Transport Properties of Highly Aligned Polymer Light-Emitting-Diodes

We investigate hole transport in polymer light-emitting-diodes in which the emissive layer is made of liquid-crystalline polymer chains aligned perpendicular to the direction of transport. Calculations of the current as a function of time via a random-walk model show excellent qualitative agreement with experiments conducted on electroluminescent polyfluorene demonstrating non-dispersive hole transport. The current exhibits a constant plateau as the charge carriers move with a time-independent drift velocity, followed by a long tail when they reach the collecting electrode. Variation of the parameters within the model allows the investigation of the transition from non-dispersive to dispersive transport in highly aligned polymers. It turns out that large inter-chain hopping is required for non-dispersive hole transport and that structural disorder obstructs the propagation of holes through the polymer film.Comment: 4 pages, 5 figure

Including a Cold Pool Representation in a Convection Parameterization and Simulating Its Impacts on the Spatial and Temporal Variability of the Precipitation in the NASA GEOS GCM

We developed and implemented a simple representation of a cold pool in the Grell-Freitas (GF) convection parameterization. The cold pool parameterization is based on the observation that convective-scale downdrafts produce a local deficit of the moist static energy (MSE). This information is advected and becoming downwind available to trigger and intensify new convection. The cold pool is dissipated by a simple exponential decay using a lifetime of a few hours, or by interacting with the underneath surface by exchanging latent and sensible heat fluxes. Preliminary results show some improvement of the simulation of the diurnal cycle of the precipitation over the land, mainly during the nighttime

Autocatalytic metallization of fabrics using Si ink, for biosensors, batteries and energy harvesting

Commercially available metal inks are mainly designed for planar substrates (for example, polyethylene terephthalate foils or ceramics), and they contain hydrophobic polymer binders that fill the pores in fabrics when printed, thus resulting in hydrophobic electrodes. Here, a low‐cost binder‐free method for the metallization of woven and nonwoven fabrics is presented that preserves the 3D structure and hydrophilicity of the substrate. Metals such as Au, Ag, and Pt are grown autocatalytically, using metal salts, inside the fibrous network of fabrics at room temperature in a two‐step process, with a water‐based silicon particle ink acting as precursor. Using this method, (patterned) metallized fabrics are being enabled to be produced with low electrical resistance (less than 3.5 Ω sq−1). In addition to fabrics, the method is also compatible with other 3D hydrophilic substrates such as nitrocellulose membranes. The versatility of this method is demonstrated by producing coil antennas for wireless energy harvesting, Ag–Zn batteries for energy storage, electrochemical biosensors for the detection of DNA/proteins, and as a substrate for optical sensing by surface enhanced Raman spectroscopy. In the future, this method of metallization may pave the way for new classes of high‐performance devices using low‐cost fabrics

Links between topography, wind, deflation, lakes and dust: The case of the Bodélé Depression, Chad

The Bodélé Depression, Chad is the planet's largest single source of dust. Deflation from the Bodélé could be seen as a simple coincidence of two key prerequisites: strong surface winds and a large source of suitable sediment. But here we hypothesise that long term links between topography, winds, deflation and dust ensure the maintenance of the dust source such that these two apparently coincidental key ingredients are connected by land-atmosphere processes with topography acting as the overall controlling agent. We use a variety of observational and numerical techniques, including a regional climate model, to show that: 1) contemporary deflation from the Bodélé is delineated by topography and a surface wind stress maximum; 2) the Tibesti and Ennedi mountains play a key role in the generation of the erosive winds in the form of the Bodélé Low Level Jet (LLJ); 3) enhanced deflation from a stronger Bodélé LLJ during drier phases, for example, the Last Glacial Maximum, was probably sufficient to create the shallow lake in which diatoms lived during wetter phases, such as the Holocene pluvial. Winds may therefore have helped to create the depression in which erodible diatom material accumulated. Instead of a simple coincidence of nature, dust from the world's largest source may result from the operation of long term processes on paleo timescales which have led to ideal conditions for dust generation in the world's largest dust source. Similar processes plausibly operate in other dust hotspots in topographic depressions

The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) ? Part 1: Model description and evaluation

