Valleytronics; disruptive diagnostics; IoT data framework.
Encoding electrons with valleytronics
Researchers at the U.S. Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a new type of electronics that could lead to faster and more efficient computer logic systems and data storage chips in next-generation devices that they refer to as “valleytronics.”
Specifically, the team has experimentally demonstrated the ability to electrically generate and control valley electrons in a 2D semiconductor.
Valley electrons are named thusly because they carry a valley “degree of freedom,” which is a new way to harness electrons for information processing in addition to utilizing an electron’s other degrees of freedom, which are quantum spin in spintronic devices and charge in conventional electronics, the researchers explained.
Further, the electronic valleys refer to the energy peaks and valleys in electronic bands: a 2D semiconductor called transition metal dichalcogenide (TMDC) has two distinguishable valleys of opposite spin and momentum, and because of this, the material is suitable for valleytronic devices, in which information processing and storage could be carried out by selectively populating one valley or another.
And while developing valleytronic devices requires the electrical control over the population of valley electrons, which has proven very challenging to achieve so far, the Berkeley Lab researchers have experimentally demonstrated the ability to electrically generate and control valley electrons in TMDCs. They said this is an especially important advance because TMDCs are considered to be more device ready than other semiconductors that exhibit valleytronic properties.
It is believed this research could lead to a new type of electronics that utilize all three degrees of freedom—charge, spin, and valley, which together could encode an electron with eight bits of information instead of two in today’s electronics meaning that future chips could process more information with less power, enabling faster and more energy efficient computing technologies.
In an effort to radically change the way health care is approached, Arizona State University researchers have created a diagnostic chip that takes a snapshot of a person’s immune system that provides an in-depth picture of a person’s health given that some of the leading causes of death—both infectious and chronic diseases like cancer—give rise to immune responses fairly early in the course of disease.
As part of their work, the team spun out HealthTell, a startup company to commercialize the technology.
For HealthTell’s tests, only a single microliter—or 1/20 of a drop—of blood is needed. This is spotted onto a piece of filter paper and dropped off in the mail. At HealthTell, the blood is diluted and put on a piece of a silicon wafer.
Interestingly, the same chip can be used for all diseases in all species. It detects any type of antibody. There is no sample preparation. Samples up to 20 years old can be used, and it is 10 to 100 times more sensitive than a standard tests on the market.
IoT data analytics framework
To realize the potential of the IoT, programmers need tools that make it easier to create applications that combine devices and the cloud so to this end, Rensselaer Polytechnic Institute researchers are building tools and developing a framework that developers can use to easily perform data analytics over a multitude of devices.
The team said rather than developers designing custom algorithms for each network of devices, they are going to build a framework of software that sits on all these devices and the cloud that will automatically manage communication between the devices and deal with device and network failures, so that the developer only needs to provide a little bit of code to say this is how it should work, and the framework will take care of the rest.
The project is an extension of Rensselaer’s current research into enhancing the utility of sensors embedded in automobiles, by creating real-time networks that allow automobiles to pool their individual information into a larger shared picture of driving conditions in the area.