arXiv subjects

Douglas E. Wolfe

Publications and source records attributed to Douglas E. Wolfe.

7 recordsLinked to original sources

arXiv2026

The Case Against Hall-Petch Hardening in High Entropy Carbide Ceramics

Grain size is often used with the Hall-Petch relationship to justify differences in hardness in ceramic materials. Herein, hardness does not vary systematically with grain-size for fully dense, single-phase (Cr,Mo,Ta,V,W)C1-δ high entropy carbide ceramics for grain sizes that varied by a factor of three. Fully dense, single-phase ceramics with grain sizes from 9.3+/-0.3 to 28.8+/-0.7 microns exhibited a pronounced indentation size effect, with Vickers hardness decreasing from ~28-30 GPa at 0.49 N to ~20-21 GPa at 9.81 N, and Berkovich nanohardness ranging from 26 to 30 GPa at 10 mN. However, at a given load, hardness remained within a narrow range across the grain-size series, and no consistent Hall-Petch dependence was resolved. The lack of grain-size dependence likely indicates that the deformation volume sampled by the indenter was not controlled by grain-boundary interactions; instead, hardness was governed primarily by indentation load and local response of the rock salt carbide matrix.

cond-mat.mtrl-sci↗

arXiv2026

Grain Growth Kinetics in (Cr,Mo,Ta,V,W)C1-δ High-Entropy Carbide Ceramics

Understanding grain-boundary mobility during spark plasma sintering can enable microstructure control in high-entropy carbides, yet quantitative grain-growth kinetics remain scarce. In this work, grain growth kinetics and densification behavior were investigated for single-phase fully dense (Cr,Mo,Ta,V,W)C1-δ high-entropy carbide ceramics. Specimens were densified by spark plasma sintering for a constant dwell time of 10 min at temperatures between 1750 °C and 1950 °C to isolate the role of temperature on microstructural evolution. Increasing sintering temperature produced grain growth and increased lattice parameter, while maintaining a single-phase rock salt structure. Elemental mapping showed a progressive reduction of Ta segregation with increasing sintering temperature, suggesting enhanced chemical homogenization at elevated temperatures. Grain growth kinetics were analyzed using a normal grain growth model with an assumed growth exponent of n=3, physically reasonable for grain-boundary-controlled growth influenced by solute and vacancy pinning. Arrhenius analysis of the growth factor yielded an apparent activation energy of approximately 620 kJ mol-1, comparable to diffusion-controlled processes in refractory transition-metal carbides. Densification curves revealed rapid consolidation prior to reaching the peak temperature followed by temperature-dominated grain coarsening. These results establish quantitative relationships between densification temperature, grain growth, and diffusion kinetics in a carbide system, providing insight into the microstructural stability of high-entropy, ultra-high-temperature carbide ceramics.

cond-mat.mtrl-sci↗

arXiv2025

A Software Package for Generating Robust and Accurate Potentials using the Moment Tensor Potential Framework

We present the Plan for Robust and Accurate Potentials (PRAPs), a software package for training and using moment tensor potentials (MTPs) in concert with the Machine Learned Interatomic Potentials (MLIP) software package. PRAPs provides an automated workflow to train MTPs using active learning procedures, and a variety of utilities to ease and improve workflows when utilizing the MLIP software. PRAPs was originally developed in the context of crystal structure prediction, in which one calculates convex hulls and predicts low energy metastable and thermodynamically stable structures, but the potentials PRAPs develops are not limited to such applications. PRAPs produces two potentials, one capable of rough estimates of the energies, forces and stresses of almost any chemical structure in the specified compositional space -- the Robust Potential -- and a second potential intended to provide more accurate descriptions of ground state and metastable structures -- the Accurate Potential. We also present a Python library, mliputils, designed to assist users in working with the chemical structural files used by the MLIP package.

