Evidence map›Paper›PMID 41597846›Full record

ArticleMicromachines2025

Inverse Design of Thermal Imaging Metalens Achieving 100° Field of View on a 4 × 4 Microbolometer Array.

Munseong Bae, Eunbi Jang, Chanik Kang, Haejun Chung

Abstract read
In one paragraph

Article in Micromachines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Munseong BaeDepartment of Electronic Engineering, Hanyang University, Seoul 04763, Republic of Korea.ORCID 0009-0008-8910-6149
Eunbi JangDepartment of Artificial Intelligence Semiconductor Engineering, Hanyang University, Seoul 04763, Republic of Korea.ORCID 0000-0002-0857-1524
Chanik KangDepartment of Artificial Intelligence, Hanyang University, Seoul 04763, Republic of Korea.ORCID 0009-0006-4592-7629
Haejun ChungDepartment of Electronic Engineering, Hanyang University, Seoul 04763, Republic of Korea.ORCID 0000-0001-8959-237X

Funding

Artificial Intelligence Semiconductor Support Program IITP-(2025)-RS-2023- 00253914Global Research Support Program in the Digital Field RS-2024-00412644Hanyang University RS-2020-II201373Korea Creative Content Agency, funded by the Ministry of Culture, Sports and Tourism RS-2024-00332210Korea government (MSIT) RS-2025-02218723Korea government (MSIT) RS-2025-02283217National Research Foundation of Korea (NRF) RS-2024-00338048National Research Foundation of Korea (NRF) RS-2025-25463760
6 · The paper itself

Abstract

We present an inverse designed metalens for long-wave infrared (LWIR) imaging tailored to consumer and Internet of Things (IoT) platforms. Conventional LWIR optics either rely on costly specialty materials or suffer from low efficiency and narrow fields of view (FoV), limiting scalability. Our approach integrates adjoint-based inverse design with fabrication-aware constraints and a cone-shaped source model that efficiently captures oblique incidence during optimization. The resulting multi-level metalens achieves a wide FoV up to 100° while maintaining robust focusing efficiency and stable angle-to-position mapping on low-power 4×4 microbolometer arrays representative of edge devices. We further demonstrate application-level imaging on 4×4 microbolometer arrays, showing that the proposed metalens delivers a substantially wider FoV than a commercial narrow FoV lens while meeting low-resolution, low-cost, and low-power constraints for edge LWIR modules. By eliminating bulky multi-element stacks and reducing cost and form factor, the proposed design provides a practical pathway to compact, energy-efficient LWIR modules for consumer applications such as occupancy analytics, smart-building automation, mobile sensing, and outdoor fire surveillance.

Indexed as

adjoint optimizationinverse designlong-wave infrared (LWIR)low-resolution IoT sensorsmetalensthermal imagingwide field of view (FoV)

Identifiers

PMID41597846
PMCPMC12844331

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.