The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
The Degree of Rate Control: A Powerful Tool for Catalysis Research
Abstract
High Resolution Image Download MS PowerPoint Slide The “degree of rate control” (DRC) is a mathematical approach for analyzing multistep reaction mechanisms that has proven very useful in catalysis research. It identifies the “rate-controlling transition states and intermediates” (i.e., those whose DRCs are large in magnitude). Even in mechanisms with over 30 intermediates and transition states, these are generally just a few distinct chemical species whose energies, if they could be independently changed, would achieve a faster net reaction rate to the product of interest. For example, when there is a single “rate-determining step”, the DRC for its transition state (TS) is 1, which means (by definition) that if this TS’s energy could be decreased by k B T (where k B is Boltzmann’s constant and T is temperature), the net rate would increase by a factor of e . Because the (relative) energies of these key adsorbed intermediates and transition states can be adjusted by modifying the catalyst or solvent, or even a reactant’s molecular structure, the DRC values provide important ideas for catalyst improvement. The species with large DRCs are also the ones whose energetics must be most accurately measured or calculated to achieve an accurate kinetic model for any reaction mechanism. A tutorial on DRC analysis, the calculation of DRCs, and examples of the applications of DRCs in catalysis research is presented here. Applications of DRC analysis include the following: clarifying reaction kinetics, improving the accuracy of computational models, improving reaction conditions, improving choice of oxidant in selective oxidation, incorporation in algorithms which calculate net reaction rates of multistep mechanisms without solving the differential equations involved, and high-throughput computational screening of catalyst materials. Because DRC values can be determined experimentally, a full microkinetic model is not required to take advantage of DRC analysis.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Towards the computational design of solid catalysts
Nørskov, J. K., Bligaard, T., Rossmeisl, J., & Christensen, C. H. (2009) · Nature Chemistry · doi:10.1038/nchem.121 · Cited by 4,161
Computational high-throughput screening of electrocatalytic materials for hydrogen evolution
Greeley, J., Jaramillo, T. F., Bonde, J., Chorkendorff, I., & Nørskov, J. K. (2006) · Nature Materials · doi:10.1038/nmat1752 · Cited by 4,097
Alloys of platinum and early transition metals as oxygen reduction electrocatalysts
Greeley, J., Stephens, I. E. L., Bondarenko, A. S., Johansson, T. P., Hansen, H. A., Jaramillo, T. F., Rossmeisl, J., Chorkendorff, I., & Nørskov, J. K. (2009) · Nature Chemistry · doi:10.1038/nchem.367 · Cited by 3,203
Density functional theory in surface chemistry and catalysis
Nørskov, J. K., Abild-Pedersen, F., Studt, F., & Bligaard, T. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1006652108 · Cited by 2,611
From the Sabatier principle to a predictive theory of transition-metal heterogeneous catalysis
Medford, A. J., Vojvodic, A., Hummelshøj, J. S., Voss, J., Abild-Pedersen, F., Studt, F., Bligaard, T., Nilsson, A., & Nørskov, J. K. (2015) · Journal of Catalysis · doi:10.1016/j.jcat.2014.12.033 · Cited by 2,254
