Material Model Research Articles

Preface

Abstract With the continuous changes in material demand and the development of related disciplines driven by economic and social development, in recent years, material research has shown some new trends. The deep integration of material technology and information technology has deepened our understanding of material structure and performance, leading to more precise control over the material preparation process and functionality. The conference shares practical experiences and enlightening ideas from mateirals physics and appliacations and will be of interest to researchers in and practitioners everywhere. Keynote speakers includes Prof. Junhui Hu, from Nanjing University of Aeronautics & Astronautics, China, Prof. Karamanis Dimitrios from University of Patras, Greece, Prof. Osman Adiguzel from Firat University, Elazig, Turkey. The proceedings present papers from the International Conference on Materials Physics and Applications, held in Xi’an during 1-3 October, 2024. All papers were carefully reviewed by the technical program committee (TPC) and reviewers, bearing in mind the quality, novelty, breadth and depth of the research themes which fall into the ICMPA scope. The topics of papers accepted in the Proceedings of ICMPA 2024 can be classified as Material Modeling and Application, Phase Transition and Mechanical Properties of Materials, Glasses & Ceramics, Composites Materials. Furthermore, we are very grateful to everyone, especially the program committee members and reviewers, who devoted time to assess the papers. Our particular thanks and regards also go to the Journal of Physics: Conference Series, for supporting this conference. List of Conference Committees are available in this Pdf.

Coupled 3D non-orthogonal constitutive model for woven composites in preforming and compaction processes

Woven composites are considered promising for lightweight applications with great environmental and economic benefits. One of the most promising techniques for mass-production of woven composite parts with complex geometry is closed-mold thermoforming including preforming, compaction/consolidation and curing steps. The ignored effects on non-uniform thickness deformation and compaction modulus caused by preforming are considered in the coupled 3D non-orthogonal constitutive model to capture the coupled material behaviors during preforming and compaction. The in-plane tension, compression and shear modulus in the model are calibrated using tension, bending and bias-extension experiments, respectively. Meanwhile, the out-plane compaction experiments are designed, with high-accuracy measurement method for the initial thickness and deformation process, to obtain the material properties of sheared woven composites. These experiments can be regarded as one benchmark for compaction tests of woven composites. The new material model has been implemented in Abaqus software and validated by the bias-extension experiments.

A fine-segmentation algorithm for XCT images of multiphase composite building materials based on deep learning

In response to the challenges presented by the variable internal structures and complex components of multiphase composite building materials, this study introduces a novel image segmentation network named UT-FusionNet. Building on the U-Net model, UT-FusionNet integrates Transformer module and tensor concatenation and fusion mechanism to overcome the limitations of convolutional networks in relation to the receptive field. UT-FusionNet is employed to segment CT images of conventional concrete, grout consolidation bodies, and fiber-reinforced concrete. The results demonstrate that UT-FusionNet achieves superior segmentation accuracy and robustness, with Accuracy (ACC), Intersection over Union (IoU) and Dice scores exceeding 90 % across all subtasks. The mean accuracy metrics are 99.44 %, 96.70 %, and 98.31 %, respectively. This innovative end-to-end network offers robust support for detailed structural analysis, damage detection, and digital modeling of multiphase composite building materials through deep learning.

Nonlinear twofold saddle point-based mixed finite element methods for a regularized μ(I)-rheology model of granular materials

We propose and analyze new mixed finite element methods for a regularized μ(I)-rheology model of granular flows with an equivalent viscosity depending nonlinearly on the pressure and the Euclidean norm of the symmetric part of the velocity gradient. To this end, and besides the velocity, the pressure and the aforementioned strain rate, we introduce a modified stress tensor that includes the convective term, and the skew-symmetric vorticity, as auxiliary tensor unknowns, thus yielding a mixed variational formulation within a Banach spaces framework. Then, the pressure is obtained through an iterative postprocess suggested by the incompressibility condition of the fluid, which allows us to express this unknown in terms of the aforementioned stress and the velocity. A fixed-point strategy combined with a solvability result for a class of nonlinear twofold saddle point operator equations in Banach spaces, is employed to show, along with the classical Banach fixed-point theorem, the well-posedness of the continuous and discrete formulations. In particular, PEERS and AFW elements of order ℓ⩾0 for the stress, the velocity, and the skew-symmetric vorticity, and piecewise polynomials of degree ⩽ℓ+n (resp. ⩽ℓ+1) for the strain rate with PEERS (resp. with AFW), yield stable Galerkin schemes. Optimal a priori error estimates are derived and associated rates of convergence are established. Finally, numerical results confirming the latter and illustrating the good performance of the methods, are reported.

