A computational investigation of nucleation processes in organic crystals

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, February 2008.Includes bibliographical references.Nucleation processes are ubiquitous in nature and technology. For instance, cloud formation in the atmosphere, the casting of metals, protein crystallization, biomineralization, the production of porous materials, and separation of pharmaceutical compounds from solution are a few examples of relevant nucleation processes. One pathway for nucleation to occur is homogeneous nucleation, in which an embryo of a more stable phase forms within an original metastable medium. Homogeneous nucleation is an activated process, meaning that a free energy barrier must be overcome for the transition to take place, and the height of the free energy barrier determines the rate at which the process will occur. Despite considerable advances in both theoretical and experimental techniques to date, determining nucleation mechanisms for real systems remains a considerable technical challenge. The aim of this thesis is therefore to apply molecular simulation techniques to elucidate nucleation mechanisms in organic crystals. Specifically, the newly developed methods of aimless shooting and likelihood maximization are applied for the first time to study nucleation processes in complex and technically relevant systems. The first portion of the thesis examines polymorphism, or the ability of a material to pack in different crystal lattices whilst retaining the same chemical composition. Transformation to a more stable polymorph can readily occur in the solid state, which has broad implications in pharmaceutical processing. To date, over 160 mechanisms have been proposed for polymorph transitions in the solid state, but none have been definitively verified. A model compound, terephthalic acid, is chosen for computational studies because it is similar in size to a small molecule therapeutic and exhibits a common bonding motif for organic crystals. Using aimless shooting and likelihood maximization, the mechanism of the solid state polymorph transformation in terephthalic acid is shown to be comer nucleation. The mechanism shows that for a given nucleus size, the interfacial area between the crystalline domains is minimized, thus reducing the unfavorable surface free energy penalty required for nucleation to occur.(cont.) Furthermore, based on the results presented, it is anticipated that corner nucleation may be a common mechanism for many polymorph transformations in hydrogen bonded crystalline materials. The second portion of the thesis investigates the mechanism of freezing a subcooled liquid to form a crystal. This phenomenon has widespread application across many technical domains. Similar studies to date on freezing have been limited to model systems, such as Lennard-Jones particles or hard spheres. Benzene is chosen as a model compound. A periodic system is constructed and aimless shooting and likelihood maximization are applied to determine the nature of the critical nucleus. Local order analysis is implemented to distinguish among solid and liquid-like molecules. Preliminary results indicate that the critical nucleus is on the order of 200-300 molecules at 50 K subcooling. This thesis demonstrates that the complementary molecular simulation techniques of aimless shooting and likelihood maximization offer fundamental insight into nucleation mechanisms in molecular crystals. Knowledge of the mechanism from likelihood maximization is essential for accurate free energies and pathway optimization methods, and it should therefore be applied in computational studies of rare events prior to free energy or rate constant calculations. Moreover, these methods provide quantitative understanding of the important physical variables that determine experimentally observable rates and can further aid in experimental design.by Gregg Tyler Beckham.Ph.D

Classification of Multi-Domain Glycoside Hydrolases to Aid in the Enzymatic Production of Biofuels from Biomass

Biomass conversion to renewable biofuels provides an alternative to conventional fossil-fuel based transportation fuels and a means to reduce dependence on foreign oil. However, plant cell walls have evolved to be quite resistant to enzymatic deconstruction, a phenomenon generally termed biomass recalcitrance. As enzymes represent a substantial cost in biofuels production, there is significant impetus to understand and improve their efficiency in converting cell wall carbohydrates to fermentable sugars. Much research has been conducted on single free enzymes with one catalytic unit per protein and on the much larger, complexed cellulosomes with many tens of catalytic units per protein, but little work has been done on multi-domain enzymes that are an interpolation in size between free enzymes and cellulosomes. A bioinformatics study on multi-domain glycoside hydrolases was conducted to gather information on the various ways each family is found and organized in nature. GH61s, GH6s and GH7s in particular have been classified based on order of protein domain, catalytic domain, carbohydrate binding module, linker length, and origin. It is hoped that this will eventually become a complete database of multi-domain enzymes that will aid in the development of cost-effective methods of lignocellulosic biomass conversion

Machine learning reveals sequence-function relationships in family 7 glycoside hydrolases

Family 7 glycoside hydrolases (GH7) are among the principal enzymes for cellulose degradation in nature and industrially. These enzymes are often bimodular, including a catalytic domain and carbohydrate-binding module (CBM) attached via a flexible linker, and exhibit an active site that binds cello-oligomers of up to ten glucosyl moieties. GH7 cellulases consist of two major subtypes: cellobiohydrolases (CBH) and endoglucanases (EG). Despite the critical importance of GH7 enzymes, there remain gaps in our understanding of how GH7 sequence and structure relate to function. Here, we employed machine learning to gain data-driven insights into relation-ships between sequence, structure, and function across the GH7 family. Machine-learning models, trained only on the number of residues in the active-site loops as features, were able to discriminate GH7 CBHs and EGs with up to 99% ac-curacy, demonstrating that the lengths of loops A4, B2, B3, and B4 strongly correlate with functional subtype across the GH7 family. Classification rules were derived such that specific residues at 42 different sequence positions each predicted the functional subtype with accuracies surpassing 87%. A random forest model trained on residues at 19 positions in the catalytic domain predicted the presence of a CBM with 89.5% accuracy. Our machine learning results recapitulate, as top-performing features, a substantial number of the sequence positions determined by previous experimental studies to play vital roles in GH7 activity. We surmise that the yet-to-be-explored sequence positions among the top-performing features also contribute to GH7 functional variation and may be exploited to understand and manipulate function

