Statistically Derived Proxy Potentials Accelerate Geometry Optimization of Crystal Structures.

The crystal structures of known materials contain the information about the interatomic interactions that produced these stable compounds. Similar to the use of reported protein structures to extract effective interactions between amino acids, that has been a useful tool in protein structure prediction, we demonstrate how to use this statistical paradigm to learn the effective inter-atomic interactions in crystalline inorganic solids. By analyzing the reported crystallographic data for inorganic materials, we have constructed statistically derived proxy potentials (SPPs) that can be used to assess how realistic or unusual a computer-generated structure is compared to the reported experimental structures. The SPPs can be directly used for structure optimization to improve this similarity metric, that we refer to as the SPP score. We apply such optimization step to markedly improve the quality of the input crystal structures for DFT calculations and demonstrate that the SPPs accelerate geometry optimization for three systems relevant to battery materials. As this approach is chemistry-agnostic and can be used at scale, we produced a database of all possible pair potentials in a tabulated form ready to use.

Inferring energy-composition relationships with Bayesian optimization enhances exploration of inorganic materials.

Computational exploration of the compositional spaces of materials can provide guidance for synthetic research and thus accelerate the discovery of novel materials. Most approaches employ high-throughput sampling and focus on reducing the time for energy evaluation for individual compositions, often at the cost of accuracy. Here, we present an alternative approach focusing on effective sampling of the compositional space. The learning algorithm PhaseBO optimizes the stoichiometry of the potential target material while improving the probability of and accelerating its discovery without compromising the accuracy of energy evaluation.

Enhancement of Low Temperature Superionic Conductivity by Suppression of Li Site Ordering in Li7Si2-xGexS7I.

Ge4+ substitution into the recently discovered superionic conductor Li7Si2S7I is demonstrated by synthesis of Li7Si2-xGexS7I, where x ≤ 1.2. The anion packing and tetrahedral silicon location of Li7Si2S7I are retained upon substitution. Single crystal X-ray diffraction shows that substitution of larger Ge4+ for Si4+ expands the unit cell volume and further increases Li+ site disorder, such that Li7Si0.88Ge1.12S7I has one Li+ site more (sixteen in total) than Li7Si2S7I. The ionic conductivity of Li7Si0.8Ge1.2S7I (x = 1.2) at 303 K is 1.02(3) × 10-2 S cm-1 with low activation energies for Li+ transport demonstrated over a wide temperature range by AC impedance and 7Li NMR spectroscopy. All sixteen Li+ sites remain occupied to temperatures as low as 30 K in Li7Si0.88Ge1.12S7I as a result of the structural expansion. This differs from Li7Si2S7I, where the partial Li+ site ordering observed below room temperature reduces the ionic conductivity. The suppression of Li+ site depopulation by Ge4+ substitution retains the high mobility to temperatures as low as 200 K, yielding low temperature performance comparable with state-of-the-art Li ion conducting materials.

Extended Condensed Ultraphosphate Frameworks with Monovalent Ions Combine Lithium Mobility with High Computed Electrochemical Stability.

Extended anionic frameworks based on condensation of polyhedral main group non-metal anions offer a wide range of structure types. Despite the widespread chemistry and earth abundance of phosphates and silicates, there are no reports of extended ultraphosphate anions with lithium. We describe the lithium ultraphosphates Li3P5O14 and Li4P6O17 based on extended layers and chains of phosphate, respectively. Li3P5O14 presents a complex structure containing infinite ultraphosphate layers with 12-membered rings that are stacked alternately with lithium polyhedral layers. Two distinct vacant tetrahedral sites were identified at the end of two distinct finite Li6O1626- chains. Li4P6O17 features a new type of loop-branched chain defined by six PO43- tetrahedra. The ionic conductivities and electrochemical properties of Li3P5O14 were examined by impedance spectroscopy combined with DC polarization, NMR spectroscopy, and galvanostatic plating/stripping measurements. The structure of Li3P5O14 enables three-dimensional lithium migration that affords the highest ionic conductivity (8.5(5) × 10-7 S cm-1 at room temperature for bulk), comparable to that of commercialized LiPON glass thin film electrolytes, and lowest activation energy (0.43(7) eV) among all reported ternary Li-P-O phases. Both new lithium ultraphosphates are predicted to have high thermodynamic stability against oxidation, especially Li3P5O14, which is predicted to be stable to 4.8 V, significantly higher than that of LiPON and other solid electrolytes. The condensed phosphate units defining these ultraphosphate structures offer a new route to optimize the interplay of conductivity and electrochemical stability required, for example, in cathode coatings for lithium ion batteries.

