Density of bulk trap states in organic semiconductor crystals: discrete levels induced by oxygen in rubrene

The density of trap states in the bandgap of semiconducting organic single crystals has been measured quantitatively and with high energy resolution by means of the experimental method of temperature-dependent space-charge-limited-current spectroscopy (TD-SCLC). This spectroscopy has been applied to study bulk rubrene single crystals, which are shown by this technique to be of high chemical and structural quality. A density of deep trap states as low as ~ 10^{15} cm^{-3} is measured in the purest crystals, and the exponentially varying shallow trap density near the band edge could be identified (1 decade in the density of states per ~25 meV). Furthermore, we have induced and spectroscopically identified an oxygen related sharp hole bulk trap state at 0.27 eV above the valence band.Comment: published in Phys. Rev. B, high quality figures: http://www.cpfs.mpg.de/~krellner

Field-induced charge transport at the surface of pentacene single crystals: a method to study charge dynamics of 2D electron systems in organic crystals

A method has been developed to inject mobile charges at the surface of organic molecular crystals, and the DC transport of field-induced holes has been measured at the surface of pentacene single crystals. To minimize damage to the soft and fragile surface, the crystals are attached to a pre-fabricated substrate which incorporates a gate dielectric (SiO_2) and four probe pads. The surface mobility of the pentacene crystals ranges from 0.1 to 0.5 cm^2/Vs and is nearly temperature-independent above ~150 K, while it becomes thermally activated at lower temperatures when the induced charges become localized. Ruling out the influence of electric contacts and crystal grain boundaries, the results contribute to the microscopic understanding of trapping and detrapping mechanisms in organic molecular crystals.Comment: 14 pages, 4 figures. Submitted to J. Appl. Phy

Hole mobility in organic single crystals measured by a "flip-crystal" field-effect technique

We report on single crystal high mobility organic field-effect transistors (OFETs) prepared on prefabricated substrates using a "flip-crystal" approach. This method minimizes crystal handling and avoids direct processing of the crystal that may degrade the FET electrical characteristics. A chemical treatment process for the substrate ensures a reproducible device quality. With limited purification of the starting materials, hole mobilities of 10.7, 1.3, and 1.4 cm^2/Vs have been measured on rubrene, tetracene, and pentacene single crystals, respectively. Four-terminal measurements allow for the extraction of the "intrinsic" transistor channel resistance and the parasitic series contact resistances. The technique employed in this study shows potential as a general method for studying charge transport in field-accumulated carrier channels near the surface of organic single crystals.Comment: 26 pages, 7 figure

Coarsening in surface growth models without slope selection

We study conserved models of crystal growth in one dimension [$\partial_t z(x,t) =-\partial_x j(x,t)$] which are linearly unstable and develop a mound structure whose typical size L increases in time ($L = t^n$). If the local slope ($m =\partial_x z$) increases indefinitely, $n$ depends on the exponent $\gamma$ characterizing the large $m$ behaviour of the surface current $j$ ($j = 1/|m|^\gamma$): $n=1/4$ for $1< \gamma <3$ and $n=(1+\gamma)/(1+5\gamma)$ for $\gamma>3$.Comment: 7 pages, 2 EPS figures. To be published in J. Phys. A (Letter to the Editor

THE EFFECT OF DIFFERENT FOOTWEAR ON THE MYOELECTRIC ACTIVITY OF M. TIBIALIS POSTERIOR DURING TREADMILL RUNNING

Overload running injuries of the lower extremity, particularly the knee, are associated with excessive pronation of the foot resulting in tibial rotation (Nigg et al., 1995). M. tibialis posterior (TP) is shown to have an active influence on pronation and the medial longitudinal arch (Kaye & Jahss, 1991). Its functional role during running and interaction with footwear is still not clearly understood (Reber et al., 1993; O’Connor & Hamill, 2004). Therefore the purpose of this study is to investigate the influence of different footwear on the muscle’s EMG pattern

WIRE EMG OF FLEXOR HALLUCIS LONGUS DURING BAREFOOT AND SHOD RUNNING ON A TREADMILL: A PILOT STUDY

Excessive pronation is associated with overload injuries of the lower extremity (Nigg, 1995). The flexor hallucis longus (FHL) acts against the pronation of the calcaneus (Klein, 1996). The influence of different footwear on the activity of the FHL was neither measured in walking nor running. The purpose of this study was to investigate the activity of the FHL during different phases in stance of walking and running in different footwear conditions

Influence of Hydrodynamic Interactions on the Adsorption Process of Large Particles

We have studied the adsorption process of non-Brownian particles on a line incorporating hydrodynamic interactionsa and we have numerically analyzed their effect on typical relevant quantities. We compare our model to the ballistic deposition model (BM) and address the limitations of BM in experimental situations. The results obtained can explain some differences observed between recent experiments and BM predictions.Comment: 10 pages, LaTeX. 4 Figures upon reques

Table Detection in Invoice Documents by Graph Neural Networks

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.Tabular structures in documents offer a complementary dimension to the raw textual data, representing logical or quantitative relationships among pieces of information. In digital mail room applications, where a large amount of administrative documents must be processed with reasonable accuracy, the detection and interpretation of tables is crucial. Table recognition has gained interest in document image analysis, in particular in unconstrained formats (absence of rule lines, unknown information of rows and columns). In this work, we propose a graph-based approach for detecting tables in document images. Instead of using the raw content (recognized text), we make use of the location, context and content type, thus it is purely a structure perception approach, not dependent on the language and the quality of the text reading. Our framework makes use of Graph Neural Networks (GNNs) in order to describe the local repetitive structural information of tables in invoice documents. Our proposed model has been experimentally validated in two invoice datasets and achieved encouraging results. Additionally, due to the scarcity of benchmark datasets for this task, we have contributed to the community a novel dataset derived from the RVL-CDIP invoice data. It will be publicly released to facilitate future research.European Unio