Spatio-temporal correlations in aqueous systems: computational studies of static and dynamic heterogeneity by 2D-IR spectroscopy

Local heterogeneity is ubiquitous in natural aqueous systems. It can be caused locally by external biomolecular subsystems like proteins, DNA, micelles and reverse micelles, nanoscopic materials etc., but can also be intrinsic to the thermodynamic nature of the aqueous solution itself (like binary mixtures or at the gas-liquid interface). The altered dynamics of water in the presence of such diverse surfaces has attracted considerable attention in recent years. As these interfaces are quite narrow, only a few molecular layers thick, they are hard to study by conventional methods. The recent development of two dimensional infra-red (2D-IR) spectroscopy allows us to estimate length and time scales of such dynamics fairly accurately. In this work, we present a series of interesting studies employing two dimensional infra-red spectroscopy (2D-IR) to investigate (i) the heterogeneous dynamics of water inside reverse micelles of varying sizes, (ii) supercritical water near the Widom line that is known to exhibit pronounced density fluctuations and also study (iii) the collective and local polarization fluctuation of water molecules in the presence of several different proteins. The spatio-temporal correlation of confined water molecules inside reverse micelles of varying sizes is well captured through the spectral diffusion of corresponding 2D-IR spectra. In the case of supercritical water also, we observe a strong signature of dynamic heterogeneity from the elongated nature of the 2D-IR spectra. In this case the relaxation is ultrafast. We find remarkable agreement between the different tools employed to study the relaxation of density heterogeneity. For aqueous protein solutions, we find that the calculated dielectric constant of the respective systems unanimously shows a noticeable increment compared to that of neat water. However, the `effective' dielectric constant for successive layers shows significant variation, with the layer adjacent to the protein having a much lower value. Relaxation is also slowest at the surface. We find that the dielectric constant achieves the bulk value at distances more than 3 nm from the surface of the protein.

Non-covalent C-Cl center dot center dot center dot pi interaction in acetylene-carbon tetrachloride adducts: Matrix isolation infrared and ab initio computational studies

Non-covalent halogen-bonding interactions between n cloud of acetylene (C2H2) and chlorine atom of carbon tetrachloride (CCl4) have been investigated using matrix isolation infrared spectroscopy and quantum chemical computations. The structure and the energies of the 1:1 C2H2-CCl4 adducts were computed at the B3LYP, MP2 and M05-2X levels of theory using 6-311++G(d,p) basis set. The computations indicated two minima for the 1:1 C2H2-CCl4 adducts; with the C-Cl center dot center dot center dot pi adduct being the global minimum, where pi cloud of C2H2 is the electron donor. The second minimum corresponded to a C-H...Cl adduct, in which C2H2 is the proton donor. The interaction energies for the adducts A and B were found to be nearly identical. Experimentally, both C-Cl center dot center dot center dot pi and C-H center dot center dot center dot Cl adducts were generated in Ar and N2 matrixes and characterized using infrared spectroscopy. This is the first report on halogen bonded adduct, stabilized through C-Cl center dot center dot center dot pi interaction being identified at low temperatures using matrix isolation infrared spectroscopy. Atoms in Molecules (AIM) and Natural Bond Orbital (NBO) analyses were performed to support the experimental results. The structures of 2:1 ((C2H2)(2)-CCl4) and 1:2 (C2H2-(CCl4)(2)) multimers and their identification in the low temperature matrixes were also discussed. (C) 2015 Elsevier B.V. All rights reserved.

From transistor to trapped-ion computers for quantum chemistry

Over the last few decades, quantum chemistry has progressed through the development of computational methods based on modern digital computers. However, these methods can hardly fulfill the exponentially-growing resource requirements when applied to large quantum systems. As pointed out by Feynman, this restriction is intrinsic to all computational models based on classical physics. Recently, the rapid advancement of trapped-ion technologies has opened new possibilities for quantum control and quantum simulations. Here, we present an efficient toolkit that exploits both the internal and motional degrees of freedom of trapped ions for solving problems in quantum chemistry, including molecular electronic structure, molecular dynamics, and vibronic coupling. We focus on applications that go beyond the capacity of classical computers, but may be realizable on state-of-the-art trapped-ion systems. These results allow us to envision a new paradigm of quantum chemistry that shifts from the current transistor to a near-future trapped-ion-based technology.

