Calphad-computer Coupling of Phase Diagrams and Thermochemistry最新文献

Phase equilibria of the Y–Co–Zr ternary system at 600 °C and 800 °C were studied for the first time using the diffusion couple technique and equilibrium alloy method with electron probe microanalysis (EPMA), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The results reveal that the stable ternary intermetallic compounds were not found, while YCo₂ and Co₂Zr are formed a continuous solid solution phase (Y, Zr)Co₂ with a Cu₂Mg-type structure. The solid solubility of Zr in α-Y₂Co₁₇, YCo₅, Y₂Co₇, α-YCo₃, YCo and Y₃Co at 800 °C was determined to be 5.6, 2.4, 9.4, 18.0, 1.4 and 1.4 at.%, respectively, while the solid solubility of Y in Co₂₃Zr₆, CoZr and CoZr₃ was measured to be 6.4, 6.3 and 2.6 at.%. Meanwhile, the solid solubility of Zr in α-Y₂Co₁₇, YCo₅, Y₂Co₇, α-YCo₃, YCo, Y₄Co₃, Y₃Co₂, Y₈Co₅ and Y₃Co at 600 °C was measured to be 4.4, 3.0, 9.4, 17.2, 1.6, 1.6, 1.9, 1.9 and 3.2 at.%, respectively, while the solid solubility of Y in Co₂₃Zr₆ and CoZr was measured to be 4.8 and 2.4 at.%. Two isothermal sections of the Y–Co–Zr ternary system at 600 °C and 800 °C were constructed finally. It provides the fundamental information for the development of high-performance Y–Co–Zr-based magnetic alloys.

In this work, a long-established but sparsely documented method of obtaining semi-analytic derivatives of thermodynamic properties with respect to equilibrium conditions is briefly reviewed and rigorously derived. This procedure is then leveraged to construct general forms of derivatives of the residual driving force, a metric for measuring phase stability used in CALPHAD model optimization, with respect to overall system and individual phase compositions. Applied examples – calculating heat capacity in the Al-Fe system, thermodynamic factors in the Nb-V-W system, and residual driving force derivatives in the Ni-Ti system – demonstrate the versatility, accuracy, and extensibility of this method. Using the developed method, residual driving force gradients can be applied directly in CALPHAD model optimizers, as well as in materials design frameworks, to identify regions of phase stability with an efficient, gradient-based approach.

The phase diagram of the CaO–MgO–P₂O₅ system was established by both experimental investigation and thermodynamic assessment. The presence of the contentious binary compound Ca₄P₆O₁₉ in the CaO–P₂O₅ system was confirmed. The phase relationships in the CaO–MgO–P₂O₅ system at temperature 1150 °C and 1200 °C were studied via high-temperature quenching experiments in conjunction with X-ray diffraction (XRD) and electron probe micro-analyzer (EPMA) techniques. The CaO–MgO–P₂O₅ system was critically evaluated and optimized by means of the CALPHAD (CALculation of PHAse Diagrams) methodology. The ionic two-sublattice model (Ca⁺², Mg⁺²)_P (O⁻²,PO₃⁻¹,PO₄⁻³,PO_7/2⁻²,PO_5/2)_Q is used to describe the liquid phase in the CaO–MgO–P₂O₅ system due to the ionic nature of oxide melts and the presence of ions with different charges. A set of self-consistent thermodynamic parameters were obtained, showing good agreement between the experimental data and the calculated results. This study holds significant implications for guiding the manufacturing processes of phosphate ceramics.

A common challenge in accelerated material design is to apply machine learning (ML) methods that can handle data with different structures and dimensions, and also provide physical interpretability. Unfortunately, most existing ML methods are ‘black box’ models incapable of providing physical interpretation or dealing with missing dimensions data that are often encountered in materials science. To overcome this challenge, we propose an interpretable and extensible machine learning framework based on thermodynamically informed graphs and deep data mining from graph neural networks. We demonstrate our framework on the problem of predicting the martensite start (M_s) temperature, which depends on various factors (composition, austenite grain size, and outfield conditions). We construct a thermodynamically informed graph that captures the quantitative relationships between these factors and the M_s temperature using limited and incomplete data. The prediction results indicate that our framework provides clear physical insights because the thermodynamic mechanisms are embedded in the thermodynamic representation graph. Our framework has several advantages: 1) it incorporates thermodynamic mechanisms into the graph structure, 2) it can handle missing dimensions data by filling in the gaps with graph information, and 3) it can be easily extended to new features without requiring much additional data for training. Moreover, we derive a general empirical equation for the M_s temperature prediction from the trained graph neural networks for practical applications.

