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Molecular modelling applications in metalloenzyme design are still scarce due to a series of challenges. In top of that, the simulations of metal-mediated binding and the identification of catalytic competent geometries requiring both large conformational exploration and simulation of fine electronic properties. Here, we demonstrate how the incorporation of new tools in multiscale strategies, namely substrate diffusion exploration, allow taking a step further. As a showcase the enantioselective profiles of the most outstanding variants of an artificial Rh2-based cyclopropanase (GSH, HFF and RFY) developed by Lewis and co-workers have been rationalized. DFT calculations on the free-cofactor-mediated process identify the carbene insertion and the cyclopropanoid formation as crucial events, being the latter the enantiodetermining step, which displays up to 8 competitive orientations easily altered by the protein environment. The key intermediates of the reaction were docked into the protein scaffold showing that some mutated residues have direct interaction with the cofactor and/or the co-substrate. These interactions take form of a direct coordination of Rh in GSH and HFF and a strong hydrophobic patch with the carbene moiety in RFY. Posterior molecular dynamics sustain that the cofactor induces global re-arrangements of the protein. Finally, massive exploration of substrate diffusion, based on the GPathFinder approach, defines this event as the origin of the enantioselectivity in GSH and RFY. For HFF, fine molecular dockings suggest that it is likely related to local interactions upon diffusion. This work shows how modelling of long-range mutations on the catalytic profiles of metalloenzymes may be unavoidable and software simulating substrate diffusion should be applied.

Elucidating the physicochemical laws that govern the phase behaviour of biomolecules is a cardinal milestone to understand crucial open questions in biology ranging from the spatiotemporal organisation of the cytoplasm in the eukaryotic cell to the emergence of pathological cellular states. Understanding the governing principles of protein and nucleic acid phase behaviour implies deciphering how atomic-scale processes modulate molecular interactions, and how such interactions, in turn, dictate the large-scale thermodynamic behaviour of biomolecules. In this thesis, Molecular Dynamics and Statistical Mechanics have been used to understand the driving forces that modulate protein collective behaviour along such wide-ranging spatial scales. Simulations with a minimal coarse-grained model showed how enriching the structural ensemble of proteins in open, expanded conformations can promote their propensity to undergo liquid-liquid phase separation. This is because more expanded conformations favour inter-protein interactions which increase the molecular connectivity inside protein droplets, favouring their stability. In addition, I present a pioneering chemically specific coarse-grained force field for intrinsically disordered proteins that explicitly considers the effect of solvent in phase separation of proteins. I find our model in near-quantitative experimental agreement both with single-protein structural descriptors as well as with available thermodynamic data of phase separated-protein condensates such as water and protein content in FUS condensates. The model enables studying the structure of the solvent inside protein droplets and recovers experimentally observed salt-inhibited and salt-driven phase separation. Next, I focus on delineating the role of spontaneous beta-sheet folding – prime drivers for neurodisease-linked phase transitions – in the kinetic and transport properties of condensates as a function of the abundance and strength of such transitions. Using atomistic umbrella sampling simulations I estimated the free energy of binding when 8-residue NUP-98 sequence replicas remain disordered as opposed to when they undergo folding into a beta-sheet, finding that folding can increase the binding free energy up to an order of magnitude. Transferring such information from the atomistic to a coarse-grained model, it was established how the timescale between diffusion loss and droplet coalescence determines the shape of phase-separated protein condensates. Finally, I study how disorder-to-order transitions can give rise to single component Fused in Sacroma (FUS) multi-phase condensates. Atomistic free energy calculations were used to establish that such structural transitions can increase four-fold the interaction between FUS sequences which are prone to spontaneous beta-sheet folding. I transferred these findings to a sequence-dependent coarse-grained model which predicted that proteins that underwent folding contribute to lower the interfacial free energy of the condensates. Moreover, our dynamical minimal model informed with the findings from the atomistic and coarse-grained scales predicts single component FUS multi-phase condensates with an inhomogenous organisation where a liquid-core of disordered proteins is surrounded by a gel-like shell of the proteins which underwent disorder-to-order transitions. Taken together, this work sheds light on the molecular driving forces of protein phase behaviour that are crucial to understand cell function both in health and disease and proposes a pioneering approach that advances the realism and explanatory power of coarse-grained biomolecular simulations., EPSRSC grant agreement EP/N509620/1

This paper presents a new polymorphic element modelling approach for multi-scale simulation, with an application to fracture in composite structures. We propose the concept of polymorphic elements; these are elements that exist as an evolving superposition of various states, each representing the relevant physics with the required level of fidelity. During a numerical simulation, polymorphic elements can change their formulation to more effectively represent the structural state or to improve computational efficiency. This change is achieved by transitioning progressively between states and by repartitioning each state on-the-fly as required at any given instant during the analysis. In this way, polymorphic elements offer the possibility to carry out a multiscale simulation without having to define a priori where the local model should be located. Polymorphic elements can be implemented as simple user-defined elements which can be readily integrated in a Finite Element code. Each individual user-defined polymorphic element contains all the relevant superposed states (and their coupling), as well as the ability to self-refine. We implemented a polymorphic element with continuum (plain strain) and structural (beam) states for the multiscale simulation of crack propagation. To verify the formulation, we applied it to the multiscale simulation of known mode I, mode II andmixed-mode I and II crack propagation scenarios, obtaining good accuracy and up to 70% reduction in computational time —the reduction in computational time can potentially be even more significant for large engineering structures where the local model is a small portion of the total. We further applied our polymorphic element formulation to the multiscale simulation of a more complex problem involving interaction between cracks (delamination migration), thereby demonstrating the potential impact of the proposed multiscale modelling approach for realistic engineering problems.

Charge transport properties of a P3HT:DIPBI bulk heterojunction solar cell are modelled by kinetic Monte Carlo simulations based on a morphology obtained from coarse-grained molecular dynamics. Different methods for calculating the hopping integrals entering the charge transfer rates are compared and calibrated for hole transport in amorphous P3HT. The influence of intermolecular and intramolecular charge transfer on the total charge carrier mobility and hence the power conversion efficiency is investigated in detail. An analysis of the most probable pathways with low resistance for hole transport is performed, establishing a connection between charge mobility and morphology.

We present a scheme for accelerating hybrid continuum-atomistic models in multiscale fluidic systems by using Gaussian process regression as a surrogate model for computationally expensive molecular dynamics simulations. Using Gaussian process regression, we are able to accurately predict atomic-scale information purely by consideration of the macroscopic continuum-model inputs and outputs and judge on the fly whether the uncertainty of our prediction is at an acceptable level, else a new molecular simulation is performed to continually augment the database, which is never required to be complete. This provides a substantial improvement over the current generation of hybrid methods, which often require many similar atomistic simulations to be performed, discarding information after it is used once. We apply our hybrid scheme to nano-confined unsteady flow through a high-aspect-ratio converging-diverging channel, and make comparisons between the new scheme and full molecular dynamics simulations for a range of uncertainty thresholds and initial databases. For low thresholds, our hybrid solution is highly accurate-around that of thermal noise. As the uncertainty threshold is raised, the accuracy of our scheme decreases and the computational speed-up increases (relative to a full molecular simulation), enabling the compromise between accuracy and efficiency to be tuned. The speed-up of our hybrid solution ranges from an order of magnitude, with no initial database, to cases where an extensive initial database ensures no new MD simulations are required.

