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Katherine Derbyshire

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Katherine Derbyshire is a technical editor at Semiconductor Engineering.

Author's Latest Posts

Interest Grows In Ferroelectric Devices
By Katherine Derbyshire - 27 Dec, 2018 - Comments: 0

Ferroelectric FETs and memories are beginning to show promise as researchers begin developing and testing next-generation transistors. One measure of the efficiency of a transistor is the subthreshold swing, which is the change in gate voltage needed to increase the drain current by one order of magnitude. Measured in units of millivolts per decade, in conventional MOSFETs it is limited to k... » read more

What’s A Mott FET?
By Katherine Derbyshire - 17 Dec, 2018 - Comments: 0

The unique physics of two-dimensional semiconductors offers the potential for new kinds of switches that could extend the usefulness of conventional MOSFETs into a variety of new areas. A MOSFET applies a voltage to one side of the gate capacitor. The resulting electric field in the channel shifts the band structure and facilitates or impedes the flow of carriers. So as devices shrink, the g... » read more

Can Graphene Be Mass Manufactured?
By Katherine Derbyshire - 18 Oct, 2018 - Comments: 3

Since the isolation of graphene in 2004, the high mobility and unique transport properties of 2-dimensional semiconductors have tantalized physicists and materials scientists. Their in-plane carrier transport and lack of dangling bonds potentially can minimize line/edge scattering and other effects of extreme scaling. While 2-D materials cannot compete with silicon at current device dime... » read more

Collaboration And Advanced Substrates
By Katherine Derbyshire - 08 Oct, 2018 - Comments: 0

Discussions of semiconductor manufacturing tend to focus on CMOS logic and memory devices, sometimes to the exclusion of everything else. Discussions of silicon-on-insulator wafer markets focus on the needs of high performance logic. Lithography analysts emphasize high density memories. It’s easy to forget that real systems contain other devices, too. A modern smartphone probably supports ... » read more

Making Organic Semiconductors Plastic
By Katherine Derbyshire - 12 Jul, 2018 - Comments: 0

Plastic. The very word implies deformability, the ability to bend and flex without damage in response to stress. In applications from biomedical sensors to solar cells, the potential advantages of organic semiconductors depend almost entirely on their deformability—are they flexible enough for inexpensive roll-to-roll processing? Able to tolerate flexion in use? Able to do without the bulky a... » read more

The Growing Materials Challenge
By Katherine Derbyshire - 11 Jun, 2018 - Comments: 0

By Katherine Derbyshire & Ed Sperling Materials have emerged as a growing challenge across the semiconductor supply chain, as chips continue to scale, or as they are utilized in new devices such as sensors for AI or machine learning systems. Engineered materials are no longer optional at advanced nodes. They are now a requirement, and the amount of new material content in chips contin... » read more

Integrating Memristors For Neuromorphic Computing
By Katherine Derbyshire - 16 May, 2018 - Comments: 1

Much of the current research on neuromorphic computing focuses on the use of non-volatile memory arrays as a compute-in-memory component for artificial neural networks (ANNs). By using Ohm’s Law to apply stored weights to incoming signals, and Kirchoff’s Laws to sum up the results, memristor arrays can accelerate the many multiply-accumulate steps in ANN algorithms. ANNs are being dep... » read more

Preparing For AI
By Katherine Derbyshire - 03 May, 2018 - Comments: 0

Suppose an autonomous car is coming up an on-ramp onto a bridge. The ramp is fine, but the bridge is icy, and there’s an overturned bus full of children blocking several lanes. Children are evacuating through the windows and milling around on the pavement. There isn’t time to stop, even with the better-than-human reaction time an autonomous car might have. Swerving to one side might send... » read more

How The Brain Saves Energy By Doing Less
By Katherine Derbyshire - 15 Mar, 2018 - Comments: 0

One of the arguments for neuromorphic computing is the efficiency of the human brain relative to conventional computers. By looking at how the brain works, this argument contends, we can design systems that accomplish more with less power. However, as Mireille Conrad and others at the University of Geneva pointed out in work presented at December's IEEE Electron Device Meeting, the brain... » read more

What If We Had Bi-Directional RRAM?
By Katherine Derbyshire - 15 Feb, 2018 - Comments: 0

The ideal memristor device for neuromorphic computing would have linear and symmetric resistance behavior. Resistance would both increase and decrease gradually, allowing a direct correlation between the number of programming pulses and the resistance value. Real world RRAM devices, however, generally do not have these characteristics. In filamentary RRAM devices, the RESET operation can raise ... » read more

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