Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 167

The DOI matches its Crossref record.

A Single Picture Explains Diversity of Hyperthermia Response of Magnetic Nanoparticles

Open access
Conde-Leboran, Ivan, Baldomir, Daniel, Martinez-Boubeta, Carlos, Chubykalo-Fesenko, Oksana, del Puerto Morales, María, Salas, Gorka, Cabrera, David, Camarero, Julio, Teran, Francisco J., Serantes, David·2015·The Journal of Physical Chemistry C

Abstract

Progress in the design of nanoscale magnets for localized hyperthermia cancer therapy has been largely driven by trial-and-error approaches, for instance, by changing of the stoichiometry composition, size, and shape of the magnetic entities. So far, widely different and often conflicting heat dissipation results have been reported, particularly as a function of the nanoparticle concentration. Thus, achieving hyperthermia-efficient magnetic ferrofluids remains an outstanding challenge. Here we demonstrate that diverging heat-dissipation patterns found in the literature can be actually described by a single picture accounting for both the intrinsic magnetic features of the particles (anisotropy, magnetization) and experimental conditions (concentration, magnetic field). Importantly, this general magnetic-hyperthermia scenario also predicts a novel non-monotonic concentration dependence with optimum heating features, which we experimentally confirmed in iron oxide nanoparticle ferrofluids by fine-tuning the particle size. Overall, our approach implies a magnetic hyperthermia trilemma that may constitute a simple strategy for development of magnetic nanomaterials for optimal hyperthermia efficiency.

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/acs.jpcc.5b02555

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

Metadata

Authors
Conde-Leboran, I., Baldomir, D., Martinez-Boubeta, C., Chubykalo-Fesenko, O., del Puerto Morales, M., Salas, G., Cabrera, D., Camarero, J., Teran, F. J., & Serantes, D.
Venue
The Journal of Physical Chemistry C
Published
2015-06-24
Volume
119
Issue
27
Pages
15698-15706
ISSN
  • 1932-7447 (ISSN-L)
  • 1932-7455
OpenAlex
W2515065431
Cited by
167
References
0
FWCI
9.28
Type
journal article
Language
en
Open access
green

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

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.