KR102166322B1 - 메트롤로지 데이터로부터의 소스 분리 - Google Patents
메트롤로지 데이터로부터의 소스 분리 Download PDFInfo
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- KR102166322B1 KR102166322B1 KR1020187020353A KR20187020353A KR102166322B1 KR 102166322 B1 KR102166322 B1 KR 102166322B1 KR 1020187020353 A KR1020187020353 A KR 1020187020353A KR 20187020353 A KR20187020353 A KR 20187020353A KR 102166322 B1 KR102166322 B1 KR 102166322B1
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Abstract
Description
도 2a는 리소그래피 공정에서 결함들을 예측하는 방법을 개략적으로 도시하는 도면;
도 2b는 소정 조명 모드들을 제공하는 제 1 쌍의 조명 어퍼처(illumination aperture)들을 이용하여 본 발명의 실시예들에 따른 타겟들을 측정하는 데 사용되는 다크 필드(dark field) 측정 장치의 개략적인 다이어그램;
도 2c는 주어진 방향의 조명에 대한 타겟의 상세한 회절 스펙트럼을 개략적으로 도시하는 도면;
도 2d는 회절 기반 오버레이 측정들을 위해 측정 장치를 이용함에 있어서 또 다른 조명 모드들을 제공하는 제 2 쌍의 조명 어퍼처들을 개략적으로 예시하는 도면;
도 2e는 회절 기반 오버레이 측정들을 위해 측정 장치를 이용함에 있어서 또 다른 조명 모드들을 제공하는 제 1 및 제 2 쌍들의 어퍼처들을 조합한 제 3 쌍의 조명 어퍼처들을 개략적으로 예시하는 도면;
도 2f는 일 형태의 다수 주기적 구조체(예를 들어, 다수 격자) 타겟 및 기판 상의 측정 스폿의 윤곽(outline)을 도시하는 도면;
도 2g는 도 2b의 장치에서 얻어진 도 2f의 타겟의 이미지를 도시하는 도면;
도 3은 각 복제품(copy)들이 기판의 4 개의 상이한 영역들에 배치되는 2 개의 별개의 타겟들(P 및 Q)을 갖는 기판을 개략적으로 나타내는 도면;
도 4a 및 도 4b는 동일한 타겟이 어떻게 상이한 기판 측정 레시피들에서 상이한 시스템적 오차(systematic error)들을 도입할 수 있는지를 입증하는 도면;
도 5는 측정 결과들의 세트에서의 (시스템적 오차들 및 실제 값과 같은) 다양한 소스들로부터의 기여들의 조합을 개략적으로 나타내는 도면;
도 6은 도 5의 결과들의 예시들로서, 기판 상의 상이한 위치들에서 측정된 12 개의 오버레이 값들을 개략적으로 나타내는 도면;
도 7은 12 개의 오버레이 값들, 오버레이의 실제 값들, 및 비대칭으로부터의 기여가 맵들로서(즉, 위치들의 함수로서) 플롯구성될 수 있음을 개략적으로 나타내는 도면;
도 8은 일 실시예에 따라, 리소그래피 공정 또는 리소그래피 공정에 의해 처리되는 기판으로부터 측정된 결과들의 세트에서 상이한 소스들로부터의 기여들을 결정하는 방법에 대한 흐름도를 개략적으로 나타내는 도면;
도 9는 일 실시예에 따라, 도 8에서 결정되는 기여들 사이에서의 측정으로부터 실제 값으로부터의 기여가 식별될 수 있음을 개략적으로 나타내는 도면;
도 10은 일 실시예에 따라, 도 8에서 결과들을 얻는 데 사용되는 기판 측정 레시피들의 정확성이 도 8의 흐름에서 결정되는 매트릭스 또는 기여들로부터 결정될 수 있음을 개략적으로 나타내는 도면;
도 11a, 도 11b 및 도 11c는 각각 16 개의 상이한 기판 측정 레시피들(수평축)을 이용하여 얻어진 결과들에서 3 개의 소스들로부터 정규화된 기여들(수직축)을 나타내는 도면;
도 12는 예시적인 컴퓨터 시스템의 블록 다이어그램;
도 13은 리소그래피 장치의 개략적인 다이어그램;
도 14는 또 다른 리소그래피 장치의 개략적인 다이어그램; 및
도 15는 도 14의 장치의 더 상세한 도면이다.
Claims (14)
- 기판을 검사하는 방법에 있어서,
컴퓨터를 이용하여, 복수의 상이한 기판 측정 레시피(substrate measurement recipe)들을 이용하여 리소그래피 공정에 의해 처리된 기판으로부터 측정되는 결과들로부터 독립적인 소스들로부터의 기여(contribution)들을 결정하는 단계 -상기 기여들은 상기 기판으로부터 측정되는 특성의 실제 값으로부터의 기여를 포함함- ; 및
상기 실제 값으로부터의 기여를 식별하는 단계 -상기 실제 값으로부터의 기여를 식별하는 단계는 a) 다른 데이터로의 검증(verification), 또는 b) 상기 기여들 중 어느 것이 상기 복수의 기판 측정 레시피들에 걸쳐 일관성이 있는지를 발견하는 단계를 포함함-
을 포함하는 방법. - 제 1 항에 있어서,
상기 결과들의 차원(dimension)들의 수를 감소시키는 단계를 더 포함하는 방법. - 제 2 항에 있어서,
상기 차원들의 수를 감소시키는 단계는 주 성분 분석(PCA)을 이용하는 단계를 포함하는 방법. - 제 1 항에 있어서,
상기 결과들은 상기 기여들의 선형 조합들인 방법. - 제 1 항에 있어서,
상기 기여들을 매트릭스로 컴파일(compile)하는 단계를 더 포함하는 방법. - 제 1 항에 있어서,
상기 결과들은 복수의 상이한 위치들로부터 얻어진 오버레이 값들을 포함하는 방법. - 제 1 항에 있어서,
상기 기판 측정 레시피들은 상기 기판 측정 레시피들이 수행하는 측정의 파라미터, 또는 상기 기판 측정 레시피들에 의해 측정되는 패턴의 파라미터에 있어서 상이한 방법. - 제 1 항에 있어서,
상기 실제 값으로부터의 기여로부터 상기 실제 값을 결정하는 단계를 더 포함하는 방법. - 제 1 항에 있어서,
상기 기여들로부터 상기 기판 측정 레시피들의 정확성을 결정하는 단계를 더 포함하는 방법. - 명령어들이 기록되어 있는 컴퓨터 판독가능한 매체에 저장된 컴퓨터 프로그램에 있어서,
상기 명령어들은 컴퓨터에 의해 실행되는 경우, 제 1 항의 방법을 구현하는 컴퓨터 프로그램. - 삭제
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| US20180239851A1 (en) * | 2017-02-21 | 2018-08-23 | Asml Netherlands B.V. | Apparatus and method for inferring parameters of a model of a measurement structure for a patterning process |
| EP3910418A1 (en) * | 2020-05-14 | 2021-11-17 | ASML Netherlands B.V. | Method for direct decomposition of stochastic contributors |
| CN115605811A (zh) * | 2020-05-14 | 2023-01-13 | Asml荷兰有限公司(Nl) | 用于预测随机贡献方的方法 |
| CN117940851A (zh) * | 2021-09-15 | 2024-04-26 | Asml荷兰有限公司 | 从量测数据的源分离 |
| CN120188105A (zh) * | 2022-11-09 | 2025-06-20 | Asml荷兰有限公司 | 用于套刻模型构建和应用的系统、方法和软件 |
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| US20200192229A1 (en) | 2020-06-18 |
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