Application Note. L. PREDIBOND in Heterogeneous Catalysis Predicting Activity Patterns. Introduction

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1 Application Note L. PREDIBOND in Heterogeneous Catalysis Predicting Introduction The performance of catalytic materials depends on complex phenomena linked to chemical composition, preparation, activation procedures, and surface conditions under operational conditions. This complexity requires a comprehensive arsenal of R&D approaches including theoretical and computational methods. While many fundamental research efforts are currently directed at a detailed understanding of surface reaction mechanisms, PREDIBOND TM focuses on bond strength and local chemical environment as central descriptors of chemical reactivity. By combining in a unique and proprietary way experimental reactivity data on model systems with experimental structural data and computed information, PREDIBOND TM allows the classification of catalytic materials and thus the prediction of promising areas in the catalyst design space. This application note focuses on the application of PREDIBOND TM to a specific example in heterogeneous catalysis, namely hydrodesulphurization with catalytically active metal sulfide surfaces. The problem Consider the hydrodesulphurization reaction C n H m S+H 2 C n H m +H 2 S (1-3) A set of known catalytic materials for this reaction is listed in the table on the right. Note that the catalysts with the highest activity contain rare and expensive metals. The obvious question arises, if there are more cost effective compounds with the same or possibly even higher catalytic activity. To this end, one could extend the search to include ternary and higher compounds, but apparently, one would face a huge combinatorial space to explore. Where do we start looking for new and improved catalysts? Preparing sample structures and testing them is time consuming and costly. Criteria for prioritization are needed. PREDIBOND TM offers just these by exploiting the well-known Sabatier principle, which states in essence that Catalytically active surfaces show intermediate bond strength with the reacting molecule While strong bonding of a molecule blocks the surface, weak bonding does not provide the interactions needed to retain reacting molecules at the surface and activate their bonds. Catalyst Activity [1] Activity [2] RuS OsS IrS Rh 2 S ReS PtS PdS MoS Cr 2 S WS NbS Ni 3 S Co 9 S VS FeS TaS MnS Copyright Materials Design, Inc

2 Bond Strength Bond strength is a key concept to rationalize many complicated phenomena in areas as diverse as heterogeneous catalysis, sensor materials, and energy storage systems. The intuitive notion of the strength of a chemical bond is hard to express in a mathematically rigorous and practically useful scheme. In fact, crystallographers and theoretical chemists have developed a range of approaches to address this problem. For example, a very simple concept relates bond strength with bond distances. Shorter bond lengths are an indication of stronger bonds. The problem in this approach is a proper definition of a reference. PREDIBOND TM applies a particularly useful definition and is the basis of a patent by Hervé Toulhoat from the French Petroleum Institute[3]. How does PREDIBOND TM work? PREDIBOND TM uses a correlation between the bond strength and catalytic activity to predict candidates for specific reactions. No explicit surface models are involved in the derivation of the PREDIBOND TM descriptor. Therefore, it represents an efficient screening tool to prioritize the choice of starting materials for further investigations. In essence, the bond strength of a particular target atom, for example sulfur, to its neighboring atoms is determined from experimental (or computed) stable crystal structures, which contain the bond type of interest. Three total energy calculations are performed, one for the full crystal structure and two calculations for hypothetical sub-lattices. The difference of the total energies of the full crystal and the two sub-lattices yields the interaction energy of the target atom with the surrounding atoms. This is accomplished by ab initio quantum mechanical methods. The bond energy follows from a normalization of the interaction energy by the number of nearest neighbors of the target atom in the full crystal structure. A detailed description of the approach is given in [4; 5]. PREDIBOND TM thus allows a ranking of the compounds according to bond strength. If the target atom does play a central role in the catalytic reaction of interest, then there exists a correlation between catalytic activity and the PREDIBOND TM bond strength in the form of a volcano curve. The PREDIBOND TM concept is implemented in the MEDEA technology platform as the PREDIBOND module. Its application is illustrated step-by-step in the following sections. 1. Build a PREDIBOND spreadsheet In MEDEA choose PrediBond from the tool menu. If you do not have a license but wish to work with PREDIBOND, please contact info@materialsdesign.com. In the PrediBond submenu select New. An empty unnamed spreadsheet will come up. This spreadsheet is your starting point for building up a list of structures, defining parameters for PREDIBOND runs and launching your PREDIBOND jobs. As you go along and build up spreadsheets it is recommended to save them in MEDEA s internal database for later use. Choose Save As from the PREDIBOND submenu and choose an appropriate name. In this example let us name the spreadsheet TM-S. Next we will add structures from the database to our worksheet. To this Copyright Materials Design, Inc

