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Pan, Jian

Publications and source records attributed to Pan, Jian.

6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Ethane dehydrogenation over manganese oxides supported on ZSM-5 zeolites

Mn-ZSM5 catalysts are shown to have high reaction rates, C 2 H 4 selectivity and stability for the ethane dehydrogenation reaction. The specific reaction rate increases with the Mn loading until the optimal Mn amount of 3.4 wt% for zeolites with a Si/Al ratio of 12. Structure characterizations and spectra analysis have unveiled that this catalyst contains MnO 2 nanoparticles on the zeolite external surface and (MnOH) + groups on the external surface of the zeolite. The MnO 2 nanoparticles contain the catalytic sites for ethane dehydrogenation while the (MnOH) + groups help stabilize the oxide particles, leading to the high stability of the Mn-ZSM5 catalyst for EDH. As a result, the Mn-ZSM5 samples can catalyze EDH for over 150 h at 600 °C with a high reaction rate (>10 mmol C 2 H 6 g cat –1 h –1 ) and high C 2 H 4 selectivity (>98%). Finally, the spent catalyst can also be regenerated by calcination in dry or wet air (3% steam).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Catalytic Dehydrogenation of Ethane over Mn Oxide Supported on Zeolite Chabazite

A new class of Mn-containing zeolites prepared by incipient wetness impregnation (IWI) have been found to catalyze the ethane dehydrogenation reaction with high selectivity (98 %+). Preparation by IWI leads to the formation of Mn 2 O 3 nanoparticles on the external surface of the zeolite crystals and herein is shown that the primary active sites for the reaction are located on the surface of these particles. Propane dehydrogenation is also successfully catalyzed by this catalyst. Furthermore, other Mn-zeolites (MFI and BEA) also have high reactivity and selectivity towards light alkane dehydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Comparative investigation of Ga- and In-CHA in the non-oxidative ethane dehydrogenation reaction

Ga- and In-exchanged chabazite (CHA) zeolites with same Si/Al and metal/Al ratios were prepared via the incipient wetness impregnation method, were characterized using N 2 adsorption, electron microscopy, temperature-programed reactions and were evaluated for the ethane dehydrogenation reaction using flow microreactors. Ga-CHA has higher reaction rates and a lower activation energy of 107 kJ/mol than In-CHA (E a = 175 kJ/mol). Rietveld refinement of the X-ray powder diffraction pattern shows that the In + cation is predominantly located above the 6-ring of the CHA cage. It is proposed that the reaction proceeds through the alkyl mechanism based on stability of alkyl hydride intermediates as determined using DFT calculations. The oxidative addition of ethane to the metal shows much lower Gibbs free energy for Ga-CHA (+27.95 kJ/mol) vs In-CHA (+124.85 kJ/mol). Finally, these results indicate that oxidative addition may be the rate-limiting step of ethane dehydrogenation in these materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

On domains of convergence in optimization problems

Numerical optimization algorithms require the knowledge of an initial set of design variables. Starting from an initial design x(sup 0), improved solutions are obtained by updating the design iteratively in a way prescribed by the particular algorithm used. If the algorithm is successful, convergence is achieved to a local optimal solution. Let A denote the iterative procedure that characterizes a typical optimization algorithm, applied to the problem: Find x belonging to R(sup n) that maximizes f(x) subject to x belonging to Omega contained in R(sup n). We are interested in problems with several local maxima (x(sub j))(sup *), j=1, ..., m, in the feasible design space Omega. In general, convergence of the algorithm A to a specific solution (x(sub j))(sup *) is determined by the choice of initial design x(sup 0). The domain of convergence D(sub j) of A associated with a local maximum (x(sub j))(sup *) is a subset of initial designs x(sup 0) in Omega such that the sequence (x(sup k)), k=0,1,2,... defined by x(sup k+1) = A(x(sup k)), k=0,1,... converges to (x(sub j))(sup *). The set D(sub j) is also called the basin of attraction of (x(sub j))(sup *). Cayley first proposed the problem of finding the basin of attraction for Newton's method in 1897. It has been shown that the basin of attraction for Newton's method exhibits chaotic behavior in problems with polynomial objective. This implies that there may be regions in the feasible design space where arbitrarily close starting points will converge to different local optimal solutions. Furthermore, the boundaries of the domains of convergence may have a very complex, even fractal structure. In this paper we show that even simple structural optimization problems solved using standard gradient based (first order) algorithms exhibit similar features.

Diaz, Alejandro R.↗