Graph neural network-based multiscale thermal modeling for heterogeneous materials with complex structures

This study presents a novel GNN-based model for multiscale thermal characterization of heterogeneous materials with complex microstructures. It incorporates relationships between composition, structure, and thermal transport across multiple scales, leveraging the structure of GNNs. Results demonstrate enhanced performance of the GNN-based model compared with existing methods. Specifically, the GNN model improved thermal conductivity prediction with a mean absolute error of 0.18 W/mK (15 % improvement over the Bayesian neural network-based model) and provided a 30x speedup in computation time. The model successfully connected atomic-scale interactions to macroscale properties, achieving less than 5 % error in predicting effective thermal conductivity from one scale to another. Furthermore, it demonstrated the ability to capture nonlinear thermal transport phenomena with 92 % accuracy. The model also improved the prediction of the transient thermal responses by 20 %, accurately capturing the time-varying behaviour of materials. This work also proved the model’s ability to handle new material systems with transfer learning, achieving 88 % accuracy. Finally, Bayesian neural networks integrated into the model provided uncertainty quantification, with 95 % of experimental measurements falling within the predicted bounds. This work demonstrated the ability of the framework to handle complex microstructures, nonlinear phenomena, and transient responses while maintaining a computationally efficient model that can enable real-time applications in design and optimization needed in modern materials innovation. It represents a powerful tool for data-driven multiscale mechanics that could accelerate materials research and development for the aerospace, electronics cooling, and additive manufacturing industries.

Modeling of Fe-Based Soft Magnetic Materials for Multiphysical Analysis of Medium-Frequency Transformers

Modeling of Fe-Based Soft Magnetic Materials for Multiphysical Analysis of Medium-Frequency Transformers

Theory and Experiment on Rock-Cutter Interfacial Friction and Rock Mohr-Coulomb Parameter Estimations

Summary The Mohr-Coulomb (M-C) failure criteria is by far the most widely used model for granular materials (including rocks and soils) in many geotechnical industries due to its simplicity. Its parameters are conventionally obtained by performing a series of pressurized triaxial compression tests (TCTs). The peak stress from each confining pressure is plotted at a single point as the maximum vs. the minimum principal stresses. The M-C parameters are obtained by the best linear fitting through the failure envelope formed by the peak stress points of interest. The TCT is time-consuming, costly, and destructive. Is there an experiment that can provide the failure envelope with one single test, even at the atmospheric pressure? This seems impossible, at least has never been rigorously reported. In this work, we present our finding of such a test. The paper first provides the experimental setup and the theoretical solution for a hemispherical scratch test of a polycrystalline diamond cutter (PDC) at low rate of cut (ROC) and low depth of cut (DOC); the theoretical characteristic response of the test is identified and validated. Next, the formula for the rock-cutter interfacial coefficient of friction (COF) is derived, which provides a theoretical guide for the friction measurement for shaped cutters. Then, the nominal average drag and thrust stresses are evaluated, which are observed experimentally and then proved theoretically to behave in a linear relation, analogous to the M-C envelope from the TCTs. We also provide a first method that can self-consistently evaluate the M-C parameters for the crushed zone, which plays a very important role in rock cutting. By comparing the M-C results for three rocks at different loading conditions, good agreements under different scratch conditions are made against the M-C parameters for several rocks from the TCTs.

Slot coating of time-dependent structured materials: Effects of thixotropy on the flow dynamics and operating limits

Some of the most common liquid-like formulations rooted in the coating industry consist of rheologically complex structured materials such as inks, paints, and slurries. Yet, the impact of time-dependent structuring effects due to thixotropy on thin film coating applications remains elusive and still unclear. Here, we present a computational study of the effects of thixotropy on slot coating of time-dependent structured materials. By coupling a recent fluidity-based constitutive model for thixotropic materials with a well-established finite element/elliptic mesh generation method for free surface flows, we assess the role of thixotropy by comparing the predictions from the thixotropic model with those from a simple Generalized Newtonian Fluid model that uses the same flow curve for the material steady-state equilibrium viscosity. We find that thixotropy can indeed have a major impact on slot coating applications, potentially bringing strong implications not only to the flow dynamics but also to the operating limits of the process. In conclusion, the results and discussions we present in this study underscore the importance of accounting for thixotropy to genuinely model and fundamentally understand the behavior of time-dependent structured materials with complex rheology in processing flows like those ubiquitous across the broad fields of coating science and engineering.

