Direct synthesis of hydrogen peroxide over Pd nanoparticles embedded between HZSM-5 nanosheets layers

Direct synthesis of hydrogen peroxide(DSHP)was studied over Pd loaded on HZSM-5 nanosheets(Pd/ZN).Pd nanoparticles with average size of ca.4.3 nm were introduced into the adjacent nanosheet layers(thickness of ca.2.9 nm)by impregnation method.Pd/ZN with theoretical Si/Al molar ratio of 25 showed the highest selectivity for H2O2 among the prepared catalysts,together with highest formation rate of H2O2(38.0 mmol·(g cat)^-1·h^-1),1.9 times than that of Pd supported on conventional HZSM-5 zeolite(Pd/CZ-50).Better catalytic performance of nanosheet catalysts was attributed to the promoted Pd dispersion which promoted H2 dissociation,more BrΦnsted acid sites and stronger metal-support interaction which inhibited the dissociation of O-O bond in H2O2.The embedded structure sufficiently protected the Pd nanoparticles by space confinement which restrained the Pd leaching,leading to a better catalytic stability with 90%activity retained after 3 cycles,which was almost 3 times than that of Pd/CZ-50(30.4%activity retained).

Controllably tailoring external surface sites of nanosheet HZSM-5 for maximizing light olefins in catalytic cracking of n-decane

A series of triphenylethoxysilane(TPEOS)-modified nanosheet HZSM-5 catalysts(ZN-x,x=4%,8%and16%,mass)were synthesized by chemical liquid deposition to selectively change external acidity distributions.TPEOS modification was found to passivate some external Br?nsted and Lewis acid sites by37.8%,in which Br?nsted acid sites(BAS)were found more easily sacrificed by breaking the surface Al AO bond of bridging hydroxyl groups and forming Si AOASi bonds.The selectivity of ZN-8 catalyst for light olefins(ethylene,propylene and butene)in n-decane catalytic cracking is up to 26%(450℃,WHSV=10.95 h^(-1)),which is ca.78%higher than that of parent one.The better performance was attributed to the appropriate external acid density in ZN-8,which inhibits bimolecular hydrogen transfer reaction of light olefins on the adjacent acid sites,resulting in more olefins,few coke precursors and thus an excellent catalytic stability.

Role of Ni species in ZnO supported on Silicalite-1 for efficient propane dehydrogenation

Propane dehydrogenation(PDH)is one of the most effective technologies to produce propene.Non-noble zinc-based catalysts have paid increasing attention because of low cost and nontoxic,compared with industrial Pt and Cr-based catalysts.However,they often suffer from limited catalytic activity and poor stability.Here,we introduced moderate Ni into ZnO supported Silicalite-1 zeolite to increase catalytic activity and stability simultaneously.Zn^(2+) was the definite active site and NiZn alloy facilitated the sluggish H recombination into H_(2)via reverse spillover.Furthermore,the introduction of Ni increased Lewis acid strength caused by electron transfer from ZnO to NiZn alloy,contributing to improved stability.For resulted 0.5 NiZn/S-1,propene formation rate was 0.18 mol C_(3)H_(6)·(g Zn)^(-1)·h^(-1) at 550℃,which was above 1.5 times higher than that over Zn/S-1 without Ni.Under stability test,the deactivation of0.5 NiZn/S-1 was 0.019 h^(-1),which was only 1/10 of that over Zn/S-1.

Disorder induced phase transition in magnetic higher-order topological insulator: A machine learning study

Previous studies presented the phase diagram induced by the disorder existing separately either in the higher-order topological states or in the topological trivial states, respectively. However, the influence of disorder on the system with the coexistence of the higher-order topological states and other traditional topological states has not been investigated. In this paper, we investigate the disorder induced phase transition in the magnetic higher-order topological insulator. By using the convolutional neural network and non-commutative geometry methods, two independent phase diagrams are calculated.With the comparison between these two diagrams, a topological transition from the normal insulator to the Chern insulator is confirmed. Furthermore, the network based on eigenstate wavefunction studies also presents a transition between the higher-order topological insulator and the Chern insulator.

Multi-Owner Keyword Search over Shared Data without Secure Channels in the Cloud

Searchable encryption allows cloud users to outsource the massive encrypted data to the remote cloud and to search over the data without revealing the sensitive information. Many schemes have been proposed to support the keyword search in a public cloud. However,they have some potential limitations. First,most of the existing schemes only consider the scenario with the single data owner. Second,they need secure channels to guarantee the secure transmission of secret keys from the data owner to data users. Third,in some schemes,the data owner should be online to help data users when data users intend to perform the search,which is inconvenient.In this paper,we propose a novel searchable scheme which supports the multi-owner keyword search without secure channels. More than that,our scheme is a non-interactive solution,in which all the users only need to communicate with the cloud server. Furthermore,the analysis proves that our scheme can guarantee the security even without secure channels. Unlike most existing public key encryption based searchable schemes,we evaluate the performance of our scheme,which shows that our scheme is practical.

Adaptive Linearized Alternating Direction Method of Multipliers for Non-Convex Compositely Regularized Optimization Problems

We consider a wide range of non-convex regularized minimization problems, where the non-convex regularization term is composite with a linear function engaged in sparse learning. Recent theoretical investigations have demonstrated their superiority over their convex counterparts. The computational challenge lies in the fact that the proximal mapping associated with non-convex regularization is not easily obtained due to the imposed linear composition. Fortunately, the problem structure allows one to introduce an auxiliary variable and reformulate it as an optimization problem with linear constraints, which can be solved using the Linearized Alternating Direction Method of Multipliers （LADMM）. Despite the success of LADMM in practice, it remains unknown whether LADMM is convergent in solving such non-convex compositely regularized optimizations. In this research, we first present a detailed convergence analysis of the LADMM algorithm for solving a non-convex compositely regularized optimization problem with a large class of non-convex penalties. Furthermore, we propose an Adaptive LADMM （AdaLADMM） algorithm with a line-search criterion. Experimental results on different genres of datasets validate the efficacy of the proposed algorithm.

Direct synthesis of hydrogen peroxide on Pd nanosheets with edge decorated by Au nanoparticles

Direct synthesis of hydrogen peroxide from hydrogen and oxide(DSHP)is considered as a green pathway for H2O2 production because of the simple reaction route and 100%theoretical atom efficiency.Here,1.5 wt%Pd and 0.5 wt%Au were loaded on HZSM-5 nanosheets through sequential isovolumetric impregnation.TEM images and CO-TPD curves showed that Pd nanosheets were successfully synthesized between HZSM-5 nanosheets under zeolite confinement effect,and Au particles were loaded on the edge of Pd nanosheets and formed a structure that Pd nanosheets with edge decorated by Au nanoparticles(Au–Pd/ZN).The results showed that the selectivity for H2O2 could be reached around 60%in a 30 min reaction and the initial H2O2 productivity could reach 338.5 mmol gcat1 h1 on the Au–Pd/ZN catalyst.The enhanced selectivity and productivity could be related with high content of terrace sites and Au particles on the step sites of bimetallic nanosheets,in which both the terrace sites and the step sites replaced by Au particles showed higher dissociation activation energy for breaking the O–O bond than traditional step sites on Pd particles,inhibited the by-product reactions(2H2O2→2H2OþO2,2H2þO2→2H2O).