Evidence map›Paper›PMID 40830332›Full record

ArticleLight, science & applications2025

Ultrabroadband air-dielectric double-chirped mirrors for laser frequency combs.

Tianyi Zeng, Yamac Dikmelik, Feng Xie, Kevin Lascola, David Burghoff, Qing Hu

Abstract read
In one paragraph

Article in Light, science & applications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Tianyi ZengDepartment of Electrical Engineering and Computer Science, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.
Yamac DikmelikGeneral Dynamics Mission Systems, Annapolis Junction, 20701, MD, USA.
Feng XieThorlabs Quantum Electronics (TQE), Jessup, 20794, MD, USA.
Kevin LascolaThorlabs Quantum Electronics (TQE), Jessup, 20794, MD, USA.
David BurghoffChandra Department of Electrical and Computer Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, 78712, TX, USA.ORCID http://orcid.org/0000-0001-5848-2389
Qing HuDepartment of Electrical Engineering and Computer Science, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA. qhu@mit.edu.ORCID http://orcid.org/0000-0003-1982-4053

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dispersion engineering is critical for the creation of integrated broadband laser frequency combs. In the long wavelength infrared range (LWIR, 8-13 µm), frequency combs based on quantum cascade lasers are attractive since they are monolithic, fundamental oscillators with high power levels and efficiencies. One effective approach for expanding quantum cascade laser gain bandwidth is by stacking multiple gain media with different center lasing frequencies, as this leads to flatter broadband gain spectra. However, as the gain bandwidth is increased, dispersion becomes the main limiting factor for comb bandwidth. Therefore, achieving broadband combs requires schemes that can flexibly engineer the dispersion over broad bandwidths. Here, we demonstrate the ultimate nanophotonic dispersion compensation scheme: an air-dielectric slab double-chirped mirror, which we fully integrate with the quantum cascade laser gain section. This scheme relies on the highest possible index contrast and therefore provides the maximum correction per unit length over a very broad bandwidth. With this approach, we report the successful demonstration of a broadband room-temperature LWIR laser frequency comb on a gain medium that normally does not form combs without deliberate dispersion compensations. Our air-dielectric mirrors are versatile and can be extended to other integrated laser frequency combs in different material platforms and frequency bands.

Identifiers

PMID40830332
PMCPMC12365168

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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.