Density Functional Theory screening of gas-treatment strategies for stabilization of high energy-density lithium metal anodes

To explore the potential of molecular gas treatment of freshly cut lithium foils in non-electrolyte based passivation of high energy-density Li anodes, density functional theory (DFT) has been used to study the decomposition of molecular gases on metallic lithium surfaces. By combining DFT geometry optimization and Molecular Dynamics, the effects of atmospheric (N2, O2, CO2) and hazardous (F2, SO2) gas decomposition on Li(bcc) (100), (110), and (111) surfaces on relative surface energies, work functions, and emerging electronic and elastic properties are investigated. The simulations suggest that exposure to different molecular gases can be used to induce and control reconstructions of the metal Li surface and substantial changes (up to over 1 eV) in the work function of the passivated system. Contrary to the other considered gases, which form metallic adlayers, SO2 treatment emerges as the most effective in creating an insulating passivation layer for dosages <= 1 mono-layer. The substantial Li->adsorbate charge transfer and adlayer relaxation produce marked elastic stiffening of the interface, with the smallest change shown by nitrogen-treated adlayers

Performance and degradation of Proton Exchange Membrane Fuel Cells: State of the art in modeling from atomistic to system scale

Jahnke, T. et al.Proton Exchange Membrane Fuel Cells (PEMFC) are energy efficient and environmentally friendly alternatives to conventional energy conversion systems in many yet emerging applications. In order to enable prediction of their performance and durability, it is crucial to gain a deeper understanding of the relevant operation phenomena, e.g., electrochemistry, transport phenomena, thermodynamics as well as the mechanisms leading to the degradation of cell components. Achieving the goal of providing predictive tools to model PEMFC performance, durability and degradation is a challenging task requiring the development of detailed and realistic models reaching from the atomic/molecular scale over the meso scale of structures and materials up to components, stack and system level. In addition an appropriate way of coupling the different scales is required. This review provides a comprehensive overview of the state of the art in modeling of PEMFC, covering all relevant scales from atomistic up to system level as well as the coupling between these scales. Furthermore, it focuses on the modeling of PEMFC degradation mechanisms and on the coupling between performance and degradation models.The research leading to this review has been partially supported by the European Union's Seventh Framework Program for the Fuel Cells and Hydrogen Joint Technology Initiative under the project PUMA MIND (grant agreement no 303419).Peer Reviewe

Particle-modified Surface Plasmon Resonance Biosensor

Surface plasmon resonance (SPR) biosensors have attracted great attention in scientific research in the past three decades. Extensive studies on the immobilisation of biorecognition elements have been conducted in pursuit of higher sensitivity, but trialled formats have focussed on a thin layer modification next to the plasmon film, which usually requires in situ derivatization. This thesis investigates an ‘off-chip’ immobilisation strategy for SPR biosensing using silica particles and considers the implications of a particle-modified evanescent field on the signal amplitude and kinetics, for an exemplar affinity binding between immobilised IgG and its anti-IgG complement. Submicron silica particles were synthesized as carriers for the bio-recognition elements. They were then immobilised to form a sub-monolayer on the gold film of an SPR biosensor using two methods: thiolsilane coupling and physical adsorption aided by mechanical pressure. The bio-sensitivity towards an antigen/antibody interaction was lower than an SPR biosensor with an alkanethiolate SAM due to the difference in ligand capacity and position in the evanescent field. The binding kinetics of antigen/antibody pair was found to follow the Langmuir model closely in a continuous flow configuration but was heavily limited by the mass transport from the bulk to the sensor surface in a stop-flow configuration. A packed channel configuration was designed with larger gel particles as ligand carriers, packed on top of a gold film to create a column-modified SPR biosensor. This sensor has comparable bio-sensitivity to the previous sub-monolayer particle-modified systems, but the binding and dissociation of the analyte was heavily dependent on mass transport and binding equilibria across the column. A bi-directional diffusion mechanism was proposed based on a two-compartment mass transport model and the expanded model fitted well with the experimental data. The column-modified sensor was also studied by SPR imaging and analyte band formation was observed and analysed. Using the lateral resolution, a multiplexing particle column configuration was explored, and its potential in distinguishing a multicomponent analyte.Agency for Science Technology and Research, Singapor

Nonlinear Dynamic Modeling, Simulation And Characterization Of The Mesoscale Neuron-electrode Interface

