Carbon monoxide adsorption on molybdenum phosphides: Fourier transform infrared spectroscopic and density functional theory studies

Molybdenum phosphide (MoP) and supported molybdenum phosphide (MoP/gamma-Al2O3) have been prepared by the temperature-programmed reduction method. The surface sites of the MoP/gamma-Al2O3 catalyst were characterized by carbon monoxide (CO) adsorption with in situ Fourier transform infrared (FT-IR) spectroscopy. A characteristic IR band at 2037 cm(-1) was observed on the MoP/gamma-Al2O3 that was reduced at 973 K. This band is attributed to linearly adsorbed CO on Mo atoms of the MoP surface and is similar to IR bands at 2040-2060 cm(-1), which correspond to CO that has been adsorbed on some noble metals, such as platinum, palladium, and rhodium. Density functional calculations of the structure of molybdenum phosphides, as well as CO chemisorption on the MoP(001) surface, have also been studied on periodic surface models, using the generalized gradient approximation (GGA) for the exchange-correlation functional. The results show that the chemisorption of CO on MoP occurred mainly on top of molybdenum, because the bonding of CO requires a localized mininum potential energy. The adsorption energy obtained is DeltaH(ads) approximate to -2.18 eV, and the vibrational frequency of CO is 2047 cm-1, which is in good agreement with the IR result of CO chernisorption on MoP/gamma-Al2O3.

Origin of antiferromagnetism in CoO: A density functional theory study

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Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

The alternate combinational approach of genetic algorithm and neural network (AGANN) has been presented to correct the systematic error of the density functional theory (DFT) calculation. It treats the DFT as a black box and models the error through external statistical information. As a demonstration, the AGANN method has been applied in the correction of the lattice energies from the DFT calculation for 72 metal halides and hydrides. Through the AGANN correction, the mean absolute value of the relative errors of the calculated lattice energies to the experimental values decreases from 4.93% to 1.20% in the testing set. For comparison, the neural network approach reduces the mean value to 2.56%. And for the common combinational approach of genetic algorithm and neural network, the value drops to 2.15%. The multiple linear regression method almost has no correction effect here.

Quantum master equation scheme of time-dependent density functional theory to time-dependent transport in nanoelectronic devices

In this work a practical scheme is developed for the first-principles study of time-dependent quantum transport. The basic idea is to combine the transport master equation with the well-known time-dependent density functional theory. The key ingredients of this paper include (i) the partitioning-free initial condition and the consideration of the time-dependent bias voltages which base our treatment on the Runge-Gross existence theorem; (ii) the non-Markovian master equation for the reduced (many-body) central system (i.e., the device); and (iii) the construction of Kohn-Sham master equations for the reduced single-particle density matrix, where a number of auxiliary functions are introduced and their equations of motion (EOMs) are established based on the technique of spectral decomposition. As a result, starting with a well-defined initial state, the time-dependent transport current can be calculated simultaneously along with the propagation of the Kohn-Sham master equation and the EOMs of the auxiliary functions.