Algorithmic Optimization of Transistors Applied to Silicon LDMOS
We propose a pioneering approach that integrates optimization algorithms and technology computer-aided design to automatically optimize laterally-diffused metal-oxide-semiconductors (LDMOS) with a field-oxide structure. We define the ratio of the square of the breakdown voltage divided by the specif...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10155324/ |
| _version_ | 1797790948734795776 |
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| author | Ping-Ju Chuang Ali Saadat Maarten L. Van De Put Hal Edwards William G. Vandenberghe |
| author_facet | Ping-Ju Chuang Ali Saadat Maarten L. Van De Put Hal Edwards William G. Vandenberghe |
| author_sort | Ping-Ju Chuang |
| collection | DOAJ |
| description | We propose a pioneering approach that integrates optimization algorithms and technology computer-aided design to automatically optimize laterally-diffused metal-oxide-semiconductors (LDMOS) with a field-oxide structure. We define the ratio of the square of the breakdown voltage divided by the specific on-resistance as the figure-of-merit (FOM) and the objective function of our optimization. We compare the performance of three different algorithms: Nelder-Mead, Powell, and Bayesian Optimization. We show how the LDMOS performance evolves as each of the three optimization algorithms reach their optimized structure. We show that a straightforward Nelder-Mead optimization leads to a local optimum when optimizing over six input parameters. We find that Bayesian Optimization is the most data-efficient method to find the global optimized structure in the multi-domain design space. |
| first_indexed | 2024-03-13T02:11:47Z |
| format | Article |
| id | doaj.art-2e11c6369146490484618caeecf7dc34 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-13T02:11:47Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2e11c6369146490484618caeecf7dc342023-06-30T23:01:12ZengIEEEIEEE Access2169-35362023-01-0111641606416910.1109/ACCESS.2023.328720410155324Algorithmic Optimization of Transistors Applied to Silicon LDMOSPing-Ju Chuang0https://orcid.org/0000-0001-9552-5579Ali Saadat1https://orcid.org/0000-0001-8628-0098Maarten L. Van De Put2Hal Edwards3https://orcid.org/0000-0002-1101-661XWilliam G. Vandenberghe4https://orcid.org/0000-0002-6717-5046Department of Materials Science and Engineering, The University of Texas at Dallas, Richardson, TX, USADepartment of Materials Science and Engineering, The University of Texas at Dallas, Richardson, TX, USAInteruniversity Microelectronics Centre (IMEC), Leuven, BelgiumAnalog Technology Development, Texas Instruments Inc., Dallas, TX, USADepartment of Materials Science and Engineering, The University of Texas at Dallas, Richardson, TX, USAWe propose a pioneering approach that integrates optimization algorithms and technology computer-aided design to automatically optimize laterally-diffused metal-oxide-semiconductors (LDMOS) with a field-oxide structure. We define the ratio of the square of the breakdown voltage divided by the specific on-resistance as the figure-of-merit (FOM) and the objective function of our optimization. We compare the performance of three different algorithms: Nelder-Mead, Powell, and Bayesian Optimization. We show how the LDMOS performance evolves as each of the three optimization algorithms reach their optimized structure. We show that a straightforward Nelder-Mead optimization leads to a local optimum when optimizing over six input parameters. We find that Bayesian Optimization is the most data-efficient method to find the global optimized structure in the multi-domain design space.https://ieeexplore.ieee.org/document/10155324/Bayesian optimizationLDMOSnelder-mead algorithmpower semiconductor devicepowell algorithmstep gate field oxide structure |
| spellingShingle | Ping-Ju Chuang Ali Saadat Maarten L. Van De Put Hal Edwards William G. Vandenberghe Algorithmic Optimization of Transistors Applied to Silicon LDMOS IEEE Access Bayesian optimization LDMOS nelder-mead algorithm power semiconductor device powell algorithm step gate field oxide structure |
| title | Algorithmic Optimization of Transistors Applied to Silicon LDMOS |
| title_full | Algorithmic Optimization of Transistors Applied to Silicon LDMOS |
| title_fullStr | Algorithmic Optimization of Transistors Applied to Silicon LDMOS |
| title_full_unstemmed | Algorithmic Optimization of Transistors Applied to Silicon LDMOS |
| title_short | Algorithmic Optimization of Transistors Applied to Silicon LDMOS |
| title_sort | algorithmic optimization of transistors applied to silicon ldmos |
| topic | Bayesian optimization LDMOS nelder-mead algorithm power semiconductor device powell algorithm step gate field oxide structure |
| url | https://ieeexplore.ieee.org/document/10155324/ |
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