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Design and Automation for High Fidelity Flexible Hybrid Electronics.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Design and Automation for High Fidelity Flexible Hybrid Electronics./
作者:	Shao, Leilai.
面頁冊數:	1 online resource (147 pages)
附註:	Source: Dissertations Abstracts International, Volume: 82-04, Section: B.
Contained By:	Dissertations Abstracts International82-04B.
標題:	Computer engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28089018click for full text (PQDT)
ISBN:	9798684681912

Design and Automation for High Fidelity Flexible Hybrid Electronics.
Shao, Leilai.

Design and Automation for High Fidelity Flexible Hybrid Electronics. - 1 online resource (147 pages)

Source: Dissertations Abstracts International, Volume: 82-04, Section: B.

Thesis (Ph.D.)--University of California, Santa Barbara, 2020.

Includes bibliographical references

Design and Automation for High Fidelity Flexible Hybrid Electronicsby Leilai ShaoFlexible electronics is emerging as an alternative to conventional silicon electronics for appli- cations such as wearable sensors, artificial skin, medical patches, bendable displays, foldable solar cells and disposable RFID tags. Combining FE with thinned silicon chips, known as flexi- ble hybrid electronics (FHE), can take advantages of both low-cost printed electronics and high performance silicon chips. There exist several challenges before FHE can be broadly employed for next-generation wearable and IoT products. Due to material properties, TFTs are usually mono-type, either only p- or only n-type, devices. Existing CMOS design methodologies for silicon electronics, therefore, cannot be directly applied for designing flexible electronics. To address these challenges, a trustworthy TFT compact model and process design kit (PDK) is needed to facilitate simulations and design explorations.In the first part, we developed the compact model for thin film transistors, which has been validated extensively with carbon nanotube (CNT), organic and indium gallium oxide (IGZO) devices. The developed model has been implemented in Verilog-A, which can perform co- simulations with silicon chips. With the developed model, we further built the FHE-PDK for flexible thin-film transistors (TFTs) and passive elements, including technology files for design rule checking (DRC), layout versus schematic (LVS) and layout parasitics extraction (LPE), as well as SPICE-compatible models. Wafer scale measurements are used to validate our SPICE models and design rules are derived accordingly to assure a satisfactory yield. With the developed FHE-PDK, we further built the robust Pseudo-CMOS cell library to address the mono-type design challenges.In the second part, we focused on addressing FHE system design issues. Specifically, motion noises in the flex-rigid interface and sensor defects in large area sensing system. We proposed the "active electrode" (with a thickness ≤2 um), which integrates the electrode with a thin-film transistor (TFT) based amplifier, to effectively suppress motion artifacts. The fab- ricated ultra-thin amplifier can achieve a gain of 32 dB at 20 kHz. The simulation results indicate that the active electrode can significantly improve the signal quality under motion noise (achieving ≥30 dB improvement in signal-to-noise ratio (SNR)) and boost classification accuracy by ≥19% for atrial fibrillation (AF) detection. We further study robustness issue of ultra-thin flexible electronics caused by inadequate device yield, reliability and stability which is inevitable due to the low temperature requirement for fabrication and the large-area nature of flexible sensing arrays. As signals sensed by body sensor arrays exhibit sparse statistical char- acteristics, we present a system design solution to leverage the sparse nature via compressed sensing (CS) which can ensure system robustness without relying on highly reliable devices. Specifically, we implement a flexible CS encoder together with the sensor array using carbon- nanotube-based flexible TFTs and decode the compressed signal in the silicon side. Our quan- titative analysis, validated through two case studies: temperature imaging and tactile-sensor based object recognition, showed that the proposed robust sensing schema can accommodate up to 20% sparse defects (device defects or transient errors).

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798684681912Subjects--Topical Terms:

621879
Computer engineering.
Subjects--Index Terms:

Flexible hybrid electronicsIndex Terms--Genre/Form:

542853
Electronic books.

Design and Automation for High Fidelity Flexible Hybrid Electronics.
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504 $a Includes bibliographical references
520 $a Design and Automation for High Fidelity Flexible Hybrid Electronicsby Leilai ShaoFlexible electronics is emerging as an alternative to conventional silicon electronics for appli- cations such as wearable sensors, artificial skin, medical patches, bendable displays, foldable solar cells and disposable RFID tags. Combining FE with thinned silicon chips, known as flexi- ble hybrid electronics (FHE), can take advantages of both low-cost printed electronics and high performance silicon chips. There exist several challenges before FHE can be broadly employed for next-generation wearable and IoT products. Due to material properties, TFTs are usually mono-type, either only p- or only n-type, devices. Existing CMOS design methodologies for silicon electronics, therefore, cannot be directly applied for designing flexible electronics. To address these challenges, a trustworthy TFT compact model and process design kit (PDK) is needed to facilitate simulations and design explorations.In the first part, we developed the compact model for thin film transistors, which has been validated extensively with carbon nanotube (CNT), organic and indium gallium oxide (IGZO) devices. The developed model has been implemented in Verilog-A, which can perform co- simulations with silicon chips. With the developed model, we further built the FHE-PDK for flexible thin-film transistors (TFTs) and passive elements, including technology files for design rule checking (DRC), layout versus schematic (LVS) and layout parasitics extraction (LPE), as well as SPICE-compatible models. Wafer scale measurements are used to validate our SPICE models and design rules are derived accordingly to assure a satisfactory yield. With the developed FHE-PDK, we further built the robust Pseudo-CMOS cell library to address the mono-type design challenges.In the second part, we focused on addressing FHE system design issues. Specifically, motion noises in the flex-rigid interface and sensor defects in large area sensing system. We proposed the "active electrode" (with a thickness ≤2 um), which integrates the electrode with a thin-film transistor (TFT) based amplifier, to effectively suppress motion artifacts. The fab- ricated ultra-thin amplifier can achieve a gain of 32 dB at 20 kHz. The simulation results indicate that the active electrode can significantly improve the signal quality under motion noise (achieving ≥30 dB improvement in signal-to-noise ratio (SNR)) and boost classification accuracy by ≥19% for atrial fibrillation (AF) detection. We further study robustness issue of ultra-thin flexible electronics caused by inadequate device yield, reliability and stability which is inevitable due to the low temperature requirement for fabrication and the large-area nature of flexible sensing arrays. As signals sensed by body sensor arrays exhibit sparse statistical char- acteristics, we present a system design solution to leverage the sparse nature via compressed sensing (CS) which can ensure system robustness without relying on highly reliable devices. Specifically, we implement a flexible CS encoder together with the sensor array using carbon- nanotube-based flexible TFTs and decode the compressed signal in the silicon side. Our quan- titative analysis, validated through two case studies: temperature imaging and tactile-sensor based object recognition, showed that the proposed robust sensing schema can accommodate up to 20% sparse defects (device defects or transient errors).
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