Star-shaped hexaaryltriindoles small molecules: Tuning molecular properties towards solution processed organic light emitting devices

We present a series of differently substituted star-shaped hexaaryltriindoles with tunable light-emitting properties. The deep blue emission is unchanged by donor peripheral substituents while an increasing acceptor character produces a reduction of the optical gap, an increased Stokes shift and eventually leads to the appearance of a new electronic level and to the simultaneous deep blue (413 nm) and green (552 nm) emission in solution. Quenching by concentration increases with the acceptor character but is lower as the tendency of these compounds to aggregate is stronger. Solution processed thin films present optical and morphological qualities adequate for device fabrication and similar electronic structure compared to solutions with an emission range from 423 nm up to 657 nm (red), demonstrating the possibility of tuning the energy levels by chemical functionalization. We have fabricated and characterized single-layer solution processed organic light emitting diodes (OLED) to investigate the influence on transport and emission properties of the substituting species. We analyzed the I–V response using a single-carrier numerical model that includes injection barriers and non-uniform electric-field across the layer. As a result, we obtained the electric field dependence of the mobility for each device. Best results are obtained on the most electron rich derivative functionalized with six donor methoxy groups. This material shows the highest emission efficiency in solid state, due to aggregation-induced enhancement, and better transport properties with the highest mobility and a very low turn-on voltage of 2.8 V. The solution processed OLED devices produce stable deep blue (CIE coordinates (0.16, 0.16)) to white (CIE coordinates (0.33, 0.3)) emission with similar luminous efficiencies.     

Transport and Mechanical Properties of High-ZT Mg2.08Si0.4−x Sn0.6Sb x Thermoelectric Materials

Mg₂(Si,Sn) compounds are promising candidate low-cost, lightweight, nontoxic thermoelectric materials made from abundant elements and are suited for power generation applications in the intermediate temperature range of 600 K to 800 K. Knowledge on the transport and mechanical properties of Mg₂(Si,Sn) compounds is essential to the design of Mg₂(Si,Sn)-based thermoelectric devices. In this work, such materials were synthesized using the molten-salt sealing method and were powder processed, followed by pulsed electric sintering densification. A set of Mg_2.08Si_0.4?x Sn_0.6Sb _x (0 ≤ x ≤ 0.072) compounds were investigated, and a peak ZT of 1.50 was obtained at 716 K in Mg_2.08Si_0.364Sn_0.6Sb_0.036. The high ZT is attributed to a high electrical conductivity in these samples, possibly caused by a magnesium deficiency in the final product. The mechanical response of the material to stresses is a function of the elastic moduli. The temperature-dependent Young’s modulus, shear modulus, bulk modulus, Poisson’s ratio, acoustic wave speeds, and acoustic Debye temperature of the undoped Mg₂(Si,Sn) compounds were measured using resonant ultrasound spectroscopy from 295 K to 603 K. In addition, the hardness and fracture toughness were measured at room temperature.     

STC power for 15 MW of PV comparing nameplate,initial power and power after 4 years

To date, the majority of quality controls performed at PV plants are based on the measurement of a small sample of individual modules. Consequently, there is very little representative data on the real Standard Test Conditions (STC) power output values for PV generators. This paper presents the power output values for more than 1300 PV generators having a total installed power capacity of almost 15.3 MW. The values were obtained by the INGEPER‐UPNA group, in collaboration with the IES‐UPM, through a study to monitor the power output of a number of PV plants from 2006 to 2009. This work has made it possible to determine, amongst other things, the power dispersion that can be expected amongst generators made by different manufacturers, amongst generators made by the same manufacturer but comprising modules of different nameplate ratings and also amongst generators formed by modules with the same characteristics. The work also analyses the STC power output evolution over time in the course of this 4‐year study. The values presented here could be considered to be representative of generators with fault‐free modules. Copyright © 2012 John Wiley & Sons, Ltd.     

Diagnosis of learner dropout based on learning styles for online distance learning

The amount of data generated by computer systems in Online Distance Learning (ODL) contains rich information. One example of this information we define as the Learner Learning Trail (LLT), which is the sequence of interactions between the students and the virtual environment. Another example is the Learner Learning Style (LLS), which is associated with the student behavior and choices during the learning process. This information can be used to identify learner behavior and learning style. We perceived, after the study of related literature, that the research field of learner diagnosis for ODL does not apply the conjoint use of LLT and LLS. In this article, we propose a model capable of integrating data generated from the behavior of students in ODL with cognitive aspects of them, such as their Learning Styles, by crossing LLT with LLS. We also propose the CPAD method (Collect, Preprocessing, Analysis, Diagnosis), which is implemented by collecting the raw data regarding learning activities, preprocessing the data into structured time sequences, analyzing the sequences regarding the learning styles and using this analysis to diagnose the learner behavior. We selected the dropout to investigate, once the dropout rate in ODL is a real problem in universities around the world. In addition, the dropout is a student decision which can be associated with previous students behaviors. We performed a study with 202 learners to evaluate if learning styles are capable of explaining aspects of the student behavior. The results suggest that Sequential/Global learning style dimension is more capable of explaining the dropout than the other dimensions. Also, we performed four classification experiments to verify how the dimensions of Felder-Silverman Learning Style Model influence the learner diagnosis. We perceived that the Sequential/Global dimension could provide a higher accuracy average with lower variation independently of the diagnosis technique.     

