86 research outputs found

    Characterization of self-heating effects and assessment of its impact on reliability in finfet technology

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    The systematically growing power (heat) dissipation in CMOS transistors with each successive technology node is reaching levels which could impact its reliable operation. The emergence of technologies such as bulk/SOI FinFETs has dramatically confined the heat in the device channel due to its vertical geometry and it is expected to further exacerbate with gate-all-around transistors. This work studies heat generation in the channel of semiconductor devices and measures its dissipation by means of wafer level characterization and predictive thermal simulation. The experimental work is based on several existing device thermometry techniques to which additional layout improvements are made in state of the art bulk FinFET and SOI FinFET 14nm technology nodes. The sensors produce excellent matching results which are confirmed through TCAD thermal simulation, differences between sensor types are quantified and error bars on measurements are established. The lateral heat transport measurements determine that heat from the source is mostly dissipated at a distance of 1ยตm and 1.5ยตm in bulk FinFET and SOI FinFET, respectively. Heat additivity is successfully confirmed to prove and highlight the fact that the whole system needs to be considered when performing thermal analysis. Furthermore, an investigation is devoted to study self-heating with different layout densities by varying the number of fins and fingers per active region (RX). Fin thermal resistance is measured at different ambient temperatures to show its variation of up to 70% between -40ยฐC to 175ยฐC. Therefore, the Si fin has a more dominant effect in heat transport and its varying thermal conductivity should be taken into account. The effect of ambient temperature on self-heating measurement is confirmed by supplying heat through thermal chuck and adjacent heater devices themselves. Motivation for this work is the continuous evolution of the transistor geometry and use of exotic materials, which in the recent technology nodes made heat removal more challenging. This poses reliability and performance concerns. Therefore, this work studies the impact of self-heating on reliability testing at DC conditions as well as realistic CMOS logic operating (AC) conditions. Front-end-of-line (FEOL) reliability mechanisms, such as hot carrier injection (HCI) and non-uniform time dependent dielectric breakdown (TDDB), are studied to show that self-heating effects can impact measurement results and recommendations are given on how to mitigate them. By performing an HCI stress at moderate bias conditions, this dissertation shows that the laborious techniques of heat subtraction are no longer necessary. Self-heating is also studied at more realistic device switching conditions by utilizing ring oscillators with several densities and stage counts to show that self-heating is considerably lower compared to constant voltage stress conditions and degradation is not distinguishable

    PAOD: a predictive approach for optimization of design in FinFET/SRAM

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    The evolutions in the modern memory units are comeup with FinFET/SRAM which can be utilized over high scaled computing units and in other devices. Some of the recent systems were surveyed through which it is known that existing systems lags with improving the performance and optimization of FinFET/SRAM design. Thus, the paper introduces an optimized model based on Search Optimization mechanism that uses Predictive Approach to optimize the design structure of FinFET/SRAM (PAOD). Using this can achieve significant fault tolerance under dynamic cumpting devices and applications. The model uses mathematical methodology which helps to attain less computational time and significant output even at more simulation iteration. This POAD is cost effective as it provides better convergence of FinFET/SRAM design than recursive design