Density functional theory (DFT) and molecular dynamics (MD) simulations were employed to investigate the interaction of cellulose and lignin with acetic anhydride for explaining the wood modification process. Cellulose was modelled with a cellobiose unit and dibenzodioxocin was used to represent the lignin model. Results obtained from both methods revealed that acetic anhydride interacted substantially more with the cellobiose model than the lignin model. The interaction energy of cellobiose–acetic anhydride was higher (about 20 kJ mol1 ) than that of lignin-acetic anhydride. DFT results on hydrogen bonding indicated that the hydroxyl group from cellobiose and the aromatic hydroxyl group from lignin models have similar energy values, which explain the equal strength of hydrogen bond interaction. The same trend was also obtained for the substitution of acetyl group in the hydroxyl group. MD results have also predicted that acetic anhydride forms a stronger interaction with cellobiose than with the lignin model, and these findings were in agreement with the DFT results.

National audience; Bone sarcomas are extremely invasive tumours, at the expense of patients prognosis. Precision of ablation of pathological tissue during surgical treatment can largely be improved and novel signalling pathways targeted by poly-chemotherapy must be discovered. The purpose of my project is to explore fundamental mechanisms underlying bone and Ewing sarcomas aggressiveness by means of computer-based simulations at the tissue and molecular scales. We have recently hypothesised that sarcomas proliferation results from the double catalysis of sarcomas by bone tissue and bone tissue by sarcomas. The spectacular morphology of the remodelled bone tissue in presence of tumour cells may well be induced by this synergetic effect triggered by signalling molecules released by sarcomas. We have developed a simple model based on a cellular automaton of the evolution of bone tissue and sarcoma morphology accounting for both catalytic effects. Simulations results show the dependence of the morphology to the double catalysis. This demonstration orients our recent research toward clarifying the specific molecular signals capable of triggering this synergetic mechanism. To that extent, I am now pursuing our investigations at the molecular scale by investigating the mechanisms of mineralisation of collagen fibrils altered by such potential molecular signalling. I perform molecular dynamics simulations of the hydration of collagen microfibrils to determine how mineral transport and deposition occurs. These simulations will help us understand in detail the catalytic effect of sarcoma on bone tissue remodelling, and in particular why its results in weakly mineralised collagen structures similar to osteid.

International audience; We present a new multistage method to study the N-Methyl-D-Aspartate (NMDA) neuroreceptor starting from the reconstruction of its crystallographic structure. Thanks to the combination of Homology Modelling, Molecular Dynamics and Lattice Boltzmann simulations, we analyse the allosteric transition of NDMA upon ligand binding and compute the receptor response to ionic passage across the membrane.

The dispersion of inorganic particles within polymeric materials is an extensively used method to enhance their mechanical properties. One of the major challenges in the simulation of polymer composites is to model the uneven surface of the fillers which strongly affects the dynamics of the adsorbed polymers and consequently the macroscopic mechanical properties of the final composite. Here we propose a new multiscale approach that, using experimental adsorption data, constructs the filler surface to statistically reproduce the surface defects. We use this approach to analyse the structure and dynamics of highly entangled polyisoprene melt in contact with different realistic carbon black samples. We show that the presence of the heterogeneous surface has a negligible influence on the structure of the polymer chains but a major effect on their dynamics and the surface wettability.

Photoelectrochemical (PEC) splitting of water to make hydrogen is a promising clean-energy technology. The oxygen evolution reaction (OER) largely determines the energy efficiency in PEC water-splitting. Hematite, which is a cheap and sustainable semiconductor material with excellent chemical properties, a favourable band gap (2.1 eV) and composed of earth abundant elements is a suitable model photoanode material for studying OER. To understand the design of energy efficient anodes, it is highly desirable to have mechanistic insight into OER at an atomistic level which can be directly connected to experimentally measured quantities. We present a multiscale computational model of OER which connects the thermodynamics and kinetics of elementary charge transfer reactions in OER to kinetics of OER at laboratory length and time scales. We couple density functional theory (DFT) and DFT based molecular dynamics (DFT-MD) simulations with solvent effects at an atomistic level with kinetic Monte Carlo (kMC) simulations at a coarse-grained level in our multiscale model. The time and applied bias potential dependent surface coverage, which are experimentally not known, and the O2 evolution rate during OER at the hematite-water interface are calculated by the multiscale model. Furthermore, the multiscale model demonstrates the effect of explicitly modelling the interaction of water with the electrode surface via direct adsorption. This journal is

Morphologies of adsorbed molecular films are of interest in a wide range of applications. To study the epitaxial growth of these systems in computer simulations requires access to long time and length scales, and one typically resorts to kinetic Monte Carlo (KMC) simulations. However, KMC simulations require as input transition rates and their dependence on external parameters (such as temperature). Experimental data allow only limited and indirect access to these rates, and models are often oversimplified. Here, we follow a bottom-up approach and aim at systematically constructing all relevant rates for an example system that has shown interesting properties in experiments, buckminsterfullerene on a calcium fluoride substrate. We develop classical force fields (both atomistic and coarse-grained) and perform molecular dynamics simulations of the elementary transitions in order to derive explicit expressions for the transition rates with a minimal number of free parameters.

The dispersion of inorganic particles within polymeric materials is an extensively used method to enhance their mechanical properties. One of the major challenges in the simulation of polymer composites is to model the uneven surface of the fillers which strongly affects the dynamics of the adsorbed polymers and consequently the macroscopic mechanical properties of the final composite. Here we propose a new multiscale approach that, using experimental adsorption data, constructs the filler surface to statistically reproduce the surface defects. We use this approach to analyse the structure and dynamics of highly entangled polyisoprene melt in contact with different realistic carbon black samples. We show that the presence of the heterogeneous surface has a negligible influence on the structure of the polymer chains but a major effect on their dynamics and the surface wettability.

