Cation Distribution and Anion Transport in the La3Ga5-xGe1+xO14+0.5x Langasite Structure.

Exploration of compositional disorder using conventional diffraction-based techniques is challenging for systems containing isoelectronic ions possessing similar coherent neutron scattering lengths. Here, we show that a multinuclear solid-state Nuclear Magnetic Resonance (NMR) approach provides compelling insight into the Ga3+/Ge4+ cation distribution and oxygen anion transport in a family of solid electrolytes with langasite structure and La3Ga5-xGe1+xO14+0.5x composition. Ultrahigh field 71Ga Magic Angle Spinning (MAS) NMR experiments acquired at 35.2 T offer striking resolution enhancement, thereby enabling clear detection of Ga sites in different coordination environments. Three-connected GaO4, four-connected GaO4 and GaO6 polyhedra are probed for the parent La3Ga5GeO14 structure, while one additional spectral feature corresponding to the key (Ga,Ge)2O8 structural unit which forms to accommodate the interstitial oxide ions is detected for the Ge4+-doped La3Ga3.5Ge2.5O14.75 phase. The complex spectral line shapes observed in the MAS NMR spectra are reproduced very accurately by the NMR parameters computed for a symmetry-adapted configurational ensemble that comprehensively models site disorder. This approach further reveals a Ga3+/Ge4+ distribution across all Ga/Ge sites that is controlled by a kinetically governed cation diffusion process. Variable temperature 17O MAS NMR experiments up to 700 °C importantly indicate that the presence of interstitial oxide ions triggers chemical exchange between all oxygen sites, thereby enabling atomic-scale understanding of the anion diffusion mechanism underpinning the transport properties of these materials.

Synthesis, Structure, and Properties of CuBiSeCl2: A Chalcohalide Material with Low Thermal Conductivity.

Mixed anion halide-chalcogenide materials have recently attracted attention for a variety of applications, owing to their desirable optoelectronic properties. We report the synthesis of a previously unreported mixed-metal chalcohalide material, CuBiSeCl2 (Pnma), accessed through a simple, low-temperature solid-state route. The physical structure is characterized through single-crystal X-ray diffraction and reveals significant Cu displacement within the CuSe2Cl4 octahedra. The electronic structure of CuBiSeCl2 is investigated computationally, which indicates highly anisotropic charge carrier effective masses, and by experimental verification using X-ray photoelectron spectroscopy, which reveals a valence band dominated by Cu orbitals. The band gap is measured to be 1.33(2) eV, a suitable value for solar absorption applications. The electronic and thermal properties, including resistivity, Seebeck coefficient, thermal conductivity, and heat capacity, are also measured, and it is found that CuBiSeCl2 exhibits a low room temperature thermal conductivity of 0.27(4) W K-1 m-1, realized through modifications to the phonon landscape through increased bonding anisotropy.

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.

Control of Polarity in Kagome-NiAs Bismuthides.

A 2×2×1 superstructure of the P63/mmc NiAs structure is reported in which kagome nets are stabilized in the octahedral transition metal layers of the compounds Ni0.7Pd0.2Bi, Ni0.6Pt0.4Bi, and Mn0.99Pd0.01Bi. The ordered vacancies that yield the true hexagonal kagome motif lead to filling of trigonal bipyramidal interstitial sites with the transition metal in this family of "kagome-NiAs" type materials. Further ordering of vacancies within these interstitial layers can be compositionally driven to simultaneously yield kagome-connected layers and a net polarization along the c axes in Ni0.9Bi and Ni0.79Pd0.08Bi, which adopt Fmm2 symmetry. The polar and non-polar materials exhibit different electronic transport behaviour, reflecting the tuneability of both structure and properties within the NiAs-type bismuthide materials family.

Accessing Mg-Ion Storage in V2PS10 via Combined Cationic-Anionic Redox with Selective Bond Cleavage.

