Direct assignment of molecular vibrations via normal mode analysis of the neutron dynamic pair distribution function technique

A New Spin on Material Properties: Local Magnetic Structure in Functional and Quantum Materials

The past few decades have made clear that the properties and performances of emerging functional and quantum materials can depend strongly on their local atomic and/or magnetic structure, particularly when details of the local structure deviate from the long-range structure averaged over space and time. Traditional methods of structural refinement (e.g., Rietveld) are typically sensitive only to the average structure, creating a need for more advanced structural probes suitable for extracting information about structural correlations on short length- and time-scales. In this Perspective, we describe the importance of local magnetic structure in several classes of emerging materials and present the magnetic pair distribution function (mPDF) technique as a powerful tool for studying short-range magnetism from neutron total-scattering data. We then provide a selection of examples of mPDF analysis applied to magnetic materials of recent technological and fundamental interest, including the antiferromagnetic semiconductor MnTe, geometrically frustrated magnets, and iron-oxide magnetic nanoparticles. The rapid development of mPDF analysis since its formalization a decade ago puts this technique in a strong position for making continued impact in the study of local magnetism in emerging materials.

The curious case of the structural phase transition in SnSe insights from neutron total scattering

At elevated temperatures SnSe is reported to undergo a structural transition from the low symmetry orthorhombic GeS-type to a higher symmetry orthorhombic TlI-type. Although increasing symmetry should likewise increase lattice thermal conductivity, many experiments on single crystals and polycrystalline materials indicate that this is not the case. Here we present temperature dependent analysis of time-of-flight (TOF) neutron total scattering data in combination with theoretical modeling to probe the local to long-range evolution of the structure. We report that while SnSe is well characterized on average within the high symmetry space group above the transition, over length scales of a few unit cells SnSe remains better characterized in the low symmetry GeS-type space group. Our finding from robust modeling provides further insight into the curious case of a dynamic order-disorder phase transition in SnSe, a model consistent with the soft-phonon picture of the high thermoelectric power above the phase transition.

Metal-Metal Bonding as an Electrode Design Principle in the Low-Strain Cluster Compound LiScMo3O8

Electrode materials for Li⁺-ion batteries require optimization along several disparate axes related to cost, performance, and sustainability. One of the important performance axes is the ability to retain structural integrity though cycles of charge/discharge. Metal-metal bonding is a distinct feature of some refractory metal oxides that has been largely underutilized in electrochemical energy storage, but that could potentially impact structural integrity. Here LiScMo₃O₈, a compound containing triangular clusters of metal-metal bonded Mo atoms, is studied as a potential anode material in Li⁺-ion batteries. Electrons inserted though lithiation are localized across rigid Mo₃ triangles (rather than on individual metal ions), resulting in minimal structural change as suggested by operando diffraction. The unusual chemical bonding allows this compound to be cycled with Mo atoms below a formally +4 valence state, resulting in an acceptable voltage regime that is appropriate for an anode material. Several characterization methods including potentiometric entropy measurements indicate two-phase regions, which are attributed through extensive first-principles modeling to Li⁺ ordering. This study of LiScMo₃O₈ provides valuable insights for design principles for structural motifs that stably and reversibly permit Li⁺ (de)insertion.

Learning from Correlations Based on Local Structure: Rare-Earth Nickelates Revisited

Statistical analysis of local atomic distortions in crystalline materials is a powerful tool for understanding coupled electronic and structural phase transitions in transition metal compounds. The analyses of such complex materials, however, often require significant domain knowledge to recognize limitations in the available data, whether it be experimentally reported crystal structures, property measurements, or computed quantities, and to understand when additional experiments or simulations may be necessary. Here we show how additional descriptive statistics and computational experiments can help researchers explicitly recognize these limitations and fill in missing gaps by constructing amplitude ( a) and normalized-amplitude ( n) distortion-mode property correlation-coefficient heat maps, aCCHMs and nCCHMs, respectively. We demonstrate this utility within the rare-earth nickelate perovskites RNiO₃ (R = rare earth ≠ La), which exhibit antiferromagnetic and metal-insulator transitions with crystallographic symmetry breaking, and analyze the CCHMs obtained from experimental and first-principles derived symmetry modes. In contrast with the crystallographic trends gleaned from the reported experimental structures, the equilibrium structures obtained from density functional theory indicate that the Jahn-Teller distortion mode plays a negligible role in affecting the Néel temperature. We explain this discrepancy and discuss how different researchers might draw disparate conclusions from the same evidence, in particular from aCCHMs and nCCHMs. Last, we propose a general method for utilizing CCHMs for screening large databases of structures.

Direct assignment of molecular vibrations via normal mode analysis of the neutron dynamic pair distribution function technique

For over a century, vibrational spectroscopy has enhanced the study of materials. Yet, assignment of particular molecular motions to vibrational excitations has relied on indirect methods. Here, we demonstrate that applying group theoretical methods to the dynamic pair distribution function analysis of neutron scattering data provides direct access to the individual atomic displacements responsible for these excitations. Applied to the molecule-based frustrated magnet with a potential magnetic valence-bond state, LiZn2Mo3O8, this approach allows direct assignment of the constrained rotational mode of Mo3O13 clusters and internal modes of MoO6 polyhedra. We anticipate that coupling this well known data analysis technique with dynamic pair distribution function analysis will have broad application in connecting structural dynamics to physical properties in a wide range of molecular and solid state systems.