Coarse-grained molecular dynamic model and wettability simulation of graphite materials

Although progress has been made in high-performance computing, there are still limitations on temporal and spatial scales of molecular dynamic calculations. A major issue in molecular dynamic (MD) simulations is the computational cost, and coarse-grained methods can save computational costs and accelerate calculations by reducing the degrees of freedom in the system. This method takes a selected group of representative atoms in the atomic microstructure as a bead and uses the proportional relationship of atomic scale atomic potentials in MD simulation to define the interaction between beads and solve the motion equation of beads. This article proposed a coarse-grained potential for graphite based on the modification of Airebo potential, with an n3: 1 mapping, and established a corresponding n3: 1 coarse-grained model, where one bead represents the number of n3 atoms. The results indicated that the coarse-grained model well reflected the basic thermal and mechanical properties of graphite. In addition, this article also proposed a coarsening method for the Lennard–Jones (L–J) potential function parameters and established a coarse-grained wetting model with n = 2. The results indicate that the coarse-grained wetting model can effectively predict the wetting performance of copper droplets on graphite in only 60% of the time using the all-atom model. The coarsening potential function and model proposed in this article are also applicable to graphite with rough surfaces. It can be anticipated that coarse-grained molecular dynamics methods will have more applications in the future, as they can handle large-scale calculations more quickly.

Concurrent experimental testing and computational micromechanical modeling of a UD NCF GFRP composite ply

The current research work presents a detailed and thoroughly validated computational micromechanical modeling methodology to study the damage initiation and propagation in a uni-directional (UD) glass fiber-reinforced non-crimp fabric (NCF) composite ply. Under the applied transverse tension and compression loads, the effect of various microscale material and geometrical parameters on the ply level stress–strain behavior is studied. To this end, along with the distinctly modeled individual microscale constituents of the UD NCF composite ply (axial fibers, backing fibers, and matrix), the generated RVE (Representative Volume Element) model consists of manufacturing-induced defects and variabilities such as voids as well as the backing fiber’s out-of-plane waviness. The fiber/matrix interface failure behavior in the generated RVE model is simulated using cohesive zone formulations that follow bi-linear traction-separation law. Whereas the hydrostatic pressure-dependent non-linear stress–strain response followed by the fracture of the epoxy matrix is captured using the linear Drucker-Prager plasticity model coupled with the stress triaxiality-based failure criterion. The backing fibers stress–strain and failure behavior is modeled using the linear elastic and isotropic material model in conjunction with the maximum stress criterion.The proposed numerical methodology is thoroughly validated both qualitatively and quantitatively by conducting detailed experiments on a neat epoxy as well as at the composites laminate level. Upon comparing the experimental and computational results, the observed knee or slope change in the bi-linear stress–strain response of the UD NCF composite ply under transverse tension is attributed to the loss of the load-carrying ability of the axial fiber bundle due to fiber/matrix interface debonding followed by the ply splitting. Under the application of transverse compression load, the composite ply failure behavior is governed by the formation of a dominant matrix plastic shear band in the axial fiber bundles, which is in turn triggered by the fiber/matrix interface failure. Under the applied loads in the matrix-dominated direction, the presented research work provides a detailed insight into the microscale damage initiation and propagation in a UD NCF composite ply and its consequent influence on the macroscale stress–strain response.