Tunable Nanoparticle and Cell Assembly Using Combined Self‐Powered Microfluidics and Microcontact Printing

The combination of cell microenvironment control and real‐time monitoring of cell signaling events can provide key biological information. Through precise multipatterning of gold nanoparticles (GNPs) around cells, sensing and actuating elements can be introduced in the cells' microenviroment, providing a powerful substrate for cell studies. In this work, a combination of techniques are implemented to engineer complex substrates for cell studies. Alternating GNPs and bioactive areas are created with micrometer separation by means of a combination of vacumm soft‐lithography of GNPs and protein microcontract printing. Instead of conventional microfluidics that need syringe pumps to flow liquid in the microchannels, degas driven flow is used to fill dead‐end channels with GNP solutions, rendering the fabrication process straightforward and accessible. This new combined technique is called Printing and Vacuum lithography (PnV lithography). By using different GNPs with various organic coating ligands, different macroscale patterns are obtained, such as wires, supercrystals, and uniformly spread nanoparticle layers that can find different applications depending on the need of the user. The application of the system is tested to pattern a range of mammalian cell lines and obtain readouts on cell viability, cell morphology, and the presence of cell adhesive proteins.     

Self-organized Ce(1-x)Gd(x)O(2-y) nanowire networks with very fast coarsening driven by attractive elastic interactions

Assembling arrays of ordered nanowires is a key objective for many of their potential applications. However, a lack of understanding and control of the nanowires' growth mechanisms limits their thorough development. In this work, an appealing new path towards self-organized epitaxial nanowire networks produced by high-throughput solution methods is reported. Two requisites are identified to generate the nanowires: a thermodynamic driving force for an unrestricted elongated equilibrium island shape, and a very fast effective coarsening rate. These requirements are met in anisotropically strained Ce(1-x)Gd(x)O(2-y) nanowires with the (011) orientation grown on the (001) surface of LaAlO(3) substrates. Nanowires with aspect ratios above ≈100 oriented along two mutually orthogonal axes are obtained leading to labyrinthine networks. A very fast effective nanowire growth rate (≈60 nm min(-1)) for ex-situ thermally annealed nanostructures derives from simultaneous kinetic processes occurring in a branched network. Ostwald ripening and anisotropic dynamic coalescence, both promoted by strain-driven attractive nanowire interaction, and rapid recrystallization, enabled by fast atomic diffusion associated with a high concentration of oxygen vacancies, contribute to such an effective growth rate. This bottom-up approach to self-organized nanowire growth has a wide potential for many materials and functionalities.     

Analytical study of a solution-processed diode based on ZnO nanoparticles using multi-walled carbon nanotubes as Schottky contact

Journal of Materials Science: Materials in Electronics - The search for good electrodes processed by solution has interested several niches to produce printed solar cells, lighting emitting diodes,...     

Reduction of Listeria monocytogenes on frankfurters treated with lactic acid solutions of various temperatures

United States regulations require ready-to-eat meat and poultry processors to control Listeria monocytogenes using interventions which may include antimicrobials that reduce post-processing contamination by at least 1 log-cycle; if the treatment achieves ≥2 log reductions, the plant is subject to less frequent microbial testing. Lactic acid (LA) may be useful as a post-lethality intervention and its antimicrobial properties may increase with temperature of application. The aim of this study was to evaluate the effect of LA solution concentration and temperature on L. monocytogenes counts of inoculated frankfurters and to identify parameters (concentration, temperature, and time) that achieve 1 and 2 log-unit immediate reductions. Frankfurters were surface-inoculated with a 10-strain mixture of L. monocytogenes (4.4 ± 0.1 log CFU/cm²) and then immersed in distilled water or LA solutions (0–3%) of 4, 25, 40, or 55 °C for 0–120 s. A regression equation for L. monocytogenes reduction included significant (P < 0.05) effects by the terms of concentration, time, temperature, and the interaction of concentration and temperature; other tested parameters (other interactions, quadratic and cubic terms), within the experimental range examined, did not affect (P ≥ 0.05) the extent of reduction. Results indicated that the effectiveness of LA against L. monocytogenes, in addition to concentration, increased with solution temperature (in the range of 0.6–2.8 log CFU/cm²). The developed equation may allow processors to vary conditions of treatment with LA to achieve a 1 or 2 log-unit reduction of the pathogen and comply with United States regulations.