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Unlike conventional aluminosilicate zeolites synthesized in alkaline media, aluminophosphate molecular sieves (AlPOs) have always been prepared under acidic conditions in the past three decades; this has been regarded as one of essential factors for synthesis, except for the case of silica‐substituted analogues (SAPOs). For the first time, we demonstrate herein a simple and generalized route for synthesizing various types of aluminophosphate molecular sieves in alkaline media. A series of aluminophosphate sieves and their analogues have been prepared with different quaternary ammonium cations as structure‐directing agents in this manner. The above successes have extended the systematic media from acidic or neutral to alkaline for the preparation of a series of aluminophosphate molecular sieves, which possibly open an alternative route for the synthesis of aluminophosphate molecular sieves. [ABSTRACT FROM AUTHOR]

The 31P chemical shift anisotropy (CSA) offers a potential source of new information to help determine the structures of aluminophosphate (AlPO) framework materials. We investigate how to measure the CSAs, which are small (span of ~20–30 ppm) for AlPOs, demonstrating the need for CSA‐amplification experiments (often in conjunction with 27Al and/or 1H decoupling) at high magnetic field (20.0 T) to obtain accurate values. We show that the most shielded component of the chemical shift tensor, δ33, is related to the length of the shortest P─O bond, whereas the more deshielded components, δ11 and δ22 can be related more readily to the mean P─O bond lengths and P─O─Al angles. Using the case of Mg‐doped STA‐2 as an example, the CSA is shown to be much larger for P(OAl)4–n(OMg)n environments, primarily owing to a much shorter P─O(Mg) bond affecting δ33, however, because the mean P─O bond lengths and P─O─T (T = Al, Mg) bond angles do not change significantly between P(OAl)4 and P(OAl)4–n(OMg)n sites, the isotropic chemical shifts for these species are similar, leading to overlapped spectral lines. When the CSA information is included, spectral assignment becomes unambiguous, therefore, although the specialist conditions required might preclude the routine measurement of 31P CSAs in AlPOs, in some cases (particularly doped materials), the experiments can still provide valuable additional information for spectral assignment. [ABSTRACT FROM AUTHOR]

Feature selection has been regarded as an effective tool to help researchers understand the generating process of data. For mining the synthesis mechanism of microporous AlPOs, this paper proposes a novel feature selection method by joint l2,1 norm and Fisher discrimination constraints (JNFDC). In order to obtain more effective feature subset, the proposed method can be achieved in two steps. The first step is to rank the features according to sparse and discriminative constraints. The second step is to establish predictive model with the ranked features, and select the most significant features in the light of the contribution of improving the predictive accuracy. To the best of our knowledge, JNFDC is the first work which employs the sparse representation theory to explore the synthesis mechanism of six kinds of pore rings. Numerical simulations demonstrate that our proposed method can select significant features affecting the specified structural property and improve the predictive accuracy. Moreover, comparison results show that JNFDC can obtain better predictive performances than some other state-of-the-art feature selection methods. [ABSTRACT FROM AUTHOR]

The relationship between synthetic factors and the resulting structures is critical for rational synthesis of zeolites and related microporous materials. In this paper, we develop a new feature selection method for synthetic factor analysis of (6,12)-ring-containing microporous aluminophosphates (AlPOs). The proposed method is based on a maximum weight and minimum redundancy criterion. With the proposed method, we can select the feature subset in which the features are most relevant to the synthetic structure while the redundancy among these selected features is minimal. Based on the database of AlPO synthesis, we use (6,12)-ring-containing AlPOs as the target class and incorporate 21 synthetic factors including gel composition, solvent and organic template to predict the formation of (6,12)-ring-containing microporous aluminophosphates (AlPOs). From these 21 features, 12 selected features are deemed as the optimized features to distinguish (6,12)-ring-containing AlPOs from other AlPOs without such rings. The prediction model achieves a classification accuracy rate of 91.12% using the optimal feature subset. Comprehensive experiments demonstrate the effectiveness of the proposed algorithm, and deep analysis is given for the synthetic factors selected by the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: A series of aluminumphosphate molecular sieves supported platinum–cobalt catalysts were prepared and tested for the preferential oxidation of CO in H2-rich gases. The catalysts were characterized by XRD, HRTEM, EDX, TPR and XPS techniques. The optimized catalysts were highly active and selective, CO could be purified below 10ppm in the reaction temperature range of 110°C–125°C under 1% CO, 1% O2, 12.5% CO2, 15% H2O, 50% H2 in volume and N2 balance at the space velocity of 24,000mLgcat −1 h−1 . Pt–Co/CoAPO-5 exhibited the best catalytic performance and Pt–Co/AlPO-5 was the most active catalyst at low reaction temperature, in which particles of Pt–Co alloy were formed and the particles were highly dispersed on the surface of the support. The high activity could be attributed to the Pt–Co nano-partilces with small sizes. The enlarged temperature window for CO purification should be ascribed to the loaded cobalt oxide. Substitution of cobalt ions for aluminium ions has obvious influence on the interaction between the support and platinum/cobalt species. [Copyright &y& Elsevier]

Abstract: The hydrogen adsorption simulations were carried for several model AlPOs (VPI-5, AlPO-5, AlPO-11 and AlPO-25) employing the Grand Canonical Monte Carlo (GCMC) simulations at 77K to investigate the effect of pore size and the pore volume on the hydrogen uptake. The adsorption capacity showed no relationship with the pore size, surface area and micropore volume of AlPOs. However, the adsorption capacity per unit micropore volume increased as the pore size decreases. The heat of adsorption also increased as the pore size decreases. For all model AlPOs, the hydrogen exists homogeneously near the oxygen atoms in the framework. [Copyright &y& Elsevier]

