Control of zeolite microenvironment for propene synthesis from methanol

Optimising the balance between propene selectivity, propene/ethene ratio and catalytic stability and unravelling the explicit mechanism on formation of the first carbon–carbon bond are challenging goals of great importance in state-of-the-art methanol-to-olefin (MTO) research. We report a strategy to finely control the nature of active sites within the pores of commercial MFI-zeolites by incorporating tantalum(V) and aluminium(III) centres into the framework. The resultant TaAlS-1 zeolite exhibits simultaneously remarkable propene selectivity (51%), propene/ethene ratio (8.3) and catalytic stability (>50 h) at full methanol conversion. In situ synchrotron X-ray powder diffraction, X-ray absorption spectroscopy and inelastic neutron scattering coupled with DFT calculations reveal that the first carbon–carbon bond is formed between an activated methanol molecule and a trimethyloxonium intermediate. The unprecedented cooperativity between tantalum(V) and Brønsted acid sites creates an optimal microenvironment for efficient conversion of methanol and thus greatly promotes the application of zeolites in the sustainable manufacturing of light olefins.We thank EPSRC (EP/P011632/1), the Royal Society, National Natural Science Foundation of China (21733011, 21890761, 21673076), and the University of Manchester for funding. We thank EPSRC for funding and the EPSRC National Service for EPR Spectroscopy at Manchester. A.M.S. is supported by a Royal Society Newton International Fellowship. We are grateful to the STFC/ISIS Facility, Oak Ridge National Laboratory (ORNL) and Diamond Light Source (DLS) for access to the beamlines TOSCA/MAPS, VISION and I11/I20, respectively. We acknowledge Dr. L. Keenan for help at I20 beamline (SP23594-1). UK Catalysis Hub is kindly thanked for resources and support provided via our membership of the UK Catalysis Hub Consortium and funded by EPSRC grant: EP/R026939/1, EP/R026815/1, EP/R026645/1, EP/R027129/1 or EP/M013219/1 (biocatalysis). We acknowledge the support of The University of Manchester’s Dalton Cumbrian Facility (DCF), a partner in the National Nuclear User Facility, the EPSRC UK National Ion Beam Centre and the Henry Royce Institute. We recognise Dr. R. Edge and Dr. K. Warren for their assistance during the 60Co γ-irradiation processes. We thank Prof. A. Jentys from the Technical University of Munich for the measurement of the INS spectrum of iso-butene. We thank C. Webb, E. Enston and G. Smith for help with GC–MS; Dr. L. Hughes for help with SEM and EDX; M. Kibble for help at TOSCA/MAPS beamlines. Computing resources (time on the SCARF compute cluster for some of the CASTEP calculations) was provided by STFC’s e-Science facility. A portion of this research used resources at the Spallation Neutron Source, a DOE Office of Science User Facility operated by ORNL. The computing resources at ORNL were made available through the VirtuES and the ICE-MAN projects, funded by Laboratory Directed Research and Development programme and Compute and Data Environment for Science (CADES

A Double Evolutionary Learning Moth-Flame Optimization for Real-parameter Global Optimization Problems

The original moth-flame optimization (MFO) algorithm neither generates high-performance flames, nor utilizes the flames to offer enough effective search guidance for moths in solution spaces, causing the degeneration of the global search capability and convergence speed in confronting complicated problems. To overwhelm those imperfections, this paper proposes a double evolutionary learning MFO algorithm (DELMFO), where two different evolutionary learning strategies, namely the differential evolution flame generation (DEFG) and dynamic flame guidance (DFG) strategy, are presented to generate high-performance flames and dynamically guide the search of moths, respectively. By constructing the cascading collaboration between DEFG and DFG, DELMFO offers a positive feedback channel that makes the personal best historical solutions (PBHSs), flames, and moths promote each other. This improves the global search capability and accelerates convergence speed. DELMFO is compared with six MFO algorithms and nine popular stochastic optimization algorithms on the CEC2013 test suite. Furthermore, DELMFO also is further compared with the ten stochastic optimization algorithms on the CEC2017 test suite. Experimental results show that DELMFO obtains the competitive performance on the global search capability, convergence speed, and scalability among all the algorithms

Control of zeolite microenvironment for propene synthesis from methanol

Lower olefins are mainly produced from fossil resources and the methanol-to-olefins process offers a new sustainable pathway. Here, the authors show a new zeolite containing tantalum and aluminium centres which shows simultaneously high propene selectivity, catalytic activity, and stability for the synthesis of propene