Assessment of aluminium alloys’ formability by elevated temperature testing

Abstract This work presents an investigation of the warm formability of AA7075-T6 aluminium alloy sheets using both experimental and numerical methods. Forming limit diagrams (FLDs) can be created by plotting the failure criteria on a graph with two axes representing major and minor strains. Sheets with a grid can be used to quantify both large and minor strains. General techniques available for the grid involve regular patterns of circles in this experiment. Experiments were conducted at various temperature levels, including room temperature, 100, 120, 140, 160, and 180 °C, as well as different strain rates. The investigation has revealed a significant impact of temperature on formability, while the effect of forming speed is quite insignificant across the whole range studied. At an ageing temperature of 140 °C, the distribution of precipitates is evenly balanced, resulting in improved mechanical strength. To offer accurate numerical models for warm-forming processes, a proposed constitutive model is introduced for aluminium alloy sheets. The present model incorporates plastic anisotropy and the effects of temperature and strain rate dependence. An investigation was conducted on the stress-strain behaviour of thin sheets composed of AA7075-T6 aluminium alloy under elevated temperatures and different strain rates. The objective was to ascertain the appropriate fitting parameters. It was associated with ABAQUS finite element modelling. The recommended material model was utilized to build finite element models, which were subsequently compared to the experimental data. The findings obtained from simulated isothermal uniaxial tensile tests were compared to the empirical measurements. The models used in the tensile test accurately predicted the material’s mechanical response. The predicted failure location, punch forces, and strain distributions for all three forming processes were found to be in close agreement with the experimental results. During deep draw operation, the warm forming limit curves were utilized to precisely predict both the pierce depth at which failure occurs and the precise location where the failure initiates.

The density effect on disposable mask waste as an acoustic absorber material

Abstract Mask ability in absorbing sound has been proven as it increases in line with thickness adding. Another characteristic that can optimize the absorption is density. This article aims to study the effect of mask density on the sound-absorption capability. This research was conducted by making absorber material models made of masks from two different brands. In the model making, this research uses two types of masks, the folded peach-colored folded face mask black duckbill type which are arranged up to 2.5 cm in thickness. In that thickness, the folded peach mask has 254 kg/m3 density and the black mask has 305 kg/m3 density. The analysis is carried out using the tube method. The research results show that at a frequency of 400 Hz, the folded peach mask has the highest absorption coefficient of 0.70, whereas the black mask has an absorption coefficient of 0.48. There is a significantly reduced absorption coefficient at the 600 Hz frequency that makes the mask not meet the standard. It can be concluded that the mask material can be used as an acoustic material as it meets the acoustic standard on absorption coefficient of at least 0.3. These findings support previous research on the potency of mask waste as an acoustic material. Therefore, the absorber material from used mask could be a solution to reduce non-degradable waste.

Numerical evaluation of the performance of UHPC beams under bending and shear loads using different material models

The Microplane and Menetrey-Willam concrete models are formulated on the research work of Bazant and Gambarova and Menetrey-Willam in the nineties respectively. They are used in this thesis to predict how reinforced Ultra-High-Performance Concrete (UHPC) beams will behave when subjected to flexural and shear dominant loadings. The numerical models are available in ANSYS, and they can simulate UHPC's extraordinary mechanical properties, such as high compression and tension strength, strain hardening, and softening behavior in compression and tension. In this research, four UHPC beams with dimensions of 180 wide by 270 deep by 4000 mm long with tensile reinforcements were studied using the two cementitious composite models mentioned above with the ANSYS software. The beams were investigated under flexural four-point loading and shear three-point loading with the ANSYS program. A quarter-geometric section model of the full beam was considered for the four-point loading to take advantage of symmetry in the longitudinal and transverse directions of the beam. For the three-point loading, the full geometry model of the beam was considered only because of the lack of symmetry. The results from the ANSYS finite element software were validated with an experimental study conducted by different researchers to show its capacity to predict the bending and shear behavior of reinforced UHPC beams. The comparisons of the results of both material models show that they can simulate the behavior of UHPC beams by using experimental load-deflection plots of the beam specimens and force strain plots of the longitudinal tensile reinforcements in the sample beams.

A microstructural thermo‐elastoplastic analysis of the mushy zone during laser beam welding