Computational engineering design for micro-scale combustion devices: A thermally improved configuration

A multi-objective design optimisation study has been carried out with the objectives to improve the overall efficiency of the device and to reduce the fuel consumption for the proposed micro-scale combustor design configuration. In a previous study we identified the topology of the combustion chamber that produced improved behaviour of the device in terms of the above design criteria. We now extend our design approach, and we propose a new configuration by the addition of a micro-cooling channel that will improve the thermal behaviour of the design as previously suggested in literature. Our initial numerical results revealed an improvement of 2.6% in the combustion efficiency when we applied the micro-cooling channel to an optimum design configuration we identified from our earlier multi-objective optimisation study, and under the same operating conditions. The computational modelling of the combustion process is implemented in the commercial computational fluid dynamics package ANSYS-CFX using Finite Rate Chemistry and a single step hydrogen-air reaction. With this model we try to balance good accuracy of the combustion solution and at the same time practicality within the context of an optimisation process. The whole design system comprises also the ANSYS-ICEM CFD package for the automatic geometry and mesh generation and the Multi-Objective Tabu Search algorithm for the design space exploration. We model the design problem with 5 geometrical parameters and 3 operational parameters subject to 5 design constraints that secure practicality and feasibility of the new optimum design configurations. The final results demonstrate the reliability and efficiency of the developed computational design system and most importantly we assess the practicality and manufacturability of the revealed optimum design configurations of micro-combustor devices. Copyright © 2013 by ASME.

Computational modelling and characterisation of nanoparticle-based tuneable photonic crystal sensors

Photonic crystals are materials that are used to control or manipulate the propagation of light through a medium for a desired application. Common fabrication methods to prepare photonic crystals are both costly and intricate. However, through a cost-effective laser-induced photochemical patterning, one-dimensional responsive and tuneable photonic crystals can easily be fabricated. These structures act as optical transducers and respond to external stimuli. These photonic crystals are generally made of a responsive hydrogel that can host metallic nanoparticles in the form of arrays. The hydrogel-based photonic crystal has the capability to alter its periodicity in situ but also recover its initial geometrical dimensions, thereby rendering it fully reversible and reusable. Such responsive photonic crystals have applications in various responsive and tuneable optical devices. In this study, we fabricated a pH-sensitive photonic crystal sensor through photochemical patterning and demonstrated computational simulations of the sensor through a finite element modelling technique in order to analyse its optical properties on varying the pattern and characteristics of the nanoparticle arrays within the responsive hydrogel matrix. Both simulations and experimental results show the wavelength tuneability of the sensor with good agreement. Various factors, including nanoparticle size and distribution within the hydrogel-based responsive matrices that directly affect the performance of the sensors, are also studied computationally. © 2014 The Royal Society of Chemistry.

Influence of turbulence-chemistry interaction for n-heptane spray combustion under diesel engine conditions with emphasis on soot formation and oxidation

The influence of the turbulence-chemistry interaction (TCI) for n-heptane sprays under diesel engine conditions has been investigated by means of computational fluid dynamics (CFD) simulations. The conditional moment closure approach, which has been previously validated thoroughly for such flows, and the homogeneous reactor (i.e. no turbulent combustion model) approach have been compared, in view of the recent resurgence of the latter approaches for diesel engine CFD. Experimental data available from a constant-volume combustion chamber have been used for model validation purposes for a broad range of conditions including variations in ambient oxygen (8-21% by vol.), ambient temperature (900 and 1000 K) and ambient density (14.8 and 30 kg/m3). The results from both numerical approaches have been compared to the experimental values of ignition delay (ID), flame lift-off length (LOL), and soot volume fraction distributions. TCI was found to have a weak influence on ignition delay for the conditions simulated, attributed to the low values of the scalar dissipation relative to the critical value above which auto-ignition does not occur. In contrast, the flame LOL was considerably affected, in particular at low oxygen concentrations. Quasi-steady soot formation was similar; however, pronounced differences in soot oxidation behaviour are reported. The differences were further emphasised for a case with short injection duration: in such conditions, TCI was found to play a major role concerning the soot oxidation behaviour because of the importance of soot-oxidiser structure in mixture fraction space. Neglecting TCI leads to a strong over-estimation of soot oxidation after the end of injection. The results suggest that for some engines, and for some phenomena, the neglect of turbulent fluctuations may lead to predictions of acceptable engineering accuracy, but that a proper turbulent combustion model is needed for more reliable results. © 2014 Taylor & Francis.

