Evidence map›Paper›PMID 42646410›Full record

ArticleNanomaterials (Basel, Switzerland)2026

Generation Characteristics and Regulation Mechanisms of Monodisperse Droplets of JP-10-Based Nanofluids via Drop-on-Demand Technology.

Bingzheng Wang, Tianhang Wang, Zixuan Zhou, Hui Wang, Shengji Li, Xuefeng Huang

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

6 authors.

Bingzheng WangInstitute of Energy, Department of Physics, Hangzhou Dianzi University, Hangzhou 310018, China.
Tianhang WangInstitute of Energy, Department of Physics, Hangzhou Dianzi University, Hangzhou 310018, China.
Zixuan ZhouInstitute of Energy, Department of Physics, Hangzhou Dianzi University, Hangzhou 310018, China.
Hui WangInstitute of Energy, Department of Physics, Hangzhou Dianzi University, Hangzhou 310018, China.
Shengji LiCollege of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0000-0002-2687-9805
Xuefeng HuangInstitute of Energy, Department of Physics, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0000-0002-6511-3538

Funding

National Natural Science Foundation of China 52027809
6 · The paper itself

Abstract

JP-10 is a pivotal high-density hydrocarbon fuel for advanced aerospace propulsion systems. Doping aluminum nanoparticles to prepare nanofluid fuels is a promising route to enhance its energy density and combustion performance, yet the droplet formation mechanism of such multiphase fuels remains poorly understood, hindering single-droplet combustion research and atomization system optimization. This work constructed a piezoelectric drop-on-demand (DOD) monodisperse droplet generation platform integrated with phase Doppler anemometry (PDA) and high-speed imaging. Using Al/JP-10/OA nanofluids with aluminum mass fractions of 0.1 wt. %, 0.5 wt. % and 1.0 wt. %, we systematically explored the effects of liquid flow rate, driving frequency and particle concentration on droplet size, size uniformity and ejection velocity. In this work, Al/JP-10/OA nanofluids with aluminum mass fractions of 0.1 wt. %, 0.5 wt. % and 1.0 wt. % were tested under liquid flow rates of 1.1-1.5 mL/min and driving frequencies of 10-50 kHz, with measured droplet diameter ranging from 241.04 μm to 292.26 μm and ejection velocity ranging from 1.65 m/s to 2.45 m/s. The results demonstrate that average droplet diameter increases linearly with flow rate and decreases monotonically with driving frequency. Compared with the 0.1 wt. % nanofluid, the 1.0 wt. % nanofluid shows a 4.4% larger droplet diameter and 12.1% lower ejection velocity, while the 0.1 wt. % sample retains excellent monodispersity with a size

Indexed as

droplet breakup mechanismdrop-on-demandJP-10-based nanofluidsmonodisperse dropletsphase Doppler anemometry

Identifiers

PMID42646410
PMCPMC13515627

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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.