Deflectometry is a non-destructive, full-field phase measuring method, which is usually used for inspecting optical specimens with special characteristics, such as highly reflective or specular surfaces, as well as free-form surfaces. One of the important steps in the Deflectometry method is to retrieve the surface from slope data of points on the sample map or surface reconstruction. This paper proposes a modal reconstruction method using an adjustable number of Zernike polynomials. In addition, the proposed method enables the analyses on practical surfaces that require an infinite number of Zernike terms to be represented. Experiments on simulated surfaces indicated that the algorithm is able to reveal the number of major-contributing Zernike terms, as well as reconstruct the surface with a micrometer-scale from slope data with a signal-to-noise ratio of 10.

M o S 2 , a two-dimensional transition metal dichalcogenide (TMD), has garnered significant interest for its promising applications in semiconductors and solar cells due to its unique photovoltaic properties. This work investigates the role of M o S 2 layers in enhancing solar cell performance, with a focus on layer optimization through both simulation and experimental validation. Using the SCAPS-1D simulation tool, we analyze and optimize key parameters such as layer thickness, defect density, band gap, temperature, and buffer layer, aiming to maximize photovoltaic performance. The impact of these parameters on critical performance metrics including power conversion efficiency (PCE), open-circuit voltage (V_oc), short-circuit current density (J_sc), and fill factor (FF) is examined. Simulation results are compared with experimental data, highlighting key discrepancies and confirming the accuracy of the model. The study reveals that optimal layer parameters, including a thickness of 50 nm, acceptor density of 100 × 10¹⁸ cm⁻³, band gap of 1.2 eV, and a temperature of 300 K, result in a significant boost in solar cell efficiency. With these optimal parameters, the PCE reaches 21.06%, demonstrating a clear path toward high-performance solar cell design. This research bridges theoretical simulations and practical applications, offering valuable insights into the design and optimization of M o S 2 -based solar cells.

In laser machining and microprocessing using ultrashort pulses, reliable simulation of laser ablation is crucial for analyzing laser-target interactions and optimizing ablation efficiency. However, this task presents significant challenges due to the extremely short timescales, multiphysics complexities, and phase transitions. This study focuses on developing a two dimensional two-temperature model to improve the accuracy of ablation depth predictions for gold and silver electrodes. Moreover, this study also highlights the importance of precisely controlling ablation depth in material processing, particularly for the fabrication of electronic components such as electrodes and display substrates. Simulations were conducted for both single and multi-pulse ablation across varying laser fluences. The results indicated that the simulated ablation depth for single-pulse ultrafast laser irradiation of gold and silver increases with fluence. Surface temperature decreases more slowly under femtosecond compared to picosecond laser processing. Finally, the simulation results were compared with experimental data. Under multipulse irradiation, ablation depth increases linearly with pulse number. A fluence of 2.5 J cm⁻² is recommended for micromachining 100 nm gold films to optimize cost and efficiency in electronics manufacturing.

Cranioplasty is a standard neurosurgical procedure performed on patients following decompressive craniectomy. This study investigates the influence of implant thickness and material on biomechanical performance through finite element analysis. Cranial implants composed of Polyether Ether Ketone (PEEK), Polymethyl Methacrylate (PMMA), and Ti6Al4V with thicknesses in the range of 1 mm to 5 mm were systematically evaluated under three loading conditions. The findings indicate that increased implant thickness significantly reduces both deformation and von Mises stress. Implants with thicknesses of 1 mm and 2 mm exhibited the greatest deformation, potentially surpassing the material’s yield strength. Maximum stress was predominantly localized at the interface between the implant fixation points and the skull, with implant thickness exerting a more pronounced effect than material type. Notably, implants with a 4 mm thickness in PEEK and PMMA demonstrated optimal mechanical performance, maintaining strain values at screw locations within the safe range of 200 to 2500 μ ε , thereby promoting bone formation and growth. Additionally, implant micromotion (IMM) was assessed to determine the biological durability of the implants. This analysis provides critical insights into cranial implants’ biocompatibility and long-term mechanical stability.