Radiation Damage in XFEL: Case study from the oxygen-evolving complex of Photosystem II

Structural changes induced by radiation damage in X-ray crystallography hinder the ability to understand the structure/function relationship in chemical reactions. Serial femtosecond crystallography overcomes this problem by exposing the sample to very short and intense laser pulse leading to measurement before destruction. Here we use molecular modeling to map the radiation damage during the 10–50 fs to the intensity, the energy and the time duration of the laser pulse on the oxygen-evolving complex (OEC) of photosystem II. In the model, the nuclei move classically in a fully quantum potential created by electron density under the effect of strong laser pulse in the Ehrenfest dynamics regime. The results show that the Mn-Mn and Mn-Ca distances are less affected by radiation damage due to the their heavy masses, while one μ-oxo bridge (O5) moves significantly. The radiation damage may induce conformational changes of the water ligands but only bond elongation for the amino acids ligands. These effects are relatively intensity independent from 1016 to 1017 W/cm2, but changes increase dramatically if the beam intensity is increased to 1018 W/cm2. In addition, the self amplified spontaneous emission (SASE) nature of the laser beam does not affect the dynamics of the ions

Optimization of locations of diffusion spots in indoor optical wireless local area networks

In this paper, we present a novel optimization of the locations of the diffusion spots in indoor optical wireless local area networks, based on the central force optimization (CFO) scheme. The users’ performance uniformity is addressed by using the CFO algorithm, and adopting different objective function’s configurations, while considering maximization and minimization of the signal to noise ratio and the delay spread, respectively. We also investigate the effect of varying the objective function’s weights on the system and the users’ performance as part of the adaptation process. The results show that the proposed objective function configuration-based optimization procedure offers an improvement of 65% in the standard deviation of individual receivers’ performance

Recent Trends in Plasmonic Nanowire Solar Cells

Light trapping is crucial for low-cost and highly efficient nanowire (NW) solar cells (SCs). In order to increase the light absorption through the NWSCs, plasmonic materials can be incorporated inside or above the NW design. In this regard, two novel designs of plasmonic NWSCs are reported and analyzed using 3D finite difference time domain method. The geometrical parameters of the reported designs are studied to improve their electrical and optical efficiencies. The ultimate and power conversion efficiencies (PCE) are used to quantify the conversion efficiency of the light into electricity. The first design relies on funnel shaped SiNWs with plasmonic core while the cylindrical NWs of the second design are decorated by Ag diamond shaped. The calculated ultimate efficiency and PCE of the plasmonic funnel design are equal to 44% and 18.9%, respectively with an enhancement of 43.3 % over its cylindrical NWs counterpart. This enhancement can be explained by the coupling between the three optical modes, supported by the upper cylinder, lower cone and plasmonic material. Moreover, the cylindrical SiNWs decorated by Ag diamond offer an ultimate efficiency and short-circuit current density of 25.7%, and 21.03 mA∕cm2, respectively with an improvement of 63% over the conventional cylindrical SiNWs

Randomized ancillary qubit overcomes detector-control and intercept-resend hacking of quantum key distribution

Practical implementations of quantum key distribution (QKD) have been shown to be subject to various detector side-channel attacks that compromise the promised unconditional security. Most notable is a general class of attacks adopting the use of faked-state photons as in the detector-control and, more broadly, the intercept-resend attacks. In this paper, we present a simple scheme to overcome such class of attacks: A legitimate user, Bob, uses a polarization randomizer at his gateway to distort an ancillary polarization of a phase-encoded photon in a bidirectional QKD configuration. Passing through the randomizer once on the way to his partner, Alice, and again in the opposite direction, the polarization qubit of the genuine photon is immune to randomization. However, the polarization state of a photon from an intruder, Eve, to Bob is randomized and hence directed to a detector in a different path, whereupon it triggers an alert. We demonstrate theoretically and experimentally that, using commercial off-the-shelf detectors, it can be made impossible for Eve to avoid triggering the alert, no matter what faked-state of light she uses.Comment: Quantum encryption, bidirectional quantum key distribution, detector control, intercept and resend attacks, faked state photon

