Evidence map›Paper›PMID 40243918›Full record

ArticleSmall methods2025

Efficient Large-Area Graphene p-n Junction Terahertz Receivers on an Integrated Optical Platform.

Leonardo Viti, Vladimir Pushkarev, Syed Muhammad Abouzar Sarfraz, Gaetano Scamarcio, Miriam S Vitiello

Abstract read
In one paragraph

Article in Small methods, 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

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. Review
  2. 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

5 authors.

Leonardo VitiNEST, CNR-Istituto Nanoscienze and Scuola Normale Superiore, Piazza San Silvestro 12, Pisa, 56127, Italy.ORCID https://orcid.org/0000-0002-4844-2081
Vladimir PushkarevNEST, CNR-Istituto Nanoscienze and Scuola Normale Superiore, Piazza San Silvestro 12, Pisa, 56127, Italy.
Syed Muhammad Abouzar SarfrazDipartimento Interateneo di Fisica, Università degli studi di Bari, Via Amendola 173, Bari, Italy.
Gaetano ScamarcioDipartimento Interateneo di Fisica, Università degli studi di Bari, Via Amendola 173, Bari, Italy.ORCID https://orcid.org/0000-0003-0808-4336
Miriam S VitielloNEST, CNR-Istituto Nanoscienze and Scuola Normale Superiore, Piazza San Silvestro 12, Pisa, 56127, Italy.ORCID https://orcid.org/0000-0002-4914-0421

Funding

European Union - Next Generation EUH2020 European Research Council 101157731
6 · The paper itself

Abstract

The integration of graphene-based p-n junctions into photonic or optoelectronic platforms can allow efficient guiding and absorption of the light signals into the detection element, promising a major improvement in the efficiency of the system, by minimizing optical losses and enhancing the light coupling. These platforms can also potentially provide additional functionalities, such as frequency filtering, modulation, or multiplexing of the signals. At terahertz (THz) frequencies, this can lead to a variety of new applications such as sensing, imaging, and communication, as well as advancements in high-speed electronics and wireless technologies. Here, we took advantage of large area industrial-scale graphene, realized via an inexpensive production process, to engineer an antenna-integrated graphene Salisbury screen (AgSS) p-n junction photodetector, in which the electromagnetic coupling between graphene and the free-space wavelength is optimized by controlling the antenna dimensions and its distance from a sub-wavelength thin reflective mirror. Room-temperature noise equivalent powers < 300 pWHz

Indexed as

grapheneSalisbury screenterahertz

Identifiers

PMID40243918
PMCPMC12641380

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.