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Physical Measurement Laboratory / Nanoscale Device Characterization Division

Alternative Computing Group

Projects/Programs

Displaying 1 - 13 of 13
Microscope image of a crossbar array

Hardware Accelerators for Neural Networks

Ongoing
One promising candidate for building a hardware accelerator comes from the field of spintronics, where information is carried by electronic spin rather than charge. Magnetic tunnel junctions are particularly suited because of their multifunctionality and compatibility with standard integrated
Temporal Chip

Hardware Accelerators for Statistical Computing

Ongoing
Finding good solutions to many hard problems, like combinatorial optimization and traveling salesman problems, counterintuitively requires making the estimated solution worse before making it better. This situation results from many hard problems having many “solutions” that cannot be improved
Small array of transistors designed for single device integration.

Integrated CMOS Testbeds for Nanoelectronics and Machine Learning

Ongoing
The increasingly complex device requirements for next-generation computing architectures such as neuromorphic computing or nanoelectronic machine learning accelerators present challenges for researchers across the spectrum of institutions, from small businesses and universities to government
Crossbar Memory Arrays

Integrated Testbeds for Advanced Metrology

Ongoing
Crossbar Memory Arrays An especially prolific structure in memory architectures aimed at accelerating neural network operation is the crossbar array (Fig. 1). We produce medium-scale arrays that hold up to 20,000 nanodevices which can be characterized, read from, and written to individually or in
Layout of the Nanotechnology Xccelerator Reticle with 30 unique tiles occupying 41 different slots within the reticle.

The Nanotechnology Xccelerator

Ongoing
The Nanotechnology Xccelerator was announced on September 13, 2022 and was officially accepted for production at Skywater Technology Foundry using the Sky130 technology in Q1 2024. Sky130, which comes in both a conventional and open-source process design kit, is a 5-metal layer process. To
EBIC Current

Neuromorphic Device Measurements

Ongoing
One type of device that is emerging as an attractive artificial synapse is the resistive switch, or memristor. These devices, which usually consist of a thin layer of oxide between two electrodes, have conductivity that depends on their history of applied voltage, and thus have highly nonlinear
Picture of magnetic tunnel junction

Novel Hardware for Alternative Computing

Ongoing
Magnetic tunnel junctions Magnetic tunnel junctions (see Fig. 1) consist of two thin films of a ferromagnetic material separated by a few atomic layers of an insulating material.  The insulator is so thin that electrons can tunnel quantum mechanically through it. The rate at which the electrons
schematic of the MOTIS ion beam source

Novel Sources for Focused-ion Beams

Completed
Commercial focused ion beams (FIBs) are used in a wide variety of applications. For example, they serve as diagnostic tools, slicing through a nanodevice to expose its internal structure. They can also shape nanoscale materials either by adding atoms to a structure or by shaving them off. And they
The Daffodil Board

Prototyping Platforms for Emerging Technologies

Ongoing
Emerging technologies aim to overcome traditional memory limitations with higher density, lower power consumption, faster read/write speeds, better endurance, and lower cost [2]. Many new candidate memory elements are analog or stochastic, requiring new testing infrastructure, and the context of
Schematic of device structure designed to utilize novel spin current generation in a ferromagnet (FM) to achieve electrical switching of a perpendicularly magnetized FM layer

Spin-orbit interaction in devices and quantum materials

Ongoing
The spin degree of freedom can provide a basis for next-generation electronic devices. Spintronic devices typically include materials with magnetic ordering, such as ferromagnets or antiferromagnets. The state of the magnetization influences charge and spin current through an effect known as
Fig. 1. Die containing 285 superparamagnetic tunnel junctions.

Spintronics for Neuromorphic Computing

Ongoing
Magnetic tunnel junctions (see Fig. 1) consist of two thin films of ferromagnetic material separated by a few atomic layers of an insulating material. The insulator is so thin that electrons can tunnel quantum mechanically through it. The rate at which the electrons tunnel is affected by the
Fig. 1. Time re-Envisioned: Not a biproduct of computation but the domain in which information is encoded. Leads to different mathematical functions becoming energy efficient primitives.

Temporal Computing

Ongoing
In standard integrated circuits, information that is coded as ones and zeros is implemented by voltages on wires being high or low. The circuits consume energy during transitions between these voltages. Binary numbers have a voltage per bit so there are a lot of transitions each time a number
A current (white arrow) flowing through a tantalum film generates a current of spins (dark blue arrows) that impinges on the ferromagnetic cobalt iron boron layer and causes the magnetization (gold arrow) to charge directions (light blue arrow).

Theory of Spin-Orbit Torque

Completed
A ferromagnetic material such as iron acquires its magnetization because the magnetic orientation of its constituent atoms all line up in the same way. Because individual electrons also have an intrinsic magnetic moment – which is often referred to as the electron “spin” - they can interact with