Bayesian Machine Learning for Efficient Minimization of Defects in ALD Passivation Layers-Reference-Cited by-同舟云学术

Bayesian Machine Learning for Efficient Minimization of Defects in ALD Passivation Layers

Published:2021-11-04 Issue:45 Volume:13 Page:54503-54515
ISSN:1944-8244
Container-title:ACS Applied Materials & Interfaces
language:en
Short-container-title:ACS Appl. Mater. Interfaces

Author:

Dogan Gül¹²,Demir Sinan O.²,Gutzler Rico³,Gruhn Herbert⁴,Dayan Cem B.²,Sanli Umut T.²,Silber Christian¹,Culha Utku²,Sitti Metin²^ORCID,Schütz Gisela²,Grévent Corinne¹,Keskinbora Kahraman²

Affiliation:

1. Robert Bosch GmbH, Automotive Electronics, Postfach 13 42, 72703 Reutlingen, Germany

2. Max Planck Institute for Intelligent Systems, Heisenbergstr 3, 70569 Stuttgart, Germany

3. Max Planck Institute for Solid State Research, Heisenbergstr 1, 70569 Stuttgart, Germany

4. Robert Bosch GmbH, Corporate Sector Research and Advance Engineering , Robert-Bosch-Campus1, 71272 Stuttgart, Germany

Funder

Milli E??itim Bakanli??i

H2020 European Research Council

Publisher

American Chemical Society (ACS)

Subject

General Materials Science

Link

https://pubs.acs.org/doi/pdf/10.1021/acsami.1c14586

Reference94 articles.

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5. Development of a Deep Silicon Phase Fresnel Lens Using Gray-Scale Lithography and Deep Reactive Ion Etching

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