Inverse design of a photonic moiré lattice waveguide towards improved slow light performances.

Slow light waveguides in photonic crystals are engineered using a conventional method or a deep learning (DL) method, which is data-intensive and suffers from data inconsistency, and both methods result in overlong computation time with low efficiency. In this paper, we overcome these problems by inversely optimizing the dispersion band of a photonic moiré lattice waveguide using automatic differentiation (AD). The AD framework allows the creation of a definite target band to which a selected band is optimized, and a mean square error (MSE) as an objective function between the selected and the target bands is used to efficiently compute gradients using the autograd backend of the AD library. Using a limited-memory Broyden-Fletcher-Goldfarb-Shanno minimizer algorithm, the optimization converges to the target band, with the lowest MSE value of 9.844×10-7, and a waveguide that produces the exact target band is obtained. The optimized structure supports a slow light mode with a group index of 35.3, a bandwidth of 110 nm, and a normalized-delay-bandwidth-product of 0.805, which is a 140.9% and 178.9% significant improvement if compared to conventional and DL optimization methods, respectively. The waveguide could be utilized in slow light devices for buffering.

Photonic Moiré lattice waveguide with a large slow light bandwidth and delay-bandwidth product.

We proposed an effective approach to enlarge the slow light bandwidth and normalized-delay-bandwidth product in an optimized moiré lattice-based photonic crystal waveguide that exhibits intrinsic mid-band characteristics. A flatband corresponding to a nearly constant group index of 34 over a wide bandwidth of 82 nm centered at 1550 nm with near-zero group velocity dispersion was achieved. A large normalized-delay-bandwidth product of 0.5712 with a relative dispersion of 0.114%/µm was obtained, which is a significant improvement if compared with previous results. Our results indicate that the photonic moiré lattice waveguide could advance slow light applications.

Frequency optimization of permeability metamaterial for enhanced resolution.

We analyze and optimize the performance of unconventional negative permeability (µ) metamaterial and demonstrate its ability to focus and restore the decaying Fourier harmonics (FH) in microwave regime operating frequencies. We show that multiple real µr' and imaginary µr'' values of µr at same or multiple operating frequencies for a resonant type of -µ metamaterial could not exhibit finest resolution at the region of interest (ROI), unless and until the distance of the source plane with respect to metamaterial and ROI could be re-optimized in accordance with µr' and µr'' of µr. Using the variable parameters to enhance the resolution limit of -µ metamaterial, we optimize the metamaterial's configuration for maximum propagation field absorption and regeneration of decaying FH at ROI. The optimization of the test bed that contains the source plane, -µ metamaterial, and ROI followed by the regeneration of the decaying FH from the source plane at the surface of the material, yielded a high image resolution at ROI.

Exploring soil radon (Rn) concentrations and their connection to geological and meteorological factors.

The relationship between soil radon and meteorological parameters in a region can provide insight into natural processes occurring between the lithosphere and the atmosphere. Understanding this relationship can help models establish more realistic results, rather than depending on theoretical consequences. Radon variation can be complicated to model due to the various physical variables which can affect it, posing a limitation in atmospheric studies. To predict Rn variation from meteorological parameters, a hybrid mod el called multiANN, which is a combination of multi-regression and artificial neural network (ANN) models, is established. The model was trained with 70% of the data and tested on the remaining 30%, and its robustness was tested using the Monte-Carlo method. The regions with low performance are identified and possibly related to seismic events. This model can be a good candidate for predicting Rn concentrations from meteorological parameters and establishing the lower boundary conditions in seismo-ionospheric coupling models.

Computational Study of Doping in Dopamine with Halogens to Control Optical and Spectroscopic Properties.

In this research, a comprehensive study of dopamine was conducted using the theoretical first principles method due to its crucial importance as a hormone for the neurotransmission process in the animal body. Many basis sets and functionals were used for optimization of the compound to attain stability and find the appropriate energy point for the overall calculations. Then, the compound was doped with the first three members of the halogen family (fluorine, chlorine, and bromine) to analyze the effect of their presence in terms of change in their electronic properties, such as band gap and density of states, and spectroscopic parameters, such as nuclear magnetic resonance and Fourier transform infrared. It was found that the band gap of the system changes depending on the doping of halogens.

Halogen Doping to Control the Band Gap of Ascorbic Acid: A Theoretical Study.

Ascorbic acid is an important antioxidant agent that acts as an electron donor and is involved in many physiological processes. Structural modification in ascorbic acid is a subject of extensive biochemical research due to its involvement in a variety of relevant phenomena including electron transport, complex redox reactions, neurochemical reactions, enzymatic reactions, and chemotherapeutic potential. In this work, the structure of ascorbic acid is modified via doping with the first three members of the halogen group to investigate the changes in the electronic structure and spectroscopic parameters using first-principles methods. To obtain the lowest-energy structures, different basis sets in density functional theory (DFT) and Hartree-Fock approaches were employed in the geometry optimization process. The potential energy maps of the structures were computed to study the molecular orientations and their optical and electrical properties. The spectroscopic properties were computed via UV-vis and nuclear magnetic resonance (NMR) spectroscopies to study the effects of doping into the compound. To obtain further insights into the chemical structure, the Fourier transform infrared (FT-IR) spectra of the materials were theoretically investigated. It was found that the band gap is sensitive to doping as we moved from fluorine to chlorine and then to bromine.