Shyue Ping Ong

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

Accelerating the discovery of advanced materials is essential for human welfare and sustainable, clean energy. In this paper, we introduce the Materials Project (www.materialsproject.org), a core program of the Materials Genome Initiative that uses high-throughput computing to uncover the properties of all known inorganic materials. This open dataset can be accessed through multiple channels for both interactive exploration and data mining. The Materials Project also seeks to create open-source platforms for developing robust, sophisticated materials analyses. Future efforts will enable users to perform ‘‘rapid-prototyping’’ of new materials in silico, and provide researchers with new avenues for cost-effective, data-driven materials design.

Voltage, Stability and Diffusion Barrier Differences between Sodium-ion and Lithium-ion Intercalation Materials

To evaluate the potential of Na-ion batteries, we contrast in this work the difference between Na-ion and Li-ion based intercalation chemistries in terms of three key battery properties—voltage, phase stability and diffusion barriers. The compounds investigated comprise the layered AMO2 and AMS2 structures, the olivine and maricite AMPO4 structures, and the NASICON A3V2(PO4)3 structures. The calculated Na voltages for the compounds investigated are 0.18–0.57 V lower than that of the corresponding Li voltages, in agreement with previous experimental data. We believe the observed lower voltages for Na compounds are predominantly a cathodic effect related to the much smaller energy gain from inserting Na into the host structure compared to inserting Li. We also found a relatively strong dependence of battery properties on structural features. In general, the difference between the Na and Li voltage of the same structure, DVNa–Li, is less negative for the maricite structures preferred by Na, and more negative for the olivine structures preferred by Li. The layered compounds have the most negative DVNa–Li. In terms of phase stability, we found that open structures, such as the layered and NASICON structures, that are better able to accommodate the larger Na+ ion generally have both Na and Li versions of the same compound. For the close-packed AMPO4 structures, our results show that Na generally prefers the maricite structure, while Li prefers the olivine structure, in agreement with previous experimental work. We also found surprising evidence that the barriers for Na+ migration can potentially be lower than that for Li+ migration in the layered structures. Overall, our findings indicate that Na-ion systems can be competitive with Li-ion systems.

Design principles for solid-state lithium superionic conductors

Lithium solid electrolytes can potentially address two key limitations of the organic electrolytes used in todays lithium-ion batteries, namely, their flammability and limited electrochemical stability. However, achieving a Li(+) conductivity in the solid state comparable to existing liquid electrolytes (>1 mS cm(-1)) is particularly challenging. In this work, we reveal a fundamental relationship between anion packing and ionic transport in fast Li-conducting materials and expose the desirable structural attributes of good Li-ion conductors. We find that an underlying body-centred cubic-like anion framework, which allows direct Li hops between adjacent tetrahedral sites, is most desirable for achieving high ionic conductivity, and that indeed this anion arrangement is present in several known fast Li-conducting materials and other fast ion conductors. These findings provide important insight towards the understanding of ionic transport in Li-ion conductors and serve as design principles for future discovery and design of improved electrolytes for Li-ion batteries.

Phase stability, electrochemical stability and ionic conductivity of the Li10±1MP2X12 (M = Ge, Si, Sn, Al or P, and X = O, S or Se) family of superionic conductors

We present an investigation of the phase stability, electrochemical stability and Li+ conductivity of the Li10±1MP2X12 (M = Ge, Si, Sn, Al or P, and X = O, S or Se) family of superionic conductors using first principles calculations. The Li10GeP2S12 (LGPS) superionic conductor has the highest Li+ conductivity reported to date, with excellent electrochemical performance demonstrated in a Li-ion rechargeable battery. Our results show that isovalent cation substitutions of Ge4+ have a small effect on the relevant intrinsic properties, with Li10SiP2S12 and Li10SnP2S12 having similar phase stability, electrochemical stability and Li+ conductivity as LGPS. Aliovalent cation substitutions (M = Al or P) with compensating changes in the Li+ concentration also have a small effect on the Li+ conductivity in this structure. Anion substitutions, however, have a much larger effect on these properties. The oxygen-substituted Li10MP2O12 compounds are predicted not to be stable (with equilibrium decomposition energies >90 meV per atom) and have much lower Li+ conductivities than their sulfide counterparts. The selenium-substituted Li10MP2Se12 compounds, on the other hand, show a marginal improvement in conductivity, but at the expense of reduced electrochemical stability. We also studied the effect of lattice parameter changes on the Li+ conductivity and found the same asymmetry in behavior between increases and decreases in the lattice parameters, i.e., decreases in the lattice parameters lower the Li+ conductivity significantly, while increases in the lattice parameters increase the Li+ conductivity only marginally. Based on these results, we conclude that the size of the S2− is near optimal for Li+ conduction in this structural framework.

Direct visualization of the Jahn–Teller effect coupled to Na ordering in Na5/8MnO2

The cooperative Jahn-Teller effect (CJTE) refers to the correlation of distortions arising from individual Jahn-Teller centres in complex compounds. The effect usually induces strong coupling between the static or dynamic charge, orbital and magnetic ordering, which has been related to many important phenomena such as colossal magnetoresistance and superconductivity. Here we report a Na5/8MnO2 superstructure with a pronounced static CJTE that is coupled to an unusual Na vacancy ordering. We visualize this coupled distortion and Na ordering down to the atomic scale. The Mn planes are periodically distorted by a charge modulation on the Mn stripes, which in turn drives an unusually large displacement of some Na ions through long-ranged Na-O-Mn(3+)-O-Na interactions into a highly distorted octahedral site. At lower temperatures, magnetic order appears, in which Mn atomic stripes with different magnetic couplings are interwoven with each other. Our work demonstrates the strong interaction between alkali ordering, displacement, and electronic and magnetic structure, and underlines the important role that structural details play in determining electronic behaviour.

