Memory device breaks high-temperature performance record – Physics World

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A memory device that can operate at temperatures over 700 °C could enable electronic systems to withstand harsh conditions with less need for cooling. The device, which is a memristor based on graphene, tungsten and a hafnium oxide ceramic, can store data for over 50 hours, has a working voltage of just 1.5 V, and is robust to more than 10⁹ switching cycles. It also has a high switching speed of just tens of nanoseconds, according to its developers at the University of Southern California (USC), US.
“Our work provides one of the most critical electronic components – memory – for a wide range of applications, particularly in extreme environments,” says Joshua Yang, who directs USC’s Center On Neuromorphic Computing undeR ExTreme Environments (CONCRETE). “These include space exploration, deep-Earth drilling (for geothermal energy) and nuclear and fusion energy plants in which intense heat is generated.”
Heat-tolerant electronics could also dramatically reduce the need for energy-intensive cooling systems, cutting both power consumption and fan noise, Yang adds. “Our work also shows that these devices require significantly lower voltage and current to operate at elevated temperatures – meaning higher ambient temperature can actually improve energy efficiency of computing systems.”
Rather than being fixed, the resistance of a memristor (or memory-resistor to give it its full name) changes depending on the current or voltage previously applied to it. This means that specific resistances can be programmed into the devices and subsequently stored. Importantly, the “remembered” value of the resistive state persists even when the power is switched off, making it a non-volatile form of electronic memory.
Memristors are also capable of processing large amounts of data in parallel, making them faster and more energy-efficient than conventional memories for certain calculations such as matrix-vector multiplication. They are therefore useful for in-memory computer technologies, including those that are now routinely employed in artificial intelligence (AI) hardware.
The memristor described in the new CONCRETE Center study consists of a hafnium oxide (HfO₂) layer sandwiched between two electrodes: a tungsten one on top and a graphene one on the bottom. Tungsten has the highest melting point of any metallic element, and the study’s first author, Jian Zhao, notes that graphene (a sheet of carbon just one atom thick) can also withstand high temperatures without degrading. Nevertheless, Yang says they didn’t specifically set out to make a super-high temperature device.
“As often in science, this work originated from an unexpected discovery,” he explains. “We identified a material stack with significantly higher temperature tolerance while investigating something else completely – namely trying to build a different kind of device using graphene.”
Understanding why this stack could withstand such high temperatures and validating their hypotheses took considerable effort, Yang tells Physics World. The team used a combination of advanced electron microscopy, spectroscopy and first-principles calculations to work out the physical mechanisms behind the process, he adds.
In conventional ceramic-based memristors, like those with a platinum bottom electrode, high temperatures cause the metal atoms from the top electrode to migrate through the ceramic layer until they reach the bottom electrode. When this happens, the two electrodes permanently connect and the devices short-circuit.
Memristive synapses could reduce AI energy consumption
In the USC team’s memristor, though, this simply wasn’t happening. “Graphene puts an end to this process,” Yang explains. “Tungsten atoms still drift towards the graphene electrode as expected, but because of its surface chemistry and structure they cannot anchor onto it. These atoms therefore end up migrating away from the electrode, so avoiding short-circuiting and device failure.”
The researchers, who report their work in Science, say that one future research direction might be to search for materials that have a similar surface chemistry to graphene, but are easier to handle. Their next goal, which they acknowledge will be challenging, is to integrate their high-temperature memristors with logic devices (such as those based on SiC substrates) that can also withstand extreme temperatures.
To advance their memristor technology, Yang and his colleagues Glenn Ge, Miao Hu and Qiangfei Xia have founded a start-up company, Tetramem Inc., focused on developing memristor-based machine learning/AI accelerators. Though scaling up their devices will take time – the current examples were made by hand in the lab at the sub-microscale – Yang says that creating high-operating-temperature accelerators could enable intelligent computing in extreme environments, including space applications or datacentres.
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