Advances in the Surface Passivation of Silicon Solar Cells

AbstractThe surface passivation properties of aluminium oxide (Al2O3) on crystalline Si are compared with the traditional passivation system of silicon nitride (SiNx). It is shown that Al2O3 has fundamental advantages over SiNx when applied to the rear of p-type silicon solar cells as well as to the p+ emitter of n-type silicon solar cells. Special emphasis is paid to the transfer of Al2O3 into industrial solar cell production. We compare different Al2O3 deposition techniques suitable for mass production such as ultrafast spatial atomic layer deposition, inline plasma-enhanced chemical vapour deposition and reactive sputtering. Finally, we review the most recent cell results with Al2O3 passivation and give a brief outlook on the future prospects of Al2O3 in silicon solar cell production

On the construction of high-order force gradient algorithms for integration of motion in classical and quantum systems

A consequent approach is proposed to construct symplectic force-gradient algorithms of arbitrarily high orders in the time step for precise integration of motion in classical and quantum mechanics simulations. Within this approach the basic algorithms are first derived up to the eighth order by direct decompositions of exponential propagators and further collected using an advanced composition scheme to obtain the algorithms of higher orders. Contrary to the scheme by Chin and Kidwell [Phys. Rev. E 62, 8746 (2000)], where high-order algorithms are introduced by standard iterations of a force-gradient integrator of order four, the present method allows to reduce the total number of expensive force and its gradient evaluations to a minimum. At the same time, the precision of the integration increases significantly, especially with increasing the order of the generated schemes. The algorithms are tested in molecular dynamics and celestial mechanics simulations. It is shown, in particular, that the efficiency of the new fourth-order-based algorithms is better approximately in factors 5 to 1000 for orders 4 to 12, respectively. The results corresponding to sixth- and eighth-order-based composition schemes are also presented up to the sixteenth order. For orders 14 and 16, such highly precise schemes, at considerably smaller computational costs, allow to reduce unphysical deviations in the total energy up in 100 000 times with respect to those of the standard fourth-order-based iteration approach.Comment: 23 pages, 2 figures; submitted to Phys. Rev.

A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

BACKGROUND: Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. METHODOLOGY: We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. CONCLUSIONS: This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking

The ELBA Force Field for Coarse-Grain Modeling of Lipid Membranes

A new coarse-grain model for molecular dynamics simulation of lipid membranes is presented. Following a simple and conventional approach, lipid molecules are modeled by spherical sites, each representing a group of several atoms. In contrast to common coarse-grain methods, two original (interdependent) features are here adopted. First, the main electrostatics are modeled explicitly by charges and dipoles, which interact realistically through a relative dielectric constant of unity (). Second, water molecules are represented individually through a new parametrization of the simple Stockmayer potential for polar fluids; each water molecule is therefore described by a single spherical site embedded with a point dipole. The force field is shown to accurately reproduce the main physical properties of single-species phospholipid bilayers comprising dioleoylphosphatidylcholine (DOPC) and dioleoylphosphatidylethanolamine (DOPE) in the liquid crystal phase, as well as distearoylphosphatidylcholine (DSPC) in the liquid crystal and gel phases. Insights are presented into fundamental properties and phenomena that can be difficult or impossible to study with alternative computational or experimental methods. For example, we investigate the internal pressure distribution, dipole potential, lipid diffusion, and spontaneous self-assembly. Simulations lasting up to 1.5 microseconds were conducted for systems of different sizes (128, 512 and 1058 lipids); this also allowed us to identify size-dependent artifacts that are expected to affect membrane simulations in general. Future extensions and applications are discussed, particularly in relation to the methodology's inherent multiscale capabilities

Firing stability of SiN(y)/SiN(x) stacks for the surface passivation of crystalline silicon solar cells

In the photovoltaic industry contacts to crystalline silicon are typically formed by firing of screen-printed metallization pastes. However, the stability of surface passivation layers during high temperature contact formation is a major challenge. Here, we investigate the thermal stability of the surface passivation by amorphous silicon nitride double layers (SiNy/SiNx). The SiNy passivation layer is silicon rich with refractive index larger than 3. Whereas the SiNx capping layer has a refractive index of 2.05. Compared to pure hydrogenated amorphous silicon, the nitrogen in the SiNy passivation layer improves the firing stability. We achieve an effective surface recombination velocity after a conventional co-firing process of (5.2 +/- 2) cm/s on p-type (1.5 Omega cm) FZ-silicon wafers at an injection density of 10(15) cm(-3). An analysis of the improved firing stability is presented based on FTIR and hydrogen effusion measurements. The incorporation of an SiNy/SiNx stack into the passivated rear of Cz silicon screen-printed solar cells results in an energy conversion efficiency of 18.3% compared to reference solar cells with conventional aluminum back surface field showing 17.9% efficiency. The short circuit current density increases by up to 0.8 mA/cm(2) compared to conventional solar cells due to the improved optical reflectance and rear side surface passivation. (C) 2011 Elsevier By. All rights reserved