Evidence map›Paper›PMID 39738203›Full record

ArticleScientific reports2024

Graphene metamaterial solar absorber using Al-TiN-Fe for efficient solar thermal energy conversion and optimization using machine learning.

Khaled Aliqab, Bo Bo Han, Om Prakash Kumar, Meshari Alsharari, Ammar Armghan, Shobhit K Patel

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 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.

Khaled AliqabDepartment of Electrical Engineering, College of Engineering, Jouf University, 72388, Sakaka, Saudi Arabia.
Bo Bo HanDepartment of Information and Communication Technology, Marwadi University, Rajkot, 360003, India.
Om Prakash KumarDepartment of Electronics and Communication Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India. omprakash.kumar@manipal.edu.
Meshari AlsharariDepartment of Electrical Engineering, College of Engineering, Jouf University, 72388, Sakaka, Saudi Arabia.
Ammar ArmghanDepartment of Electrical Engineering, College of Engineering, Jouf University, 72388, Sakaka, Saudi Arabia. aarmghan@ju.edu.sa.
Shobhit K PatelDepartment of Computer Engineering, Marwadi University, Rajkot, 360003, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The contributed absorber design in graphene addition with the displacement of three materials for resonator design in Aluminum (Al), the middle substrate position with Titanium nitride (TiN), and the ground layer deposition by Iron (Fe) respectively. For the absorption validation highlight, the best four absorption wavelengths (µm) of 0.29, 0.58, 1, and 2 are also selected to indicate the changes in radiation outputs for every observation. With the displacement of wavelength and bandwidth configuration, the current absorber is observed at 97.32% (more than 97%) for 1.5-2.5 µm wavelength range (1000 nm bandwidth) and above 95% rate (95.38%) is displayed by the 2000 nm bandwidth due to 0.5 and 2.5 µm wavelength separation. The 2800 nm band rate demonstration by 0.2-3 µm wavelength separation verifies 92.42%. For every analysis in this work, the output radiation is shown in ultraviolet region (UV), visible spectrum (Vis), and near-infrared (NIR) area respectively. In the following distribution of the current absorber, the design development in lithography and step-by-step, parametric assignment and AM configuration, radiation analysis for each parameter changes in graph presentation and conclusion. Additionally, the ML approach is applied to reduce the time required in the study. The current solar absorber in the new design can be generated for the multi-solar purposes of water heating, lighting, ventilation, charging for electronic devices, and electric vehicle transportation.

Indexed as

GrapheneHeatingMachine learningPlasmonicSolar absorberSurface plasmon resonance

Identifiers

PMID39738203
PMCPMC11685637

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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.