    ์ฐจ์„ธ๋Œ€ ๋ฐ˜๋„์ฒด ๋ฐฐ์„ ์„ ์œ„ํ•œ ์ฝ”๋ฐœํŠธ ํ•ฉ๊ธˆ ์ž๊ฐ€ํ˜•์„ฑ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰ ์žฌ๋ฃŒ ์„ค๊ณ„ ๋ฐ ์ „๊ธฐ์  ์‹ ๋ขฐ์„ฑ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์žฌ๋ฃŒ๊ณตํ•™๋ถ€, 2022.2. ์ฃผ์˜์ฐฝ.Recently, the resistance-capacitance (RC) delay of the Cu interconnects in metal 1 (M1) level has been increased rapidly due to the reduction of the interconnect linewidth along with the transistor scaling down, and the interconnect reliability becomes a severe issue again. In order to overcome interconnect performance problems and move forward to the next-generation interconnects system, study on low resistivity (ฯo) and low electron mean free path (ฮป) metals was conducted. Generally, metals such as Cobalt (Co), Ruthenium (Ru), and Molybdenum (Mo) are mentioned as candidates for next-generation interconnect materials, and since they have a low ฯo ร— ฮป value, it is expected that the influence of interface scatterings and surface scattering can be minimized. However, harsh operating environments such as high electric fields, critical Joule heating, and reduction of the pitch size are severely deteriorating the performance of electronic devices as well as device reliability. For example, since time dependent dielectric breakdown (TDDB) problems for next-generation interconnect system have been reported recently, it is necessary to study alternative barrier materials and processes to improve the interconnect reliability. Specifically, extrinsic dielectric breakdown due to penetration of Co metal ions in high electric fields has been reported as a reliability problem to be solved in Co interconnect systems. Therefore, there is a need for new material system design and research on a robust diffusion barrier that prevents metal ions from penetrating into the dielectric, thereby improving the reliability of Co interconnects. Moreover, in order to lower the resistance of the interconnect, it is necessary to develop an ultra-thin barrier. This is because even a barrier with good reliability characteristics will degrade chip performance if it takes up a lot of volume in the interconnect. The recommended thickness for a single diffusion barrier layer is currently reported to be less than 2.5 nm. As a result, it is essential to develop materials that comprehensively consider performance and reliability. In this study, we designed a Co alloy self-forming barrier (SFB) material that can make sure of low resistance and high reliability for Co interconnects, which is attracting attention as a next-generation interconnect system. The self-forming barrier methodology induces diffusion of an alloy dopant at the interface between the metal and the dielectric during the annealing process. And the diffused dopant reacts with the dielectric to form an ultra-thin diffusion barrier. Through this methodology, it is possible to improve reliability by preventing the movement of metal ions. First of all, material design rules were established to screen the appropriate alloy dopants and all CMOS-compatible metals were