The depletion of conventional oil reservoirs forced companies and consequently researchers to pursue alternatives such as resources that in the past were considered not economically viable, in consequence of the high depth, low porosity and permeability of the play zone. The exploration challenges were overcome mainly by the development of horizontal drilling and hydraulic fracturing. However, the extremely high temperatures and pressures, in association to a complex nanopore structure, in which reservoir fluids are now encountered, instigate further investigation of fluid phase behavior and composition, and challenge conventional macroscale reservoir simulation predictions. Moreover, the unusual high temperatures and pressures have increased the cost as well as the hazardous level for reservoir analyzes by lab experiments. Molecular Dynamics (MD) simulation of reservoirs can be a safe and inexpensive alternative tool to replicate reservoir pore and fluid conditions, as well as to monitor fluid behavior. In this study, a MD simulation of nanoconfinement effect on hydrocarbon fluid phase and compositional behavior in organic shale rocks is presented. Chapter 1 reviews and discusses previous works on MD simulations of geological resources. With the knowledge acquired, a fully atomistic squared graphite pore is proposed and applied to study hydrocarbon fluid phase and compositional behavior in organic shale rocks in Chapter 2. Results demonstrate that nano-confinement increases fluid mass density, which can contribute to phase transition, and heptane composition inside studied pores. The higher fluid density results in an alteration of oil in place (OIP) prediction by reservoir simulations, when nano-confinement effect is not considered. / Master of Science / Petroleum sub products are present in the day to day life of almost any human. The list include gasoline, plastics, perfumes, medications, polyester for clothing. Petroleum is naturally encountered in the void space, known as pores, inside rocks at reservoirs thousands of feet underground. In the past, the pores of oil reservoirs in development were larger and interconnected, which facilitates its extraction and reserve predictions. Most of reservoirs being developed nowadays have pores in the nanoscale and with poor interconnection as well as higher reservoir temperatures and pressure. These "new conditions", instigates further investigation of fluid phase behavior and composition, and challenge macroscale reservoir simulation predictions. In this study, the effect of decrease in pore size, as well as higher temperature and pressure conditions, in fluid behavior and composition is studied. Chapter 1 reviews and discusses previous works on geological resources modeling and simulation. With the knowledge acquired, a fully squared shale pore is proposed and applied to study hydrocarbon fluid phase and compositional behavior in organic shale rocks in Chapter 2. Results demonstrate that pores in the nanoscale region tend to increase fluid mass density, which can contribute to phase transition, and heptane composition inside studied pores. The higher fluid density results in an underestimation of reserves prediction by reservoir simulations, when the change in density is not considered.

No / Martensitic transformations are of considerable technological importance, a particularly promising application being the possibility of using martensitic materials, possibly proteins, as tiny machines. For organic crystals, however, a molecular level understanding of such transformations is lacking. We have studied a martensitic-type transformation in crystals of the amino acid DL-norleucine using molecular dynamics simulation. The crystal structures of DL-norleucine comprise stacks of bilayers (formed as a result of strong hydrogen bonding) that translate relative to each other on transformation. The simulations reveal that the transformation occurs by concerted molecular displacements involving entire bilayers rather than on a molecule-by-molecule basis. These observations can be rationalized on the basis that at sufficiently high excess temperatures, the free energy barriers to concerted molecular displacements can be overcome by the available thermal energy. Furthermore, in displacive transformations, the molecular displacements can occur by the propagation of a displacement wave (akin to a kink in a carpet), which requires the molecules to overcome only a local barrier. Concerted molecular displacements are therefore considered to be a significant feature of all displacive transformations. This finding is expected to be of value toward developing strategies for controlling or modulating martensitic-type transformations.

Yes / The structure and dynamics of a single molecule of the nonionic surfactant polysorbate 80 (POE (20) sorbitan monooleate; Tween 80 ) as well as a micelle of polysorbate 80 in water have been investigated by molecular dynamics simulation. In its free state in water the polysorbate 80 molecule samples almost its entire conformational space. The micelle structure is compact and exhibits a prolate ellipsoid shape, with the surface being dominated by the polar terminal groups of the POE chains. The radius of gyration of the micelle was 26.2 A. The physical radius, determined from both the radius of gyration and atomic density, was about 35 A. The estimated diffusion constants for the free molecule (1.8 10 6 cm2 s 1) and the micelle (1.8 10 7 cm2 s 1) were found to be remarkably close to the respective experimental values. The lateral diffusion of the molecules on the micelle surface was estimated to be 1.7 10 7 cm2 s 1, which confirms the highly dynamic nature of the micelle structure. / Tehran University of Medical Sciences & Health Services

No / We address the problem of recognition and growth of ice nuclei in simulation of supercooled bulk water. Bond orientation order parameters based on the spherical harmonics analysis are shown to be ineffective when applied to ice nucleation. Here we present an alternative method which robustly differentiates between hexagonal and cubic ice forms. The method is based on accumulation of the maximum projection of bond orientations onto a set of predetermined vectors, where different terms can contribute with opposite signs with the result that the irrelevant or incompatible molecular arrangements are damped out. We also introduce an effective cluster size by assigning a quality weight to each molecule in an ice-like cluster. We employ our cluster analysis in Monte Carlo simulation of homogeneous ice formation. Replica-exchange umbrella sampling is used for biasing the growth of the largest cluster and calculating the associated free energy barrier. Our results suggest that the ice formation can be seen as a two-stage process. Initially, short tetrahedrally arranged threads and rings are present; these become correlated and form a diffuse ice-genic network. Later, hydrogen bond arrangements within the amorphous ice-like structure gradually settle down and simultaneously `tune-up¿ nearby water molecules. As a result, a well-shaped ice core emerges and spreads throughout the system. The process is very slow and diverse owing to the rough energetic landscape and sluggish molecular motion in supercooled water, while large configurational fluctuations are needed for crystallization to occur. In the small systems studied so far the highly cooperative molecular rearrangements eventually lead to a relatively fast percolation of the forming ice structure through the periodic boundaries, which inevitably affects the simulation results. / EPSRC