Tese de Doutoramento em Ciências (Especialidade em Física), Esta tese é dedicada à simulação e modelação de poliisocianatos alifáticos, uma família de moléculas de reticulação usada na produção de poliuretanos. O seu uso é limitado pela sua elevada viscosidade, e entender a origem deste facto é essencial para sintetizar poliisocianatos de baixa viscosidade, permitindo processos mais sustentáveis com um uso reduzido de compostos químicos e solventes. O conhecimento fundamental sobre a viscosidade desta família molecular é escasso, e uma ampla gama de técnicas de simulação, abrangendo diferentes escalas, é utilizada para preencher essa lacuna. Um campo de força clássico para isocianatos foi desenvolvido e testado para permitir simulações de dinâmica molecular fiáveis da fase líquida. Os resultados da simulação reproduzem de forma excelente as viscosidades experimentais de poliisocianatos e sugerem a presença de interações peculiares entre anéis de isocianurato e os grupos isocianato, sendo possivelmente responsáveis pela origem da viscosidade dos poliisocianatos. A presença e o papel dessas interações são investigados usando uma ampla gama de métodos ab initio e de dinâmica molecular, revelando que os anéis de isocianurato são realmente capazes de fortes ligações não covalentes e que a interação isocianato-isocianurato é responsável pelo aumento viscosidade dos poliisocianatos. Este resultado encorajou a exploração da possibilidade de usar isocianuratos para a funcionalização não covalente de materiais 2D, e resultados promissores foram obtidos. Foi feita a simulação da formação de redes poliméricas reticuladas usando cadeias funcionalizadas nos extremos com isocianatos, usando o método da dinâmica de partículas com dissipação, conjugado com a modelação da reação de reticulação. Estudou-se as propriedades topológicas e capacidade de dilatação destas redes, demonstrando-se que esta nova abordagem permite obter redes poliméricas reticuladas cujas propriedades são muito próximas às obtidas com métodos tradicionais de processamento. Esta tese clarifica a ligação existente entre interações moleculares e as propriedades macroscópicas dos poliisocianatos, revelando o mecanismo responsável pelo comportamento da viscosidade dos poliisocianatos e fornecendo, ao mesmo tempo, ferramentas de simulação eficazes para o estudo futuro de materiais baseados nesta família de moléculas., This thesis is devoted to the simulation and modelling of aliphatic polyisocyanates, a family of crosslinking molecules which is the basic building block of polyurethane materials. Their use is limited by their high viscosity, and understanding its origin is fundamental to devise low-viscosity polyisocyanates, allowing for more sustainable processes with a reduced use of chemical compounds and solvents. Up to now, this knowledge was missing, and a wide range of simulation techniques, embracing different scales, is employed here to fill this gap. A classical force field for isocyanates is developed and tested to enable reliable liquid phase simulations using all-atom molecular dynamics. Simulation results reproduce very well the experimental viscosities of polyisocyanates and suggest the presence of peculiar interactions between isocyanurate rings and isocyanate groups, possibly involved in determining the isocyanates’ viscosity. The presence and role of these interactions is investigated using a wide range of ab initio methods and molecular dynamics free energy estimations, revealing that isocyanurate rings are indeed capable of strong non-covalent bindings, and that the isocyanate-isocyanurate interaction is responsible for the increased viscosity of polyisocyanates. Encouraged by this, we explore the possibility of using isocyanurates for non-covalent functionalization of 2D materials, and promising results are shown. Dissipative particle dynamics simulations, conjugated with a crosslinking reaction modelling, are employed to simulate the formation of polymer networks using isocyanate end-functionalized chains and study their swelling and topological properties. It is demonstrated that using the end-functionalized chains approach provides networks with properties very close to those obtained with traditional processing routes. This thesis clarifies the connection between molecular interactions and macroscopic properties of polyisocyanate systems, revealing the mechanism responsible of viscosity behaviour of polyisocyanates and providing, at the same time, effective simulation tools for further research., This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement no. 642890 (http://thelink-project.eu/). The project was supported by the Portuguese Foundation for Science and Technology(FCT) grant number SFRH/BD/128666/2017 and partly supported by FCT in the framework of the Strategic Funding UID/FIS/04650/2013 and by the project ”Search-ON2: Revitalization of HPC infrastructure of Uminho” (NORTE-07-0162-FEDER-0000869), under the National Strategic Reference Framework, through the European Regional Development Fund.

In dieser Arbeit ist eine Methodik entwickelt worden, um Adsorptionsprozesse mithilfe eines multiskalen Verfahrens am Beispiel der CO2-Abtrennung von Kraftwerksabgasen und der Olefin/Paraffin-Trennung auszulegen. Von allen Treibhausgasen ist die Emissionsmenge von CO2 anteilig am größten, welche hauptsächlich von der energieerzeugenden Industrie emittiert werden. Momentan wird CO2 mittels einer Aminwäsche vom Abgas abgetrennt, welche allerdings den Nachteil hat, dass sie einen sehr hohen Energieverbrauch wegen der Rückgewinnung des Lösemittels hat. Der Adsorptionsprozess kann diese Technologie mit "metal-organic frameworks" (MOFs) als Adsorbentien potentiell ersetzen. Wissenschaftliche Studien zeigten, dass Mg-MOF-74 wegen seiner offenen Adsorptionsstellen an Metallatomen eines der besten Materialien für die Abtrennung von CO2 aus Kraftwerksabgasen ist, wobei gleichzeitig auch Wasser adsorbiert wird. Kraftfelder sind entwickelt und getestet worden, um die Adsorption und Diffusion mit molekularen Simulationen vorherzusagen. Adsorptionsisothermen und Selbstdiffusionskoeffzienten sind sowohl für die Reinstoffe als auch Mischungen bestimmt worden. Es kann gezeigt werden, dass Wasser nahezu komplett aus dem Gas entfernt werden muss, damit Mg-MOF-74 sein volles Trennpotential erreicht. Die Simulation eines Festbettadsorbers mit diesem System beweist, dass diese Technologie eine Alternative darstellt. Ethen und Propen sind zwei der wichtigsten Ressourcen der chemischen Industrie. Die Trennung dieser Stoffe von ihren paraffnen Gegenstücken ist wegen ähnlicher Stoffeigenschaften sehr schwierig. Zur Zeit werden solche Mischungen in einer kryogenen Destillationskolonne getrennt, welche einen sehr hohen Energieverbrauch hat. Der Vorteil eines Adsorptionsprozesses mit MOFs ist, dass er bei Umgebungsbedingungen stattfinden kann und somit weniger Energie benötigt. In dieser Arbeit werden ZIF-8, ZIF-9, ZIF-71 und IFP-n (n=1, 3, 5, 7) bezüglich ihrer Kapazitäten als Adsorbent für diese Art Trennproblem untersucht. Adsorptionsisothermen werden mit molekularen Simulationen berechnet und mit experimentellen Daten verglichen, wobei es eine hohe Übereinstimmung beider Methoden gibt. Die meisten Kristalle sind hierbei olefin-selektiv. Diffusionsuntersuchungen haben ergeben, dass die Flexibilität der Kristalle eine große Rolle für die Mobilität der Gastmoleküle spielt. Die Simulation eines Festbettadsorbers, welcher mit ZIF-8 gefüllt ist, beweist, dass die Trennung prinzipiell machbar ist. Diese Arbeit hat gezeigt, dass die hier entwickelte Methodik auch für komplexe Trennprobleme über mehrere Zeit- und Längenskalen erfolgreich angewendet werden kann., A methodology for the design of adsorption processes by a multi-scale approach is developed, using the two separation problems of CO2 sequestration from flue gas and olefin/paraffin-separation as examples for this ansatz. Out of all greenhouse gases CO2 is emitted the most, in particular from the energy generating industry. Currently, the state-of-the-art technology to remove CO2 from flue gases is amine scrubbing, which has the disadvantage of high energy consumption because of the solvent regeneration step. The adsorption process is a potential replacement for this technology, using metalorganic frameworks (MOFs) as adsorption material. Mg-MOF-74 has been identified in the literature as one of the best materials for the removal of CO2 from flue gas because of its open metal sites, which strongly interact with CO2 and water. In order to predict the adsorption accurately in molecular simulations a force field for both species is developed. Adsorption isotherms and self-diffusivity were calculated for each pure component and for mixtures using molecular simulations. We show that in order to use Mg-MOF-74 to its fullest potential, water has to be removed from the system almost completely. Fixed-bed adsorber simulations show as a proof of principle that an adsorption process using Mg-MOF-74 is a promising alternative. Ethene and propene are the two most important chemical feedstocks for the chemical industry. The separation of those two components from their respective paraffin-counterpart is very difficult because of their similar structure and molecular and thermophysical properties. The state-of-the art process to separate olefin/paraffin-mixtures is the cryogenic distillation, which is carried out at temperatures as low as -100°C, and therefore, has a high energy consumption. The advantage of adsorption processes is that they can run at ambient conditions using MOFs as adsorbent, making it a potential replacement technology. In this work, ZIF-8, ZIF-9, ZIF-71, IFP-1, IFP-3, IFP-5, and IFP-7 are investigated regarding their separation potential for the separation of olefin/paraffin-mixtures. Adsorption isotherms are calculated by molecular simulations and compared to experiments, showing a very good agreement for the C2 and C3 molecules. In most crystals, the selectivity is slightly in favor of the olefin. Diffusion studies show that the flexibility of the frameworks plays an important role during diffusion processes. The simulation of a fixed-bed adsorption process indicates that the separation is feasible with ZIF-8 as adsorption material. This work demonstrates that the developed methodology can be applied to complex separation problems successfully, modelling the process on an atomistic scale all the way up to an industrial sized fixed-bed apparatus.

