Interface and defects engineering for multilayer laser coatings

High-reflective multilayer laser coatings are widely used in advanced optical systems from high power laser facilities to high precision metrology systems. However, the real interface quality and defects will significantly affect absorption/scattering losses and laser induced damage thresholds of multilayer coatings. With the recent advances in the control of coating design and deposition processes, these coating properties can be significantly improved when properly engineered the interface and defects. This paper reviews the recent progress in the physics of laser damage, optical losses and environmental stability involved in multilayer reflective coatings for high power nanosecond near-infrared lasers. We first provide an overview of the layer growth mechanisms, ways to control the microstructures and reduce layer roughness, as well as the nature of defects which are critical to the optical loss and laser induced damage. Then an overview of interface engineering based on the design of coating structure and the regulation of deposition materials reveals their ability to improve the laser induced damage threshold, reduce the backscattering, and realize the desirable properties of environmental stability and exceptional multifunctionality. Moreover, we describe the recent progress in the laser damage and scattering mechanism of nodule defects and give the approaches to suppress the defect-induced damage and scattering of the multilayer laser coatings. Finally, the present challenges and limitations of high-performance multilayer laser coatings are highlighted, along with the comments on likely trends in future.     

An efficient edge based data structure for the compressible Reynolds-averaged Navier–Stokes equations on hybrid unstructured meshes

An efficient edge based data structure has been developed in order to implement an unstructured vertex based finite volume algorithm for the Reynolds-averaged Navier–Stokes equations on hybrid meshes. In the present approach, the data structure is tailored to meet the requirements of the vertex based algorithm by considering data access patterns and cache efficiency. The required data are packed and allocated in a way that they are close to each other in the physical memory. Therefore, the proposed data structure increases cache performance and improves computation time. As a result, the explicit flow solver indicates a significant speed up compared to other open-source solvers in terms of CPU time. A fully implicit version has also been implemented based on the PETSc library in order to improve the robustness of the algorithm. The resulting algebraic equations due to the compressible Navier–Stokes and the one equation Spalart–Allmaras turbulence equations are solved in a monolithic manner using the restricted additive Schwarz preconditioner combined with the FGMRES Krylov subspace algorithm. In order to further improve the computational accuracy, the multiscale metric based anisotropic mesh refinement library PyAMG is used for mesh adaptation. The numerical algorithm is validated for the classical benchmark problems such as the transonic turbulent flow around a supercritical RAE2822 airfoil and DLR-F6 wing-body-nacelle-pylon configuration. The efficiency of the data structure is demonstrated by achieving up to an order of magnitude speed up in CPU times.     

Prediction of the drag reduction effect of pulsating pipe flow based on machine learning

Prediction of drag reduction effect caused by pulsating pipe flows is examined using machine learning. First, a large set of flow field data is obtained experimentally by measuring turbulent pipe flows with various pulsation patterns. Consequently, more than 7000 waveforms are applied, obtaining a maximum drag reduction rate and maximum energy saving rate of 38.6% and 31.4%, respectively. The results indicate that the pulsating flow effect can be characterized by the pulsation period and pressure gradient during acceleration and deceleration. Subsequently, two machine learning models are tested to predict the drag reduction rate. The results confirm that the machine learning model developed for predicting the time variation of the flow velocity and differential pressure with respect to the pump voltage can accurately predict the nonlinearity of pressure gradients. Therefore, using this model, the drag reduction effect can be estimated with high accuracy.     

Fluid‐structure coupling of linear elastic model with compressible flow models

Cavitation erosion is caused in solids exposed to strong pressure waves developing in an adjacent fluid field. The knowledge of the transient distribution of stresses in the solid is important to understand the cause of damaging by comparisons with breaking points of the material. The modeling of this problem requires the coupling of the models for the fluid and the solid. For this purpose, we use a strategy based on the solution of coupled Riemann problems that has been originally developed for the coupling of 2 fluids. This concept is exemplified for the coupling of a linear elastic structure with an ideal gas. The coupling procedure relies on the solution of a nonlinear equation. Existence and uniqueness of the solution is proven. The coupling conditions are validated by means of quasi‐1D problems for which an explicit solution can be determined. For a more realistic scenario, a 2D application is considered where in a compressible single fluid, a hot gas bubble at low pressure collapses in a cold gas at high pressure near an adjacent structure.     

