Method and system for determining sample composition from spectral data
Disclosed are a method and system that determine a sample composition from the spectrum data acquired by a charged particle microscope inspection system. Chemical elements, in the sample, are identified by processing the spectrum data with a trained neural network (NN). If the identified chemical el...
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| creator | KAPLENKO MYKOLA MACHEK ONDREJ TUMA TOMAS KLUSACEK JAN KAPLENKO OLEKSII |
| description | Disclosed are a method and system that determine a sample composition from the spectrum data acquired by a charged particle microscope inspection system. Chemical elements, in the sample, are identified by processing the spectrum data with a trained neural network (NN). If the identified chemical elements do not match a known elemental composition of the sample, the trained NN is retrained with the known elemental composition and spectrum data of the sample. The retrained NN may then be used to identify the chemical elements within the next sample.
하전된 입자 현미경검사 시스템에 의해 획득된 스펙트럼 데이터로부터 샘플 조성을 결정하는 방법 및 시스템이 개시된다. 샘플에서 화학적 원소들은 스펙트럼 데이터를 훈련된 신경망 (NN)으로 처리함으로써 식별된다. 샘플의 알려진 원소성 조성과 매칭하지 않는 식별된 화학적 원소들이면, 훈련된 NN은 샘플의 알려진 원소성 조성 및 스펙트럼 데이터로 재훈련된다. 재훈련된 NN은 그 다음 다른 샘플 내에서 화학적 원소들을 식별하는데 사용될 수 있다. |
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하전된 입자 현미경검사 시스템에 의해 획득된 스펙트럼 데이터로부터 샘플 조성을 결정하는 방법 및 시스템이 개시된다. 샘플에서 화학적 원소들은 스펙트럼 데이터를 훈련된 신경망 (NN)으로 처리함으로써 식별된다. 샘플의 알려진 원소성 조성과 매칭하지 않는 식별된 화학적 원소들이면, 훈련된 NN은 샘플의 알려진 원소성 조성 및 스펙트럼 데이터로 재훈련된다. 재훈련된 NN은 그 다음 다른 샘플 내에서 화학적 원소들을 식별하는데 사용될 수 있다.</description><subject>BASIC ELECTRIC ELEMENTS</subject><subject>ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS</subject><subject>ELECTRICITY</subject><subject>INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES</subject><subject>MEASURING</subject><subject>PHYSICS</subject><subject>TESTING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyrEKwjAQANAsDqL-w4GzEFqss0irIC7iXo7kUgNJLuRu8e9d_ACnt7y1uT5I3-wBiwf5iFKGwA08KbUcSywLCOaaCBznyhI1coHQOINUctowgUfFrVkFTEK7nxuzn8bX5XagyjNJRUeFdL4_O9v11trjaRjO_X_rC15aNSA</recordid><startdate>20230110</startdate><enddate>20230110</enddate><creator>KAPLENKO MYKOLA</creator><creator>MACHEK ONDREJ</creator><creator>TUMA TOMAS</creator><creator>KLUSACEK JAN</creator><creator>KAPLENKO OLEKSII</creator><scope>EVB</scope></search><sort><creationdate>20230110</creationdate><title>Method and system for determining sample composition from spectral data</title><author>KAPLENKO MYKOLA ; MACHEK ONDREJ ; TUMA TOMAS ; KLUSACEK JAN ; KAPLENKO OLEKSII</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_KR20230005766A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; kor</language><creationdate>2023</creationdate><topic>BASIC ELECTRIC ELEMENTS</topic><topic>ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS</topic><topic>ELECTRICITY</topic><topic>INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES</topic><topic>MEASURING</topic><topic>PHYSICS</topic><topic>TESTING</topic><toplevel>online_resources</toplevel><creatorcontrib>KAPLENKO MYKOLA</creatorcontrib><creatorcontrib>MACHEK ONDREJ</creatorcontrib><creatorcontrib>TUMA TOMAS</creatorcontrib><creatorcontrib>KLUSACEK JAN</creatorcontrib><creatorcontrib>KAPLENKO OLEKSII</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>KAPLENKO MYKOLA</au><au>MACHEK ONDREJ</au><au>TUMA TOMAS</au><au>KLUSACEK JAN</au><au>KAPLENKO OLEKSII</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Method and system for determining sample composition from spectral data</title><date>2023-01-10</date><risdate>2023</risdate><abstract>Disclosed are a method and system that determine a sample composition from the spectrum data acquired by a charged particle microscope inspection system. Chemical elements, in the sample, are identified by processing the spectrum data with a trained neural network (NN). If the identified chemical elements do not match a known elemental composition of the sample, the trained NN is retrained with the known elemental composition and spectrum data of the sample. The retrained NN may then be used to identify the chemical elements within the next sample.
하전된 입자 현미경검사 시스템에 의해 획득된 스펙트럼 데이터로부터 샘플 조성을 결정하는 방법 및 시스템이 개시된다. 샘플에서 화학적 원소들은 스펙트럼 데이터를 훈련된 신경망 (NN)으로 처리함으로써 식별된다. 샘플의 알려진 원소성 조성과 매칭하지 않는 식별된 화학적 원소들이면, 훈련된 NN은 샘플의 알려진 원소성 조성 및 스펙트럼 데이터로 재훈련된다. 재훈련된 NN은 그 다음 다른 샘플 내에서 화학적 원소들을 식별하는데 사용될 수 있다.</abstract><oa>free_for_read</oa></addata></record> |
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| title | Method and system for determining sample composition from spectral data |
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