Tapered Plasmonic Nanoantennas for Energy Harvesting Applications

In this chapter, novel designs of tapered-dipole nanoantennas are investigated for energy harvesting applications. A full systematic analysis for the proposed structure is presented where the harvesting efficiency, return loss, radiation pattern, and near-field enhancement are calculated using a finite-element frequency domain solver. Simulation results show that the proposed nanoantennas can achieve a harvesting efficiency of 60% at a wavelength of 500 nm where the antenna input impedance is matched to that of fabricated rectifying devices. Additionally, the cross-tapered nanoantenna offers a near-field enhancement factor of 252 V/m, which is relatively high compared to previously reported nanoantennas. The spatial and spectral resonance modes are investigated, and the simulation results indicate the ability of the cross geometry to be utilized in color-sorting applications. Moreover, the particle swarm optimization technique is adapted to configure the proposed designs for maximum performance

Machine learning approach for computing optical properties of a photonic crystal fiber

Photonic crystal fibers (PCFs) are the specialized optical waveguides that led to many interesting applications ranging from nonlinear optical signal processing to high-power fiber amplifiers. In this paper, machine learning techniques are used to compute various optical properties including effective index, effective mode area, dispersion and confinement loss for a solid-core PCF. These machine learning algorithms based on artificial neural networks are able to make accurate predictions of above-mentioned optical properties for usual parameter space of wavelength ranging from 0.5-1.8 µm, pitch from 0.8-2.0 µm, diameter by pitch from 0.6-0.9 and number of rings as 4 or 5 in a silica solid-core PCF. We demonstrate the use of simple and fast-training feed-forward artificial neural networks that predicts the output for unknown device parameters faster than conventional numerical simulation techniques. Computation runtimes required with neural networks (for training and testing) and Lumerical MODE solutions are also compared

Enhancing land cover classification in remote sensing imagery using an optimal deep learning model

The land cover classification process, accomplished through Remote Sensing Imagery (RSI), exploits advanced Machine Learning (ML) approaches to classify different types of land cover within the geographical area, captured by the RS method. The model distinguishes various types of land cover under different classes, such as agricultural fields, water bodies, urban areas, forests, etc. based on the patterns present in these images. The application of Deep Learning (DL)-based land cover classification technique in RSI revolutionizes the accuracy and efficiency of land cover mapping. By leveraging the abilities of Deep Neural Networks (DNNs) namely, Convolutional Neural Networks (CNN) or Recurrent Neural Networks (RNN), the technology can autonomously learn spatial and spectral features inherent to the RSI. The current study presents an Improved Sand Cat Swarm Optimization with Deep Learning-based Land Cover Classification (ISCSODL-LCC) approach on the RSIs. The main objective of the proposed method is to efficiently classify the dissimilar land cover types within the geographical area, pictured by remote sensing models. The ISCSODL-LCC technique utilizes advanced machine learning methods by employing the Squeeze-Excitation ResNet (SE-ResNet) model for feature extraction and the Stacked Gated Recurrent Unit (SGRU) mechanism for land cover classification. Since ‘manual hyperparameter tuning’ is an erroneous and laborious task, the AIMS Mathematics Volume 9, Issue 1, 140–159. hyperparameter selection is accomplished with the help of the Reptile Search Algorithm (RSA). The simulation analysis was conducted upon the ISCSODL-LCC model using two benchmark datasets and the results established the superior performance of the proposed model. The simulation values infer better outcomes of the ISCSODL-LCC method over other techniques with the maximum accuracy values such as 97.92% and 99.14% under India Pines and Pavia University datasets, respectively

Light absorption enhancement in thin film hydrgenated amorphus Si solar cells

In this paper, light absorption enhancement in thin film solar cell (SC) is reported and analyzed. The suggested design is based on a nanostructured pattern that increases the diffuse scattered component of radiation and hence the absorption through the active layer. An ion beam sputtering (lBS) approach is used to texture large areas of the glass substrate with high aspect-ratio ripples in order to increase light scattering. Then, thin film SC supported on the textured glass is simulated and analyzed using 3D finite difference time domain (FDTD) method. The suggested SC can offer an ultimate efficiency of 19.26% with short circuit current of 15.76 mA/cm2 with an enhancement of 31.435% over the SC without texturing surface