Magnesium batteries attract interest as alternative energy-storage devices because of elemental abundance and potential for high energy density. Development is limited by the absence of suitable cathodes, associated with poor diffusion kinetics resulting from strong interactions between Mg2+ and the host structure. V2PS10 is reported as a positive electrode material for rechargeable magnesium batteries. Cyclable capacity of 100 mAh g-1 is achieved with fast Mg2+ diffusion of 7.2 × ${\times }$ 10-11-4 × ${\times }$ 10-14 cm2 s-1. The fast insertion mechanism results from combined cationic redox on the V site and anionic redox on the (S2)2- site; enabled by reversible cleavage of S-S bonds, identified by X-ray photoelectron and X-ray absorption spectroscopy. Detailed structural characterisation with maximum entropy method analysis, supported by density functional theory and projected density of states analysis, reveals that the sulphur species involved in anion redox are not connected to the transition metal centres, spatially separating the two redox processes. This facilitates fast and reversible Mg insertion in which the nature of the redox process depends on the cation insertion site, creating a synergy between the occupancy of specific Mg sites and the location of the electrons transferred.

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.

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.

A high throughput synthetic workflow for solid state synthesis of oxides.

High-throughput synthetic methods are well-established for chemistries involving liquid- or vapour-phase reagents and have been harnessed to prepare arrays of inorganic materials. The versatile but labour-intensive sub-solidus reaction pathway that is the backbone of the functional and electroceramics materials industries has proved more challenging to automate because of the use of solid-state reagents. We present a high-throughput sub-solidus synthesis workflow that permits rapid screening of oxide chemical space that will accelerate materials discovery by enabling simultaneous expansion of explored compositions and synthetic conditions. This increases throughput by using manual steps where actions are undertaken on multiple, rather than individual, samples which are then further combined with researcher-hands-free automated processes. We exemplify this by extending the BaYxSn1-xO3-x/2 solid solution beyond the reported limit to a previously unreported composition and by exploring the Nb-Al-P-O composition space showing the applicability of the workflow to polyanion-based compositions beyond oxides.

Local Structure in Disordered Melilite Revealed by Ultrahigh Field 71Ga and 139La Solid-State Nuclear Magnetic Resonance Spectroscopy.

Multinuclear Nuclear Magnetic Resonance (NMR) spectroscopy of quadrupolar nuclei at ultrahigh magnetic field provides compelling insight into the short-range structure in a family of fast oxide ion electrolytes with La1+xSr1-xGa3O7+0.5x melilite structure. The striking resolution enhancement in the solid-state 71Ga NMR spectra measured with the world's unique series connected hybrid magnet operating at 35.2 T distinctly resolves Ga sites in four- and five-fold coordination environments. Detection of five-coordinate Ga centers in the site-disordered La1.54Sr0.46Ga3O7.27 melilite is critical given that the GaO5 unit accommodates interstitial oxide ions and provides excellent transport properties. This work highlights the importance of ultrahigh magnetic fields for the detection of otherwise broad spectral features in systems containing quadrupolar nuclei and the potential of ensemble-based computational approaches for the interpretation of NMR data acquired for site-disordered materials.

A proxy for oxygen storage capacity from high-throughput screening and automated data analysis.

Oxygen storage and release is a foundational part of many key pathways in heterogeneous catalysis, such as the Mars-van Krevelen mechanism. However, direct measurement of oxygen storage capacity (OSC) is time-consuming and difficult to parallelise. To accelerate the discovery of stable high OSC rare-earth doped ceria-zirconia oxygen storage catalysts, a high-throughput robotic-based co-precipitation synthesis route was coupled with sequentially automated powder X-ray diffraction (PXRD), Raman and thermogravimetric analysis (TGA) characterisation of the resulting materials libraries. Automated extraction of data enabled rapid trend identification and provided a data set for the development of an OSC prediction model, investigating the significance of each extracted quantity towards OSC. The optimal OSC prediction model produced incorporated variables from only fast-to-measure analytical techniques and gave predicted values of OSC that agreed with experimental observations across an independent validation set. Those measured quantities that feature in the model emerge as proxies for OSC performance. The ability to predict the OSC of the materials accelerates the discovery of high-capacity oxygen storage materials and motivates the development of similar high-throughput workflows to identify candidate catalysts for other heterogeneous transformations.

