KR102539586B1 - 이온 주입 반도체 제조 툴에서의 컴포넌트 고장들의 정정 - Google Patents
이온 주입 반도체 제조 툴에서의 컴포넌트 고장들의 정정 Download PDFInfo
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- KR102539586B1 KR102539586B1 KR1020217027568A KR20217027568A KR102539586B1 KR 102539586 B1 KR102539586 B1 KR 102539586B1 KR 1020217027568 A KR1020217027568 A KR 1020217027568A KR 20217027568 A KR20217027568 A KR 20217027568A KR 102539586 B1 KR102539586 B1 KR 102539586B1
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- South Korea
- Prior art keywords
- failure
- window
- sensor data
- ion implantation
- components
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
- H01J37/00—Discharge tubes with provision for introducing objects or material to be exposed to the discharge, e.g. for the purpose of examination or processing thereof
- H01J37/30—Electron-beam or ion-beam tubes for localised treatment of objects
- H01J37/317—Electron-beam or ion-beam tubes for localised treatment of objects for changing properties of the objects or for applying thin layers thereon, e.g. for ion implantation
- H01J37/3171—Electron-beam or ion-beam tubes for localised treatment of objects for changing properties of the objects or for applying thin layers thereon, e.g. for ion implantation for ion implantation
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
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- H—ELECTRICITY
- H10—SEMICONDUCTOR DEVICES; ELECTRIC SOLID-STATE DEVICES NOT OTHERWISE PROVIDED FOR
- H10P—GENERIC PROCESSES OR APPARATUS FOR THE MANUFACTURE OR TREATMENT OF DEVICES COVERED BY CLASS H10
- H10P72/00—Handling or holding of wafers, substrates or devices during manufacture or treatment thereof
- H10P72/04—Apparatus for manufacture or treatment
- H10P72/0451—Apparatus for manufacturing or treating in a plurality of work-stations
- H10P72/0468—Apparatus for manufacturing or treating in a plurality of work-stations comprising a chamber adapted to a particular process
- H10P72/0471—Apparatus for manufacturing or treating in a plurality of work-stations comprising a chamber adapted to a particular process comprising at least one ion or electron beam chamber
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
- G05B23/024—Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Program-control systems
- G05B19/02—Program-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
- G05B23/0254—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0283—Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]
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- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/243—Classification techniques relating to the number of classes
- G06F18/2433—Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
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- G06N20/00—Machine learning
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/044—Recurrent networks, e.g. Hopfield networks
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- G—PHYSICS
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/044—Recurrent networks, e.g. Hopfield networks
- G06N3/0442—Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
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- G06N3/00—Computing arrangements based on biological models
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- G06N3/0464—Convolutional networks [CNN, ConvNet]
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- G—PHYSICS
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/09—Supervised learning
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/0985—Hyperparameter optimisation; Meta-learning; Learning-to-learn
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
- G06N20/20—Ensemble learning
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/048—Activation functions