How to Conceptualize Catalytic Cycles? The Energetic Span Model
Kozuch, S., & Shaik, S. (2011) · Accounts of Chemical Research · doi:10.1021/ar1000956 · Cited by 1,859
The Brønsted–Evans–Polanyi relation and the volcano curve in heterogeneous catalysis
Bligaard, T., Nørskov, J. K., Dahl, S., Matthiesen, J., Christensen, C. H., & Sehested, J. (2004) · Journal of Catalysis · doi:10.1016/j.jcat.2004.02.034 · Cited by 1,713
Abild-Pedersen, F., Greeley, J., Studt, F., Rossmeisl, J., Munter, T. R., Moses, P. G., Skúlason, E., Bligaard, T., & Nørskov, J. K. (2007) · Physical Review Letters · doi:10.1103/physrevlett.99.016105 · Cited by 1,678
Activity Descriptors for CO 2 Electroreduction to Methane on Transition-Metal Catalysts
Peterson, A. A., & Nørskov, J. K. (2012) · The Journal of Physical Chemistry Letters · doi:10.1021/jz201461p · Cited by 1,667
Universality in Heterogeneous Catalysis
Nørskov, J. K., Bligaard, T., Logadottir, A., Bahn, S., Hansen, L. B., Bollinger, M., Bengaard, H., Hammer, B., Sljivancanin, Z., Mavrikakis, M., et al. (2002) · Journal of Catalysis · doi:10.1006/jcat.2002.3615 · Cited by 1,400
Ru–Pt core–shell nanoparticles for preferential oxidation of carbon monoxide in hydrogen
Alayoglu, S., Nilekar, A. U., Mavrikakis, M., & Eichhorn, B. (2008) · Nature Materials · doi:10.1038/nmat2156 · Cited by 1,245
Identification of Non-Precious Metal Alloy Catalysts for Selective Hydrogenation of Acetylene
Studt, F., Abild-Pedersen, F., Bligaard, T., Sørensen, R. Z., Christensen, C. H., & Nørskov, J. K. (2008) · Science · doi:10.1126/science.1156660 · Cited by 1,199
Alloy catalysts designed from first principles
Greeley, J., & Mavrikakis, M. (2004) · Nature Materials · doi:10.1038/nmat1223 · Cited by 1,156
Discovery of a Ni-Ga catalyst for carbon dioxide reduction to methanol
Studt, F., Sharafutdinov, I., Abild-Pedersen, F., Elkjær, C. F., Hummelshøj, J. S., Dahl, S., Chorkendorff, I., & Nørskov, J. K. (2014) · Nature Chemistry · doi:10.1038/nchem.1873 · Cited by 1,071
On the Mechanism of Low-Temperature Water Gas Shift Reaction on Copper
Gokhale, A. A., Dumesic, J. A., & Mavrikakis, M. (2008) · Journal of the American Chemical Society · doi:10.1021/ja0768237 · Cited by 984
Degree of Rate Control: How Much the Energies of Intermediates and Transition States Control Rates
Stegelmann, C., Andreasen, A., & Campbell, C. T. (2009) · Journal of the American Chemical Society · doi:10.1021/ja9000097 · Cited by 576
Self-citationWellendorff, J., Silbaugh, T. L., Garcia-Pintos, D., Nørskov, J. K., Bligaard, T., Studt, F., & Campbell, C. T. (2015) · Surface Science · doi:10.1016/j.susc.2015.03.023 · Cited by 572
Self-citationKozuch, S., & Shaik, S. (2006) · Journal of the American Chemical Society · doi:10.1021/ja0559146 · Cited by 553
Grabow, L. C., Gokhale, A. A., Evans, S. T., Dumesic, J. A., & Mavrikakis, M. (2008) · The Journal of Physical Chemistry C · doi:10.1021/jp7099702 · Cited by 525
CatMAP: A Software Package for Descriptor-Based Microkinetic Mapping of Catalytic Trends
Medford, A. J., Shi, C., Hoffmann, M. J., Lausche, A. C., Fitzgibbon, S. R., Bligaard, T., & Nørskov, J. K. (2015) · Catalysis Letters · doi:10.1007/s10562-015-1495-6 · Cited by 495
Reuter, K., & Scheffler, M. (2003) · Physical Review Letters · doi:10.1103/physrevlett.90.046103 · Cited by 464
New design paradigm for heterogeneous catalysts
Vojvodic, A., & Nørskov, J. K. (2015) · National Science Review · doi:10.1093/nsr/nwv023 · Cited by 408
