Evidence map›Paper›PMID 38133011›Full record

ArticleNanomaterials (Basel, Switzerland)2023

On-Chip Integration of a Plasmonic FET Source and a Nano-Patch Antenna for Efficient Terahertz Wave Radiation.

Justin Crabb, Xavier Cantos-Roman, Gregory Aizin, Josep Miquel Jornet

Open access · goldAbstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 39% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

4 authors at 2 institutions in 1 country.

Justin CrabbDepartment of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA.ORCID 0000-0001-8255-7707
Xavier Cantos-RomanDepartment of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA.ORCID 0000-0003-1016-3607
Gregory AizinKingsborough College, The City University of New York, Brooklyn, NY 11235, USA.
Josep Miquel JornetDepartment of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA.ORCID 0000-0001-6351-1754
Northeastern University · USCity University of New York · US

Funding

National Science Foundation CNS- 312 2011411United States Air Force Office of Scientific Research A9550-16-1-0188
6 · The paper itself

Abstract

Graphene-based Field-Effect Transistors (FETs) integrated with microstrip patch antennas offer a promising approach for terahertz signal radiation. In this study, a dual-stage simulation methodology is employed to comprehensively investigate the device's performance. The initial stage, executed in MATLAB, delves into charge transport dynamics within a FET under asymmetric boundary conditions, employing hydrodynamic equations for electron transport in the graphene channel. Electromagnetic field interactions are modeled via Finite-Difference Time-Domain (FDTD) techniques. The second stage, conducted in COMSOL Multiphysics, focuses on the microstrip patch antenna's radiative characteristics. Notably, analysis of the S11 curve reveals minimal reflections at the FET's resonant frequency of 1.34672 THz, indicating efficient impedance matching. Examination of the radiation pattern demonstrates the antenna's favorable directional properties. This research underscores the potential of graphene-based FETs for terahertz applications, offering tunable impedance matching and high radiation efficiency for future terahertz devices.

Indexed as

antennagrapheneplasmonicterahertztransistor

Identifiers

PMID38133011
PMCPMC10746025
OpenAlexW4389548741

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.