QUANTITATIVE STRUCTURE-ACTIVITY-RELATIONSHIPS FOR TOXICITY OF PHENOLS USING REGRESSION-ANALYSIS AND COMPUTATIONAL NEURAL NETWORKS

Quantitative structure-toxicity models were developed that directly link the molecular structures of a et of 50 alkYlated and/or halogenated phenols with their polar narcosis toxicity, expressed as the negative logarithm of the IGC50 (50% growth inhibitor

Computational study of the growth of copper thin films by atomic layer deposition

Copper is the main interconnect material in microelectronic devices, and a 2 nm-thick continuous Cu film seed layer needs to be deposited to produce microelectronic devices with the smallest features and more functionality. Atomic layer deposition (ALD) is the most suitable method to deposit such thin films. However, the reaction mechanism and the surface chemistry of copper ALD remain unclear, which is deterring the development of better precursors and design of new ALD processes. In this thesis, we study the surface chemistries during ALD of copper by means of density functional theory (DFT). To understand the effect of temperature and pressure on the composition of copper with substrates, we used ab initio atomistic thermodynamics to obtain phase diagram of the Cu(111)/SiO2(0001) interface. We found that the interfacial oxide Cu2O phases prefer high oxygen pressure and low temperature while the silicide phases are stable at low oxygen pressure and high temperature for Cu/SiO2 interface, which is in good agreement with experimental observations. Understanding the precursor adsorption on surfaces is important for understanding the surface chemistry and reaction mechanism of the Cu ALD process. Focusing on two common Cu ALD precursors, Cu(dmap)2 and Cu(acac)2, we studied the precursor adsorption on Cu surfaces by means of van der Waals (vdW) inclusive DFT methods. We found that the adsorption energies and adsorption geometries are dependent on the adsorption sites and on the method used to include vdW in the DFT calculation. Both precursor molecules are partially decomposed and the Cu cations are partially reduced in their chemisorbed structure. It is found that clean cleavage of the ligand−metal bond is one of the requirements for selecting precursors for ALD of metals. 2 Bonding between surface and an atom in the ligand which is not coordinated with the Cu may result in impurities in the thin film. To have insight into the reaction mechanism of a full ALD cycle of Cu ALD, we proposed reaction pathways based on activation energies and reaction energies for a range of surface reactions between Cu(dmap)2 and Et2Zn. The butane formation and desorption steps are found to be extremely exothermic, explaining the ALD reaction scheme of original experimental work. Endothermic ligand diffusion and re-ordering steps may result in residual dmap ligands blocking surface sites at the end of the Et2Zn pulse, and in residual Zn being reduced and incorporated as an impurity. This may lead to very slow growth rate, as was the case in the experimental work. By investigating the reduction of CuO to metallic Cu, we elucidated the role of the reducing agent in indirect ALD of Cu. We found that CuO bulk is protected from reduction during vacuum annealing by the CuO surface and that H2 is required in order to reduce that surface, which shows that the strength of reducing agent is important to obtain fully reduced metal thin films during indirect ALD processes. Overall, in this thesis, we studied the surface chemistries and reaction mechanisms of Cu ALD processes and the nucleation of Cu to form a thin film.

Finite volume methods applied to the computational modelling of welding phenomena

This paper presents the computational modelling of welding phenomena within a versatile numerical framework. The framework embraces models from both the fields of computational fluid dynamics (CFD) and computational solid mechanics (CSM). With regard to the CFD modelling of the weld pool fluid dynamics, heat transfer and phase change, cell-centred finite volume (FV) methods are employed. Additionally, novel vertex-based FV methods are employed with regard to the elasto-plastic deformation associated with the CSM. The FV methods are included within an integrated modelling framework, PHYSICA, which can be readily applied to unstructured meshes. The modelling techniques are validated against a variety of reference solutions.

