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.

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.

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.

Evolution of Short-Range Order of Amorphous GeTe Upon Structural Relaxation Obtained by TEM Diffractometry and RMC Methods.

Glasses frequently reveal structural relaxation that leads to changes in their physical properties including enthalpy, specific volume, and resistivity. Analyzing the short-range order (SRO) obtained from electron diffraction by transmission electron microscopy (TEM) in combination with Reverse-Monte-Carlo (RMC) simulations is shown to provide information on the atomic arrangement. The technique elaborated here features several benefits including reliability, accessibility, and allows for obtaining detailed structural data quickly. This is demonstrated with a detailed view of the structural changes in the as-deposited amorphous phase change material (PCM) GeTe. The data show a significant increase in the average bond angle upon thermal treatment. At the same time the fraction of tetrahedrally coordinated Ge atoms decreases due to an increase in octahedrally distorted and pyramidal motifs. This finding provides further evidence for the atomic processes that govern structural relaxation in amorphous GeTe and other PCMs. A thorough literature review finally unveils possible origins of the large discrepancies reported on the structure of amorphous GeTe.

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.

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.

Exploring the Role of Cluster Formation in UiO Family Hf Metal-Organic Frameworks with in Situ X-ray Pair Distribution Function Analysis.

The structures of Zr and Hf metal-organic frameworks (MOFs) are very sensitive to small changes in synthetic conditions. One key difference affecting the structure of UiO MOF phases is the shape and nuclearity of Zr or Hf metal clusters acting as nodes in the framework; although these clusters are crucial, their evolution during MOF synthesis is not fully understood. In this paper, we explore the nature of Hf metal clusters that form in different reaction solutions, including in a mixture of DMF, formic acid, and water. We show that the choice of solvent and reaction temperature in UiO MOF syntheses determines the cluster identity and hence the MOF structure. Using in situ X-ray pair distribution function measurements, we demonstrate that the evolution of different Hf cluster species can be tracked during UiO MOF synthesis, from solution stages to the full crystalline framework, and use our understanding to propose a formation mechanism for the hcp UiO-66(Hf) MOF, in which first the metal clusters aggregate from the M6 cluster (as in fcu UiO-66) to the hcp-characteristic M12 double cluster and, following this, the crystalline hcp framework forms. These insights pave the way toward rationally designing syntheses of as-yet unknown MOF structures, via tuning the synthesis conditions to select different cluster species.

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.

High-Throughput Discovery of a Rhombohedral Twelve-Connected Zirconium-Based Metal-Organic Framework with Ordered Terephthalate and Fumarate Linkers.

We report a metal-organic framework where an ordered array of two linkers with differing length and geometry connect [Zr6 (OH)4 O4 ]12+ clusters into a twelve-connected fcu net that is rhombohedrally distorted from cubic symmetry. The ordered binding of equal numbers of terephthalate and fumarate ditopic carboxylate linkers at the trigonal antiprismatic Zr6 core creates close-packed layers of fumarate-connected clusters that are connected along the single remaining threefold axis by terephthalates. This well-defined linker arrangement retains the three-dimensional porosity of the Zr cluster-based UiO family while creating two distinct windows within the channels that define two distinct guest diffusion paths. The ordered material is accessed by a restricted combination of composition and process parameters that were identified by high-throughput synthesis.

Low thermal conductivity in a modular inorganic material with bonding anisotropy and mismatch.

The thermal conductivity of crystalline materials cannot be arbitrarily low, as the intrinsic limit depends on the phonon dispersion. We used complementary strategies to suppress the contribution of the longitudinal and transverse phonons to heat transport in layered materials that contain different types of intrinsic chemical interfaces. BiOCl and Bi2O2Se encapsulate these design principles for longitudinal and transverse modes, respectively, and the bulk superlattice material Bi4O4SeCl2 combines these effects by ordering both interface types within its unit cell to reach an extremely low thermal conductivity of 0.1 watts per kelvin per meter at room temperature along its stacking direction. This value comes within a factor of four of the thermal conductivity of air. We demonstrated that chemical control of the spatial arrangement of distinct interfaces can synergically modify vibrational modes to minimize thermal conductivity.

Discovery of a Low Thermal Conductivity Oxide Guided by Probe Structure Prediction and Machine Learning.

We report the aperiodic titanate Ba10 Y6 Ti4 O27 with a room-temperature thermal conductivity that equals the lowest reported for an oxide. The structure is characterised by discontinuous occupancy modulation of each of the sites and can be considered as a quasicrystal. The resulting localisation of lattice vibrations suppresses phonon transport of heat. This new lead material for low-thermal-conductivity oxides is metastable and located within a quaternary phase field that has been previously explored. Its isolation thus requires a precisely defined synthetic protocol. The necessary narrowing of the search space for experimental investigation was achieved by evaluation of titanate crystal chemistry, prediction of unexplored structural motifs that would favour synthetically accessible new compositions, and assessment of their properties with machine-learning models.