Disorder and Oxide Ion Diffusion Mechanism in La1.54Sr0.46Ga3O7.27 Melilite from Nuclear Magnetic Resonance.

Layered tetrahedral network melilite is a promising structural family of fast ion conductors that exhibits the flexibility required to accommodate interstitial oxide anions, leading to excellent ionic transport properties at moderate temperatures. Here, we present a combined experimental and computational magic angle spinning (MAS) nuclear magnetic resonance (NMR) approach which aims at elucidating the local configurational disorder and oxide ion diffusion mechanism in a key member of this structural family possessing the La1.54Sr0.46Ga3O7.27 composition. 17O and 71Ga MAS NMR spectra display complex spectral line shapes that could be accurately predicted using a computational ensemble-based approach to model site disorder across multiple cationic and anionic sites, thereby enabling the assignment of bridging/nonbridging oxygens and the identification of distinct gallium coordination environments. The 17O and 71Ga MAS NMR spectra of La1.54Sr0.46Ga3O7.27 display additional features not observed for the parent LaSrGa3O7 phase which are attributed to interstitial oxide ions incorporated upon cation doping and stabilized by the formation of five-coordinate Ga centers conferring framework flexibility. 17O high-temperature (HT) MAS NMR experiments capture exchange within the bridging oxygens at 130 °C and reveal coalescence of all oxygen signals in La1.54Sr0.46Ga3O7.27 at approximately 300 °C, indicative of the participation of both interstitial and framework oxide ions in the transport process. These results further supported by the coalescence of the 71Ga resonances in the 71Ga HT MAS NMR spectra of La1.54Sr0.46Ga3O7.27 unequivocally provide evidence of the conduction mechanism in this melilite phase and highlight the potential of MAS NMR spectroscopy to enhance the understanding of ionic motion in solid electrolytes.

4D Visualization of a Nonthermal Coherent Magnon in a Laser Heated Lattice by an X-ray Free Electron Laser.

Ultrafast optical manipulation of magnetic phenomena is an exciting achievement of mankind, expanding one's horizon of knowledge toward the functional nonequilibrium states. The dynamics acting on an extremely short timescale push the detection limits that reveal fascinating light-matter interactions for nonthermal creation of effective magnetic fields. While some cases are benchmarked by emergent transient behaviors, otherwise identifying the nonthermal effects remains challenging. Here, a femtosecond time-resolved resonant magnetic X-ray diffraction experiment is introduced, which uses an X-ray free-electron laser (XFEL) to distinguish between the effective field and the photoinduced thermal effect. It is observed that a multiferroic Y-type hexaferrite exhibits magnetic Bragg peak intensity oscillations manifesting entangled antiferromagnetic (AFM) and ferromagnetic (FM) Fourier components of a coherent AFM magnon. The magnon trajectory constructed in 3D space and time domains is decisive to evince ultrafast field formation preceding the lattice thermalization. A remarkable impact of photoexcitation across the electronic bandgap is directly unraveled, amplifying the photomagnetic coupling that is one of the highest among AFM dielectrics. Leveraging the above-bandgap photoexcitation, this energy-efficient optical process further suggests a novel photomagnetic control of ferroelectricity in multiferroics.

Optimality guarantees for crystal structure prediction.

Crystalline materials enable essential technologies, and their properties are determined by their structures. Crystal structure prediction can thus play a central part in the design of new functional materials1,2. Researchers have developed efficient heuristics to identify structural minima on the potential energy surface3-5. Although these methods can often access all configurations in principle, there is no guarantee that the lowest energy structure has been found. Here we show that the structure of a crystalline material can be predicted with energy guarantees by an algorithm that finds all the unknown atomic positions within a unit cell by combining combinatorial and continuous optimization. We encode the combinatorial task of finding the lowest energy periodic allocation of all atoms on a lattice as a mathematical optimization problem of integer programming6,7, enabling guaranteed identification of the global optimum using well-developed algorithms. A single subsequent local minimization of the resulting atom allocations then reaches the correct structures of key inorganic materials directly, proving their energetic optimality under clear assumptions. This formulation of crystal structure prediction establishes a connection to the theory of algorithms and provides the absolute energetic status of observed or predicted materials. It provides the ground truth for heuristic or data-driven structure prediction methods and is uniquely suitable for quantum annealers8-10, opening a path to overcome the combinatorial explosion of atomic configurations.

