Researchers Use Computational Chemistry to be Able to Successfully Design Functional Materials

With the advent of innovative techniques for gaining insights into and manipulating matter at its most fundamental levels, scientists working in the interdisciplinary field of materials science have been highly successful in producing new types of materials.

Artist’s rendering of organic molecules adsorbing on a silicon surface. (Image credit: Aaron Beller)

Usually, the aim of scientists in this field is to design materials with properties that can be useful for carrying out particular functions. For instance, such materials can be resistant to physical breakage or more chemically stable, react in predictable ways to certain environmental conditions, or have beneficial electromagnetic properties.

Dr. Ralf Tonner and his research team from the University of Marburg have been working to overcome the difficulty of designing functional materials in a peculiar manner—by using strategies that are based on computational chemistry. Tonner models phenomena that take place at the atomic and subatomic scale with the help of computing resources at the High-Performance Computing Center Stuttgart (HLRS), to gain insights into the way factors such as chemical bonding, molecular structure, interactions among atoms, and electronic properties have an impact on the behavior of a material.

When you study how, for example, a molecule adsorbs on a surface, other scientists will often describe that phenomenon with methods from physics, solid state theory, or band structures. We think it can also be very helpful to ask, how would a chemist look at what’s happening here?

Dr. Ralf Tonner, University of Marburg

From this point of view, Tonner is fascinated about investigating whether gaining insights into chemical reactions—the way atoms bond together into molecules and react when they come into contact with each other—can provide useful and innovative understanding.

In a new publication in WIREs Computational Molecular Science, Tonner and his colleague Lisa Pecher highlight the potential of computational chemistry strategies using high-performance computing to unravel fascinating phenomena that take place between organic molecules and surfaces. In addition, they show more generally the way these interactions can be perceived in relation to the molecular and solid-state world. The insights they gained could prove useful in developing patterned surfaces, a goal of researchers working on the next generation of highly robust, more efficient semiconductors.

Bringing computation to chemistry

When atoms approach one another, they bond together to form molecules and compounds and subsequently share or trade electrons that orbit around their nuclei. The particular atoms involved, the physical shapes that the molecules take, their energetic characteristics, and the way they interact with other adjacent molecules are all characteristics that provide a compound with its distinctive characteristics. Such properties can govern whether compounds would possibly remain stable, or whether stresses like variations in pressure or temperature could have an impact on their reactivity.

Tonner employs a computational strategy known as density functional theory (DFT) to investigate such properties at the quantum scale—the scale where Newtonian mechanics is replaced by the considerably exotic realm of quantum mechanics (at distances of less than 100 nm). DFT involves the use of information related to changes in the density of electrons within a molecule—a quantity that can also be measured experimentally with the help of a largely used technique known as X-ray diffraction—to extract the energy of the system. This, on the other hand, allows the scientists to infer interactions among nuclei and also interactions between electrons and nuclei, factors that are crucial in gaining insights into chemical bonds and reactions.

DFT can offer useful, albeit static, information related to the energy profiles of the compounds under investigation. In order to know better about the way systems of molecules actually behave when they interact with a surface, Tonner’s team also employed high-performance computing at HLRS to carry out molecular dynamics simulations. Here, the researchers analyze the way the system of molecules develops over time, at the level of atoms and electrons and at time scales of picoseconds (one picosecond is one-trillionth of 1 second).

Typically 2000–3000 computing cores are used in such calculations, working on a problem for a week, and Tonner has been budgeted roughly 30 million CPU hours at HLRS for the existing 2-year funding cycle.

Increasing computing power has made it possible for computational chemistry and quantum chemistry to describe real molecular systems. Just 15-20 years ago, people could only look at small molecules and had to make rather strong approximations. In the last few years, the computational chemistry and solid state theory communities have solved the problem of parallelizing their codes to operate efficiently on high-performance computing systems. As supercomputers get bigger, we anticipate being able to develop increasingly realistic models for experimental systems in materials science.

Dr. Ralf Tonner, University of Marburg

Toward light-based semiconductors

One area in which Tonner has currently been using computational chemistry is to analyze ways to enhance silicon for application in innovative types of semiconductors. In the recent past, this problem has gained urgency as it is evident that the microelectronics sector is approaching the limits of its potential to enhance semiconductors in which silicon alone is used.

As reported by Tonner and experimental collaborators in a paper recently published in the Beilstein Journal of Organic Chemistry, functionalizing silicon with compounds like gallium arsenide (GaAs) or gallium phosphide (GaP) could allow designing innovative types of semiconductors. According to this study, which is based in a field known as silicon photonics, such innovative materials would render it feasible to use light rather than electrons for signal transport, supporting the development of enhanced electronic devices.

To do this, we really need to understand how the interfaces between silicon and these organic compounds look and behave. The reaction between these two material classes needs to proceed in a very controlled manner so that the interface is as perfect as possible. With computational chemistry we can look at the elemental details of these interactions and processes.

Dr. Ralf Tonner, University of Marburg

For instance, a silicon slab is covered by placing liquid precursor molecules for the constituent atoms of gallium arsenide in a bubbler, where they are subsequently brought into the gas phase. These precursor molecules are formed of the atoms needed for the new material (arsenic, gallium) and molecules or ions called ligands to stabilize them in the liquid and gas phase. These ligands are then lost in the deposition process and upon placing silicon in the system, the precursor molecules are adsorbed onto the solid silicon surface. Following adsorption and loss of the ligands, arsenide and gallium atoms bond to the silicon, giving rise to a GaAs film.

The way atoms are arranged while adsorbing to a surface is governed by chemical bonding. The density with which the GaAs precursor molecules are adsorbed and the strength of these bonds are not just impacted by the distance between them and the silicon surface but also by interactions among the precursor molecules themselves. In one interaction type, known as Pauli repulsion, electron clouds overlap and repel one other, thereby leading to a reduction in the energy available for bonding. In another type, known as attractive dispersion interaction, variations in the electronic positions in one atom lead to redistribution of electrons in other atoms, thus bringing the electron movements into harmony and reducing the energy of the entire system.

Earlier, it had been proposed that repulsive relationships among atoms are the most crucial factor in “steering” atoms into place upon adsorbing on a surface. The researchers used density functional theory and analyzed interesting aspects of ways electrons are distributed to determine that the potential of the atoms to steer other atoms into place on the surface can also be caused by attractive dispersive interactions.

Gaining better insights into these fundamental interactions should enable designers of optically active semiconductors to enhance adsorption of the precursor molecules onto silicon. This, on the other hand, would render it feasible to combine light signal conduction with silicon-based microelectonics, combining the best of both fields in optical and electronic conduction.

According to Tonner, the use of first principles methods in chemistry for materials science applications is highly promising.

Theory today is very often taken as a complement to experimental investigation. Although experimentation is extremely important, our ultimate goal is for theory to be predictive in ways that enable us to make the first steps in first principles-inspired materials design. I see this as a long term goal.

Dr. Ralf Tonner, University of Marburg

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