Large pore aluminophosphate-based molecular sieves like AlPO-5, MAPO-5, MnAPO-5 and ZAPO-5 were synthesised hydrothermally using triethylamine as a structure directing agent. These materials were characterised by X-ray diffraction (XRD),A1 andP MAS-NMR, ICP-MS, n-butylamine-TPD, BET and SEM. The catalytic performance of these materials was tested for isopropylation of benzene with 2-propanol at 250, 300, 350 and 400°C. The products were cumene, p-DIPB ( p-diisopropylbenzene) and m-DIPB ( m-diisopropylbenzene). MnAPO-5 was found to be more active than the other catalysts. Maximum conversion (20%) was noted at 350°C over MnAPO-5. The selectivity to DIPB was found to decrease with time on stream but the selectivity to cumene showed an increase after 3 h of time on stream [ABSTRACT FROM AUTHOR]

We present a thorough computational study of transition metal-doped zeolite and aluminophosphate (AlPO) frameworks. The structural and electronic chemistry of the dopants is examined with ab initio quantum mechanical calculations, and the results correlated with the Brønsted and Lewis acid strength, and with the redox potential of the dopant ions in the framework. The energetics of doping is provided, and is employed to analyze the mode of dopant incorporation, and its site ordering in the microporous framework. In total, 23 dopant ions are examined in the isostructural framework of chabasite and AlPO-34. These cover most of the isomorphous framework replacements known to occur experimentally, but also framework replacements that have not yet been achieved. In this case, ab initio modeling techniques are employed in a predictive way. Finally, we present a computational study of the alkene epoxidation on titanosilicates, that covers the whole catalytic cycle. [Copyright &y& Elsevier]

Medium pore aluminophosphate-based molecular sieves like AlPO-41, CoAPO-41, CoAPSO-41 and MnAPSO-41 have been synthesised hydrothermally using dipropylamine as the organic template. These materials have been characterised by various physical methods including X-ray powder diffraction (XRD), thermogravimetric analyses (TGA), FT-IR, ESR and scanning electron microscope (SEM). All these materials are found to be crystalline and do not contain any detectable impure phases. The catalytic performance of these materials has been examined for ethylation of ethylbenzene with ethanol at 250, 300, 350, 400 and 450 °C. Ethylbenzene conversion is observed to increase with increase in temperature with the maximum conversion at 400 °C. The major product is 1,4-diethylbenzene whose selectivity decreases with increase in temperature over all the catalysts. High temperature is favourable for the formation of 1,3-diethylbenzene which is thermodynamically more stable than the other products. Influence of feed ratio on conversion and products selectivity is examined and the results are discussed in this paper. [Copyright &y& Elsevier]

A survey is given of the catalytic methods potentially available for the production of adipic acid by the oxidation of readily available hydrocarbon precursors under environmentally benign conditions. Encouraging results are reported using H2O2 as oxidant and microporous FeAlPO-5 as catalyst at moderate temperatures. [ABSTRACT FROM AUTHOR]

The 31 P chemical shift anisotropy (CSA) offers a potential source of new information to help determine the structures of aluminophosphate (AlPO) framework materials. We investigate how to measure the CSAs, which are small (span of ~20-30 ppm) for AlPOs, demonstrating the need for CSA-amplification experiments (often in conjunction with 27 Al and/or 1 H decoupling) at high magnetic field (20.0 T) to obtain accurate values. We show that the most shielded component of the chemical shift tensor, δ 33 , is related to the length of the shortest P─O bond, whereas the more deshielded components, δ 11 and δ 22 can be related more readily to the mean P─O bond lengths and P─O─Al angles. Using the case of Mg-doped STA-2 as an example, the CSA is shown to be much larger for P(OAl) 4-n (OMg) n environments, primarily owing to a much shorter P─O(Mg) bond affecting δ 33 , however, because the mean P─O bond lengths and P─O─T (T = Al, Mg) bond angles do not change significantly between P(OAl) 4 and P(OAl) 4-n (OMg) n sites, the isotropic chemical shifts for these species are similar, leading to overlapped spectral lines. When the CSA information is included, spectral assignment becomes unambiguous, therefore, although the specialist conditions required might preclude the routine measurement of 31 P CSAs in AlPOs, in some cases (particularly doped materials), the experiments can still provide valuable additional information for spectral assignment., (© 2018 John Wiley & Sons, Ltd.)

Feature selection has been regarded as an effective tool to help researchers understand the generating process of data. For mining the synthesis mechanism of microporous AlPOs, this paper proposes a novel feature selection method by joint l 2,1 norm and Fisher discrimination constraints (JNFDC). In order to obtain more effective feature subset, the proposed method can be achieved in two steps. The first step is to rank the features according to sparse and discriminative constraints. The second step is to establish predictive model with the ranked features, and select the most significant features in the light of the contribution of improving the predictive accuracy. To the best of our knowledge, JNFDC is the first work which employs the sparse representation theory to explore the synthesis mechanism of six kinds of pore rings. Numerical simulations demonstrate that our proposed method can select significant features affecting the specified structural property and improve the predictive accuracy. Moreover, comparison results show that JNFDC can obtain better predictive performances than some other state-of-the-art feature selection methods., (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)