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The prospect of creating ferroelectric or high permittivity nanomaterials provides motivation for investigating complex transition metal oxides of the form Ba(Ti, MV)O3, where M = Nb or Ta. Solid state processing typically produces mixtures of crystalline phases, rarely beyond minimally doped Nb/Ta. Using a modified sol-gel method, we prepared single phase nanocrystals of Ba(Ti, M)O3. Compositional and elemental analysis puts the empirical formulas close to BaTi0.5Nb0.5O3−δ and BaTi0.5Ta0.5O3−δ. For both materials, a reversible temperature dependent phase transition (non-centrosymmetric to symmetric) is observed in the Raman spectrum in the region 533–583 K (260–310 °C); for Ba(Ti, Nb)O3, the onset is at 543 K (270 °C); and for Ba(Ti, Ta)O3, the onset is at 533 K (260 °C), which are comparable with 390–393 K (117–120 °C) for bulk BaTiO3. The crystal structure was resolved by examination of the powder x-ray diffraction and atomic pair distribution function (PDF) analysis of synchrotron total scattering data. It was postulated whether the structure adopted at the nanoscale was single or double perovskite. Double perovskites (A2B′B″O6) are characterized by the type and extent of cation ordering, which gives rise to higher symmetry crystal structures. PDF analysis was used to examine all likely candidate structures and to look for evidence of higher symmetry. The feasible phase space that evolves includes the ordered double perovskite structure Ba2(Ti, MV)O6 (M = Nb, Ta) Fm-3m, a disordered cubic structure, as a suitable high temperature analog, Ba(Ti, MV)O3Pm-3m, and an orthorhombic Ba(Ti, MV)O3Amm2, a room temperature structure that presents an unusually high level of lattice displacement, possibly due to octahedral tilting, and indication of a highly polarized crystal.

 

Survival relies on the ability to flexibly choose between different actions according to varying environmental circumstances. Many lines of evidence indicate that action selection involves signaling in corticostriatal circuits, including the orbitofrontal cortex (OFC) and dorsomedial striatum (DMS). While choice-specific responses have been found in individual neurons from both areas, it is unclear whether populations of OFC or DMS neurons are better at encoding an animal’s choice. To address this, we trained head-fixed mice to perform an auditory guided two-alternative choice task, which required moving a joystick forward or backward. We then used silicon microprobes to simultaneously measure the spiking activity of OFC and DMS ensembles, allowing us to directly compare population dynamics between these areas within the same animals. Consistent with previous literature, both areas contained neurons that were selective for specific stimulus-action associations. However, analysis of concurrently recorded ensemble activity revealed that the animal’s trial-by-trial behavior could be decoded more accurately from DMS dynamics. These results reveal substantial regional differences in encoding action selection, suggesting that DMS neural dynamics are more specialized than OFC at representing an animal’s choice of action. NEW & NOTEWORTHY While previous literature shows that both orbitofrontal cortex (OFC) and dorsomedial striatum (DMS) represent information relevant to selecting specific actions, few studies have directly compared neural signals between these areas. Here we compared OFC and DMS dynamics in mice performing a two-alternative choice task. We found that the animal’s choice could be decoded more accurately from DMS population activity. This work provides among the first evidence that OFC and DMS differentially represent information about an animal’s selected action. 

Mesoscale climate models provide indispensable tools to understand land‐atmosphere interactions over urban regions. However, uncertainties in urban canopy parameters (UCPs) and parameterization schemes lead to degraded representation of the drag effect in complex built terrains. In particular, for the widely applied single‐layer urban canopy model (SLUCM) coupled with the Weather Research and Forecasting (WRF) model, near‐surface horizontal wind speed is known to be overestimated systematically. In this study, idealized large eddy simulations (LES) and WRF‐SLUCM simulations are conducted to study the separate effect of UCPs and aerodynamic parameterization on atmospheric boundary layer processes and rainfall variabilities in Phoenix, Arizona. For LES that explicitly resolves surface geometry, significant differences between three‐dimensional (3D) versus two‐dimensional (2D) representation of urban morphology are found in the surface layer and above. When surface drag is parameterized following SLUCM, surface morphologies have little impacts on the mean momentum transfer. WRF‐SLUCM simulation results, incorporated with 3D urban morphology data, indicate that simply refining the frontal area index will reduce the surface drag, which further amplifies the systematic positive bias of SLUCM in predicting horizontal wind speed. Replacing the drag parameterization in SLUCM by LES‐based aerodynamic parameters has evident impacts on near‐surface wind speed. The impact of urban roughness representation becomes the most evident during rainfall periods, due to the important role of surface drag in dictating moisture convergence. Our study underlines that apart from intensive efforts in obtaining detailed UCPs, it is also critical to enhance the urban momentum exchange parameterization schemes.

 

Using Pair Distribution Function (PDF) analysis of in situ total scattering data, we investigate the formation of tungsten and niobium oxides in a simple solvothermal synthesis. We use Pearson Correlation Coefficient (PCC) analysis of the time resolved PDFs to both map the structural changes taking place throughout the synthesis and identify structural models for precursor and product through PCC‐based structure mining. Our analysis first shows that ultra‐small tungsten and niobium oxide nanoparticles form instantaneously upon heating, with sizes between 1.5 and 2 nm. We show that the main structural motifs in the nanoparticles can be described with structures containing pentagonal columns, which is characteristic for many bulk tungsten and niobium oxides. We furthermore elucidate the structure of the precursor complex as clusters of octahedra with O‐ and Cl‐ligands. The PCC based methodology automates the structure characterization and proves useful for analysis of large datasets of for example, time resolved X‐ray scattering studies. The PCC is implemented in ‘PDF in the cloud’, a web platform for PDF analysis.