Design of Ultra-Compact and High-Efficiency Waveguide Bends on Lithium Niobate Thin Films.

Yi-Wen Wang, Zhi-Chen Wei, Xiao-Dong Wen, Tian-Xue Ma

Abstract read

In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yi-Wen WangSchool of Mathematics and Physics, Lanzhou Jiaotong University, Lanzhou 730070, China.

Zhi-Chen WeiSchool of Mathematics and Physics, Lanzhou Jiaotong University, Lanzhou 730070, China.

Xiao-Dong WenSchool of Mathematics and Physics, Lanzhou Jiaotong University, Lanzhou 730070, China.

Tian-Xue MaDepartment of Mechanics, School of Physical Science and Engineering, Beijing Jiaotong University, Beijing 100044, China.

Funding

Founda-tion for Innovative Fundamental Research Group Project of Gansu Province 25JRRA805Gansu Provincial Science and Technology Department 20JR10RA252Lanzhou Jiaotong University LH2025019

6 · The paper itself

Abstract

This paper systematically investigates the structural design and numerical characterization of ultra-compact low-loss waveguide bends on lithium niobate-on-insulator (LNOI) thin films via 3D-FDTD simulations. Six 90° bend architectures are analyzed to unravel transmission behaviors and intrinsic loss mechanisms, including three smooth bend optimizations: straight-bend lateral offset, local width tapering, and Euler-circular hybrid curvature modulation, alongside resonant-cavity and corner-mirror L-shaped bends. All structures achieve evident loss reduction within proper parameter windows. At

Indexed as

integrated opticslithium niobate thin filmwaveguide bends

Identifiers

PMID42646413

DOI10.3390/nano16161004

PMCPMC13516482

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.