ABX3 perovskite-based materials have attracted research attention in various electronic and optoelectronic applications. The ability to tune the energy band gap through various dopants makes perovskites a potential candidate in many implementations. Among various perovskite materials, BaTiO3 has shown great applicability as a robust UV absorber with an energy band gap of around 3.2 eV. Herein, we provide a new sonochemical-assisted solid-phase method for preparing BaTiO3 thin films that optoelectronic devices can typically be used. BaTiO3 nano-powder and the thin film deposited on a glass substrate were characterized using physicochemical and optical techniques. In addition, the work demonstrated a computational attempt to optically model the BaTiO3 from the atomistic level using density functional theory to the thin film level using finite difference time domain Maxwell's equation solver. Seeking repeatability, the dispersion and the extinction behavior of the BaTiO3 thin film have been modeled using Lorentz-Dude (LD) coefficients, where all fitting parameters are listed. A numerical model has been experimentally verified using the experimental UV–Vis spectrometer measurements, recording an average root-mean-square error of 1.44%.

Various solar cell architectures and materials are currently studied, seeking enhanced photon management mechanisms. Herein, we provide an attempt to prepare, characterize, model, and simulate a novel semiconductor, Lithium Titanate, which has a band gap of 3.55 eV. The semiconductor was prepared from H2TiO3 and LiCO3 by calcination at 500 °C for 5 h after grinding with deionized water. XRD, SEM, EDX, and AFM carried out a complete morphological characterization on powder and thin-film levels. Additionally, experimentally validated atomistic DFT modeling was performed where the density of states and the imaginary part of the permittivity were extracted. Finally, the optical transmission spectrum was simulated for a 4.28 μm thickness film, with the aid of a finite-difference time-domain solver, against an experimentally measured spectrum, showing a root-mean-square mismatching error of 3.78%.

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Low-power IoT sensing applications have proliferated, focusing on self-powered sensors. Accordingly, researchers have investigated serval procedures for the power management of such self-powered sensors. Obesely, minimizing the energy consumed by the sensor is critical to efficient power management. However, another challenge is still considered in harvesting energy effectively. Herein, we provide an attempt to investigate light harvesters that are capable of semi-transparent applications. Six samples were simulated under three light sources while performing a unifacial and bifacial optical injection. The optoelectronic numerical model has shown the utility of perovskite solar cells to harvest the AM1.5G solar spectrum up to 28.63%, with transparency reaching 87%. On the other hand, the bifacial condition boosted the overall cell efficiency to nearly 33% with transparency of 90%, without considering Fresnel glass reflection of 8%. The proposed bifacial cell is a primary light-harvesting source for four IoT sensing applications, including biomedical sensing, underwater harvesting, and IoT sensing in intelligent vehicles and buildings.