An approach of dynamic mesh adaptation for simulating 3‐dimensional unsteady moving‐immersed‐boundary flows

In this paper, we present an approach of dynamic mesh adaptation for simulating complex 3‐dimensional incompressible moving‐boundary flows by immersed boundary methods. Tetrahedral meshes are adapted by a hierarchical refining/coarsening algorithm. Regular refinement is accomplished by dividing 1 tetrahedron into 8 subcells, and irregular refinement is only for eliminating the hanging points. Merging the 8 subcells obtained by regular refinement, the mesh is coarsened. With hierarchical refining/coarsening, mesh adaptivity can be achieved by adjusting the mesh only 1 time for each adaptation period. The level difference between 2 neighboring cells never exceeds 1, and the geometrical quality of mesh does not degrade as the level of adaptive mesh increases. A predictor‐corrector scheme is introduced to eliminate the phase lag between adapted mesh and unsteady solution. The error caused by each solution transferring from the old mesh to the new adapted one is small because most of the nodes on the 2 meshes are coincident. An immersed boundary method named local domain‐free discretization is employed to solve the flow equations. Several numerical experiments have been conducted for 3‐dimensional incompressible moving‐boundary flows. By using the present approach, the number of mesh nodes is reduced greatly while the accuracy of solution can be preserved.     

Residual strain in cadmium telluride/gallium arsenide (001) heterostructures as a function of temperature

Optical studies of residual strain in cadmium telluride (CdTe) films grown using molecular beam epitaxy on gallium arsenide (GaAs) substrate have been performed using photoreflectance techniques. Measurements have been conducted to determine the fundamental transition energy, heavy-hole and light-hole transition energy critical-point parameters in a range of temperatures between 12 and 300 K. There are problems inherent in the fabrication of optoelectronic devices using high-quality CdTe films, due to strain effects resulting from both the lattice mismatch (CdTe: 14.6%) and the thermal expansion coefficient difference. The CdTe film exhibits compressive stress causing valence-band splitting for light and heavy holes. We have used different models to fit the obtained experimental data and, although the critical thickness for the CdTe has been surpassed, the strain due to the lattice mismatch is still significant. However, the strain due to the thermal expansion is dominant. We have found that the fundamental transition energy, E₀, is affected by the compressive strain and the characteristic values are smaller than those reported. In addition, the total strain is compressive for the full measured range, since the strain due to the lattice mismatch is one order of magnitude higher than that calculated from the thermal expansion.     

Defects related emission and nanosecond optical power limiting in CuS quantum dots

We report optical and nonlinear optical properties of CuS quantum dots and nanoparticles prepared through a nontoxic, green, one-pot synthesis method. The presence of surface states and defects in the quantum dots are evident from the luminescent behavior and enhanced nonlinear optical properties measured using the open aperture Z-scan, employing 5 ns laser pulses at 532 nm. The quantum dots exhibit large effective third order nonlinear optical coefficients with a relatively lower optical limiting threshold of 2.3 J cm⁻², and the optical nonlinearity arises largely from absorption saturation and excited state absorption. Results suggest that these materials are potential candidates for designing efficient optical limiters with applications in laser safety devices.     

Curvature investigation in tapered fibers and its application to sensing and mode conversion

Non-adiabatic tapered fibers are basic photonic components used in a wide range of applications. Here we investigate a way to increase their utility through the controllable bending of one of their tapered sections. The experiments carried out explain, for the first time, the mechanics of this approach showing how these tapers can be used to build more sensitive sensors. Their use as highly efficient mode converters is also discussed.