Evidence of Cosmic Impact at Abu Hureyra, Syria at the Younger Dryas Onset (~12.8 ka): High-temperature melting at >2200 °C.

At Abu Hureyra (AH), Syria, the 12,800-year-old Younger Dryas boundary layer (YDB) contains peak abundances in meltglass, nanodiamonds, microspherules, and charcoal. AH meltglass comprises 1.6 wt.% of bulk sediment, and crossed polarizers indicate that the meltglass is isotropic. High YDB concentrations of iridium, platinum, nickel, and cobalt suggest mixing of melted local sediment with small quantities of meteoritic material. Approximately 40% of AH glass display carbon-infused, siliceous plant imprints that laboratory experiments show formed at a minimum of 1200°-1300 °C; however, reflectance-inferred temperatures for the encapsulated carbon were lower by up to 1000 °C. Alternately, melted grains of quartz, chromferide, and magnetite in AH glass suggest exposure to minimum temperatures of 1720 °C ranging to >2200 °C. This argues against formation of AH meltglass in thatched hut fires at 1100°-1200 °C, and low values of remanent magnetism indicate the meltglass was not created by lightning. Low meltglass water content (0.02-0.05% H2O) is consistent with a formation process similar to that of tektites and inconsistent with volcanism and anthropogenesis. The wide range of evidence supports the hypothesis that a cosmic event occurred at Abu Hureyra ~12,800 years ago, coeval with impacts that deposited high-temperature meltglass, melted microspherules, and/or platinum at other YDB sites on four continents.

Tracking the evolution of a single composite particle during redox cycling for application in H2 production.

Composite materials consisting of metal and metal oxide phases are being researched intensively for various energy conversion applications where they are often expected to operate under redox conditions at elevated temperature. Understanding of the dynamics of composite evolution during redox cycling is still very limited, yet critical to maximising performance and increasing durability. Here we track the microstructural evolution of a single composite particle over 200 redox cycles for hydrogen production by chemical looping, using multi-length scale X-ray computed tomography. We show that redox cycling triggers a centrifugal redispersion of the metal phase and a centripetal clustering of porosity, both seemingly driven by the asymmetric nature of oxygen exchange in composites. Initially, the particle develops a large amount of internal porosity which boosts activity, but on the long term this facilitates structural and compositional reorganisation and eventually degradation. These results provide valuable insight into redox-driven microstructural changes and also for the design of new composite materials with enhanced durability.

One class classification as a practical approach for accelerating π-π co-crystal discovery.

The implementation of machine learning models has brought major changes in the decision-making process for materials design. One matter of concern for the data-driven approaches is the lack of negative data from unsuccessful synthetic attempts, which might generate inherently imbalanced datasets. We propose the application of the one-class classification methodology as an effective tool for tackling these limitations on the materials design problems. This is a concept of learning based only on a well-defined class without counter examples. An extensive study on the different one-class classification algorithms is performed until the most appropriate workflow is identified for guiding the discovery of emerging materials belonging to a relatively small class, that being the weakly bound polyaromatic hydrocarbon co-crystals. The two-step approach presented in this study first trains the model using all the known molecular combinations that form this class of co-crystals extracted from the Cambridge Structural Database (1722 molecular combinations), followed by scoring possible yet unknown pairs from the ZINC15 database (21 736 possible molecular combinations). Focusing on the highest-ranking pairs predicted to have higher probability of forming co-crystals, materials discovery can be accelerated by reducing the vast molecular space and directing the synthetic efforts of chemists. Further on, using interpretability techniques a more detailed understanding of the molecular properties causing co-crystallization is sought after. The applicability of the current methodology is demonstrated with the discovery of two novel co-crystals, namely pyrene-6H-benzo[c]chromen-6-one (1) and pyrene-9,10-dicyanoanthracene (2).

Unlocking the key to persistent luminescence with X-ray absorption spectroscopy: a local structure investigation of Cr-substituted spinel-type phosphors.

Developing new persistent luminescent phosphors, a unique class of inorganic materials that can produce a visible light emission lasting minutes to hours requires improving our understanding of their fundamental structure-property relationships. Research has shown that one of the most critical components governing persistent luminescence is the existence of lattice defects in a material. Specifically, vacancies and anti-site defects that coincide with substitution of the luminescent center, e.g., Eu2+ or Cr3+, are generally considered essential to generate the ultra-long luminescent lifetimes. This research solidifies the connection between defects and the remarkable optical properties. The persistent luminescent compound Zn(Ga1-xAlx)2O4 (x = 0-1), which adopts a spinel-type structure, is investigated by examining the X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine-structure (EXAFS) at the Cr K and Zn K edges. This investigation reveals a structural distortion of the octahedrally coordinated main group metal site concurrent with increasing Al3+ content. Moreover, these results suggest there is a dependence between the local crystallographic distortions, the presence of defects, and a material's persistent luminescence. In combination, this work provides an avenue to understand the connection between the structure-defect-property relationships that govern the properties of many functional inorganic materials.

