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Machine-Learning Potentials Predict Orientation- and Mode-Dependent Fracture in Refractory Diborides

Shuyao Lin, Zhuo Chen, Rebecca Janknecht, Zaoli Zhang, Lars Hultman, Paul H. Mayrhofer, Nikola Koutna, Davide G. Sangiovanni

TL;DR

This work addresses the challenge of predicting fracture properties in brittle ceramics by developing machine-learning interatomic potentials (MLIPs) trained on ab initio data for TiB$_2$, ZrB$_2$, and HfB$_2$ (TMB$_2$). Using $K$-controlled molecular statics with atomistic cracked-plate models, the authors map orientation- and mode-dependent fracture pathways across six crack geometries and extrapolate macroscale initiation toughness $K_{Ic}^{ inity}$ and fracture strength $\sigma_{ ext{max}}^{ inity}$, finding intrinsic brittleness with $K_{Ic}^{ inity}$ in the ~1.8–2.9 MPa$\, ext{m}^{1/2}$ range and $\sigma_{ ext{max}}^{ inity}$ around 2.0 GPa. They further explore mixed Mode-I/II loading in TiB$_2$, revealing mode-dependent crack deflection onto pyramidal planes and establishing a practical mixed-mode framework with $K^{ ext{mix}}=\\sqrt{K_I^2+K_{II}^2}$ and related partitioning, supported by nanoindentation experiments showing oblique crack trajectories near 40 degrees. Comparisons with experiments highlight microstructural effects not captured in defect-free atomistic models, motivating future extensions to finite temperature and defect-inclusive microstructures. Overall, the MLIP-based approach provides a predictive, atomistic framework for orientation- and mode-dependent fracture in refractory ceramics with potential for broader applicability.

Abstract

Fracture toughness ($K_\mathrm{Ic}$) and fracture strength ($σ_\mathrm{f}$) are key criteria in the selection and design of reliable ceramics. However, their experimental characterization remains challenging -- especially for ceramic thin films, where size and interfacial effects hinder accurate and reproducible measurements. Here, machine-learning interatomic potentials (MLIPs) trained on \textit{ab initio} datasets of single crystal models deformed up to fracture are used to characterize transgranular cleavage in pre-cracked ceramic diboride TMB$_2$ (TM = Ti, Zr, Hf) lattices through stress intensity factor ($K$)-controlled loading. Mode-I simulations performed across distinct crack geometries show that fracture is primarily driven by straight crack extension along the original plane. The corresponding macroscale fracture-initiation properties ($K_\mathrm{Ic} \approx 1.7$-2.9 MPa$\cdot\sqrt{\text{m}}$, $σ_\mathrm{f} \approx 1.6$-2.4 GPa) are extrapolated using established scaling laws. Considering TiB$_2$ as a representative system, additional simulations explore loading conditions ranging from pure Mode-I (opening) to Mode-II (sliding). TiB$_2$ models containing prismatic cracks exhibit their lowest fracture resistance under mixed-mode conditions, where the crack deflects onto pyramidal planes--as confirmed by nanoindentation tests on TiB$_2$(0001) thin films. This study establishes $K$-controlled, MLIP-based simulations as predictive tools for orientation- and mode-dependent fracture in ceramics. The approach is readily extendable to finite temperatures for evaluating fracture behavior under conditions relevant to refractory applications.

Machine-Learning Potentials Predict Orientation- and Mode-Dependent Fracture in Refractory Diborides

TL;DR

This work addresses the challenge of predicting fracture properties in brittle ceramics by developing machine-learning interatomic potentials (MLIPs) trained on ab initio data for TiB, ZrB, and HfB (TMB). Using -controlled molecular statics with atomistic cracked-plate models, the authors map orientation- and mode-dependent fracture pathways across six crack geometries and extrapolate macroscale initiation toughness and fracture strength , finding intrinsic brittleness with in the ~1.8–2.9 MPa range and around 2.0 GPa. They further explore mixed Mode-I/II loading in TiB, revealing mode-dependent crack deflection onto pyramidal planes and establishing a practical mixed-mode framework with and related partitioning, supported by nanoindentation experiments showing oblique crack trajectories near 40 degrees. Comparisons with experiments highlight microstructural effects not captured in defect-free atomistic models, motivating future extensions to finite temperature and defect-inclusive microstructures. Overall, the MLIP-based approach provides a predictive, atomistic framework for orientation- and mode-dependent fracture in refractory ceramics with potential for broader applicability.

