Structure and Dynamics in Liquid Iron at High Pressure and Temperature. A First Principles Study

González, L.; González, D. J.

doi:10.1029/2022jb025119

Cited by 3 publications

(4 citation statements)

References 81 publications

(202 reference statements)

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“…According to Figure b, the Fe 3 d states constitute two gentle and broad peaks with maximum values above ∼ – 4 eV, tapering off in lower energies. This DOS pattern agrees well with earlier liquid iron simulations using different supercell sizes . Remarkably, this electronic behavior is in stark contrast to the Fe DOS in solid, which forms a very sharp peak closer to the Fermi level at ∼ – 0.5 eV .…”

Section: Resultsmentioning

confidence: 93%

“…This DOS pattern agrees well with earlier liquid iron simulations using different supercell sizes. 41 Remarkably, this electronic behavior is in stark contrast to the Fe DOS in solid, which forms a very sharp peak closer to the Fermi level at ∼ − 0.5 eV. 42 C 2p states peak at an even lower energy of ∼ − 6 eV in an outspread peak, contracting the DOS distribution in solid C where at the same energy, the DOS peak is considerably steeper and more pointed.…”

Section: ■ Settings and Modelsmentioning

confidence: 99%

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Transforming Cl-Containing Waste Plastics into Carbon Resource for Steelmaking: Theoretical Insight

Assadi,

Doustkhah

2023

ACS Eng. Au

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The accumulation of waste plastics poses a significant environmental challenge, leading to persistent pollution in terrestrial and aquatic ecosystems. A practical approach to address this issue involves the transformation of postconsumer waste plastics into industrially valuable products. This study focuses on an example of harnessing the carbon content in these polymers for carbon-demanding industrial processes, thereby reducing waste plastics from the environment and alleviating the demand for mined carbon resources. Employing quantum simulations, we examine the viability of polychloroprene as a carburizing agent in the steelmaking process. Our simulations reveal that polychloroprene exhibits excellent carbon diffusivity in molten iron, with a theoretical diffusion coefficient of 8.983 × 10–5cm2 s–1. This value competes favorably with that of metallurgical coke and surpasses the carbon diffusivity of other polymers, such as polycarbonate, polyurethane, and polysulfide. Additionally, our findings demonstrate that the chlorine content in polychloroprene does not permeate into molten iron but instead remains confined to the molten iron and slag interface.

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Section: Resultsmentioning

confidence: 93%

Section: ■ Settings and Modelsmentioning

confidence: 99%

Transforming Cl-Containing Waste Plastics into Carbon Resource for Steelmaking: Theoretical Insight

Assadi,

Doustkhah

2023

ACS Eng. Au

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“…To further elucidate the suitability of our GAP to model the behavior of iron under extreme conditions, we computed the (RDFs) of liquid iron at various (p, T ) and compared them to reference data from ab initio MD (AIMD) calculations [56], shown in Fig. 10.…”

Section: Phase Diagrammentioning

confidence: 99%

“…10. Liquid iron RDFs at high (p, T ) along the AIMD melting line [56] (dashed lines). Data computed using our GAP overlaid (solid lines).…”

Section: Nanoparticlesmentioning

confidence: 99%

Searching for iron nanoparticles with a general-purpose Gaussian approximation potential

Jana

Miguel

2023

Phys. Rev. B

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We present a general-purpose machine learning Gaussian approximation potential (GAP) for iron that is applicable to all bulk crystal structures found experimentally under diverse thermodynamic conditions, as well as surfaces and nanoparticles (NPs). By studying its phase diagram, we show that our GAP remains stable at extreme conditions, including those found in the Earth's core. The new GAP is particularly accurate for the description of NPs. We use it to identify new low-energy NPs, whose stability is verified by performing density functional theory calculations on the GAP structures. Many of these NPs are lower in energy than those previously available in the literature up to N atoms = 100. We further extend the convex hull of available stable structures to N atoms = 200. For these NPs, we study characteristic surface atomic motifs using data clustering and low-dimensional embedding techniques. With a few exceptions, e.g., at magic numbers N atoms = 59, 65, 76, and 78, we find that iron tends to form irregularly shaped NPs without a dominant surface character or characteristic atomic motif, and no reminiscence of crystalline features. We hypothesize that the observed disorder stems from an intricate balance and competition between the stable bulk motif formation, with bcc structure, and the stable surface motif formation, with fcc structure. We expect these results to improve our understanding of the fundamental properties and structure of low-dimensional forms of iron and to facilitate future work in the field of iron-based catalysis.

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Large scale and quantum accurate molecular dynamics simulation: Liquid iron under extreme condition

Zeng,

Chen,

Kang

et al. 2023

Acta Phys. Sin.

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Liquid iron is the major component of planetary cores. Its structure and dynamics under high pressure and temperature is of great significance in studying geophysics and planetary science. However, for experimental techniques, it is still difficult to generate and probe such a state of matter under extreme conditions, while for theoretical method like molecular dynamics simulation, the reliable estimation of dynamic properties requires both large simulation size and <i>ab initio</i> accuracy, resulting in unaffordable computational costs for traditional method. Owing to the technical limitation, the understanding of such matters remains limited. In this work, combining molecular dynamics simulation, we establish a neural network potential energy surface model to study the static and dynamic properties of liquid iron at its extreme thermodynamic state close to core-mantle boundary. The implementation of deep neural network extends the simulation scales from one hundred atoms to millions of atoms within quantum accuracy. The estimated static and dynamic structure factor show good consistency with all available X-ray diffraction and inelastic X-ray scattering experimental observations, while the empirical potential based on embedding-atom-method fails to give a unified description of liquid iron across a wide range of thermodynamic conditions. We also demonstrate that the transport property like diffusion coefficient exhibits a strong size effect, which requires more than at least ten thousands of atoms to give a converged value. Our results show that the combination of deep learning technology and molecular modelling provides a way to describe matter realistically under extreme conditions.

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Structure and Dynamics in Liquid Iron at High Pressure and Temperature. A First Principles Study

Cited by 3 publications

References 81 publications

Transforming Cl-Containing Waste Plastics into Carbon Resource for Steelmaking: Theoretical Insight

Transforming Cl-Containing Waste Plastics into Carbon Resource for Steelmaking: Theoretical Insight

Searching for iron nanoparticles with a general-purpose Gaussian approximation potential

Large scale and quantum accurate molecular dynamics simulation: Liquid iron under extreme condition

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