Strain-engineered high-responsivity MoTe2 photodetector for silicon photonic integrated circuits

R. Maiti, C. Patil, M. A.S.R. Saadi, T. Xie, J. G. Azadani, B. Uluutku, R. Amin, A. F. Briggs, M. Miscuglio, D. Van Thourhout, S. D. Solares, T. Low, R. Agarwal, S. R. Bank, V. J. Sorger

Research output: Contribution to journalArticlepeer-review

223 Scopus citations

Abstract

In integrated photonics, specific wavelengths such as 1,550 nm are preferred due to low-loss transmission and the availability of optical gain in this spectral region. For chip-based photodetectors, two-dimensional materials bear scientifically and technologically relevant properties such as electrostatic tunability and strong light–matter interactions. However, no efficient photodetector in the telecommunication C-band has been realized with two-dimensional transition metal dichalcogenide materials due to their large optical bandgaps. Here we demonstrate a MoTe2-based photodetector featuring a strong photoresponse (responsivity 0.5 A W–1) operating at 1,550 nm in silicon photonics enabled by strain engineering the two-dimensional material. Non-planarized waveguide structures show a bandgap modulation of 0.2 eV, resulting in a large photoresponse in an otherwise photoinactive medium when unstrained. Unlike graphene-based photodetectors that rely on a gapless band structure, this photodetector shows an approximately 100-fold reduction in dark current, enabling an efficient noise-equivalent power of 90 pW Hz0.5. Such a strain-engineered integrated photodetector provides new opportunities for integrated optoelectronic systems.

Original languageEnglish (US)
Pages (from-to)578-584
Number of pages7
JournalNature Photonics
Volume14
Issue number9
DOIs
StatePublished - Sep 1 2020

Bibliographical note

Funding Information:
V.J.S. is supported by AFOSR (grant no. FA9550-17-1-0377) and ARO (grant no. W911NF-16-2-0194). M.A.S.R.S., B.U. and S.D.S. acknowledge support from the US Department of Energy, Office of Science, Basic Energy Sciences under award no. DE-SC0018041. S.R.B. acknowledges support from NSF grant nos. DMR-1839175 and CCF-1838435. We acknowledge computational support from the Minnesota Supercomputing Institute (MSI).

Publisher Copyright:
© 2020, The Author(s), under exclusive licence to Springer Nature Limited.

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