CoCrFeMnNi High-Entropy Alloy

• CoCrFeMnNi high-entropy alloy is a model equiatomic fcc material distinguished by high configurational entropy and stable single-phase structure over broad temperature ranges.
• It exhibits unique atomic disorder and localized chemical ordering, with detailed diffusion and grain boundary analyses underpinning its tunable mechanical performance.
• Advanced computational and machine learning models enable predictive design, optimizing phase behavior, mechanical strength, and electronic properties in engineering applications.

CoCrFeMnNi high-entropy alloy, commonly referred to as the "Cantor alloy," is the archetypal five-component equiatomic face-centered cubic (fcc) high-entropy alloy (HEA). Characterized by exceptional solid-solution stability, compositional and structural disorder, and a suite of advanced mechanical, kinetic, and thermophysical properties, it has become a central model for both fundamental HEA research and engineering applications. The equimolar composition of cobalt, chromium, iron, manganese, and nickel maximizes configurational entropy and enables the stabilization of a single-phase fcc structure over a broad temperature range, distinguishing it from conventional multi-component alloys.

1. Thermodynamic Stabilization and Phase Behavior

The formation and stability of the single-phase fcc structure in CoCrFeMnNi are governed by its configurational entropy, weakly exothermic mixing enthalpy, minimal atomic size mismatch, and strategic electron concentration. The configurational entropy at equiatomic composition ($\Delta S_\text{mix} \approx 1.61\,R$, or $13.38\,\text{J}\,\text{mol}^{-1}\,\text{K}^{-1}$) is among the highest achievable for metallic alloys, providing a substantial entropic driving force for random solid solution formation (Chen et al., 2022, Lopanitsyna et al., 2022).

From high-throughput DFT-based regular-solution models, the mixing enthalpy is weakly negative ($\Delta H_\text{mix} \approx -0.7\,\text{kJ/mol}$), with all binary $\Omega_{ij}$ parameters close to zero or slightly negative (Chen et al., 2022, Lopanitsyna et al., 2022). The atomic size mismatch ($\delta \approx 1.08\%$) and parameter $$\Omega = T_\text{m} \Delta S_\text{mix} / |\Delta H_\text{mix}| \approx 36.5$$ confirm extremely strong stabilization of the random solution at synthesis and annealing temperatures $T > 1000$ K.

The free energy of the fcc solid solution remains lower than competing ordered intermetallics (e.g., $\sigma$-CrCo, B2-CoNi) at $T \gtrsim 0.6\,T_\text{m}$ ($\sim1000$ K). At lower temperature, the entropy contribution diminishes and phase decomposition into ordered phases may occur, though sluggish kinetics often permit the single-phase state to persist to ambient conditions (Chen et al., 2022, Lopanitsyna et al., 2022). This thermodynamic regime is confirmed by machine learning-accelerated atomistic simulations, which reproduce mixing enthalpies, free energies, and subtle short-range order (SRO) phenomena consistent with experimental probes (Lopanitsyna et al., 2022).

2. Atomic Structure and Chemical Ordering

Local structure in CoCrFeMnNi is dominated by uniform atomic-scale coordination and significant atomic displacement disorder. Multi-edge EXAFS and reverse Monte Carlo (RMC) modeling demonstrate that all atomic pairs (Cr–X, Mn–X, Fe–X, Co–X, Ni–X) exhibit nearly identical mean nearest-neighbor distances ($2.54$–$2.55 \,\text{Å}$) (Smekhova et al., 2022). However, Cr stands out with the largest mean-square displacements (MSD $\approx 0.24\,\text{Å}$), and higher mean-square relative displacement (MSRD $0.033$–$0.050\,\text{Å}^2$) compared to other pairs (MSRD $\approx 0.023$–$0.028\,\text{Å}^2$), indicating enhanced static and thermal disorder centered on Cr sites.

Despite overall chemical homogeneity at the atomic scale, short-range ordering is non-negligible. Model calculations and atom-probe/neutron studies report strong local avoidance among Cr–Cr ($\alpha_\text{Cr–Cr}\approx+0.95$ at 300 K, dropping to $+0.45$ by 720 K), mild Ni–Ni clustering, and slight Fe–Mn attraction. Only weak SRO persists at high temperatures, with more pronounced segregation phenomena emerging below $500$ K (Lopanitsyna et al., 2022).

