(4el) Predictive Models for Speeding Up Catalyst Discovery

Catalytic materials are essential components in ~90% of the world’s large-scale chemical processes. It is, however, astonishing that all industrial catalysts used today were discovered via costly and time-consuming empirical testing, and far from optimized for energy efficiency and product selectivity. Recent developments of density functional theory (DFT) and the emerging catalysis informatics project have led to an unprecedented atomic-scale understanding of the complex processes occurring on catalyst surfaces and an identification of potentially improved catalysts from first-principles. However, the immense phase space of catalytic materials spanned by structural and compositional degrees of freedom precludes thorough screening, even with combinatorial quantum-chemical calculations and high-throughput experiments. Development of predictive structure-reactivity models for rapid discovery of novel catalytic materials still remains a grant challenge in fundamental catalysis.

During my PhD studies under the supervision of Prof. Suljo Linic, we developed a general theoretical framework for understanding variations in the surface reactivity of transition metals upon a perturbation of their electronic properties. I will discuss this framework on three applications: 1) rapid screening of Pt multimetallic electrocatalysts for the oxygen reduction reaction in PEM fuel cells; 2) understanding of alkali promotion mechanisms for oxidation reactions on Ag surfaces; 3) coupling of thermal energies and energetic electrons for chemical bond activation on optically-excited plasmonic Ag nanoparticles. Each model system is characterized by one specific type of perturbation, introduced either by alloying with impurity elements, by doping of substrates with chemical promoters, or by exposing plasmonic nanoparticles to visible photons. Our study opened up a new path for designing highly efficient and selective chemical, electrochemical, and photochemical processes.

My post-doctoral research with Prof. Jens Nørskov and Dr. Frank Abild-Pedersen aims to obtain a detailed understanding of the surface reactivity of complex materials using DFT calculations and molecular dynamics (MD) simulations. One of such systems involves transition metal alloys that are outliers of the d-band model description of surface chemisorption. Another system of importance is associated with transition metal oxides that are computationally cumbersome to describe with reasonable accuracy due to strong electronic correlations. Establishing structure-reactivity relationships for these systems becomes tremendously important for the rapid discovery of highly-efficient and cost-effective materials for chemical manufacturing, renewable energy generation and storage, etc.

My future research interests focus on dynamic aspects of chemical reactions driven by energetic charge carriers. My knowledge and experience on multiscale modeling has provided me a unique opportunity to tackle those challenges in energy related catalyst design. The objective is to develop 1) an ab-inito mechanistic understanding of chemical energetics and excited-state dynamics of molecule-surface interactions, and 2) predictive models that link easily accessible physical characteristics of constituent components of catalytic materials to their surface reactivity.

Relevant publications:

1. H. Xin, N. Schweitzer, E. Nikolla, S. Linic, J. Chem. Phys., 132, 111101, (2010)
2. N. Schweitzer, H. Xin, E. Nikolla, J.T. Miller, S. Linic, Top Catal, 53, 348, (2010)
3. H. Xin, S. Linic, J. Chem. Phys., 132, 221101, (2010)
4. P. Christopher, H. Xin, S. Linic, Nature Chem., 3, 467, (2011)
5. H. Xin, A. Holewinski, S. Linic, ACS Catal., 2, 12, (2012)
6. H. Xin, A. Holewinski, N. Schweitzer, E. Nikolla, S. Linic, Top Catal, 55, 376, (2012)
7. P. Christopher, H. Xin, A. Marimuthu, S. Linic, Nature Mater. 11, 1044, (2012)
8. S. Linic, P. Christopher, H. Xin, A. Marimuthu, Acc. Chem. Res., accepted (2013)
9. A. Holewinski, H. Xin, E. Nikolla and S. Linic, Curr Opin Chem Eng., accepted (2013)