Evidence map›Paper›PMID 35214428›Full record

ArticleSensors (Basel, Switzerland)2022

Impedance Spectroscopy of Hierarchical Porous Nanomaterials Based on por-Si, por-Si Incorporated by Ni and Metal Oxides for Gas Sensors.

Anton Bobkov, Victor Luchinin, Vyacheslav Moshnikov, Svetlana Nalimova, Yulia Spivak

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. WOMolecules (Basel, Switzerland) · 2025
    Article
  4. Article
  5. 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.

Anton BobkovDepartment of Micro- and Nanoelectronics, Saint Petersburg Electrotechnical University "LETI", Professor Popov Str. 5, 197376 St. Petersburg, Russia.ORCID 0000-0002-0209-9273
Victor LuchininDepartment of Micro- and Nanoelectronics, Saint Petersburg Electrotechnical University "LETI", Professor Popov Str. 5, 197376 St. Petersburg, Russia.
Vyacheslav MoshnikovDepartment of Micro- and Nanoelectronics, Saint Petersburg Electrotechnical University "LETI", Professor Popov Str. 5, 197376 St. Petersburg, Russia.
Svetlana NalimovaDepartment of Micro- and Nanoelectronics, Saint Petersburg Electrotechnical University "LETI", Professor Popov Str. 5, 197376 St. Petersburg, Russia.
Yulia SpivakDepartment of Micro- and Nanoelectronics, Saint Petersburg Electrotechnical University "LETI", Professor Popov Str. 5, 197376 St. Petersburg, Russia.ORCID 0000-0002-5852-999X

Funding

Development program of ETU "LETI" within the framework of the program of strategic academic leadership" Priority-2030 No 075-15-2021-1318 on 29 Sept 2021 075-15-2021-1318
6 · The paper itself

Abstract

Approaches are being developed to create composite materials with a fractal-percolation structure based on intercalated porous matrices to increase the sensitivity of adsorption gas sensors. Porous silicon, nickel-containing porous silicon, and zinc oxide have been synthesized as materials for such structures. Using the impedance spectroscopy method, it has been shown that the obtained materials demonstrate high sensitivity to organic solvent vapors and can be used in gas sensors. A model is proposed that explains the high sensitivity and inductive nature of the impedance at low frequencies, considering the structural features and fractal-percolation properties of the obtained oxide materials.

Indexed as

adsorption gas sensorsfractalgas sensorimpedance spectroscopypercolationporous siliconzinc oxide

Identifiers

PMID35214428
PMCPMC8877289

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.