Publications

Five recent publications

1. "Temperature dependence of O solubility in liquid Na by atomistic simulation of Na(l)–Na2O(s) interfaces using corrected machine learning potential: a step towards simulating Na combustion"

C. Kim, T. Oda*, Phys. Chem. Chem. Phys. 25,  20933-20946 (2023). [https://doi.org/10.1039/D3CP01348K]

Liquid Na combustion is a significant safety concern in sodium-cooled fast reactors. Atomistic simulations are an alternative to experiments for studying detailed mechanisms of complex combustion processes. However, accurate simulations of the interfaces involved in combustion are challenging even for density functional theory (DFT), because the systematic error between different chemical systems cannot be fully cancelled. Herein, we report the achievement of a key milestone in atomistic simulation of liquid Na combustion, which involves the development of a machine learning (ML) moment tensor potential that allows accurate simulation of interface systems between liquid Na and solid Na2O. The ML potential is trained by using supervised and active learning to ensure DFT-level accuracy. An empirical correction is then applied to achieve experimental accuracy by reducing systematic error. Consequently, the basic properties of liquid Na and solid Na2O are accurately simulated. In addition, with empirical correction, experimental O solubility data for liquid Na at 350–900 K are reproduced by using interface molecular dynamics simulations and a thermodynamic model. The temperature dependence of the enthalpy and entropy of the Na2O solution and their effect on O solubility are evaluated. The results show that, despite the increase in solution enthalpy with temperature, O solubility increases more rapidly than the linear Arrhenius plot due to the effect of solution entropy. The results of this study indicate that, with appropriate correction, ML potentials can achieve near-experimental accuracy, beyond the accuracy of DFT, in interface simulations and material properties calculations, paving the way for sodium combustion simulations in the future.

2. "Steady-state tritium inventory in plasma-facing tungsten for fusion reactors: An effective calculation method and implications of calculation results"

T. Oda*, J. Nucl. Mater. 577, 154294 (2023). [https://doi.org/10.1016/j.jnucmat.2023.154294]

The tritium inventory in plasma-facing components needs to be evaluated with sufficient accuracy since it is relevant to the safety and fuel-cycle sustainability of fusion reactors. Here, we propose an effective method to calculate the steady-state tritium inventory in plasma-facing tungsten. In this method, the surface and diffusion processes of hydrogen isotopes (HI) are first modelled by rate theory to obtain a steady-state concentration profile of HI dissolved in the lattice. Subsequently, trap effects are modelled by equilibrium theory. By decoupling the trapping/detrapping processes from the surface/diffusion processes and focusing only on the steady state, the calculation cost is largely reduced, and atomic resolution is realized in the rate model to describe surface processes in detail. The applicability and performance of the proposed method are demonstrated with a one-dimensional test case simulating the ITER tungsten mono- block. The calculation results show that tritium retention in the deep region becomes the main source of tritium inventory at a steady state due to the large temperature gradient in plasma-facing tungsten. Several implications for DEMO and beyond are obtained regarding tritium inventory and HI effects on mechanical integrity. The proposed method can be complementary to the macroscopic rate model for tritium inventory calculations.

3. "Accurate description of hydrogen diffusivity in bcc metals using machine-learning moment tensor potentials and path-integral methods"

H. Kwon, M. Shiga, H. Kimizuka, T. Oda*, Acta Mater. 247, 118739 (2023). [10.1016/j.actamat.2023.118739]

Hydrogen diffusivity in metals has been extensively investigated owing to its rich physical characteristics and importance in materials engineering. However, there are large deviations in the reported experimental data of diffusion coefficients due to surface and trapping effects, indicating that accurate measurements are inherently difficult, especially at low temperatures. For computational studies, several atomistic simulation methods have been proposed and used to determine the true hydrogen diffusivity in the lattice; however, their accuracy remains questionable as most studies have not accurately simulated the force field, dynamic effects, or nuclear quantum effects. In this study, using three bcc metals (Nb, Fe, and W) as test cases, we estimated the diffusivity of dilute hydrogen from long-time path integral simulations using machine-learning moment tensor potentials with the accuracy of density functional theory, which accurately handles the three factors simultaneously. Calculations based on such accurate modeling revealed that existing measurements are reliable only if the experimental methods and conditions are appropriate for representing bulk hydrogen diffusion. In the temperature range where the experiments seem reliable (<800 K for Nb, >500 K for Fe, and >1500 K for W), our calculations show excellent agreement for all three bcc metals. Isotope effects were also consistent with the experimental data. These results demonstrate that precise measurements over a wide temperature range remain a challenge in experimental studies and that predicted data from accurate computer simulations can compensate for missing experimental data.

4. "Accurate and Efficient Calculation of the Solution Enthalpy and Diffusivity of Solutes in Liquid Metals Using Machine Learning Potential"

J. Gil, T. Oda*, J. Chem. Theory Comput. 18, 5568-5576 (2022). [https://doi.org/10.1021/acs.jctc.2c00270]

Liquid metals (LMs) have various applications in energy systems, such as coolants in advanced nuclear reactors. In addition, room-temperature LMs are attracting attention as flexible components in robotics and electronics and as novel chemical reaction media to form low-dimensional materials. In many of these applications, the capabilities of LMs can be further enhanced if one can better understand and control the chemical reactivity of LMs, which is largely affected by the stability and mobility of solutes in LMs. Here, we propose an automated method using a machine learning moment tensor potential to efficiently calculate the solution enthalpy and diffusivity of solutes in LMs. From several test cases in liquid Na, we demonstrate that the method can achieve an accuracy comparable to that of a direct calculation using first-principles molecular dynamics, while significantly reducing the calculation cost to the order of 1/10 to 1/100. The method is expected to contribute to the advancement of LM chemistry and the development of new LMs.

5. "Correction methods for first-principles calculations of the solution enthalpy of gases and compounds in liquid metals"

J. Gil, T. Oda*, Phys. Chem. Chem. Phys. 24, 757-770 (2022). [https://doi.org/10.1039/D1CP02450G]

Liquid metals (LMs) have a wide range of engineering applications, such as in coolants, batteries, and flexible electronics. While accurate calculation methods for thermodynamic properties based on density functional theory (DFT) have been extensively developed for solid materials, including methods to correct identified systematic errors, almost no attempt has been made for LMs. In the present study, four correction methods for the first-principles calculation of the solution enthalpy of gases and compounds in LMs are proposed, namely, Correction-1, using the experimental binding energy of an impurity gas molecule; Correction-2, additionally using the experimental enthalpy of formation of a solid compound composed of LM and gas-impurity elements; Correction-3, using the concept of the fitted elemental-phase reference energies (FERE) method; and Correction-4, using the concept of the coordination corrected enthalpies (CCE) method. The performance of each method is examined with hydrogen, nitrogen, oxygen, and iodine gases and their sodium compounds in liquid sodium, and the operating principle of each method is clarified. In general, the four correction methods effectively reduce the calculation error, and Correction-2 reduces the error to less than 10 kJ/mol, while the uncorrected errors are up to several tens of kJ/mol. This study demonstrates that, with appropriate correction, the DFT calculation of the solution enthalpy of impurities in LMs can achieve the same level of accuracy as in precise experiments.

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