Atomistic Study of the Role of Defects on α → ϵ Phase Transformations in Iron under Hydrostatic Compression

Strategic sampling with stochastic surface walking for machine learning force fields in iron's bcc-hcp phase transitions

This study developed a machine learning-based force field for simulating the bcc-hcp phase transitions of iron. By employing traditional molecular dynamics sampling methods and stochastic surface walking sampling methods, combined with Bayesian inference, we construct an efficient machine learning potential for iron. By using SOAP descriptors to map structural data, we find that the machine learning force field exhibits good coverage in the phase transition space. Accuracy evaluation shows that the machine learning force field has small errors compared to DFT calculations in terms of energy, force, and stress evaluations, indicating excellent reproducibility. Additionally, the machine learning force field accurately predicts the stable crystal structure parameters, elastic constants, and bulk modulus of bcc and hcp phases of iron, and demonstrates good performance in predicting higher-order derivatives and phase transition processes, as evidenced by comparisons with DFT calculations and existing experimental data. Therefore, our study provides an effective tool for investigating the phase transitions of iron using machine learning methods, offering new insights and approaches for materials science and solid-state physics research.

Cast Iron Parts Obtained in Ceramic Molds Produced by Binder Jetting 3D Printing-Morphological and Mechanical Characterization

Mechanical behavior and characteristics of two different types of materials: cast iron with lamellar graphite EN-GJL-250 and cast iron with spheroidal graphite EN-GJS-400-15 which were cast in ceramic molds using gravitational casting method has considered in this research. The ceramic molds were obtained by 3D printing method. First, a finite element analysis was developed to determine Tresca and von Mises stresses and the deformations of the ceramic molds under an applied pressure of 25 MPa. Samples were produced by gravitational casting using two types of cast iron materials. Mechanical tests were made using samples produced from these two types of materials and microstructure analysis evaluation of fractured zones was realized by scanning electron microscopy. Obtained results were finally used for designing, developing, and producing of one ‘hydraulic block’ of a railway installation by the Benninger Guss company of Switzerland.

Phase Stability of Iron Nitride Fe4N at High Pressure-Pressure-Dependent Evolution of Phase Equilibria in the Fe-N System

Although the general instability of the iron nitride γ'-Fe₄N with respect to other phases at high pressure is well established, the actual type of phase transitions and equilibrium conditions of their occurrence are, as of yet, poorly investigated. In the present study, samples of γ'-Fe₄N and mixtures of α Fe and γ'-Fe₄N powders have been heat-treated at temperatures between 250 and 1000 °C and pressures between 2 and 8 GPa in a multi-anvil press, in order to investigate phase equilibria involving the γ' phase. Samples heat-treated at high-pressure conditions, were quenched, subsequently decompressed, and then analysed ex situ. Microstructure analysis is used to derive implications on the phase transformations during the heat treatments. Further, it is confirmed that the Fe-N phases in the target composition range are quenchable. Thus, phase proportions and chemical composition of the phases, determined from ex situ X-ray diffraction data, allowed conclusions about the phase equilibria at high-pressure conditions. Further, evidence for the low-temperature eutectoid decomposition γ'→α+ε' is presented for the first time. From the observed equilibria, a P-T projection of the univariant equilibria in the Fe-rich portion of the Fe-N system is derived, which features a quadruple point at 5 GPa and 375 °C, above which γ'-Fe₄N is thermodynamically unstable. The experimental work is supplemented by ab initio calculations in order to discuss the relative phase stability and energy landscape in the Fe-N system, from the ground state to conditions accessible in the multi-anvil experiments. It is concluded that γ'-Fe₄N, which is unstable with respect to other phases at 0 K (at any pressure), has to be entropically stabilised in order to occur as stable phase in the system. In view of the frequently reported metastable retention of the γ' phase during room temperature compression experiments, energetic and kinetic aspects of the polymorphic transition γ'⇌ε' are discussed.

Atomistic Simulation of the Strain Driven Phase Transition in Pure Iron Thin Films Containing Twin Boundaries

Using molecular dynamics (MD) simulation, the strain-induced phase transitions in pure body-centered-cubic (bcc) iron (Fe) thin films containing twin boundaries (TBs) with different TB fractions and orientations are studied. Two groups of bcc thin films with different TB-surface orientation relationships are designed. In film group 1, the (112) [ 11 1 ¯ ] TBs are perpendicular to the ( 11 1 ¯ ) free surfaces, while the (112) [ 11 1 ¯ ] TBs are parallel to the free surfaces in film group 2. We vary the TB numbers inserted into the films to study the effect of TB fraction on the phase transition. Biaxial strains are applied to the films to induce the bcc to close packed (cp) phase transition. The critical strain, at which the first phase transition takes place, decreases with the TB fraction increase in film group 1 with a perpendicular TB-surface orientation, while such a relationship is not observed in film group 2 with parallel TB-surface orientation. We focus on the free surface and TB as the nucleation positions of the new phase and the afterward growth. In addition, the dynamics of the phase transition is discussed. This work may help to understand the mechanism of phase transition in nanoscale or surface-dominant systems with pre-existing defects.