The electrical conductivity of graphene rubber nanocomposites under large deformation is studied based on multiscale modeling with effective medium theory and molecular dynamics simulations. The effects of graphene filling volume fractions, graphene dispersion patterns and interfacial interaction strengths of graphene/rubber are investigated on the electrical properties of the composites. The results show that the strain-resistance sensitivity of the composites is determined by graphene volume fractions and the relationship between the average spacing of graphene sheets and the strain, which might take a nonlinear form for the system with large initial spacing ratios of graphene. Detailed analysis of graphene clusters and system energy reveals that too high or too low interfacial interaction might decrease the strain-resistance sensitivity by preventing the decomposition of large graphene clusters while moderate interfacial interaction can help maintain the structure of graphene conductive networks with high strain-resistance sensitivity.

Lytic polysaccharide monooxygenase (LPMO) enzymes have attracted considerable attention due to their ability to enhance polysaccharide depolymerization, making them interesting in respect to production of biofuel from cellulose. The LPMOs are metalloenzymes that contain a mononuclear copper active site that can active dioxygen. However, many details of this activation are unclear, and have previously been investigated from a computational angle. Yet, these studies have either employed only molecular mechanics (MM), which are inaccurate for metal active sites, or they have described only the active site with quantum mechanics (QM) and neglected the effect of the protein. Here, we employ hybrid QM and MM (QM/MM) methods to investigate the first steps of the LPMO mechanism, which is reduction of of Cu(II) to Cu(I) and formation of a Cu(II)-superoxide complex. In the latter complex, the superoxide can bind either in an equatorial or an axial position. For both steps we obtain structures that are markedly different from previous suggestions, based on vacuum calculations. Our calculations show that the equatorial isomer of the superoxide complex is over 60 kJ/mol more stable than the axial isomer, being stabilized by interactions with a second-coordination-sphere Gln residue, showing a possible role for this residue. Coordination of superoxide in this manner is in agreement with recent experimental suggestions., 21 pages, 6 figures, 3 tables. 20 pages Supporting Information

Beryllium is proposed to be a neutron multiplier and plasma facing material in future fusion devices. Therefore, it is crucial to acquire an understanding of the microscopic mechanisms of tritium accumulation and release as a result of transmutation processes that Be undergoes under neutron irradiation. A multiscale simulation of ad- and desorption of hydrogen isotopes on the beryllium (0001) surface is developed. It consists of ab initio calculations of certain H adsorption configurations, a suitable cluster expansion approximating the energies of arbitrary configurations, and a kinetic Monte Carlo method for dynamic simulations of adsorption and desorption. The processes implemented in the kinetic Monte Carlo simulation are deduced from further ab initio calculations comprising both, static relaxation as well as molecular dynamics runs. The simulation is used to reproduce experimental data and the results are compared and discussed. Based on the observed results, proposals for a refined model are made.

The capillary and dynamic wetting behaviour in porous media is crucial in many engineering problems which are highly related to the multiphase interactions between fluids and solids. This thesis will focus on the behaviour of dynamic contact angle of the supercritical CO2/water flow in the silica slit as a function of the contact line velocity at both the nanoscale and microscale, which can help us gain an in-depth understanding of the dynamic processes in CO2 geosequestration in saline aquifers. Our molecular dynamics (MD) simulations calculate the contact angle quantitatively at different velocities at the nanoscale and also validate the molecular kinetic theory through the detailed analysis of the equilibrium jump distance and frequency of the water and CO2 molecules at the solid surfaces. While the MD simulations provide the results of dynamic contact angle at the nanoscale, which can be suitable for the nanopores of the low permeability rock, the dynamic contact angle behaviour at the microscale is also important and investigated in this thesis. This work also develops a coarse-grained molecular dynamic (CGMD) framework to model the liquid-vapour-solid interactions at the microscale. The newly developed CGMD framework has been applied and extended to the study of the dynamic contact angle for the CO2-water-silica system at the microscale. The microscale CGMD simulation of CO2-water-silica system shows that there is an increase in the CO2 contact angle as the increase of the contact line velocity at three different pressures. The dynamic contact angles under a water pressure of 18.9 MPa seem to be slightly larger than those under the water pressures of 9.41 MPa and 14.3 MPa. Moreover, the comparison between the MD and CGMD results suggests that there could be a pore size effect on the dynamic contact angle for the studied CO2-water-silica system.

The present study investigates the dissolution behaviour of cellulose and hemicellulose in potential ionic liquids (ILs) using both the quantum chemical and experimental validation. For converging upon the recommended IL, 1428 ILs consisting of 42 cations and 34 anions were studied with the conductor like screening model for real solvents (COSMO-RS) model. Based on the infinite dilution activity coefficient of the components in IL, the selected anions and cations were visualised by observing their interactions with cellulose and hemicellulose using interaction energies, natural bonding orbital analysis and molecular dynamics simulations. The dissolution order of cellulose and hemicellulose in ILs was primarily determined by the evaluation of hydrogen bonds between the oxygen atom of anion and hydroxyl proton of cellulose/hemicellulose. From this discernible fact, the anion of the IL was observed to play a leading role in the solvation process as compared to the cation. Eventually, acetate [OAc]– anion and 1-ethyl-3-methylimidazolium [EMIM]+ cation were found to be good candidates for the dissolution of cellulose and hemicellulose. This was further confirmed by the measurement of solid-liquid equilibria with cellulose and hemicellulose. The regenerated cellulose powder was then characterised by Fourier transform spectroscopy(FTIR), X-ray diffraction (XRD) and Thermal gravimetric analysis (TGA).

