A classification of data quality assessment and improvement methods

Data quality (DQ) assessment and improvement in larger information systems would often not be feasible without using suitable “DQ methods”, which are algorithms that can be automatically executed by computer systems to detect and/or correct problems in datasets. Currently, these methods are already essential, and they will be of even greater importance as the quantity of data in organisational systems grows. This paper provides a review of existing methods for both DQ assessment and improvement and classifies them according to the DQ problem and problem context. Six gaps have been identified in the classification, where no current DQ methods exist, and these show where new methods are required as a guide for future research and DQ tool development.This is the accepted manuscript. It's currently embargoed pending publication by Inderscience

Perspective: On the active site model in computational catalyst screening

First-principles screening approaches exploiting energy trends in surface adsorption represent an unparalleled success story in recent computational catalysis research. Here we argue that our still limited understanding of the structure of active sites is one of the major bottlenecks towards an ever extended and reliable use of such computational screening for catalyst discovery. For low-index transition metal surfaces, the prevalently chosen high-symmetry (terrace and step) sites offered by the nominal bulk-truncated crystal lattice might be justified. For more complex surfaces and composite catalyst materials, computational screening studies will need to actively embrace a considerable uncertainty with respect to what truly are the active sites. By systematically exploring the space of possible active site motifs, such studies might eventually contribute towards a targeted design of optimized sites in future catalysts

Equilibrium free energies from fast-switching trajectories with large time steps

Jarzynski's identity for the free energy difference between two equilibrium states can be viewed as a special case of a more general procedure based on phase space mappings. Solving a system's equation of motion by approximate means generates a mapping that is perfectly valid for this purpose, regardless of how closely the solution mimics true time evolution. We exploit this fact, using crudely dynamical trajectories to compute free energy differences that are in principle exact. Numerical simulations show that Newton's equation can be discretized to low order over very large time steps (limited only by the computer's ability to represent resulting values of dynamical variables) without sacrificing thermodynamic accuracy. For computing the reversible work required to move a particle through a dense liquid, these calculations are more efficient than conventional fast switching simulations by more than an order of magnitude. We also explore consequences of the phase space mapping perspective for systems at equilibrium, deriving an exact expression for the statistics of energy fluctuations in simulated conservative systems

Generalized molecular solvation in non-aqueous solutions by a single parameter implicit solvation scheme

In computer simulations of solvation effects on chemical reactions, continuum modeling techniques regain popularity as a way to efficiently circumvent an otherwise costly sampling of solvent degrees of freedom. As effective techniques, such implicit solvation models always depend on a number of parameters that need to be determined earlier. In the past, the focus lay mostly on an accurate parametrization of water models. Yet, non-aqueous solvents have recently attracted increasing atten- tion, in particular, for the design of battery materials. To this end, we present a systematic parametrization protocol for the Self-Consistent Continuum Solvation (SCCS) model resulting in optimized parameters for 67 non-aqueous solvents. Our parametrization is based on a collection of ≈6000 experimentally measured partition coefficients, which we collected in the Solv@TUM database presented here. The accuracy of our optimized SCCS model is comparable to the well-known universal continuum solvation model (SMx) family of methods, while relying on only a single fit parameter and thereby largely reducing sta- tistical noise. Furthermore, slightly modifying the non-electrostatic terms of the model, we present the SCCS-P solvation model as a more accurate alternative, in particular, for aromatic solutes. Finally, we show that SCCS parameters can, to a good degree of accuracy, also be predicted for solvents outside the database using merely the dielectric bulk permittivity of the solvent of choice

Embedded-Cluster Calculations in a Numeric Atomic Orbital Density-Functional Theory Framework

We integrate the all-electron electronic structure code FHI-aims into the general ChemShell package for solid-state embedding (QM/MM) calculations. A major undertaking in this integration is the implementation of pseudopotential functionality into FHI-aims to describe cations at the QM/MM boundary through effective core potentials and therewith prevent spurious overpolarization of the electronic density. Based on numeric atomic orbital basis sets, FHI-aims offers particularly efficient access to exact exchange and second order perturbation theory, rendering the established QM/MM setup an ideal tool for hybrid and double-hybrid level DFT calculations of solid systems. We illustrate this capability by calculating the reduction potential of Fe in the Fe-substituted ZSM-5 zeolitic framework and the reaction energy profile for (photo-)catalytic water oxidation at TiO2(110).Comment: 12 pages, 4 figure

Equilibrium Sampling From Nonequilibrium Dynamics

We present some applications of an Interacting Particle System (IPS) methodology to the field of Molecular Dynamics. This IPS method allows several simulations of a switched random process to keep closer to equilibrium at each time, thanks to a selection mechanism based on the relative virtual work induced on the system. It is therefore an efficient improvement of usual non-equilibrium simulations, which can be used to compute canonical averages, free energy differences, and typical transitions paths

Photoswitching in nanoporous, crystalline solids: an experimental and theoretical study for azobenzene linkers incorporated in MOFs

In this article, we use the popular photoswitchable molecule, azobenzene, to demonstrate that the embedding in a nanoporous, crystalline solid enables a precise understanding of light-induced, reversible molecular motion. We investigate two similar azobenzene-containing, pillared-layer metal–organic frameworks (MOFs): Cu2(AzoBPDC)2(BiPy) and Cu2(NDC)2(AzoBiPy). Experimental results from UV-vis spectroscopy and molecular uptake experiments as well as theoretical results based on density-functional theory (DFT) show that in the Cu2(AzoBPDC)2(BiPy) MOF structure, the azobenzene side groups undergo photoisomerization when irradiated with UV or visible light. In a very similar MOF structure, Cu2(NDC)2(AzoBiPy), the experimental studies show an unexpected absence of photoisomerization. The DFT calculations reveal that in both MOFs the initial and final states of the photoswitching process (the trans and the cis conformation) have similar energies, which strongly suggests that the reason for the effective blocking of photoswitching in the AzoBiPy-based MOFs must be related to the switching process itself. More detailed calculations show that in Cu2(NDC)2(AzoBiPy) a naphthalene linker from the molecular framework blocks the photoisomerization trajectory which leads from the trans to the cis conformation. For Cu2(AzoBPDC)2(BiPy), as a result of the different geometry, such a steric hindrance is absent

Convergence Without Hard Criteria: Does EU Soft Law Affect Domestic Unemployment Protection Schemes?

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