Microelectronics Projects | Argonne National Laboratory

Argonne is well equipped in terms of expertise and capabilities required for long-term, future microelectronics science. This ranges from Argonne’s activities in the software and architecture area, to materials, physics and devices.

Argonne projects include:

Imaging Memristive Behavior with Operando X-ray Microscopy

Neuromorphic computing and memristive devices may provide a means for achieving faster and more efficient computations than conventional computers.

Argonne National Laboratory

Layered transition metal dichalcogenide barriers for interconnects

We are exploring ultra-thin layered materials grown conformally using atomic layer deposition and etching as metal diffusion barriers for 3D integration in microelectronic devices.

Argonne National Laboratory

Low-Power Printable Transistors Enabled by Novel Redox Gate Materials

We are developing redox gate and channel materials that can operate beyond the electrostatic doping limitation while the charge carriers are still electrons or holes to achieve printable transistors operating at sub-volt gate voltages.

Argonne National Laboratory

Neuromorphic Computing Based on Novel Electrochemical Transistors

This project involves the co-design of brain-inspired learning devices with organic material.

Argonne National Laboratory

Pushing computing onto detector silicon

With the availability of advanced microelectronics technology nodes, more digital functionality from the computing domains can be integrated directly into detector silicon to increase data velocity.

Argonne National Laboratory

Recycling Heterostructures to Upcycle Microelectronics

A remarkable synthesis strategy has emerged allowing the growth of 2D single crystals on graphene that can be “stacked” atop each other to form a new pseudo-3D material.

Argonne National Laboratory

Ultra-dense, near perfect, atomic and synaptic memory

Our goal is to develop the scientific understanding and carry out the discovery science required to build ultra-dense, fast, DNA-class memory and synaptic memory that will be used in neuromorphic engines that can approach biological energy efficiencies.

Materials Science

Threadwork

Threadwork is an innovative co-design approach that seeks to transform the process by which we conduct microelectronics research.