Explore the vast range of titles available.

Employing high-rate ion-intercalation electrodes represents a feasible way to mitigate the inherent trade-off between energy density and power density for electrochemical energy storage devices, but efficient approaches to boost the charge-storage kinetics of electrodes are still needed. Here, we demonstrate a water-incorporation strategy to expand the interlayer gap of α-MoO 3 , in which water molecules take the place of lattice oxygen of α-MoO 3 . Accordingly, the modified α-MoO 3 electrode exhibits theoretical-value-close specific capacity (963 C g −1 at 0.1 mV s −1 ), greatly improved rate capability (from 4.4% to 40.2% at 100 mV s −1 ) and boosted cycling stability (from 21 to 71% over 600 cycles). A fast-kinetics dual-ion-intercalation energy storage device is further assembled by combining the modified α-MoO 3 anode with an anion-intercalation graphite cathode, operating well over a wide discharge rate range. Our study sheds light on a promising design strategy of layered materials for high-kinetics charge storage. The power/energy trade-off is a common feature seen in a Ragone plot for an electrochemical storage device. Here the authors approach this issue by showing water-incorporated α-MoO 3 anodes with expanded interlayer gaps, which allow for the assembling of dual-ion energy storage devices.

There has been a long debate on the stable phase of iron under the Earth’s inner core conditions. Because of the solid‐liquid coexistence at the inner core boundary, the thermodynamic stability of solid phases directly relates to their melting temperatures, which remains considerable uncertainty. In the present study, we utilized a semi‐empirical potential fitted to high‐temperature ab initio data to perform a thermodynamic integration from classical systems described by this potential to ab initio systems. This method provides a smooth path for thermodynamic integration and significantly reduces the uncertainty caused by the finite‐size effect. Our results suggest the hcp phase is the stable phase of pure iron under the inner core conditions, while the free energy difference between the hcp and bcc phases is tiny, on the order of 10 s meV/atom near the melting temperature. Plain Language Summary The structure of Earth’s solid inner core is a fundamental question in understanding the Earth’s interior. Fe is the major element in the Earth’s solid inner core, while its stable phase under inner core conditions is still under debate. The inaccuracy of present ab initio free energy calculations was too large to estimate the small free energy difference between different Fe phases, making this debate unsolved. In this paper, we developed a method to determine Fe’s melting temperatures from ab initio calculations. This was achieved by utilizing a potential fitted to high‐temperature ab initio data and performing a thermodynamic integration from classical systems described by this potential to ab initio systems. This method significantly reduces the uncertainty caused by the finite size effect in the ab initio calculations. Using this method, we calculated the free energy difference and melting temperatures of hcp and bcc Fe under inner‐core boundary and center conditions. We show that the hcp phase is the stable phase of pure Fe throughout the inner core condition. However, the bcc and hcp phases show a very small free energy difference that may be altered by other elements in the inner core. Key Points Thermodynamic integration with a potential fitted to high‐temperature ab initio data allows precise melting temperature determinations Hcp and bcc Fe’s melting temperatures are computed at the same ab initio accuracy at 323 and 360 GPa Bcc Fe is metastable while its free energy is only ∼10 meV/atom higher than the stable hcp phase under inner core conditions

We develop a new implementation of the Gutzwiller approximation in combination with the local density approximation, which enables us to study complex 4f and 5f systems beyond the reach of previous approaches. We calculate from first principles the zero-temperature phase diagram and electronic structure of Pr and Pu, finding good agreement with the experiments. Our study of Pr indicates that its pressure-induced volume-collapse transition would not occur without change of lattice structure—contrarily to Ce. Our study of Pu shows that the most important effect originating the differentiation between the equilibrium densities of its allotropes is the competition between the Peierls effect and the Madelung interaction and not the dependence of the electron correlations on the lattice structure.

Magnetic materials are essential for energy generation and information devices, and they play an important role in advanced technologies and green energy economies. Currently, the most widely used magnets contain rare earth (RE) elements. An outstanding challenge of notable scientific interest is the discovery and synthesis of novel magnetic materials without RE elements that meet the performance and cost goals for advanced electromagnetic devices. Here, we report our discovery and synthesis of an RE-free magnetic compound, Fe₃CoB₂, through an efficient feedback framework by integrating machine learning (ML), an adaptive genetic algorithm, first-principles calculations, and experimental synthesis. Magnetic measurements show that Fe₃CoB₂ exhibits a high magnetic anisotropy (K₁ = 1.2 MJ/m³) and saturation magnetic polarization (J s = 1.39 T), which is suitable for RE-free permanent-magnet applications. Our ML-guided approach presents a promising paradigm for efficient materials design and discovery and can also be applied to the search for other functional materials.

