We are interested in designing nanostructured materials to produce hydrogen from green and renewable resources. Hydrogen is the most abundant element on the planet making up three-quarters of matter, with most of this available hydrogen tied up in molecules such as oxygenates and water. Hydrogen has a high energy content per unit weight (120.7 kJ/g). The widespread use of H2 as an energy carrier requires the development of efficient and renewable methods for its production.
1. Hydrogen production via steam reforming
Reforming is a chemical process where hydrogen-containing compounds react with steam, oxygen, or both into hydrogen-rich gas stream. Steam reforming is one of the most widely used technologies for hydrogen production, and achieved by reaction over a catalyst at elevated temperatures. The steam reforming of biomass-derived oxygenates draws much attention as a sustainable and potentially carbon-neutral process.
CxHyOz + H2O --> nCO + mCO2 + pH2
The initial step in steam reforming is dissociative adsorption of oxygenates on the metal sites of the catalysts; the formed surface species subsequently reacts with water\hydroxyls that are, in most cases, activated on oxide supports.
Our approach to understand this process consists of (1) design and fabrication of nanostructured catalysts that can efficiently convert oxygenates (e.g., bio-derived alcohols) to hydrogen; (2) understanding the roles of different surface active sites in the catalytic reforming processes; (3) figuring out the reactivity-structure correlations in reforming reactions; (4) fundamental mechanistic insights into the origin of deactivation on metal-based catalysts; (5) understanding of differences and similarities of the reforming process of mono- and poly-alcohols; and (6) exploration and manipulation of reaction pathways (e.g., the water-gas shift reaction and methanation) involved in the system. Current projects include:
●Steam reforming of bio-derived alcohols (e.g., ethanol, ethylene glycerol, and glycerin) on
supported metal clusters
●Promoting the resistance to sintering and coke deposition by rational catalyst design
●Studying reforming reactions on surface by ultra-high vacuum surface techniques
●Mechanistic investigations of steam reforming of methanol/ethanol on metal surfaces via DFT calculations
●Process intensification and optimization
2. Propane dehydrogenation to propylene
●Rational design and fabrication of effective Pt-based catalysts (e.g., PtCu/Al2O3, Pt/TiO2-Al2O3) and alternative non-noble metal oxide based catalysts
●Exploration of the nanostructure of designed catalysts and understanding the reaction pathways and functional mechanism of Pt-based catalysts
●Mechanistic studies of PDH and/or catalyst deactivation via DFT calculations
3. Selective oxidation of alcohols over solid acid catalysts
The selective oxidation of alcohols is an important step in synthesizing many valuable intermediates for the food, fragrance and pharmaceutical industries. This chemistry traditionally uses stoichiometric amounts of hazardous and toxic oxidants such as peroxides and chromates and generates large quantities of harmful waste. We aimed to develop a range of supported transition metals and oxides which are effective for the aerobic selective oxidation of alcohols to the corresponding aldehydes, ketenes, and esters under mild conditions. We have employed a number of advanced characterization tools to look at surface reaction and pathways of the reaction and the role that metal, oxide, and their interface play. Current projects include:
●Selective oxidation of methanol to dimethoxymethane over bifunctional hybrid oxides
●Mechanism and kinetics of selective oxidation of alcohols on supported metal clusters
Photo- & Electro-Catalysis
1. Hydrogen production via photoelectrochemical water splitting
●Hierarchical bottom-up approach to a new generation of photoanodes
●Fabrication of nanostructured photoanodes via reactive angle deposition
2. Fuel generation by photocatalytic CO2 reduction
●Investigation on the relationship between selectivity and CO2 reduction co-catalyst
●Surface modification of the photocatalysts to reduce the activation energy or overpotential for CO2 reduction
3. Well-controlled nanocatalysts for fuel cell-related reactions
Fuel cells are receiving extensive attention owing to their numerous advantages, including high efficiency, high specific energy density, and low pollution. The performance of a fuel cell is directly determined by the activity of its catalysts. Among various types of catalysts, the platinum-group metals (PGMs) are broadly used as the key catalysts in several kinds of fuel cells, such as proton exchange membrane fuel cell (PEMFC), direct formic acid fuel cell (DFAFC) and direct methanol fuel cell (DMFC). However, their low abundance in the earth’s crust and their ever increasing prices have created a major roadblock for the large-scale commercialization of PGMs-related fuel cells. We aimed to develop more active catalysts through tuning the utilization efficiency, exposed surfaces and composition of Pt- or Pd- based nanocrystals. The mechanism for relationship between the well-controlled nanocrystals and their performance in fuel cell-related electrocatalytic reactions are carefully investigated via DFT calculations. Current projects include:
●Shape-controlled synthesis of Pd-Au alloy with high-energy surfaces
●Preparation of Pt-based core-shell structure to achieve a high mass activity towards oxidation reduction reaction
●Rational design of Pt-free catalysts for oxidation reduction reaction
4. Selective oxidation of alcohols via photocatalysis
●Photocatalytic oxidation of benzyl alcohol over metal-oxides with expanded absorption range of irradiation
●Mechanism of photocatalytic oxidation over various photocatalysts
●Photocatalytic oxidation over oxides with oxidation and reduction cocatalysts which could improve the separation of electrons and holes.
