Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 292

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Scalable Synthesis of High Entropy Alloy Nanoparticles by Microwave Heating

Qiao, Haiyu, Saray, Mahmoud Tamadoni, Wang, Xizheng, Xu, Shaomao, Chen, Gang, Huang, Zhennan, Chen, Chaoji, Zhong, Geng, Dong, Qi, Hong, Min, Xie, Hua, Shahbazian-Yassar, Reza, Hu, Liangbing·2021·ACS Nano

Abstract

High entropy alloy nanoparticles (HEA-NPs) are reported to have superior performance in catalysis, energy storage, and conversion due to the broad range of elements that can be incorporated in these materials, enabling tunable activity, excellent thermal and chemical stability, and a synergistic catalytic effect. However, scaling the manufacturing of HEA-NPs with uniform particle size and homogeneous elemental distribution efficiently is still a challenge due to the required critical synthetic conditions where high temperature is typically involved. In this work, we demonstrate an efficient and scalable microwave heating method using carbon-based materials as substrates to fabricate HEA-NPs with uniform particle size. Due to the abundant functional group defects that can absorb microwave efficiently, reduced graphene oxide is employed as a model substrate to produce an average temperature reaching as high as ∼1850 K within seconds. As a proof-of-concept, we utilize this rapid, high-temperature heating process to synthesize PtPdFeCoNi HEA-NPs, which exhibit an average particle size of ∼12 nm and uniform elemental mixing resulting from decomposition nearly at the same time and liquid metal solidification without diffusion. Various carbon-based materials can also be employed as substrates, including one-dimensional carbon nanofibers and three-dimensional carbonized wood, which can achieve temperatures of >1400 K. This facile and efficient microwave heating method is also compatible with the roll-to-roll process, providing a feasible route for scalable HEA-NPs manufacturing.

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 · 10.1021/acsnano.1c05113

Cites

48 of 48 references verified0 citation errors · 0 not checkable

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

Cites

Show all 48 references

Cited by

See all 292

Metadata

Authors
Qiao, H., Saray, M. T., Wang, X., Xu, S., Chen, G., Huang, Z., Chen, C., Zhong, G., Dong, Q., Hong, M., Xie, H., Shahbazian-Yassar, R., & Hu, L.
Venue
ACS Nano
Published
2021-08-23
Volume
15
Issue
9
Pages
14928-14937
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W3193989662
Cited by
292
References
48
FWCI
15.84
Type
journal article
Language
en
Open access
closed

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: Scalable Synthesis of High Entropy Alloy Nanoparticles by Microwave Heating. https://app.cochat.ai/papers/10.1021/acsnano.1c05113
The paper
Qiao, H., Saray, M. T., Wang, X., Xu, S., Chen, G., Huang, Z., Chen, C., Zhong, G., Dong, Q., Hong, M., Xie, H., Shahbazian-Yassar, R., & Hu, L. (2021). Scalable Synthesis of High Entropy Alloy Nanoparticles by Microwave Heating. ACS Nano. https://doi.org/10.1021/acsnano.1c05113

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.