Molecular dynamics and kinetic Monte Carlo hybrid approach for efficient dynamics and proton conduction in phosphoric acid

Proton conducting media are important materials to facilitate further the progress of efficient energy conversion systems, such as proton-exchange membrane (PEM) fuel cells. Nafion, a sulfonic acid based proton conductor, is one of the most promising and commonly used H+-conductors due to its high chemical stability and high proton conductivity. However, because of the hydration requirement, the operating temperature of the Nafion membranes is limited to the range from 0 to 100 °C. The operating temperature above this range is one of the ways to enhance the proton conductivity and cell performance. Therefore, H+-conductors with working temperature above 100 °C are urgently required to substitute water in the Nafion membranes. Phosphoric acid (boiling temperature is 213 °C) is one of the candidates that can serve that purpose, because it conducts protons even when it is anhydrous [1]. To systematically design the phosphoric acid based H+-conductors, one has, firstly, to accurately describe the proton conductivity in phosphoric acid. Molecular dynamics (MD) based on density functional theory (DFT) calculations is the most reliable method that can describe the protondynamics based on the accurate DFT estimation of the energy barriers for the H+-hopping. However, this DFT-MD approach is very time consuming. The kinetic Monte Carlo (kMC) is one of the methods that can provide accelerated dynamics of the system, if the energy barriers for the H+-hopping are estimated beforehand, for example, using the DFT method. However, the drawback of the kMC approach is ability to treat only solid phases [2], not liquid. Another possible method, to have accelerated system dynamics, is the classical MD. But, with the conventional MD models it is difficult to accurately describe potential profiles for the H+-migration between molecules and ions. Therefore, to overcome the limitations of the MD and kMC methods, we combine classical MD and kMC methods to develop a hybrid MD-kMC model that can describe the proton conductivity in phosphoric acid. Parameters of the interatomic interaction were adopted from Yan et al. [3]. The energy barriers for the H+-hopping were initially estimated by DFT calculations and then were slightly adjusted to get better agreement with experimental values of the self-diffusion coefficients of 1H (DH) and 31P (DP) at 100 °C [4]. Please click Additional Files below to see the full abstract

Many-body calculations for periodic materials via quantum machine learning

A state-of-the-art method that combines a quantum computational algorithm and machine learning, so-called quantum machine learning, can be a powerful approach for solving quantum many-body problems. However, the research scope in the field was mainly limited to organic molecules and simple lattice models. Here, we propose a workflow of quantum machine learning applications for periodic systems on the basis of an effective model construction from first principles. The band structures of the Hubbard model of graphene with the mean-field approximation are calculated as a benchmark, and the calculated eigenvalues show good agreement with the exact diagonalization results within a few meV by employing the transfer learning technique in quantum machine learning. The results show that the present computational scheme has the potential to solve many-body problems quickly and correctly for periodic systems using a quantum computer.Comment: 20 pages, 4 figure

Evolutionally search with density functional calculations for a new class of one-dimensional electride

An electride, a unique material in which electrons serve as anions, has begun to attract attention for its high performances in electronic and catalytic applications. However, the chemically active property of electrides make the synthesis very difficult, and thus finding stable electrides is a big challenge. Based on a dimensional analysis on the stability of electrides [1], we focused on phosphide-based compounds, and we adopted a state-of-the-art theoretical evolutionally search combined with density functional calculations for a new class of electrides; Strontium phosphide in which anionic electrons are ordered in a one-dimensional network (Fig.1) was found [2]. The presence of the one-dimensional electride was proved by the successful synthesis and X-ray diffraction pattern of the compound. However, an interesting discrepancy appears in its electronic property: metal from density functional theory, but insulator from experiment [2]. We analyzed the discrepancy in terms of the inherent instability of one-dimensional metal especially in half-filled systems, and found a gap-opening by introducing electron correlations, which implies the possibility of the one-dimensional electride as a Mott-insulator. Recently, ytterbium antimonide which takes the same crystal structure of the strontium phosphide is found as a Mott-insulating electride [3]. Although a standard density functional calculation is not preferred for correlated systems, the “structure prediction” by evolutionally search combined with density functional probably work well also for such a system because of the energy scale differences between structural changes and electron correlations. Please click Additional Files below to see the full abstract