Ordered Oxygen Vacancies in the Lithium-Rich Oxide Li4CuSbO5.5, a Triclinic Structure Type Derived from the Cubic Rocksalt Structure.

Li-rich rocksalt oxides are promising candidates as high-energy density cathode materials for next-generation Li-ion batteries because they present extremely diverse structures and compositions. Most reported materials in this family contain as many cations as anions, a characteristic of the ideal cubic closed-packed rocksalt composition. In this work, a new rocksalt-derived structure type is stabilized by selecting divalent Cu and pentavalent Sb cations to favor the formation of oxygen vacancies during synthesis. The structure and composition of the oxygen-deficient Li4CuSbO5.5□0.5 phase is characterized by combining X-ray and neutron diffraction, ICP-OES, XAS, and magnetometry measurements. The ordering of cations and oxygen vacancies is discussed in comparison with the related Li2CuO2□1 and Li5SbO5□1 phases. The electrochemical properties of this material are presented, with only 0.55 Li+ extracted upon oxidation, corresponding to a limited utilization of cationic and/or anionic redox, whereas more than 2 Li+ ions can be reversibly inserted upon reduction to 1 V vs Li+/Li, a large capacity attributed to a conversion reaction and the reduction of Cu2+ to Cu0. Control of the formation of oxygen vacancies in Li-rich rocksalt oxides by selecting appropriate cations and synthesis conditions affords a new route for tuning the electrochemical properties of cathode materials for Li-ion batteries. Furthermore, the development of material models of the required level of detail to predict phase diagrams and electrochemical properties, including oxygen release in Li-rich rocksalt oxides, still relies on the accurate prediction of crystal structures. Experimental identification of new accessible structure types stabilized by oxygen vacancies represents a valuable step forward in the development of predictive models.

Superionic lithium transport via multiple coordination environments defined by two-anion packing.

Fast cation transport in solids underpins energy storage. Materials design has focused on structures that can define transport pathways with minimal cation coordination change, restricting attention to a small part of chemical space. Motivated by the greater structural diversity of binary intermetallics than that of the metallic elements, we used two anions to build a pathway for three-dimensional superionic lithium ion conductivity that exploits multiple cation coordination environments. Li7Si2S7I is a pure lithium ion conductor created by an ordering of sulphide and iodide that combines elements of hexagonal and cubic close-packing analogously to the structure of NiZr. The resulting diverse network of lithium positions with distinct geometries and anion coordination chemistries affords low barriers to transport, opening a large structural space for high cation conductivity.

Li4.3AlS3.3Cl0.7: A Sulfide-Chloride Lithium Ion Conductor with Highly Disordered Structure and Increased Conductivity.

Mixed anion materials and anion doping are very promising strategies to improve solid-state electrolyte properties by enabling an optimized balance between good electrochemical stability and high ionic conductivity. In this work, we present the discovery of a novel lithium aluminum sulfide-chloride phase, obtained by substitution of chloride for sulfur in Li3AlS3 and Li5AlS4 materials. The structure is strongly affected by the presence of chloride anions on the sulfur site, as the substitution was shown to be directly responsible for the stabilization of a higher symmetry phase presenting a large degree of cationic site disorder, as well as disordered octahedral lithium vacancies. The effect of disorder on the lithium conductivity properties was assessed by a combined experimental-theoretical approach. In particular, the conductivity is increased by a factor 103 compared to the pure sulfide phase. Although it remains moderate (10-6 S·cm-1), ab initio molecular dynamics and maximum entropy (applied to neutron diffraction data) methods show that disorder leads to a 3D diffusion pathway, where Li atoms move thanks to a concerted mechanism. An understanding of the structure-property relationships is developed to determine the limiting factor governing lithium ion conductivity. This analysis, added to the strong step forward obtained in the determination of the dimensionality of diffusion, paves the way for accessing even higher conductivity in materials comprising an hcp anion arrangement.

Linear and Helical Cesium Iodide Atomic Chains in Ultranarrow Single-Walled Carbon Nanotubes: Impact on Optical Properties.