investigated. Dopant resistivity, intermetallic compound formation, solubility in Co, activity coefficient in Co, and oxidation tendency is considered as the criteria for the dopant to escape from the Co matrix and react at the Co/SiO2 interface. In addition, thermodynamic calculations were performed to predict which phases would be formed after the annealing process. Based on thermodynamic calculations, 5 dopant metals were selected, prioritized for self-forming behavior. And the self-forming material was finally selected through thin film and device analysis. We confirmed that Cr, Zn, and Mn out-diffused to the surface of the thin film structure using X-ray photoelectron spectroscopy (XPS) depth profile and investigated the chemical state of out-diffused dopants through the analysis of a binding energy. Cr shows the most ideal self-forming behavior with the SiO2 dielectric and reacted with oxygen to form a Cr2O3 barrier. In metal-insulator-semiconductor (MIS) structure, out-diffused Cr reacts with SiO2 at the interface and forms a self-formed single layer. It was confirmed that the thickness of the diffusion barrier layer is about 1.2 nm, which is an ultra-thin layer capable of minimizing the total effective resistance. Through voltage-ramping dielectric breakdown (VRDB) tests, Co-Cr alloy showed highest breakdown voltage (VBD) up to 200 % than pure Co. The effect of Cr doping concentration and heat treatment condition applicable to the interconnect process was confirmed. When Cr was doped less than 1 at%, the robust electrical reliability was exhibited. Also, it was found that a Cr2O3 interfacial layer was formed when annealing process was performed at 250 ยฐC or higher for 30 minutes or longer. In other words, Co-Cr alloy is well suited for the interconnect process because current interconnect process temperature is below 400 ยฐC. And when the film thickness was lowered from 150 nm to 20 nm, excellent VBD values were confirmed even at high Cr doping concentration (~7.5 at%). It seems that the amount of Cr present at the Co/SiO2 interface plays a very important role in improving the Cr oxide SFB quality. Physical modeling is necessary to understand the amount of Cr at the interface according to the interconnect volumes and the reliability of the Cr oxide self-forming barrier. TDDB lifetime test also performed and Co-Cr alloy interconnect shows a highly reliable diffusion barrier property of self-formed interfacial layer. The DFT analysis also confirmed that Cr2O3 is a very promising barrier material because it showed a higher energy barrier value than the TiN diffusion barrier currently being studied. A Co-based self-forming barrier was designed through thermodynamic calculations that take performance and reliability into account in interconnect material system. A Co interconnect system with an ultra-thin Cr2O3 diffusion barrier with excellent reliability is proposed. Through this design, it is expected that high-performance interconnects based on robust reliability in the advanced interconnect can be implemented in the near future.