Metal-to-Insulating Transition in the Perovskite System YSr2Cu2FeO8-δ (0 < δ < 1) Modeled by DFT Methods.

Progress in the design of functional perovskite oxides relies on advances in density functional theory (DFT) methods to efficiently and effectively model complex systems composed of several transition-metal ions. This work reports the application of DFT methods to investigate the electronic structure of the YSr2Cu2FeO8-δ (0 < δ < 1) family in which the insulating, metal, or superconducting behaviors and even anion conductivity can be tuned by modifying the oxygen content. In particular, we assess the performance of the generalized gradient approximation (GGA), its Hubbard-U correction (GGA + U), and the strongly constrained and appropriately normed (SCAN) to model the metallic (idealized YSr2Cu2FeO8) and insulating (idealized YSr2Cu2FeO7) phases of the system. The analysis of the DFT results is supported by DC resistivity measurements that denote the metal character of the synthesized YSr2Cu2FeO7.86 and the semiconducting character of YSr2Cu2FeO7.08 prepared under reducing conditions. In addition, the band gap of YSr2Cu2FeO7.08, in the range of 0.73-1.2 eV, has been extracted from diffuse reflectance spectroscopy (DRS). While the three methodologies (GGA, GGA + U, SCAN) permit the reproduction of the crystal structures of the synthetized oxides (determined here in the case of YSr2Cu2FeO7.08 by neutron powder diffraction (NPD)), the SCAN emerges as the only one capable to predict the basic electronic and magnetic properties across the YSr2Cu2FeO8-δ (0 < δ < 1) series. The picture that emerges for the metal (δ = 0) to insulating (δ = 1) transition is the one in which oxygen vacancies contribute electrons to the filling of the Cu/Fe-3dx2-y2 states of the conduction band. These results validate the SCAN functional for future DFT investigations of complex functional oxides that combine several transition metals.

ß-V2O5 as Magnesium Intercalation Cathode.

Magnesium batteries have attracted great attention as an alternative to Li-ion batteries but still suffer from limited choice of positive electrode materials. V2O5 exhibits high theoretical capacities, but previous studies have been mostly limited to α-V2O5. Herein, we report on the ß-V2O5 polymorph as a Mg intercalation electrode. The structural changes associated with the Mg2+ (de-) intercalation were analyzed by a combination of several characterization techniques: in situ high resolution X-ray diffraction, scanning transmission electron microscopy, electron energy-loss spectroscopy, and X-ray absorption spectroscopy. The reversible capacity reached 361 mAh g-1, the highest value found at room temperature for V2O5 polymorphs.

Appraisal of calcium ferrites as cathodes for calcium rechargeable batteries: DFT, synthesis, characterization and electrochemistry of Ca4Fe9O17.

Sustainability combined with high energy density prospects makes Fe-based oxides attractive as cathodes for calcium rechargeable batteries. This work presents a DFT evaluation of the CaFe2+nO4+n (0 < n < 3) family, for which both the average intercalation voltage and the theoretical specific capacity decrease with the increasing n value. The term n = 1/4, Ca4Fe9O17, meets the most appealing characteristics: a calculated average voltage of 4.16 V, a theoretical specific capacity of 230 mA h g-1 and the lowest energy barrier for Ca migration so far predicted for an existing oxide (0.72 eV). To overcome the previously reported synthesis difficulties, we employed a novel synthesis procedure in sealed quartz tubes followed by quenching in water. The XRD and SAED patterns of the prepared Ca4Fe9O17 powder reveal a certain degree of stacking defects along the c axis. Attempts to deinsert Ca ions from Ca4Fe9O17 by chemical means (NO2BF4 in ACN) and in electrochemical Ca cells were unsuccessful, although some hints of oxidation are observed in Li cells with the LP30 electrolyte. The suitability of Ca4Fe9O17 as a Ca cathode is pending further studies utilizing Ca-electrolytes with high anodic stability.

Achievements, Challenges, and Prospects of Calcium Batteries.

This Review flows from past attempts to develop a (rechargeable) battery technology based on Ca via crucial breakthroughs to arrive at a comprehensive discussion of the current challenges at hand. The realization of a rechargeable Ca battery technology primarily requires identification and development of suitable electrodes and electrolytes, which is why we here cover the progress starting from the fundamental electrode/electrolyte requirements, concepts, materials, and compositions employed and finally a critical analysis of the state-of-the-art, allowing us to conclude with the particular roadblocks still existing. As for crucial breakthroughs, reversible plating and stripping of calcium at the metal-anode interface was achieved only recently and for very specific electrolyte formulations. Therefore, while much of the current research aims at finding suitable cathodes to achieve proof-of-concept for a full Ca battery, the spectrum of electrolytes researched is also expanded. Compatibility of cell components is essential, and to ensure this, proper characterization is needed, which requires design of a multitude of reliable experimental setups and sometimes methodology development beyond that of other next generation battery technologies. Finally, we conclude with recommendations for future strategies to make best use of the current advances in materials science combined with computational design, electrochemistry, and battery engineering, all to propel the Ca battery technology to reality and ultimately reach its full potential for energy storage.

Recent advances in first principles computational research of cathode materials for lithium-ion batteries.

To meet the increasing demands of energy storage, particularly for transportation applications such as plug-in hybrid electric vehicles, researchers will need to develop improved lithium-ion battery electrode materials that exhibit high energy density, high power, better safety, and longer cycle life. The acceleration of materials discovery, synthesis, and optimization will benefit from the combination of both experimental and computational methods. First principles (ab Initio) computational methods have been widely used in materials science and can play an important role in accelerating the development and optimization of new energy storage materials. These methods can prescreen previously unknown compounds and can explain complex phenomena observed with these compounds. Intercalation compounds, where Li(+) ions insert into the host structure without causing significant rearrangement of the original structure, have served as the workhorse for lithium ion rechargeable battery electrodes. Intercalation compounds will also facilitate the development of new battery chemistries such as sodium-ion batteries. During the electrochemical discharge reaction process, the intercalating species travel from the negative to the positive electrode, driving the transition metal ion in the positive electrode to a lower oxidation state, which delivers useful current. Many materials properties change as a function of the intercalating species concentrations (at different state of charge). Therefore, researchers will need to understand and control these dynamic changes to optimize the electrochemical performance of the cell. In this Account, we focus on first-principles computational investigations toward understanding, controlling, and improving the intrinsic properties of five well known high energy density Li intercalation electrode materials: layered oxides (LiMO2), spinel oxides (LiM2O4), olivine phosphates (LiMPO4), silicates-Li2MSiO4, and the tavorite-LiM(XO4)F (M = 3d transition metal elements). For these five classes of materials, we describe the crystal structures, the redox potentials, the ion mobilities, the possible phase transformation mechanisms, and structural stability changes, and the relevance of these properties to the development of high-energy, high-power, low-cost electrochemical systems. These results demonstrate the importance of computational tools in real-world materials development, to optimize or minimize experimental synthesis and testing, and to predict a material's performance under diverse conditions.