Toward Understanding of the Li-Ion Migration Pathways in the Lithium Aluminum Sulfides Li3AlS3 and Li4.3AlS3.3Cl0.7 via 6,7Li Solid-State Nuclear Magnetic Resonance Spectroscopy.

Li-containing materials providing fast ion transport pathways are fundamental in Li solid electrolytes and the future of all-solid-state batteries. Understanding these pathways, which usually benefit from structural disorder and cation/anion substitution, is paramount for further developments in next-generation Li solid electrolytes. Here, we exploit a range of variable temperature 6Li and 7Li nuclear magnetic resonance approaches to determine Li-ion mobility pathways, quantify Li-ion jump rates, and subsequently identify the limiting factors for Li-ion diffusion in Li3AlS3 and chlorine-doped analogue Li4.3AlS3.3Cl0.7. Static 7Li NMR line narrowing spectra of Li3AlS3 show the existence of both mobile and immobile Li ions, with the latter limiting long-range translational ion diffusion, while in Li4.3AlS3.3Cl0.7, a single type of fast-moving ion is present and responsible for the higher conductivity of this phase. 6Li-6Li exchange spectroscopy spectra of Li3AlS3 reveal that the slower moving ions hop between non-equivalent Li positions in different structural layers. The absence of the immobile ions in Li4.3AlS3.3Cl0.7, as revealed from 7Li line narrowing experiments, suggests an increased rate of ion exchange between the layers in this phase compared with Li3AlS3. Detailed analysis of spin-lattice relaxation data allows extraction of Li-ion jump rates that are significantly increased for the doped material and identify Li mobility pathways in both materials to be three-dimensional. The identification of factors limiting long-range translational Li diffusion and understanding the effects of structural modification (such as anion substitution) on Li-ion mobility provide a framework for the further development of more highly conductive Li solid electrolytes.

Control of Ionic Conductivity by Lithium Distribution in Cubic Oxide Argyrodites Li6+xP1-xSixO5Cl.

Argyrodite is a key structure type for ion-transporting materials. Oxide argyrodites are largely unexplored despite sulfide argyrodites being a leading family of solid-state lithium-ion conductors, in which the control of lithium distribution over a wide range of available sites strongly influences the conductivity. We present a new cubic Li-rich (>6 Li+ per formula unit) oxide argyrodite Li7SiO5Cl that crystallizes with an ordered cubic (P213) structure at room temperature, undergoing a transition at 473 K to a Li+ site disordered F4̅3m structure, consistent with the symmetry adopted by superionic sulfide argyrodites. Four different Li+ sites are occupied in Li7SiO5Cl (T5, T5a, T3, and T4), the combination of which is previously unreported for Li-containing argyrodites. The disordered F4̅3m structure is stabilized to room temperature via substitution of Si4+ with P5+ in Li6+xP1-xSixO5Cl (0.3 < x < 0.85) solid solution. The resulting delocalization of Li+ sites leads to a maximum ionic conductivity of 1.82(1) × 10-6 S cm-1 at x = 0.75, which is 3 orders of magnitude higher than the conductivities reported previously for oxide argyrodites. The variation of ionic conductivity with composition in Li6+xP1-xSixO5Cl is directly connected to structural changes occurring within the Li+ sublattice. These materials present superior atmospheric stability over analogous sulfide argyrodites and are stable against Li metal. The ability to control the ionic conductivity through structure and composition emphasizes the advances that can be made with further research in the open field of oxide argyrodites.

