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Photodetectors Based on Emerging Materials
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems.ORCID iD: 0000-0002-6430-6135
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electronics and Embedded systems.ORCID iD: 0000-0002-5845-3032
2023 (English)In: Springer Handbook of Semiconductor Devices / [ed] Massimo Rudan, Rossella Brunetti, Susanna Reggiani, Springer Nature , 2023, p. 777-805Chapter in book (Refereed)
Abstract [en]

Photodetectors that convert light into electrical signals have become an indispensable element for a large number of technologies to enable extensive applications, ranging from optical communications to advanced imaging and motion detection, to automotive industry particularly including self-driving cars, and to astronomy and space exploration under harsh environment. The present photodetector market is predominated by silicon (CMOS-based) photodetectors. With the continuous growth of application areas, highly desired are photodetectors of higher performance in terms of speed, efficiency, detectable wavelength range, and integrability with semiconductor technology. These necessitate the development of new photodetectors based on special materials, rather than the conventional silicon single crystals, as building blocks for various advanced photodetection platforms. To this end, we summarize in this chapter the recent status of advanced photodetectors based on the emerging material, graphene. Our discussion includes the performance metrics, working mechanisms, practical implementation, as well as opportunities and challenges, for graphene-based photodetectors. 

Place, publisher, year, edition, pages
Springer Nature , 2023. p. 777-805
Series
Springer Handbooks, ISSN 2522-8692, E-ISSN 2522-8706
Keywords [en]
3D substrates, Charge neutrality point, Graphene, Heterostructure, Optical cavity, Photodetection mechanism, Photodetectors, Waveguide
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:kth:diva-329008DOI: 10.1007/978-3-030-79827-7_21Scopus ID: 2-s2.0-85142031315OAI: oai:DiVA.org:kth-329008DiVA, id: diva2:1767629
Note

QC 20230614

Available from: 2023-06-14 Created: 2023-06-14 Last updated: 2023-06-14Bibliographically approved

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Li, JiantongÖstling, Mikael

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