Hydrogen Evolution Over Bimetallic Systems: Understanding the Trends
Greeley, J., Nørskov, J. K., Kibler, L. A., El‐Aziz, A. M., & Kolb, D. M. (2006) · ChemPhysChem · doi:10.1002/cphc.200500663 · Cited by 394
Toward computational screening in heterogeneous catalysis: Pareto-optimal methanation catalysts
ANDERSSON, M., BLIGAARD, T., KUSTOV, A., LARSEN, K., GREELEY, J., JOHANNESSEN, T., CHRISTENSEN, C., & NORSKOV, J. (2006) · Journal of Catalysis · doi:10.1016/j.jcat.2006.02.016 · Cited by 366
Reuter, K., & Scheffler, M. (2006) · Physical Review B · doi:10.1103/physrevb.73.045433 · Cited by 359
Kozuch, S., & Shaik, S. (2008) · The Journal of Physical Chemistry A · doi:10.1021/jp8004772 · Cited by 347
A First-Principles Study of Methanol Decomposition on Pt(111)
Greeley, J., & Mavrikakis, M. (2002) · Journal of the American Chemical Society · doi:10.1021/ja017818k · Cited by 345
The Steady State of Heterogeneous Catalysis, Studied by First-Principles Statistical Mechanics
Reuter, K., Frenkel, D., & Scheffler, M. (2004) · Physical Review Letters · doi:10.1103/physrevlett.93.116105 · Cited by 321
Campbell, C. T. (1994) · Topics in Catalysis · doi:10.1007/bf01492288 · Cited by 314
Self-citationPropane Aromatization over HZSM‐5 and Ga/HZSM‐5 Catalysts
Bhan, A., & Nicholas Delgass, W. (2008) · Catalysis Reviews · doi:10.1080/01614940701804745 · Cited by 305
Finding the Rate-Determining Step in a Mechanism
Campbell, C. T. (2001) · Journal of Catalysis · doi:10.1006/jcat.2001.3396 · Cited by 289
Self-citationToward Benchmarking in Catalysis Science: Best Practices, Challenges, and Opportunities
Bligaard, T., Bullock, R. M., Campbell, C. T., Chen, J. G., Gates, B. C., Gorte, R. J., Jones, C. W., Jones, W. D., Kitchin, J. R., & Scott, S. L. (2016) · ACS Catalysis · doi:10.1021/acscatal.6b00183 · Cited by 285
Self-citationAutomatic analysis of computed catalytic cycles
Uhe, A., Kozuch, S., & Shaik, S. (2011) · Journal of Computational Chemistry · doi:10.1002/jcc.21669 · Cited by 279
Molecular-level descriptions of surface chemistry in kinetic models using density functional theory
Gokhale, A. A., Kandoi, S., Greeley, J. P., Mavrikakis, M., & Dumesic, J. A. (2004) · Chemical Engineering Science · doi:10.1016/j.ces.2004.09.038 · Cited by 272
Ab Initio Thermodynamics and First-Principles Microkinetics for Surface Catalysis
Reuter, K. (2016) · Catalysis Letters · doi:10.1007/s10562-015-1684-3 · Cited by 222
Activity and Selectivity Trends in Synthesis Gas Conversion to Higher Alcohols
Medford, A. J., Lausche, A. C., Abild-Pedersen, F., Temel, B., Schjødt, N. C., Nørskov, J. K., & Studt, F. (2014) · Topics in Catalysis · doi:10.1007/s11244-013-0169-0 · Cited by 208
Microkinetic modeling of ethylene oxidation over silver
Stegelmann, C., Schiødt, N. C., Campbell, C. T., & Stoltze, P. (2004) · Journal of Catalysis · doi:10.1016/j.jcat.2003.10.004 · Cited by 202
Self-citationMicrokinetic simulation of catalytic reactions
Stoltze, P. (2000) · Progress in Surface Science · doi:10.1016/s0079-6816(00)00019-8 · Cited by 200
Linic, S. (2003) · Journal of Catalysis · doi:10.1016/s0021-9517(02)00156-2 · Cited by 197
Large-scale, density functional theory-based screening of alloys for hydrogen evolution
Greeley, J., & Nørskov, J. K. (2007) · Surface Science · doi:10.1016/j.susc.2007.01.037 · Cited by 194
Hindered Translator and Hindered Rotor Models for Adsorbates: Partition Functions and Entropies