Band Structure Engineering of Bi4O4SeCl2 for Thermoelectric Applications.

The mixed anion material Bi4O4SeCl2 has an ultralow thermal conductivity of 0.1 W m-1 K-1 along its stacking axis (c axis) at room temperature, which makes it an ideal candidate for electronic band structure optimization via doping to improve its thermoelectric performance. Here, we design and realize an optimal doping strategy for Bi4O4SeCl2 from first principles and predict an enhancement in the density of states at the Fermi level of the material upon Sn and Ge doping. Experimental work realizes the as-predicted behavior in Bi4-x Sn x O4SeCl2 (x = 0.01) through the precise control of composition. Careful consideration of multiple accessible dopant sites and charge states allows for the effective computational screening of dopants for thermoelectric properties in Bi4O4SeCl2 and may be a suitable route for assessing other candidate materials.

Predicting spinel solid solutions using a random atom substitution method.

Exploration of chemical composition and structural configuration space is the central problem in crystal structure prediction. Even in limiting structure space to a single structure type, many different compositions and configurations are possible. In this work, we attempt to address this problem using an extension to the existing ChemDASH code in which variable compositions can be explored. We show that ChemDASH is an efficient method for exploring a fixed-composition space of spinel structures and build upon this to include variable compositions in the Mn-Fe-Zn-O spinel phase field. This work presents the first basin-hopping crystal structure prediction method that can explore variable compositions.

Cation Disorder and Large Tetragonal Supercell Ordering in the Li-Rich Argyrodite Li7Zn0.5SiS6.

A tetragonal argyrodite with >7 mobile cations, Li7Zn0.5SiS6, is experimentally realized for the first time through solid state synthesis and exploration of the Li-Zn-Si-S phase diagram. The crystal structure of Li7Zn0.5SiS6 was solved ab initio from high-resolution X-ray and neutron powder diffraction data and supported by solid-state NMR. Li7Zn0.5SiS6 adopts a tetragonal I4 structure at room temperature with ordered Li and Zn positions and undergoes a transition above 411.1 K to a higher symmetry disordered F43m structure more typical of Li-containing argyrodites. Simultaneous occupation of four types of Li site (T5, T5a, T2, T4) at high temperature and five types of Li site (T5, T2, T4, T1, and a new trigonal planar T2a position) at room temperature is observed. This combination of sites forms interconnected Li pathways driven by the incorporation of Zn2+ into the Li sublattice and enables a range of possible jump processes. Zn2+ occupies the 48h T5 site in the high-temperature F43m structure, and a unique ordering pattern emerges in which only a subset of these T5 sites are occupied at room temperature in I4 Li7Zn0.5SiS6. The ionic conductivity, examined via AC impedance spectroscopy and VT-NMR, is 1.0(2) × 10-7 S cm-1 at room temperature and 4.3(4) × 10-4 S cm-1 at 503 K. The transition between the ordered I4 and disordered F43m structures is associated with a dramatic decrease in activation energy to 0.34(1) eV above 411 K. The incorporation of a small amount of Zn2+ exercises dramatic control of Li order in Li7Zn0.5SiS6 yielding a previously unseen distribution of Li sites, expanding our understanding of structure-property relationships in argyrodite materials.

Machine-Learning Prediction of Metal-Organic Framework Guest Accessibility from Linker and Metal Chemistry.

The choice of metal and linker together define the structure and therefore the guest accessibility of a metal-organic framework (MOF), but the large number of possible metal-linker combinations makes the selection of components for synthesis challenging. We predict the guest accessibility of a MOF with 80.5 % certainty based solely on the identity of these two components as chosen by the experimentalist, by decomposing reported experimental three-dimensional MOF structures in the Cambridge Structural Database into metal and linker and then learning the connection between the components' chemistry and the MOF porosity. Pore dimensions of the guest-accessible space are classified into four ranges with three sequential models. Both the dataset and the predictive models are available to download and offer simple guidance in prioritization of the choice of the components for exploratory MOF synthesis for separation and catalysis based on guest accessibility considerations.