Evidence map›Paper›PMID 34683302›Full record

ReviewMicromachines2021

Oxygen Generation Using Catalytic Nano/Micromotors.

Sumayyah Naeem, Farah Naeem, Jawayria Mujtaba, Ashish Kumar Shukla, Shirsendu Mitra, Gaoshan Huang, Larisa Gulina, Polina Rudakovskaya, Jizhai Cui, Valeri Tolstoy and 4 more

Abstract readReview
In one paragraph

Review in Micromachines, 2021. 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. Metareview: a survey of active matter reviews.The European physical journal. E, Soft matter · 2025
    Review
  2. Article
  3. Micro/nanorobots for gastrointestinal tract.Frontiers in chemistry · 2024
    Review
  4. NiFeMicromachines · 2023
    Article
  5. Review
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

14 authors.

Sumayyah NaeemDepartment of Materials Science, Fudan University, Shanghai 200433, China.
Farah NaeemDepartment of Materials Science, Fudan University, Shanghai 200433, China.
Jawayria MujtabaDepartment of Materials Science, Fudan University, Shanghai 200433, China.ORCID 0000-0001-6051-1273
Ashish Kumar ShuklaDiscipline of Physics, Indian Institute of Technology Gandhinagar, Palaj 382355, Gujarat, India.ORCID 0000-0002-8405-4895
Shirsendu MitraDiscipline of Physics, Indian Institute of Technology Gandhinagar, Palaj 382355, Gujarat, India.ORCID 0000-0001-9111-7703
Gaoshan HuangDepartment of Materials Science, Fudan University, Shanghai 200433, China.ORCID 0000-0002-0525-7177
Larisa GulinaInstitute of Chemistry, Saint Petersburg State University, 26 Universitetskii Prospect, Petergof, 198504 St. Petersburg, Russia.ORCID 0000-0002-1622-4311
Polina RudakovskayaCenter of Photonics & Quantum Materials, Skolkovo Institute of Science and Technology, 3 Nobelya Str., 121205 Moscow, Russia.
Jizhai CuiDepartment of Materials Science, Fudan University, Shanghai 200433, China.
Valeri TolstoyInstitute of Chemistry, Saint Petersburg State University, 26 Universitetskii Prospect, Petergof, 198504 St. Petersburg, Russia.ORCID 0000-0003-3857-7238
Dmitry GorinCenter of Photonics & Quantum Materials, Skolkovo Institute of Science and Technology, 3 Nobelya Str., 121205 Moscow, Russia.
Yongfeng MeiDepartment of Materials Science, Fudan University, Shanghai 200433, China.
Alexander A SolovevDepartment of Materials Science, Fudan University, Shanghai 200433, China.
Krishna Kanti DeyDiscipline of Physics, Indian Institute of Technology Gandhinagar, Palaj 382355, Gujarat, India.

Funding

Department of Science and Technology DST/ICD/BRICS/PilotCall 3/BioTheraBubble/2019IIT Gandhinagar IP/IITGN/PH/KD/201617-10National Natural Science Foundation of China 51475093National Natural Science Foundation of China 51961145108RSF (Russia) 18-19-00370-PRussian Foundation for Basic Research 19-53-80047 BRICS_tScience and Engineering Research Board ECR/2017/002649Science and Technology Commission of Shanghai Municipality, the Program of Shanghai Academic Research Leader 19XD1400600Shanghai Natural Science Foundation 19ZR1402700
6 · The paper itself

Abstract

Gaseous oxygen plays a vital role in driving the metabolism of living organisms and has multiple agricultural, medical, and technological applications. Different methods have been discovered to produce oxygen, including plants, oxygen concentrators and catalytic reactions. However, many such approaches are relatively expensive, involve challenges, complexities in post-production processes or generate undesired reaction products. Catalytic oxygen generation using hydrogen peroxide is one of the simplest and cleanest methods to produce oxygen in the required quantities. Chemically powered micro/nanomotors, capable of self-propulsion in liquid media, offer convenient and economic platforms for on-the-fly generation of gaseous oxygen on demand. Micromotors have opened up opportunities for controlled oxygen generation and transport under complex conditions, critical medical diagnostics and therapy. Mobile oxygen micro-carriers help better understand the energy transduction efficiencies of micro/nanoscopic active matter by careful selection of catalytic materials, fuel compositions and concentrations, catalyst surface curvatures and catalytic particle size, which opens avenues for controllable oxygen release on the level of a single catalytic microreactor. This review discusses various micro/nanomotor systems capable of functioning as mobile oxygen generators while highlighting their features, efficiencies and application potentials in different fields.

Indexed as

active mattercatalysishydrogen peroxidemicro-/nanomotoroxygenself-propulsion

Identifiers

PMID34683302
PMCPMC8541545

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.