์ตœ๊ทผ ๋ฐ˜๋„์ฒด ์†Œ์ž ์Šค์ผ€์ผ๋ง์— ๋”ฐ๋ฅธ ๋ฐฐ์„  ์„ ํญ ๊ฐ์†Œ๋กœ M0, M1์˜์—ญ์—์„œ์˜ metal ๋น„์ €ํ•ญ์ด ๊ธ‰๊ฒฉํžˆ ์ฆ๊ฐ€ํ•˜์—ฌ ๋ฐฐ์„ ์—์„œ์˜ RC delay๊ฐ€ ๋‹ค์‹œ ํ•œ๋ฒˆ ํฌ๊ฒŒ ๋ฌธ์ œ๊ฐ€ ๋˜๊ณ  ์žˆ๋‹ค. ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด์„œ ์ฐจ์„ธ๋Œ€ ๋ฐฐ์„  ์‹œ์Šคํ…œ์—์„œ๋Š” ๋‚ฎ์€ ๋น„์ €ํ•ญ๊ณผ electron mean free path (EMFP)์„ ๊ฐ€์ง€๋Š” ๋ฌผ์งˆ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ๋Œ€ํ‘œ์ ์œผ๋กœ Co, Ru, Mo์™€ ๊ฐ™์€ ๊ธˆ์†๋“ค์ด ์ฐจ์„ธ๋Œ€ ๋ฐฐ์„  ์žฌ๋ฃŒ ํ›„๋ณด๋กœ ์–ธ๊ธ‰๋˜๊ณ  ์žˆ์œผ๋ฉฐ ๋‚ฎ์€ ฯ0 ร— ฮป ๊ฐ’์„ ๊ฐ–๊ธฐ ๋•Œ๋ฌธ์— interface (surface) scattering๊ณผ grain boundary scattering ์˜ํ–ฅ์„ ์ตœ์†Œํ™”ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๋ณด๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ฐ€ํ˜นํ•œ electrical field์™€ ๋†’์€ Joule heating์ด ๋ฐœ์ƒํ•˜๋Š” ๋™์ž‘ ํ™˜๊ฒฝ์œผ๋กœ ์ธํ•ด performance๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์†Œ์ž ์‹ ๋ขฐ์„ฑ์ด ๋” ์—ด์•…ํ•œ ์ƒํ™ฉ์— ๋†“์—ฌ์žˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด ์ฐจ์„ธ๋Œ€ ๊ธˆ์†์— ๋Œ€ํ•œ time dependent dielectric breakdown (TDDB) ์‹ ๋ขฐ์„ฑ ๋ฌธ์ œ๊ฐ€ ๋ณด๊ณ ๋˜๊ณ  ์žˆ๊ธฐ ๋•Œ๋ฌธ์— ์ด๋ฅผ ๋ณด์•ˆํ•  ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰ ๋ฌผ์งˆ ๋ฐ ๊ณต์ •์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ํŠนํžˆ ๋†’์€ ์ „๊ธฐ์žฅ์—์„œ Co ion์ด ์œ ์ „์ฒด๋กœ ์นจํˆฌํ•˜์—ฌ extrinsic dielectric breakdown ์‹ ๋ขฐ์„ฑ ๋ฌธ์ œ๊ฐ€ ์ตœ๊ทผ ๋ณด๊ณ ๋˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๊ธˆ์† ์ด์˜จ์ด ์œ ์ „์ฒด ๋‚ด๋ถ€๋กœ ์นจํˆฌํ•˜๋Š” ๊ฒƒ์„ ๋ฐฉ์ง€ํ•˜์—ฌ, Co ๋ฐฐ์„ ์˜ ์‹ ๋ขฐ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ฌ ์ˆ˜ ๊ฒฌ๊ณ ํ•œ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰ ๊ฐœ๋ฐœ ๋ฐ ์ƒˆ๋กœ์šด ๋ฐฐ์„  ์‹œ์Šคํ…œ ์„ค๊ณ„๊ฐ€ ํ•„์š”ํ•œ ์‹œ์ ์ด๋‹ค. ๋˜ํ•œ, ๋ฐฐ์„  ์ €ํ•ญ์„ ๋‚ฎ์ถ”๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋งค์šฐ ์–‡์€ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰ ๊ฐœ๋ฐœ์ด ํ•„์š”ํ•˜๋‹ค. ์‹ ๋ขฐ์„ฑ์ด ์ข‹์€ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰์ด๋ผ๋„ ๋ฐฐ์„ ์—์„œ ๋งŽ์€ ์˜์—ญ์„ ์ฐจ์ง€ํ•  ๊ฒฝ์šฐ ์ „์ฒด ์„ฑ๋Šฅ์ด ์ €ํ•˜๋˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. Cu ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰์œผ๋กœ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋Š” TaN ์ธต์€ 2.5 nm ๋ณด๋‹ค ์–‡์„ ๊ฒฝ์šฐ ์‹ ๋ขฐ์„ฑ์ด ๊ธ‰๊ฒฉํžˆ ๋‚˜๋น ์ง€๋ฏ€๋กœ 2.5 nm๋ณด๋‹ค ์–‡์€ ๋‘๊ป˜์˜ ๊ฒฌ๊ณ ํ•œ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰ ๊ฐœ๋ฐœ์ด ํ•„์š”ํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ฐจ์„ธ๋Œ€ ๋ฐ˜๋„์ฒด ๋ฐฐ์„  ๋ฌผ์งˆ๋กœ ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ๋Š” Co ๊ธˆ์†์— ๋Œ€ํ•˜์—ฌ ์ €์ €ํ•ญยท๊ณ ์‹ ๋ขฐ์„ฑ์„ ํ™•๋ณดํ•  ์ˆ˜ ์žˆ๋Š” Co alloy ์ž๊ฐ€ํ˜•์„ฑ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰ (Co alloy self-forming barrier, SFB) ์†Œ์žฌ ๋””์ž์ธํ•˜์˜€๋‹ค. ์ž๊ฐ€ํ˜•์„ฑ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰ ๋ฐฉ๋ฒ•๋ก ์€ ์—ด์ฒ˜๋ฆฌ ๊ณผ์ •์—์„œ ๊ธˆ์†๊ณผ ์œ ์ „์ฒด ๊ณ„๋ฉด์—์„œ ๋„ํŽ€ํŠธ๊ฐ€ ํ™•์‚ฐํ•˜๊ฒŒ ๋œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ํ™•์‚ฐ๋˜๋‹ˆ ๋„ํŽ€ํŠธ๋Š” ์–‡์€ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰์„ ํ˜•์„ฑํ•˜๋Š” ๋ฐฉ๋ฒ•๋ก ์ด๋‹ค. ์ด ๋ฐฉ๋ฒ•๋ก ์„ ํ†ตํ•ด ๊ธˆ์† ์ด์˜จ์˜ ์ด๋™์„ ๋ฐฉ์ง€ํ•˜์—ฌ Co ๋ฐฐ์„  ์‹ ๋ขฐ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒํ•˜์˜€๋‹ค. ์šฐ์„ , Co ํ•ฉ๊ธˆ์ƒ์—์„œ ์ ์ ˆํ•œ ๋„ํŽ€ํŠธ๋ฅผ ์ฐพ๊ธฐ ์œ„ํ•ด์„œ CMOS ๊ณต์ •์— ์ ์šฉ ๊ฐ€๋Šฅํ•œ ๊ธˆ์†๋“ค์„ ์„ ๋ณ„ํ•˜์˜€๋‹ค. ๋„ํŽ€ํŠธ ์ €ํ•ญ, ๊ธˆ์†๊ฐ„ ํ™”ํ•ฉ๋ฌผ ํ˜•์„ฑ ์—ฌ๋ถ€, Co๋‚ด ๊ณ ์šฉ๋„, Co alloy์—์„œ์˜ ํ™œ์„ฑ๊ณ„์ˆ˜, ์‚ฐํ™”๋„, Co/SiO2 ๊ณ„๋ฉด์—์„œ์˜ ์•ˆ์ •์ƒ์„ ์—ด์—ญํ•™์  ๊ณ„์‚ฐ์„ ํ†ตํ•ด์„œ ๋ฌผ์งˆ ์„ ์ • ๊ธฐ์ค€์œผ๋กœ ์„ธ์› ๋‹ค. ์—ด์—ญํ•™์  ๊ณ„์‚ฐ์„ ๊ธฐ๋ฐ˜์œผ๋กœ 9๊ฐœ์˜ ๋„ํŽ€ํŠธ ๊ธˆ์†์ด ์„ ํƒ๋˜์—ˆ์œผ๋ฉฐ, Co ํ•ฉ๊ธˆ ์ž๊ฐ€ํ˜•์„ฑ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰ ๊ธฐ์ค€์— ๋”ฐ๋ผ์„œ ์šฐ์„  ์ˆœ์œ„๋ฅผ ์ง€์ •ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ตœ์ข…์ ์œผ๋กœ ๋ฐ•๋ง‰๊ณผ ์†Œ์ž ์‹ ๋ขฐ์„ฑ ํ‰๊ฐ€๋ฅผ ํ†ตํ•ด์„œ ๊ฐ€์žฅ ์ ํ•ฉํ•œ ์ž๊ฐ€ํ˜•์„ฑ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰ ๋ฌผ์งˆ์„ ์„ ์ •ํ•˜์˜€๋‹ค. X-ray photoelectron spectroscopy (XPS) ๋ถ„์„์„ ์ด์šฉํ•˜์—ฌ Cr, Zn, Mn์ด ๋ฐ•๋ง‰ ๊ตฌ์กฐ์˜ ํ‘œ๋ฉด์œผ๋กœ ์™ธ๋ถ€ ํ™•์‚ฐ ์—ฌ๋ถ€๋ฅผ ํ™•์ธํ•˜๊ณ  ๊ฒฐํ•ฉ ์—๋„ˆ์ง€ ๋ถ„์„์„ ํ†ตํ•ด ์™ธ๋ถ€๋กœ ํ™•์‚ฐ๋œ ๋„ํŽ€ํŠธ์˜ ํ™”ํ•™์  ์ƒํƒœ๋ฅผ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ Cr, Zn, Mn์ด ์œ ์ „์ฒด ๊ณ„๋ฉด์œผ๋กœ ํ™•์‚ฐ๋˜์–ด ์‚ฐ์†Œ์™€ ๋ฐ˜์‘ํ•˜์—ฌoxide/silicate ํ™•์‚ฐ ๋ฐฉ์ง€๋ง‰ (e.g. Cr2O3, Zn2SiO4, MnSiO3)์„ ํ˜•์„ฑํ•œ ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ทธ ์ค‘ Cr์€ SiO2 ์œ ์ „์ฒด์™€ ํ•จ๊ป˜ ๊ฐ€์žฅ ์ด์ƒ์ ์ธ ์ž๊ธฐ ํ˜•์„ฑ ๊ฑฐ๋™์„ ๋‚˜ํƒ€๋‚ด๋ฉฐ ์‚ฐ์†Œ์™€ ๋ฐ˜์‘ํ•˜์—ฌ Cr2O3 ์ธต์„ ํ˜•์„ฑํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. MIS (Metal-Insulator-Semiconductor) ๊ตฌ์กฐ์—์„œ๋„ ์™ธ๋ถ€๋กœ ํ™•์‚ฐ๋œ Cr์€ ๊ณ„๋ฉด์—์„œ SiO2์™€ ๋ฐ˜์‘ํ•˜์—ฌ Cr2O3 ์ž๊ฐ€ํ˜•์„ฑ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰์ด ํ˜•์„ฑ๋˜์—ˆ๋‹ค. ํ™•์‚ฐ๋ฐฉ์ง€์ธต์˜ ๋‘๊ป˜๋Š” ์•ฝ 1.2nm๋กœ ์ „์ฒด ์œ ํšจ์ €ํ•ญ์„ ์ตœ์†Œํ™”ํ•  ์ˆ˜ ์žˆ๋Š” ์ถฉ๋ถ„ํžˆ ์–‡์€ ๋‘๊ป˜๋ฅผ ํ™•๋ณดํ•˜์˜€๋‹ค. VRDB (Voltage-Ramping Dielectric Breakdown) ํ…Œ์ŠคํŠธ๋ฅผ ํ†ตํ•ด Co-Cr ํ•ฉ๊ธˆ์€ ์ˆœ์ˆ˜ Co๋ณด๋‹ค ์ตœ๋Œ€ 200% ๋†’์€ ํ•ญ๋ณต ์ „์•• (breakdown voltage)์„ ๋ณด์˜€๋‹ค. ๋ฐ˜๋„์ฒด ๋ฐฐ์„  ๊ณต์ •์— ์ ์šฉํ•  ์ˆ˜ ์žˆ๋Š” Cr ๋„ํ•‘ ๋†๋„์™€ ์—ด์ฒ˜๋ฆฌ ์กฐ๊ฑด์˜ ์˜ํ–ฅ์„ ํ™•์ธํ•˜์˜€๋‹ค. Cr์ด 1at% ๋ฏธ๋งŒ์œผ๋กœ ๋„ํ•‘๋˜์—ˆ์„ ๋•Œ ์šฐ์ˆ˜ํ•œ ์ „๊ธฐ์  ์‹ ๋ขฐ์„ฑ์„ ๋‚˜ํƒ€๋‚ด์—ˆ๋‹ค. ๋˜ํ•œ, 250โ„ƒ ์ด์ƒ์—์„œ 30๋ถ„ ์ด์ƒ ์—ด์ฒ˜๋ฆฌ๋ฅผ ํ•˜์˜€์„ ๋•Œ Cr2O3 ๊ณ„๋ฉด์ธต์ด ํ˜•์„ฑ๋จ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ฆ‰, ํ˜„์žฌ ๋ฐฐ์„  ๊ณต์ • ์˜จ๋„๊ฐ€ 400ยฐC ๋ฏธ๋งŒ์ด๊ธฐ ๋•Œ๋ฌธ์— Co-Cr ํ•ฉ๊ธˆ์ด ๋ฐฐ์„  ๊ณต์ •์— ์ ์šฉ ๊ฐ€๋Šฅํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. TDDB ์ˆ˜๋ช… ํ…Œ์ŠคํŠธ๋„ ์ˆ˜ํ–‰๋˜์—ˆ์œผ๋ฉฐ Co-Cr ํ•ฉ๊ธˆ ๋ฐฐ์„ ์€ ์ž์ฒด ํ˜•์„ฑ๋œ ๊ณ„๋ฉด์ธต์˜ ๋งค์šฐ ์•ˆ์ •์ ์ธ ํ™•์‚ฐ ์žฅ๋ฒฝ ํŠน์„ฑ์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. DFT ๋ถ„์„์€ Cr2O3์ž๊ฐ€ํ˜•์„ฑ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰์ด ํ˜„์žฌ ์—ฐ๊ตฌ๋˜๊ณ  ์žˆ๋Š” TiN ํ™•์‚ฐ ์žฅ๋ฒฝ๋ณด๋‹ค ๋” ๋†’์€ ์—๋„ˆ์ง€ ์žฅ๋ฒฝ ๊ฐ’์„ ๋ณด์—ฌ์ฃผ๊ธฐ ๋•Œ๋ฌธ์— ๋งค์šฐ ์œ ๋งํ•œ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰์ž„์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ฐ˜๋„์ฑ„ ๋ฐฐ์„  ๋ฌผ์งˆ ์‹œ์Šคํ…œ์—์„œ ์„ฑ๋Šฅ๊ณผ ์‹ ๋ขฐ์„ฑ์„ ๊ณ ๋ คํ•œ ์—ด์—ญํ•™์  ๊ณ„์‚ฐ์„ ํ†ตํ•ด Co ๊ธฐ๋ฐ˜ ์ž๊ฐ€ํ˜•์„ฑ ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰์„ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ ์‹ ๋ขฐ์„ฑ์ด ์šฐ์ˆ˜ํ•˜๊ณ  ์•„์ฃผ ์–‡์€ Cr2O3 ํ™•์‚ฐ๋ฐฉ์ง€๋ง‰์ด ์žˆ๋Š” Co-Cr ํ•ฉ๊ธˆ์ด ์ œ์•ˆํ•˜์˜€๋‹ค. ๋ฌผ์งˆ ์„ค๊ณ„์™€ ์ „๊ธฐ์  ์‹ ๋ขฐ์„ฑ ๊ฒ€์ฆ์„ Co/Cr2O3/SiO2 ๋ฌผ์งˆ ์‹œ์Šคํ…œ์„ ์ œ์•ˆํ•˜์˜€๊ณ  ์•ž์œผ๋กœ์˜ ๋‹ค๊ฐ€์˜ฌ ์ฐจ์„ธ๋Œ€ ๋ฐฐ์„ ์—์„œ ๊ตฌํ˜„๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.Abstract i Table of Contents v List of Tables ix List of Figures xii Chapter 1. Introduction 1 1.1. Scaling down of VLSI systems 1 1.2. Driving force of interconnect system evolution 7 1.3. Driving force of beyond Cu interconnects 11 1.4. Objective of the thesis 18 1.5. Organization of the thesis 21 Chapter 2. Theoretical Background 22 2.1. Evolution of interconnect systems 22 2.1.1. Cu/barrier/low-k interconnect system 22 2.1.2. Process developments for interconnect reliability 27 2.1.3. 3rd generation of interconnect system 31 2.2 Thermodynamic tools for Co self-forming barrier 42 2.2.1 Binary phase diagram 42 2.2.2 Ellingham diagram 42 2.2.3 Activity coefficient 43 2.3. Reliability of Interconnects 45 2.3.1. Current conduction mechanisms in dielectrics 45 2.3.2. Reliability test vehicles 50 2.3.3. Dielectric breakdown assessment 52 2.3.4. Dielectric breakdown mechanisms 55 2.3.5. Reliability test: VRDB and TDDB 56 2.3.6. Lifetime models 57 Chapter 3. Experimental Procedures 60 3.1. Thin film deposition 60 3.1.1. Substrate preparation 60 3.1.2. Oxidation 61 3.1.3. Co alloy deposition using DC magnetron sputtering 61 3.1.4. Annealing process 65 3.2. Thin film characterization 67 3.2.1. Sheet resistance 67 3.2.2. X-ray photoelectron spectroscopy (XPS) 68 3.3. Metal-Insulator-Semiconductor (MIS) device fabrication 70 3.3.1. Patterning using lift-off process 70 3.3.2. TDDB packaging 72 3.4. Reliability analysis 74 3.4.1. Electrical reliability analysis 74 3.4.2. Transmission electron microscopy (TEM) analysis 75 3.5. Computation 76 3.5.1 FactsageTM calculation 76 3.5.2. Density Functional Theory (DFT) calculation 77 Chapter 4. Co Alloy Design for Advanced Interconnects 78 4.1. Material design of Co alloy self-forming barrier 78 4.1.1. Rule of thumb of Co-X alloy 78 4.1.2. Co alloy phase 80 4.1.3. Out-diffusion stage 81 4.1.4. Reaction step with SiO2 dielectric 89 4.1.5. Comparison criteria 94 4.2. Comparison of Co alloy candidates 97 4.2.1. Thin film resistivity evaluation 97 4.2.2. Self-forming behavior using XPS depth profile analysis 102 4.2.3. MIS device reliability test 110 4.3 Summary 115 Chapter 5. Co-Cr Alloy Interconnect with Robust Self-Forming Barrier 117 5.1. Compatibility of Co-Cr alloy SFB process 117 5.1.1. Effect of Cr doping concentration 117 5.1.2. Annealing process condition optimization 119 5.2. Reliability of Co-Cr interconnects 122 5.2.1. VRDB quality test with Co-Cr alloys 122 5.2.2. Lifetime evaluation using TDDB method 141 5.2.3. Barrier mechanism using DFT 142 5.3. Summary 145 Chapter 6. Conclusion 148 6.1. Summary of results 148 6.2. Research perspectives 150 References 151 Abstract (In Korean) 166 Curriculum Vitae 169๋ฐ•

