Direct structural identification of carbenium ions and investigation of host-guest interaction in the methanol to olefins reaction obtained by multinuclear NMR correlations

Probing and determining the intermediates formed during catalytic reactions in heterogeneous catalysis are strong challenges. Using C-13 labelling and two dimensional C-13-C-13 through-bond NMR correlations, we directly reveal the structures of a range of carbenium ion species formed during the conversion of methanol to olefins on acidic H-ZSM-5 zeolite by mapping the carbon-carbon bond connectivities. Additionally, we use C-13-Al-27 and Si-29-C-13 through-space NMR experiments to probe the interactions between the confined carbon species (including carbenium ions) and the framework of the zeolite, which quantitatively provide an estimate for the carbon-aluminium and carbon-silicon distances, respectively

MiLMo:Minority Multilingual Pre-trained Language Model

Pre-trained language models are trained on large-scale unsupervised data, and they can fine-turn the model only on small-scale labeled datasets, and achieve good results. Multilingual pre-trained language models can be trained on multiple languages, and the model can understand multiple languages at the same time. At present, the search on pre-trained models mainly focuses on rich resources, while there is relatively little research on low-resource languages such as minority languages, and the public multilingual pre-trained language model can not work well for minority languages. Therefore, this paper constructs a multilingual pre-trained model named MiLMo that performs better on minority language tasks, including Mongolian, Tibetan, Uyghur, Kazakh and Korean. To solve the problem of scarcity of datasets on minority languages and verify the effectiveness of the MiLMo model, this paper constructs a minority multilingual text classification dataset named MiTC, and trains a word2vec model for each language. By comparing the word2vec model and the pre-trained model in the text classification task, this paper provides an optimal scheme for the downstream task research of minority languages. The final experimental results show that the performance of the pre-trained model is better than that of the word2vec model, and it has achieved the best results in minority multilingual text classification. The multilingual pre-trained model MiLMo, multilingual word2vec model and multilingual text classification dataset MiTC are published on http://milmo.cmli-nlp.com/

Enhanced oxidation resistance of active nanostructures via dynamic size effect.

A major challenge limiting the practical applications of nanomaterials is that the activities of nanostructures (NSs) increase with reduced size, often sacrificing their stability in the chemical environment. Under oxidative conditions, NSs with smaller sizes and higher defect densities are commonly expected to oxidize more easily, since high-concentration defects can facilitate oxidation by enhancing the reactivity with O2 and providing a fast channel for oxygen incorporation. Here, using FeO NSs as an example, we show to the contrary, that reducing the size of active NSs can drastically increase their oxidation resistance. A maximum oxidation resistance is found for FeO NSs with dimensions below 3.2 nm. Rather than being determined by the structure or electronic properties of active sites, the enhanced oxidation resistance originates from the size-dependent structural dynamics of FeO NSs in O2. We find this dynamic size effect to govern the chemical properties of active NSs

Identification of different carbenium ion intermediates in zeolites with identical chabazite topology via(13)C-C-13 through-bond NMR correlations

C-13-C-13 through-bond NMR correlation experiments reveal the stabilization of different carbenium ion intermediates in two zeolites possessing identical CHA topology (H-SAPO-34 and H-SSZ-13) during the methanol to olefins reaction

Creation of Brønsted acid sites on Sn-based solid catalysts for the conversion of biomass

Hydroxyl-attached Sn species are highly dispersed on the surface of mesoporous silica (SBA-15) by the grafting of dimethyldichlorostannane followed by calcination to transform the methyl groups into hydroxyl groups (S–Sn–OH). S–Sn–OH has both Lewis and Brønsted acidic sites, resulting in superior catalytic activities in the acetalisation of glycerol

Fast detection and structural identification of carbocations on zeolites by dynamic nuclear polarization enhanced solid-state NMR

Acidic zeolites are porous aluminosilicates used in a wide range of industrial processes such as adsorption and catalysis. The formation of carbocation intermediates plays a key role in reactivity, selectivity and deactivation in heterogeneous catalytic processes. However, the observation and determination of carbocations remain a significant challenge in heterogeneous catalysis due to the lack of selective techniques of sufficient sensitivity to detect their low concentrations. Here, we combine 13C isotopic enrichment and efficient dynamic nuclear polarization magic angle spinning nuclear magnetic resonance spectroscopy to detect carbocations in zeolites. We use two dimensional 13C–13C through-bond correlations to establish their structures and 29Si–13C through-space experiments to quantitatively probe the interaction between multiple surface sites of the zeolites and the confined hydrocarbon pool species. We show that a range of various membered ring carbocations are intermediates in the methanol to hydrocarbons reaction catalysed by different microstructural β-zeolites and highlight that different reaction routes for the formation of both targeted hydrocarbon products and coke exist. These species have strong van der Waals interaction with the zeolite framework demonstrating that their accumulation in the channels of the zeolites leads to deactivation. These results enable understanding of deactivation pathways and open up opportunities for the design of catalysts with improved performances

Rational approach to guest confinement inside MOF cavities for low-temperature catalysis.

Geometric or electronic confinement of guests inside nanoporous hosts promises to deliver unusual catalytic or opto-electronic functionality from existing materials but is challenging to obtain particularly using metastable hosts, such as metal-organic frameworks (MOFs). Reagents (e.g. precursor) may be too large for impregnation and synthesis conditions may also destroy the hosts. Here we use thermodynamic Pourbaix diagrams (favorable redox and pH conditions) to describe a general method for metal-compound guest synthesis by rationally selecting reaction agents and conditions. Specifically we demonstrate a MOF-confined RuO2 catalyst (RuO2@MOF-808-P) with exceptionally high catalytic CO oxidation below 150 °C as compared to the conventionally made SiO2-supported RuO2 (RuO2/SiO2). This can be caused by weaker interactions between CO/O and the MOF-encapsulated RuO2 surface thus avoiding adsorption-induced catalytic surface passivation. We further describe applications of the Pourbaix-enabled guest synthesis (PEGS) strategy with tutorial examples for the general synthesis of arbitrary guests (e.g. metals, oxides, hydroxides, sulfides).EPSRC Centre for Doctoral Training in Sensor Technologies and Applications (EP/L015889/1)； EPSRC Centre for Doctoral Training in Sensor Technologies and Applications (1566990)； EPSRC grants (EP/L011700/1); EPSRC grants (EP/N004272/1); Isaac Newton Trust [Minute 13.38(k)]; European Research Council (ERC) EMATTER (# 280078)； National Natural Science Foundation of China (No. 21688102); National Natural Science Foundation of China (No. 21825203); Ministry of Science and Technology of China (No. 2016YFA0200200); Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDB17020000); Ras Al Khaimah Center for Advanced Materials (RAK-CAM); China Scholarship Council (CSC)