The long perceived notion that G-Protein Coupled Receptors (GPCRs) function in monomeric form has recently been changed by the description of a number of GPCRs that are found in oligomeric states. The mechanism of GPCR oligomerization, and its effect on receptor function, is not well understood. In the present study, coarse grained molecular dynamics (CGMD) approach was adopted for studying the self-assembly process of the human GPCR, @b2-adrenergic receptor (@b2-AR), for which several experimental evidences of the dimerization process and its effect on cellular functions are available. Since the crystal structure of @b2-AR lacks the third intracellular loop, initially it was modelled and simulated using restrained MD in order to get a stable starting conformation. This structure was then converted to CG representation and 16 copies of it, inserted into a hydrated lipid bilayer, were simulated for [email protected] using the MARTINI force field. At the end of [email protected], oligomers of @b2-AR were found to be formed through the self-assembly mechanism which were further validated through various analyses of the receptors. The lipid bilayer analysis also helped to quantify this assembly mechanism. In order to identify the domains which are responsible for this oligomerization, a reverse transformation of the CG system back to all-atom structure and simulated annealing run were carried out at the end of [email protected] CGMD run. Analysis of the all-atom dimers thus obtained, revealed that TM1/TM1, H8/H8, TM1/TM5 and TM6/TM6 regions formed most of the dimerization surfaces, which is in accordance with some of the experimental observations and recent simulation results.

This chapter introduces MesoBioNano Explorer (MBN Explorer) (Solov’yov et al. J Comput Chem 33:2412–2439, (2012), [1]), a software package for the advanced multiscale simulations of complex molecular structure and dynamics and highlights some of its biomedical and nanotechnology applications. MBN Explorer has many unique features, a wide range of applications in Physics, Chemistry, Biology, Material Science, and in related Industries. It is suitable for classical molecular dynamics, Monte Carlo and relativistic dynamics simulations of a large range of molecular systems of different kind, such as nano- and biological systems, nanostructured materials, composite/hybrid materials, gases, liquids, solids and various interfaces, with the sizes ranging from atomic to mesoscopic. MBN Explorer can be exploited together with MBN Studio (Solov’yov et al. MBN Studio, (2015), [2]), a specially developed graphical user interface.

International audience

This thesis addresses the sampling problem in a high-dimensional space, i.e., the computation of averages with respect to a defined probability density that is a function of many variables. Such sampling problems arise in many application areas, including molecular dynamics, multiscale models, and Bayesian sampling techniques used in emerging machine learning applications. Of particular interest are thermostat techniques, in the setting of a stochastic-dynamical system, that preserve the canonical Gibbs ensemble defined by an exponentiated energy function. In this thesis we explore theory, algorithms, and numerous applications in this setting. We begin by comparing numerical methods for particle-based models. The class of methods considered includes dissipative particle dynamics (DPD) as well as a newly proposed stochastic pairwise Nosé-Hoover-Langevin (PNHL) method. Splitting methods are developed and studied in terms of their thermodynamic accuracy, two-point correlation functions, and convergence. When computational efficiency is measured by the ratio of thermodynamic accuracy to CPU time, we report significant advantages in simulation for the PNHL method compared to popular alternative schemes in the low-friction regime, without degradation of convergence rate. We propose a pairwise adaptive Langevin (PAdL) thermostat that fully captures the dynamics of DPD and thus can be directly applied in the setting of momentum-conserving simulation. These methods are potentially valuable for nonequilibrium simulation of physical systems. We again report substantial improvements in both equilibrium and nonequilibrium simulations compared to popular schemes in the literature. We also discuss the proper treatment of the Lees-Edwards boundary conditions, an essential part of modelling shear flow. We also study numerical methods for sampling probability measures in high dimension where the underlying model is only approximately identified with a gradient system. These methods are important in multiscale modelling and in the design of new machine learning algorithms for inference and parameterization for large datasets, challenges which are increasingly important in "big data" applications. In addition to providing a more comprehensive discussion of the foundations of these methods, we propose a new numerical method for the adaptive Langevin/stochastic gradient Nosé-Hoover thermostat that achieves a dramatic improvement in numerical efficiency over the most popular stochastic gradient methods reported in the literature. We demonstrate that the newly established method inherits a superconvergence property (fourth order convergence to the invariant measure for configurational quantities) recently demonstrated in the setting of Langevin dynamics. Furthermore, we propose a covariance-controlled adaptive Langevin (CCAdL) thermostat that can effectively dissipate parameter-dependent noise while maintaining a desired target distribution. The proposed method achieves a substantial speedup over popular alternative schemes for large-scale machine learning applications.

In this study, different scale analyses have been performed to understand the very beginning stage of the Ni–Cr(1 1 1) binary alloy surface oxidation mechanism. The finite elements method (FEM) has been applied to find the stress intensity effect on a compact tension (CT) specimen crack tip, and a 2-μm rectangular region has been prepared for the quasi-continuum (QC) model. The displacement load calculated by FEM was applied at the upper and lower boundaries of the QC model. The obtained atomic positions of the deformed crystal structure were considered for quantum chemical molecular dynamics (QCMD) analysis by placing water molecules on the surface. Water molecules dissociate on the top site followed by the quick diffusion of hydrogen atoms on the surface through the hollow sites. Hydrogen is easily transported into the lattice due to its small atomic size. Increases in stress intensity factor (K) act to deform the structure, which augments oxygen penetration and reduces hydrogen diffusion time; as a consequence, changes in K result in an increase of metallic surface oxidation. Oxygen preferentially bonds with chromium to develop a protective passive film on the surface, and the quickly diffused hydrogen is trapped on the metal surface. Hydrogen bonds with the metal by receiving electrons and, therefore, works as an oxidant on the surface and weakens the metal atomic bond at the primary stage. Initially, the oxidized surface forms a strong bond with oxygen, resulting in the breakage of metal–metal bonds. Therefore, this hydrogen action enhances the very early stage surface oxidation.

Ab initio simulations aimed at modelling and interpreting STM induced molecular isomerization of naphthalocyanine molecule are presented. Free energy profile, reaction path and activation energies were obtained using the metadynamics method in the frame of Car-Parrinello Molecular Dynamics (CPMD). We propose a multiscale model of the molecular switch process, based on the Ehrenfest Molecular Dynamics and on the knowledge of the electronic excited states as computed from ab initio calculations. The time evolution of the electronic density during the switch process induced by an external bias potential is calculated exploiting the multiscale model. Simulations were performed on IBM Blue Gene/P supercomputer at Moscow State University.

Most materials phenomena are manifestations of processes that are operative ove ra vast range of length and time scales. A complete understanding of the behaviour of materials thereby requires theoretical and computational tools that span the atomic-scale detail of first-principles methods and the more coarsegrained description provided by continuum equations. Recent efforts have focused on combining traditional methodologies—density functional theory, molecular dynamics, Monte Carlo methods and continuum descriptions— within a unified multiscale framework. This review covers the techniques that have been developed to model various aspects of materials behaviour with the ultimate aim of systematically coupling the atomistic to the continuum descriptions. The approaches described typically have been motivated by particular applications but can often be applied in wider contexts. The selfassembly of quantum dot ensembles will be used as a case study for the issues that arise and the methods used for all nanostructures. Although quantum dots can be obtained with all the standard growth methods and for a variety of material systems, their appearance is a quite selective process, involving the competition between equilibrium and kinetic effects, and the interplay between atomistic and long-range interactions. Most theoretical models have addressed particular aspects of the ordering kinetics of quantum dot ensembles, with fa rf ewer attempts at a comprehensive synthesis of this inherently multiscale phenomenon. We conclude with an assessment of the current status of multiscale modelling strategies and highlight the main outstanding issues.