    Defect Induced Aging and Breakdown in High-k Dielectrics

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    abstract: High-k dielectrics have been employed in the metal-oxide semiconductor field effect transistors (MOSFETs) since 45 nm technology node. In this MOSFET industry, Mooreโ€™s law projects the feature size of MOSFET scales half within every 18 months. Such scaling down theory has not only led to the physical limit of manufacturing but also raised the reliability issues in MOSFETs. After the incorporation of HfO2 based high-k dielectrics, the stacked oxides based gate insulator is facing rather challenging reliability issues due to the vulnerable HfO2 layer, ultra-thin interfacial SiO2 layer, and even messy interface between SiO2 and HfO2. Bias temperature instabilities (BTI), hot channel electrons injections (HCI), stress-induced leakage current (SILC), and time dependent dielectric breakdown (TDDB) are the four most prominent reliability challenges impacting the lifetime of the chips under use. In order to fully understand the origins that could potentially challenge the reliability of the MOSFETs the defects induced aging and breakdown of the high-k dielectrics have been profoundly investigated here. BTI aging has been investigated to be related to charging effects from the bulk oxide traps and generations of Si-H bonds related interface traps. CVS and RVS induced dielectric breakdown studies have been performed and investigated. The breakdown process is regarded to be related to oxygen vacancies generations triggered by hot hole injections from anode. Post breakdown conduction study in the RRAM devices have shown irreversible characteristics of the dielectrics, although the resistance could be switched into high resistance state.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

    Reliability-aware memory design using advanced reconfiguration mechanisms

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    Fast and Complex Data Memory systems has become a necessity in modern computational units in today's integrated circuits. These memory systems are integrated in form of large embedded memory for data manipulation and storage. This goal has been achieved by the aggressive scaling of transistor dimensions to few nanometer (nm) sizes, though; such a progress comes with a drawback, making it critical to obtain high yields of the chips. Process variability, due to manufacturing imperfections, along with temporal aging, mainly induced by higher electric fields and temperature, are two of the more significant threats that can no longer be ignored in nano-scale embedded memory circuits, and can have high impact on their robustness. Static Random Access Memory (SRAM) is one of the most used embedded memories; generally implemented with the smallest device dimensions and therefore its robustness can be highly important in nanometer domain design paradigm. Their reliable operation needs to be considered and achieved both in cell and also in architectural SRAM array design. Recently, and with the approach to near/below 10nm design generations, novel non-FET devices such as Memristors are attracting high attention as a possible candidate to replace the conventional memory technologies. In spite of their favorable characteristics such as being low power and highly scalable, they also suffer with reliability challenges, such as process variability and endurance degradation, which needs to be mitigated at device and architectural level. This thesis work tackles such problem of reliability concerns in memories by utilizing advanced reconfiguration techniques. In both SRAM arrays and Memristive crossbar memories novel reconfiguration strategies are considered and analyzed, which can extend the memory lifetime. These techniques include monitoring circuits to check the reliability status of the memory units, and architectural implementations in order to reconfigure the memory system to a more reliable configuration before a fail happens.Actualmente, el diseรฑo de sistemas de memoria en circuitos integrados busca continuamente que sean mรกs rรกpidos y complejos, lo cual se ha vuelto de gran necesidad para las unidades de computaciรณn modernas. Estos sistemas de memoria estรกn integrados en forma de memoria embebida para una mejor manipulaciรณn de los datos y de su almacenamiento. Dicho objetivo ha sido conseguido gracias al agresivo escalado de las dimensiones del transistor, el cual estรก llegando a las dimensiones nanomรฉtricas. Ahora bien, tal progreso ha conllevado el inconveniente de una menor fiabilidad, dado que ha sido altamente difรญcil obtener elevados rendimientos de los chips. La variabilidad de proceso - debido a las imperfecciones de fabricaciรณn - junto con la degradaciรณn de los dispositivos - principalmente inducido por el elevado campo elรฉctrico y altas temperaturas - son dos de las mรกs relevantes amenazas que no pueden ni deben ser ignoradas por mรกs tiempo en los circuitos embebidos de memoria, echo que puede tener un elevado impacto en su robusteza final. Static Random Access Memory (SRAM) es una de las celdas de memoria mรกs utilizadas en la actualidad. Generalmente, estas celdas son implementadas con las menores dimensiones de dispositivos, lo que conlleva que el estudio de su robusteza es de gran relevancia en el actual paradigma de diseรฑo en el rango nanomรฉtrico. La fiabilidad de sus operaciones necesita ser considerada y conseguida tanto a nivel de celda de memoria como en el diseรฑo de arquitecturas complejas basadas en celdas de memoria SRAM. Actualmente, con el diseรฑo de sistemas basados en dispositivos de 10nm, dispositivos nuevos no-FET tales como los memristores estรกn atrayendo una elevada atenciรณn como posibles candidatos para reemplazar las actuales tecnologรญas de memorias convencionales. A pesar de sus caracterรญsticas favorables, tales como el bajo consumo como la alta escabilidad, ellos tambiรฉn padecen de relevantes retos de fiabilidad, como son la variabilidad de proceso y la degradaciรณn de la resistencia, la cual necesita ser mitigada tanto a nivel de dispositivo como a nivel arquitectural. Con todo esto, esta tesis doctoral afronta tales problemas de fiabilidad en memorias mediante la utilizaciรณn de tรฉcnicas de reconfiguraciรณn avanzada. La consideraciรณn de nuevas estrategias de reconfiguraciรณn han resultado ser validas tanto para las memorias basadas en celdas SRAM como en `memristive crossbarยฟ, donde se ha observado una mejora significativa del tiempo de vida en ambos casos. Estas tรฉcnicas incluyen circuitos de monitorizaciรณn para comprobar la fiabilidad de las unidades de memoria, y la implementaciรณn arquitectural con el objetivo de reconfigurar los sistemas de memoria hacia una configuraciรณn mucho mรกs fiables antes de que el fallo suced

