ArticleNature communications2025
Accurate and rapid measurement of fluid thermal conductivity.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Thermal and dielectric performance of transformer oil-based nanofluid with fullerene CScientific reports · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
A rapid energy transition will require new heat transfer fluids, and a faster means of discovering and optimizing them. Existing methods, however, are constrained by speed, accuracy, and sample volume - with accurate measurements requiring large sample volumes and long equilibration times. Here, we present a measurement approach that bypasses precise temperature measurement and heat flux measurements. Thermal conductivity, k, is determined by comparing thermally driven voltage variations across an array of resistive heaters embedded in fluid cavities. This measurement, relative to the reference material, minimizes errors from ambient temperature fluctuation, unquantified heat losses, and measurement uncertainties, and it eliminates direct temperature sensing. We report a microfluidic device and measurement method that implements in-run on-chip auto-calibration with a reference material; we test the device on a wide range of substances, including liquids, gases, mixtures, and nanofluids. It delivers results in <10 s, using ~5 µL of sample, about two orders of magnitude faster than conventional steady-state methods - while maintaining accuracy competitive with gold-standard techniques (mean signed error 0.0030 ± 0.0059 W/(m · K) (1.4% ± 3.1%), median absolute error 0.0019 W/(m · K) (MAPE 2.6 %), and expanded uncertainty of k, U = 8.3% ± 0.24% (SD across 10 runs)). This approach makes thermal conductivity measurement accessible to accelerated materials discovery and optimization workflows.
Identifiers
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Registered trials
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.