Chemical Bonding at Surfaces and Interfaces

Anders Nilsson, Lars G.M. Pettersson, Jens Norskov

• Publisher: Elsevier Science
• Year: 2011
• ISBN:
  9780080551913
• Topic: Physical Sciences
• Subtopic: Physics
• Index: Physics

Molecular surface science has made enormous progress in the past 30 years. The development can be characterized by a revolution in fundamental knowledge obtained from simple model systems and by an explosion in the number of experimental techniques. The last 10 years has seen an equally rapid development of quantum mechanical modeling of surface processes using Density Functional Theory (DFT).

Chemical Bonding at Surfaces and Interfaces focuses on phenomena and concepts rather than on experimental or theoretical techniques. The aim is to provide the common basis for describing the interaction of atoms and molecules with surfaces and this to be used very broadly in science and technology.

The book begins with an overview of structural information on surface adsorbates and discusses the structure of a number of important chemisorption systems. Chapter 2 describes in detail the chemical bond between atoms or molecules and a metal surface in the observed surface structures. A detailed description of experimental information on the dynamics of bond-formation and bond-breaking at surfaces make up Chapter 3. Followed by an in-depth analysis of aspects of heterogeneous catalysis based on the d-band model. In Chapter 5 adsorption and chemistry on the enormously important Si and Ge semiconductor surfaces are covered. In the remaining two Chapters the book moves on from solid-gas interfaces and looks at solid-liquid interface processes. In the final chapter an overview is given of the environmentally important chemical processes occurring on mineral and oxide surfaces in contact with water and electrolytes.

• Gives examples of how modern theoretical DFT techniques can be used to design heterogeneous catalysts
• This book suits the rapid introduction of methods and concepts from surface science into a broad range of scientific disciplines where the interaction between a solid and the surrounding gas or liquid phase is an essential component
• Shows how insight into chemical bonding at surfaces can be applied to a range of scientific problems in heterogeneous catalysis, electrochemistry, environmental science and semiconductor processing
• Provides both the fundamental perspective and an overview of chemical bonding in terms of structure, electronic structure and dynamics of bond rearrangements at surfaces

Chapter 1

Surface Structure

D.P. Woodruff, Physics Department, University of Warwick, Coventry CV4 7AL, UK

Publisher Summary

Quantifying and understanding the structure of surfaces, and particularly of adsorbates on surfaces, is a key step to understanding many aspects of the behaviour of surfaces including the electronic structure and the associated chemical properties. Methods to determine the structure of surfaces by ab initio methods, in which the structural model and the positions of the atoms are varied to find the lowest energy configuration form the basis of the calculation of the electronic and chemical properties. This chapter illustrates some of the structural phenomena associated with adsorbate bonding at surfaces and shows how (experimental) quantitative surface structure determination can provide insight into the nature of adsorbate bonding at surfaces. It begins with a brief outline of the methods used for adsorbate structure determination. These methods are important to understand the strengths and limitations of the various methods in order to evaluate the data that arise from them. Following this, the study presents a few examples of the way that adsorbates may modify the structure of the outermost atomic layers of the surface onto which they are adsorbed, and the significance of such adsorbate-induced reconstruction. Furthermore, it describes investigations of molecular adsorbates of varying size. Finally, it explores the issues raised by careful quantitative measurements of chemisorption bondlengths, and discusses the insight they give into bonding mechanisms.

1 Why surface structure?

Quantifying and understanding the structure of surfaces, and particularly of adsorbates on surfaces, is a key step to understanding many aspects of the behaviour of surfaces including the electronic structure and the associated chemical properties. For example, any calculation of the electronic structure starts from the structure. Of course, it is now common to try to determine the structure of surfaces by ab initio methods, in which the structural model and the positions of the atoms are varied to find the lowest energy configuration which then forms the basis of the calculation of the electronic and chemical properties. Such methods have become increasingly powerful and effective in recent years, yet experimental tests of these optimised structures are crucial to ensure the integrity of such calculations, and there are certainly clear examples in the literature of the failure of these calculations to reproduce well-established experimental structural trends (e.g., CO on Pt(111) — see Section 4). A particular example of the significance of surface structure in surface chemistry is in the field of heterogeneous catalysis, in which one frequently reads references to ‘the active site’. Underlying such statements is the belief that key steps in surface chemical reactions occur at specific geometrical sites on a surface, and that understanding the nature of these sites could greatly improve our understanding of how to make more efficient catalysts. In those cases in which a catalytic system is found to be ‘structure sensitive’ it seems likely that these active surface sites may be quite specific and thus their availability is dependent on the mode of catalyst preparation.

