Chloride electrode composed of ubiquitous elements for high-energy-density all-solid-state sodium-ion batteries.

Inexpensive and safe energy-storage batteries with high energy densities are in high demand (e.g., for electric vehicles and grid-level renewable energy storage). This study focused on using NaFeCl4, comprising ubiquitous elements, as an electrode material for all-solid-state sodium-ion batteries. Monoclinic NaFeCl4, expected to be the most resource-attractive Fe redox material, is also thermodynamically stable. The Fe2+/3+ redox reaction of the monoclinic NaFeCl4 electrode has a higher potential (3.45 V vs. Na/Na+) than conventional oxide electrodes (e.g., Fe2O3 with 1.5 V vs. Na/Na+) because of the noble properties of chlorine. Additionally, NaFeCl4 exhibits unusually high deformability (99% of the relative density of the pellet) upon uniaxial pressing (382 MPa) at 298 K. NaFeCl4 operates at 333 K in an electrode system containing no electrolyte, thereby realizing next-generation all-solid-state batteries with high safety. A high energy density per positive electrode of 281 Wh kg-1 was achieved using only a simple powder press.

Drawing a materials map with an autoencoder for lithium ionic conductors.

Efforts to optimize known materials and enhance their performance are ongoing, driven by the advancements resulting from the discovery of novel functional materials. Traditionally, the search for and optimization of functional materials has relied on the experience and intuition of specialized researchers. However, materials informatics (MI), which integrates materials data and machine learning, has frequently been used to realize systematic and efficient materials exploration without depending on manual tasks. Nonetheless, the discovery of new materials using MI remains challenging. In this study, we propose a method for the discovery of materials outside the scope of existing databases by combining MI with the experience and intuition of researchers. Specifically, we designed a two-dimensional map that plots known materials data based on their composition and structure, facilitating researchers' intuitive search for new materials. The materials map was implemented using an autoencoder-based neural network. We focused on the conductivity of 708 lithium oxide materials and considered the correlation with migration energy (ME), an index of lithium-ion conductivity. The distribution of existing data reflected in the materials map can contribute to the development of new lithium-ion conductive materials by enhancing the experience and intuition of material researchers.

Increasing the Sodium Metal Electrode Compatibility with the Na3 PS4 Solid-State Electrolyte through Heteroatom Substitution.

Rechargeable batteries are essential to the global shift towards renewable energy sources and their storage. At present, improvements in their safety and sustainability are of great importance as part of global sustainable development goals. A major contender in this shift are rechargeable solid-state sodium batteries, as a low-cost, safe, and sustainable alternative to conventional lithium-ion batteries. Recently, solid-state electrolytes with a high ionic conductivity and low flammability have been developed. However, these still face challenges with the highly reactive sodium metal electrode. The study of these electrolyte-electrode interfaces is challenging from a computational and experimental point of view, but recent advances in molecular dynamics neural-network potentials are finally enabling access to these environments compared to more computationally expensive conventional ab-initio techniques. In this study, heteroatom-substituted Na3 PS3 X1 analogues, where X is sulfur, oxygen, selenium, tellurium, nitrogen, chlorine, and fluorine, are investigated using total-trajectory analysis and neural-network molecular dynamics. It was found that inductive electron-withdrawing and electron-donating effects, alongside differences in heteroatom atomic radius, electronegativity, and valency, influenced the electrolyte reactivity. The Na3 PS3 O1 oxygen analogue was found to have superior chemical stability against the sodium metal electrode, paving the way towards high-performance, long lifetime and reliable rechargeable solid-state sodium batteries.

Bayesian optimisation with transfer learning for NASICON-type solid electrolytes for all-solid-state Li-metal batteries.

