This work presents a detailed study of thin zinc oxide (ZnO) films and ZnO composite films doped with the organic luminescent dye PQX, prepared by the sol-gel method and spin coating. The optical, thermo-optical, structural, and morphological properties of these films were investigated using spectroscopic ellipsometry, X-ray diffraction, thermal analysis, atomic force microscopy, and scanning electron microscopy. The PQX dye showed strong absorption in the blue region of the spectrum with a large Stokes shift, indicating potential for luminescent solar concentrator (LSC) applications. Thermal studies revealed limited stability of PQX in thin films with partial degradation beginning at 100 degrees C and complete decomposition above 300 degrees C, which affected the optical and structural properties of the composite films. Annealing led to an amorphous state transition of the organic component and increased porosity in the ZnO matrix. ZnO:PQX films exhibited increased surface roughness and reduced refractive index compared to pure ZnO. These findings suggest that while PQX enhances certain optical properties, its thermal instability limits the performance of ZnO:PQX composites in LSC devices, highlighting the need for further materials optimization.
This study assesses the material integrity of hot-plate-welded unplasticized PVC profiles reinforced with glass-fibre composite inserts, focusing on whether cycle shortening preserves the weld-zone state beyond satisfying macroscopic strength criteria. The constituent materials were characterised to define the mechanical and thermomechanical mismatch of the hybrid system. Welded corner specimens were produced under selected parameter sets and examined by ball indentation hardness testing, stereomicroscopy, differential scanning calorimetry, and Fourier-transform infrared spectroscopy in attenuated total reflectance mode. The composite contained 52.25 wt.% glass fibre and showed higher stiffness, strength, and heat deflection temperature than PVC-U, but substantially lower deformability, confirming pronounced material asymmetry in the joint region. The weld produced at 264 °C for 22 s exhibited a material response comparable to the reference condition of 264 °C for 30 s. Hardness, microscopy, DSC, and FTIR-ATR revealed no detectable microstructural, thermal, or chemical deterioration after reducing plasticisation time from 30 s to 22 s. Conversely, although the 270 °C/21 s variant remained mechanically acceptable in terms of the failure-load criterion, it showed light-brown discoloration extending from the bead into the joint interior, lower weld-zone hardness, and a broader DSC response, indicating local thermal overexposure. These results show that mechanical acceptability does not necessarily imply material stability and that cycle-time reduction should therefore be evaluated using complementary mechanical, morphological, thermal, and chemical criteria.
Passive synchronization of two pneumatic actuators is difficult because differences in external load, friction, and pneumatic resistance may cause unequal piston-rod motion. This study investigates the airflow characteristics of a passive pneumatic synchronizing element and the influence of its principal internal geometric parameters. Airflow measurements were performed at a constant supply gauge pressure of 2.4 ∙ 105 Pa. Equalizing-channel diameters of 3 ∙ 10−4 and 4 ∙ 10−4 m were tested with the annular microgap closed. The influence of the microgap height was then investigated for a constant channel diameter of 3 ∙ 10−4 m, using microgap heights from 2.5 ∙ 10−5 to 1.0 ∙ 10−4 m. Increasing the equalizing-channel diameter from 3 ∙ 10−4 m to 4 ∙ 10−4 m increased the airflow rate from 8.58 ∙ 10−5 m3/s to 1.14 · 10−4 m3/s. Increasing the microgap height from 2.5 ∙ 10−5 to 1.0 ∙ 10−4 m increased the airflow rate from 8.85 ∙ 10−5 m3/s to 2.18 ∙ 10−4m3/s . For the required airflow rate of 1.001 ∙ 10−4 m3/s, linear interpolation yielded 𝑆𝑆2,𝑖𝑖𝑖𝑖𝑖𝑖 = 3.99 ∙ 10−5m, corresponding to approximately 4.0 ∙ 10−5 m. The airflow capacity of the passive synchronizing element can be adjusted through the combined selection of the equalizing-channel diameter, investigated at 3.0 ∙ 10−4 m and 4.0 ∙ 10−4 m, and the annular microgap height, varied from 2.5 ∙ 10−5 m to 1.0 ∙ 10−4 m . The proposed procedure provides a practical basis for adapting the element to the airflow demand and piston-rod velocity limitation of a specific dual-actuator pneumatic system. The reported values are valid for the investigated geometry and operating conditions, including a supply gauge pressure of 2.4 ∙ 105 Pa, equalizing-channel diameters of 3.0 ∙ 10−4 m and 4. 0 ∙ 10−4 m, and annular microgap heights from 2.5 ∙ 10−5 m to 1. 0 ∙ 10−4 m.
Q-PINN-opt creates a new framework by combining the concepts of quantum computing with Physics-Informed Neural Networks (PINNs) for multi-modal optimization of diffractive optics under laser conditions. In high-power laser applications, which involve the optimization of complex problems, the model employs quantum-enhanced optimization coupled with physics-informed learning. In contrast to traditional approaches based on PINNs or Wiener filters, which are limited by their inability to scale, poor computational efficiency, and limited resilience to extreme conditions, Q-PINN-opt is a hybrid quantum-classical algorithm that accelerates convergence and maximizes computational efficiency. The major innovation of the Q-PINN-opt variant is that quantum algorithms (such as Quantum Gradient Descent and Quantum Approximate Optimization Algorithm (QAOA)) are implemented using classical PINNs. This enables faster, scalable, and multimodal optimization of problems, including diffraction efficiency, phase accuracy, and resistance to thermal, non-linear, and quantum-induced effects. Current models such as PINNs may also exhibit slow convergence and computational inefficiency when applied to optimization problems of complex, high-dimensional nature, especially when multiple performance criteria are to be optimized simultaneously. Q-PINN-opt addresses all these shortcomings; thus, it is specifically applicable to the optimization of diffractive optics for real-time adaptive learning. Q-PINN-opt addresses this problem by leveraging quantum computing to train more effectively and process large-scale data efficiently. Moreover, the hybrid quantum-classical model ensures the racial-physical constraints of network solutions, enhancing the resilience and scalability of high-performance optical systems. The Q- INN-opt framework metric analysis reveals that it performs better than models. MSE, SSIM, and SNR in the model are 6.84, 0.99, and 7.98, respectively, which imply the model has high accuracy, diffraction efficiency, and resistance to noise. Compared with the Original Model, the Original Model has an MSE of 9.55 and an SNR of 5.54. This improved both the training and the convergence of the optimization, making Q-PINN-opt well-constructed and efficient for the design of complicated diffractive optics in extreme environments.
In the paper, a novel decomposition technique of a non-symmetric real square matrix is presented. The algorithm is a generalization of QR Givens rotations technique by means of matrices provisionally called perturbed rotations. It is described in detail and summarized in algorithmic steps. Its existence conditions are given. The orthogonal matrix case is discussed. To illustrate the algorithm, a simple exemplary matrix decomposition is included.