Correlation of solder paste rheology with computational simulations of the stencil printing process

Soldering technologies continue to evolve to meet the demands of the continuous miniaturisation of electronic products, particularly in the area of solder paste formulations used in the reflow soldering of surface mount devices. Stencil printing continues to be a leading process used for the deposition of solder paste onto printed circuit boards (PCBs) in the volume production of electronic assemblies, despite problems in achieving a consistent print quality at an ultra-fine pitch. In order to eliminate these defects a good understanding of the processes involved in printing is important. Computational simulations may complement experimental print trials and paste characterisation studies, and provide an extra dimension to the understanding of the process. The characteristics and flow properties of solder pastes depend primarily on their chemical and physical composition and good material property data is essential for meaningful results to be obtained by computational simulation.This paper describes paste characterisation and computational simulation studies that have been undertaken through the collaboration of the School of Aeronautical, Mechanical and Manufacturing Engineering at Salford University and the Centre for Numerical Modelling and Process Analysis at the University of Greenwich. The rheological profile of two different paste formulations (lead and lead-free) for sub 100 micron flip-chip devices are tested and applied to computational simulations of their flow behaviour during the printing process.

A computational model of coupled heat and moisture transfer with phase change in granular sugar during varying environmental conditions

As part of a comprehensive effort to predict the development of caking in granular materials, a mathematical model is introduced to model simultaneous heat and moisture transfer with phase change in porous media when undergoing temperature oscillations/cycling. The resulting model partial differential equations were solved using finite-volume procedures in the context of the PHYSICA framework and then applied to the analysis of sugar in storage. The influence of temperature on absorption/desorption and diffusion coefficients is coupled into the transport equations. The temperature profile, the depth of penetration of the temperature oscillation into the bulk solid, and the solids moisture content distribution were first calculated, and these proved to be in good agreement with experimental data. Then, the influence of temperature oscillation on absolute humidity, moisture concentration, and moisture migration for different parameters and boundary conditions was examined. As expected, the results show that moisture near boundary regions responds faster than farther away from them with surface temperature changes. The moisture absorption and desorption in materials occurs mainly near boundary regions (where interactions with the environment are more pronounced). Small amounts of solids moisture content, driven by both temperature and vapour concentration gradients, migrate between boundary and center with oscillating temperature.

Molecular Computational Elements Encode Large Populations of Small Objects

Since the introduction of molecular computation1, 2, experimental molecular computational elements have grown3, 4, 5 to encompass small-scale integration6, arithmetic7 and games8, among others. However, the need for a practical application has been pressing. Here we present molecular computational identification (MCID), a demonstration that molecular logic and computation can be applied to a widely relevant issue. Examples of populations that need encoding in the microscopic world are cells in diagnostics or beads in combinatorial chemistry (tags). Taking advantage of the small size9 (about 1 nm) and large 'on/off' output ratios of molecular logic gates and using the great variety of logic types, input chemical combinations, switching thresholds and even gate arrays in addition to colours, we produce unique identifiers for members of populations of small polymer beads (about 100 m) used for synthesis of combinatorial libraries10, 11. Many millions of distinguishable tags become available. This method should be extensible to far smaller objects, with the only requirement being a 'wash and watch' protocol12. Our focus on converting molecular science into technology concerning analog sensors13, 14, turns to digital logic devices in the present work.

Ion Association in [bmim][PF6]/Naphthalene Mixtures: An Experimental and Computational Study

Mixtures of room temperature ionic liquids (IL) with neutral organic molecules provide a valuable testing ground to investigate the interplay of the ionic and molecular-dipolar state in dense Coulomb systems at near ambient conditions. In the present study, the viscosity eta and the ionic conductivity a of 1-n-butyl-3-methylimidazolium hexafluorophosphate ([bmim][PF6])/naphthalene mixtures at T = 80 degrees C have been measured at 10 stoichiometries spanning the composition range from pure naphthalene to pure [bmim][PF6]. The viscosity grows nearly monotonically with increasing IL mole fraction (x), whereas the conductivity per ion displays a clear peak at x approximate to 15%. The origin of this maximum has been investigated using molecular dynamics simulations based on a classical force field. Snapshots of the simulated samples show that the conductivity maximum is due to the gradual transition in the IL component from an ionic state at high x to a dipolar fluid made of neutral ion pairs at low x. At concentrations x <0.20 the ion pairs condense into molecular-thin filaments bound by dipolar forces and extending in between nanometric droplets of IL. These results are confirmed and complemented by the computation of dynamic and transport properties in [bmim][PF6]/naphthalene mixtures at low IL concentration.