A comparison of destabilization mechanisms of the layered NaxMO2 and LixMO2 compounds upon alkali de-intercalation

To understand the difference in reversible energy storage capacity between the O3-type layered Na and Li compounds, we use first principles calculations to study and contrast the effect of two well-known destabilization mechanisms, transformation into the spinel-type structures and cation mixing due to transition metal migration. This study is performed on the layered oxides at the A(0.5)MO(2) composition, where A = (Na, Li) and M is a 3d transition metal. We find that while all Li(0.5)MO(2) compounds have strong driving forces and low energy kinetic paths to transform to the spinel structure, Na(0.5)MO(2) compounds do not have thermodynamic driving forces to transform to spinel type structures. We also find that transition metal mobility is higher in Li layered compounds than in Na layered compounds because of the unusual activated state for transition metal hopping. For many compounds, migration goes along an oct-tet-oct path, but transition metal migration needs to be assisted by alkali migration into a tetrahedral site forming activated A(tet)-M(tet) defects; substituting Na for Li in the layered structure results in increased transition metal migration barriers due to the larger size of Na(+) ions. Overall, our findings indicate that Na compounds in the layered O3 structure have fundamentally different destabilization mechanisms to those of Li compounds. This distinction allows superior battery electrode performance in many Na compounds and offers optimistic perspective on finding many high energy density Na electrodes that cycle with stable high capacity.

Novel mixed polyanions lithium-ion battery cathode materials predicted by high-throughput ab initio computations

The discovery of new chemistries outperforming current lithium intercalation cathodes is of major technological importance. In this context, polyanionic systems with the potential to exchange multiple electrons per transition metal are particularly interesting because they could combine the safety of polyanion systems with higher specific energy. In this paper, we report on a series of new mixed polyanions compounds of formula AxM(YO3)(XO4) (with A = Na, Li; X = Si, As, P; Y = C, B; M = a redox active metal; and x = 0 to 3) identified by high-throughput ab initio computing. The computed stability of both lithium and sodium-based compounds is analyzed along with the voltage, specific energy and energy density of the lithium-based compounds. This analysis suggests several novel carbonophosphates and carbonosilicates as potential high capacity (>200 mAh/g) and specific energy (>700 Wh/kg) cathode materials for lithium-ion batteries.

Accelerating Electrolyte Discovery for Energy Storage with High-Throughput Screening

Computational screening techniques have been found to be an effective alternative to the trial and error of experimentation for discovery of new materials. With increased interest in development of advanced electrical energy storage systems, it is essential to find new electrolytes that function effectively. This Perspective reviews various methods for screening electrolytes and then describes a hierarchical computational scheme to screen multiple properties of advanced electrical energy storage electrolytes using high-throughput quantum chemical calculations. The approach effectively down-selects a large pool of candidates based on successive property evaluation. As an example, results of screening are presented for redox potentials, solvation energies, and structural changes of ∼1400 organic molecules for nonaqueous redox flow batteries. Importantly, on the basis of high-throughput screening, in silico design of suitable candidate molecules for synthesis and electrochemical testing can be achieved. We anticipate that the computational approach described in this Perspective coupled with experimentation will have a significant role to play in the discovery of materials for future energy needs.

Nanoscale Stabilization of Sodium Oxides: Implications for Na–O2 Batteries

The thermodynamic stability of materials can depend on particle size due to the competition between surface and bulk energy. In this Letter, we show that, while sodium peroxide (Na2O2) is the stable bulk phase of Na in an oxygen environment at standard conditions, sodium superoxide (NaO2) is considerably more stable at the nanoscale. As a consequence, the superoxide requires a much lower nucleation energy than the peroxide, explaining why it can be observed as the discharge product in some Na-O2 batteries. As the superoxide can be recharged (decomposed) at much lower overpotentials than the peroxide, these findings are important to create highly reversible Na-O2 batteries. We derive the specific electrochemical conditions to nucleate and retain Na-superoxides and comment on the importance of considering the nanophase thermodynamics when optimizing an electrochemical system.

FireWorks: a dynamic workflow system designed for high-throughput applications

This paper introduces FireWorks, a workflow software for running high‐throughput calculation workflows at supercomputing centers. FireWorks has been used to complete over 50 million CPU‐hours worth of computational chemistry and materials science calculations at the National Energy Research Supercomputing Center. It has been designed to serve the demanding high‐throughput computing needs of these applications, with extensive support for (i) concurrent execution through job packing, (ii) failure detection and correction, (iii) provenance and reporting for long‐running projects, (iv) automated duplicate detection, and (v) dynamic workflows (i.e., modifying the workflow graph during runtime). We have found that these features are highly relevant to enabling modern data‐driven and high‐throughput science applications, and we discuss our implementation strategy that rests on Python and NoSQL databases (MongoDB). Finally, we present performance data and limitations of our approach along with planned future work. Copyright