International audienceWe introduce the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS). CATT-BRAMS is an on-line transport model fully consistent with the simulated atmospheric dynamics. Emission sources from biomass burning and urban-industrial-vehicular activities for trace gases and aerosol particles are obtained from several published datasets and remote sensing information. The tracer and aerosol mass concentration prognostic includes the effects of sub-grid scale turbulence in the planetary boundary layer, convective transport by shallow and deep moist convection, wet and dry deposition, and plume rise associated with vegetation fires in addition to the grid scale transport. The radiation parameterization takes into account the interaction between aerosol particles and short and long wave radiation. The atmospheric model BRAMS is based on the Regional Atmospheric Modeling System (RAMS), with several improvements associated with cumulus convection representation, soil moisture initialization and surface scheme tuned for the tropics, among others. In this paper the CATT-BRAMS model is used to simulate carbon monoxide and particulate material (PM2.5) surface fluxes and atmospheric transport during the 2002 LBA field campaigns, conducted during the transition from the dry to wet season in the southwest Amazon Basin. Model evaluation is addressed with comparisons between model results and near surface, radiosonde and airborne measurements performed during the field campaign, as well as remote sensing derived products. We show the matching of emissions strengths to observed carbon monoxide in the LBA campaign. A relatively good comparison to the MOPITT data, in spite of the fact that MOPITT a priori assumptions imply several difficulties, is also obtained

Structure, Photophysics and the Order-Disorder Transition to the Beta Phase in Poly(9,9-(di -n,n-octyl)fluorene)

X-ray diffraction, UV-vis absorption and photoluminescence (PL) spectroscopy have been used to study the well-known order-disorder transition (ODT) to the beta phase in poly(9,9-(di n,n-octyl)fluorene)) (PF8) thin film samples through combination of time-dependent and temperature-dependent measurements. The ODT is well described by a simple Avrami picture of one-dimensional nucleation and growth but crystallization, on cooling, proceeds only after molecular-level conformational relaxation to the so called beta phase. Rapid thermal quenching is employed for PF8 studies of pure alpha phase samples while extended low-temperature annealing is used for improved beta phase formation. Low temperature PL studies reveal sharp Franck-Condon type emission bands and, in the beta phase, two distinguishable vibronic sub-bands with energies of approximately 199 and 158 meV at 25 K. This improved molecular level structural order leads to a more complete analysis of the higher-order vibronic bands. A net Huang-Rhys coupling parameter of just under 0.7 is typically observed but the relative contributions by the two distinguishable vibronic sub-bands exhibit an anomalous temperature dependence. The PL studies also identify strongly correlated behavior between the relative beta phase 0-0 PL peak position and peak width. This relationship is modeled under the assumption that emission represents excitons in thermodynamic equilibrium from states at the bottom of a quasi-one-dimensional exciton band. The crystalline phase, as observed in annealed thin-film samples, has scattering peaks which are incompatible with a simple hexagonal packing of the PF8 chains.Comment: Submitted to PRB, 12 files; 1 tex, 1 bbl, 10 eps figure

Subseasonal Forecasting with an Icosahedral, Vertically Quasi-Lagrangian Coupled Model. Part I: Model Overview and Evaluation of Systematic Errors

The atmospheric hydrostatic Flow-Following Icosahedral Model (FIM), developed for medium-range weather prediction, provides a unique three-dimensional grid structurea quasi-uniform icosahedral horizontal grid and an adaptive quasi-Lagrangian vertical coordinate. To extend the FIM framework to subseasonal time scales, an icosahedral-grid rendition of the Hybrid Coordinate Ocean Model (iHYCOM) was developed and coupled to FIM. By sharing a common horizontal mesh, airsea fluxes between the two models are conserved locally and globally. Both models use similar adaptive hybrid vertical coordinates. Another unique aspect of the coupled model (referred to as FIMiHYCOM) is the use of the GrellFreitas scale-aware convective scheme in the atmosphere. A multiyear retrospective study is necessary to demonstrate the potential usefulness and allow for immediate bias correction of a subseasonal prediction model. In these two articles, results are shown based on a 16-yr period of hindcasts from FIMiHYCOM, which has been providing real-time forecasts out to a lead time of 4 weeks for NOAAs Subseasonal Experiment (SubX) starting July 2017. Part I provides an overview of FIMiHYCOM and compares its systematic errors at subseasonal time scales to those of NOAAs operational Climate Forecast System version 2 (CFSv2). Part II uses bias-corrected hindcasts to assess both deterministic and probabilistic subseasonal skill of FIMiHYCOM. FIMiHYCOM has smaller biases than CFSv2 for some fields (including precipitation) and comparable biases for other fields (including sea surface temperature). FIMiHYCOM also has less drift in bias between weeks 1 and 4 than CFSv2. The unique grid structure and physics suite of FIMiHYCOM is expected to add diversity to multimodel ensemble forecasts at subseasonal time scales in SubX

