Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,760

The DOI matches its Crossref record.

“Green” Nanotechnologies: Synthesis of Metal Nanoparticles Using Plants

Open access
Makarov, V V, Love, A. J., Sinitsyna, O. V., Makarova, S. S., Yaminsky, I. V., Taliansky, M. E., Kalinina, N. O.·2014·Acta Naturae

Abstract

While metal nanoparticles are being increasingly used in many sectors of the economy, there is growing interest in the biological and environmental safety of their production. The main methods for nanoparticle production are chemical and physical approaches that are often costly and potentially harmful to the environment. The present review is devoted to the possibility of metal nanoparticle synthesis using plant extracts. This approach has been actively pursued in recent years as an alternative, efficient, inexpensive, and environmentally safe method for producing nanoparticles with specified properties. This review provides a detailed analysis of the various factors affecting the morphology, size, and yield of metal nanoparticles. The main focus is on the role of the natural plant biomolecules involved in the bioreduction of metal salts during the nanoparticle synthesis. Examples of effective use of exogenous biomatrices (peptides, proteins, and viral particles) to obtain nanoparticles in plant extracts are discussed.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.32607/20758251-2014-6-1-35-44

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 1,760

Metadata

Authors
Makarov, V. V., Love, A. J., Sinitsyna, O. V., Makarova, S. S., Yaminsky, I. V., Taliansky, M. E., & Kalinina, N. O.
Venue
Acta Naturae
Published
2014-03-15
Volume
6
Issue
1
Pages
35-44
ISSN
  • 2075-8243 (ISSN-L)
  • 2075-8251
OpenAlex
W4294117312
Cited by
1,760
References
0
FWCI
25.46
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: “Green” Nanotechnologies: Synthesis of Metal Nanoparticles Using Plants. https://app.cochat.ai/papers/10.32607/20758251-2014-6-1-35-44
The paper
Makarov, V. V., Love, A. J., Sinitsyna, O. V., Makarova, S. S., Yaminsky, I. V., Taliansky, M. E., & Kalinina, N. O. (2014). “Green” Nanotechnologies: Synthesis of Metal Nanoparticles Using Plants. Acta Naturae. https://doi.org/10.32607/20758251-2014-6-1-35-44

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.