Interfacial & Surface Catalysis
1. Gold catalysis for green chemical processes
Since then, gold-based heterogeneous catalysts have attracted much attention, particularly for low temperature CO oxidation, the water gas shift reaction, and selective oxidation. These subjects are now more intensively investigated, due to fundamental and applied aspects relevant to the support, particle size and shape, and structural sensitivity, especially in the context of catalysis, surface science, biology, nanoscience, and nanotechnology. Numerous studies have addressed how the structure and electronic properties of the Au surfaces and particles correlate with the catalytic activity. For example, the gold single crystal surfaces covered with atomic oxygen are highly reactive in a large number of reactions. The size of the Au nanoparticles and the properties of the support have been shown to be critical in giving rise to the unique catalytic activity. Furthermore, active sites have been proposed to reside at the interface between the Au nanoparticles and the oxide support. However, the size distribution and shapes of nanoparticles in oxide-supported catalysts often vary widely, and the particle structure, particularly at the metal–oxide interface, is generally not well-defined. Because of these complexities the active site and structure of Au-based catalysts remain unclear. Therefore, detailed mechanistic studies aimed at understanding gold’s promising catalytic characteristics are urgently needed.
2. Mechanistic study by computational chemistry
Exploration of catalyst reaction mechanisms is of fundamental importance in improving known catalysts or designing new catalysts. In recent years, a great number of the catalytic processes have been computationally studied using Density Functional Theory (DFT) calculations and other relative methods. Along with the development of computational chemistry methods, parallel computing and high-performance computing cluster, state-of-the-art computational chemistry researches not only uncover the essence of a known catalytic process, but also are used as a fast and low-cost pre-screening technic to assist new catalyst design.Currently, we are focusing on following projects
i. Mechanistic research on propane dehydrogenation to propylene: In order to gain deeper understanding of dehydrogenations of saturated hydrocarbons, we selected propane dehydrogenation reactions as our model reactions, which was catalyzed by Pt based catalyst. To facilitate determination of systematic trends in the propane dehydrogenationon Pt based catalyst, we will first investigate propane dehydrogenation on flat and stepped Pt and PtM alloy surfaces as well as interfaces of metal oxides, including MgO, Al2O3, and TiO2. They were selected for initial study as supports with at least one surface which matches the shape and size of the Pt(100) or Pt(111) surface. In a practical sense, the matched lattice dimensions provide a more uniform geometry between systems, thus facilitating initial development of correlations and Brønsted–Evans–Polanyi (BEP) relationships at the metal/support interfaces. By systematically permuting the alloy metal and nature of the substrates, we will establish correlations and reactivity patterns, including the development of BEP relationships. In the future, the analysis can be extended to other supported transition metal catalysts, and "volcano" relationships can be constructed between the predicted activity of different metal alloy/support structures and key catalytic parameters that are identified through the analysis.
ii. Development of Global Optimization Algorithm: One challenge to build a realistic catalyst model is to determining its most stable structure (global minimum) or set of lowest energy structures of a catalyst under reaction conditions. Although local minimum optimization technics have already been well developed, it could not guarantee the optimized structure to be the most stable one in case with complicated environment, like high adsorbate coverage, surface reconstruction, etc. Ideally, the global minimum can be located by exploring the whole potential energy surface with conducting numbers of local optimizations. We are interested in improvement of global optimization efficiency by reducing the number of local optimizations to obtain the desired global minimum with advanced computational algorithms like genetic algorithm, machine learning.