Sprowl, L. H., Campbell, C. T., & Árnadóttir, L. (2016) · The Journal of Physical Chemistry C · doi:10.1021/acs.jpcc.5b11616 · Cited by 186
Self-citationRates and mechanisms of chemical reactions
Gardiner, W. C. (1969) · Andalas University Repository (Andalas University) · Cited by 173
Avanesian, T., Gusmão, G. S., & Christopher, P. (2016) · Journal of Catalysis · doi:10.1016/j.jcat.2016.03.016 · Cited by 154
Campbell, C. T., Sprowl, L. H., & Árnadóttir, L. (2016) · The Journal of Physical Chemistry C · doi:10.1021/acs.jpcc.6b00975 · Cited by 148
Self-citationDegree of rate control approach to computational catalyst screening
Wolcott, C. A., Medford, A. J., Studt, F., & Campbell, C. T. (2015) · Journal of Catalysis · doi:10.1016/j.jcat.2015.07.015 · Cited by 140
Self-citationZhao, Z., Li, Z., Cui, Y., Zhu, H., Schneider, W. F., Delgass, W. N., Ribeiro, F. H., & Greeley, J. (2016) · Journal of Catalysis · doi:10.1016/j.jcat.2016.11.008 · Cited by 136
Lattice strain effects on CO oxidation on Pt(111)
Grabow, L. C., Xu, Y., & Mavrikakis, M. (2006) · Physical Chemistry Chemical Physics · doi:10.1039/b606131a · Cited by 105
Rate Control and Reaction Engineering
Nørskov, J. K., Bligaard, T., & Kleis, J. (2009) · Science · doi:10.1126/science.1174885 · Cited by 87
Partial Oxidation of Methanol on MoO3 (010): A DFT and Microkinetic Study
Choksi, T. S., & Greeley, J. (2016) · ACS Catalysis · doi:10.1021/acscatal.6b01633 · Cited by 85
Mavrikakis, M. (2006) · Nature Materials · doi:10.1038/nmat1767 · Cited by 54
Analysis of reaction schemes using maximum rates of constituent steps
Motagamwala, A. H., & Dumesic, J. A. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1605742113 · Cited by 43
Avanesian, T., & Christopher, P. (2016) · ACS Catalysis · doi:10.1021/acscatal.6b01547 · Cited by 28
Water-assisted oxygen activation during selective oxidation reactions
Tran, H.-V., Doan, H. A., Chandler, B. D., & Grabow, L. C. (2016) · Current Opinion in Chemical Engineering · doi:10.1016/j.coche.2016.08.010 · Cited by 27
Cited by
Huang, J., Sheng, H., Ross, R. D., Han, J., Wang, X., Song, B., & Jin, S. (2021) · Nature Communications · doi:10.1038/s41467-021-23390-8 · Cited by 707
Electrocatalysis in Alkaline Media and Alkaline Membrane-Based Energy Technologies
Yang, Y., Peltier, C. R., Zeng, R., Schimmenti, R., Li, Q., Huang, X., Yan, Z., Potsi, G., Selhorst, R., Lu, X., et al. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00331 · Cited by 544
Microkinetic Modeling: A Tool for Rational Catalyst Design
Motagamwala, A. H., & Dumesic, J. A. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.0c00394 · Cited by 485
Machine learning for heterogeneous catalyst design and discovery
Goldsmith, B. R., Esterhuizen, J., Liu, J., Bartel, C. J., & Sutton, C. (2018) · AIChE Journal · doi:10.1002/aic.16198 · Cited by 444
Computational Approach to Molecular Catalysis by 3d Transition Metals: Challenges and Opportunities
Vogiatzis, K. D., Polynski, M. V., Kirkland, J. K., Townsend, J., Hashemi, A., Liu, C., & Pidko, E. A. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00361 · Cited by 423
Metadata
- Authors
- Campbell, C. T.
- Venue
- ACS Catalysis
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-03-21
- Volume
- 7
- Issue
- 4
- Pages
- 2770-2779
- ISSN
- 2155-5435 (ISSN-L)
- OpenAlex
- W2593663142
- Cited by
- 572
- References
- 53
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.