NASICON-type LiZr2(PO4)3 (LZP) has attracted significant attention as a solid oxide electrolyte for all-solid-state Li-ion or Li-metal batteries owing to its high Li-ion conductivity, usability in all-solid-state batteries, and electrochemical stability against Li metal. In this study, we aim to improve the Li-ion conductivity of Li-rich NASICON-type LZPs doped with CaO and SiO2, i.e., Li1+x+2y Ca y Zr2-y Si x P3-x O12(0 ≤ x ≤ 0.3, 0 ≤ y ≤ 0.3) (LCZSP). Herein, a total of 49 compositions were synthesised, and their crystal structures, relative densities, and Li-ion conductivities were characterised experimentally. We confirmed the improvement in Li-ion conductivity by simultaneous replacement of Zr and P sites with Ca and Si ions, respectively. However, the intuition-derived determination of the composition exhibiting the highest Li-ion conductivity is technically difficult because the compositional dependence of the relative density and the crystalline phase of the sample is very complex. Bayesian optimisation (BO) was performed to efficiently discover the optimal composition that exhibited the highest Li-ion conductivity among the samples evaluated experimentally. We also optimised the composition of the LCZSP using multi-task Gaussian process regression after transferring prior knowledge of 47 compositions of Li1+x+2y Y x Ca y Zr2-x-y P3O12 (0 ≤ x ≤ 0.376, 0 ≤ y ≤ 0.376) (LYCZP), i.e., BO with transfer learning. The present study successfully demonstrated that BO with transfer learning can search for optimal compositions two times as rapid as the conventional BO approach. This approach can be widely applicable for the optimisation of various functional materials as well as ionic conductors.

Computational studies on defect chemistry and Li-ion conductivity of spinel-type LiAl5O8 as coating material for Li-metal electrode.

Li-metal rechargeable batteries are an attractive option for devices that require an extremely high specific energy density, high robustness, and long-term durability, such as high-altitude platform stations. However, Li dendrite growth during charge-discharge cycling causes short-circuit problems. One technical solution is to form an intermediate layer between the Li metal and electrolyte. This interfacial layer should possess mechanical strength, electrochemical stability in the presence of Li, and Li-ion conductivity. In this study, the Li-ion conductivity of spinel-type LiAl5O8 was investigated using first-principles density functional theory and force field molecular dynamics calculations. The calculation results confirmed that stoichiometric LiAl5O8 compounds do not exhibit Li-ion conductivity, whereas off-stoichiometric compounds with excess Li show long-range Li-ion diffusion. The evaluated activation energy was 0.28 eV, which is as low as that of well-known fast Li-ion conductors, such as garnet-type Li7La3Zr2O12. However, the extrapolated Li-ion conductivity at 298 K was relatively low (~ 10-6 S/cm) owing to the limited formation of migration pathways.

Na superionic conductor-type LiZr2(PO4)3 as a promising solid electrolyte for use in all-solid-state Li metal batteries.

All-solid-state Li-ion batteries are of considerable interest as safer alternatives to Li-ion batteries containing flammable organic electrolytes. To date, however, achieving sufficient charging and discharging rates, in addition to capacity, at room temperature using these all-solid-state batteries has been challenging. To overcome these issues, material simulations and informatics investigations of a relatively new Na superionic conductor (NASICON)-type LiZr2(PO4)3 (LZP) electrolyte were conducted to elucidate its characteristics and material functions. The following thermodynamic and/or kinetic properties of NASICON-type Li-ion conductive oxides were investigated with respect to the crystal structure mainly using material simulation and informatics approaches: (1) the electrochemical stabilities of LZP materials with respect to Li metal and (2) Li-ion conductivities in the bulk and at the grain boundaries. An efficient materials informatics search method was employed to optimise the material functions of the LZP electrolyte via Bayesian optimisation. This study should promote the application of LZP in all-solid-state batteries for use in technologies such as mobile devices and electric vehicles and enable more complex composition and process control.

Novel Mg-ion conductive oxide of µ-cordierite Mg0.6Al1.2Si1.8O6.