In this chapter, the objective is to illustrate some of the structural phenomena associated with adsorbate bonding at surfaces and to show how (experimental) quantitative surface structure determination can provide insight into the nature of adsorbate bonding at surfaces. To achieve this, a brief outline of the methods used for adsorbate structure determination is first given in Section 2. Details of these methods are not the focus of this chapter, yet it is important to understand the strengths and limitations of the various methods in order to evaluate the data that arise from them. In Section 3, are presented a few examples of the way that adsorbates may modify the structure of the outermost atomic layers of the surface onto which they are adsorbed, and the significance of such adsorbate-induced reconstruction. Section 4 includes illustrations of investigations of molecular adsorbates of varying size, while in Section 5 issues raised by careful quantitative measurements of chemisorption bondlengths, and the insight they give into bonding mechanisms, are discussed.

2 Methods of surface adsorbate structure determination

2.1 General comments

In this section, some key aspects of the various methods of surface adsorbate structure determination are described. Far more detailed descriptions of the individual methods may be found elsewhere (some relevant references are given), and the objective here is rather to highlight the particular strengths, limitations and special aspects of the techniques which need to be considered when evaluating and comparing the results of applications of these methods. One particular feature which is common to the great majority of these techniques is that the structure is extracted from the experiment through some kind of trial-and-error modelling. In this approach one ‘guesses’ a possible structure and then compares the results of the experiment with the results which would be expected from the guessed structure, through a computation based on the known physical phenomena that underlie the experiment. In many cases it is possible to refine the structural model in an automated and objective fashion by varying the structural parameter values in the model calculation and searching for the best agreement with experiment, typically identified as the minimum value of some kind of reliability- or R-factor. R-factors are commonly based on a sum of the squares of the differences of the experimentally measured and theoretically computed quantities. This type of optimisation, however, is only conducted within a specific structural model. For example, one may adjust the interlayer spacings within the substrate, within a molecular adsorbate, and between the substrate and adsorbate, and may also adjust lateral positions of atoms, but typically within some applied symmetry constraints. It is then necessary to compare the results of such structural optimisations for different structural models. These models may only differ in the lateral registry of the adsorbate of the adsorbate — e.g., adsorption in atop, bridge or hollow sites — but may also include specific models of adsorbate-induced substrate reconstruction, such as changes in the atomic density of the outermost layer or layers of the substrate.

An important general limitation of this approach is that the ultimate structure determination is limited by the imagination of the researcher. If the correct structural model is not tested, the final solution will be the best structure tried, but not the correct one. Indeed, this best structure may differ fundamentally from the true structure. Notice, too, that this limitation also applies to ab initio total energy calculations to determine surface structures theoretically. Here, too, one must start from specific trial models of a structure which can then be optimised.

A second general issue in surface structure determination using the trial-and-error modelling approach is uniqueness. In any optimisation of a structural model one can find an optimal set of structural parameters which defines a minimum in the R-factor. This minimum value may represent a ‘good fit’ but is still not necessarily the correct structure. One can then compare the R-factor values associated with these local minima for different structural models, perhaps resulting in several ‘good fits’. Ideally, one of the structural models gives a significantly lower R-factor. In some cases, however, the goodness-of-fit is similar for more than one best-fit structure. The risk of this problem arising can generally be greatly reduced by ensuring that the size of the data set being used for theory-experiment comparison is large. Large data sets not only reduce the likelihood of this type of ambiguity, but also reduce the size of the variance of the R-factor and thus render significant smaller differences in minimum R-factor values. For this reason the size of the data set is an important issue in determining the reliability of any experimental structure determination, as well as its precision. Of course, there are also situations in ab initio total energy calculations in which two structures have essentially ...

Table of contents

• Cover image
• Title page
• Table of Contents
• Preface
• Chapter 1: Surface Structure
• Chapter 2: Adsorbate Electronic Structure and Bonding on Metal Surfaces
• Chapter 3: The Dynamics of Making and Breaking Bonds at Surfaces
• Chapter 4: Heterogeneous Catalysis
• Chapter 5: Semiconductor Surface Chemistry
• Chapter 6: Surface Electrochemistry
• Chapter 7: Geochemistry of Mineral Surfaces and Factors Affecting Their Chemical Reactivity
• Index