We describe here the main research areas the Kitchin Group has been active in. For each area we briefly describe what we have done, with reference to most of the publications that resulted from the work.

For a complete listing of our publications see ./publications.html.

1 Machine learned atomistic potentials

Molecular simulation continues to drive scientific progress. In all simulations, one of the main challenges is how to get good computational models to describe the chemistry and physics of the system. For decades we have relied on physical insight to build these models, but even these often have computationally practical approximations. A new approach using models derived by machine learning has developed in the past decade. In this approach, we use large databases of calculations from density functional theory to build neural network models of atomistic systems.

You can see our work in these papers.

A comparison of a neural network potential with ReaxFF for gold
Using a neural network potential to model coverage dependent adsorption
Using a neural network potential to model segregation in an alloy

This is an exciting new area we will be publishing in for the next few years!

2 Data sharing and functional scientific documents

We are huge proponents of using org-mode to write scientific documents. This has enabled our group to develop novel data sharing strategies kitchin-2015-examp,kitchin-2015-data-surfac-scien and increase our productivity significantly.

We recently published this work on automated data sharing kitchin-2017-autom-data.

3 Alloy catalysis

Alloy catalysts frequently do not have the same reactivity as the parent metals. We use density functional theory calculations to understand how the electronic structure of the alloy differs from the parent metals, and how those differences lead to different reactivities. We are especially interested in modeling heterogeneous site distributions boes-2015-estim-bulk, modeling XPS spectra of alloys boes-2015-core-cu, and the limit of single atom alloys tierney-2009-hydrog-dissoc.

We have used density functional theory to identify S-tolerant alloys inoglu-2011-ident-sulfur. Our current work will develop a new understanding of selectivity in acetylene hydrogenation.

PhD Jacob Boes: boes-2017-multis-model

4 Metal oxide reactivity

We are generally interested in understanding the reactivity of metal oxides towards oxygen and fuels. We use computational tools to model the electronic structure and reactivity of metal oxides for applications in water splitting and chemical looping.

We derived a number of heuristic rules that describe the reactivity of perovskites akhade-2011-effec,akhade-2012-effec. These principles were expanded into a concept of outer electrons that was used to describe the reactivity of a broad range of oxides calle-vallejo-2013-number. These observations have been found to be robust across a broad range of assumptions in the models used, although some care must be taken in a few cases curnan-2014-effec-concen. We have found novel relationships between oxide electronic structure and reactivity for oxides with rocksalt structures xu-2014-relat.

We did some work in infiltrating solid oxide fuel cell electrodes with electrocatalysts to improve their activity chao-2011-prepar-mesop,chao-2012-struc-relat.

An outstanding challenge in modeling oxides is the highly correlated electrons especially in the 3d orbitals of transition metals. We have expanded an approach to use a linear response method to compute U, making a nearly predictive, first-principles method for computing oxide formation energies with pretty good accuracy xu-2015-accur-u.

One new direction we have taken is to identify oxide polymorphs that may be grown as epitaxial thin films mehta-2015-ident-poten. Subsequent work xu-2017-first-princ has shown some design principles for predicting epitaxial stabilization, including the successful synthesis of columbite SnO2 wittkamper-2017-compet-growt.

PhD Robin Chao: chao-2012-improv-solid

5 Past research topics

We have worked in these research areas in the past, but are not currently actively working on them.

5.1 CO2 Capture

CO2 capture remains an important tool in considering how to mitigate the role of fossil energy on climate change rubin-2012. We have investigated the use of supported amines alesi-2010-co2-adsor, and a commercially available ion exchange resin as a CO2 capture sorbent alesi-2012-evaluat-primar. We have shown that supported amines are poisoned by SO2, but may they may be partially regenerated in some cases hallenbeck-2013-effec-o2.

We have used density functional theory calculations to model amine-CO2 reactions lee-2012-chemic-molec,mao-2013-inter, as well as process modeling to show that different process conditions are required to optimize a capture process for different solvents lee-2013-compar-co2. We have considered ionic liquids as potential CO2 capture solvents thompson-2014-co2-react.

We also have developed a high pressure silica capillary cell for in situ Raman measurements of CO2 solubility in solvents for precombustion capture applications. Our current interests include developing a microfluidic device for measuring CO2 absorption rates in amine-based solvents. We collaborate with the the Anna group on this.

We previously explored the electrochemical separation of CO2 from flue gas landon-2010-elect-concen,pennline-2010-separ-co2.

PhD Anita Lee: lee-2013-multi-scale

PhD Rich Alesi: walesi-2012-amine-based-sorben

5.2 Oxygen evolution electrocatalysis

We are using Raman spectroscopy to probe the oxide/electrolyte interface under oxygen evolution conditions. We have focused most of our work on Ni-oxide containing materials, which are highly active when promoted by Fe impurities landon-2012-spect-charac,michael-2015-alkal-elect. We have also examined Fe-containing molecular electrocatalysts demeter-2014-elect-oxygen.

We have used density functional theory to show that there are correlations in the reactions of the oxygen evolution reaction that likely limit the activity of oxide-based electrocatalysts man-2011-univer-oxygen. These observations are robust, even with advanced computational methods such as the linear response DFT+U methods xu-2015-linear-respon.

PhD James Landon: landon-2011-elect-oxygen-produc

PhD Ethan Demeter: demeter-2013-promot-base

5.3 Coverage dependent adsorption

Our earliest work was in modeling the coverage dependent adsorption energies of atomic adsorbates on late transition metal surfaces. We showed that there exist strong configurational correlations for many adsorbates on Pd(111) kitchin-2009-correl-pd, and for oxygen on late transition metal surfaces miller-2009-relat-au,miller-2011-config. These principles were generalized in a simple physical model inoglu-2010-simpl that showed the origin of the coverage dependence was an adsorbate-induced modification of the surface electronic structure. We wrote a review book chapter on this topic miller-2012-cover. We demonstrated that DFT can be used to interpret the coverage dependent desorption behavior of oxygen on Pt(111) miller-2014-simul-temper. Finally, we showed the generality of configurational correlations across many surfaces and for many adsorbates, demonstrating that geometric similarity is a requirement for correlation xu-2014-probin-cover.

PhD Spencer Miller: miller-2011-towar-under

PhD Nilay Inoglu: inoglu-2012-desig-sulfur