Sallye Gathmann

Figure showing the steps of water splitting. Multi-step transformation of water (left) to O2 (right) via water splitting. O: red; H: white; e-: yellow; H+: blue.

Did you know that many of the objects you use throughout the day were produced with the help of a catalyst? Catalysts are special materials that “speed up” chemical reactions. They are used in the production of familiar products like plastics, medicine, fertilizer, and fuels. In fact, scientists are working to develop new processes for making cost-competitive “clean” fuels, such as hydrogen (H2), which don’t emit harmful greenhouse gases like CO2. Improved catalysts will be at the heart of such processes.

Designing catalysts that work much better than what we have today is challenging. That’s because chemical reactions are complex, and catalysts must be designed to balance this complexity. Take water splitting as an example: while there is only one reactant (water) and two products (H2 and O2), there are several intermediate steps. A catalyst interacts with all chemical species, including those that are produced in the intermediate steps. This challenge of optimizing multiple processes on a single catalyst creates a reaction “speed limit” that is difficult to overcome. 

Researchers at the Center for Programmable Energy Catalysis (CPEC) are pioneering a new strategy to circumvent this catalytic speed limit. They developed a new type of catalyst, called a “catalytic condenser,” that can rapidly oscillate much like the capacitors in your computer. By applying an electrical bias across the catalytic condenser, charge is reversibly added or removed from the catalyst. This extra charge tunes how strongly the catalyst interacts with reaction intermediates, changing the reaction rate. In a recent publication, a team of CPEC scientists described how they can tune the performance of platinum (Pt), an expensive (but very good!) catalyst.1 The researchers used standard nanofabrication techniques to make the catalytic condenser structure, which behaves like a parallel plate capacitor. The condenser is a “sandwich” of materials: doped silicon, hafnium dioxide (HfO2), and a catalyst layer on top. Here, the catalyst layer is made of 2 nm Pt nanoclusters dispersed on graphene. The middle HfO2 layer is insulating, meaning it does not allow current to pass through it. This enables each end plate (the silicon and the catalyst) to store charge when an electrical bias is applied to the device. The researchers quantified the charge stored as ~1013 electrons per cm2 at a bias of ±6 V. While this is an enormous number, it’s actually several times lower than the number of active sites in the Pt film (metal surface atoms, ~1015 per cm2), meaning that only a fraction of an electron per site is added to the catalyst.2-4

Next, to understand how the charge condensation can alter catalysis, the researchers studied carbon monoxide (CO) desorption using a technique called temperature programmed desorption. This technique quantifies the binding energy of CO, which is a measure of how strongly the catalyst interacts with the CO. When the researchers applied a bias to the device, they observed a change in the binding energy. Overall, they measured a ±12 kJ/mol (ca. ±10%) change in CO binding energy across a ±6 V applied voltage window. At negative voltages, when extra electrons (negative charge) are stored in the Pt/graphene, the binding energy of CO decreases; conversely, positive voltages store holes (positive charge) and increase the binding energy. The team also discovered that the extra charge stored in the catalyst can be oscillated at kHz frequencies, a prerequisite to using these devices to enhance chemical reaction rates.

“CO adsorption on Pt is a model system. Studying this system allows us to gain fundamental insights about the catalyst and its properties,” said Dr. Tzia Ming Onn, a post-doctoral researcher at CPEC and lead author of the study.

In future experiments, researchers at CPEC plan to oscillate the charge stored in the catalytic condenser during a continuous reaction by oscillating the bias according to a desired waveform shape and frequency. They predict that doing so will increase the reaction rate by optimizing the catalyst to each step in a reaction sequence. By developing a fundamental understanding of how these “programmable” catalysts can accelerate chemistry, CPEC aims to overcome the catalytic speed limit for societally important reactions, such as those used to make fuels or fertilizer (e.g., methanol and ammonia synthesis). The team also hopes to enable the use of cheaper, more abundant materials (such as copper or nickel) as catalysts by improving the performance of such materials.

More Information

[1] Onn, T. M.; Gathmann, S. R.; Guo, S.; Solanki, S. P. S.; Walton, A.; Page, B. J.; Rojas, R.; Neurock, M.; Grabow, L. C.; Mkhoyan, K. A.; Abdelrahman, O. A.; Frisbie, C. D.; Dauenhauer, P. J. Platinum Graphene Catalytic Condenser for Millisecond Programmable Metal Surfaces. J. Am. Chem. Soc. 2022, 144 (48), 22113-22127.

[2] Shetty, M.; Walton, A.; Gathmann, S. R.; Ardagh, M. A.; Gopeesingh, J.; Resasco, J.; Birol, T.; Zhang, Q.; Tsapatsis, M.; Vlachos, D. G.; Christopher, P.; Frisbie, C. D.; Abdelrahman, O. A.; Dauenhauer, P. J. The Catalytic Mechanics of Dynamic Surfaces: Stimulating Methods for Promoting Catalytic Resonance. ACS Catal. 2020, 12 (21), 12666-12695.

[3] Ardagh, M. A.; Abdelrahman, O. A.; Dauenhauer, P. J. Principles of Dynamic Heterogeneous Catalysis: Surface Resonance and Turnover Frequency Response. ACS Catal. 2019, 9 (8), 6929-6937.

[4] Onn, T. M.; Gathmann, S. R.; Wang, Y.; Patel, R.; Guo, S.; Chen, H.; Soeherman, J. K.; Christopher, P.; Rojas, G.; Mkhoyan, K. A.; Neurock, M.; Abdelrahman, O. A.; Frisbie, C. D.; Dauenhauer, P. J. Alumina Graphene Catalytic Condenser for Programmable Solid Acids. JACS Au, 2022, 2 (5), 1123-1133.


Ref. (1) was supported by the Center for Programmable Energy Catalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences at the University of Minnesota under award #DE-SC0023464. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231. S.P.S.S. and L.C.G. acknowledge the use of the Opuntia, Sabine, and Carya Clusters provided by the Research Computing Data Core at the University of Houston. The authors also thank Keith and Amy Steva for their generous support of this project through their donor advised fund.

Refs. (2-3) were supported by the Catalysis Center for Energy Innovation, a U.S. Department of Energy – Energy Frontier Research Center under grant DE-SC0001004. These studies used resourced from the Minnesota Supercomputing Institute (MSI) at the University of Minnesota. 

S.R.G. acknowledges support from the National Science Foundation Graduate Research Fellowship under Grant CON-75851, Project 00074041.  Ref. (4) was supported by the U.S. Department of Energy, Basic Energy Sciences Catalysis program (DE-SC0021163) and the National Science Foundation CBET-Catalysis program (award #1937641). S.G. and K.A.M. were supported by University of Minnesota (UMN) MRSEC program DMR-2011401. The electron microscopy work was carried out in the Characterization Facility of University of Minnesota supported in part by the NSF through the UMN MRSEC.

About the author(s):

Sallye Gathmann is a Ph.D. Candidate and NSF Graduate Research Fellow at the University of Minnesota, where she is co-advised by Profs. Paul J. Dauenhauer and C. Daniel Frisbie. Within the Center for Programmable Energy Catalysis (CEPC), her research encompasses modeling- and nanofabrication-based investigation of programmable catalysts for renewable energy applications. ORCID: 0000-0002-1001-6650.

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