A novel mask proximity correction software combining accuracy and reduced writing time for the manufacturing of advanced photomasks

Schiavone, Patrick; Martin, Luc; Browning, Clyde; Farys, V.; Sundermann, Frank; Narukawa, Shogo; Takikawa, Tadahiko; Hayashi, Naoya

doi:10.1117/12.981609

Cited by 5 publications

(3 citation statements)

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“…In order to achieve these requirements, mask process correction (MPC) software will be required. Some work on MPC software has already been reported 5,6 . In preparation for the manufacturing introduction of EUV, we have been actively engaged in evaluating the performance of such software from various EDA suppliers 7 .…”

Section: Introductionmentioning

confidence: 98%

A new mask linearity specification for EUV masks based on time dependent dielectric breakdown requirements

Standiford

Bürgel

2013

SPIE Proceedings

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When compared to conventional chrome absorber masks, electron beam patterning of EUV masks requires additional corrections to account for intermediate range electron backscattering from the mirror and tantalum based absorber layers. The performance of this Mask Proximity Correction software should not be specified based solely on traditional mask linearity measures. We propose a new mask linearity specification based on Time Dependent Dielectric Breakdown requirements for metal layers.

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Section: Introductionmentioning

confidence: 98%

A new mask linearity specification for EUV masks based on time dependent dielectric breakdown requirements

Standiford

Bürgel

2013

SPIE Proceedings

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“…Design and production departments must work closely together to solve this problem [9]. Schiavone et al [10] presented a novel mask proximity correction software to ensure accuracy and to reduce writing time in photomask manufacturing. The trend in the field of circuit technology to reduce the dimensions of critical features has drastically increased the size of design files.…”

Section: Introductionmentioning

confidence: 99%

Solving the Mask Data Preparation Scheduling Problem Using Meta-Heuristics

et al. 2019

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Mask data preparation (MDP) is a part of the mask data process for fabricating semiconductors, and its importance has commonly been neglected. This paper proposes an integer linear programming model and two meta-heuristics, a genetic algorithm (GA) and simulated annealing (SA), for solving the MDP scheduling problem (MDPSP). The proposed meta-heuristics are empirically evaluated using 768 simulation instances of MDPSP based on the characteristics of a real technology company and compared with the most commonly used first-come, first-served method. The experimental results reveal that the proposed GA and SA algorithms can critically improve the manufacturing schedule for semiconductor factories.INDEX TERMS Scheduling, integer linear programming, mask data preparation, meta-heuristics, genetic algorithm, simulated annealing.

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“…Therefore, we considered altering the mask design in line with a process model to compensate the process signature, much like optical proximity correction (OPC), a technique that corrects errors by moving edges or modifying the exposure dose on a per-shot basis. [4][5][6][7] In analogy to OPC, this method is called mask process correction (MPC).…”

mentioning

confidence: 99%