The eMinerals project: developing the concept of the virtual organisation to support collaborative work on molecular-scale environmental simulations

The eMinerals project has established an integrated compute and data minigrid infrastructure together with a set of collaborative tools,. The infrastructure is designed to support molecular simulation scientists working together as a virtual organisation aiming to understand a number of strategic processes in environmental science. The eMinerals virtual organisation is now working towards applying this infrastructure to tackle a new generation of scientific problems. This paper describes the achievements of the eMinerals virtual organisation to date, and describes ongoing applications of the virtual organisation infrastructure.

Mineral surfaces and bioavailability of heavy metals: A molecular-scale perspective

There is a continual influx of heavy metal contaminants and pollutants into the biosphere from both natural and anthropogenic sources. A complex variety of abiotic and biotic processes affects their speciation and distribution, including adsorption onto and desorption from mineral surfaces, incorporation in precipitates or coprecipitates, release through the dissolution of minerals, and interactions with plants and microbes. Some of these processes can effectively isolate heavy metals from the biosphere, whereas others cause their release or transformation to different species that may be more (or less) bioavailable and/or toxic to organisms. Here we focus on abiotic adsorption and precipitation or coprecipitation processes involving the common heavy metal contaminant lead and the metalloids arsenic and selenium in mine tailings and contaminated soils. We have used extremely intense x-rays from synchrotron sources and a structure-sensitive method known as x-ray absorption fine structure (XAFS) spectroscopy to determine the molecular-level speciation of these elements at concentrations of 50 to several thousand ppm in the contaminated environmental samples as well as in synthetic sorption samples. Our XAFS studies of As and Pb in the mine tailings show that up to 50% of these contaminants in the samples studied may be present as adsorbed species on mineral surfaces, which makes them potentially more bioavailable than when present in sparingly soluble solid phases. Our XAFS studies of Se(VI) sorption on Fe2+-containing sulfates show that this element undergoes redox reactions that transform it into less bioavailable and less toxic species. This type of information on molecular-level speciation of heavy metal and metalloid contaminants in various environmental settings is needed to prioritize remediation efforts and to assess their potential hazard to humans and other organisms.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

Catalytic CO2 hydrogenation: study at the molecular scale using field emission techniques

An accurate characterization of the rhodium specimen was obtained via FIM experiments. Reaction behaviors between H2 and CO2 were observed in FEM mode at 700 K. At this temperature, CO desorption occurs, preventing CO+H2 reaction. Surface is mainly recovered by oxygen; reaction with hydrogen occurs. Finally, we can identify the reaction as the Reverse Water Gas Shift.

Control of ordered structure and morphology of large-pore periodic mesoporous organosilicas by inorganic salt

Highly ordered rodlike periodic mesoporous organosilicas (PMO) were successfully synthesized using 1.2-bis(trimethoxysilyl)ethane as an precursor and triblock copolymer P123 as a template at low acid concentration and in the presence of inorganic salts (KCl). The role of acid and salt as well as the effects of synthesis temperature and reactant mole ratio in the control of morphology and the formation of ordered mesostructure was systematically examined. It was found that the addition of inorganic salt can dramatically expand the range of the synthesis parameters to produce highly ordered PMO structure and improve the quality of PMO materials. The morphology of PMOs was significantly dependent on the induction time for precipitation. The uniform PMO rods can only be synthesized in a narrow range of acid and salt concentrations. The results also show that the optimized salt concentration (I M) and low acidity (0.167 M) were beneficial to the formation of not only highly ordered mesostructure but also rodlike morphology. Increasing acidity resulted in fast hydrolysis reaction and short rod or plate-like particles. Highly ordered rod can also be prepared at low temperature (35 degrees C) with high salt amount (1.5 M) or high temperature (45 degrees C) with low salt amount (0.5 M). Optimum reactant molar composition at 40 degrees C is 0.035P123:8KCl:1.34HCI:444H(2)O:1.0bis(trimethoxysilyl)ethane. Lower or higher SiO2/PI23 ratio led to the formation of uniform meso-macropores or pore-blocking effect. (c) 2005 Elsevier Inc. All rights reserved.

