Some Understanding of Fischer-Tropsch Synthesis from Density Functional Theory Calculations

The combination of density functional theory (DFT) calculations and kinetic analyses is a very useful approach to study surface reactions in heterogeneous catalysis. The present paper reviews some recent work applying this approach to Fischer-Tropsch (FT) synthesis. Emphasis is placed on the following fundamental issues in FT synthesis: (i) reactive sites for both hydrogenation and C-C coupling reactions; (ii) reaction mechanisms including carbene mechanism, CO-insertion mechanism and hydroxyl-carbene mechanism; (iii) selectivity with a focus on CH(4) selectivity, alpha-olefin selectivity and chain growth probability; and (iv) activity.

Density Functional Theory Study of Iron and Cobalt Carbides for Fischer-Tropsch Synthesis

Carbides are important phases in heterogeneous catalysis. However, the understanding of carbide phases is inadequate: Fe and Co are the two commercial catalysts for Fischer-Tropsch (FT) synthesis, and experimental work showed that Fe carbide is the active phase in FT synthesis, whereas the appearance of Co carbide is considered as a possible deactivation cause, TO understand very different catalytic roles of carbides, all the key elementary steps in FT synthesis, that is, CO dissociation, C(1) hydrogenation, and C(1)+C(1) coupling, are extensively investigated on both carbide surfaces using first principles calculations. In particular, the most important issues in FT synthesis, the activity and methane selectivity, on the carbide surfaces are quantitatively determined and analyzed. They are also discussed together with metallic Fe and Co surfaces. It is found that (i) Fe carbide is more active than metallic Fe and has similar methane selectivity to Fe, being consistent with the experiments; and (ii) Co carbide is less active than Co and has higher methane selectivity, providing evidence on the molecular level to support the suggestion that the formation of Co carbide is a cause of relatively high methane selectivity and deactivation on Co catalysts.

A density functional theory study of CO oxidation on Ru(0001) at low coverage

We have performed ab initio density functional theory calculations with the generalized gradient approximation to investigate CO oxidation on Ru(0001). Several reaction pathways and transition states are identified. A much higher reaction barrier compared to that on Pt(111) is determined, confirming that the Ru is very inactive for CO oxidation under UHV conditions. The origin of the reaction barrier was analyzed. It is found that in the transition state the chemisorbed O atom sits in an unfavorable bonding site and a significant competition for bonding with the same substrate atoms occurs between the CO and the chemisorbed O, resulting in the high barrier. Ab initio molecular dynamics calculations show that the activation of the chemisorbed O atom from the initial hcp hollow site (the most stable site) to the bridge site is the crucial step for the reaction. The CO oxidation on Ru(0001) via the Eley-Rideal mechanism has also been investigated. A comparison with previous theoretical work has been made. (C) 2000 American Institute of Physics. [S0021-9606(00)31223-5].

A comprehensive strategy to detect the fraudulent adulteration of herbs: The oregano approach

Fraud in the global food supply chain is becoming increasingly common due to the huge profits associated with this type of criminal activity. Food commodities and ingredients that are expensive and are part of complex supply chains are particularly vulnerable. Both herbs and spices fit these criteria perfectly and yet strategies to detect fraudulent adulteration are still far from robust. An FT-IR screening method coupled to data analysis using chemometrics and a second method using LC-HRMS were developed, with the latter detecting commonly used adulterants by biomarker identification. The two tier testing strategy was applied to 78 samples obtained from a variety of retail and on-line sources. There was 100% agreement between the two tests that over 24% of all samples tested had some form of adulterants present. The innovative strategy devised could potentially be used for testing the global supply chains for fraud in many different forms of herbs.

Generating Data Augmented Spectroscopic Data For Performance Enhancement

The application of chemometrics in food science has revolutionized the field by allowing the creation of models able to automate a broad range of applications such as food authenticity and food fraud detection. In order to create effective and general models able to address the complexity of real life problems, a vast amount of varied training samples are required. Training dataset has to cover all possible types of sample and instrument variability. However, acquiring a varied amount of samples is a time consuming and costly process, in which collecting samples representative of the real world variation is not always possible, specially in some application fields. To address this problem, a novel framework for the application of data augmentation techniques to spectroscopic data has been designed and implemented. This is a carefully designed pipeline of four complementary and independent blocks which can be finely tuned depending on the desired variance for enhancing model's robustness: a) blending spectra, b) changing baseline, c) shifting along x axis, and d) adding random noise.
This novel data augmentation solution has been tested in order to obtain highly efficient generalised classification model based on spectroscopic data. Fourier transform mid-infrared (FT-IR) spectroscopic data of eleven pure vegetable oils (106 admixtures) for the rapid identification of vegetable oil species in mixtures of oils have been used as a case study to demonstrate the influence of this pioneering approach in chemometrics, obtaining a 10% improvement in classification which is crucial in some applications of food adulteration.