Advances in a-Si:H/c-Si heterojunction solar cell fabrication and characterization

Our progress in amorphous/crystalline silicon (a-Si:H/c-Si) heterojunction solar cell technology and current understanding of fundamental device physics are presented. In a-Si:H/c-Si cells, device performance is strongly dependent on the quality of the a-Si:H/c-Si heterojunction. Four topics are crucial to minimize recombination at the junction and thereby maximize cell efficiency: wet-chemical pre-treatment of the c-Si surface prior to a-Si:H deposition; optimum a-Si:H doping; thermal and plasma post-treatments of the a-Si:H/c-Si structure. By optimizing these aspects using specifically developed characterization methods, we were able to realize (n)a-Si:H/(p)c-Si and (p)a-Si:H/(n)c-Si cells with up to 18.5% and 19.8% efficiency, respectively.     

Electrical and photoelectrical properties of P3HT/n-Si hybrid organic–inorganic heterojunction solar cells

A detail analysis of electrical and photoelectrical properties of hybrid organic–inorganic heterojunction solar cells poly(3-hexylthiophene) (P3HT)/n-Si, fabricated by spin-coating of the polymeric thin film onto oxide passivated Si(1 0 0) surface, was carried out within the temperature ranging from 283 to 333 K. The dominating current transport mechanisms were established to be the multistep tunnel-recombination and space charge limited current at forward bias and leakage current through the shunt resistance at reverse bias. A simple approach was developed and successfully applied for the correct analysis of the high frequency C–V characteristics of hybrid heterojunction solar cells. The P3HT/n-Si solar cell under investigation possessed the following photoelectric parameters: J_sc = 16.25 mA/cm², V_oc = 0.456 V, FF = 0.45, η = 3.32% at 100 mW/cm² AM 1.5 illumination. The light dependence of the current transport mechanisms through the P3HT/n-Si hybrid solar cells is presented quantitatively and discussed in detail.     

Grain growth of silicon

In this paper we report on 2-D phase-field simulations in order to study the influence of the growth kinetics and the surface energy on the growth behaviour of grains during solidification of silicon. We investigated in detail the growth of two grains.     

Residential location choice of knowledge-workers: The role of amenities,workplace and lifestyle

This study investigates the residential location choice of knowledge-workers at the intra-metropolitan level by applying discrete choice models. The models represent housing choices of 833 knowledge-workers in high-technology and financial services and analyze the relative importance of lifestyle and cultural amenities in addition to classic location factors. Hence, the model bridges the gap between the recent lifestyle-oriented and the classical utility-oriented conceptualizations of the residential choice of knowledge-workers. The most important factors are municipal socioeconomic level, housing affordability and commuting time, while substantial secondary factors are cultural and educational land-use and culture-oriented lifestyle.     

Holonic multilevel simulation of complex systems: Application to real-time pedestrians simulation in virtual urban environment

Simulation, which creates abstractions of the system is an appropriate approach for studying complex systems that are inaccessible through direct observation and measurement. The problem with simulation of great numbers of interacting entities is that it is difficult to create a reliable and tractable abstraction of the real system. Indeed, simulating large numbers of entities requires great computing resources. A solution to avoid this problem is to use macroscopic models. However, this type of model may be unavailable or not reliable for the problem at hand and it does not allow the observation of individual behaviours. In this paper, a multilevel simulation model is proposed to allow the use of both microscopic and macroscopic techniques. This model is based upon Holonic Multi-Agent Systems which offer a promising approach for developing applications in complex domains characterised by a hierarchical structure. The proposed approach provides a generic scheduling model for multilevel simulations: dynamically adapting the level of simulated behaviours while being as faithful as possible to the simulated model. It does not only manage the level of entities’ behaviour but also of behaviours classically assigned to the environmental part of a simulation. A set of physics-based indicators is also introduced to dynamically determine the most suitable level for each entity and to maintain the best trade-off between simulation accuracy and constraints (dependent on the model or the experimental context).     

Diverse food-based applications of nuclear magnetic resonance (NMR) technology

Nuclear magnetic resonance (NMR) spectroscopy is one of the most common investigative techniques used by both chemists and biochemists to identify molecular structures as well as to study the progress of chemical reactions. Magnetic resonance imaging (MRI), another type of NMR technology, has extensively been used in medical radiology to obtain soft tissue images for diagnostic purposes in medicine. Food scientists have also explored the use of both NMR and MRI and continue to develop a wide range of applications for food analysis and food processing. This review begins with a brief introduction to NMR and then focuses on current diverse NMR applications in food research and manufacturing. Topics covered include chemical compositional analysis and structural identification of functional components in foods, determination of composition and formulation of packaging materials, detection of food authentication, optimization of food processing parameters, and inspection of microbiological, physical and chemical quality of foods. This review also emphasizes the pros and cons of specific NMR applications in the analysis of representative foods such as wine, cheese, fruits, vegetables, meat, fish, beverages (i.e. tomato juice and pulp, green tea, coffee) and edible oils, as well as discussing both the challenges and future opportunities in NMR applications in food science.     

New catalytic materials for the high-temperature synthesis of hydrocyanic acid from methane and ammonia by high-throughput approach

For converting methane and ammonia to hydrocyanic acid, catalysts were prepared and tested in a 48-parallel channel fixed-bed reactor unit operating at temperatures up to 1373 K. The catalysts were synthesized with a robot applying a genetic algorithm as the design tool. New and improved catalyst compositions were discovered by using a total of seven generations each consisting of 92 potential catalysts. Thereby, the catalyst support turned out as an important input variable. Furthermore, platinum, which is well known as a catalytic material was confirmed. Moreover, improvements in HCN yield were achieved by addition of promoters like Ir, Au, Ni, Mo, Zn and Re. Multi-way analysis of variance and regression trees were applied to establish correlations between HCN yield and catalyst composition (support and metal additives). The obtained results are considered as the base for future even more efficient screening experiments.     

Infrared characterization of the surface intermediates in the oxidation of toluene on vanadyl pyrophosphate catalysts

The adsorption and reaction of toluene on vanadyl pyrophosphate catalysts was studied by in situ infrared spectroscopy. Strongly adsorbed benzaldehyde and physically adsorbed cyclic anhydride species were observed at temperatures above 523 K. Water formed during reaction generates acid hydroxyl groups which cause a stronger adsorption of benzaldehyde and consecutive oxidation reactions. By co-adsorption of pyridine the acid sites are blocked and the deeper oxidation is suppressed. This revised version was published online in August 2006 with corrections to the Cover Date.     

Effect of the dielectric transition on laser-induced phase explosion in metals

Phase explosion is an explosive liquid to vapor phase change that occurs during laser ablation as the surface approaches 90% of the thermodynamic critical temperature (0.9T_c), which is the upper limit of superheating. Large variations in properties are expected to occur near 0.8T_c, transforming the electrically conductive metal into a nearly transparent dielectric, an effect that has been neglected in previous models of laser ablation. The work presented in this paper numerically investigates the possible effect of the dielectric transition using a one dimensional heat transfer model. The results show that accurate knowledge of the absorption coefficient above 0.8T_c is critical for predicting the laser fluence at which phase explosion occurs.