Fate of the herbicide glyphosate and its metabolite AMPA in soils and their transfer to surface waters: A multi-scale approach in the Lavaux vineyards, western Switzerland

The use of herbicides in agriculture may lead to environmental problems, such as surface water pollution, with a potential risk for aquatic organisms. The herbicide glyphosate is the most used active ingredient in the world and in Switzerland. In the Lavaux vineyards it is nearly the only molecule applied. This work aimed at studying its fate in soils and its transfer to surface waters, using a multi-scale approach: from molecular (10-9 m) and microscopic scales (10-6 m), to macroscopic (m) and landscape ones (103 m). First of all, an analytical method was developed for the trace level quantification of this widely used herbicide and its main by-product, aminomethylphosphonic acid (AMPA). Due to their polar nature, their derivatization with 9-fluorenylmethyl chloroformate (FMOC-Cl) was done prior to their concentration and purification by solid phase extraction. They were then analyzed by ultra performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). The method was tested in different aqueous matrices with spiking tests and validated for the matrix effect correction in relevant environmental samples. Calibration curves established between 10 and 1000ng/l showed r2 values above 0.989, mean recoveries varied between 86 and 133% and limits of detection and quantification of the method were as low as 5 and 10ng/l respectively. At the parcel scale, two parcels of the Lavaux vineyard area, located near the Lutrive River at 6km to the east of Lausanne, were monitored to assess to which extent glyphosate and AMPA were retained in the soil or exported to surface waters. They were equipped at their bottom with porous ceramic cups and runoff collectors, which allowed retrieving water samples for the growing seasons 2010 and 2011. Results revealed that the mobility of glyphosate and AMPA in the unsaturated zone was likely driven by the precipitation regime and the soil characteristics, such as slope, porosity structure and layer permeability discrepancy. Elevated glyphosate and AMPA concentrations were measured at 60 and 80 cm depth at parcel bottoms, suggesting their infiltration in the upper parts of the parcels and the presence of preferential flow in the studied parcels. Indeed, the succession of rainy days induced the gradual saturation of the soil porosity, leading to rapid infiltration through macropores, as well as surface runoff formation. Furthermore, the presence of more impervious weathered marls at 100 cm depth induced throughflows, the importance of which for the lateral transport of the herbicide molecules was determined by the slope steepness. Important rainfall events (>10 mm/day) were clearly exporting molecules from the soil top layer, as indicated by important concentrations in runoff samples. A mass balance showed that total loss (10-20%) mainly occurred through surface runoff (96%) and, to a minor extent, by throughflows in soils (4%), with subsequent exfiltration to surface waters. Observations made in the Lutrive River revealed interesting details of glyphosate and AMPA dynamics in urbanized landscapes, such as the Lavaux vineyards. Indeed, besides their physical and chemical properties, herbicide dynamics at the catchment level strongly depend on application rates, precipitation regime, land use and also on the presence of drains or constructed channels. Elevated concentrations, up to 4970 ng/l, observed just after the application, confirmed the diffuse export of these compounds from the vineyard area by surface runoff during main rain events. From April to September 2011, a total load of 7.1 kg was calculated, with 85% coming from vineyards and minor urban sources and 15% from arable crops. Small vineyard surfaces could generate high concentrations of herbicides and contribute considerably to the total load calculated at the outlet, due to their steep slopes (~10%). The extrapolated total amount transferred yearly from the Lavaux vineyards to the Lake of Geneva was of 190kg. At the molecular scale, the possible involvement of dissolved organic matter (DOM) in glyphosate and copper transport was studied using UV/Vis fluorescence spectroscopy. Combined with parallel factor (PARAFAC) analysis, this technique allowed characterizing DOM of soil and surface water samples from the studied vineyard area. Glyphosate concentrations were linked to the fulvic-like spectroscopic signature of DOM in soil water samples, as well as to copper, suggesting the formation of ternary complexes. In surface water samples, its concentrations were also correlated to copper ones, but not in a significant way to the fulvic-like signature. Quenching experiments with standards confirmed field tendencies in the laboratory, with a stronger decrease in fluorescence intensity for fulvic-like fluorophore than for more aromatic ones. Lastly, based on maximum concentrations measured in the river, an environmental risk for these compounds was assessed, using laboratory tests and ecotoxicity data from the literature. In our case and with the methodology applied, the risk towards aquatic species was found negligible (RF<1).