Advanced materials characterization techniques with ever-growing data acquisition speed and storage capabilities represent a challenge in modern materials science and new procedures to quickly assess and analyze the data are needed. Machine learning approaches are effective in reducing the complexity of data and rapidly homing in on the underlying trend in multi-dimensional data. Here, we show that by employing an algorithm called the mean shift theory to a large amount of diffraction data in high-throughput experimentation, one can streamline the process of delineating the structural evolution across compositional variations mapped on combinatorial libraries with minimal computational cost. Data collected at a synchrotron beamline are analyzed on the fly and by integrating experimental data with the inorganic crystal structure database (ICSD), we can substantially enhance the accuracy in classifying the structural phases across ternary phase spaces. We have used this approach to identify a novel magnetic phase with enhanced magnetic anisotropy which is a candidate for rare-earth free permanent magnet.

The physical and chemical properties of V-M″ and Nb-M″ (M″ is 3d or 4d transition metal) co-doped BaTiO3 were studied by first-principles calculation based on density functional theory. Our calculation results show that V-M″ co-doping is more favorable than Nb-M″ co-doping in terms of narrowing the bandgap and increasing the visible-light absorption. In pure BaTiO3, the bandgap depends on the energy levels of the Ti 3d and O 2p states. The appropriate co-doping can effectively manipulate the bandgap by introducing new energy levels interacting with those of the pure BaTiO3. The optimal co-doping effect comes from the V-Cr co-doping system, which not only has smaller impurity formation energy, but also significantly reduces the bandgap. Detailed analysis of the density of states, band structure, and charge-density distribution in the doping systems demonstrates the synergistic effect induced by the V and Cr co-doping. The results can provide not only useful insights into the understanding of the bandgap engineering by element doping, but also beneficial guidance to the experimental study of BaTiO3 for visible-light photoelectrical applications.

Fe, Mg, and O are among the most abundant elements in terrestrial planets. While the behavior of the Fe–O, Mg–O, and Fe–Mg binary systems under pressure have been investigated, there are still very few studies of the Fe–Mg–O ternary system at relevant Earth’s core and super-Earth’s mantle pressures. Here, we use the adaptive genetic algorithm (AGA) to study ternary Fe x Mg y O z phases in a wide range of stoichiometries at 200 GPa and 350 GPa. We discovered three dynamically stable phases with stoichiometries FeMg 2 O 4 , Fe 2 MgO 4, and FeMg 3 O 4 with lower enthalpy than any known combination of Fe–Mg–O high-pressure compounds at 350 GPa. With the discovery of these phases, we construct the Fe–Mg–O ternary convex hull. We further clarify the composition- and pressure-dependence of structural motifs with the analysis of the AGA-found stable and metastable structures. Analysis of binary and ternary stable phases suggest that O, Mg, or both could stabilize a BCC iron alloy at inner core pressures.

We analyze the underlying structural order that transcends liquid, glass and crystalline states in metallic systems. A genetic algorithm is applied to search for the most common energetically favorable packing motifs in crystalline structures. These motifs are in turn compared to the observed packing motifs in the actual liquid or glass structures using a cluster-alignment method. Using this method, we have revealed the nature of the short-range order in Cu 64 Zr 36 glasses. More importantly, we identified a novel structural order in the Al 90 Sm 10 system. In addition, our approach brings new insight into understanding the origin of vitrification and describing mesoscopic order-disorder transitions in condensed matter systems.

The structures and electronic properties of partial C, Si and Ge decorated graphene were investigated by first-principles calculations. The calculations show that the interaction between graphene and the decoration patches is weak and the semiconductor patches act as agents for weak electron doping without much disturbing graphene electronic π-bands. Redistribution of electrons due to the partial decoration causes the electrostatic potential lower in the decorated graphene areas, thus induced an electric field across the boundary between the decorated and non-decorated domains. Such an alternating electric field can change normal stochastic adatom diffusion to biased diffusion, leading to selective mass transport.

Using a motif-network search scheme, we studied the tetrahedral structures of the dilithium/disodium transition metal orthosilicates A 2 MSiO 4 with A = Li or Na and M = Mn, Fe or Co. In addition to finding all previously reported structures, we discovered many other different tetrahedral-network-based crystal structures which are highly degenerate in energy. These structures can be classified into structures with 1D, 2D and 3D M-Si-O frameworks. A clear trend of the structural preference in different systems was revealed and possible indicators that affect the structure stabilities were introduced. For the case of Na systems which have been much less investigated in the literature relative to the Li systems, we predicted their ground state structures and found evidence for the existence of new structural motifs.