No / There is considerable interest, both fundamental and technological, in understanding how additives and impurities influence crystal nucleation, and in the modulation of nucleation in a predictable way by using designer additives. An appropriate additive can promote, retard, or inhibit crystal nucleation and growth, assist in the selective crystallization of a particular enantiomer or polymorphic form, or enable crystals of a desired habit to be obtained.[1¿3] Applications involving additives include the control of the nucleation of proteins,[4] the inhibition of urinary-stone formation[5] and of ice formation in living tissues during cryoprotection,[6] their use as antifreeze agents in Antarctic fish,[7,8] the prevention of blockages in oil and gas pipelines as a result of wax precipitation[9] and gas-hydrate formation,[10] crystal-twin formation,[11] and as a possible basis for the antimalarial activity of some drugs.[12]We report herein the mode of action and explicit (apparently intuitive) rules for designing additive molecules for the modulation of crystal nucleation. The mode of action and the design features have been derived from molecular-dynamics simulations involving simple models.[13] These findings will help to rationalize how known nucleation inhibitors and modulators exert their effect and aid in the identification or design of new additives for the inhibition or promotion of nucleation in specific systems.

No / Most rotamer libraries are generated from subsets of the PDB and do not fully represent the conformational scope of protein side chains. Previous attempts to rectify this sparse coverage of conformational space have involved application of weighting and smoothing functions. We resolve these limitations by using physics-based molecular dynamics simulations to determine more accurate frequencies of rotameric states. This work forms part of our Dynameomics initiative and uses a set of 807 proteins selected to represent 97% of known autonomous protein folds, thereby eliminating the bias toward common topologies found within the PDB. Our Dynameomics derived rotamer libraries encompass 4.8 × 10(9) rotamers, sampled from at least 51,000 occurrences of each of 93,642 residues. Here, we provide a backbone-dependent rotamer library, based on secondary structure ϕ/ψ regions, and an update to our 2011 backbone-independent library that addresses the doubling of our dataset since its original publication. / NIH

No / This chapter gives an introduction to protein simulation methodology aimed at experimentalists and graduate students new to in silico investigations. More emphasis is placed on the knowledge needed to select appropriate simulation protocols, leaving theoretical and mathematical depth for other texts to take care of. The chapter explains some of the more practical considerations of performing simulations of proteins, in particular, the additional considerations required when studying protein folding where nonnative environments are modeled. Forced unfolding simulations are highly relevant and invaluable in characterizing proteins naturally exposed to mechanical stress as a component of their biological function. The chapter illustrates this utility by discussing research that has been done primarily on the giant muscle protein titin. Using Molecular dynamics (MD) simulations to investigate protein folding faces two main challenges. The most obvious relates to the timescale of protein folding and the computational expense required for adequate sampling. / NIH

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25301号 / 工博第5260号 / 京都大学大学院工学研究科物質エネルギー化学専攻 / (主査)教授 作花 哲夫, 教授 安部 武志, 教授 佐藤 啓文 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

Computational methodologies were employed to study a supramolecular micellar structure and its application, nanoreactor. This task was done through rigorous scale-up procedure using both atomistic and mesoscopic simulations. Primarily, density functional theory (DFT) calculation was used to characterize the smallest unit of complex molecules in the multicomponent mixture system. The following step involved transferring the information achieved by DFT calculation to larger scale simulation, such as molecular dynamics (MD) simulation. Lastly, based on the atomistic simulation results, we performed a series of dissipative particle dynamics (DPD) simulations to study a full body of polymeric multicompartment micelle. In the course of research, we built a systematic procedure to minimize the complexity of computation and efficiently characterize macromolecular structures and its application.

Doctor of Philosophy / Department of Chemistry / Paul E. Smith / In the study of biological systems, molecular dynamics (MD) simulations have played an important role in providing atomic details for phenomena of interest. The force field used in MD simulations is a critical factor determining the quality of the simulations. Recently, Kirkwood-Buff (KB) theory has been applied to study preferential interactions and to develop a new force field. KB theory provides a path from quantities determined from simulation data to the corresponding thermodynamic data. Here we combine KB theory and molecular simulations to study a variety of intermolecular interactions in solution. First, recent results concerning the formulation and evaluation of preferential interactions in biological systems in terms of KB integrals are presented. In particular, experimental and simulated preferential interactions of a cosolvent with a biomolecule in the presence of water are described. Second, a force field for the computer simulation of aqueous solutions of amides is presented. The force field is designed to reproduce the experimentally observed density and KB integrals for N-methylacetamide (NMA), allowing for an accurate description of the NMA activity. Other properties such as the translational diffusion constant and heat of mixing are also well reproduced. The force field is then extended to include N,N'-dimethylacetamide and acetamide with good success. The models presented here provide a basis for an accurate force field for peptides and proteins. Comparison between the developed KB force fields (KBFF) and existing force fields is performed for amide and glycine and proves that the KBFF approach is competitive. Also, explicit expressions are developed for the chemical potential derivatives, partial molar volumes, and isothermal compressibility of solution mixtures involving four components at finite concentrations using the KB theory of solutions. A general recursion relationship is also provided which can be used to generate the chemical potential derivatives for higher component solutions. Finally, a pairwise preferential interaction model (PPIM), described by KB integrals is developed to quantify and characterize the interactions between functional groups observed in peptides.