DNA for nano-bio scale computation of chemical formalisms using Higher Order Logic (HOL) and analysis using an interdisciplinary approach

Bio-molecular computing, 'computations performed by bio-molecules', is already challenging traditional approaches to computation both theoretically and technologically. Often placed within the wider context of ´bio-inspired' or 'natural' or even 'unconventional' computing, the study of natural and artificial molecular computations is adding to our understanding of biology, physical sciences and computer science well beyond the framework of existing design and implementation paradigms. In this introduction, We wish to outline the current scope of the field and assemble some basic arguments that, bio-molecular computation is of central importance to computer science, physical sciences and biology using HOL - Higher Order Logic. HOL is used as the computational tool in our R&D work. DNA was analyzed as a chemical computing engine, in our effort to develop novel formalisms to understand the molecular scale bio-chemical computing behavior using HOL. In our view, our focus is one of the pioneering efforts in this promising domain of nano-bio scale chemical information processing dynamics.

Systematic functionalization of molecules for molecular self-assembly

This thesis describes the investigation of systematically varied organic molecules for use in molecular self-assembly processes. All experiments were performed using high-resolution non-contact atomic force microscopy under UHV conditions and at room temperature. Using this technique, three different approaches for influencing intermolecular and molecule-surface interaction on the insulating calcite(10.4) surface were investigated by imaging the structure formation at the molecular scale. I first demonstrated the functionalization of shape-persistent oligo(p-benzamide)s that was engineered by introducing different functional groups and investigating their effect on the structural formation on the sample surface. The molecular core was designed to provide significant electrostatic anchoring towards the surface, while at the same time maintaining the flexibility to fine-tune the resulting structure by adjusting the intermolecular cohesion energy. The success of this strategy is based on a clear separation of the molecule-substrate interaction from the molecule-molecule interaction. My results show that sufficient molecule-surface anchoring can be achieved without restricting the structural flexibility that is needed for the design of complex molecular systems. Three derivatives of terephthalic acid (TPA) were investigated in chapter 7. Here, the focus was on changing the adhesion to the calcite surface by introducing different anchor functionalities to the TPA backbone. For all observed molecules, the strong substrate templating effect results in molecular structures that are strictly oriented along the calcite main crystal directions. This templating is especially pronounced in the case of 2-ATPA where chain formation on the calcite surface is observed in contrast to the formation of molecular layers in the bulk. At the same time, the amino group of 2-ATPA proved an efficient anchor functionality, successfully stabilizing the molecular chains on the sample surface. These findings emphasizes, once again, the importance of balancing and fine-tuning molecule-molecule and molecule-surface interactions in order to achieve stable, yet structurally flexible molecular arrangements on the sample surface. In the last chapter, I showed how the intrinsic property of molecular chirality decisively influences the structure formation in molecular self-assembly. This effect is especially pronounced in the case of the chiral heptahelicene-2-carboxylic acid. Deposition of the enantiopure molecules results in the formation of homochiral islands on the sample surface which is in sharp contrast to the formation of uni-directional double rows upon deposition of the racemate onto the same surface. While it remained uncertain from these previous experiments whether the double rows are composed of hetero- or homochiral molecules, I could clearly answer that question here and demonstrate that the rows are of heterochiral origin. Chirality, thus, proves to be another important parameter to steer the intermolecular interaction on surfaces. Altogether, the results of this thesis demonstrate that, in order to successfully control the structure formation in molecular self-assembly, the correct combination of molecule and surface properties is crucial. This is of special importance when working on substrates that exhibit a strong influence on the structure formation, such as the calcite(10.4) surface. Through the systematic variation of functional groups several important parameters that influence the balance between molecule-surface and molecule-molecule interaction were identified here, and the results of this thesis can, thus, act as a guideline for the rational design of molecules for use in molecular self-assembly.

