A random scattering approach to enhance light extraction in white top-emitting organic light-emitting diodes (OLEDs) is reported. Through solution processing from fluorinated solvents, a nano-particle scattering layer (NPSL) can be deposited directly on top of small molecule OLEDs without affecting their electrical performance. The scattering length for light inside the NPSL is determined from transmission measurements and found to be in agreement with Mie scattering theory. Furthermore, the dependence of the light outcoupling enhancement on electron transport layer thickness is studied. Depending on the electron transport layer thickness, the NPSL enhances the external quantum efficiency of the investigated white OLEDs by between 1.5 and 2.3-fold. For a device structure that has been optimized prior to application of the NPSL, the maximum external quantum efficiency is improved from 4.7% to 7.4% (1.6-fold improvement). In addition, the scattering layer strongly reduces the undesired shift in emission color with viewing angle.
Can we really “read the mind in the eyes”? Moreover, can AI assist us in this task? This paper answers these two questions by introducing a machine learning system that predicts personality characteristics of individuals on the basis of their face. It does so by tracking the emotional response of the individual’s face through facial emotion recognition (FER) while watching a series of 15 short videos of different genres. To calibrate the system, we invited 85 people to watch the videos, while their emotional responses were analyzed through their facial expression. At the same time, these individuals also took four well-validated surveys of personality characteristics and moral values: the revised NEO FFI personality inventory, the Haidt moral foundations test, the Schwartz personal value system, and the domain-specific risk-taking scale (DOSPERT). We found that personality characteristics and moral values of an individual can be predicted through their emotional response to the videos as shown in their face, with an accuracy of up to 86% using gradient-boosted trees. We also found that different personality characteristics are better predicted by different videos, in other words, there is no single video that will provide accurate predictions for all personality characteristics, but it is the response to the mix of different videos that allows for accurate prediction.
Electronic charge-coupled device (CCD) cameras equipped with image intensifiers are increasingly being used for radiographic applications. These systems may be used to replace film recording for static imaging, or at other times CCDs coupled with electro-optical shutters may be used for static or dynamic (explosive) radiography. Image intensifiers provide precise shuttering and signal gain. We have developed a set of performance measures to calibrate systems, compare one system to another, and to predict experimental performance. The performance measures discussed in this paper are concerned with image quality parameters that relate to resolution and signal-to-noise ratio.
Quantum state resolved molecular beam scattering studies of small polyatomic molecules from metal surfaces present new challenges for experimentalists, but provide unprecedented new opportunities for detailed study of polyatomic molecular dynamics at surfaces. In the current work, we report preliminary characterization of the scattering of formaldehyde from the Au(111) surface. We report the measured desorption energy (0.31 eV), and characterize the distinct trapping-desorption and direct scattering channels, via the dependence of the scattered velocity and rotational distributions on surface temperature and incident molecular beam energy. Finally, we estimate the trapping probability as a function of incidence energy, which indicates the importance of molecular degrees of freedom in the mechanism for trapping.
Formaldehyde is the smallest stable organic molecule containing the carbonyl functional group, and is commonly considered to be a prototype for the study of high-resolution spectroscopy of polyatomic molecules. The a-axis Coriolis interaction between the near-degenerate ν 4 and ν 6 (out-of-plane and in-plane wagging modes, respectively) of the ground electronic state has received extensive attention and is thoroughly understood. In the first excited singletà 1 A 2 electronic state, the analogous Coriolis interaction does not occur, because theà state suffers from a pseudo Jahn-Teller distortion, which causes a double-well potential energy structure in the q 4 out-of-plane coordinate, and which dramatically reduces the effective ν 4 frequency. The ν 4 frequency is reduced by so great an extent in theà state that it is the 3ν 4 overtone which is near degenerate with ν 6. In the current work, we report the precise ν 6 fundamental frequency in theà state, and we determine the strength of the a-axis Coriolis interaction between 3ν 4 and ν 6. We also provide a rotational analysis of the ν 4 + ν 6 combination band, which interacts with 3ν 4 via an additional c-axis Coriolis perturbation, and which allows us to provide a complete deperturbed fit to the 3ν 4 rotational structure. Knowledge of the Coriolis interaction strengths among the lowest-lying levels in theà state will aid the interpretation of the spectroscopy and dynamics of many higher-lying band structures, which are perturbed by analogous interactions.
Experiments have been conducted in Sarov, Russia, with a dynamic radiographic system designed to establish the volume of an imploding 14-mm-diameter tungsten cylinder. Images were formed using a 65-MeV gamma source, lutetium oxyorthosilicate doped with cerium (LSO:Ce) radiation-to-light converter, and a fiber optic imaging bundle. Three radiographs were recorded in the course of approximately 2 microseconds using an electronic streak camera with intensified charge-coupled device (CCD) readout. Significant improvements in system performance were achieved over lens coupling of components by the introduction of coherent fiber optics.
By following explicit instructions humans can instantaneously get the hang of tasks they have never performed before. Here, we used a specially calibrated multivariate analysis technique to uncover the elusive representational states following newly instructed arbitrary behavioural rules such as 'for coffee, press red button', while transitioning from 'knowing what to do' to 'actually doing it'. Subtle variation in distributed neural activity patterns reflected rule-specific representations within the ventrolateral prefrontal cortex (VLPFC), confined to instructed stimulus-response learning in contrast to incidental learning involving the same stimuli and responses. VLPFC representations were established right after first-time instruction and remained stable across early implementation trials. More and more fluent application of novel rule representations was channelled through increasing cooperation between VLPFC and anterior striatum. These findings inform representational theories on how the prefrontal cortex supports behavioural flexibility by enabling ad-hoc coding of novel task rules without recourse to familiar sub-routines
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