Permeation of small molecules across membrane channels can be measured by a multiscale computational protocol based on Brownian dynamics and the potential of mean force formalism. In this article we look at ways to compute the potential of mean force by reusing pre-existing molecular dynamics trajectories via a protocol centered on instantaneous forward/reverse transformations. We apply the method to the energetics of water across the narrow channel formed by Gramicidin A and reproduce several features of the energy barrier across the channel albeit at a coarse level of detail due to limits imposed by the exponential averages intrinsic to the method and the small size of the channel. The implications for ions and less dense systems are briefly discussed.

This chapter presents multi-scale models of the reactions that occur in the in situ oil sands upgrading process. Its focus is on the various modelling tools and their applications to the benzene hydrogenation reactions catalyzed by molybdenum carbide nanoparticles. As the reaction mechanism of benzene hydrogenation on molybdenum carbide is not clear, we start with density functional theory (DFT) studies to elucidate the reaction mechanism, using both periodic and cluster models. Benzene hydrogenation on molybdenum carbide follows the Langmuir-Hinshelwood mechanism, with the six-member ring tilting up gradually. A tight-binding quantum chemical molecular dynamics (TB-QCMD) method is used to track the physical motion of the atoms in the reaction processes of C6H6 on a Mo-terminated α-Mo2C (0001) surface. The approximate DFT method, density functional tight-binding (DFTB), was parameterized to allow the quantum mechanical treatment of nanoscale systems. With the nudged elastic band method, the potential energy profiles of benzene hydrogenation on molybdenum carbide nanoparticles have been obtained. Finally a force field was brought in to describe the solvent environment in the system, leading to a multiscale quantum mechanical/molecular mechanical (QM/MM) model. This study suggests that entropy and the environment play important roles in heterogeneous reactions catalyzed by molybdenum carbide nanoparticles.

We used a combination of ab-initio force relaxation and empirical molecular dynamics simulations to study the atomic structure of a dense monolayer of benzene- or anthracene-terminated alkyl chains chemisorbed onto a (100) Si surface. We find a transition to a free-rotor phase at about 400 K, with the chains rising to a nearly perpendicular orientation to the surface. At the same temperature, other internal degrees of freedom of the molecules are activated. Above the transition an increase in free-surface roughness is observed. We compare our findings to experimental results of the synthesis of self-assembled monolayers as molecular current rectifiers in silicon-integrated nanoscale electronics.

A key issue for the simulation of radiation effects in reactor pressure vessel (RPV) steels is the kinetics of formation of Cu–vacancy complexes (Cu–VC) in a ferritic matrix, starting from displacement cascade debris. In the present work the evolution of molecular dynamics (MD) and corresponding binary collision approximation (BCA) displacement cascades has been studied using two different kinetic Monte Carlo (KMC) techniques in Fe–0.2% Cu. This exercise allows an assessment of the cascade debris features that are likely to influence their long-term evolution in interaction with the solute atoms, as well as the differences between simulation techniques. The results show that, at the current level of approximation of KMC methods, the use of BCA as damage input in KMC simulations does not introduce major biases, the difference with respect to the use of an MD source being a second-order effect. This justifies the use of BCA cascade debris as input damage for KMC parametric studies of Cu precipitation in Fe ...

International audience; We report some recent applications of multiscale modelling to the transport of ions, water and CO 2 in clays. On the one hand, simulations on different scales allow to investigate the physico-chemical processes underlying the geochemical and transport behaviour of these fluids in the interparticle pores and at the surface of clay minerals. We discuss more specifically the insights gained from molecular simulations on the acidity of surface edge sites, ion exchange and the behaviour of clay interlayers in contact with a CO 2 reservoir. On the other hand, upscaling the descriptions from the molecular level to the macroscopic scale without forgetting the fundamental role of interfaces on the mesoscopic scale provides a means to capture complex phenomena such as electrokinetic couplings. We illustrate the complementarity of molecular dynamics, lattice-based mesoscopic simulations and Pore Network Models to address this issue.

Atomic- and continuum-scale computer simulation techniques have now become sufficiently powerful that many phenomena associated with radiation damage effects in metals can be modelled with a high degree of realism. Recent studies of several such phenomena are reviewed here. Primary knock-on atoms (PKAs) that recoil under collision from energetic atomic particles such as neutrons or ions are the principal source of damage. At high enough recoil energy, they create cascades of atomic displacements that result in single and clustered self-interstitial and vacancy defects. The time and length scales of the cascade process are ideally suited to atomic-scale computer simulation by molecular dynamics (MD). This method provides data on the number of defects produced and their distribution in clusters. This information was not available from earlier models and so the nature of the primary damage state is now much clearer. MD is also being used to reveal the nature of the motion and interaction of defects. Prediction and understanding of mechanical properties of irradiated metals requires simulation of dislocation–obstacle interactions. Models based on the continuum approximation are now being extended by large-scale MD simulations of the motion of dislocations gliding through irradiation-induced features such as voids and precipitates, and these reveal the strength and weakness of the earlier studies. Dynamic effects at temperatures greater than 0 K are also being investigated. The place of modelling in the multiscale problems of radiation damage is emphasised.

This paper discusses some current trends in computational materials science, especially the striving to forge links between modelling activities at various length and timescales. At the atomistic scale, methods based on quantum mechanical, especially density-functional, theories for electronic properties link to atomic/molecular dynamics and kinetic Monte Carlo simulations. Coarse graining leads to lattice-gas and cellular automata, and eventually to continuum equations solved by finite-element and finite-difference techniques. As examples of hierarchical modelling of materials, the paper describes recent work on anisotropic chemical etching of silicon, irradiation processing of fullerenes, oxygen clustering in silicon and self-diffusion in the compound semiconductor GaSb.

Fluctuations of liquids at the scales where the hydrodynamic and atomistic descriptions overlap are considered. The importance of these fluctuations for atomistic motions is discussed and examples of their accurate modelling with a multi-space–time-scale fluctuating hydrodynamics scheme are provided. To resolve microscopic details of liquid systems, including biomolecular solutions, together with macroscopic fluctuations in space–time, a novel hybrid atomistic–fluctuating hydrodynamics approach is introduced. For a smooth transition between the atomistic and continuum representations, an analogy with two-phase hydrodynamics is used that leads to a strict preservation of macroscopic mass and momentum conservation laws. Examples of numerical implementation of the new hybrid approach for the multiscale simulation of liquid argon in equilibrium conditions are provided.

Rapid progress in first principles modelling of nanostructured materials currently provides many good opportunities to investigate interfacial electron transfer processes in detail and to guide the development of technologically important applications such as nanoscale energy conversion. New multiscale modelling methods also offer significant prospects for studying complex materials and processes that are still too challenging for pure ab initio calculations, including advanced force field simulation methods designed to bridge the gap between accurate but time-consuming quantum chemical calculations and fast, but usually less accurate, molecular dynamics simulations.

The structural responses of silicon and silicon carbide under hydrostatic compression have been analyzed by using Tersoff interatomic potential function. We show the elastic stability criteria, based on the elastic stiffness coefficients gives consistent predictions of critical pressures at which the lattices become unstable with molecular dynamics simulations. However, the predicted values are considerably higher than that of another prediction based on the thermodynamic criteria. By calculating activation barriers for the homogeneous silicon phase transition from cubic diamond to β-Sn, we suggest that the elastic and thermodynamic criteria give upper and lower bounds respectively on the transition pressure. We also show that the effect of the atomic size disparity between Si and C atoms can be dominant in favoring amorphization over polymorphic transition in silicon carbide.