One-dimensional (1D) atomic chains of CsI were previously reported in double-walled carbon nanotubes with ∼0.8 nm inner diameter. Here, we demonstrate that, while 1D CsI chains form within narrow ∼0.73 nm diameter single-walled carbon nanotubes (SWCNTs), wider SWCNT tubules (∼0.8-1.1 nm) promote the formation of helical chains of CsI 2 × 1 atoms in cross-section. These CsI helices create complementary oval distortions in encapsulating SWCNTs with highly strained helices formed from strained Cs2I2 parallelogram units in narrow tubes to lower strain Cs2I2 units in wider tubes. The observed structural changes and charge distribution were analyzed by density-functional theory and Bader analysis. CsI chains also produce conformation-selective changes to the electronic structure and optical properties of the encapsulating tubules. The observed defects are an interesting variation from defects commonly observed in alkali halides as these are normally associated with the Schottky and Frenkel type. The energetics of CsI 2 × 1 helix formation in SWCNTs suggests how these could be controllably formed.

Element selection for crystalline inorganic solid discovery guided by unsupervised machine learning of experimentally explored chemistry.

The selection of the elements to combine delimits the possible outcomes of synthetic chemistry because it determines the range of compositions and structures, and thus properties, that can arise. For example, in the solid state, the elemental components of a phase field will determine the likelihood of finding a new crystalline material. Researchers make these choices based on their understanding of chemical structure and bonding. Extensive data are available on those element combinations that produce synthetically isolable materials, but it is difficult to assimilate the scale of this information to guide selection from the diversity of potential new chemistries. Here, we show that unsupervised machine learning captures the complex patterns of similarity between element combinations that afford reported crystalline inorganic materials. This model guides prioritisation of quaternary phase fields containing two anions for synthetic exploration to identify lithium solid electrolytes in a collaborative workflow that leads to the discovery of Li3.3SnS3.3Cl0.7. The interstitial site occupancy combination in this defect stuffed wurtzite enables a low-barrier ion transport pathway in hexagonal close-packing.

Electronic Structure Control of Sub-nanometer 1D SnTe via Nanostructuring within Single-Walled Carbon Nanotubes.

Nanostructuring, e. g., reduction of dimensionality in materials, offers a viable route toward regulation of materials electronic and hence functional properties. Here, we present the extreme case of nanostructuring, exploiting the capillarity of single-walled carbon nanotubes (SWCNTs) for the synthesis of the smallest possible SnTe nanowires with cross sections as thin as a single atom column. We demonstrate that by choosing the appropriate diameter of a template SWCNT, we can manipulate the structure of the quasi-one-dimensional (1D) SnTe to design electronic behavior. From first principles, we predict the structural re-formations that SnTe undergoes in varying encapsulations and confront the prediction with TEM imagery. To further illustrate the control of physical properties by nanostructuring, we study the evolution of transport properties in a homologous series of models of synthesized and isolated SnTe nanowires varying only in morphology and atomic layer thickness. This extreme scaling is predicted to significantly enhance thermoelectric performance of SnTe, offering a prospect for further experimental studies and future applications.

Single-Atom Scale Structural Selectivity in Te Nanowires Encapsulated Inside Ultranarrow, Single-Walled Carbon Nanotubes.

Extreme nanowires (ENs) represent the ultimate class of crystals: They are the smallest possible periodic materials. With atom-wide motifs repeated in one dimension (1D), they offer a privileged perspective into the physics and chemistry of low-dimensional systems. Single-walled carbon nanotubes (SWCNTs) provide ideal environments for the creation of such materials. Here we present a comprehensive study of Te ENs encapsulated inside ultranarrow SWCNTs with diameters between 0.7 nm and 1.1 nm. We combine state-of-the-art imaging techniques and 1D-adapted ab initio structure prediction to treat both confinement and periodicity effects. The studied Te ENs adopt a variety of structures, exhibiting a true 1D realization of a Peierls structural distortion and transition from metallic to insulating behavior as a function of encapsulating diameter. We analyze the mechanical stability of the encapsulated ENs and show that nanoconfinement is not only a useful means to produce ENs but also may actually be necessary, in some cases, to prevent them from disintegrating. The ability to control functional properties of these ENs with confinement has numerous applications in future device technologies, and we anticipate that our study will set the basic paradigm to be adopted in the characterization and understanding of such systems.