Precipitation is a natural phenomenon that is known to play an important role in the strengthening of Al–Li alloys. Cluster dynamics is powerful and effective in modeling the precipitation kinetics of precipitates in heat-treatable metallic materials, especially in the early stage. In this work, a cluster dynamics model with cluster mobility is further developed by redefining the effective monomer diffusivity for self-consistently modeling multicomponent and multiphase precipitation. The precipitation kinetic data for Al₃Sc in Al–Sc binary alloys and Al₃Li in Al–Li binary alloys are systematically reviewed and evaluated. The metastable fcc_A1/Al₃Li two-phase equilibria are reoptimized using the split four sublattice compound energy formalism to accommodate both the related phase equilibrium measurements and precipitation kinetic measurements. One set of precipitation kinetic parameters is respectively assessed for each of the two precipitate phases. The improved cluster dynamics model, together with the assessed model parameters, can reasonably reproduce the reliable experimental precipitation kinetic data of the two phases. The model parameter determination includes extensive sensitivity studies to use physically reasonable values, and the present work also studies the use of cluster mobility in modeling the early stage precipitation kinetics. The present work indicates that the obtained model parameters can be used to develop the fundamental informative CALPHAD-type precipitation kinetic database.

THE CALPHAD L 2023 conference was held in Boston, MA, USA from June 25^th to 30^th, 2023. We have 176 attendees from 23 countries. The activities in CALPHAD L 2023 included 84 oral presentations, 138 student posters, and two software workshops. The topics covered during the conference were gathered in nine categories.

In this study computational methods are used to derive thermochemical data for Sc, Fe, Co, Ni, and Hf hydroxides and oxyhydroxides. As done previously, molecular geometries and vibrational modes were derived with DFT methods; for the enthalpies of formation more computationally intensive coupled cluster methods were necessary. For each species Δ_fH^o(298), S^o(298), and C_p in the form A + BT + CT² + D/T + E/T² with A, B, C, D, and E fitted constants are presented. These are combined with previously reported calculations for Al, Cr, Si, Ta, Al, Zr, Y, Yb, Gd, and Mn to build a compound database for metal hydroxides and oxyhydroxides. Sample calculations for applications where high temperature water vapor is encountered are shown. The majority of the database was generated from ab initio calculations; however, experiments were critical benchmarks for many of the species.

The study presents a pressure-dependent CALPHAD-based model for assessment of the Al, Cu and Li unary systems, focusing on phase changes under varying pressures. By incorporating the Murnaghan equation of state and ab initio phonon calculations, the thermal properties for stable and metastable phases are accurately predicted. To ensure a comprehensive representation of the system's response to pressure changes; compressibility, volumetric thermal expansion coefficient as a function of temperature, the derivative of bulk modulus with pressure, and molar volume for the condensed phases are integrated in the framework. The model provides essential insights into pressure-induced transformation, aiding in the understanding of solid-state processing, such as high-pressure torsion and extrusion. The results from this work are in excellent agreement with the experimental literature and can be utilized to enhance phase predictions under non-equilibrium conditions.

The phase equilibria of the Sm-Fe-B ternary system at 873 K and 1073 K were experimentally investigated by equilibrated alloy method using scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS) and X-ray diffraction (XRD). Four ternary intermetallic compounds, Sm₂Fe₁₄B with a Nd₂Fe₁₄B-type structure and space group P4₂/mnm, Sm₁₇(Fe₄B₄)₁₅ with a RE_l.1Fe₄B₄-type structure and space group P4₂/n, SmFeB₄ with a YCrB₄-type structure and space group Pbam and Sm₅Fe₂B₆ with a Pr₅Co₂B₆-type structure and space group $R\bar{3}m$ , were confirmed by the SEM-EDS results and the XRD Rietveld refinements. The isothermal sections of this ternary system at 873 K and 1073 K were established. Furthermore, in the combination with the previous assessments of the Sm-Fe, Sm-B and Fe-B binary systems and the measured and reported experimental results, thermodynamic calculation of the Sm-Fe-B ternary system was performed using the CALPHAD method. The calculated isothermal sections at 873 K and 1073 K are in good agreement with the determined experimental results. Thermodynamic parameters of the Sm-Fe-B ternary system were obtained finally, which would provide a good basis for the development of a thermodynamic database of RE-Fe-B-based magnetic alloys.