Non-Destructive Evaluation of Ion-Implanted Semiconductor Thin Films Using Photothermal Deflections Spectroscopy

Materials and equipment which fail to achieve the design requirements or projected life due to undetected defects may require expensive repair or early replacement. Such defects may also be the cause of unsafe conditions or catastrophic unexpected failure, and will lead to loss of revenue due to plant shutdown. Non-Destructive Evaluation (NDE) / Non Destructive Testing (NDT) is used for the examination of materials and components without changing or destroying their usefulness. NDT can be applied to each stage of a system’s construction, to monitor the integrity of the system or structure throughout its life.

Non-destructive evaluation of photovoltaic materials and solar cells using Photoluminescence

Photoluminescence (PL) spectroscopy is an optical technique that has emerged successful in the field of semiconductor material and device characterization. This technique is quite a powerful one which gives idea about the defect levels in a material, the band gap of the material, composition as well as material quality. Over the recent years it has received an elevation as a mainstream characterization technique. This thesis is an attempt to characterize each individual layer used in a thin film solar cell with special focus on the electrical properties. This will be highly beneficial from the lab as well as industrial point of view because electrical measurements generally are contact mode measurements which tend to damage the surface. As far as a thin film solar cell is concerned, the constituent layers are the transparent conducting oxide (TCO), absorber layer, buffer layer and top electrode contact. Each layer has a specific role to play and the performance of a solar cell is decided and limited by the quality of each individual layer. Various aspects of PL spectroscopy have been employed for studying compound semiconductor thin films [deposited using chemical spray pyrolysis (CSP)] proposed for solar cell application. This thesis has been structured in to seven chapters

Non-destructive evaluation of carrier transport properties in CuInS2 and CuInSe2 thin films using photothermal deflection technique

Photothermal deflection technique (PTD) is a non-destructive tool for measuring the temperature distribution in and around a sample, due to various non-radiative decay processes occurring within the material. This tool was used to measure the carrier transport properties of CuInS2 and CuInSe2 thin films. Films with thickness <1 μm were prepared with different Cu/In ratios to vary the electrical properties. The surface recombination velocity was least for Cu-rich films (5×105 cm/s for CuInS2, 1×103 cm/s for CuInSe2), while stoichiometric films exhibited high mobility (0.6 cm2/V s for CuInS2, 32 cm2/V s for CuInSe2) and high minority carrier lifetime (0.35 μs for CuInS2, 12 μs for CuInSe2

A calibrated, non-invasive method for measuring the internal interface height field at high resolution in the rotating, two-layer annulus

We describe a remote sensing method for measuring the internal interface height field in a rotating, two-layer annulus laboratory experiment. The method is non-invasive, avoiding the possibility of an interaction between the flow and the measurement device. The height fields retrieved are accurate and highly resolved in both space and time. The technique is based on a flow visualization method developed by previous workers, and relies upon the optical rotation properties of the working liquids. The previous methods returned only qualitative interface maps, however. In the present study, a technique is developed for deriving quantitative maps by calibrating height against the colour fields registered by a camera which views the flow from above. We use a layer-wise torque balance analysis to determine the equilibrium interface height field analytically, in order to derive the calibration curves. With the current system, viewing an annulus of outer radius 125 mm and depth 250 mm from a distance of 2 m, the inferred height fields have horizontal, vertical and temporal resolutions of up to 0.2 mm, 1 mm and 0.04 s, respectively.

Software-based study of a non-sorting method for median calculation on a set of integer numbers

This paper presents a software-based study of a hardware-based non-sorting median calculation method on a set of integer numbers. The method divides the binary representation of each integer element in the set into bit slices in order to find the element located in the middle position. The method exhibits a linear complexity order and our analysis shows that the best performance in execution time is obtained when slices of 4-bit in size are used for 8-bit and 16-bit integers, in mostly any data set size. Results suggest that software implementation of bit slice method for median calculation outperforms sorting-based methods with increasing improvement for larger data set size. For data set sizes of N > 5, our simulations show an improvement of at least 40%.

Machine vision for the automatic classification of images acquired from Non-destructive tests

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

A non-invasive method for silencing gene transcription in honeybees maintained under natural conditions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A simple and non-destructive model for individual leaf area estimation in citrus

Introduction. Leaf area is often related to plant growth, development, physiology and yield. Many non-destructive models have been proposed for leaf area estimation of several plant genotypes, demonstrating that leaf length, leaf width and leaf area are closely correlated. Thus, the objective of our study was to develop a reliable model for leaf area estimation from linear measurements of leaf dimensions for citrus genotypes. Materials and methods. Leaves of citrus genotypes were harvested, and their dimensions (length, width and area) were measured. Values of leaf area were regressed against length, width, the square of length, the square of width and the product (length x width). The most accurate equations, either linear or second-order polynomial, were regressed again with a new data set; then the most reliable equation was defined. Results and discussion. The first analysis showed that the variables length, width and the square of length gave better results in second-order polynomial equations, while the linear equations were more suitable and accurate when the width and the product (length x width) were used. When these equations were regressed with the new data set, the coefficient of determination (R(2)) and the agreement index 'd' were higher for the one that used the variable product (length x width), while the Mean Absolute Percentage Error was lower. Conclusion. The product of the simple leaf dimensions (length x width) can provide a reliable and simple non-destructive model for leaf area estimation across citrus genotypes.

