Modeling the behavior of electrons unveils the fundamental reactions between compounds. Computational quantum chemists track these interactions for both theoretical and applied tasks, such as drug development and materials science. According to the experts interviewed here, this field provides growing opportunities in academics, government laboratories, and industry.
Since 1926, when the Austrian physicist Erwin Schrödinger developed the equation that bears his name and describes the behavior of electrons, chemists imagined modeling the interactions of complex compounds. That dream grows closer to reality with every improved algorithm and increase in computing power. Today, computational quantum chemists can model the properties of hundreds—thousands in some cases—of electrons to predict the behavior of interacting elements and compounds. This development can be applied to biology, engineering, materials science, molecular electronics, and many other fields.
“Computational quantum chemistry,” says Martin Head-Gordon, professor of chemistry at the University of California, Berkeley, “is basically the field that develops theoretical algorithms and software based on quantum mechanics to predict properties of molecules from first principles.” He adds, “The success of this field was recognized with the Nobel Prize in chemistry in 1998.” That year, Walter Kohn and John A. Pople were awarded the Nobel Prize for work in computational quantum chemistry. Today, work in this area leads to a wide range of career options.
Expanding the Scope
Improved computing and novel algorithms allow quantum chemistry to treat more complex interactions. “Most chemical and biochemical processes are on the level of valence electrons that interact with each other,” says Jorge H. Rodriguez, assistant professor of physics at Purdue University. “This makes electrons of one atom bond with electrons of another.” In the past, hand calculations could not handle many electrons, because of the complexity of the equations. “Now,” says Rodriguez, “much faster computers allow us to solve the Schrödinger equation for many valence electrons. Still, we cannot do this exactly, so we use approximations.”
As one example of such an approximation, Rodriquez explains, the scientist assumes that in many chemical processes only the electrons move, and the nucleus is modeled as motionless. “From that perspective, the nuclei are just positive charges that keep electrons bound.” Still, the large number of electrons and complexity of the calculations demand lots of computer time.
Today’s computing power lets scientists apply quantum chemistry to more areas. Tamar Seideman, professor of chemistry at Northwestern University, says, “One uses computational quantum chemistry to understand complex biological processes, to design molecules for various applications, and to make predictions in different fields of science and technology, ranging from engineering and materials research through molecular electronics and photonics to environmental research and pharmaceuticals.”
The Scope of Skills
The computational complexity of this field demands a strong foundation in mathematics, computing, and quantum physics. Rodriguez adds, “This is a multidisciplinary field, and you need extra skills to contribute to specific applications, such as some knowledge of organic, inorganic, and biochemistry, as well as some skill in statistical physics.”
Nonetheless, success in computational quantum chemistry goes beyond the basics. James R. Chelikowsky, the W.A. “Tex” Moncrief, Jr., Chair of Computational Materials in the departments of physics, chemical engineering, and chemistry and biochemistry and director of the Center for Computational Materials at the University of Texas at Austin, says, “To be really good in this field, you need to know what the numbers mean, not just how to create them.” He asks: If your calculations produce garbage, how do you know that? “That takes physical intuition.”
So some of the skills can be hard to teach. For example, Chelikowsky adds that researchers in computational quantum chemistry need infinite patience. “You can change one line of code that makes mistakes in two others. You need the ability to find trouble spots.”
The sources of jobs in computational quantum chemistry continually change. “In the mid-1970s,” says Chelikowsky, “the ‘center of gravity’ was in industry—IBM and Bell Labs—but there were a number of workers in universities and national labs.” Now, jobs tend to be more spread out in academics, industry, and national labs.
Also, computational quantum chemists can work on many topics. Seideman points out a long list: biological and medical research, catalysis and design of materials, data analysis, development of computer algorithms, molecular modeling, and pharmacological modeling. She adds, “The number and variety of applications in industry are growing. At the same time, emerging industries—for example, in the broad field of nanotechnology—pose new fundamental questions for research in academic environments.”
Head-Gordon also sees students going to national laboratories. There, he says, a postdoctoral fellowship at a national laboratory can lead to being hired as a permanent member of the staff. He also points out that software companies often hire computational quantum chemists right out of graduate school.
In addition, this field offers the opportunity to change directions. One of Head-Gordon’s former students completed a thesis involving the Schrödinger equation and then moved to solving Maxwell’s equations to develop photonic devices for the telecommunications industry. “Some people make major changes,” Head-Gordon says. “There are many, many directions one can go. Virtually all leading universities have a faculty member in quantum chemistry and nearly every national lab has a staff in computational quantum chemistry.”
Chelikowsky has also seen his students go to new fields. One of his graduate students worked on atomic clusters, and then got a job modeling reservoirs for a major petrochemical company. He says that computational quantum chemists can also work in many areas of material physics, including carbon nanotubes, electronic materials, magnetic systems, and nanomaterials.
Rodriguez sees new possibilities, especially in three areas. First, he points to quantum biochemistry, like his lab’s work on active sites in metaloenzymes or proteins. He adds that understanding the quantum side of biochemistry generates wide opportunities in industry. For example, his research team explores an enzyme that catalyzes the conversion of methane to methanol. He says, “This will be of interest to the energy industry.”
Second, Rodriguez mentions nanoscience. As an example, he describes single-molecule magnets—synthetic, discrete molecules that contain 10 to 20 metal ions. “These metal clusters can be candidates for building blocks for memory storage at the molecular level,” he says, “which potentially will allow the knowledge industry to store huge amounts of information in a very small space, at the nanoscale.”
Rodriguez also sees lots of potential for computational quantum chemistry in the pharmaceutical industry. “Drug design,” he says, “would be enhanced by using the laws of quantum mechanics to understand how drugs interact with binding sites.”
Moreover, Seideman expects growth for computational quantum chemistry in medical research. She says, “There are good reasons to expect that we will make growing use of computational quantum chemistry to better understand and control function-structure relationships in systems of biomedical relevance.” Seideman says, “In the future, one expects the understanding of complex processes—such as protein folding and enzyme reactions—to bring medical research beyond trial and error. Instead, it could be based on calculations.”
Funding the Computations
It’s never easy to gauge the financing available in any field. Chelikowsky says, “In general, the funding environment isn’t great.” But after being in the field since the mid 1970s, he adds, “I only remember once when people said the funding would be pretty good. For the most part, nobody ever says that.”
Head-Gordon agrees that the money side is tolerable. He calls the funding environment “generally reasonable.” Then he adds, “We never seem to have quite as much as we want or as little as we might fear.” It looks about the same to Rodriguez, who says, “There is a moderate amount of funding at the present time. It’s not bad but it could improve.” But he adds, “As the applications gain notice, the level of funding will likely increase.”
The applications of this field depend on a scientist’s imagination. As Head-Gordon says, “A computational quantum chemist can do research that ranges from curiosity driven work on fundamental problems in a university setting to software development and commercialization.” He adds, “You can also make logical leaps to adjoining fields.” Such leaps can carry a computational quantum chemist to areas limited only by creativity and inspiration.