arXiv subjects

Shuyao Lin

Publications and source records attributed to Shuyao Lin.

6 recordsLinked to original sources

arXiv2026

Anharmonicity Driven by Vacancy Ordering Unlocks High-performance Thermoelectric Conversion in Defective Chalcopyrites II-III$_2$-VI$_4$

Defective chalcopyrites have recently emerged as promising thermoelectric materials because their ordered intrinsic vacancies can profoundly reshape both lattice dynamics and electronic structure. Here, we present a comprehensive theoretical investigation of the lattice thermal and carrier transport properties of II-III$_2$-VI$_4$ defective chalcopyrites by combining first-principles calculations with machine-learning interatomic potentials. We show that vacancy ordering enhances lattice distortion, leading to strong anharmonicity and metavalent bonding. The interplay of soft low-frequency phonons, strongly negative Gr\"uneisen parameters, and a substantially enlarged four-phonon scattering phase space results in four-phonon-scattering-dominated heat transport, yielding ultralow lattice thermal conductivity. Meanwhile, systematic anion substitution at the VI-site provides an effective route to tune the electronic structure: reduced anion electronegativity weakens metal-anion hybridization, shifts anion $p$ states upward, narrows the band gap, and thereby improves electrical transport. Benefiting from this synergy between vacancy-induced phonon suppression and anion-regulated electronic optimization, CdGa$_2$Te$_4$ exhibits an ultralow lattice thermal conductivity of 0.19 W$\cdot$m$^{-1}$K$^{-1}$ and a high room-temperature $ZT$ of 0.957. This work not only predicts defective chalcopyrites as a promising platform for high-performance thermoelectrics but also provides a practical design strategy by integrating vacancy ordering, higher-order phonon scattering, and anion-dependent band engineering.

cond-mat.mtrl-sci↗

arXiv2025

High- and medium-entropy nitride coatings from the Cr-Hf-Mo-Ta-W-N system: properties and high-temperature stability

High- and medium-entropy nitride coatings from the Cr-Hf-Mo-Ta-W-N system were studied using ab initio calculations and experiments to clarify the role of entropy and individual elements in phase stability, microstructure, and high-temperature behaviour. Formation energy calculations indicated that nitrogen vacancies stabilise the cubic (fcc) phase, with hafnium and tantalum acting as strong stabilisers, while tungsten destabilises the lattice. Coatings were deposited by reactive magnetron sputtering at approx. 50C (AT) and approx. 580C (HT). All exhibited columnar fcc structures; high-temperature deposition produced denser coatings, lower nitrogen content, and larger crystallites, resulting in higher hardness and elastic modulus. Thermal stability was tested up to 1200C on Si and oxidation at 1400C on sapphire. AT coatings failed early, while most HT coatings endured. Nitrogen loss less than 10 at.% at 1000C was critical for survival. TEM revealed tungsten segregation and HfO2 formation, while fcc nitride remained dominant. Ta enrichment proved essential for superior thermal and oxidation stability.

cond-mat.mtrl-sci↗

arXiv2025

Diffuson-Dominated Thermal Transport Crossover from Ordered to Liquid-like Cu$_3$BiS$_3$:The Negligible Role of Ion Hopping