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/01—Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
- H01J2237/00—Discharge tubes exposing object to beam, e.g. for analysis treatment, etching, imaging
- H01J2237/30—Electron or ion beam tubes for processing objects
- H01J2237/304—Controlling tubes
- H01J2237/30405—Details
- H01J2237/30427—Details using neural networks or fuzzy logic
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Computing Systems (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Computational Linguistics (AREA)
- Biophysics (AREA)
- Biomedical Technology (AREA)
- Health & Medical Sciences (AREA)
- Automation & Control Theory (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Medical Informatics (AREA)
- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Testing And Monitoring For Control Systems (AREA)
- Physical Vapour Deposition (AREA)
- Crystals, And After-Treatments Of Crystals (AREA)
- Testing Or Measuring Of Semiconductors Or The Like (AREA)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| KR1020237018033A KR102731064B1 (ko) | 2019-01-31 | 2020-01-17 | 이온 주입 반도체 제조 툴에서의 컴포넌트 고장들의 정정 |
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US16/264,034 US11348813B2 (en) | 2019-01-31 | 2019-01-31 | Correcting component failures in ion implant semiconductor manufacturing tool |
| US16/264,034 | 2019-01-31 | ||
| PCT/US2020/014197 WO2020159730A1 (en) | 2019-01-31 | 2020-01-17 | Correcting component failures in ion implant semiconductor manufacturing tool |
Related Child Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| KR1020237018033A Division KR102731064B1 (ko) | 2019-01-31 | 2020-01-17 | 이온 주입 반도체 제조 툴에서의 컴포넌트 고장들의 정정 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| KR20210109673A KR20210109673A (ko) | 2021-09-06 |
| KR102539586B1 true KR102539586B1 (ko) | 2023-06-01 |
Family
ID=71836669
Family Applications (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| KR1020217027568A Active KR102539586B1 (ko) | 2019-01-31 | 2020-01-17 | 이온 주입 반도체 제조 툴에서의 컴포넌트 고장들의 정정 |
| KR1020237018033A Active KR102731064B1 (ko) | 2019-01-31 | 2020-01-17 | 이온 주입 반도체 제조 툴에서의 컴포넌트 고장들의 정정 |
Family Applications After (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| KR1020237018033A Active KR102731064B1 (ko) | 2019-01-31 | 2020-01-17 | 이온 주입 반도체 제조 툴에서의 컴포넌트 고장들의 정정 |
Country Status (6)
| Country | Link |
|---|---|
| US (2) | US11348813B2 (https=) |
| JP (2) | JP7238146B2 (https=) |
| KR (2) | KR102539586B1 (https=) |
| CN (2) | CN113383282B (https=) |
| TW (2) | TWI797418B (https=) |
| WO (1) | WO2020159730A1 (https=) |
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| US20210133213A1 (en) * | 2019-10-31 | 2021-05-06 | Vettd, Inc. | Method and system for performing hierarchical classification of data |
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| US11226805B2 (en) * | 2019-07-31 | 2022-01-18 | Dell Products L.P. | Method and system for predicting upgrade completion times in hyper-converged infrastructure environments |
| JP7414589B2 (ja) * | 2020-03-04 | 2024-01-16 | 住友重機械イオンテクノロジー株式会社 | イオン注入装置およびモデル生成方法 |
| WO2022093271A1 (en) * | 2020-10-30 | 2022-05-05 | Hitachi Vantara Llc | Automated real-time detection, prediction and prevention of rare failures in industrial system with unlabeled sensor data |
| CN112560327B (zh) * | 2020-11-13 | 2024-03-12 | 盐城工学院 | 一种基于深度梯度下降森林的轴承剩余寿命预测方法 |
| WO2022117218A1 (en) * | 2020-12-02 | 2022-06-09 | Hitachi Energy Switzerland Ag | Prognosis of high voltage equipment |
| WO2022224693A1 (ja) * | 2021-04-19 | 2022-10-27 | パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカ | 製造方法、生成装置、推定装置、識別情報付与方法、及び付与装置 |
| EP4242904B1 (en) * | 2021-07-02 | 2026-04-01 | Comet AG | Method for machine learning a detection of at least one irregularity in a plasma system |
| US12506024B2 (en) * | 2021-07-08 | 2025-12-23 | Applied Materials, Inc. | Method and mechanism for contact-free process chamber characterization |
