Physics informed neural network surrogate modeling and global sensitivity analysis of magnetized nanofluid flow over a porous cylinder for solar thermal energy applications
- DOI
- 10.1186/s11671-026-05023-5
- Published
- 2026-10-28
- Container
- Discover Nano
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1186/s11671-026-05023-5,
title = {Physics informed neural network surrogate modeling and global sensitivity analysis of magnetized nanofluid flow over a porous cylinder for solar thermal energy applications},
author = {Mohib Hussain and Abdullah Alhushaybari},
year = {2026},
journal = {Discover Nano},
doi = {10.1186/s11671-026-05023-5},
url = {https://doi.org/10.1186/s11671-026-05023-5}
}RIS
TY - JOUR TI - Physics informed neural network surrogate modeling and global sensitivity analysis of magnetized nanofluid flow over a porous cylinder for solar thermal energy applications AU - Mohib Hussain AU - Abdullah Alhushaybari PY - 2026 JO - Discover Nano DO - 10.1186/s11671-026-05023-5 UR - https://doi.org/10.1186/s11671-026-05023-5 ER -
APA
Hussain, M., & Alhushaybari, A. (2026). Physics informed neural network surrogate modeling and global sensitivity analysis of magnetized nanofluid flow over a porous cylinder for solar thermal energy applications. Discover Nano. https://doi.org/10.1186/s11671-026-05023-5
Source records
- crossref · retrieved 2026-11-10T13:16:50.906Z