. connect with a large number of other neurons. This means that information can be processed in parallel, rather than sequentially (as in modern computers). This is the reason why “living” neural networks are so immensely effective both in terms of speed and energy consumption in solving large range of tasks, such as image / voice recognition, etc. Over time, synapses may change their “weight,” i.e. their ability to transmit a signal. This property is believed to be the key to understanding the learning and memory functions of the brain. From the physical point of view, synaptic “memory” and “learning” in the brain can be interpreted as follows: the neural connection possesses a certain “conductivity”, which is determined by the previous “history” of signals that have passed through the connection. If a synapse transmits a signal from one neuron to another, we can say that it has high “conductivity”, and if it does not, we say it has low “conductivity.” However, synapses do not simply function in on/off mode; they can have any intermediate “weight” (intermediate conductivity value). Accordingly, if we want to simulate them using certain devices, these devices will also have to have analogous characteristics, they explained.
On-demand nanotube forests
Purdue University researchers have created a system that uses a laser and electrical current to precisely position and align carbon nanotubes, which represents a potential new tool for creating electronic devices out of the tiny fibers.
Because carbon nanotubes have unique thermal and electrical properties, they may have future applications in electronic cooling and as devices in microchips, sensors and circuits, the team said. Being able to orient the carbon nanotubes in the same direction and precisely position them could allow these nanostructures to be used in such applications.
It is difficult, however, to manipulate something so small that thousands of them would fit within the diameter of a single strand of hair, but the researchers said carbon nanotubes can be assembled using this technique called rapid electrokinetic patterning (REP) into complicated structures.
REP uses two parallel electrodes made of indium tin oxide, a transparent and electrically conductive material. The nanotubes are arranged randomly while suspended in deionized water. Applying an electric field causes them to orient vertically. Then an infrared laser heats the fluid, producing a doughnut-shaped vortex of circulating liquid between the two electrodes. This vortex enables the researchers to move the nanotubes and reposition them.
When they apply the electric field, they are immediately oriented vertically, and then when the laser is applied, it starts a vortex, that sweeps them into little nanotube forests.
The researchers assert this technique overcomes limitations of other methods for manipulating particles measured on the scale of nanometers, or billionths of a meter. In this study, the procedure was used for multiwalled carbon nanotubes, which are rolled-up ultrathin sheets of carbon called graphene. But using this technique other nanoparticles such as nanowires and nanorods can be similarly positioned and fixed in vertical orientation.
Building better TB tests with video game
Stanford University School of Medicine researchers are releasing a new version of a web-based video game called Eterna that will harness the creative brain power of thousands of nonscientist players.
They said the goal in coming months is for Eterna Medicine players to design a molecule that could help spur the development of a new tuberculosis test, given that the disease infects a third of the world’s population and kills about 1.5 million each year but health organizations lack a simple-to-use blood test that can detect active infection in many patients, especially in remote villages.
Like a previous iteration of the game, the new version of Eterna challenges players to build molecules of RNA with increasingly difficult-to-design shapes because these molecules can be useful to biomedical researchers.
Eterna, the first version of the video game, was launched five years ago as a way to let non-scientists design potentially useful biomolecules that are stable enough to function inside a living cell. Over the years, the players have become more and more expert in designing complex RNA molecules. They are so good at it now that the players recently co-authored an article in the Journal of Molecular Biology describing a set of rules for predicting how difficult it will be to build a given RNA molecule.