Sensitivity of feedback effects in CBMZ/MOSAIC chemical mechanism

To investigate the impact of the aerosol effects on meteorological variables and pollutant concentrations two simulations with the WRF-Chem model have been performed over Europe for year 2010. We have performed a baseline simulation without any feedback effects and a second simulation including the direct as well as the indirect aerosol effect. The paper describes the full configuration of the model, the simulation design, special impacts and evaluation. Although low aerosol particle concentrations are detected, the inclusion of the feedback effects results in an increase of solar radiation at the surface over cloudy areas (North-West, including the Atlantic) and decrease over more sunny locations (South-East). Aerosol effects produce an increase of the water vapor and decrease the planet boundary layer height over the whole domain except in the Sahara area, where the maximum particle concentrations are detected. Significant ozone concentrations are found over the Mediterranean area. Simulated feedback effects between aerosol concentrations and meteorological variables and on pollutant distributions strongly depend on the aerosol concentrations and the clouds. Further investigations are necessary with higher aerosol particle concentrations. WRF-Chem variables are evaluated using available hourly observations in terms of performance statistics. Standardized observations from the ENSEMBLE system web-interface were used. The research was developed under the second phase of Air Quality Model Evaluation International Initiative (AQMEII). WRF-Chem demonstrates its capability in capturing temporal and spatial variations of the major meteorological variables and pollutants, except the wind speed over complex terrain. The wind speed bias may affect the accuracy in the chemical predictions (NO2, SO2). The analysis of the correlations between simulated data sets and observational data sets indicates that the simulation with aerosol effects performs slightly better. These results indicate potential importance of the aerosol feedback effects and an urgent need to further improve the representations in current atmospheric models to reduce uncertainties at all scales

X-ray Raman scattering study of aligned polyfluorene

We present a non-resonant inelastic x-ray scattering study at the carbon K-edge on aligned poly[9,9-bis(2-ethylhexyl)-fluorene-2,7-diyl] and show that the x-ray Raman scattering technique can be used as a practical alternative to x-ray absorption measurements. We demonstrate that this novel method can be applied to studies on aligned $\pi$-conjugated polymers complementing diffraction and optical studies. Combining the experimental data and a very recently proposed theoretical scheme we demonstrate a unique property of x-ray Raman scattering by performing the symmetry decomposition on the density of unoccupied electronic states into $s$- and $p$-type symmetry contributions.Comment: 19 pages, 8 figure

Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

Abstract. Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of three-dimensional chemical (including aerosol) concentrations and perform inverse modeling of input variables or model parameters (e.g., emissions). Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. They offer the possibility to assimilate both meteorological and chemical data; however, because CCMM are fairly recent, data assimilation in CCMM has been limited to date. We review here the current status of data assimilation in atmospheric chemistry models with a particular focus on future prospects for data assimilation in CCMM. We first review the methods available for data assimilation in atmospheric models, including variational methods, ensemble Kalman filters, and hybrid methods. Next, we review past applications that have included chemical data assimilation in chemical transport models (CTM) and in CCMM. Observational data sets available for chemical data assimilation are described, including surface data, surface-based remote sensing, airborne data, and satellite data. Several case studies of chemical data assimilation in CCMM are presented to highlight the benefits obtained by assimilating chemical data in CCMM. A case study of data assimilation to constrain emissions is also presented. There are few examples to date of joint meteorological and chemical data assimilation in CCMM and potential difficulties associated with data assimilation in CCMM are discussed. As the number of variables being assimilated increases, it is essential to characterize correctly the errors; in particular, the specification of error cross-correlations may be problematic. In some cases, offline diagnostics are necessary to ensure that data assimilation can truly improve model performance. However, the main challenge is likely to be the paucity of chemical data available for assimilation in CCMM