Design driven test patterns for OPC models calibration

Al-Imam, Mohamed

doi:10.1117/12.813975

Cited by 6 publications

(4 citation statements)

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“…Semi-automatic approaches typically consist in manually trying to span the image parameter space with the help of various tools. For example, [2] uses data binning while [6] uses grid plots. These approaches are partially manual, which precludes testing on a full layout mask.…”

Section: State Of the Artmentioning

confidence: 99%

“…Moreover, to ensure early market entry and better data coverage, turn-around time is becoming more critical. Recent research results report to address these problems via clustering in distance space derived from image pixels between points and sometimes image parameter space to eliminate redundancy ([3]- [6]). Unfortunately, data compression based on clustering cannot be used alone, because this would lead to arbitrary pattern exclusion due to the large test masks sizes.…”

Section: Introductionmentioning

confidence: 99%

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Automated sample plan selection for OPC modeling

et al. 2014

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It is desired to reduce the time required to produce metrology data for calibration of Optical Proximity Correction (OPC) models and also maintain or improve the quality of the data collected with regard to how well that data represents the types of patterns that occur in real circuit designs. Previous work based on clustering in geometry and/or image parameter space has shown some benefit over strictly manual or intuitive selection, but leads to arbitrary pattern exclusion or selection which may not be the best representation of the product. Forming the pattern selection as an optimization problem, which co-optimizes a number of objective functions reflecting modelers' insight and expertise, has shown to produce models with equivalent quality to the traditional plan of record (POR) set but in a less time.

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Section: State Of the Artmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automated sample plan selection for OPC modeling

et al. 2014

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“…The blood was diluted with the white blood cells diluting fluid (Türk's solution). It was prepared by mixing 2 ml of glacial acetic acid and 98 ml of distilled water with adding 2 drops of methylene blue [11,12]. The general formula is used:…”

Section: Total White Blood Cells Countmentioning

confidence: 99%

Effect of Aqueous Extract of Fig (Ficus carica) Fruit on Some Hematological Parameters in Female Rabbits

Al-Jowari,

Al-Obaidi,

Yousif

2011

Baghdad Sci.J

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The effect of the aqueous extract of fig (Ficus carica) fruit was studied by using different concentrations of this fruit (15, 20 and 25 mg/kg of body weight) on some hematological parameters (hemoglobin concentration, packed cell volume, white blood cell count and platelets count) in female rabbits. Twenty female rabbits were randomly divided into four groups (five animals in each group). Three groups were dosed with the concentrations mentioned above, while the last was administered with distilled water and considered as control group. These animals were orally dosed by aqueous extract using a micropipette. The results showed that there was a significant (P

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“…One is a method of pattern selection using optical features such as intensity or slope [1]. However, the optical feature approach requires much simulation runtime because of complex TCC calculation.…”

Section: Introductionmentioning

confidence: 99%

Generator of predictive verification pattern using vision system based on higher-order local autocorrelation

et al. 2012

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Although lithography conditions, such as NA, illumination condition, resolution enhancement technique (RET), and material stack on wafer, have been determined to obtain hotspot-free wafer images, hotspots are still often found on wafers. This is because the lithography conditions are optimized with a limited variety of patterns. For 40 nm technology node and beyond, it becomes a critical issue causing not only the delay of process development but also the opportunity loss of the business. One of the easiest ways to avoid unpredictable hotspots is to verify an enormous variety of patterns in advance. This, however, is time consuming and cost inefficient. This paper proposes a new method to create a group of patterns to cover pattern variations in a chip layout based on Higher-Order Local Autocorrelation (HLAC), which consists of two phases. The first one is the "analyzing phase" and the second is the "generating phase". In the analyzing phase, geometrical features are extracted from actual layouts using the HLAC technique. Those extracted features are statistically analyzed and define the "feature space". In the generating phase, a group of patterns representing actual layout features are generated by correlating the feature space and the process margin. By verifying the proposed generated patterns, the lithography conditions can be optimized efficiently and the number of hotspots dramatically reduced.

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Design driven test patterns for OPC models calibration

Cited by 6 publications

References 0 publications

Automated sample plan selection for OPC modeling

Automated sample plan selection for OPC modeling

Effect of Aqueous Extract of Fig (Ficus carica) Fruit on Some Hematological Parameters in Female Rabbits

Generator of predictive verification pattern using vision system based on higher-order local autocorrelation

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