Extracellular neuroelectronic interfacing has important applications in the fields of neural prosthetics, biological computation and whole-cell biosensing for drug screening and toxin detection. While the field of neuroelectronic interfacing holds great promise, the recording of high-fidelity signals from extracellular devices has long suffered from the problem of low signal-to-noise ratios and changes in signal shapes due to the presence of highly dispersive dielectric medium in the neuron-microelectrode cleft. This has made it difficult to correlate the extracellularly recorded signals with the intracellular signals recorded using conventional patch-clamp electrophysiology. For bringing about an improvement in the signalto-noise ratio of the signals recorded on the extracellular microelectrodes and to explore strategies for engineering the neuron-electrode interface there exists a need to model, simulate and characterize the cell-sensor interface to better understand the mechanism of signal transduction across the interface. Efforts to date for modeling the neuron-electrode interface have primarily focused on the use of point or area contact linear equivalent circuit models for a description of the interface with an assumption of passive linearity for the dynamics of the interfacial medium in the cell-electrode cleft. In this dissertation, results are presented from a nonlinear dynamic characterization of the neuroelectronic junction based on Volterra-Wiener modeling which showed that the process of signal transduction at the interface may have nonlinear contributions from the interfacial medium. An optimization based study of linear equivalent circuit models for representing signals recorded at the neuron-electrode interface subsequently iv proved conclusively that the process of signal transduction across the interface is indeed nonlinear. Following this a theoretical framework for the extraction of the complex nonlinear material parameters of the interfacial medium like the dielectric permittivity, conductivity and diffusivity tensors based on dynamic nonlinear Volterra-Wiener modeling was developed. Within this framework, the use of Gaussian bandlimited white noise for nonlinear impedance spectroscopy was shown to offer considerable advantages over the use of sinusoidal inputs for nonlinear harmonic analysis currently employed in impedance characterization of nonlinear electrochemical systems. Signal transduction at the neuron-microelectrode interface is mediated by the interfacial medium confined to a thin cleft with thickness on the scale of 20-110 nm giving rise to Knudsen numbers (ratio of mean free path to characteristic system length) in the range of 0.015 and 0.003 for ionic electrodiffusion. At these Knudsen numbers, the continuum assumptions made in the use of Poisson-Nernst-Planck system of equations for modeling ionic electrodiffusion are not valid. Therefore, a lattice Boltzmann method (LBM) based multiphysics solver suitable for modeling ionic electrodiffusion at the mesoscale neuron-microelectrode interface was developed. Additionally, a molecular speed dependent relaxation time was proposed for use in the lattice Boltzmann equation. Such a relaxation time holds promise for enhancing the numerical stability of lattice Boltzmann algorithms as it helped recover a physically correct description of microscopic phenomena related to particle collisions governed by their local density on the lattice. Next, using this multiphysics solver simulations were carried out for the charge relaxation dynamics of an electrolytic nanocapacitor with the intention of ultimately employing it for a simulation of the capacitive coupling between the neuron and the v planar microelectrode on a microelectrode array (MEA). Simulations of the charge relaxation dynamics for a step potential applied at t = 0 to the capacitor electrodes were carried out for varying conditions of electric double layer (EDL) overlap, solvent viscosity, electrode spacing and ratio of cation to anion diffusivity. For a large EDL overlap, an anomalous plasma-like collective behavior of oscillating ions at a frequency much lower than the plasma frequency of the electrolyte was observed and as such it appears to be purely an effect of nanoscale confinement. Results from these simulations are then discussed in the context of the dynamics of the interfacial medium in the neuron-microelectrode cleft. In conclusion, a synergistic approach to engineering the neuron-microelectrode interface is outlined through a use of the nonlinear dynamic modeling, simulation and characterization tools developed as part of this dissertation research

Design of a Graphene Nitrene Two-Dimensional Catalyst Heterostructure Providing a Well-Defined Site Accommodating 1 to 3 Metals, with Application to CO₂ Reduction Electrocatalysis for the 2 Metal Case

Recently, the reduction of CO₂ to fuels has been the subject of numerous studies, but the selectivity and activity remain inadequate. Progress has been made on single-site two-dimensional catalysts based on graphene coupled to a metal and nitrogen for the CO₂ reduction reaction (CO₂RR); however, the product is usually CO, and the metal–N environment remains ambiguous. We report a novel two-dimensional graphene nitrene heterostructure (grafiN₆) providing well-defined active sites (N₆) that can bind one to three metals for the CO₂RR. We find that homobimetallic FeFe–grafiN₆ could reduce CO₂ to CH₄ at −0.61 V and to CH₃CH₂OH at −0.68 V versus reversible hydrogen electrode, with high product selectivity. Moreover, the heteronuclear FeCu–grafiN₆ system may be significantly less affected by hydrogen evolution reaction, while maintaining a low limiting potential (−0.68 V) for C1 and C2 mechanisms. Binding metals to one N₆ site but not the other could promote efficient electron transport facilitating some reaction steps. This framework for single or multiple metal sites might also provide unique catalytic sites for other catalytic processes

Computational modelling of the effect of side chain chemistry on the micro-structure and electrolyte interactions of mixed transport polymers

As we scale up our use of energy storage facilities to meet the demands of the future, the prob- lems associated with current energy storage technologies will grow to unacceptable levels. In this work I explore how we can develop high performing polymers for use as cathode materials in energy storage devices operating with aqueous electrolytes. Energy storage devices using these materials have the potential for low cost production and safe operation. Through a combination of atomistic simulation methods, this thesis relates aspects of the polymer chemistry to their microstructural properties, and subsequently to their ability to operate successfully as electrodes.Open Acces

Modeling and Simulation of Thermo-Fluid-Electrochemical Ion Flow in Biological Channels

In this article we address the study of ion charge transport in the biological channels separating the intra and extracellular regions of a cell. The focus of the investigation is devoted to including thermal driving forces in the well-known velocity-extended Poisson-Nernst-Planck (vPNP) electrodiffusion model. Two extensions of the vPNP system are proposed: the velocity-extended Thermo-Hydrodynamic model (vTHD) and the velocity-extended Electro-Thermal model (vET). Both formulations are based on the principles of conservation of mass, momentum and energy, and collapse into the vPNP model under thermodynamical equilibrium conditions. Upon introducing a suitable one-dimensional geometrical representation of the channel, we discuss appropriate boundary conditions that depend only on effectively accessible measurable quantities. Then, we describe the novel models, the solution map used to iteratively solve them, and the mixed-hybrid flux-conservative stabilized finite element scheme used to discretize the linearized equations. Finally, we successfully apply our computational algorithms to the simulation of two different realistic biological channels: 1) the Gramicidin-A channel considered in~\cite{JeromeBPJ}; and 2) the bipolar nanofluidic diode considered in~\cite{Siwy7}