physics.chem-ph↗

arXiv2025

Variable-Temperature Plasmonic High-Entropy Carbides

Effective thermal management at variable and extreme temperatures face limitations for the development of novel energy and aerospace applications. Plasmonic approaches, shown to be capable of tailoring black-body emission, could be effective if materials with high-temperature and tunable plasmonic-resonance were available. Here, we report a synergy between experimental and theoretical results proving that many high-entropy transition-metal carbides, consisting of four or more metals at equal molar ratio, have plasmonic resonance at room, high (>1000C) and variable temperatures. We also found that these high-entropy carbides can be tuned and show considerable plasmonic thermal cycling stability. This paradigm-shift approach could prove quite advantageous as it facilitates the accelerated rational discovery and manufacturability of optically highly-optimized high-entropy carbides with ad-hoc properties.

cond-mat.mtrl-sci↗

arXiv2024

Interfacial defect properties of high-entropy carbides: Stacking faults, Shockley partial dislocations, and a new Evans-Polanyi-Semenov relation

Using first principles calculations, {111} intrinsic stacking fault (ISF) energies in Group IVB, VB, and VIB high-entropy transition metal carbides are shown to be predictable from an optimized rule of mixtures based on the properties of the single metal carbide constituents present near the stacking fault. A composition-independent linear relationship is demonstrated between the ISF energies and the unstable stacking fault (USF) energies along the <112>{111} gamma surface slip path. Treating the ISF and USF energies as analogous to the heat of reaction and transition state barrier in chemical reactions, this linear relationship represents a new application of the Evans-Polanyi-Semenov principle. Further, a full defect energy distribution can be obtained from the predicted ISF energies with only the composition as an input for the mixed early-transition metal carbides. Applying a model that balances the elastic repulsion between partial dislocations with the distribution of ISF energies, we show that Shockley partial edge dislocations should remain bound for all valence electron concentration values up to about 9.6, even when the average stacking fault energy is negative.

cond-mat.mtrl-sci↗

arXiv2024

Machine Learned Interatomic Potentials for Ternary Carbides trained on the AFLOW Database

Large density functional theory (DFT) databases are a treasure trove of energies, forces and stresses that can be used to train machine learned interatomic potentials for atomistic modeling. Herein, we employ structural relaxations from the AFLOW database to train moment tensor potentials (MTPs) for four carbide systems: HfTaC, HfZrC, MoWC and TaTiC. The resulting MTPs are used to relax ~6300 random symmetric structures, and are subsequently improved via active learning to generate robust potentials (RP) that can relax a wide variety of structures, and accurate potentials (AP) designed for the relaxation of low-energy systems. This protocol is shown to yield convex hulls that are indistinguishable from those predicted by AFLOW for the HfTaC, HfZrC and TaTiC systems, and in the case of the MoWC system to predict thermodynamically stable structures that are not found within AFLOW, highlighting the potential of the employed protocol within crystal structure prediction. Relaxation of over three hundred Mo$_{1-x}$W$_x$C stoichiometry crystals first with the RP then with the AP yields formation enthalpies that are in excellent agreement with those obtained via DFT.

cond-mat.mtrl-sci↗

arXiv2023

A priori procedure to establish spinodal decomposition in alloys

Spinodal decomposition can improve a number of essential properties in materials, especially hardness. Yet, the theoretical prediction of the onset of this phenomenon (e.g., temperature) and its microstructure (e.g., wavelength) often requires input parameters coming from costly and time-consuming experimental efforts, hindering rational materials optimization. Here, we present a procedure where such parameters are not derived from experiments. First, we calculate the spinodal temperature by modeling nucleation in the solid solution while approaching the spinode boundary. Then, we compute the spinodal wavelength self-consistently using a few reasonable approximations. Our results show remarkable agreement with experiments and, for NiRh, the calculated yield strength due to spinodal microstructures surpasses even those of Ni-based superalloys. We believe that this procedure will accelerate the exploration of the complex materials experiencing spinodal decomposition, critical for their macroscopic properties.

cond-mat.mtrl-sci↗