Cost effective high efficiency solar cells

textTo make solar energy mainstream, lower-cost and more efficient power generation is key. A lot of effort in the silicon photovoltaic industry has gone into using fewer raw materials (i.e., silicon) and using more inexpensive processing techniques and materials to reduce cost. Utilizing thinner substrates not only reduces cost, but improves cell efficiency provided both front and back surfaces are well-passivated. In the current work, a kerf-less process is developed in which ultra-thin (~25 [mu]m), flexible mono-crystalline silicon substrates can be obtained through an exfoliation technique from a thicker parent wafer. These substrates, when exfoliated, have thick metal backing which provides mechanical support to the thin silicon and enables ease of processing of the substrates for device fabrication. Optical, electrical, and reliability characterization studies for completed cells show this technology’s compatibility with a heterojunction solar cell process flow. Building on the promising results achieved on exfoliated substrates, further optimization work was carried out. Namely, an improved cleaning process was developed to remove front surface contamination on textured surfaces of exfoliated, flexible mono-crystalline silicon. This process is very effective at cleaning metallic and organic residues, without introducing additional contamination or degrading the supporting back metal used for ultra-thin substrate handling. Spectroscopic studies were performed to qualitatively and quantitatively understand the efficacy of different cleaning procedures in order to develop the new cleaning process. Results of the spectroscopic studies were further supported by comparing the electrical performance of cells fabricated with different cleans. To replace silver as contact metal with a cheaper substitute like nickel or copper, patterning and etching processes are generally used. A low-cost alternative is proposed, where a reusable shadow mask with a metal grid pattern is kept in contact with the surface of the substrate in a plasma-enhanced chemical vapor deposition chamber during silicon nitride deposition. This leaves a patterned silicon surface for selective metal growth by direct electro-deposition. The viability of this process flow is demonstrated by fabricating diffused junction n[superscript+]pp[superscript+] monofacial and bifacial cells and electrically characterizing them. Investigation of the factors limiting the efficiency of the cells was carried out by lifetime measurement experiments.Electrical and Computer Engineerin

Comparative Studies on Decentralized Multiloop PID Controller Design Using Evolutionary Algorithms

Decentralized PID controllers have been designed in this paper for simultaneous tracking of individual process variables in multivariable systems under step reference input. The controller design framework takes into account the minimization of a weighted sum of Integral of Time multiplied Squared Error (ITSE) and Integral of Squared Controller Output (ISCO) so as to balance the overall tracking errors for the process variables and required variation in the corresponding manipulated variables. Decentralized PID gains are tuned using three popular Evolutionary Algorithms (EAs) viz. Genetic Algorithm (GA), Evolutionary Strategy (ES) and Cultural Algorithm (CA). Credible simulation comparisons have been reported for four benchmark 2x2 multivariable processes.Comment: 6 pages, 9 figure

Estimation, Analysis and Smoothing of Self-Similar Network Induced Delays in Feedback Control of Nuclear Reactors

This paper analyzes a nuclear reactor power signal that suffers from network induced random delays in the shared data network while being fed-back to the Reactor Regulating System (RRS). A detailed study is carried out to investigate the self similarity of random delay dynamics due to the network traffic in shared medium. The fractionality or selfsimilarity in the network induced delay that corrupts the measured power signal coming from Self Powered Neutron Detectors (SPND) is estimated and analyzed. As any fractional order randomness is intrinsically different from conventional Gaussian kind of randomness, these delay dynamics need to be handled efficiently, before reaching the controller within the RRS. An attempt has been made to minimize the effect of the randomness in the reactor power transient data with few classes of smoothing filters. The performance measure of the smoothers with fractional order noise consideration is also investigated into.Comment: 6 pages, 6 figure

Exploring noise-induced chaos and complexity in a red blood cell system

We investigate dynamical changes and its corresponding phase space complexity in a stochastic red blood cell system. The system is obtained by incorporating power noise with the associated sinusoidal flow. Both chaotic and non-chaotic dynamics of sinusoidal flow in red blood cell are identified by 0-1 test. Furthermore, dynamical complexity of the sinusoidal flow in the system is investigated by heterogeneous recurrence based entropy. The numerical simulation is performed to quantify the existence of chaotic dynamics and complexity for the sinusoidal blood flow.Comment: 10 page

Cluster profiles from beyond-the-QE CMB lensing mass maps

Clusters of galaxies, being the largest collapsed structures in the universe, offer valuable insights into the nature of cosmic evolution. Precise calibration of the mass of clusters can be obtained by extracting their gravitational lensing signal on the Cosmic Microwave Background (CMB) fluctuations. We extend and test here the performance achieved on cluster scales by the parameter-free, maximum a posteriori (MAP) CMB lensing reconstruction method, which has been shown to be optimal in the broader context of CMB lensing mass map and power spectrum estimation. In the context of cluster lensing, the lensing signal of other large-scale structures acts as an additional source of noise. We show here that by delensing the CMB fluctuations around each and every cluster, this noise variance is reduced according to expectations. We also demonstrate that the well-known bias in the temperature quadratic estimator in this regime, sourced by the strong non-Gaussianity of the signal, is almost entirely mitigated without any scale cuts. Being statistically speaking an optimal and blind lensing mass map reconstruction, the MAP estimator is a promising tool for the calibration of the masses of clusters.Comment: 11 pages, 4 figures, prepared for PRD submissio