3 end, bring up INFOMATICA from the Tools menu and choose Search from its submenu. In the search window choose the following criteria to search the databases: Launching a search with these criteria should give you more than 500 hits from ICSD and Pauling together.you can sort with respect to columns by right clicking on the column header: sort the sum column in the search result window by choosing Sort ascending. Let s browse these entries for compounds listed with their activities in the above table. To run this example you should choose compounds showing high medium and low activities. You can select more than one entry at the time by holding down the Ctrl-key while left clicking on the entries. Copy selected structures using the Copy entry of the context sensitive menu (right-click). As an example choose the following structures from INFOMATICA: ID Space group name H-M Sum coordination number PREDIBOND (kj/mol) ICSD P63MC CdS CRYSTMET Pnma IrS 2 ICSD.2400 P63/MMC Mo S 2 CRYSTMET P63/mmc Nb S 2 ICSD PA3- Os S 2 ICCSD P42/M PdS ICSD PBCN Rh 2 S 3 ICSD PA3- RuS 2 CRYSTMET P63/mmc TaS 2 CRYSTMET P63/mmc WS 2 CRYSTMET P63/mmc FeS CRYSTMET R32r Ni 3 S 2 Select the worksheet and transfer the selected candidates with Paste structures 2. Configure and run a PREDIBOND job Define Target atoms for which you would like to calculate the PREDIBOND energy Copyright Materials Design, Inc

4 You are going to calculate the energy per bond of target atom to the other elements in each compound on the list (obviously, each compound in the PREDIBOND spreadsheet must contain the target atom). PREDIBOND will apply the algorithm described above to each of the structures and derive the bond energy per bond. In the above example select Target atoms from the PREDIBOND menu and type S into the text field. Select the computational tasks Select Engine. You can perform a PREDIBOND with VASP or any other computational engine. In our example select VASP as an engine and choose Structure optimization from the VASP settings menu. Activate Allow cell volume to change and Allow cell shape to change. This will relax each structure to the theoretical lattice parameters and atomic positions before applying the vacancy method. Click OK to close the dialogue and choose Run from the PREDIBOND dialogue to launch the job. As your job is being processed, MEDEA will import the key results from each run into your worksheet, which is then updated automatically. Once you have collected all data, you can sort with respect to columns by right clicking on the header cell of each column. In order to export to Excel, highlight a region of the spreadsheet and choose Copy from the contextmenu (right click on highlighted region). Below is an example of such a calculation presented in an Excel spreadsheet with experimental activities added. You can sort your results either directly in PREDIBOND or you can use Excel to sort and format your worksheets. PREDIBOND and MEDEA offer various units of energy, right-click on the corresponding column header to change units to kj/mol or ev. Space group name H-M Formula a (Å) total (Ha) E coh (kj/mol) Coordination number n E PREDIBOND (kj/mol) Activity P63/mmc VS FM-3M MnS P63mc FeS R32 Ni 3 S P42/M PdS PBCN Rh 2 S PA-3 RuS P42/MMC PtS FM3-M Co 9 S Pnma IrS P63/mmc NbS P63/mmc WS Pa3 OsS P63/mmc TaS Copyright Materials Design, Inc

