Energy needs are projected to continue to increase in the coming decades, and with the drive to use more clean energy to combat climate change, nuclear energy is poised to become an important player in the energy portfolio of the world. Due to the unique nature of nuclear energy, it is always vital to have safe and efficient generation of that energy. In current light water reactors, the most common fuel is uranium dioxide (UO2), an oxide ceramic. There is also ongoing research examining uranium-based based metallic fuels, such as uranium-molybdenum (U-Mo) fuels with low uranium (U) enrichment for research reactors as part of a broader effort to combat nuclear proliferation, and uranium-zirconium-based fuels for Generation IV fast reactors. Each nuclear fuel has weaknesses that need to be addressed for safer and more efficient use. Two major challenges of using UO¬2 are the fission gas (e.g. xenon) release and the decreasing thermal conductivity with increasing burnup. In UMo alloys, the major weakness is the breakaway swelling that occurs at high fission densities. The challenges presented by both fuel types are heavily impacted by microstructure, and several studies have identified that the initial microstructure of the fuel in particular (e.g. initial grain size and grain aspect ratio) plays a large role in determining when and how quickly these processes occur. Thus, knowledge of how such initial microstructures evolve is paramount in having stable and predictable fission gas release and thermal conductivity decrease (in UO2) and fuel swelling (in UMo alloys). Mobility is a critical grain boundary (GB) property that impacts microstructural evolution. Existing literature examines GB mobility for a few specific boundaries but does not (in general) identify the anisotropy relationships that this property has. This work first examined the anisotropy in GB mobility, specifically identifying the anisotropy trend for the low-index rotation axes for tilt GBs in BCC γ U, and fluorite UO2 via molecular dynamics simulation. GB mobility is calculated using the shrinking cylindrical grain method, which uses the capillary effect induced by the GB curvature to drive grain growth. The mobilities are calculated for different rotation axes, misorientation angles, and temperatures in these systems. The results indicated that the density of the atomic plane perpendicular to the (tilt) GB plane (which is also perpendicular to the rotation axis) significantly impacts which GB rotation axis has the fastest boundaries. Specifically, the atomic plane that has a higher density tends to have a faster mobility, because it is more efficient for atoms moving across the GB along such planes. For example, for body-centered cubic materials, the <110> tilt GBs are determined to have the fastest mobilities, while face-centered cubic (FCC) and FCC-like structures such as fluorite have <111> tilt GBs as the fastest. Knowledge of GB mobility and its anisotropy in pure materials is helpful as a baseline, but real materials have solutes or impurities (both intentionally and unintentionally) which are known to affect GB mobility by processes such as solute drag and Zener pinning. Additionally, in reactors, nuclear fission can produce many fission products, each of which acts as an additional impurity that will interact with the GB in some way. Because the initial microstructure and its subsequent evolution are vital for addressing the challenges of using nuclear fuel as described above, knowledge of the impacts of these impurities on GB mobility is required. Therefore, this work examined the impact of solutes and impurities on GB mobility and its anisotropy. In particular, the solute effect was examined using the UMo alloy system, while the impurity effect was examined using Xe (a very common fission product) in the γ U, UMo, and UO2 systems. It is found that both Mo and Xe can cause a solute drag effect on GB mobility in the γ U system, with the effect of Xe being stronger than Mo at the same solute/impurity concentration. Xe also causes a solute drag effect in UO2, though the magnitude of the effect is interatomic-potential-dependent. The mobility anisotropy trend was found to disappear at high solute and impurity concentrations in the metallic U and UMo systems but was largely unaffected in the UO2 system. These results not only increase our fundamental understanding of GB mobility, its anisotropy, and solute/impurity drag effects, but also can be used as inputs for mesoscale simulations to examine polycrystalline grain growth with anisotropic GB mobility and in turn examine how the fuel performance parameters change with these properties. / Doctor of Philosophy / Worldwide, energy needs continue to increase each year. Concerns related to climate change have led to an increased emphasis on renewable energies such as solar and wind, but the limitations of these resources prevent them from being the only energy sources. Nuclear energy is uniquely positioned to address several energy concerns: it is clean (no carbon emissions and air pollution), reliable (for example, 24/7 energy production, independent of weather), and energy-dense (one kilogram of fissile uranium provides roughly the same amount of energy as 3000 metric tons of coal). Currently, nuclear energy provides roughly 20% of the energy of the United States, but future predictions show a decrease in the total share of energy generation due to aging systems and a limited number of new reactors being built. The safety and efficacy of existing and future reactors are among the primary concerns for being able to allow nuclear energy to increase its energy share. To determine the safety and efficacy of new reactor designs, a computer simulation tool called fuel performance modeling has been used over the last few decades. This tool requires several material properties as input, one of which is how the nuclear reactor fuel microstructure changes based on a variety of conditions. A significant process contributing to microstructural change is grain growth. Grains (crystallites that make up the whole material) meet at interfaces called grain boundaries (GBs), and these GBs have two properties that largely determine how grain growth occurs: energy and mobility. Significant effort is being put into understanding these properties and their anisotropy, or how they change based on the GB character which is the relative mismatch between the two grains. This work contributes additional understanding of GB mobility anisotropy in two nuclear fuels: uranium dioxide (UO2, the primary fuel in current reactors) and a uranium-molybdenum (UMo) alloy (the primary fuel for newer research reactors). In particular, computer simulation is used to determine GB mobility for several unique GB systems. It is found that for pure nuclear fuels, GB mobility anisotropy is largely determined by which atomic plane has the highest density perpendicular to the GB. When the fuel is no longer pure (through the addition of alloying elements or other impurities) the anisotropy changes significantly in UMo fuels, such that at high concentrations of solute or impurities there is little to no anisotropy, while very little change is observed in the anisotropy in UO2.