Quantum transport in a single molecular junction

The craze for faster and smaller electronic devices has never gone down and this has always kept researchers on their toes. Following Moore’s law, which states that the number of transistors in a single chip will double in every 18 months, today “30 million transistors can fit into the head of a 1.5 mm diameter pin”. But this miniaturization cannot continue indefinitely due to the ‘quantum leakage’ limit in the thickness of the insulating layer between the gate electrode and the current carrying channel. To bypass this limitation, scientists came up with the idea of using vastly available organic molecules as components in an electronic device. One of the primary challenges in this field was the ability to perform conductance measurements across single molecular junctions. Once that was achieved the focus shifted to a deeper understanding of the underlying physics behind the electron transport across these molecular scale devices. Our initial theoretical approach is based on the conventional Non-Equilibrium Green Function(NEGF) formulation, but the self-energy of the leads is modified to include a weighting factor that ensures negligible current in the absence of a molecular pathway as observed in a Mechanically Controlled Break Junction (MCBJ) experiment. The formulation is then made parameter free by a more careful estimation of the self-energy of the leads. The calculated conductance turns out to be atleast an order more than the experimental values which is probably due to a strong chemical bond at the metal-molecule junction unlike in the experiments. The focus is then shifted to a comparative study of charge transport in molecular wires of different lengths within the same formalism. The molecular wires, composed of a series of organic molecules, are sanwiched between two gold electrodes to make a two terminal device. The length of the wire is increased by sequentially increasing the number of molecules in the wire from 1 to 3. In the low bias regime all the molecular devices are found to exhibit Ohmic behavior. However, the magnitude of conductance decreases exponentially with increase in length of the wire. In the next study, the relative contribution of the ‘in-phase’ and the ‘out-of-phase’ components of the total electronic current under the influence of an external bias is estimated for the wires of three different lengths. In the low bias regime, the ‘out-of-phase’ contribution to the total current is minimal and the ‘in-phase’ elastic tunneling of the electrons is responsible for the net electronic current. This is true irrespective of the length of the molecular spacer. In this regime, the current-voltage characteristics follow Ohm’s law and the conductance of the wires is found to decrease exponentially with increase in length which is in agreement with experimental results. However, after a certain ‘off-set’ voltage, the current increases non-linearly with bias and the ‘out-of-phase’ tunneling of electrons reduces the net current substantially. Subsequently, the interaction of conduction electrons with the vibrational modes as a function of external bias in the three different oligomers is studied since they are one of the main sources of phase-breaking scattering. The number of vibrational modes that couple strongly with the frontier molecular orbitals are found to increase with length of the spacer and the external field. This is consistent with the existence of lowest ‘off-set’ voltage for the longest wire under study.

Electron transport in molecular systems

The remarkable advances in nanoscience and nanotechnology over the last two decades allow one to manipulate individuals atoms, molecules and nanostructures, make it possible to build devices with only a few nanometers, and enhance the nano-bio fusion in tackling biological and medical problems. It complies with the ever-increasing need for device miniaturization, from magnetic storage devices, electronic building blocks for computers, to chemical and biological sensors. Despite the continuing efforts based on conventional methods, they are likely to reach the fundamental limit of miniaturization in the next decade, when feature lengths shrink below 100 nm. On the one hand, quantum mechanical efforts of the underlying material structure dominate device characteristics. On the other hand, one faces the technical difficulty in fabricating uniform devices. This has posed a great challenge for both the scientific and the technical communities. The proposal of using a single or a few organic molecules in electronic devices has not only opened an alternative way of miniaturization in electronics, but also brought up brand-new concepts and physical working mechanisms in electronic devices. This thesis work stands as one of the efforts in understanding and building of electronic functional units at the molecular and atomic levels. We have explored the possibility of having molecules working in a wide spectrum of electronic devices, ranging from molecular wires, spin valves/switches, diodes, transistors, and sensors. More specifically, we have observed significant magnetoresistive effect in a spin-valve structure where the non-magnetic spacer sandwiched between two magnetic conducting materials is replaced by a self-assembled monolayer of organic molecules or a single molecule (like a carbon fullerene). The diode behavior in donor(D)-bridge(B)-acceptor(A) type of single molecules is then discussed and a unimolecular transistor is designed. Lastly, we have proposed and primarily tested the idea of using functionalized electrodes for rapid nanopore DNA sequencing. In these studies, the fundamental roles of molecules and molecule-electrode interfaces on quantum electron transport have been investigated based on first-principles calculations of the electronic structure. Both the intrinsic properties of molecules themselves and the detailed interfacial features are found to play critical roles in electron transport at the molecular scale. The flexibility and tailorability of the properties of molecules have opened great opportunity in a purpose-driven design of electronic devices from the bottom up. The results that we gained from this work have helped in understanding the underlying physics, developing the fundamental mechanism and providing guidance for future experimental efforts.