5 3. Analyzing results Let us look at the volcano curve produced by correlating the above results with experimental activities. To do so, create an Excel graph relating PREDIBOND energies on the x-axis and the activities listed above on the (logarithmic) y-axis. The plot represents the characteristic volcano shape, which is an expression of the Sabatier principle: Solids with extremely low or high TM-S bond strength show low activities while those with intermediate bond strength have higher activities. We have accomplished the mapping of a descriptor calculated from experimental bulk crystal structures onto experimental activity data for a highly complex heterogeneous catalyst. The only input was the crystal structure from experiment. Based on this information, VASP recreates the chemical bonds and using the PREDIBOND descriptor we have succeeded in establishing a valuable activity pattern: the optimal metal-sulfur PREDIBOND energy for the given system is around 140 kj/mol. In this region the bond energy of the metal-sulfur bond is favorable for activating the sulfur bond of a sulfur-containing molecule. Now the search for improved or new systems can rely on a clear steering principle Log HDS Activity per mol of metal VS Ni 3 S 2 FeS MnS PdS Rh 2 S 3 Co 9 S 8 RuS 2 PtS Co 9 S Bond strength(kj/mol) IrS 2 OsS 2 WS 2 NbS 2 TaS 2 Testing new candidates Once the correlation is established with PREDIBOND, we can use a volcano plot to estimate activities of new candidates or materials, without experimental activity data at hand. To this end we have to calculate the corresponding PREDIBOND descriptor and use the above correlation curve as a gauge to predict the activity. Copyright Materials Design, Inc

6 Navigating in the space of ternary compounds Obviously the search is not limited to binary compounds! The concept of the volcano curve, allows us to navigate in the space of ternary compounds and to identify promising candidates by combining elements from the left and right side of the volcano curve. As a matter of fact, one of the actual industrial catalysts is MoS 2 doped with Co and Ni.[6] The volcano curve obtained with PREDIBOND gives a rationale for the activity of this system. The Mo-S, like the W-S bond, is too strong and needs to be moderated by elements with weak metal-sulfur bonds. The elements Ni and Co meet this requirement. Now the power of the approach becomes obvious: there are many other potential combinations between compounds from the right and the left side of the volcano curve! Uncertainty of experimental data The experimental activity data in the table above show significant variations between the two data sets. This uncertainty is due to the great difficulty in obtaining consistent experimental data series of catalytic activity. Therefore, one should not expect that correlations obtained with PREDIBOND are always perfect. One source for the deviation can be the uncertainty in the experimental data. Another critical point is the assumption about the target atom. If it turns out that no or only a poor correlation is found with a given target atom, then this may be an indication of important steps in the reaction, which involve other atoms or effects. Inequivalent atoms in crystal structure PREDIBOND calculates bond strength energies per chemical bond. The definition of what counts as a bond is not always unambiguous. As an example let us consider the above case of Co 9 S 8 with 4 bonds between S and Co. This positions Co 9 S 8 more to the right of the volcano curve, together with PtS. When analyzing the geometry of the crystal structure it becomes obvious that there are two symmetrically distinct S atoms in Co 9 S 8. While one sulfur atom (S 1 ) has 4 Co neighbors at a distance of Å, the other Sulfur (S 2 ) has 4 Co neighbors at Å and one at Å. PREDIBOND defines a coordination sphere around each target atom thus classifying atoms strictly as either bonded or non-bonded. In cases like the above this can lead to irregularities in the PREDIBOND energies. With the coordination number increased from 4 to 4.75 the bond energy is decreased and Co 9 S 8 shifts (denoted by a green diamond) to the left side of the volcano curve. 1. Pecoraro, T A and Chianelli, R R. J. Catalysis. 1989, Vol. 67, p Ledoux, M J, et al. J. Catalysis. 1986, Vol. 102, p Toulhoat, Hervé. Conception de nouveuax materiaux dont l'usage fait intervenir une liaison chimique au moyen d'un descripteur de ladite liaison. FR France, 12 13, Toulhoat, H, et al. Catalysis Today. 1999, Vol. 50, pp Toulhoat, H and Raybaud, P. J. Catalysis. 2003, Vol. 216, 1-2, pp Schweiger, H, Raybaud, P and Toulhoat, H. J. Catalysis. 2002, Vol. 212, pp Copyright Materials Design, Inc

Heterogeneous catalysis: the fundamentals Kinetics

www.catalysiscourse.com Heterogeneous catalysis: the fundamentals Kinetics Prof dr J W (Hans) Niemantsverdriet Schuit Institute of Catalysis Catalysis is a cycle A B separation P catalyst P bonding catalyst