Single-atom catalysts have attracted attention because of improved atom efficiency, higher reactivity, and better selectivity. A major challenge is to achieve high surface concentrations while preventing these atoms from agglomeration at elevated temperatures. Here we investigate the formation of Pt single atoms on an industrial catalyst support. Using a combination of surface sensitive techniques such as XPS and LEIS, X-ray absorption spectroscopy, electron microscopy, as well as density functional theory, we demonstrate that cerium oxide can support Pt single atoms at high metal loading (3 wt % Pt), without forming any clusters or 3D aggregates when heated in air at 800 °C. The mechanism of trapping involves a reaction of the mobile PtO2 with under-coordinated cerium cations present at CeO2(111) step edges, allowing Pt to achieve a stable square planar configuration. The strong interaction of mobile single-atom species with the support, present during catalyst sintering and regeneration, helps explain the sinter resistance of ceria-supported metal catalysts.

We apply the holonomic gradient method introduced by Nakayama et al. [23] to the evaluation of the exact distribution function of the largest root of a Wishart matrix, which involves a hypergeometric function 1 F 1 of a matrix argument. Numerical evaluation of the hypergeometric function has been one of the longstanding problems in multivariate distribution theory. The holonomic gradient method offers a totally new approach, which is complementary to the infinite series expansion around the origin in terms of zonal polynomials. It allows us to move away from the origin by the use of partial differential equations satisfied by the hypergeometric function. From numerical viewpoint we show that the method works well up to dimension 10. From theoretical viewpoint the method offers many challenging problems both to statistics and D-module theory., where 0 ≤ n 1 , . . . , n m ≤ 2 and at most one of n 1 , . . . , n m is two. Denote [m] = {1, . . . , m}. For a subset J ⊂ [m] denote

Tailoring the specific stacking sequence (polytypes) of layered materials represents a powerful strategy to identify and design novel physical properties. While nanostructures built upon transition‐metal dichalcogenides (TMDs) with either the 2H or 3R crystalline phases have been routinely studied, knowledge of TMD nanomaterials based on mixed 2H/3R polytypes is far more limited. In this work, mixed 2H/3R free‐standing WS2 nanostructures displaying a flower‐like configuration are fingerprinted by means of state‐of‐the‐art transmission electron microscopy. Their rich variety of shape‐morphology configurations is correlated with relevant local electronic properties such as edge, surface, and bulk plasmons. Machine learning is deployed to establish that the 2H/3R polytype displays an indirect band gap of EnormalBG=1.6−0.2+0.3eV. Further, high resolution electron energy‐loss spectroscopy reveals energy‐gain peaks exhibiting a gain‐to‐loss ratio greater than unity, a property that can be exploited for cooling strategies of atomically‐thin TMD nanostructures and devices built upon them. The findings of this work represent a stepping stone towards an improved understanding of TMD nanomaterials based on mixed crystalline phases.

We have investigated the effects of deposition temperature and post-annealing on the passivation performance of AlOx films deposited by O3-based atomic layer deposition for crystalline Si. We found that the dramatic enhancement in the passivation performance of room-temperature deposited AlOx films by post-annealing is due to the phase transformation of aluminum silicate to mullite in an AlOx interlayer and the resulting self-aligned AlOx/SiOx interface. This result is interesting for the fabrication of high-performance silicon solar cells with AlOx passivation layers.