AbstractAs a modern method of contact free fusion, laser beam welding has gained importance in recent years. This is due to both the possibiliy of a high advance speed of the laser and low thermal distortion of the components compared to other welding processes, see Dal and Fabbro. These beneficial process properties follow from a focused laser, which thus results in a precise energy input. In addition, laser beam welding processes can be automated which makes the process attractive for a wide range of applications, cf. Dilthey. Nevertheless, various influences, like the temperature gradient, the chemical composition or process parameters, may have an effect on the occurrence of so‐called solidification cracks. Solidification cracks arise during solidification and occur in the area of the mushy zone, which is located behind the melt pool. The material behavior in the mushy zone is governed by a dendritic morphology. Due to this, liquid phase inclusions may occur in some parts of the mushy zone, see Hills et al.. When these trapped areas solidify, no further liquid phase can follow and a negative pressure is created. The resulting stresses can then lead to solidification cracks. In further studies, the geometry of the dendritic morphology will be generated on the basis of previous phase field simulations. These describe the dendrite growth controlled by the chemical concentration. The resulting geometry will then be simulated using the possibilities of a thermo‐elastoplastic material model, which will enable temperature‐driven imitation of growth. This contribution addresses the evolving state of the dendritic microstructure in a simplified manner. Therefore, for the first study, a simplified morphology is used, that is, no secondary arms and an elliptical geometry of the dendrites is assumed. Thermal as well as elastoplastic effects are already taken into account, in order to represent the inherent stress and strain states in the microstructure. These may be related to critical states leading to failure in the future.

Artificial Intelligence Modeling of Materials’ Bulk Chemical and Physical Properties

Energies of the atomic and molecular orbitals belonging to one and two atom systems from the fourth and fifth periods of the periodic table have been calculated using ab initio quantum mechanical calculations. The energies of selected occupied and unoccupied orbitals surrounding the highest occupied and lowest unoccupied orbitals (HOMOs and LUMOs) of each system were selected and used as input for our artificial intelligence (AI) software. Using the AI software, correlations between orbital parameters and selected chemical and physical properties of bulk materials composed of these elements were established. Using these correlations, the materials’ bulk properties were predicted. The Q2 correlation for the single-atom predictions of first ionization potential, melting point, and boiling point were 0.3589, 0.4599, and 0.1798 respectively. The corresponding Q2 correlations using orbital parameters describing two-atom systems increased the capability to predict the experimental properties to the respective values of 0.8551, 0.8207, and 0.7877. The accuracy in predicting materials’ bulk properties was increased up to four-fold by using two atoms instead of one. We also present results of the prediction of molecules for materials relevant to energy systems.

Theoretical design and synthesis of Co30Ni60/CC for high selective methanol oxidation assisted energy-saving hydrogen production

The integration of methanol oxidation reaction (MOR) with hydrogen evolution reaction (HER) represents an advanced approach to hydrogen production technology. Nonetheless, the rational design and synthesis of bifunctional catalysts for both MOR and HER with exceptional activity, stability and selectivity present formidable challenges. In this work, firstly, density functional theory (DFT) was utilized to design and evaluate material models with high performance for both MOR and HER. Secondly, guided by DFT, Co30Ni60/CC (CC, carbon cloth) composites with a leaf-like nanosheet structure were successfully fabricated via electrodeposition. In the MOR process, Ni acts as the predominant active center, while Co amplifies the electrochemically active surface area (ECSA) and enhances the selectivity of methanol oxidation. Conversely, in the HER process, Co serves as the primary active center, with Ni augmenting the charge transfer rate. The electrochemical results demonstrate that Co30Ni60/CC exhibits exceptional performance in both MOR and HER at a current density (j) of 10 mA cm−2, with peak potentials of 1.323 V and −95 mV, respectively. Additionally, it shows remarkable selectivity for the oxidiation of methanol to high value-added formic acid. Thirdly, following a 100 h chronopotentiometry (CP) test, the required potential demonstrates an increase of 4.9 % (MOR) and 8.1 % (HER), signifying the superior stability of Co30Ni60/CC compared to those reported in the literature. The exceptional performance of Co30Ni60/CC can be primarily attributed to that the leaf-like nanosheets structure not only exposes a plethora of active sites but also facilitates electrolyte diffusion, the monolithic structure prepared by electrodeposition enhances its stability, and the transfer of electrons from Co to Ni regulates its electronic structure, as corroborated by X-ray photoelectron spectroscopy (XPS) and density of states (DOS) analyses. Finally, at the same j, the voltage required by the Co30Ni60/CC||Co30Ni60/CC electrolytic cell, powered by an electrochemical workstation, is 198 mV lower than that required for alkaline water-splitting. Meanwhile, at higher j (100 mA cm−2), the electrolytic cell exhibits sustained and stable operation for 150 h, enabling high-efficiency hydrogen production and the synthesis of high value-added formic acid.