Reductive Catalytic Fractionation of Corn Stover Lignin

Reductive catalytic fractionation (RCF) has emerged as an effective biomass pretreatment strategy to depolymerize lignin into tractable fragments in high yields. We investigate the RCF of corn stover, a highly abundant herbaceous feedstock, using carbon-supported Ru and Ni catalysts at 200 and 250 °C in methanol and, in the presence or absence of an acid cocatalyst (H₃PO₄ or an acidified carbon support). Three key performance variables were studied: (1) the effectiveness of lignin extraction as measured by the yield of lignin oil, (2) the yield of monomers in the lignin oil, and (3) the carbohydrate retention in the residual solids after RCF. The monomers included methyl coumarate/ferulate, propyl guaiacol/syringol, and ethyl guaiacol/syringol. The Ru and Ni catalysts performed similarly in terms of product distribution and monomer yields. The monomer yields increased monotonically as a function of time for both temperatures. At 6 h, monomer yields of 27.2 and 28.3% were obtained at 250 and 200 °C, respectively, with Ni/C. The addition of an acid cocatalysts to the Ni/C system increased monomer yields to 32% for acidified carbon and 38% for phosphoric acid at 200 °C. The monomer product distribution was dominated by methyl coumarate regardless of the use of the acid cocatalysts. The use of phosphoric acid at 200 °C or the high temperature condition without acid resulted in complete lignin extraction and partial sugar solubilization (up to 50%) thereby generating lignin oil yields that exceeded the theoretical limit. In contrast, using either Ni/C or Ni on acidified carbon at 200 °C resulted in moderate lignin oil yields of ca. 55%, with sugar retention values >90%. Notably, these sugars were amenable to enzymatic digestion, reaching conversions >90% at 96 h. Characterization studies on the lignin oils using two-dimensional heteronuclear single quantum coherence nuclear magnetic resonance and gel permeation chromatrography revealed that soluble oligomers are formed via solvolysis, followed by further fragmentation on the catalyst surface via hydrogenolysis. Overall, the results show that clear trade-offs exist between the levels of lignin extraction, monomer yields, and carbohydrate retention in the residual solids for different RCF conditions of corn stover.National Science Foundation (U.S.) (1454299

Technoeconomic and life-cycle analysis of single-step catalytic conversion of wet ethanol into fungible fuel blendstocks

Technoeconomic and life-cycle analyses are presented for catalytic conversion of ethanol to fungible hydrocarbon fuel blendstocks, informed by advances in catalyst and process development. Whereas prior work toward this end focused on 3-step processes featuring dehydration, oligomerization, and hydrogenation, the consolidated alcohol dehydration and oligomerization (CADO) approach described here results in 1-step conversion of wet ethanol vapor (40 wt% in water) to hydrocarbons and water over a metal-modified zeolite catalyst. A development project increased liquid hydrocarbon yields from 36% of theoretical to >80%, reduced catalyst cost by an order of magnitude, scaled up the process by 300-fold, and reduced projected costs of ethanol conversion 12-fold. Current CADO products conform most closely to gasoline blendstocks, but can be blended with jet fuel at low levels today, and could potentially be blended at higher levels in the future. Operating plus annualized capital costs for conversion of wet ethanol to fungible blendstocks are estimated at $2.00/GJ for CADO today and$1.44/GJ in the future, similar to the unit energy cost of producing anhydrous ethanol from wet ethanol ($1.46/GJ). Including the cost of ethanol from either corn or future cellulosic biomass but not production incentives, projected minimum selling prices for fungible blendstocks produced via CADO are competitive with conventional jet fuel when oil is$100 per barrel but not at $60 per barrel. However, with existing production incentives, the projected minimum blendstock selling price is competitive with oil at$60 per barrel. Life-cycle greenhouse gas emission reductions for CADO-derived hydrocarbon blendstocks closely follow those for the ethanol feedstock

Promoting microbial utilization of phenolic substrates from bio-oil

The economic viability of the biorefinery concept is limited by the valorization of lignin. One possible method of lignin valorization is biological upgrading with aromatic-catabolic microbes. In conjunction, lignin monomers can be produced by fast pyrolysis and fractionation. However, biological upgrading of these lignin monomers is limited by low water solubility. Here, we address the problem of low water solubility with an emulsifier blend containing approximately 70 wt% Tween® 20 and 30 wt% Span® 80. Pseudomonas putida KT2440 grew to an optical density (OD600) of 1.0 ± 0.2 when supplied with 1.6 wt% emulsified phenolic monomer-rich product produced by fast pyrolysis of red oak using an emulsifier dose of 0.076 ± 0.002 g emulsifier blend per g of phenolic monomer-rich product. This approach partially mitigated the toxicity of the model phenolic monomer p-coumarate to the microbe, but not benzoate or vanillin. This study provides a proof of concept that processing of biomass-derived phenolics to increase aqueous availability can enhance microbial utilization