MONTO ACTIVOS EN

There have been a few studies on understanding the mechanism for LA to gVL conversion, but the basis for this work was a paper which studied the influence of water on the hydrogenation reaction of LA to gVL over a Ru catalyst[58]. Similar to the paper which studied the gluycopyranose, a microsolvation model was used for modelling the interactions with the solvent, as it was stated that an implicit model does not grasp the effect of hydrogen bonding well. In order to model the reaction, acetone was used as an analogue for the LA as it was more simple to work with, and it was found that they had similar trends on metal and solvent changes. In order to include the interaction with the Ru metal, a slab of Ru(0001) was used as an analogue of the metal surface.

Figure 1.25: Reaction paths in eV for the hydrogenation of acetone on Ru(0001) in the absence (left) and in the presence of a water molecule (right). Alkyl path is the dashed line, and alkoxy path is the solid like. Taken from [58]

In order to gauge the efficiency of the catalyst, the energetic spanδE was used as a comparison. The energetic span is defined as the difference in energy between the transition state (TDTS) and reaction intermediate (TDI):

δE = ET DT S− ET DI : If TDTS appears after I

Chapter 1 Kinetic Analysis and Modelling in Heterogeneous Catalysis

δE = ET DT S − ET DI + ∆Gr : If TDTS appears before TDI

Figure 1.26: Two different methods of calculating theδE taken from [58]

It was found in figure 1.25 that when there was no water present, the alkyl route was more favourable with an energetic span of 1.37eV, but when water was included in the model, the alkoxy route became more favourable with an energetic span of 0.99eV. This demonstrates that in this particular reaction that including water has a drastic effect on the calculated reaction mechanism. It was also stated that when the solvation model was increased in complexity to include 3 water molecules, and then 11 water molecules energetic span was unchanged (0.99eV for 1 water molecule, 1.03eV for 11 water molecules). Afterwards their technique was repeated using a number of different metals (see figure 1.27) and it was found that Cu would also be highly active for this reaction, with a energetic span of 0.87eV.

Using the information gathered on the literature relating to modelling of aqueous systems, it was found that for the system being studied as part of this thesis (LA to gVL using Cu−ZrO₂) the inclusion of the solvent molecules in any model would be very important.

Figure 1.27: Energetic spans for various metals for the hydrogenation of acetone taken from [58]

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In this section the programming environment in which all of the analysis software was built will be discussed, then the underlying theory behind Temperature Programmed and Temporal Analysis of Products reactions, and an explanation of the basics of Density Functional Theory will follow. These three topics will be essential for understanding the further work being discussed in this thesis.

2.1 MATLAB Programming Environment

In order to develop software for data analysis, the first, and sometimes most diffi-cult choice, is to decide which programming language to use, and for this project the multi-paradigm numerical computing environment MATLAB[1] was chosen. MAT-LAB is considered to be a high level programming language, which means that there is a large degree of abstraction away from the internal computing code. This means that the language is much more user friendly, providing many benefits to using MATLAB over other more common programming environments (e.g. Python, C, FORTRAN). Alongside the standard MATLAB package a number extra toolboxes were used throughout the code.

• Global Optimisation

• Curve Fitting

Chapter 2 Kinetic Analysis and Modelling in Heterogeneous Catalysis

• Signal Analysis

• Optimisation

• Application Compiler

The MATLAB code is built around the MATLAB scripting language. It is highly interactive, meaning it is very easy to perform simple mathematics for example:

1>> x = 3 ;

where MATLAB really excels is in its handling of vectors and matrices, through simple commands it is easy to generate a matrix of elements and quickly perform any function on that matrix:

Finally the data which has been generated can be easily saved to a structure.

1>> s S t r u c t D a t a = s t r u c t ( . . .

2 ’ peak ’, peak , . . .

3 ’ d a t a ’, data , . . .

4 ’ t i m e ’, time , . . .

5 ’ peakno ’, peakno , . . .

Using these methods, it is very simple to generate functions and pass around vari-ables, the code below provides an example of solving a differential equation numer-ically, and how a function is structured. The actual use of the function will be discussed further on in this thesis in section 2.2.

1 f u n c t i o n [ F , alphTPR ] = TPR_function (A, Ea ,m, n , g , Temp ,b e t a)

Chapter 2 Kinetic Analysis and Modelling in Heterogeneous Catalysis

It is this ability to quickly write code in a simple and human readable manner which facilitated the development of the algorithms required for analysis of TPR and TAP experiments.