The goal of multiscale modelling of heterogeneous catalytic reactors is the prediction of all steps, starting from the reaction mechanism at the active centre, the rates of reaction, adsorption and diffusion processes inside the porous system of the catalyst support, based on first principles, quantum chemistry, force field simulations and macroscopic differential equations. The progress in these fields of research will be presented, including linking models between the various levels of description. Alkylation of benzene will be used as an example to demonstrate the various approaches from the active centre to the reactor.

The pharmaceutical industry uses computer models at many stages during drug development. Quantum and molecular models are used to predict the crystal structures of potential active pharmaceutical ingredients (APIs), whereas discrete element models are used to optimise the mechanical properties of mixtures of APIs and excipient powders. The present work combines the strengths of modelling from all of the mentioned length scales to predict the behaviour of macroscopic powder granules from first principles using the molecular and crystal structures of acetazolamide as an example API. Starting with a single molecule of acetazolamide, ab initio self-consistent field calculations were used to calculate the equilibrium gas phase structure, vibrational spectra, interaction energy with water molecules and perform potential energy scans. By using these results and following the CHARMM General Force Field parameterisation process, all of the parameters required to perform a molecular dynamics simulation were iteratively determined using the CHARMM program. Next, by using crystallographic data from literature, the monoclinic and triclinic forms of the acetazolamide crystal were simulated. Material properties like the Young’s modulus and Poisson ratio, and surface energies have been calculated. These material properties are then used as input parameters in a discrete element model containing Thornton’s plastic model and the JKR cohesive force to predict the behaviour of macroscopic acetazolamide powder in angle of repose tests and tabletting simulations. Similar methodologies can be employed in the future to evaluate at an early stage the performance of novel APIs and excipients for tabletting applications.The pharmaceutical industry uses computer models at many stages during drug development. Quantum and molecular models are used to predict the crystal structures of potential active pharmaceutical ingredients (APIs), whereas discrete element models are used to optimise the mechanical properties of mixtures of APIs and excipient powders. The present work combines the strengths of modelling from all of the mentioned length scales to predict the behaviour of macroscopic powder granules from first principles using the molecular and crystal structures of acetazolamide as an example API. Starting with a single molecule of acetazolamide, ab initio self-consistent field calculations were used to calculate the equilibrium gas phase structure, vibrational spectra, interaction energy with water molecules and perform potential energy scans. By using these results and following the CHARMM General Force Field parameterisation process, all of the parameters required to perform a molecular dynamics simulation were iterati...

In this article, we present a computational multiscale model for the characterization of subcellular proteins. The model is encoded inside a simulation tool that builds coarse-grained (CG) force fields from atomistic simulations. Equilibrium molecular dynamics simulations on an all-atom model of the actin filament are performed. Then, using the statistical distribution of the distances between pairs of selected groups of atoms at the output of the MD simulations, the force field is parameterized using the Boltzmann inversion approach. This CG force field is further used to characterize the dynamics of the protein via Brownian dynamics simulations. This combination of methods into a single computational tool flow enables the simulation of actin filaments with length up to 400 nm, extending the time and length scales compared to state-of-the-art approaches. Moreover, the proposed multiscale modeling approach allows to investigate the relationship between atomistic structure and changes on the overall dynamics and mechanics of the filament and can be easily (i) extended to the characterization of other subcellular structures and (ii) used to investigate the cellular effects of molecular alterations due to pathological conditions.

The macroscopic functionality of soft (bio-)materials is often triggered by quantum-mechanical events which are highly local in space and time. In order to arrive at the resulting macroscopically observable phenomena, many orders of magnitude need to be bridged on both the time and the length scale. In the present paper, we first introduce a range of simulation methods at different scales as well as theoretical approaches to form bridges between them. We then outline a strategy to develop an adaptive multiscale simulation approach which connects the quantum to the mesoscopic level by bringing together ab initio molecular dynamics (QM), classical (force field) molecular dynamics (MM), and coarse grained (CG) simulation techniques. With a multitude of photoactive materials in mind, we apply our methodology to a prototypical test case—light-induced phase transitions in a liquid crystal containing the azobenzene photoswitch. published

This work presents a preliminary multiscale computational investigation of the effects of nucleotides and cations on the mechanics of actin filaments (F-actin). At the molecular level, Molecular Dynamics (MD) simulations are employed to characterize the rearrangements of the actin monomers (G-actin) in terms of secondary structures evolution in physiological conditions. At the mesoscale level, a coarse grain (CG) procedure is adopted where each monomer is represented by means of Elastic Network Modeling (ENM) technique. At the macroscale level, actin filaments up to hundreds of nanometers are assumed as isotropic and elastic beams and characterized via Rotation Translation Block (RTB) analysis. F-actin bound to adenosine triphosphate (ATP) shows a persistence length around 5 μm, while actin filaments bound to adenosine diphosphate (ADP) have a persistence length of about 3 μm. With magnesium bound to the high affinity binding site of G-actin, the persistence length of F-actin decreases to about 2 μm only in the ADP-bound form of the filament, while the same ion has no effects, in terms of stiffness variation, on the ATP-bound form of F-actin. The molecular mechanisms behind these changes in flexibility are herein elucidated. Thus, this study allows to analyze how the local binding of cations and nucleotides on G-actin induce molecular rearrangements that transmit to the overall F-actin, characterizing shifts of mechanical properties, that can be related with physiological and pathological cellular phenomena, as cell migration and spreading. Further, this study provides the basis for upcoming investigating of network and cellular remodelling at higher length scales.

International audience; This work presents numerical simulations of indentation at different scales. The indentation test is chosen to illustrate the multiscale approach used in most modern studies of crystalline plasticity. The multiscale approach proposed in this work consists of passing information from one model up to another model operating at an upper scale. At the atomic scale, molecular dynamics simulations give access to the shape and position of the first dislocations induced by indentation. This information is then passed to a dislocation dynamics model that can simulate dislocation organization while the loading proceeds. At the continuum level, finite element simulations are conducted within the framework of crystal plasticity. The constitutive equations used in the continuum model are informed by dedicated dislocation dynamics simulations. Finite element simulations are quantitatively compared to experimental data demonstrating that the dislocation dynamics computations are pertinent.

We have developed both 10- and 2-site molecular dynamics simulation models of biological membranes, tested their ability to model various lipid phases, and to reproduce important membrane physical properties, particularly the lateral pressure profile which is critical in determining the phases adopted in lipid systems [1]. The novelty in these models lies predominantly in the way they capture shape anisotropy, and the realistic way in which electrostatic interactions are incorporated. Furthermore, through careful design, the 10-site model in particular is compatible with atomistic models, allowing multiscale simulations of membrane systems [2].In this presentation, the design philosophy and parameterisation procedures for these models will be described, together with their validation, with a particular focus on their lateral pressure profiles and phase behaviour. The application of these models in the context of multiscale simulations will then be considered. First, their use to calculate the permeability coefficients of small molecules through phospholipid bilayers, by combining molecular dynamics simulations with constraints, will be outlined [3]. Second, the effect of small molecules on membrane properties will be discussed, focusing particularly on antibacterials, which, it is postulated, may work through modifying the underlying physics of the membrane.[1] M. Orsi, D. Y. Haubertin, W. E. Sanderson and J. W. Essex, J. Phys. Chem. B, 2008, 112, 802-815.[2] J. Michel, M. Orsi and J. W. Essex, J. Phys. Chem. B, 2008, 112, 657-660.[3] M. Orsi, W.E. Sanderson and J.W. Essex, J. Phys. Chem. B, 2009, 113, 12019-12029.

