Impact of particles in ultra pure water on random yield loss in IC production

Wali, Faisal; Knotter, D. Martin; Mud, Auke; Kuper, F.G.

doi:10.1016/j.mee.2008.09.046

Cited by 14 publications

(7 citation statements)

References 8 publications

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“…As such, distribution I in Fig. 1 follows a classical distribution and therefore we speculate that it is caused by airborne (or 'machine borne') particles that are also present in dry lithography processes (although extra sources of particles could be the topcoat deposition process, and the ultra pure water that was used in the immersion hood [16]). …”

Section: A Size Distributions Of Immersion-specific Defectsmentioning

confidence: 82%

Improving Equipment Defectivity Specifications Through Chip Yield Modeling: A Case Study for Immersion Lithography

Boogaard

Smith

Mouraille

et al. 2013

IEEE Trans. Semicond. Manufact.

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Semiconductor equipment suppliers are asked to build tools that can operate almost continuously. Once such a reliable tool is developed, defect data collection, understanding, and reduction become increasingly important since the tool has to manufacture reliable (layers of) semiconductor devices that scarcely fail. At this stage, semiconductor equipment suppliers could benefit from the concepts of chip yield modeling, because it directly relates their defect data to the yield of semiconductor devices. We present a case study in which we estimate the yield impact of defects related to immersion photolithography scanners. Defects were separated into various classes, and the size distributions of those classes were measured. Given a circuit's critical area, forecasting of the yield for any defect class becomes straightforward, and also yield predictions can be made for future technology nodes, resulting in the optimal choice of yieldenhancing strategies.

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Section: A Size Distributions Of Immersion-specific Defectsmentioning

confidence: 82%

Improving Equipment Defectivity Specifications Through Chip Yield Modeling: A Case Study for Immersion Lithography

Boogaard

Smith

Mouraille

et al. 2013

IEEE Trans. Semicond. Manufact.

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“…Furthermore, the defects are assumed to deposit randomly on any area of the whole wafer. In a recent study [10], defect density in the wafer environment was related to yield. This means that the measured particles in ultra-pure water (UPW), which is used for device manufacturing, relate to the in-line measured defect density on the respective devices.…”

Section: Random Defects and Non-random Deposition Modelmentioning

confidence: 99%

“…The maximum lift force (F l,max ) that acts on the particle is given in equation (10), where R is the particle radius, g is the surface tension of the liquid, q is the wetting angle of the particle, and a ¼ the contact angle of the liquid on the substrate.…”

Section: Particle Removal Mechanismmentioning

confidence: 99%

Particles in Semiconductor Processing

Knotter

Wali

2010

Developments in Surface Contamination and Cleaning

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“…Nanoparticles play a significant role in various fields such as biomedical imaging and diagnostics (Choi et al (2007); Huang et al (2007)), process control in semiconductor manufacturing (Wali et al (2009)), environmental monitoring and climate change (Ramanathan and Carmichael (2008); Morawska (2010)). Inhalation of ultrafine particulates in air has been shown to have adverse effects, such as inflammation of lungs or pulmonary and cardiovascular diseases (Oberdörster (2000); Somers et al (2004)).…”

Section: Introductionmentioning

confidence: 99%

Real-time optical detection of single human and bacterial viruses based on dark-field interferometry

Mitra

Ignatovich

Novotny

2012

Biosensors and Bioelectronics

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The rapid and sensitive detection and characterization of human viruses and bacteriophage is extremely important in a variety of fields, such as medical diagnostics, immunology and vaccine research, and environmental contamination and quality control. We introduce an optical detection scheme for real-time and label-free detection of human viruses and bacteriophage as small as ~ 24 nm in radius. Combining the advantages of heterodyne interferometry and dark-field microscopy, this label-free method enables us to detect and characterize various biological nanoparticles with unsurpassed sensitivity and selectivity. We demonstrate the high sensitivity and precision of the method by analyzing a mixture containing HIV virus and bacteriophage. The method also resolves the distribution of small nano-impurities (~ 20 − 30 nm) in clinically relevant virus samples.

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Impact of particles in ultra pure water on random yield loss in IC production

Cited by 14 publications

References 8 publications

Improving Equipment Defectivity Specifications Through Chip Yield Modeling: A Case Study for Immersion Lithography

Improving Equipment Defectivity Specifications Through Chip Yield Modeling: A Case Study for Immersion Lithography

Particles in Semiconductor Processing

Real-time optical detection of single human and bacterial viruses based on dark-field interferometry

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