The structure and dynamics of membranes are crucial to ensure the proper functioning of cells. There are some compounds used in therapeutics that show nonspecific interactions with membranes in addition to their specific molecular target. Among them, two compounds recently used in therapeutics against COVID-19, remdesivir and favipiravir, were subjected to molecular dynamics simulation assays. In these, we demonstrated that the compounds can spontaneously bind to model lipid membranes in the presence or absence of cholesterol. These findings correlate with the corresponding experimental results recently reported by our group. In conclusion, insertion of the compounds into the membrane is observed, with a mean position close to the phospholipid head groups.

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 / The conformational propensities of amino acids are an amalgamation of sequence effects, environmental effects and underlying intrinsic behavior. Many have attempted to investigate neighboring residue effects to aid in our understanding of protein folding and improve structure prediction efforts, especially with respect to difficult to characterize states, such as disordered or unfolded states. Host-guest peptide series are a useful tool in examining the propensities of the amino acids free from the surrounding protein structure. Here, we compare the distributions of the backbone dihedral angles (φ/ψ) of the 20 proteogenic amino acids in two different sequence contexts using the AAXAA and GGXGG host-guest pentapeptide series. We further examine their intrinsic behaviors across three environmental contexts: water at 298 K, water at 498 K, and 8 M urea at 298 K. The GGXGG systems provide the intrinsic amino acid propensities devoid of any conformational context. The alanine residues in the AAXAA series enforce backbone chirality, thereby providing a model of the intrinsic behavior of amino acids in a protein chain. Our results show modest differences in φ/ψ distributions due to the steric constraints of the Ala side chains, the magnitudes of which are dependent on the denaturing conditions. One of the strongest factors modulating φ/ψ distributions was the protonation of titratable side chains, and the largest differences observed were in the amino acid propensities for the rarely sampled αL region. / NIH

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

In the atmosphere in the height of 18000ft to 25000ft, there are some metastable droplets called supercooled liquid water in the temperature range of 0◦C to 40◦C. When these droplets impinge on the wings of an airplane, a very thin layer of ice is formed on the surface. This natural phenomenon calls “impact icing”. In this research, I studied the nanoscale impact icing on structured graphite surfaces, as the substrates at the atomistic scale using Molecular Dynamics (MD) simulations. This research focuses on the first steps of the development of a predictive multiscale strategy for molecular simulations of impact ice adhesion on nanostructured substrates. Through the simulations, the molecular level physics such as molecular interactions, interfacial energy, and nanoscale surface roughness are processed into a “microscopic ice adhesion strength” that describes the energy cost for breaking the nanoscale interfacial layer. In this work, the simulation strategy is designed based on the postulate that at the nanoscale the fracture strength of impact ice on a given substrate is controlled by the extent of the ice interdigitating the substrate. The interdigitating interfacial structure is then determined by the process of wetting the substrate by a supercooled impinged water droplet and the process of penetrating of supercooled water crystallizing into ice crystals under graphene nanoconfinement. Following this line of reasoning, I divided my impact icing simulations into three separate sections including (1) simulations of dynamic wetting of supercooled water on nanostructured graphene substrate, (2) simulations of water crystallization under nano-confinement, and (3) simulations of fracture of prescribed ice-substrate interfacial structure. Based on the results, it is concluded that the degree of surface hydrophobicity, depth of penetrated water, the order of interlocked water molecules, size of surface roughness, texture structure of the surface, and ice temperature are the key roles that dominate the investigation of fracture strength of impact ice at the solid interface. Furthermore, MD simulation results demonstrate that the surface roughness lower than 3.0nm is enabled to stop water from crystallization, a piece of useful information to design anti-icing surfaces.