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Flame synthesis achieves compositionally tailorable high-entropy metal-containing nanomaterials

Abstract

High-entropy metal-containing nanomaterials have garnered interest in diverse fields such as electrocatalysis and energy conversion. Their synthesis typically requires high temperatures (>1,000 K) to facilitate homogeneous mixing and rapid transformation of metal precursors. However, current state-of-the-art approaches typically involve complex reaction environments and require specialized equipment and operations. Herein we demonstrate a versatile flame synthesis process to fabricate high-entropy metallic single atoms and/or nanoparticles supported on soot-like carbon via blending organometallic precursors into fuel (namely, paraffin wax) and subsequent burning. The high flame temperature (~1,800 K) enables strong metal–carbon association with tailorable chemistry and homogeneous bonding between dissimilar metallic elements (up to 25 metals studied), regardless of their thermodynamic compatibility. Additionally, we show high-performance electrosynthesis of hydrogen peroxide to highlight this approach as a promising method for electrocatalyst development.

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Fig. 1: Flame synthesis of metal-containing nanomaterials.
Fig. 2: Transition from SAs to NPs.
Fig. 3: High-entropy SAs (Fe, Co, Ni, Cu and Pd) supported by soot NPs.
Fig. 4: Flame synthesis of HMN library.
Fig. 5: Metal–soot clustering simulations.

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Data availability

All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Information. Source data are provided with this paper.

Code availability

Codes for MD simulations are provided as part of the replication package in the Supplementary Information.

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Acknowledgements

We thank C. Ma from the Analytical Instrumentation Center of Hunan University for his assistance with the spherical aberration-corrected transmission electron microscopy analysis. The electron spin resonance spectroscopy experiments were performed at the State Key Laboratory of Chemo and Biosensing. E.G. acknowledges the Materials and Process Simulation (MAPS) Scienomics platform. In terms of funding, this research was supported by the following grants, schemes and fellowships: National Natural Science Foundation of China (S.P., grant nos 22378105 and 23FAA02526), Department of Science and Technology of Hunan Province (S.P., project no. 2022TP2032), National Supercomputing Center in Changsha (S.P., grant no. G2023016), Australian Research Council Future Fellowship (J.J.R., grant no. FT210100669) and the XAS and the SAXS/WAXS beamlines at the Australian Synchrotron, part of the Australian Nuclear Science and Technology Organisation (S.P., project nos 18766, 20570 and 21771).

Author information

Authors and Affiliations

Authors

Contributions

S.P. conceived the idea (with the assistance of Z.L. and R.G.) and designed and led the project. All authors performed research and/or analysed data with intellectual contributions. S.P., F.C. and Z.L. drafted the manuscript with input from all authors. All authors approved the final version of the manuscript.

Corresponding authors

Correspondence to Rui Guo, Frank Caruso or Shuaijun Pan.

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The authors declare no competing interests.

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Peer review information

Nature Chemistry thanks Feng Jiao, Mark Swihart and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–98, Tables 1–15, Materials and Methods, captions for Supplementary Videos 1–9, captions for Supplementary Data 1 and 2, captions for Supplementary Codes 1–5 and refs. 1–58.

Supplementary Data 1

Literature review on metal–carbon nanomaterials including HMNs. These reports mentioned in our work are a random selection of the literature published in the past decade. These reports are all based on carbon-supported metal-containing nanomaterials in the field including catalysis and energy storage. Specifically, the number of metals was collated in our work (Fig. 1e). This file is provided separately.

Supplementary Data 2

Flow information from Aspen simulations. The data include the flow details occurring at the reaction, the separation and the concentration sections, which were extracted from the Aspen simulation module.

Supplementary Code 1

The file describes the initial configuration of 200 coronene molecules and 400 Co atoms.

Supplementary Code 2

The file describes the ReaxFF force-field parameters.

Supplementary Code 3

The file describes the main input script.

Supplementary Code 4

The file is the ReaxFF control file.

Supplementary Code 5

The file is the charge equilibration parameters file.

Supplementary Video 1

Scaled-up production of candle soot (CS)-based nanomaterials. Four candles (each with a diameter of 2.5 cm) were ignited simultaneously for scaled-up production. A stainless steel collector (50 cm × 50 cm) was used for collection. A quantity of 4.56 g CS NPs per hour was achieved. In principle, the production of CS-based nanomaterials can be readily scaled up. This file is provided separately.

Supplementary Video 2

Collection of CS-based nanomaterials using a rotating collector. The collector was driven by a motor, and the rotating speed could be adjusted. This file is provided separately.

Supplementary Video 3

CS production using solid (powder) fuel. By burning target (metal) precursors with solid fuels, such as coal dust and graphite powder, using a solid burner, the production of CS-based nanomaterials (including HMNs) can be further increased. This file is provided separately.

Supplementary Video 4

Soot clustering simulations at 700 K in the absence of metals. Coronene molecules (200) were used as the PAH intermediates for soot formation. The simulation was carried out in a constant NST (number, size and temperature) ensemble using LAMMPS. Coalescence-induced clustering occurred relatively faster than that at 1,000 K (Supplementary Video 5). This file is provided separately.

Supplementary Video 5

Soot clustering simulations at 1,000 K in the absence of metals. This file is provided separately.

Supplementary Video 6

MD simulations in the presence of 28.2 wt% Co. In this experiment, 200 coronene molecules (plate-like objects) were simulated together with 400 Co atoms (red spheres; that is, low metal concentration). Metal aggregation was observed, suggesting the possible formation of Co NPs in the CS matrix. This file is provided separately.

Supplementary Video 7

MD simulations in the presence of 2.4 wt% Co. In this experiment, 200 coronene molecules (plate-like objects) were simulated together with 25 Co atoms (red spheres; that is, low metal concentration). No apparent metal aggregation was observed at the end of the simulation studies, suggesting the possible formation of Co SAs within the CS matrix. This file is provided separately.

Supplementary Video 8

Water droplets sticking on the CS-based coating (N doping). The coating was prepared by burning candles mixed with a N source (as detailed in the Materials and Methods section). The volume of each water droplet was about 10 μL. The tilt angle of the surface was ~15°. After releasing, water droplets rebounded at the surface and sat on the surface owing to the high hysteresis (that is, high interactions between the coating and water droplet). This file is provided separately.

Supplementary Video 9

Water droplets rolling off the CS-based coating (F doping). The coating was prepared by burning candles mixed with an F source (as detailed in the Materials and Methods section). The volume of each water droplet was about 10 μL. The tilt angle of the surface was ~15°. After releasing, water droplets rebounded freely at the surface and rolled off the surface owing to the low hysteresis (that is, low interactions between the coating and water droplet). This file is provided separately.

Source data

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Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

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Liu, Z., Goudeli, E., Guo, R. et al. Flame synthesis achieves compositionally tailorable high-entropy metal-containing nanomaterials. Nat. Chem. 17, 1497–1504 (2025). https://doi.org/10.1038/s41557-025-01894-w

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