Abstract

Fracture toughness () and fracture strength () are key criteria in the selection and design of reliable ceramics. However, their experimental characterization remains challenging -- especially for ceramic thin films, where size and interfacial effects hinder accurate and reproducible measurements. Here, machine-learning interatomic potentials (MLIPs) trained on \textit{ab initio} datasets of single crystal models deformed up to fracture are used to characterize transgranular cleavage in pre-cracked ceramic diboride TMB (TM = Ti, Zr, Hf) lattices through stress intensity factor ()-controlled loading. Mode-I simulations performed across distinct crack geometries show that fracture is primarily driven by straight crack extension along the original plane. The corresponding macroscale fracture-initiation properties (-2.9 MPa, -2.4 GPa) are extrapolated using established scaling laws. Considering TiB as a representative system, additional simulations explore loading conditions ranging from pure Mode-I (opening) to Mode-II (sliding). TiB models containing prismatic cracks exhibit their lowest fracture resistance under mixed-mode conditions, where the crack deflects onto pyramidal planes--as confirmed by nanoindentation tests on TiB(0001) thin films. This study establishes -controlled, MLIP-based simulations as predictive tools for orientation- and mode-dependent fracture in ceramics. The approach is readily extendable to finite temperatures for evaluating fracture behavior under conditions relevant to refractory applications.

Paper Structure

This paper contains 5 sections, 2 equations, 8 figures, 2 tables.

Figures (8)

  • Figure 1: Uniaxial tensile simulations at 300 K using MLIP-based molecular dynamics (ML-MD). (a) Maximum stress (theoretical tensile strength) sustained by TMB$_{2}$:s, (TM$=$Ti, Zr, Hf) during uniaxial tensile deformation along [0001] (square), $[10\overline{1}0]$ (vertical hexagon), and $[\overline{1}2\overline{1}0]$ (horizontal hexagon) directions. (b) Cleavage fracture after reaching the maximum stress point, with plane identification. The image on the right in (a) shows a diboride hexagonal lattice structure in the $\alpha$-phase, including orthogonal crystal axes. The shadowed boron hexagonal layer is aligned with the basal plane.
  • Figure 2: Cracked-plate lattice geometries of hexagonal $\alpha$-structured diborides considered in this work. (a) (0001) crack surface with $[10\overline{1}0]$ (Nr.1) and $[\overline{1}2\overline{1}0]$ (Nr.2) crack-front directions. (b) $(\overline{1}2\overline{1}0)$ crack surface with $[10\overline{1}0]$ (Nr.3) and [0001] (Nr.4) crack-front directions. (c) $(10\overline{1}0)$ crack surface with [0001] (Nr.5) and $[\overline{1}2\overline{1}0]$ (Nr.6) crack-front directions.
  • Figure 3: Bond breakage and volumetric strain distribution in cracked plate models subjected to Mode-I loading as a function of the stress intensity factor. Atomic configurations just before, shortly after, and well above $K_{Ic}$ for different crack geometries: (a, b) (0001), (c, d) $(\overline{1}2\overline{1}0)$, and (e, f) $(10\overline{1}0)$ planes. The simulation snapshots illustrate volumetric strain distributions in blue/red color scale.
  • Figure 4: Comparison of extrapolated Mode-I fracture toughness $K_{Ic}^{\infty}$ (a) and fracture strength $\sigma_{\text{max}}^{\infty}$ (b) for TiB$_2$ (teal), ZrB$_2$ (orange), and HfB$_2$ (red), across all six crack geometries. The geometry indices $Nr.1$--$Nr.6$ are also colored in teal--orange--red, consistent with Fig. \ref{['Geo']}. Note that all crack geometries are modeled for all three materials. (c) Illustration of the influence of the plate area on the calculated fracture toughness (case of TiB$_2$ with crack geometry $Nr.1$). Note that the fracture mechanism remains qualitatively unchanged with increasing size of the supercell.
  • Figure 5: Fracture mechanisms in Group-IV TMB$_2$ compounds following crack initiation ($K_I \gtrsim K_{Ic}$). Simulation snapshots are shown for one representative example per crack geometry: (a) $(0001)[10\overline{1}0]$ (Nr. 1), (b) $(\overline{1}2\overline{1}0)[10\overline{1}0]$ (Nr. 3), and (c) $(10\overline{1}0)[\overline{1}2\overline{1}0]$ (Nr. 6). Each panel compares TiB$_2$ (*-1), ZrB$_2$ (*-2), and HfB$_2$ (*-3) under pure Mode-I loading (the stress intensities $K_I$ are expressed in MPa$\cdot\sqrt{m}$). Each subpanel illustrates crack extension due to stress intensities well above $K_{Ic}$ ($K_I \gtrsim K_{Ic} + 0.5~\mathrm{MPa}\sqrt{\mathrm{m}}$), whereas the insets show magnifications of atomic configurations immediately after reaching $K_{Ic}$. Cracks are seen to either propagate along the initial plane or deflect depending on material and orientation. TM atoms (Ti, Zr, Hf) are depicted in dark gray; B atoms in light blue. The selected plate models have an area of $L^2 = 30$ nm $\times$ 30 nm = 900 nm$^2$.
  • ...and 3 more figures