| US12247283B2 (en) * | 2021-07-09 | 2025-03-11 | Applied Materials, Inc. | Method and apparatus for controlled ion implantation |
| WO2023030807A1 (en) * | 2021-09-02 | 2023-03-09 | Asml Netherlands B.V. | Method of evaluating selected set of patterns |
| US20230113095A1 (en) * | 2021-10-13 | 2023-04-13 | Applied Materials, Inc. | Verification for improving quality of maintenance of manufacturing equipment |
| US12517479B2 (en) * | 2021-12-21 | 2026-01-06 | Applied Materials, Inc. | Manufacturing equipment parts quality management system |
| CN114492184A (zh) * | 2022-01-21 | 2022-05-13 | 北京科技大学 | 一种时频域分析航空发动机剩余使用寿命预测方法及装置 |
| US11892821B2 (en) * | 2022-03-15 | 2024-02-06 | Applied Materials, Inc. | Communication node to interface between evaluation systems and a manufacturing system |
| JP7564334B2 (ja) * | 2022-03-24 | 2024-10-08 | 株式会社日立ハイテク | 装置診断システム、装置診断装置、半導体装置製造システムおよび装置診断方法 |
| US12259719B2 (en) * | 2022-05-25 | 2025-03-25 | Applied Materials, Inc. | Methods and mechanisms for preventing fluctuation in machine-learning model performance |
| JP7759298B2 (ja) * | 2022-06-10 | 2025-10-23 | 株式会社日立製作所 | 施設運用支援装置、方法およびプログラム |
| US20240086597A1 (en) * | 2022-09-14 | 2024-03-14 | Applied Materials, Inc. | Generation and utilization of virtual features for process modeling |
| CN116046078A (zh) * | 2023-03-31 | 2023-05-02 | 东莞市楷德精密机械有限公司 | 一种半导体清洗设备的故障监测预警方法及系统 |
| US20240355592A1 (en) * | 2023-04-24 | 2024-10-24 | Applied Materials, Inc. | Uniform plasma processing with a linear plasma source |
| US11995401B1 (en) | 2023-04-30 | 2024-05-28 | The Strategic Coach Inc. | Systems and methods for identifying a name |
| WO2025064622A1 (en) * | 2023-09-19 | 2025-03-27 | Eli Lilly And Company | Downtime prediction for management of machines in manufacturing network |
| CN117421679B (zh) * | 2023-10-08 | 2024-06-18 | 宁波创基机械股份有限公司 | 一种注塑机周期管控方法、装置、电子设备及存储介质 |
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| JP6860406B2 (ja) * | 2017-04-05 | 2021-04-14 | 株式会社荏原製作所 | 半導体製造装置、半導体製造装置の故障予知方法、および半導体製造装置の故障予知プログラム |
| CN107024267A (zh) * | 2017-04-12 | 2017-08-08 | 无锡研测技术有限公司 | 基于径向基神经网络的称重设备传感器故障检测方法 |
| CN107238507B (zh) * | 2017-06-20 | 2019-12-31 | 佛山市南海区广工大数控装备协同创新研究院 | 一种基于深度学习的工业设备故障预测方法 |
| CN108304941A (zh) * | 2017-12-18 | 2018-07-20 | 中国软件与技术服务股份有限公司 | 一种基于机器学习的故障预测方法 |
| CN108829933B (zh) * | 2018-05-22 | 2023-04-07 | 北京天泽智云科技有限公司 | 一种半导体制造设备的预测性维护与健康管理的方法 |
| CN109102189B (zh) * | 2018-08-10 | 2022-02-11 | 杨璇 | 一种电气设备健康管理系统和方法 |
| JP7233201B2 (ja) | 2018-11-20 | 2023-03-06 | 東京エレクトロン株式会社 | 搬送ユニットの監視方法及び監視装置並びに監視用モデル |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101081013B1 (ko) | 2003-11-03 | 2011-11-09 | 글로벌파운드리즈 인크. | 이온 주입 프로세스들에 대한 오류 검출 및 제어 방법, 및이를 수행하는 시스템 |
| KR101744194B1 (ko) | 2016-08-19 | 2017-06-09 | 인하대학교 산학협력단 | 반도체 fab 제조공정에서 유클리드 거리를 활용한 웨이퍼 자동 불량 검사 분류 예측 장치 및 방법 |
| WO2018063225A1 (en) | 2016-09-29 | 2018-04-05 | Hewlett-Packard Development Company, L.P. | Component failure prediction |
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| US20220301903A1 (en) | 2022-09-22 |
| US11862493B2 (en) | 2024-01-02 |
| JP2023085255A (ja) | 2023-06-20 |
| CN113383282B (zh) | 2024-10-18 |
| TW202329188A (zh) | 2023-07-16 |
| JP7472344B2 (ja) | 2024-04-22 |
| KR20210109673A (ko) | 2021-09-06 |
| KR102731064B1 (ko) | 2024-11-14 |
| CN113383282A (zh) | 2021-09-10 |
| KR20230084317A (ko) | 2023-06-12 |
| JP2022523101A (ja) | 2022-04-21 |
| CN119398192B (zh) | 2025-12-12 |
| TWI797418B (zh) | 2023-04-01 |
| US11348813B2 (en) | 2022-05-31 |
| CN119398192A (zh) | 2025-02-07 |
| TWI851071B (zh) | 2024-08-01 |
| WO2020159730A1 (en) | 2020-08-06 |
| JP7238146B2 (ja) | 2023-03-13 |
| US20200251360A1 (en) | 2020-08-06 |
| TW202044314A (zh) | 2020-12-01 |
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