190 research outputs found

    Limits on Fundamental Limits to Computation

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    An indispensable part of our lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the last fifty years. Such Moore scaling now requires increasingly heroic efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and enrich our understanding of integrated-circuit scaling, we review fundamental limits to computation: in manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, we recall how some limits were circumvented, compare loose and tight limits. We also point out that engineering difficulties encountered by emerging technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl

    Development and Simulation Assessment of Semiconductor Production System Enhancements for Fast Cycle Times

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    Long cycle times in semiconductor manufacturing represent an increasing challenge for the industry and lead to a growing need of break-through approaches to reduce it. Small lot sizes and the conversion of batch processes to mini-batch or single-wafer processes are widely regarded as a promising means for a step-wise cycle time reduction. Our analysis with discrete-event simulation and queueing theory shows that small lot size and the replacement of batch tools with mini-batch or single wafer tools are beneficial but lot size reduction lacks persuasive effectiveness if reduced by more than half. Because the results are not completely convincing, we develop a new semiconductor tool type that further reduces cycle time by lot streaming leveraging the lot size reduction efforts. We show that this combined approach can lead to a cycle time reduction of more than 80%

    High-Density Solid-State Memory Devices and Technologies

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    This Special Issue aims to examine high-density solid-state memory devices and technologies from various standpoints in an attempt to foster their continuous success in the future. Considering that broadening of the range of applications will likely offer different types of solid-state memories their chance in the spotlight, the Special Issue is not focused on a specific storage solution but rather embraces all the most relevant solid-state memory devices and technologies currently on stage. Even the subjects dealt with in this Special Issue are widespread, ranging from process and design issues/innovations to the experimental and theoretical analysis of the operation and from the performance and reliability of memory devices and arrays to the exploitation of solid-state memories to pursue new computing paradigms

    Analog Spiking Neuromorphic Circuits and Systems for Brain- and Nanotechnology-Inspired Cognitive Computing

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    Human society is now facing grand challenges to satisfy the growing demand for computing power, at the same time, sustain energy consumption. By the end of CMOS technology scaling, innovations are required to tackle the challenges in a radically different way. Inspired by the emerging understanding of the computing occurring in a brain and nanotechnology-enabled biological plausible synaptic plasticity, neuromorphic computing architectures are being investigated. Such a neuromorphic chip that combines CMOS analog spiking neurons and nanoscale resistive random-access memory (RRAM) using as electronics synapses can provide massive neural network parallelism, high density and online learning capability, and hence, paves the path towards a promising solution to future energy-efficient real-time computing systems. However, existing silicon neuron approaches are designed to faithfully reproduce biological neuron dynamics, and hence they are incompatible with the RRAM synapses, or require extensive peripheral circuitry to modulate a synapse, and are thus deficient in learning capability. As a result, they eliminate most of the density advantages gained by the adoption of nanoscale devices, and fail to realize a functional computing system. This dissertation describes novel hardware architectures and neuron circuit designs that synergistically assemble the fundamental and significant elements for brain-inspired computing. Versatile CMOS spiking neurons that combine integrate-and-fire, passive dense RRAM synapses drive capability, dynamic biasing for adaptive power consumption, in situ spike-timing dependent plasticity (STDP) and competitive learning in compact integrated circuit modules are presented. Real-world pattern learning and recognition tasks using the proposed architecture were demonstrated with circuit-level simulations. A test chip was implemented and fabricated to verify the proposed CMOS neuron and hardware architecture, and the subsequent chip measurement results successfully proved the idea. The work described in this dissertation realizes a key building block for large-scale integration of spiking neural network hardware, and then, serves as a step-stone for the building of next-generation energy-efficient brain-inspired cognitive computing systems

    ์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•

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