When Do Anisotropic Magnetic Susceptibilities Lead to Large NMR Shifts? Exploring Particle Shape Effects in the Battery Electrode Material LiFePO4.

Materials used as electrodes in energy storage devices have been extensively studied with solid-state NMR spectroscopy. Due to the almost ubiquitous presence of transition metals, these systems are also often magnetic. While it is well known that the presence of anisotropic bulk magnetic susceptibility (ABMS) leads to broadening of resonances under magic angle spinning, we show that for monodisperse and nonspherical particle morphologies the ABMS can also lead to considerable shifts, which vary substantially as a function of particle shape. This, on one hand, complicates the interpretation of the NMR spectrum and means that different samples of the same nominal material may no longer give rise to the same measured shift. On the other hand, the ABMS shift provides a mechanism with which to derive the particle shape from the NMR spectrum. In this work, we present a methodology to model the ABMS shift and relate it to the shape of the studied particles. The approach is tested on the 7Li NMR spectra of single crystals and powders of LiFePO4. The results show that the ABMS shift can be a major contribution to the total NMR shift in systems with large magnetic anisotropies and small hyperfine shifts, 7Li shifts for typical LiFePO4 morphologies varying by as much as 100 ppm. The results are generalized to demonstrate that the approach can be used as a means with which to probe the aspect ratio of particles. The work has implications for the analysis of NMR spectra of all materials with anisotropic magnetic susceptibilities, including diamagnetic materials such as graphite.

Mechanical properties of the ferroelectric metal-free perovskite [MDABCO](NH4)I3.

The metal-free hybrid organic-inorganic perovskite [MDABCO](NH4)I3 (with MDABCO = N-methyl-1,4-diazabicyclo[2.2.2]octane) was recently discovered to exhibit an excellent ferroelectric performance, challenging established ceramic ferroelectrics. We here probe the mechanical properties of [MDABCO](NH4)I3 by combining high pressure single crystal X-ray diffraction and nanoindentation, underlining the exceptional role and opportunities that come with the use of sustainable, metal-free perovskite ferroelectrics.

Computationally Guided Discovery of the Sulfide Li3AlS3 in the Li-Al-S Phase Field: Structure and Lithium Conductivity.

With the goal of finding new lithium solid electrolytes by a combined computational-experimental method, the exploration of the Li-Al-O-S phase field resulted in the discovery of a new sulfide Li3AlS3. The structure of the new phase was determined through an approach combining synchrotron X-ray and neutron diffraction with 6Li and 27Al magic-angle spinning nuclear magnetic resonance spectroscopy and revealed to be a highly ordered cationic polyhedral network within a sulfide anion hcp-type sublattice. The originality of the structure relies on the presence of Al2S6 repeating dimer units consisting of two edge-shared Al tetrahedra. We find that, in this structure type consisting of alternating tetrahedral layers with Li-only polyhedra layers, the formation of these dimers is constrained by the Al/S ratio of 1/3. Moreover, by comparing this structure to similar phases such as Li5AlS4 and Li4.4Al0.2Ge0.3S4 ((Al + Ge)/S = 1/4), we discovered that the AlS4 dimers not only influence atomic displacements and Li polyhedral distortions but also determine the overall Li polyhedral arrangement within the hcp lattice, leading to the presence of highly ordered vacancies in both the tetrahedral and Li-only layer. AC impedance measurements revealed a low lithium mobility, which is strongly impacted by the presence of ordered vacancies. Finally, a composition-structure-property relationship understanding was developed to explain the extent of lithium mobility in this structure type.

Control of Metal-Organic Framework Crystallization by Metastable Intermediate Pre-equilibrium Species.

There is an increasing amount of interest in metal-organic frameworks (MOFs) for a variety of applications, from gas sensing and separations to electronics and catalysis. However, the mechanisms by which they crystallize remain poorly understood. Herein, an important new insight into MOF formation is reported. It is shown that, prior to network assembly, crystallization intermediates in the canonical ZIF-8 system exist in a dynamic pre-equilibrium, which depends on the reactant concentrations and the progress of reaction. Concentration can, therefore, be used as a synthetic handle to directly control particle size, with potential implications for industrial scale-up and gas sorption applications. These findings enable the rationalization of apparent contradictions between previous studies of ZIF-8 and opens up new opportunities for the control of crystallization in network solids more generally.