3. Diffusion and Kinetics

Atomic and grain boundary (GB) diffusion in CoCrFeMnNi are central to its phase stability, precipitation, and creep resistance. Contrary to earlier "sluggish diffusion" hypotheses, detailed radiotracer and interdiffusion experiments reveal significant element-wise variations in mobility (Gaertner et al., 2018, Vaidya et al., 2017, Glienke et al., 2020).

At 1373 K, tracer diffusion coefficients display the hierarchy: $$D^*_\text{Mn} \gg D^*_\text{Cr} > D^*_\text{Fe} > D^*_\text{Co}$$, with Mn diffusing up to $6\times$ faster than Co. The behavior includes pronounced up-hill diffusion for Cr and Mn, governed by thermodynamic cross-coupling among chemical-potential gradients in the multi-component system. S-shaped (non-monotonic) concentration dependence of Co mobility is observed, maximized near $x_\text{Co}\approx0.17$–$0.18$ (Gaertner et al., 2018).

GB diffusion measured via radiotracer $^{63}$Ni, $^{57}$Co, $^{51}$Cr, $^{59}$Fe, and $^{54}$Mn probes displays Arrhenius parameters for Ni: $Q=221\pm14$ kJ mol$^{-1}$ and $D_0=0.165$ m$^2$ s$^{-1}$, with a GB width $\delta \approx 0.5$ nm and segregation factor $s\approx1$ as confirmed by atom probe (Vaidya et al., 2017, Glienke et al., 2020). Importantly, GB diffusion rates are not intrinsically reduced by high configurational entropy; in fact, they may match or exceed those of pure Ni at elevated temperatures.

Detailed analysis of GB diffusion profiles using Harrison's kinetic regimes (C-type at $643$–$703$ K, B-type at $973$–$1273$ K) shows two distinct GB populations: a relaxed, random branch and a “fast” branch characterized by local precipitation and increased dislocation density, leading to dramatically increased diffusion along decomposed boundaries at low temperature (Glienke et al., 2020). This supports the view that kinetic heterogeneity and phase segregation at GBs are central for long-term stability.

4. Mechanical Properties and Plastic Deformation

CoCrFeMnNi is notable for its high ductility, work hardening, and exceptional toughness at cryogenic temperatures—a result of its dual-mode plasticity. In situ TEM straining at room and liquid nitrogen temperatures reveals that both perfect dislocation glide (a/2<110> on {111}) and mechanical twinning (via dissociated a/6<112> partials on adjacent {111} planes) occur with substantial frequency (Oliveros et al., 2021).

The alloy’s low stacking fault energy (SFE ≈ $18$–$30\,\text{mJ/m}^2$), coupled with moderate atomic-size and modulus mismatch, enables wide dissociation of perfect dislocations and frequent twin formation. The onset and prevalence of twinning are strongly orientation-dependent and increase at lower temperatures. The critical resolved shear stress (CRSS) rises from $22$ MPa at $300$ K ($\sigma_\text{applied} \approx 55$ MPa) to $53$ MPa at $\sim100$ K ($\sigma_\text{applied} \approx 112$ MPa). The synergy of slip and twinning sustains work hardening and impedes strain localization, underlying the alloy's cryogenic toughness (Oliveros et al., 2021).

Experimentally, yield strength and hardness can be tuned by cold rolling (e.g., 60\% deformation increases yield strength by $~200$ MPa) and controlled annealing/recrystallization. Machine learning-guided optimization reaches room-temperature yield strengths up to $842$–$937$ MPa in Al/Si-modified derivatives (retaining FCC structure and ductility), with the base equiatomic alloy yielding $~280$ MPa after rolling and annealing (Bajpai et al., 23 Sep 2024).

5. Grain Boundary Dynamics and Phase Stability

Grain boundary phase behavior in CoCrFeMnNi critically affects both kinetic and mechanical stability. Below $700$ K, correlative TEM, atom probe, and Kikuchi diffraction analyses demonstrate that a subset of high-angle GBs locally decompose, forming Ni–Mn-rich and Cr-rich precipitates, sometimes of bcc/fcc or L1$_0$ type, accompanied by increased local dislocation density (Glienke et al., 2020). This microstructural evolution manifests as “fast” GB diffusion channels at low temperature, providing a pathway for accelerated local phase separation and precipitation even under moderate service conditions.

