Machine learning and high-speed circuitry in thin film transistors for sensor interfacing in hybrid large-area electronic systems

J. C. Sturm, Y. Mehlman, L. E. Aygun, C. Wu, Z. Zheng, P. Kumar, S. Wagner, N. Verma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The advent of flexible substrates with thin film transistors (TFTs) over large areas (meters) makes large-area electronics (LAE) an attractive platform for integrating very large numbers of sensors onto surfaces over large areas. While TFT's may directly interface to sensors and may be used for sensor addressing, to realistically communicate with the outside world, IC's will probably be bonded onto the "sensor sheets" to create a "hybrid" LAE/IC system. This paper examines novel architectures to minimize the number of physical interfaces to the IC, beyond the typical TFT-based active-matrix approach. Approaches demonstrated include (i) high-frequency TFT-based analog oscillators, and (ii) implementing elements of machine learning into TFT circuitry, so a higher-level information is sent to the IC's, thus requiring fewer physical connections.

Original languageEnglish (US)
Title of host publicationSemiconductor Process Integration 11
EditorsJ. Murota, C. Claeys, H. Iwai, M. Tao, S. Deleonibus, A. Mai, K. Shiojima, Y. Cao
PublisherElectrochemical Society Inc.
Pages121-134
Number of pages14
Edition4
ISBN (Electronic)9781607688785
ISBN (Print)9781607688785
DOIs
StatePublished - 2019
Event11th Symposium on Semiconductor Process Integration - 236th ECS Meeting - Atlanta, United States
Duration: Oct 13 2019Oct 17 2019

Publication series

NameECS Transactions
Number4
Volume92
ISSN (Print)1938-6737
ISSN (Electronic)1938-5862

Conference

Conference11th Symposium on Semiconductor Process Integration - 236th ECS Meeting
Country/TerritoryUnited States
CityAtlanta
Period10/13/1910/17/19

All Science Journal Classification (ASJC) codes

  • General Engineering

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