Chemical engineers at the University of Wisconsin-Madison have made a breakthrough in computational chemistry by developing a model of catalytic reactions at the atomic level. This new understanding could lead to more efficient catalysts, tuned industrial processes, and significant energy savings, as the catalyst plays a critical role in producing 90% of the products we encounter in our lives.
In a major breakthrough in computational chemistry, chemical engineers from the University of Wisconsin-Madison have created a model that shows how catalytic reactions work at the atomic level. This new understanding could enable engineers and chemists to design improved catalysts and improve industrial procedures, which could lead to massive energy savings, as catalysis is involved in the production of 90% of the products we use every day.
Lang Shaw. Credit: University of Wisconsin-Madison
Catalysts speed up chemical reactions without undergoing changes themselves. They play an important role in the processing of petroleum products and the production of a wide range of items, including medicines, plastics, food additives, fertilizers, environmentally friendly fuels, and various industrial chemicals.
Scientists and engineers have spent decades tuning catalytic reactions—but because it is currently impossible to directly observe those reactions at the extreme temperatures and pressures often associated with catalysis on an industrial scale, they didn’t know exactly what was happening on the nano and atomic scales. This new research helps unravel this mystery with potentially huge ramifications for the industry.
In fact, just three catalytic reactions—the reformation of steam and methane to produce hydrogen, the synthesis of ammonia to produce fertilizer, and the synthesis of methanol—use nearly 10% of the world’s energy.
says Manos Mavrikakis, a professor of chemical and biological engineering at Madison who led the research. “By reducing the energy you need to run all of these processes, you also reduce their impact on the environment.”
Mavrikakis and postdoctoral researchers Lang Xu and Konstantinos G. Papanicolaou along with graduate student Lisa G publish news of their progress in the April 7, 2023 issue of the journal Sciences.
Manu Mavrikakis. Credit: University of Wisconsin-Madison
In their research, University of Washington Madison engineers developed and used robust modeling techniques to simulate catalytic reactions at the atomic level. In this study, they looked at reactions involving transition metal catalysts in the form of nanoparticles, which include elements such as platinum, palladium, rhodium, copper, nickel and others important to industry and green energy.
According to the current solid surface model of catalysis, the tightly packed atoms of transition metal catalysts provide a two-dimensional surface to which reactant chemicals adhere and participate in reactions. When enough pressure, heat, or electricity is applied, the bonds between the atoms in the chemical reactants break, allowing the fragments to recombine into new chemical products.
“The prevailing assumption is that these metal atoms are strongly bound together and simply provide ‘landing points’ for the reactants. What everyone assumed was that the metal-metallic bonds remain intact during the reactions they catalyze,” says Mavrikakis. “So here, for the first time, we asked the question. , “Could the energy that breaks the bonds in the reactants be of the same magnitude as the energy needed to break the bonds within the catalyst?”
According to Mavrikakis modeling, the answer is yes. The energy provided for many of the catalytic processes is sufficient to break the bonds and allow single metal atoms (known as adatoms) to separate and begin traveling on the surface of the catalyst. These adatoms coalesce into clusters, which act as sites on the catalyst where chemical reactions can occur much more easily than the original solid surface of the catalyst.
Using a combination of special calculations, the team looked at the industrially important interactions of eight transition metal catalysts and 18 reactants, determining the energy levels and temperatures likely to form such small metal clusters, as well as the number of atoms in each group, which can also influence High on reaction rates.
Their experimental collaborators at the University of California, Berkeley, used atomic scanning tunneling microscopy to examine the adsorption of carbon monoxide on nickel(111), a stable crystalline form of nickel useful in catalysis. Their experiments confirmed that models that showed various defects in the catalyst’s structure could also affect how single metal atoms dissociate, as well as how reaction sites are formed.
Mavrikakis says the new framework challenges the foundations of how researchers understand catalysis and how it occurs. It may also apply to other non-metallic catalysts, which he will investigate in future work. It is also relevant to understanding other important phenomena, including erosion and tribology, or the interaction of moving surfaces.
“We’re revisiting some very well-established assumptions in understanding how catalysts work and, more generally, how molecules interact with solids,” says Mavrikakis.
Reference: “Formation of Active Sites on Transition Metals Through Reaction-Triggered Migration of Surface Atoms” by Lang Shaw, Konstantinos G. Papanicolaou, Barbara AJ Lechner, Lisa G, Gabor A. Somorgay, Mikel Salmeron Manos Mavrikakis April 6, 2023 Available here. Sciences.
DOI: 10.1126/science.add0089
The authors acknowledge support from the US Department of Energy, Basic Energy Sciences, Department of Chemical Sciences, and Catalysis Science Program, Grant DE-FG02-05ER15731; Office of Basic Energy Sciences, Division of Materials Science and Engineering, U.S. Department of Energy under Contract No. DE-AC02-05CH11231, by Structure and Dynamics of Material Interfaces Program (FWP KC31SM).
Mavrikakis acknowledges financial support from the Miller Institute at UC Berkeley through the Miller Visiting Professorship in the Department of Chemistry.
The team also used the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the US Department of Energy’s Office of Science under Contract No. DE-AC02-05CH11231 using NERSC BES award- ERCAP0022773.
Part of the computational work was performed using supercomputing resources at the Center for Nanomaterials, a DOE office of the Science User Facility located at Argonne National Laboratory, with support from DOE contract DE-AC02-06CH11357.