At higher temperature ($T>800$ K), these features anneal out, and GB transport reverts to a single, relaxed population. The presence of two GB populations with distinct kinetic properties supports a GB “phase transformation” scenario responsive to local chemistry and strain, which may act as a precursor to bulk phase decomposition and ultimately degrade the entropy-stabilized state under long-term exposure.

Measured GB energies increase strongly with temperature ($$\gamma_\text{gb}(T) = 0.553 + 3.37 \times 10^{-4} T$$ J/m$^2$ for Ni in CoCrFeMnNi), more so than in related quaternary alloys, suggesting that GB transformations are thermodynamically and kinetically favored at elevated temperatures (Vaidya et al., 2017).

6. Electronic and Magnetothermal Properties

In the context of ultrafast excitation (e.g., high-fluence laser irradiation), the electronic ensemble properties of CoCrFeMnNi have been quantitatively characterized by tight-binding molecular dynamics and the Boltzmann transport equation (Medvedev, 29 Jun 2025). The electronic heat capacity $C_\text{e}(T_\text{e})$, thermal conductivity $\kappa_\text{e}(T_\text{e})$, and electron–phonon coupling strength $G(T_\text{e})$ have been tabulated to $T_\text{e}\sim 5\times 10^4$ K, with key values $C_\text{e}=5.2 \times 10^6$ J/m$^3$ K at $2\times 10^4$ K and $\kappa_\text{e}=1.2\times 10^{18}$ W/m$^3$ K at $1.8\times 10^4$ K.

Nonthermal melting is triggered at $T_\text{e}\sim 24,000$ K (absorbed dose $\sim 6$ eV/atom), as electronic excitation shallows the interatomic potential wells, leading to lattice disorder on sub-picosecond timescales even without lattice heating. This must be explicitly considered for reliable modeling of ablation and extreme environments (Medvedev, 29 Jun 2025).

Macroscopically, magnetic measurements at low temperature indicate that structural relaxations of Cr atoms induce nonergodic magnetization states under field-assisted cooling, attributable to frustrated interactions in percolating Cr-centered clusters (Smekhova et al., 2022).

7. Computational Modeling and Machine Learning Potentials

The complexity of multi-element disorder in CoCrFeMnNi necessitates advanced atomistic models. Moment Tensor Potentials (MTPs) trained via active learning deliver near-DFT accuracy for defect energetics, elasticity, plasticity, indentation, and melting, enabling high-fidelity simulations on large scales. The latest MTPs (publicly available for LAMMPS integration) outperform MEAM in defect energies (e.g., vacancy formation: DFT $2.34$ eV, MTP $2.00$ eV, MEAM $3.23$ eV), elastic moduli, and solid–liquid phase behavior (Sahoo et al., 16 Nov 2025).

Alternate approaches, such as the "alchemical compression" neural-network model, allow for efficient representation and accurate prediction of energetics, phase competition, and ordering in HEAs with up to 25 d-block elements (Lopanitsyna et al., 2022).

Data-driven frameworks also now enable semi-automated alloy design, with interpretable machine learning (RELM) elucidating the composition–processing–property landscape, extracting quantitative relationships (e.g., via SHAP values), and predicting experimentally validated high-strength derivatives (Bajpai et al., 23 Sep 2024).

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References

• (Vaidya et al., 2017) Radioactive isotopes reveal a non sluggish kinetics of grain boundary diffusion in high entropy alloys
• (Gaertner et al., 2018) Concentration-dependent atomic mobilities in FCC CoCrFeMnNi high-entropy alloys
• (Glienke et al., 2020) Grain boundary diffusion in CoCrFeMnNi high entropy alloy: kinetic hints towards a phase decomposition
• (Oliveros et al., 2021) Orientation-related twinning and dislocation glide in a Cantor High Entropy Alloy at room and cryogenic temperature studied by in situ TEM straining
• (Smekhova et al., 2022) Inner relaxations in equiatomic single-phase high-entropy cantor alloy
• (Chen et al., 2022) A map of single-phase high-entropy alloys
• (Lopanitsyna et al., 2022) Modeling high-entropy transition-metal alloys with alchemical compression
• (Bajpai et al., 23 Sep 2024) Interpretable Machine Learning for High-Strength High-Entropy Alloy Design
• (Medvedev, 29 Jun 2025) Thermodynamic properties of CrMnFeCoNi high entropy alloy at elevated electronic temperatures
• (Sahoo et al., 16 Nov 2025) An Active Learning Interatomic Potential For Defect-Engineered CoCrFeMnNi High-Entropy Alloy