Large scale multiphysics modeling of neurites

Situado en el límite entre Ingeniería, Informática y Biología, la mecánica computacional de las neuronas aparece como un nuevo campo interdisciplinar que potencialmente puede ser capaz de abordar problemas clínicos desde una perspectiva diferente. Este campo es multiescala por naturaleza, yendo desde la nanoescala (como, por ejemplo, los dímeros de tubulina) a la macroescala (como, por ejemplo, el tejido cerebral), y tiene como objetivo abordar problemas que son complejos, y algunas veces imposibles, de estudiar con medios experimentales. La modelización computacional ha sido ampliamente empleada en aplicaciones Neurocientíficas tan diversas como el crecimiento neuronal o la propagación de los potenciales de acción compuestos. Sin embargo, en la mayoría de los enfoques de modelización hechos hasta ahora, la interacción entre la célula y el medio/estímulo que la rodea ha sido muy poco explorada. A pesar de la tremenda importancia de esa relación en algunos desafíos médicos—como, por ejemplo, lesiones traumáticas en el cerebro, cáncer, la enfermedad del Alzheimer—un puente que relacione las propiedades electrofisiológicas-químicas y mecánicas desde la escala molecular al nivel celular todavía no existe. Con ese objetivo, esta investigación propone un marco computacional multiescala particularizado para dos escenarios respresentativos: el crecimiento del axón y el acomplamiento electrofisiológicomecánico de las neuritas. En el primer caso, se explora la relación entre los constituyentes moleculares del axón durante su crecimiento y sus propiedades mecánicas resultantes, mientras que en el último, un estímulo mecánico provoca deficiencias funcionales a nivel celular como consecuencia de sus alteraciones electrofisiológicas-químicas. La modelización computacional empleada en este trabajo es el método de las diferencias finitas, y es implementada en un nuevo programa llamado Neurite. Aunque el método de los elementos finitos es también explorado en parte de esta investigación, el método de las diferencias finitas tiene la flexibilidad y versatilidad necesaria para implementar mode los biológicos, así como la simplicidad matemática para extenderlos a simulaciones a gran escala con un coste computacional bajo. Centrándose primero en el efecto de las propiedades electrofisiológicas-químicas sobre las propiedades mecánicas, una versión adaptada de Neurite es desarrollada para simular la polimerización de los microtúbulos en el crecimiento del axón y proporcionar las propiedades mecánicas como función de la ocupación de los microtúbulos. Después de calibrar el modelo de crecimiento del axón frente a resultados experimentales disponibles en la literatura, las características mecánicas pueden ser evaluadas durante la simulación. Las propiedades mecánicas del axón muestran variaciones dramáticas en la punta de éste, donde el cono de crecimiento soporta las señales químicas y mecánicas. Bansándose en el conocimiento ganado con el modelo de diferencias finitas, y con el objetivo de ir de 1D a 3D, este esquema preliminar pero de una naturaleza innovadora allana el camino a futuros estudios con el método de los elementos finitos. Centrándose finalmente en el efecto de las propiedades mecánicas sobre las propiedades electrofisiológicas- químicas, Neurite es empleado para relacionar las cargas mecánicas macroscópicas con las deformaciones y velocidades de deformación a escala microscópica, y simular la propagación de la señal eléctrica en las neuritas bajo carga mecánica. Las simulaciones fueron calibradas con resultados experimentales publicados en la literatura, proporcionando, por tanto, un modelo capaz de predecir las alteraciones de las funciones electrofisiológicas neuronales bajo cargas externas dañinas, y uniendo lesiones mecánicas con las correspondientes deficiencias funcionales. Para abordar simulaciones a gran escala, aunque otras arquitecturas avanzadas basadas en muchos núcleos integrados (MICs) fueron consideradas, los solvers explícito e implícito se implementaron en unidades de procesamiento central (CPU) y unidades de procesamiento gráfico (GPUs). Estudios de escalabilidad fueron llevados acabo para ambas implementaciones mostrando resultados prometedores para casos de simulaciones extremadamente grandes con GPUs. Esta tesis abre la vía para futuros modelos mecánicos con el objetivo de unir las propiedades electrofisiológicas-químicas con las propiedades mecánicas. El objetivo