Continuum variational and diffusion quantum Monte Carlo calculations

This topical review describes the methodology of continuum variational and diffusion quantum Monte Carlo calculations. These stochastic methods are based on many-body wave functions and are capable of achieving very high accuracy. The algorithms are intrinsically parallel and well-suited to petascale computers, and the computational cost scales as a polynomial of the number of particles. A guide to the systems and topics which have been investigated using these methods is given. The bulk of the article is devoted to an overview of the basic quantum Monte Carlo methods, the forms and optimisation of wave functions, performing calculations within periodic boundary conditions, using pseudopotentials, excited-state calculations, sources of calculational inaccuracy, and calculating energy differences and forces

Extraction of the materials parameters that determine the mobility in disordered organic semiconductors from the current-voltage characteristics : accuracy and limitations

The development and application of predictive models for organic electronic devices with a complex layer structure, such as white organic light-emitting diodes, require the availability of an accurate and fast method for extracting the materials parameters, which determine the mobility in each of the layers from a set of experimental data. The absence of such a generally used method may be regarded as one of the reasons why so far relatively little consensus has been obtained concerning the most appropriate transport model, the shape of the density of states (DOS), and the underlying microscopic parameters, such as the width of the DOS and the density of hopping sites. In this paper, we present a time-efficient Gauss-Newton method for extracting these parameters from current-voltage curves for single-carrier devices, obtained for various layer thicknesses and temperatures. The method takes the experimental uncertainties into account and provides the correlated uncertainty margins of the parameters studied. We focus on materials with a Gaussian DOS with random and spatially correlated disorder. Making use of artificially generated as well as experimental data sets, we demonstrate the accuracy and limitations, and show that it is possible to deduce the type of disorder from the analysis. The presence of an exponential trap DOS, as is often observed for the case of electron transport, is found to significantly reduce the accuracy of the transport parameters obtained

Clostridioides difficile infection (CDI) epidemiology and patient characteristics in Switzerland.

Clostridioides difficile infection (CDI) is a disease with high morbidity and mortality rates. The objective of this study was to describe CDI epidemiology and patient characteristics over a 5-year period in Switzerland and assess risk factors for mortality, recurrence and severe CDI. We retrospectively included all consecutive CDI cases having occurred in adult patients hospitalized in two tertiary centers: the Lausanne University Hospital (1000 beds) and the University Hospital of Zurich (900 beds), between 2014 and 2018. Suspected cases of CDI were identified from the microbiology laboratory database on the basis of a positive test and confirmed by records review. During first CDI episodes, the median age was 67 years and the median Charlson comorbidity index (CCI) score was 5. All in all, 299 out of 826 patients (36.2%) had severe infection based on the Infectious Diseases Society of America criteria. In the multivariable analysis, CCI was associated with increased risk of mortality. None of the factors recorded on admission were significantly associated with increased risk of recurrence. In the multivariable analysis, male sex and CCI were associated with severity, while immunosuppression was associated with less severe presentation. If we did not identify any criteria on admission that could be predictive of recurrences, this could be explained the retrospective nature of the study. A higher comorbidity index is a key driver for severe CDI and mortality. Reporting of CDI is not mandatory in Switzerland; structuration of CDI reporting should be a short-term priority