Nanostructured Catalytic Materials for NOx Reduction Using Combinatorial MethodologiesEPA Grant Number: R830896
Title: Nanostructured Catalytic Materials for NOx Reduction Using Combinatorial Methodologies
Investigators: Senkan, Selim M.
Institution: University of California - Los Angeles
EPA Project Officer: Lasat, Mitch
Project Period: June 1, 2003 through May 31, 2007
Project Amount: $356,000
RFA: Environmental Futures Research in Nanoscale Science Engineering and Technology (2002) RFA Text | Recipients Lists
Research Category: Hazardous Waste/Remediation , Nanotechnology , Safer Chemicals
The objective of the proposed research program is to integrate combinatorial catalysis methodologies with nanostructured materials processing for the discovery, optimization, and better understanding of new, active and stable catalytic materials for the reduction of NOx under lean-burn conditions. These objectives will be accomplished by systematically exploring (for example via the genetic algorithm approach) a large number of different combinations of metals and nanostructured metal oxide supports. Recent developments in automotive engineering have made possible the production of more fuel efficient -up to 25% - lean burning gasoline engines. However, the lack of appropriate catalytic technology to reduce NOx emissions under lean burn conditions impedes the commercialization of such engines. Although the existing three-way catalysts allow for the effective control of CO, hydrocarbon (HC) and NOx emissions in current gasoline engines that operate under stoichiometric conditions, they are virtually useless in the presence of excess oxygen encountered in lean-burn engine exhausts. Therefore, the development of a new generation of catalysts that will allow NOx control in oxygen rich environments is urgently needed.
The following approaches will be undertaken: (1) Systematic generation of solid-state libraries of catalytic materials by impregnating or ion-exchanging standard pellets or powders of catalyst support materials. Pellets will be prepared by pressing powders of nanocrystalline metal oxide support materials such as TiO2, Al2O3, CeO2, ZnO, ZrO2, SiO2 and their mixtures as well as complex oxides, zeolites, and mesoporous materials. (2) High-throughput screening of libraries of catalytic materials using array channel microreactors and mass spectrometry. Catalyst testing will proceed by placing the pellets and/or powders of catalytic materials, together with selected duplicates and blanks, into the wells of the array microreactors. Reactor arrays will then be fed with simulated engine exhaust gases having the following composition ranges: NO=300-3000 ppm, C3H6=300-3000 ppm (other hydro-carbons will also be considered), O2=2-10%, H2O=5-15%, balance helium. Following the establishment of promising leads, the optimization of catalytic materials will be accomplished using the genetic algorithms. Surface characterization of promising catalytic materials will also be undertaken.
Nanostructured materials, broadly classified as nanocrystalline or nanoporous, offer exciting new opportunities for catalysis. These materials possess a very large number of low coordination number atoms at the edge and corner sites, which can provide a large number of catalytically active sites or sites for the incorporation of active metal atoms. Similarly, the ability to custom synthesize nanoporous materials, with controlled composition and uniform pore openings in the range 2-10 nm or larger, e.g. mesoporous crystalline materials (MCM), creates new possibilities in catalysis beyond those provided by zeolites. Although nanostructured materials can themselves be catalysts, their greatest potential, nevertheless, lies in their ability to serve as support structures for the dispersion of active metals. For example, through impregnation and ion exchange large diversities of metal-incorporated nanostructured catalytic materials will be systematically be prepared and tested for desired catalytic properties. We anticipate the discovery of new leads for catalytic materials for the reduction of NOx using propylene, followed by the optimization of these leads using genetic algorithms.