Date of Award


Document type


Access Type

Open Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Chemical Engineering

First Advisor

Scott M. Auerbach

Second Advisor

George W. Huber

Third Advisor

Wm. Curtis Conner

Subject Categories

Chemical Engineering


Lignocellulosic biomass is a significant pool of energy resource, which can be harnessed to supplement or replace the dwindling fossil fuel reserves. This requires development of economically viable means to efficiently convert biomass to biofuels. A major requirement in biofuel industry is to develop highly active, selective and stable catalysts. Zeolites are an important class of micro-porous crystalline solids, and have proven to be effective and stable acid catalysts for a variety of petrochemical and fine-chemical processes. Nitrided zeolites -- i.e., those with Si-O-Si and Si-OH-Al groups substituted by Si-NH-Si and Si-NH2-Al -- have shown promise as shape-selective basic catalysts, and are potential candidates for biofuel production catalysts. In the first part of this dissertation, the stability and base characteristics of nitrided zeolites have been explored. The nitridation mechanism in HY and silicate type zeolites is computed by first time implementation of embedded-cluster procedure with nudged-elastic-band method of finding elusive transition states. The stability of nitrided sites is investigated by modeling the kinetics of nitridation in reverse, going back to untreated zeolite plus ammonia. Our calculations suggest that nitrided silicalite and HY zeolites require high temperatures to form, but once formed, they remain relatively stable, auguring well for their use as shape-selective base catalysts. In addition, a systematic study of base strength versus aluminium content or alkali cation of nitrided zeolites is also performed. Our studies suggest that K-N-Y (Si:Al = 11) optimizes the balance of activity, stability and cost. Pyrolysis of lignocellulosic biomass is a burgeoning technology to obtain renewable fuels. Commercializing pyrolysis would require efficient process design, especially reactors as they are one of the most energy intensive units in the whole process. This would in turn require detailed understanding of complex pyrolysis chemistries. Biomass is mainly composed of the biopolymer cellulose; therefore, understanding cellulose pyrolysis chemistries is important for efficiently modeling and optimizing pyrolysis reactors. In the second part of this dissertation, the mechanism(s) of conversion of crystalline cellulose to precursors of major products in cellulose pyrolysis have been explored. As the first step, the transformation of cellulose Iβ to a high-temperature (550 K) structure is modeled by computing infrared (IR) spectra as a probe of hydrogen bonding using constant-pressure classical molecular-dynamics simulations. To assist in the analysis of IR spectra, a novel synthesis of normal mode analysis and power spectrum methods is developed to assign the O-H stretches. Simulated IR spectra at elevated temperatures suggests a structural transformation above 450 K, a result in agreement with experimental IR results. The low-temperature (300-400 K) structure is found to be dominated by intrachain hydrogen bonds, whereas in the high-temperature structure (450- 550 K), many of these intrachain hydrogen bonds transform to longer, weaker interchain hydrogen bonds. Next, the subsequent decomposition of cellulose is modeled at 600 and 873 K using Car-Parrinello molecular- dynamics simulations and the metadynamics method. The computed nascent processes can explain the formation of precursors to major products observed during cellulose pyrolysis such as levoglucosan (LGA), hydroxy-methylfurfurral (HMF) and fragmentation products such as formic acid. LGA is found to be kinetically and thermodynamically favorable in comparison to other products, which explains why LGA is the major product observed during cellulose pyrolysis. The molecular insights presented in this part of the study will be helpful in developing detailed kinetic models for optimizing pyrolysis reactors.