    A COMPARATIVE STUDY OF RELIABILITY FOR FINFET

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    The continuous downscaling of CMOS technologies over the last few decades resulted in higher Integrated Circuit (IC) density and performance. The emergence of FinFET technology has brought with it the same reliability issues as standard CMOS with the addition of a new prominent degradation mechanism. The same mechanisms still exist as for previous CMOS devices, including Bias Temperature Instability (BTI), Hot Carrier Degradation (HCD), Electro-migration (EM), and Body Effects. A new and equally important reliability issue for FinFET is the Self -heating, which is a crucial complication since thermal time-constant is generally much longer than the transistor switching times. FinFET technology is the newest technological paradigm that has emerged in the past decade, as downscaling reached beyond 20 nm, which happens also to be the estimated mean free path of electrons at room temperature in silicon. As such, the reliability physics of FinFET was modified in order to fit the newly developed transistor technology. This paper highlights the roles and impacts of these various effects and aging mechanisms on FinFET transistors compared to planar transistors on the basic approach of the physics of failure mechanisms to fit to a comprehensive aging model

    Cross-Layer Resiliency Modeling and Optimization: A Device to Circuit Approach

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    The never ending demand for higher performance and lower power consumption pushes the VLSI industry to further scale the technology down. However, further downscaling of technology at nano-scale leads to major challenges. Reduced reliability is one of them, arising from multiple sources e.g. runtime variations, process variation, and transient errors. The objective of this thesis is to tackle unreliability with a cross layer approach from device up to circuit level

    Interconnects for future technology generations - conventional CMOS with copper/low-k and beyond

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    The limitations of the conventional Cu/low-k interconnect technology for use in future ultra-scaled integrated circuits down to 7 nm in the year 2020 are investigated from the power/performance point of view. Compact models are used to demonstrate the impacts of various interconnect process parameters, for instance, the interconnect barrier/liner bilayer thickness and aspect ratio, on the design and optimization of a multilevel interconnect network. A framework to perform a sensitivity analysis for the circuit behavior to interconnect process parameters is created for future FinFET CMOS technology nodes. Multiple predictive cell libraries down to the 7โ€’nm technology node are constructed to enable early investigation of the electronic chip performance using commercial electronic design automation (EDA) tools with real chip information. Findings indicated new opportunities that arise for emerging novel interconnect technologies from the materials and process perspectives. These opportunities are evaluated based on potential benefits that are quantified with rigorous circuit-level simulations and requirements for key parameters are underlined. The impacts of various emerging interconnect technologies on the performances of emerging devices are analyzed to quantify the realistic circuit- and system-level benefits that these new switches can offer.Ph.D
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