Evidence map›Paper›PMID 40026418›Full record

ArticleIEEE sensors journal2024

Experimental Study of Spectrally Selective MEMS/Metasurface Infrared Detectors.

Melisa Ekin Gülseren, Matthew Benson, Ryan W Parker, Jeronimo Segovia-Fernandez, Ernest Ting-Ta Yen, J Sebastián Gómez-Díaz

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in IEEE sensors journal, 2024. 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

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

2 citing papers in PubMed.

  1. Article
  2. Automatic Characterization of High-Performance MEMS-Based IR Sensors.IEEE access : practical innovations, open solutions · 2024
    Article
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.

Melisa Ekin GülserenElectrical and Computer Engineering Department, University of California, Davis, CA 95616 USA.ORCID 0000-0002-9375-2337
Matthew BensonElectrical and Computer Engineering Department, University of California, Davis, CA 95616 USA.ORCID 0009-0001-8228-534X
Ryan W ParkerElectrical and Computer Engineering Department, University of California, Davis, CA 95616 USA.
Jeronimo Segovia-FernandezKilby Labs-Texas Instrument, Santa Clara, CA 95051 USA.ORCID 0000-0003-4942-6080
Ernest Ting-Ta YenKilby Labs-Texas Instrument, Santa Clara, CA 95051 USA.
J Sebastián Gómez-DíazElectrical and Computer Engineering Department, University of California, Davis, CA 95616 USA.ORCID 0000-0002-6852-8317

Funding

Neural-network enabled nano-spectroscopy for label-free cancer detection in biofluidsR01CA273253 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Randy Carney, Juan Sebastian Gomez Diaz · 2023 to 2026
$2.8M
NCI NIH HHS R01 CA273253
6 · The paper itself

Abstract

This article reports a comprehensive statistical analysis of uncooled infrared (IR) detectors based on radio frequency (RF) aluminum nitride (AlN) contour mode resonators (CMRs) integrated with spectrally selective IR metasurfaces. Moreover, it reports the lowest noise equivalent power (NEP) recorded from these types of devices

Indexed as

Aluminum nitride (AlN)infrared (IR) detectormetasurfacemicroelectromechanical system (MEMS) resonatorperfect material absorber

Identifiers

PMID40026418
PMCPMC11870673

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.