Fundamentally understanding lattice dynamics and thermal transport behavior in liquid-like, partially occupied compounds remains a long-standing challenge in condensed matter physics. Here, we investigate the microscopic mechanisms underlying the ultralow thermal conductivity in ordered/liquid-like Cu$_3$BiS$_3$ by combining experimental methods with first-principles calculations. We first experimentally synthesize and characterize the ordered structure and liquid-like, partially Cu-atom occupied Cu$_3$BiS$_3$ structure with increasing temperature. We then combine self-consistent phonon calculations, including bubble-diagram corrections, with the Wigner transport equation, considering both phonon propagation and diffuson contributions, to evaluate the anharmonic lattice dynamics and thermal conductivity in phase-change Cu$_3$BiS$_3$. Our theoretical model predicts an ultralow thermal conductivity of 0.34 W/m/K at 400 K, dominated by diffuson contributions, which accurately reproduces and explains the experimental data. Importantly, the machine-learning-based molecular dynamics (MD) simulations not only reproduced the partially Cu-atom occupied Cu$_3$BiS$_3$ structure with the space group $\mathrm{P2_12_12_1}$ but also successfully replicated the thermal conductivity obtained from experiments and Wigner transport calculations. This observation highlights the negligible impact of ionic mobility arising from partially occupied Cu sites on the thermal conductivity in diffuson-dominated thermal transport compounds. Our work not only sheds light on the minimal impact of ionic mobility on ultralow thermal conductivity in phase-change materials but also demonstrates that the Wigner transport equation accurately describes thermal transport behavior in partially occupied phases with diffuson-dominant thermal transport.

cond-mat.mtrl-sci↗

arXiv2025

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

Fracture toughness ($K_\mathrm{Ic}$) and fracture strength ($\sigma_\mathrm{f}$) 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$\cdot\sqrt{\text{m}}$, $\sigma_\mathrm{f} \approx 1.6$-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.

cond-mat.mtrl-sci↗

arXiv2025

Machine-learning potentials for structurally and chemically complex MAB phases: strain hardening and ripplocation-mediated plasticity

Though offering unprecedented pathways to molecular dynamics (MD) simulations of technologically-relevant materials and conditions, machine-learning interatomic potentials (MLIPs) are typically trained for ``simple'' materials and properties with minor size effects. Our study of MAB phases (MABs) - alternating transition metal boride (MB) and group A element layers - exemplifies that MLIPs for complex materials can be fitted and used in a high-throughput fashion: for predicting structural and mechanical properties across a large chemical/phase/temperature space. Considering group 4-6 transition metal based MABs, with A=Al and the 222, 212, and 314 type phases, three MLIPs are trained and tested, including lattice and elastic constants calculations at temperatures $T\in\{0,300,1200\}$ K, extrapolation grade and energy (force, stress) error analysis for $\approx{3\cdot10^6}$ ab initio MD snapshots. Subsequently, nanoscale tensile tests serve to quantify upper limits of strength and toughness attainable in single-crystal MABs at 300~K as well as their temperature evolution. In-plane tensile deformation is characterised by relatively high strength, {110}$\langle001\rangle$ type slipping, and failure by shear banding. The response to [001] loading is softer, triggers work hardening, and failure by kinking and layer delamination. Furthermore, W$_2$AlB$_2$ able to retard fracture via ripplocations and twinning from 300 up to 1200~K.

cond-mat.mtrl-sci↗

arXiv2023

Machine-learning potentials for nanoscale simulations of deformation and fracture: example of TiB$_2$ ceramic

Machine-learning interatomic potentials (MLIPs) offer a powerful avenue for simulations beyond length and timescales of ab initio methods. Their development for investigation of mechanical properties and fracture, however, is far from trivial since extended defects -- governing plasticity and crack nucleation in most materials -- are too large to be included in the training set. Using TiB$_2$ as a model ceramic material, we propose a strategy for fitting MLIPs suitable to simulate mechanical response of monocrystals until fracture. Our MLIP accurately reproduces ab initio stresses and failure mechanisms during room-temperature uniaxial tensile deformation of TiB$_2$ at the atomic scale ($\approx{10}^3$ atoms). More realistic tensile tests (low strain rate, Poisson's contraction) at the nanoscale ($\approx{10}^4$--10$^6$ atoms) require MLIP up-fitting, i.e. learning from additional ab initio configurations. Consequently, we elucidate trends in theoretical strength, toughness, and crack initiation patterns under different loading directions. To identify useful environments for further up-fitting, i.e., making the MLIP applicable to a wider spectrum of simulations, we asses transferability to other deformation conditions and phases not explicitly trained on.

cond-mat.mtrl-sci↗