Solid electrolytes with high Mg-ion conductivity are required to develop solid-state Mg-ion batteries. The migration energies of the Mg2+ ions of 5,576 Mg compounds tabulated from the inorganic crystal structure database (ICSD) were evaluated via high-throughput calculations. Among the computational results, we focused on the Mg2+ ion diffusion in Mg0.6Al1.2 Si1.8O6, as this material showed a relatively low migration energy for Mg2+ and was composed solely of ubiquitous elements. Furthermore, first-principles molecular dynamics calculations confirmed a single-phase Mg2+ ion conductor. The bulk material with a single Mg0.6Al1.2Si1.8O6 phase was successfully prepared using the sol-gel method. The relative density of the sample was 81%. AC impedance measurements indicated an electrical conductivity of 1.6 × 10-6 Scm-1 at 500°C. The activation energy was 1.32 eV, which is comparable to that of monoclinic-type Mg0.5Zr2(PO4)3.

First-Principles Density Functional Theory Calculations for Formic Acid Adsorption onto Hydro-Garnet Compounds.

Efficient and large-scale removal of humic acid (HA) from aqueous environments is required since HA causes human health and esthetic issues. Hydro-garnet compounds, Ca3Al2(SiO4)3-x (OH)4x , have recently been suggested as HA adsorbents not only due to their superior adsorption behaviors but also because they are ubiquitous element-derived compounds. In this study, the adsorption behavior of formic acid to hydro-garnets was investigated by means of first-principles density functional theory (DFT) computations. Formic acid was chosen owing to its reasonable computational cost and inclusion of carboxylic acid as HA. Comparisons of adsorption energies for formic acid among various compounds (including platinum and kaolinite) indicate that hydro-garnet compounds are promising due to their lower (more stable) adsorption energies. Also, the optimization of composition x enables selective adsorption of formic acid against solvent water molecules. Relationships between surface electronic/atomistic structures and adsorption properties are discussed.

Asymmetry in the Solvation-Desolvation Resistance for Li Metal Batteries.

Li metal electrode is the ultimate choice use in Li ion batteries as high-energy storage systems. An obstacle to its practical realization is Li dendrite formation. In this study, the desolvation resistance of the Li metal electrode, which is strongly related to the inhibition of Li dendrite formation, is investigated. By applying a Laplace transform impedance technique, the desolvation/solvation resistances were successfully separated and analyzed in cells using liquid electrolytes containing different lithium salts, revealing asymmetry in the desolvation/solvation resistances of Li metal electrodes. The desolvation resistances, which supposedly require large amounts of energy derived from the strong interaction between Li+ ion and solvents, were smaller than the solvation resistances. It has also been revealed that the larger resistance in the desolvation process is effective for suppressing Li dendrite formation further.

Computational investigation of the Mg-ion conductivity and phase stability of MgZr4(PO4)6.

Solid electrolyte materials exhibiting high Mg-ion conductivity are required to develop Mg-ion batteries. In this study, we focused on a Mg-ion-conducting solid phosphate based electrolyte, MgZr4(PO4)6 (MZP), and evaluated the ionic conductivity of NASICON-type and ß-iron sulfate-type MgZr4(PO4)6 structures via density functional theory calculations. The calculations suggest that the migration energy of Mg is 0.63 eV for the NASICON-type structure and 0.71 eV for the ß-iron sulfate-type one, and the NASICON-type structure has higher ion conductivity. Although the NASICON-type MZP structure has not been experimentally realised, there is only an energy difference of 14 meV per atom with respect to that of the ß-iron sulfate-type structure. Therefore, in order to develop a synthesis method for the NASICON-type structure, we investigated pressure- and temperature-dependent variations in the free energy of formation using density functional perturbation theory calculations. The results suggest that the formation of the NASICON-type structure is disfavoured under the 0-2000 K and 0-20 GPa conditions.

Nanotube-structured Na2V3O7 as a Cathode Material for Sodium-Ion Batteries with High-rate and Stable Cycle Performances.

Sodium ion batteries meet the demand for large-scale energy storage, such as in electric vehicles, due to the material abundance of sodium. In this report, nanotube-type Na2V3O7 is proposed as a cathode material because of its fast sodium diffusivity, an important requirement for sodium ion batteries, through the investigation of ~4300 candidates via a high-throughput computation. High-rate performance was confirmed, showing ~65% capacity retention at a current density of 10C at room temperature, despite the large particle size of >5 µm. A good cycle performance of ca. 94% in capacity retention after 50 cycles was obtained owing to a small volumetric change of <0.4%.