Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Fabrication and Characterization of InP Fresnel Microlenses

Not Accessible

Your library or personal account may give you access

Abstract

High-power applications for diode lasers have recently been of increasing interest. In particular, one- and two-dimensional laser arrays are being investigated for this purpose. Among the most promising approaches for achieving coherent operation of the lasers in these arrays is the use of an external cavity. Successful implementations of such a system have been reported recently [1,2,3]. Since diode lasers typically have a beam divergence of a few tens of degrees, collimating the laser outputs leads to greatly improved far-field patterns, which, in turn, translates into more power in the main lobe of the combined output. Achieving this collimation in the case of a diode laser array, with its small device-to-device distance, requires an array of similarly spaced microlenses with very short focal length, small diameter and small F number. In this paper, we describe the fabrication and performance of a Fresnel microlens array etched directly in InP wafers: these microlenses have been used successfully to collimate the output of GaInAsP/InP buried-heterostructure (BH) diode lasers [4].

© 1987 Optical Society of America

PDF Article
More Like This
Fabrication and Characterization of Semiconductor Microlens Arrays

V. Diadiuk, Z. L. Liau, and J.N. Walpole
JWD1 International Lens Design (IODC) 1990

Diode Lasers with Cylindrical Mirror Facets and Reduced Beam Divergence

J. N. Walpole, Z. L. Liau, L. J. Missaggia, and D. Yap
WA8 Semiconductor Lasers (ASLA) 1987

InGaAsP/InP planar buried heterostructure laser with semi-insulating InP current blocking layers grown by MOCVD

K. Wakao, K. Nakai, T. Sanada, M. Kuno, and S. Yamakoshi
TuD5 Semiconductor Lasers (ASLA) 1987

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.