Machine Learning (ML)-Based Model to Characterize the Line Edge Roughness (LER)-Induced Random Variation in FinFET
ML (Machine Learning)-based artificial neural network (ANN) model is proposed to estimate the LER (line edge roughness)-induced performance variation in Fin-shaped Field Effect Transistor (FinFET). For a given LER features such as rms amplitude(Δ), correlation length along x-direction (A&...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9179808/ |
| _version_ | 1818727214671200256 |
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| author | Jaehyuk Lim Changhwan Shin |
| author_facet | Jaehyuk Lim Changhwan Shin |
| author_sort | Jaehyuk Lim |
| collection | DOAJ |
| description | ML (Machine Learning)-based artificial neural network (ANN) model is proposed to estimate the LER (line edge roughness)-induced performance variation in Fin-shaped Field Effect Transistor (FinFET). For a given LER features such as rms amplitude(Δ), correlation length along x-direction (A<sub>X</sub>), and correlation length along y-direction (A<sub>Y</sub>), the metrics for device performance such as on-state drive current, off-state leakage current, threshold voltage, and subthreshold swing can be computing-efficiently estimated with the ANN model. |
| first_indexed | 2024-12-17T22:10:33Z |
| format | Article |
| id | doaj.art-8779d5631c264535bc6316fbb92cc72a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T22:10:33Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8779d5631c264535bc6316fbb92cc72a2022-12-21T21:30:45ZengIEEEIEEE Access2169-35362020-01-01815823715824210.1109/ACCESS.2020.30200669179808Machine Learning (ML)-Based Model to Characterize the Line Edge Roughness (LER)-Induced Random Variation in FinFETJaehyuk Lim0https://orcid.org/0000-0003-1636-8865Changhwan Shin1https://orcid.org/0000-0001-6057-3773Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, South KoreaDepartment of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, South KoreaML (Machine Learning)-based artificial neural network (ANN) model is proposed to estimate the LER (line edge roughness)-induced performance variation in Fin-shaped Field Effect Transistor (FinFET). For a given LER features such as rms amplitude(Δ), correlation length along x-direction (A<sub>X</sub>), and correlation length along y-direction (A<sub>Y</sub>), the metrics for device performance such as on-state drive current, off-state leakage current, threshold voltage, and subthreshold swing can be computing-efficiently estimated with the ANN model.https://ieeexplore.ieee.org/document/9179808/Line edge roughnessprocess-induced random variationFinFETmachine learningartificial neural network |
| spellingShingle | Jaehyuk Lim Changhwan Shin Machine Learning (ML)-Based Model to Characterize the Line Edge Roughness (LER)-Induced Random Variation in FinFET IEEE Access Line edge roughness process-induced random variation FinFET machine learning artificial neural network |
| title | Machine Learning (ML)-Based Model to Characterize the Line Edge Roughness (LER)-Induced Random Variation in FinFET |
| title_full | Machine Learning (ML)-Based Model to Characterize the Line Edge Roughness (LER)-Induced Random Variation in FinFET |
| title_fullStr | Machine Learning (ML)-Based Model to Characterize the Line Edge Roughness (LER)-Induced Random Variation in FinFET |
| title_full_unstemmed | Machine Learning (ML)-Based Model to Characterize the Line Edge Roughness (LER)-Induced Random Variation in FinFET |
| title_short | Machine Learning (ML)-Based Model to Characterize the Line Edge Roughness (LER)-Induced Random Variation in FinFET |
| title_sort | machine learning ml based model to characterize the line edge roughness ler induced random variation in finfet |
| topic | Line edge roughness process-induced random variation FinFET machine learning artificial neural network |
| url | https://ieeexplore.ieee.org/document/9179808/ |
| work_keys_str_mv | AT jaehyuklim machinelearningmlbasedmodeltocharacterizethelineedgeroughnesslerinducedrandomvariationinfinfet AT changhwanshin machinelearningmlbasedmodeltocharacterizethelineedgeroughnesslerinducedrandomvariationinfinfet |