This paper introduces a framework based on Large Deviation Theory (LDT) to accurately and efficiently compute the rare probabilities of voltage collapse. We formulate the problem as finding the most probable failure point (the instanton) on the stability boundary and derive both first-order and second-order approximations for the collapse probability. The second-order method incorporates the local curvature of the stability boundary, yielding higher accuracy. This LDT framework generalizes methods based on Mahalanobis distance and is extensible to non-Gaussian uncertainties. We validate our approach on test systems, demonstrating that the LDT estimates converge to Monte Carlo results in the rare-event regime where direct sampling becomes computationally prohibitive.
For Pt-based superalloys with a gamma - gamma' dual-phase microstructure, the lattice misfit between the two phases significantly affects the lattice coherent strain field, thereby dictating their mechanical performance. Here, high-throughput first-principles calculations were used to estimate the lattice misfit at finite temperatures. The calculated lattice misfit for Pt3 Al, Pt3 Sc, Pt3 Ti, Pt3 Zr, and Pt3 Hf at 300 K are -0.985%, 0.525%, -0.316%, 1.405% and 0.903%, respectively. Due to the higher antiphase boundary (APB) energy and shear modulus of both Pt3 Al and Pt3 Hf, the combination of Pt3 Hf with positive lattice misfit and Pt3 Al with negative lattice misfit can optimize the overall lattice misfit in Pt3 (Al1-x Hfx )1 through compositional tuning. The calculated lattice misfit for Pt3 (Al0.625 Hf0.375 )1 is -0.154% at 300 K and approaches zero at elevated temperature. The alloy Pt82 Al11.25 Hf6.75 (at.%) was prepared, and in-situ high-temperature X-ray diffraction measurements reveal lattice misfit of -0.135%, -0.20 0%, -0.062%, -0.089%, and 0.060% at 298 K, 573 K, 873 K, 1173 K, and 1473 K, respectively, which agree well with the calculated values. High-resolution transmission electron microscopy (HR-TEM) confirms that the gamma and gamma' phases form a coherent structure. The near-zero lattice misfit induces a coherent strain field around the gamma' precipitates, effectively im peding dislocation motion. The com pressive strengths of Pt82 Al11.25 Hf6.75 at 1173 K and 1473 K were measured as 666.6 MPa and 186.4 MPa, respectively, exceeding those of previously reported Pt-Al-based superalloys. (c) 2026 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.
Supercritical CO2 (scCO(2)) plays a crucial role as a solvent in separation processes, advanced power cycles, and materials processing. Nonetheless, the atomistic comprehension of how the dense scCO(2) matrix influences the fundamental reaction of carbon monoxide (CO) is still insufficiently explored. Experimental studies and molecular dynamics (MD) simulations frequently fail to detect the highly reactive, transient intermediates, such as atomic oxygen (O), that drive these reactions. To address this issue, we have developed a novel ReaxFF reactive force field for the CO2/CO/O system. The force field parameters were calibrated using density functional theory and second-order M & oslash;ller-Plesset calculations to model CO2 crystal properties, intermolecular interactions, bond dissociation curves, and reaction energy barriers. The force field reproduces the cohesive energy of the CO2 crystal, the pressure characteristics of bulk scCO(2), the equation-of-state behavior over a wide pressure-density range, the pressure dependence of the C-O bond length under compression, and the structural properties of liquid and scCO(2), as documented by experiments, ab-initio MD, and prominent non-reactive models. The force field was subsequently applied to study the CO + O -> CO2 reaction. In a dilute environment, the reaction is inefficient as the newly formed CO2 rapidly dissociates due to excess kinetic and potential energy acquired from the exothermic reaction. Conversely, in a dense scCO(2) environment, the surrounding matrix acts as an efficient third body, stabilizing the emerging CO2 product via molecular collisions. Statistical analysis confirms an average excess energy dissipation of 133.9 +/- 3.6 kcal/mol over 112.4 +/- 17.9 ps. Kinetic energy decomposition reveals that similar to 92% of the excess kinetic energy is stored in internal (rotational and vibrational) degrees of freedom. This ReaxFF force field establishes a mechanistic foundation for third-body stabilization in dense reactive environments.
Pin-fin heat sinks are widely employed in thermal management systems due to their high surface-area-to-volume ratio and enhanced convective heat transfer capabilities. Accurate prediction of their flow-thermal performance, however, remains computationally expensive when relying on high-fidelity numerical simulations, particularly for complex geometries which typically possess high-dimensional design parameters. In this work, the Graph Neural Operator (GNO) framework is sucessfully used to model flow-thermal fields in pin-fin configurations. Computational fluid dynamics simulations are used to generate high-resolution datasets, which are then mapped onto graph representations of the flow domain. GNO models based on graph attention mechanisms are developed and evaluated under two configurations: a baseline model using spatial coordinate inputs and a boundary-aware model augmented with per-node boundary-distance features. The results demonstrate that integrating boundary-aware representations significantly improves predictive accuracy, near-wall resolution, and generalization while maintaining comparable computational cost. A SHapley Additive exPlanations-based sensitivity analysis is also performed to identify the geometric parameters that most strongly influence heat transfer rate and pressure drop. In conclusion, this study highlights the potential of boundary-aware GNO-based surrogate models as efficient and scalable alternatives to traditional numerical solvers for thermal system analysis and design interpretation.
Using a definitive screening design, we identified the main and interaction effects of ingredients reported as aggressive in canned foods (potassium chloride, sodium chloride, acetic acid, citric acid, paprika oleoresin, cysteine, and methionine) on physical proxies for can coating performance. Tinplate coated with either a legacy bisphenol A (BPA)-based epoxy phenolic resin or a novel non-BPA polyester phenolic alternative was exposed to 17 combinations of ingredient levels, retorted at 121 degrees C for 30 min, and aged at 50 degrees C for 7 days. We combined electrochemical impedance spectroscopy, differential scanning calorimetry, X-ray diffractometry, optical profilometry, and X-ray fluorescence spectroscopy to characterize coating and substrate response and found that specific ingredient pairs significantly influenced polymer degradation and tinplate corrosion. These synergistic, antagonistic, and crossover interactions, often overlooked in single-ingredient testing, mean that coatings qualified against individual components may still be vulnerable to specific ingredient combinations. By incorporating multiple components into food simulants and quantifying their interactions, this study provides fundamental knowledge of ingredient-driven degradation mechanisms: a critical step toward more representative testing protocols that better capture the complexity of real food systems and ultimately inform safer coating design and selection.
