Evidence map›Paper›PMID 30914729›Full record

ArticleScientific reports2019

Green synthesis of nitrogen-doped self-assembled porous carbon-metal oxide composite towards energy and environmental applications.

Arpita Ghosh, Sreetama Ghosh, Garapati Meenakshi Seshadhri, Sundara Ramaprabhu

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Supercapacitive Carbon-Coated δ-MnOSmall (Weinheim an der Bergstrasse, Germany) · 2026
    Article
  2. Article
  3. Engineering 3D Heterostructured NiCoNanomaterials (Basel, Switzerland) · 2025
    Article
  4. Coupling of MnNanomaterials (Basel, Switzerland) · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. 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.

Arpita GhoshAlternative Energy and Nanotechnology Laboratory (AENL), Nano Functional Materials Technology Center (NFMTC), Department of Physics, Indian Institute of Technology Madras, Chennai, 600036, India.
Sreetama GhoshAlternative Energy and Nanotechnology Laboratory (AENL), Nano Functional Materials Technology Center (NFMTC), Department of Physics, Indian Institute of Technology Madras, Chennai, 600036, India.
Garapati Meenakshi SeshadhriAlternative Energy and Nanotechnology Laboratory (AENL), Nano Functional Materials Technology Center (NFMTC), Department of Physics, Indian Institute of Technology Madras, Chennai, 600036, India.
Sundara RamaprabhuAlternative Energy and Nanotechnology Laboratory (AENL), Nano Functional Materials Technology Center (NFMTC), Department of Physics, Indian Institute of Technology Madras, Chennai, 600036, India. ramp@iitm.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing environmental pollution, shortage of efficient energy conversion and storage devices and the depletion of fossil fuels have triggered the research community to look for advanced multifunctional materials suitable for different energy-related applications. Herein, we have discussed a novel and facile synthesis mechanism of such a carbon-based nanocomposite along with its energy and environmental applications. In this present work, nitrogen-doped carbon self-assembled into ordered mesoporous structure has been synthesized via an economical and environment-friendly route and its pore generating mechanism depending on the hydrogen bonding interaction has been highlighted. Incorporation of metal oxide nanoparticles in the porous carbon network has significantly improved CO

Identifiers

PMID30914729
PMCPMC6435743

What OpenQuestion holds

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Registered trials

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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.