general es mejorar el conocimiento de las comunidades médicas y de bioingeniería sobre la mecánica de las neuronas y las deficiencias funcionales que aparecen de los daños producidos por traumatismos mecánicos, como lesiones traumáticas en el cerebro, o enfermedades neurodegenerativas como la enfermedad del Alzheimer. ABSTRACT Sitting at the interface between Engineering, Computer Science and Biology, Computational Neuron Mechanics appears as a new interdisciplinary field potentially able to tackle clinical problems from a new perspective. This field is multiscale by nature, ranging from the nanoscale (e.g., tubulin dimers) to the macroscale (e.g., brain tissue), and aims at tackling problems that are complex, and sometime impossible, to study through experimental means. Computational modeling has been widely used in different Neuroscience applications as diverse as neuronal growth or compound action potential propagation. However, in the majority of the modeling approaches done in this field to date, the interactions between the cell and its surrounding media/stimulus have been rarely explored. Despite of the tremendous importance of such relationship in several medical challenges—e.g., traumatic brain injury (TBI), cancer, Alzheimer’s disease (AD)—a bridge between electrophysiological-chemical and mechanical properties of neurons from the molecular scale to the cell level is still lacking. To this end, this research proposes a multiscale computational framework particularized for two representative scenarios: axon growth and electrophysiological-mechanical coupling of neurites. In the former case, the relation between the molecular constituents of the axon during its growth and its resulting mechanical properties is explored, whereas in the latter, a mechanical stimulus provokes functional deficits at cell level as a consequence of its electrophysiological-chemical alterations. The computational modeling approach chosen in this work is the finite difference method (FDM), and was implemented in a new program called Neurite. Although the finite element method (FEM) is also explored as part of this research, the FDM provides the necessary flexibility and versatility to implement biological models, as well as the mathematical simplicity to extend them to large scale simulations with a low computational cost. Focusing first on the effect of electrophysiological-chemical properties on the mechanical proper ties, an adaptation of Neurite was developed to simulate microtubule polymerization in axonal growth and provide the axon mechanical properties as a function of microtubule occupancy. After calibrating the axon growth model against experimental results available in the literature, the mechanical characteristics can be tracked during the simulation. The axon mechanical properties show dramatic variations at the tip of the axon, where the growth cone supports the chemical and mechanical signaling. Based on the knowledge gained from the FDM scheme, and in order to go from 1D to 3D, this preliminary yet novel scheme paves the road for future studies with FEM. Focusing then on the effect of mechanical properties on the electrophysiological-chemical properties, Neurite was used to relate macroscopic mechanical loading to microscopic strains and strain rates, and simulate the electrical signal propagation along neurites under mechanical loading. The simulations were calibrated against experimental results published in the literature, thus providing a model able to predict the alteration of neuronal electrophysiological function under external damaging load, and linking mechanical injuries to subsequent acute functional deficits. To undertake large scale simulations, although other state-of-the-art architectures based on many integrated cores (MICs) were considered, the explicit and implicit solvers were implemented for central processing units (CPUs) and graphics processing units (GPUs). Scalability studies were done for both implementations showing promising results for extremely large scale simulations with GPUs. This thesis opens the avenue for future mechanical modeling approaches aimed at linking electrophysiological- chemical properties to mechanical properties. Its overarching goal is to enhance the bioengineering and medical communities knowledge on neuronal mechanics and functional deficits arising from damages produced by direct mechanical insults, such as TBI, or neurodegenerative evolving illness, such as AD.

