Theoretical Limits of Photovoltaics Efficiency and Possible Improvements by Intuitive Approaches Learned from Photosynthesis and Quantum Coherence

In this review, we present and discussed the main trends in photovoltaics with emphasize on the conversion efficiency limits. The theoretical limits of various photovoltaics device concepts are presented and analyzed using a flexible detailed balance model where more discussion emphasize is toward the losses. Also, few lessons from nature and other fields to improve the conversion efficiency in photovoltaics are presented and discussed as well. From photosynthesis, the perfect exciton transport in photosynthetic complexes can be utilized for PVs. Also, we present some lessons learned from other fields like recombination suppression by quantum coherence. For example, the coupling in photosynthetic reaction centers is used to suppress recombination in photocells.Comment: 47 pages, 22 figures. arXiv admin note: text overlap with arXiv:1307.5093, arXiv:1105.4189 by other author

Cuckoo Search Inspired Hybridization of the Nelder-Mead Simplex Algorithm Applied to Optimization of Photovoltaic Cells

A new hybridization of the Cuckoo Search (CS) is developed and applied to optimize multi-cell solar systems; namely multi-junction and split spectrum cells. The new approach consists of combining the CS with the Nelder-Mead method. More precisely, instead of using single solutions as nests for the CS, we use the concept of a simplex which is used in the Nelder-Mead algorithm. This makes it possible to use the flip operation introduces in the Nelder-Mead algorithm instead of the Levy flight which is a standard part of the CS. In this way, the hybridized algorithm becomes more robust and less sensitive to parameter tuning which exists in CS. The goal of our work was to optimize the performance of multi-cell solar systems. Although the underlying problem consists of the minimization of a function of a relatively small number of parameters, the difficulty comes from the fact that the evaluation of the function is complex and only a small number of evaluations is possible. In our test, we show that the new method has a better performance when compared to similar but more compex hybridizations of Nelder-Mead algorithm using genetic algorithms or particle swarm optimization on standard benchmark functions. Finally, we show that the new method outperforms some standard meta-heuristics for the problem of interest

On the Kinetic Energy Density Functional: The Limit of the Density Derivative Order

Within ``orbital-free'' density functional theory, it is essential to develop general kinetic energy density (KED), denoted as $t(\mathbf{r})$. This is usually done by empirical corrections and enhancements, gradient expansions, machine learning, or axiomatic approaches to find forms that satisfy physical necessities. In all cases, it is crucial to determine the largest spatial density derivative order, $m$ in, $t(\mathbf{r})$. There have been many efforts to do so, but none have proven general or conclusive and there is no clear guide on how to set $m$. In this work, we found that, by imposing KED finitude, $m=D+1$ for systems of dimension $D$. This is consistent with observations and provides a needed guide for systematically developing more accurate KEDs

Spectral Method for Solving the Nonlinear Thomas-Fermi Equation Based on Exponential Functions

We present an efficient spectral methods solver for the Thomas-Fermi equation for neutral atoms in a semi-infinite domain. The ordinary differential equation has been solved by applying a spectral method using an exponential basis set. One of the main advantages of this approach, when compared to other relevant applications of spectral methods, is that the underlying integrals can be solved analytically and numerical integration can be avoided. The nonlinear algebraic system of equations that is derived using this method is solved using a minimization approach. The presented method has shown robustness in the sense that it can find high precision solution for a wide range of parameters that define the basis set. In our test, we show that the new approach can achieve a very high rate of convergence using a small number of bases elements. We also present a comparison of recently published results for this problem using spectral methods based on several different basis sets. The comparison shows that our method is highly competitive and in many aspects outperforms the previous work