Rohit Vijay

Multivariate and Univariate Analysis of Infrared Imaging Data for High-Throughput Studies of NH3 Decomposition and NOx Storage and Reduction Catalysts

The application of Fourier transform infrared (FTIR) spectroscopic imaging for the analysis of the reaction products from parallel reactors has been extended to the quantitative analysis of complex infrared (IR) spectra. Multivariate factor-based and univariate calibration models were developed to extract quantitative concentration information from highly overlapped IR spectra. The three multivariate factor-based models of principal component regression (PCR) and partial least squares 1 and 2 (PLS-1 and PLS-2) were employed. The effects of the number of coadded mirror scans used in the data collection and the number of factors used in the data analysis on the predictive ability of this multivariate approach were characterized. The effectiveness of these approaches is demonstrated through application to the high-throughput study of ammonia decomposition and NOx storage and reduction catalysts.

High-throughput reactor system with individual temperature control for the investigation of monolith catalysts

A high-throughput parallel reactor system has been designed and constructed to improve the reliability of results from large diameter catalysts such as monoliths. The system, which is expandable, consists of eight quartz reactors, 23.5 mm in diameter. The eight reactors were designed with separate K type thermocouples and radiant heaters, allowing for the independent measurement and control of each reactor temperature. This design gives steady state temperature distributions over the eight reactors within 0.5 degrees C of a common setpoint from 50 to 700 degrees C. Analysis of the effluent from these reactors is performed using rapid-scan Fourier transform infrared (FTIR) spectroscopic imaging. The integration of this technique to the reactor system allows a chemically specific, truly parallel analysis of the reactor effluents with a time resolution of approximately 8 s. The capabilities of this system were demonstrated via investigation of catalyst preparation conditions on the direct epoxidation of ethylene, i.e., on the ethylene conversion and the ethylene oxide selectivity. The ethylene, ethylene oxide, and carbon dioxide concentrations were calibrated based on spectra from FTIR imaging using univariate and multivariate chemometric techniques. The results from this analysis showed that the calcination conditions significantly affect the ethylene conversion, with a threefold increase in the conversion when the catalyst was calcined for 3 h versus 12 h at 400 degrees C.

Design of Experiments Combined With High-Throughput Experimentation For The Optimization of DeNOx Catalysts

Abstract Design of experiments in combination with high-throughput experimentation (HTE) is a powerful toolbox for the systematic study of vast parameter spaces encountered in the design and optimization of heterogeneous catalysts. We will present the general approach as applied to NO x storage and reduction (NSR) catalysts using response surface analysis. Empirical models were developed to predict the catalyst performance as a function of cycle time, lean fraction of cycle time, and catalyst composition. These models provide useful insight about the factors controlling the NO x storage and NO x conversion of NSR catalysts. Using these empirical models, new catalyst formulations that maximize NO x conversion and selectivity to N 2 were found. In addition, high-throughput experimentation allows for simultaneous synthesis and screening of large arrays of different materials which further accelerates the discovery and optimization process. We have also tested a variety of new materials for NSR applications, composed of different transition metals added to standard Pt/Ba-based NSR catalysts, and have discovered that a noble metal free 5Co/15Ba catalyst stores NO x as efficiently as a standard 1Pt/15Ba NSR catalyst. Using the response surface strategy we have verified that the addition of Co to NSR catalsyts improves the performance at higher lean fractions, allowing a substantial improvement in the fuel efficiency. These studies clearly establish the utility of HTE when combined with design of experiments for the efficient analysis of such vast multidimensional systems and for the discovery of new materials, which is the guiding factor for any major technological advances.