arXiv subjects

Tengfei Yang

Publications and source records attributed to Tengfei Yang.

3 recordsLinked to original sources

arXiv2026

Thermodynamics of stacking faults and phase stability in cobalt alloys: A combined computational and experimental study

Stacking fault energy dictates phase stability and deformation behavior in Co alloys and WC-Co cemented carbides, yet a quantitative assessment of alloying effects at finite temperatures remains poorly established. By integrating first-principles thermodynamics with microstructural characterization, we provide a rigorous evaluation of these influences across atomic and macroscopic scales. We show that stacking fault energetics at 0K for transition metal solutes are primarily governed by atomic misfit volume. While 4d and 5d elements follow a consistent linear trend, specific 3d solutes exhibit significant deviations due to non-negligible magnetic contributions. By incorporating phonon, electronic, longitudinal spin-fluctuation, and magnetic free-energy contributions, the model accurately captures the fcc-hcp transformation and quantifies how diverse solutes modulate the phase landscape. We demonstrate that V, Ni, Fe, Mo, and W lower the transformation temperature by stabilizing fcc phase, while Cr and C exhibit the opposite effect, consistent with experimental phase diagrams. Furthermore, microscopic analysis confirms that higher W content dissolved in the Co suppresses stacking-fault formation by elevating the stacking fault energy at finite temperatures. This work clarifies the physical mechanisms by which alloying regulates stacking fault energy and phase stability in Co-based systems, providing guidance for the design of Co-based alloys and WC-Co cemented carbides.

cond-mat.mtrl-sci↗

arXiv2026

Atomic-Scale Insights into Solute Drag Effects on Grain Boundary Motion in Mg-Al and Mg-Ca Alloys

The slip behavior of dislocations and grain boundaries critically governs recrystallization and plastic deformation in Mg alloys and can be strongly influenced by solutes. However, the quantitative effects of solute distribution on defect mobility remain unclear. Using molecular dynamics and Monte Carlo simulations, we systematically investigate how Al and Ca solutes affect the motion of dislocations, low-angle grain boundaries (LAGBs), and high-angle grain boundaries (HAGBs) in Mg. Within the idealized framework of random solid-solution, solute drag is dominated by elastic interactions arising from atomic size mismatch, resulting in a stronger resistance from Ca than from Al. In contrast, under the more realistic condition where solute segregation occurs, the dominant mechanism shifts to chemically driven pinning, whose effectiveness is governed by the attainable segregation density. Owing to strong Ca-Ca repulsion, Al achieves substantially higher segregation concentrations than Ca and therefore exerts much stronger pinning effects. Notably, solute-induced retardation is significantly more pronounced for HAGBs than for LAGBs, leading to amplified solute effects during the late stages of recrystallization, where grain growth is controlled primarily by HAGB migration. These results provide atomic-scale insight into experimentally observed grain refinement in Mg alloys.

cond-mat.mtrl-sci↗

arXiv2025

SEvoBench : A C++ Framework For Evolutionary Single-Objective Optimization Benchmarking

We present SEvoBench, a modern C++ framework for evolutionary computation (EC), specifically designed to systematically benchmark evolutionary single-objective optimization algorithms. The framework features modular implementations of Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms, organized around three core components: (1) algorithm construction with reusable modules, (2) efficient benchmark problem suites, and (3) parallel experimental analysis. Experimental evaluations demonstrate the framework's superior performance in benchmark testing and algorithm comparison. Case studies further validate its capabilities in algorithm hybridization and parameter analysis. Compared to existing frameworks, SEvoBench demonstrates three key advantages: (i) highly efficient and reusable modular implementations of PSO and DE algorithms, (ii) accelerated benchmarking through parallel execution, and (iii) enhanced computational efficiency via SIMD (Single Instruction Multiple Data) vectorization for large-scale problems.

cs.NE↗