Faraday Discuss., 2026, 264, 494–509 · The Royal Society of Chemistry
High-Entropy Alloy Nanoparticles: Achievements, Open Questions, and Future Trajectories
1. Context and Motivation
This paper presents the concluding remarks of the 2025 Faraday Discussion on High-Entropy Alloy Nanostructures. It critically reviews the state of the field and identifies the
scientific gaps that must be closed to move from empirical exploration toward rational, theory-guided design of HEA nanoparticles (HEA-NPs).
- HEAs were originally defined as ≥5-principal-element alloys in near-equiatomic ratios, stabilised by high configurational mixing entropy.
- Gibbs thermodynamics requires minimisation of the total free energy (common-tangent construction over all phases), not entropy alone.
- Most reported HEAs are in a kinetic transient; intermetallics and ordered phases form after prolonged annealing.
- At the nanoscale, surface-to-volume effects, fast surface diffusion, and the Gibbs–Thomson relation can outweigh mixing entropy as stability-governing factors.
2. Bulk HEAs vs. HEA Nanoparticles — Key Differences
HEA-NPs are not miniaturised bulk alloys. They constitute a distinct materials class with different governing physics.
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Property
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Bulk HEA
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HEA Nanoparticle
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Dominant stabilisation
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Configurational mixing entropy
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Kinetic barriers; surface/defect thermodynamics
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Phase state
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Mostly single solid-solution phase (metastable)
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Frequently multiphase; decomposition common
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Surface role
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Secondary; bulk properties dominate
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Primary; governs functionality and stability
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Oxidation kinetics
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Parabolic (Wagner theory)
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Logarithmic; chemical complexity suppresses fast diffusion pathways
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Interstitial contamination
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Manageable
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Critical; C, N, O, H, B alter crystallinity and activity
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Design metric
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Configurational entropy
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Functional descriptors (adsorption energy, magnetic moment, etc.)
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3. The Configuration Space Problem
The compositional and structural landscape of multi-element nanoparticles is computationally intractable by conventional methods.
- For N = 100 atoms with 10 data points per coordinate, the number of possible configurations approaches 10800.
- DFT scales as O(N³); a direct thermodynamic simulation of a 250-atom supercell requires ~600,000 DFT energy evaluations.
- Solution: Machine-Learning Interatomic Potentials (MLIPs) that match DFT accuracy at a fraction of the cost.
- GPU-accelerated Monte Carlo and Molecular Dynamics methods allow simulation of systems exceeding 109 atoms.
- Design searches must shift from phase-stability metrics to property-driven functional descriptors: hydrogen binding energy, magnetic moment, surface energy, work function.
4. Decomposition, Short-Range Order, and Interstitial Contamination
Stability under operational conditions is predominantly kinetic, not thermodynamic.
- In situ TEM studies reveal demixing, Kirkendall void formation, and phase separation under electrochemical conditions (e.g., PtPd / FeNiCo patch formation).
- Short-range ordering (SRO) suppresses defect jump frequencies and traps defect motion, providing a kinetic stability lever.
- Noble elements (Pt) segregate to the core; transition metals (Fe, Co, Ni, Cu) diffuse outward, forming disordered oxide layers.
- Interstitial impurities (C, N, O, H, B) — often unquantified — control glass-formation tendency, quench sensitivity, and surface activity. High C content in laser-ablated NPs can drive
amorphisation.
- Defect-phase thermodynamics and generalised adsorption isotherm theory must explicitly account for these interstitials.
5. Dynamic Surfaces and Operando Validation
The active interface of a functioning HEA-NP is chemically and structurally distinct from its bulk interior and from its post-mortem appearance.
- Catalytic systems operate via continuous surface reconstruction ("Ertl cycling"); post-mortem snapshots are often structurally unrepresentative.
- Ag enrichment and Pt depletion have been observed in AuAgCuPdPt nanoalloys — dynamically induced by temperature and reaction atmosphere.
- A key open question: How thick is the active reaction interface? Quantification requires operando X-ray reflectivity or conductivity measurements.
- Required operando toolkit: in situ STEM/TEM holders + simultaneous mass spectrometry + X-ray reflectivity + generalised adsorption isotherm theory for multi-site surfaces.
6. Synthesis Challenges
Synthesis controllability is the bottleneck between theoretical design and experimental realisation.
- Each constituent metal has unique reduction kinetics and threshold energies; unsynchronised co-reduction leads to compositional gradients and phase separation.
- Simple one-pot approaches frequently yield multiphase products; hot-injection synthesis is essential for monodisperse, ≤3 nm single-phase HEA-NPs (e.g., RhIrPtPdRu).
- Ball milling and laser ablation inherently introduce C, N, O contamination; controlled-atmosphere processing is mandatory.
- Continuous-flow reactors and wet-chemistry routes offer better size/shape uniformity while minimising energy consumption.
7. Multifunctionality and Sustainability Vision
The compositional complexity of HEA-NPs should be exploited for integrated, multi-objective property profiles rather than single-metric optimisation.
- Magneto-catalysis: Incorporating Fe, Co, Ni into Pt-group HEA-NPs (e.g., PtPdFeCoNi) enables magnetic separability and spin-polarisation-tuned catalytic selectivity.
- Non-noble electrocatalysts: Differences in electronegativity among constituent elements drive localised electron redistribution at active sites, enhancing HER/OER performance
without expensive precious metals.
- Sustainability: Priority must shift to lean-noble-metal or noble-metal-free HEA-NPs for CO₂ conversion and H₂ storage; initial reliance on Pt-group-rich compositions presents a
critical resource challenge.
- AI/ML multi-objective optimisation is indispensable for identifying compositions that simultaneously satisfy competing requirements (e.g., high activity + long-term stability + low cost).
8. Six Strategic Paradigm Shifts Required
From → To Entropy stabilisation → Kinetics and defect thermodynamics
From → To Bulk HEA analogy → Distinct nanoparticle materials class
From → To DFT-only simulation → MLIPs + GPU-accelerated large-scale MD/MC
From → To Post-mortem characterisation → Genuine operando validation
From → To Single-property optimisation → Multifunctional design
From → To Average composition metrics → Property-driven functional descriptors
"It is time to stop treating high-entropy nanoparticles as merely miniaturised bulk HEAs and start treating them as the fascinating new materials class they really are."
— D. Raabe, Faraday Discuss. 2026, 264, 509
Full reference: D. Raabe, Faraday Discuss., 2026, 264, 494–509. DOI: 10.1039/D5FD00055F. © The Royal Society
of Chemistry 2026.