Computational design of metal-supported molecular switches: Transient ion formation during light- and electron-induced isomerisation of azobenzene

In molecular nanotechnology, a single molecule is envisioned to act as the basic building block of electronic devices. Such devices may be of special interest for organic photovoltaics, data storage, and smart materials. However, more often than not the molecular function is quenched upon contact with a conducting support. Trial-and-error-based decoupling strategies via molecular functionalisation and change of substrate have in many instances proven to yield unpredictable results. The adsorbate-substrate interactions that govern the function can be understood with the help of first-principles simulation. Employing dispersion-corrected Density-Functional Theory (DFT) and linear expansion Delta-Self-Consistent-Field DFT, the electronic structure of a prototypical surface-adsorbed functional molecule, namely azobenzene adsorbed to (111) single crystal facets of copper, silver and gold, is investigated and the main reasons for the loss or survival of the switching function upon adsorption are identified. The light-induced switching ability of a functionalised derivative of azobenzene on Au(111) and azobenzene on Ag(111) and Au(111) is assessed based on the excited-state potential energy landscapes of their transient molecular ions, which are believed to be the main intermediates of the experimentally observed isomerisation reaction. We provide a rationalisation of the experimentally observed function or lack thereof that connects to the underlying chemistry of the metal-surface interaction and provides insights into general design strategies for complex light-driven reactions at metal surfaces.Comment: 14 pages, 5 figures, submitted to J. Phys. Condens. Matte

Bistability loss as key feature in azobenzene (non-)switching on metal surfaces

Coinage metal adsorbed azobenzene is investigated as prototypical molecular switch. It is shown that switching capabilities are not just lost due to excited state quenching, but already due to changes in the ground state energetics. Electron demanding coadsorbates are suggested as strategy to regain the switching function.Comment: 8 pages, 3 figure

Assessing computationally efficient isomerization dynamics: Delta-SCF density-functional theory study of azobenzene molecular switching

We present a detailed comparison of the S0, S1 (n -> \pi*) and S2 (\pi -> \pi*) potential energy surfaces (PESs) of the prototypical molecular switch azobenzene as obtained by Delta-self-consistent-field (Delta-SCF) Density-Functional Theory (DFT), time-dependent DFT (TD-DFT) and approximate Coupled Cluster Singles and Doubles (RI-CC2). All three methods unanimously agree in terms of the PES topologies, which are furthermore fully consistent with existing experimental data concerning the photo-isomerization mechanism. In particular, sum-method corrected Delta-SCF and TD-DFT yield very similar results for S1 and S2, when based on the same ground-state exchange-correlation (xc) functional. While these techniques yield the correct PES topology already on the level of semi-local xc functionals, reliable absolute excitation energies as compared to RI-CC2 or experiment require an xc treatment on the level of long-range corrected hybrids. Nevertheless, particularly the robustness of Delta-SCF with respect to state crossings as well as its numerical efficiency suggest this approach as a promising route to dynamical studies of larger azobenzene-containing systems.Comment: 25 pages, 6 figure

Modelling Wind in the Electricity Sector

We represent hourly, regional an wind data and transmission constraints in an investment planning model calibrated to the UK and test sensitivities of least cost expansions to fuel and technology prices. Thus we can calculate the value of transmission expansions to the system. We represent limited public acceptance of wind and regional network constraints by maximum built rates per region and year. Thus we calculate the marginal value of improved planning and grid connection regimes. It is likely that some constraints will remain. Market designs that do not allow for regional differentiation to reflect transmission and planning constraints can increase overall costs to consumers

Multi-Lattice Kinetic Monte Carlo Simulations from First-Principles: Reduction of the Pd(100) Surface Oxide by CO

We present a multi-lattice kinetic Monte Carlo (kMC) approach that efficiently describes the atomistic dynamics of morphological transitions between commensurate structures at crystal surfaces. As an example we study the reduction of a $(\sqrt{5}\times \sqrt{5})R27^{\circ}$ PdO(101) overlayer on Pd(100) in a CO atmosphere. Extensive density-functional theory calculations are used to establish an atomistic pathway for the oxide reduction process. First-principles multi-lattice kMC simulations on the basis of this pathway fully reproduce the experimental temperature dependence of the reduction rate [Fernandes et al., Surf. Sci. 2014, 621, 31-39] and highlight the crucial role of elementary processes special to the boundary between oxide and metal domains.Comment: 19 pages, 10 figure

Electric vehicle battery model identification and state of charge estimation in real world driving cycles

This paper describes a study demonstrating a new method of state-of-charge (SoC) estimation for batteries in real-world electric vehicle applications. This method combines realtime model identification with an adaptive neuro-fuzzy inference system (ANFIS). In the study, investigations were carried down on a small-scale battery pack. An equivalent circuit network model of the pack was developed and validated using pulse-discharge experiments. The pack was then subjected to demands representing realistic WLTP and UDDS driving cycles obtained from a model of a representative electric vehicle, scaled match the size of the battery pack. A fast system identification technique was then used to estimate battery parameter values. One of these, open circuit voltage, was selected as suitable for SoC estimation, and this was used as the input to an ANFIS system which estimated the SoC. The results were verified by comparison to a theoretical Coulomb-counting method, and the new method was judged to be effective. The case study used a small 7.2 V NiMH battery pack, but the method described is applicable to packs of any size or chemistry

Low-cost programmable battery dischargers and application in battery model identification

This paper describes a study where a low-cost programmable battery discharger was built from basic electronic components, the popular MATLAB programming environment, and an low-cost Arduino microcontroller board. After its components and their function are explained in detail, a case study is performed to evaluate the discharger's performance. The setup is principally suitable for any type of battery cell or small packs. Here a 7.2 V NiMH battery pack including six cells is used. Consecutive discharge current pulses are applied and the terminal voltage is measured as the output. With the measured data, battery model identification is performed using a simple equivalent circuit model containing the open circuit voltage and the internal resistance. The identification results are then tested by repeating similar tests. Consistent results demonstrate accuracy of the identified battery parameters, which also confirms the quality of the measurement. Furthermore, it is demonstrated that the identification method is fast enough to be used in real-time applications

Representing molecule-surface interactions with symmetry-adapted neural networks

The accurate description of molecule-surface interactions requires a detailed knowledge of the underlying potential-energy surface (PES). Recently, neural networks (NNs) have been shown to be an efficient technique to accurately interpolate the PES information provided for a set of molecular configurations, e.g. by first-principles calculations. Here, we further develop this approach by building the NN on a new type of symmetry functions, which allows to take the symmetry of the surface exactly into account. The accuracy and efficiency of such symmetry-adapted NNs is illustrated by the application to a six-dimensional PES describing the interaction of oxygen molecules with the Al(111) surface.Comment: 13 pages including 8 figures; related publications can be found at http://www.fhi-berlin.mpg.de/th/th.htm

The Effect of Schooling and Ability on Achievement Test Scores

This paper develops two methods for estimating the effect of schooling on achievement test scores that control for the endogeneity of schooling by postulating that both schooling and test scores are generated by a common unobserved latent ability. These methods are applied to data on schooling and test scores. Estimates from the two methods are in close agreement. We find that the effects of schooling on test scores are roughly linear across schooling levels. The effects of schooling on measured test scores are slightly larger for lower latent ability levels. We find that schooling increases the AFQT score on average between 2 and 4 percentage points, roughly twice as large as the effect claimed by Herrnstein and Murray (1994) but in agreement with estimates produced by Neal and Johnson (1996) andWinship and Korenman (1997). We extend the previous literature by estimating the impact of schooling on measured test scores at various quantiles of the latent ability distribution.