Systematization of the application of polymer composite materials in the design of bridge structures

Background. This study systematizes the principles of using polymer composite materials in bridge structure design, outlining the fundamental principles for calculating load-bearing structures of bridge spans featuring these materials. Aim. The goal is to enhance the strength and durability of bridge spans during construction and maintenance, while optimizing costs through the use of polymer composite materials. Materials and Methods. The research employs a modern approach to bridge structure design, utilizing mathematical statistics for experimental data analysis and numerical methods for calculating bridge structures using nonlinear deformation models of anisotropic materials. Results. Developed principles for designing bridge spans with polymer composite elements include methods for strengthening and reinforcing concrete bridge structures. These methods account for operational factors such as long-term constant and temporary loads, low and elevated temperatures, as well as methods for designing all-composite spans pedestrian and road bridges Conclusion. The principles of designing bridge spans with elements made of polymer composite materials have been introduced into the practice of transport construction in the Russian Federation. The technical and economic efficiency of using polymer composite materials in bridge structures of transport infrastructure has been confirmed.

A non-isothermal breakage-damage model for plastic-bonded granular materials incorporating temperature, pressure, and rate dependencies

Plastic-bonded granular materials (PBM) are widely used in industrial sectors, including building construction, abrasive applications, and defense applications such as plastic-bonded explosives. The mechanical behavior of PBM is highly nonlinear, irreversible, rate dependent, and temperature sensitive governed by various micromechanical attributions such as grain crushing and binder damage. This paper presents a thermodynamically consistent, microstructure-informed constitutive model to capture these characteristic behaviors of PBM. Key features of the model include a breakage internal variable to upscale the grain-scale information to the continuum level and to predict grain size evolution under mechanical loading. In addition, a damage internal state variable is introduced to account for the damage, deterioration, and debonding of the binder matrix upon loading. Temperature is taken as a fundamental external state variable to handle non-isothermal loading paths. The proposed model is able to capture with good accuracy several important aspects of the mechanical properties of PBM, such as pressure-dependent elasticity, pressure-dependent yield strength, brittle-to-ductile transition, temperature dependency, and rate dependency in the post-yielding regime. The model is validated against multiple published datasets obtained from confined and unconfined compression tests, covering various PBM compositions, confining pressures, temperatures, and strain rates.

Bayesian Inference for the Calibration of Progressive Damage Model of Dovetail Specimens from Laminated Composite Fan Blade

Abstract Composite fan blades are the preferred alternative for the fan stage of most advanced high bypass ratio turbofan engines. The ability of the dovetail to safely bear this load is one of the key points of the multi-level “test pyramid” approach of compliance demonstration for special airworthiness regulation. Debonding between adjacent layers is the main damage mode of laminated composite fan blades. However, there is difficulty in measuring the as manufactured interlaminar mechanical properties used in finite element models. In this study, tensile loading was applied to simulate the interacting centrifugal force and capture mixed mode damage evolution. Structural responses and material damages were calibrated with measured tensile loads through Bayesian inversion. Posterior probability distributions of maximum interface tractions and contact stresses were solved using Markov chain Monte Carlo sampler. Results indicated the two bilinear cohesive material models had a capacity of predicting empirical means of longitudinal reaction forces as that in test considering additional discrepancy term (0.035 kN and 0.96 kN respectively), while they made an significant impact on the prediction of tensile load history especially when two delamination cracks initiated and propagated. Interface elements provided a higher matching quality in predicting loading history and capturing damage mechanism in association with in-plane progressive damage analysis. This calibrated parameter set could be functioned as benchmark in numerically determining the ultimate tensile load of dovetail elements and reducing the necessary number of physical tests at elemental length level.

Development of Novel Ternary Alloy of CSiSn for Low-Cost Next Generation Photovoltaics

The growing need for highly efficient solar cells calls for significant advancements in the development of a new material system to meet the needs of low-cost and low-cost production. Current multi-junction solar cell alternatives are more costly to produce. This research showcases the development and analysis of a novel ternary material system, The CSiSn (CST) alloy, which shows potential for creating low-cost material with high absorption in of solar spectrum. In this work, the following aspects regarding the CST material are investigated: 1) Material modeling using density functional theory, 2) electronic band structure estimations, 3) low-temperature material growth technique via Plasma Enhanced Chemical Vapor Deposition (PE-CVD) system; 4) advanced material and optical characterizations of CST alloys.