Two original/modified Ball-Grimes models and one original/modified Lewis-Catlow models, are used in multiscale modelling of mixed mode fracture of Magnesia. The specimen is decomposed into a far field (modelled by linear elastic fracture mechanics), a near field (modelled by Atomistic Field Theory) and a crack-tip region (modelled by molecular dynamics). When two atoms get too close during the simulation of crack propagation, the attraction force artificially overcomes the repulsive barrier (Buckingham Catastrophe). The numerical results of three original models show significantly different phenomena. To demonstrate the sensitivity of interatomic potential and to prevent the catastrophe, three modified models are used. Numerical results of three modified models are compared and discussed.

Protein‐surface interactions are exploited in various processes in life sciences and biotechnology. Many of such processes are performed in presence of a buffer system, which is generally believed to have an influence on the protein‐surface interaction but is rarely investigated systematically. Combining experimental and theoretical methodologies, we herein demonstrate the strong influence of the buffer type on protein‐surface interactions. Using state of the art chromatographic experiments, we measure the interaction between individual amino acids and silica, as a reference to understand protein‐surface interactions. Among all the 20 proteinogenic amino acids studied, we found that arginine (R) and lysine (K) bind most strongly to silica, a finding validated by free energy calculations. We further measured the binding of R and K at different pH in presence of two different buffers, MOPS (3‐(N‐morpholino)propanesulfonic acid) and TRIS (tris(hydroxymethyl)aminomethane), and find dramatically different behavior. In presence of TRIS, the binding affinity of R/K increases with pH, whereas we observe an opposite trend for MOPS. These results can be understood using a multiscale modelling framework combining molecular dynamics simulation and Langmuir adsorption model. The modelling approach helps to optimize buffer conditions in various fields like biosensors, drug delivery or bio separation engineering prior to the experiment., How do buffers affect protein surface interactions? Experimental zonal elution chromatography helps to identify interactions of silica surfaces with amino acids. These interactions can be comprehended with a multiscale modelling framework combining molecular dynamics simulation and different flavors of the classical Langmuir adsorption model.

Bu çalışmanın ana konusunu, son yıllarda fiziksel özellikleriyle araştırmacıların ilgi odağında olan nikel nanoteller oluşturmaktadır. Tek kristalli nikel nanotellerin mekanik özellikleri moleküler dinamik simülasyonları vasıtasıyla incelenmiş ve literatürdeki deneysel çalışmalardan da faydalanılarak mühendislik parametreleri (elastisite modülü, akma gerilmesi ve maksimum gerilme) için ölçeklendirme kuralı geliştirilmiştir. Ayrıca nikel naotellerin deformasyon esnasındaki kristal yapısının değişimi ortak komşu analizi ile ortaya konmuştur. Bu çalışmanın en önemli hedefi; nikel nanoteller özelinde çok ölçekli modelleme için literatüre ölçeklendirme kuralı kazandırmaktır. The nickel nanowires which have been the focus of researchers' attention for their physical properties in recent years are the main subject of this study. The mechanical properties of the single crystal nickel nanowires have been investigated with the help of molecular dynamics simulations and scaling law has been developed for engineering parameters (elasticity modulus, yield stress and maximum stress) by using earlier published experimental studies. In addition, the evolution of crystal structure during the deformation of nickel nanowires was examined by common neighbor analysis. The most important goal of this study is to develop a scaling law for multi-scale modeling of the nickel nanowires.

Bu çalışmanın ana konusunu, son yıllarda fiziksel özellikleriyle araştırmacıların ilgi odağında olan nikel nanoteller oluşturmaktadır. Tek kristalli nikel nanotellerin mekanik özellikleri moleküler dinamik simülasyonları vasıtasıyla incelenmiş ve literatürdeki deneysel çalışmalardan da faydalanılarak mühendislik parametreleri (elastisite modülü, akma gerilmesi ve maksimum gerilme) için ölçeklendirme kuralı geliştirilmiştir. Ayrıca nikel naotellerin deformasyon esnasındaki kristal yapısının değişimi ortak komşu analizi ile ortaya konmuştur. Bu çalışmanın en önemli hedefi; nikel nanoteller özelinde çok ölçekli modelleme için literatüre ölçeklendirme kuralı kazandırmaktır.

Zweikomponentensysteme (TCS), bestehend aus einer Sensorhistidinkinase (HK) und einem Antwortregulationsprotein, sind Schlüsselbausteine in bakteriellen Signaluebertragungsmechanismen. Die Fähigkeit von Bakterien auf eine breite Vielfalt von chemischen und physikalischen Stimuli angemessen zu reagieren ist ausschlaggebend für ihr Überleben. Es ist daher nicht überraschend, dass TCS zu den meistuntersuchten bakteriellen Proteinsystemen gehört. Sensorhistidinkinasen sind typischerweise in die Zellmembran integrierte, homodimere Proteine bestehend aus mehreren Domänen. Reizwahrnehmung an der Sensordomäne von HK löst eine Reihe von großskaligen Konformationsübergangen entlang der Domänen aus. Während sich die strukturellen Eigenschaften von verschiedenen HKs unterscheiden können, erhalten sie alle einen katalytischen ATP-bindenden Kern (CA) und dimerisierende Histidinphosphotransferdomänen (DHp). Während der Signalkaskade nimmt der Kern eine asymmetrische Konformation an, sodass die Kinase an einem der Protomere aktiv ist und die der anderen inaktiv. Das ermöglicht es dem ATP in einer der CA-Domänen seine $\gamma$-Phosphatgruppe an das Histidin der DHp abzugeben. Diese Phosphorylgrouppe wird anschließend an das Antwortregulationsprotein weitergegeben, die eine angemessene Reaktion der Zelle veranlasst. In der vorliegenden Arbeit untersuche ich die Konformationsdynamik des Kinasekerns mithilfe von Molekulardynamiksimulationen (MD). Der Fokus der Arbeit liegt auf zwei verschiedenen HKs: WalK und CpxA. Wegen der Größe der Systeme und den erforderlichen biologischen Zeitskalen, ist es nicht möglich die relevanten Konformationsübergänge in klassischen MD-Simulationen zu berechnen. Um dieses Problem zu umgehen, verwende ich ein strukturbasiertes Modell mit paarweisen harmonischen Potentialen. Diese Näherung erlaubt es, den Übergang zwischen dem inaktiven und den aktiven Zustand mit wesentlich geringerem rechnerischen Aufwand zu untersuchen. Nachdem ich das System mithilfe dieses vereinfachten Modells erkundet habe, benutze ich angereicherte Stichprobenverfahren mit atomistischen Modellen um detailliertere Einsichten in die Dynamik zu gewinnen. Die Ergebnisse in dieser Arbeit legen nahe, dass das Verhalten der einzelnen Unterdomänen des Kinasekerns eng miteinander gekoppelt ist.