A new set of relativistic screening constants for the screened hydrogenic model

AnewRelativisticScreenedHydrogenicModel has been developed to calculate atomic data needed to compute the optical and thermodynamic properties of high energy density plasmas. The model is based on anewset of universal screeningconstants, including nlj-splitting that has been obtained by fitting to a large database of ionization potentials and excitation energies. This database was built with energies compiled from the National Institute of Standards and Technology (NIST) database of experimental atomic energy levels, and energies calculated with the Flexible Atomic Code (FAC). The screeningconstants have been computed up to the 5p3/2 subshell using a Genetic Algorithm technique with an objective function designed to minimize both the relative error and the maximum error. To select the best set of screeningconstants some additional physical criteria has been applied, which are based on the reproduction of the filling order of the shells and on obtaining the best ground state configuration. A statistical error analysis has been performed to test the model, which indicated that approximately 88% of the data lie within a ±10% error interval. We validate the model by comparing the results with ionization energies, transition energies, and wave functions computed using sophisticated self-consistent codes and experimental data.

Equation of state for hot dense matter using a relativistic screened hydrogenic model

The study of matter under conditions of high density, pressure, and temperature is a valuable subject for inertial confinement fusion (ICF), astrophysical phenomena, high-power laser interaction with matter, etc. In all these cases, matter is heated and compressed by strong shocks to high pressures and temperatures, becomes partially or completely ionized via thermal or pressure ionization, and is in the form of dense plasma. The thermodynamics and the hydrodynamics of hot dense plasmas cannot be predicted without the knowledge of the equation of state (EOS) that describes how a material reacts to pressure and how much energy is involved. Therefore, the equation of state often takes the form of pressure and energy as functions of density and temperature. Furthermore, EOS data must be obtained in a timely manner in order to be useful as input in hydrodynamic codes. By this reason, the use of fast, robust and reasonably accurate atomic models, is necessary for computing the EOS of a material.

Progress on optimization of the solar cell fabrication process by impurity-to-efficiency predictive simulator

To optimize the last high temperature step of a standard solar cell fabrication process (the contact cofiring step), the aluminium gettering is incorporated in the Impurity-to-Efficiency simulation tool, so that it models the phosphorus and aluminium co-gettering effect on iron impurities. The impact of iron on the cell efficiency will depend on the balance between precipitate dissolution and gettering. Gettering efficiency is similar in a wide range of peak temperatures (600-850 ºC), so that this peak temperature can be optimized favoring other parameters (e.g. ohmic contact). An industrial co-firing step can enhance the co-gettering effect by adding a temperature plateau after the peak of temperature. For highly contaminated materials, a short plateau (menor que 2 min) at low temperature (600 ºC) is shown to reduce the dissolved iron.

TCAD for PV: a fast method for accurately modelling metal impurity evolution during solar cell processing

Coupled device and process silumation tools, collectively known as technology computer-aided design (TCAD), have been used in the integrated circuit industry for over 30 years. These tools allow researchers to quickly converge on optimized devide designs and manufacturing processes with minimal experimental expenditures. The PV industry has been slower to adopt these tools, but is quickly developing competency in using them. This paper introduces a predictive defect engineering paradigm and simulation tool, while demonstrating its effectiveness at increasing the performance and throughput of current industrial processes. the impurity-to-efficiency (I2E) simulator is a coupled process and device simulation tool that links wafer material purity, processing parameters and cell desigh to device performance. The tool has been validated with experimental data and used successfully with partners in industry. The simulator has also been deployed in a free web-accessible applet, which is available for use by the industrial and academic communities.

Relativistic screened hydrogenic radial integrals

The computation of dipole matrix elements plays an important role in the study of absorption or emission of radiation by atoms in several fields such as astrophysics or inertial confinement fusion. In this work we obtain closed formulas for the dipole matrix elements of multielectron ions suitable for using in the framework of a Relativistic Screened Hydrogenic Model.

Ionization energies of amphoteric-doped Cu2ZnSnS4: Photovoltaic application

The substitution of Cu, Sn or Zn in the quaternary Cu2ZnSnS4 semiconductor by impurities that introduce intermediate states in the energy bandgap could have important implications either for photovoltaic or spintronic applications. This allows more generation–recombination channels than for the host semiconductor. We explore and discuss this possibility by obtaining the ionization energies from total energy first-principles calculations. The three substitutions of Cu, Sn and Zn by impurities are analyzed. From these results we have found that several impurities have an amphoteric behavior with the donor and acceptor energies in the energy bandgap. In order to analyze the role of the ionization energies in both the radiative and non-radiative processes, the host energy bandgap and the acceptor and the donor energies have been obtained as a function of the inward and outward impurity-S displacements. We carried out the analysis for both the natural and synthetic CZTS. The results show that the ionization energies are similar, whereas the energy band gaps are different.

How do Impurity Inclusions Influence the Mechanical Properties of Multicrystalline Silicon?

The purpose of this research is to characterise the mechanical properties of multicrystalline silicon for photovoltaic applications that was crystallised from silicon feedstock with a high content of several types of impurities. The mechanical strength, fracture toughness and elastic modulus were measured at different positions within a multicrystalline silicon block to quantify the effect of impurity segregation on these mechanical properties. The microstructure and fracture surfaces of the samples was exhaustively analysed with a scanning electron microscope in order to correlate the values of mechanical properties with material microstructure. Fracture stresses values were treated statistically via the Weibull statistics. The results of this research show that metals segregate to the top of the block, produce moderate microcracking and introduce high thermal stresses. Silicon oxide is produced at the bottom part of the silicon block, and its presence significantly reduces the mechanical strength and fracture toughness of multicrystalline silicon due to both thermal and elastic mismatch between silicon and the silicon oxide inclusions. Silicon carbide inclusions from the upper parts of the block increase the fracture toughness and elastic modulus of multicrystalline silicon. Additionally, the mechanical strength of multicrystalline silicon can increase when the radius of the silicon carbide inclusions is smaller than ~10 µm. The most damaging type of impurity inclusion for the multicrystalline silicon block studied in this work was amorphous silicon oxide. The oriented precipitation of silicon oxide at grain and twin boundaries eases the formation of radial cracks between inclusions and decreases significatively the mechanical strength of multicrystalline silicon. The second most influencing type of impurity inclusions were metals like aluminium and copper, that cause spontaneous microcracking in their surroundings after the crystallisation process, therefore reducing the mechanical response of multicrystalline silicon. Therefore, solar cell producers should pay attention to the content of metals and oxygen within the silicon feedstock in order to produce solar cells with reliable mechanical properties.