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The L-edge X-ray Absorption Near Edge Structure (XANES) is widely used in the characterization of transition metal compounds. Here, we report the development of a database of computed L-edge XANES using the multiple scattering theory-based FEFF9 code. The initial release of the database contains more than 140,000 L-edge spectra for more than 22,000 structures generated using a high-throughput computational workflow. The data is disseminated through the Materials Project and addresses a critical need for L-edge XANES spectra among the research community.

 

Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for obtaining precise information about the local bonding of materials, but difficult to interpret without a well-vetted dataset of reference spectra. The ability to predict NMR parameters and connect them to three-dimensional local environments is critical for understanding more complex, long-range interactions. New computational methods have revealed structural information available from²⁹Si solid-state NMR by generating computed reference spectra for solids. Such predictions are useful for the identification of new silicon-containing compounds, and serve as a starting point for determination of the local environments present in amorphous structures. In this study, we have used 42 silicon sites as a benchmarking set to compare experimentally reported²⁹Si solid-state NMR spectra with those computed by CASTEP-NMR and Vienna Ab Initio Simulation Program (VASP). Data-driven approaches enable us to identify the source of discrepancies across a range of experimental and computational results. The information from NMR (in the form of an NMR tensor) has been validated, and in some cases corrected, in an effort to catalog these for the local spectroscopy database infrastructure (LSDI), where over 10,000²⁹Si NMR tensors for crystalline materials have been computed. Knowledge of specific tensor values can serve as the basis for executing NMR experiments with precision, optimizing conditions to capture the elements accurately. The ability to predict and compare experimental observables from a wide range of structures can aid researchers in their chemical assignments and structure determination, since the computed values enables the extension beyond tables of typical chemical shift (or shielding) ranges.

 

Solid‐state NMR measurements coupled with density functional theory (DFT) calculations demonstrate how hydrogen positions can be refined in a crystalline system. The precision afforded by rotational‐echo double‐resonance (REDOR) NMR to interrogate¹³C–¹H distances is exploited along with DFT determinations of the¹³C tensor of carbonates (CO₃²⁻). Nearby¹H nuclei perturb the axial symmetry of the carbonate sites in the hydrated carbonate mineral, hydromagnesite [4 MgCO₃⋅Mg(OH)₂⋅4 H₂O]. A match between the calculated structure and solid‐state NMR was found by testing multiple semi‐local and dispersion‐corrected DFT functionals and applying them to optimize atom positions, starting from X‐ray diffraction (XRD)‐determined atomic coordinates. This was validated by comparing calculated to experimental¹³C{¹H} REDOR and¹³C chemical shift anisotropy (CSA) tensor values. The results show that the combination of solid‐state NMR, XRD, and DFT can improve structure refinement for hydrated materials.

 

Nonthermal plasma (NTP) offers a unique synthesis environment capable of producing nanocrystals of high melting point materials at relatively low gas temperatures. Despite the rapidly growing material library accessible through NTP synthesis, designing processes for new materials is predominantly empirically driven. Here, we report on the synthesis of both amorphous alumina and γ-Al 2 O 3 nanocrystals and present a simple particle heating model that is suitable for predicting the plasma power necessary for crystallization. The heating model only requires the composition, temperature, and pressure of the background gas along with the reactor geometry to calculate the temperature of particles suspended in the plasma as a function of applied power. Complete crystallization of the nanoparticle population was observed when applied power was greater than the threshold where the calculated particle temperature is equal to the crystallization temperature of amorphous alumina.