Neutron-mapping polymer flow: Scattering, flow visualization, and molecular theory

Flows of complex fluids need to be understood at both macroscopic and molecular scales, because it is the macroscopic response that controls the fluid behavior, but the molecular scale that ultimately gives rise to rheological and solid-state properties. Here the flow field of an entangled polymer melt through an extended contraction, typical of many polymer processes, is imaged optically and by small-angle neutron scattering. The dual-probe technique samples both the macroscopic stress field in the flow and the microscopic configuration of the polymer molecules at selected points. The results are compared with a recent tube model molecular theory of entangled melt flow that is able to calculate both the stress and the single-chain structure factor from first principles. The combined action of the three fundamental entangled processes of reptation, contour length fluctuation, and convective constraint release is essential to account quantitatively for the rich rheological behavior. The multiscale approach unearths a new feature: Orientation at the length scale of the entire chain decays considerably more slowly than at the smaller entanglement length.

Molecular mechanisms of salt effects on carbon nanotube dispersions in an organic solvent (N-methyl-2-pyrrolidone)

We consider the effects of salt (sodium iodide) on pristine carbon nanotube (CNT) dispersions in an organic solvent, N-methyl-2-pyrrolidone (NMP). We investigate the molecular-scale mechanisms of ion interactions with the nanotube surface and we show how the microscopic ion-surface interactions affect the stability of CNT dispersions in NMP. In our study we use a combination of fully atomistic Molecular Dynamics simulations of sodium and iodide ions at the CNT-NMP interface with direct experiments on the CNT dispersions. In the experiments we analyze the effects of salt on the stability of the dispersions by photoluminescence (PL) and optical absorption spectroscopy of the samples as well as by visual inspection. By fully atomistic Molecular Dynamics simulations we investigate the molecular-scale mechanisms of sodium and iodide ion interactions with the nanotube surface. Our simulations reveal that both ions are depleted from the CNT surface in the CNT-NMP dispersions mainly due to the two reasons: (1) there is a high energy penalty for the ion partial desolvation at the CNT surface; (2) NMP molecules form a dense solvation layer at the CNT surface that prevents ions to come close to the CNT surface. As a result, an increase of the salt concentration increases the "osmotic" stress in the CNT-NMP system and, thus, decreases the stability of the CNT dispersions in NMP. Direct experiments confirm the simulation results: addition of NaI salt into the NMP dispersions of pristine CNTs leads to precipitation of CNTs (bundle formation) even at very small salt concentration (∼10 -3 mol L -1). In line with the simulation predictions, the effect increases with the increase of the salt concentration. Overall, our results show that dissolved salt ions have strong effects on the stability of CNT dispersions. Therefore, it is possible to stimulate the bundle formation in the CNT-NMP dispersions and regulate the overall concentration of nanotubes in the dispersions by changing the NaI concentration in the solvent. © 2012 The Royal Society of Chemistry.

Free volume and water uptake in a copolymer hydrogel series

A copolymer of X-hydroxyethyl methacrylate (HEMA) with 2-ethoxy ethyl methacrylate (EEMA) was synthesized and the molecular mobility, free volume, and density properties examined as a function of composition. These properties were correlated with the equilibrium water uptake in order to determine which of the properties were most influential in causing high water sorption, as these materials are suitable candidates for hydrogel systems. It was found that the polar HEMA repeat unit results in a rigid, glassy sample at room temperature due to the high degree of hydrogen bonding between chains whereas high EEMA content leads to rubbery samples with subambient glass transition temperatures. The free volume properties on the molecular scale measured by positron annihilation Lifetime spectroscopy (PALS) showed that higher HEMA content led to smaller, fewer holes and a lower free volume fraction than EEMA. Therefore the high water uptake of HEEMA-containing copolymers is largely related to the high polarity of the HEMA unit compared to EEMA, despite the low content of free volume into which the water can initially diffuse. Trends in density with copolymer composition, as measured on a macroscopic level, differs to that seen by PALS and indicates that the two techniques are measuring different scales of packing. (C) 1998 John Wiley & Sons, Inc.