Non-destructive evaluation tool for monitoring and detection of structural damage by using neural network.

This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

Characterization of mineral contents on androgen deficient and chronic ethanol consuming rats by biochemistry and non-destructive techniques

Ethanol can compromise the body mineral composition and affect bone, and when associated to hypogonadism is considered an important risk factor for osteoporosis in man. The aim of this study was to investigate the effect of androgen deficient and chronic ethanol consuming on mineral contents by biochemistry and non-destructive techniques. Wistar rat (n=54) were divided in orchiectomy (ORQ) or SHAM-operated and subdivided by diet. They were daily fed with a Lieber DeCarli diet model for 8 weeks long. The controls groups were free-diet and pair-fed. Ca and P were analyzed by biochemistry test in the blood and by nX-ray fluorescence and FT-Raman on the femur area. Serum analysis revealed hypocalcaemia and hypeiphosphataemia in ethanol groups more than pair-fed and free-diet. In similarity, spectroscopy indicated a decrease in bone Ca content in ORQ groups, mainly for ethanol groups. Phosphorus content and Ca/P molar ratio, otherwise, doesn't diverge in all 6 groups. Ethanol consumption impaired Ca and P homeostasis in ORQ rat more than SHAM. The relationships among ethanol consume and androgen deficit support the hypothesis that ethanol affects the mineral-regulating hormones and may mediate some effects on bone. These findings demonstrate that ethanol seemed to interfere with the normal compensatory response to these Ca and P levels and is more significant M androgen deficiency rats.

Study of the thermal behavior of the transition phase of Co(II)-diclofenac compound by non-isothermal method

The Co(II)-diclofenac complex was evaluated by simultaneous thermogravimetry-differential thermal analysis (TG-DTA) and differential scanning calorimetry (DSC). The DTA curve profile shows one exothermic peak because of the transition phase of the compound between 170 and 180 A degrees C, which was confirmed by X-ray powder diffractometry. The transition phase behavior was studied by DSC curves at several heating rates of a sample mass between 1 and 10 mg in nitrogen atmosphere and in a crucible with and without a lid. Thus, the kinetic parameters were evaluated using an isoconversional non-linear fitting proposed by Capela and Ribeiro. The results show that the activation energy and pre-exponential factor for the transition phase is dependant on the different experimental conditions. Nevertheless, these results indicate that the kinetic compensation effect shows a relationship between them.

A Non-Destructive Testing Based on Electromagnetic Measurements and Neural Networks for the Inspection of Concrete Structures

This paper presents a new non-destructive testing (NDT) for reinforced concrete structures, in order to identify the components of their reinforcement. A time varying electromagnetic field is generated close to the structure by electromagnetic devices specially designed for this purpose. The presence of ferromagnetic materials (the steel bars of the reinforcement) immersed in the concrete disturbs the magnetic field at the surface of the structure. These field alterations are detected by sensors coils placed on the concrete surface. Variations in position and cross section (the size) of steel bars immersed in concrete originate slightly different values for the induced voltages at the coils.. The values for the induced voltages were obtained in laboratory tests, and multi-layer perceptron artificial neural networks with Levemberg-Marquardt training algorithm were used to identify the location and size of the bar. Preliminary results can be considered very good.

Classification of lumber of Eucalyptus using non-destructive tests

Classification and standardization of the sawn wood is a usual activity, developed by countries that come as great consumers of this material. Brazil does not practice the classification of sawn wood. This work had the main objective of evaluating the sensibility of most common non-destructive tests in the classification of dimension lumber from fast grown Eucalyptus plantation. Wood was obtained from genetic material cultivated at Minas Gerais State, Brazil. 296 beams of structural dimensions (6 cm × 12 cm × 280 cm) from 10 different clones of Eucalyptus were sampled. Beams were non-destructively (stress wave, ultrasound and transverse vibration) and destructively (static bending and compression parallel to grain) tested. Non-destructive results showed sensibility in the classification of structural dimension lumber, being possible to establish wave velocity intervals that attend to the main strength classes reported by Wooden Structures Brazilian Code.

Sparse arrays and image compounding techniques for non-destructive testing using guided acoustic waves

Piezoelectric array transducers applications are becoming usual in the ultrasonic non-destructive testing area. However, the number of elements can increase the system complexity, due to the necessity of multichannel circuitry and to the large amount of data to be processed. Synthetic aperture techniques, where one or few transmission and reception channels are necessary, and the data are post-processed, can be used to reduce the system complexity. Another possibility is to use sparse arrays instead of a full-populated array. In sparse arrays, there is a smaller number of elements and the interelement spacing is larger than half wavelength. In this work, results of ultrasonic inspection of an aluminum plate with artificial defects using guided acoustic waves and sparse arrays are presented. Synthetic aperture techniques are used to obtain a set of images that are then processed with an image compounding technique, which was previously evaluated only with full-populated arrays, in order to increase the resolution and contrast of the images. The results with sparse arrays are equivalent to the ones obtained with full-populated arrays in terms of resolution. Although there is an 8 dB contrast reduction when using sparse arrays, defect detection is preserved and there is the advantage of a reduction in the number of transducer elements and data volume. © 2013 Brazilian Society for Automatics - SBA.