Resource estimations for the Hamiltonian simulation in correlated electron materials

Correlated electron materials, such as superconductors and magnetic materials, are regarded as fascinating targets in quantum computing. However, the quantitative resources, specifically the number of quantum gates and qubits, required to perform a quantum algorithm to simulate correlated electron materials remain unclear. In this study, we estimate the resources required for the Hamiltonian simulation algorithm for correlated electron materials, specifically for organic superconductors, iron-based superconductors, binary transition metal oxides, and perovskite oxides, using the fermionic swap network. The effective Hamiltonian derived using the $ab~initio$ downfolding method is adopted for the Hamiltonian simulation, and a procedure for the resource estimation by using the fermionic swap network for the effective Hamiltonians including the exchange interactions is proposed. For example, in the system for the $10^2$ unit cells, the estimated number of gates per Trotter step and qubits are approximately $10^7$ and $10^3$, respectively, on average for the correlated electron materials. Furthermore, our results show that the number of interaction terms in the effective Hamiltonian, especially for the Coulomb interaction terms, is dominant in the gate resources when the number of unit cells constituting the whole system is up to $10^2$, whereas the number of fermionic swap operations is dominant when the number of unit cells is more than $10^3$.Comment: 10 pages, 4 figures, 3 table

Electronic correlation strength of inorganic electrides from first principles

Strongly correlated electron systems, generally recognized as d- and f-electron systems, have attracted attention as a platform for the emergence of exotic properties such as high-Tc superconductivity. However, correlated electron behaviors have been recently observed in a group of novel materials, electrides, in which s-electrons are confined in subnanometer-sized spaces. Here, we present a trend of electronic correlation of electrides by evaluating the electronic correlation strength obtained from model parameters characterizing effective Hamiltonians of 19 electrides from first principles. The calculated strengths vary in the order 0D ≫ 1D > 2D ∼ 3D electrides, which corresponds to experimental trends, and exceed 10 (a measure for the emergence of exotic properties) in all of the 0D and some of the 1D electrides. We also found the electronic correlation depends on the cation species surrounding the s-electrons. The results indicate that low-dimensional electrides will be new research targets for studies of strongly correlated electron systems

Fundamental physics activities with pulsed neutron at J-PARC(BL05)

"Neutron Optics and Physics (NOP/ BL05)" at MLF in J-PARC is a beamline for studies of fundamental physics. The beamline is divided into three branches so that different experiments can be performed in parallel. These beam branches are being used to develop a variety of new projects. We are developing an experimental project to measure the neutron lifetime with total uncertainty of 1 s (0.1%). The neutron lifetime is an important parameter in elementary particle and astrophysics. Thus far, the neutron lifetime has been measured by several groups; however, different values are obtained from different measurement methods. This experiment is using a method with different sources of systematic uncertainty than measurements conducted to date. We are also developing a source of pulsed ultra-cold neutrons (UCNs) produced from a Doppler shifter are available at the unpolarized beam branch. We are developing a time focusing device for UCNs, a so called "rebuncher", which can increase UCN density from a pulsed UCN source. At the low divergence beam branch, an experiment to search an unknown intermediate force with nanometer range is performed by measuring the angular dependence of neutron scattering by noble gases. Finally the beamline is also used for the research and development of optical elements and detectors. For example, a position sensitive neutron detector that uses emulsion to achieve sub-micrometer resolution is currently under development. We have succeeded in detecting cold and ultra-cold neutrons using the emulsion detector.Comment: 9 pages, 5 figures, Proceedings of International Conference on Neutron Optics (NOP2017