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Ultrasonic testing (UT) is one of the commonly used non-destructive testing (NDT) techniques for material evaluation and defect detection. The acquisition of UT data is largely performed automatically by using various robotic manipulators which can ensure the consistency of the recorded data. On the other hand, complete analysis of the acquired data is still performed manually by trained personnel. This makes the reliability of defect detection highly dependent on humans’ knowledge and experience. Most of the previous attempts for automated defect detection from UT data analyze individual A-scans. In such cases, valuable information present in the surrounding A-scans remains unused and limits the performance of such methods. The situation is better if a B-scan is used as an input, especially if the dataset is large enough to train a deep learning object detector. However, if each of the B-scans is analyzed individually, as it was done so far in the literature, there is still valuable information left in the surrounding B-scans that could be used to improve the precision. We showed that expanding the input layer of an existing method will not lead to an improvement and that a more complex approach is needed in order to effectively use information from neighboring B- scans. We propose two approaches based on high- dimensional feature maps merging. We showed that proposed models improve mean average precision (mAP) compared to the previous state-of-the-art model by 2% for input resolutions of 512×512 pixels, and 3.4% for input resolutions of 384×384 pixels.

The safety of nuclear power plants has always been one of the most important security issues in the industry in general. Numerous standards, techniques, and tools have been developed to deal specifically with the safety of nuclear power plants – one has specialised probes, robotized systems, electronics, and software. Although seen as a mature (or slowly evolving) industry, this notion about nuclear safety is a bit misleading – the area is developing in many promising new directions. Some recent global events will speed up this development even more. On the other hand, the industry is currently going through digital transformation, which brings networking of devices, equipment, computers, and humans. This fourth industrial revolution promises speed, reliability, and efficiencies not possible up until now. In the NDE sector, new production techniques and traditional manufacturing lines are getting to be lights-out operations (near-total automation). The same is most probably going to happen with the safety inspections and quality insurance. Robotics and automation are improving worker safety and reducing human error. The well-being of inspectors working in a hazardous environment is being taken care of. Most experts agree that the digitalization of NDE offers unprecedented opportunities to the world of inspection for infrastructure safety, inspector well-being, and even product design improvements. While the community tends to agree on the value proposition of digital transformation of NDE, it also recognizes the challenges associated with such a major shift in a well-established and regulated sector. The work presented in this paper shows a part of the project that aims to develop a modular ultrasound diagnostic NDE system (consisting of exchangeable transducers, electronics, and acquisition/analysis software algorithms), for applications in hazardous environments within nuclear power plants. The paper will show how the software part of this system can reach near-total automation by implementing various deep learning algorithms as its features and, then, testing those algorithms on laboratory samples, showing encouraging results and promises of online monitoring applications. Furthermore, future general prospects of this technology are discussed, and how this technology can affect the well-being of nuclear power plant inspectors and contribute to overall plant safety.

Ultrasonic testing (UT) is a commonly used approach for inspection of material and defect detection without causing harm to the inspected component. To improve the reliability of defect detection, the material is often scanned from various angles leading to an immense amount of data that needs to be analyzed. Some of the defects are only seen on B-scans taken from a particular angle so discarding some of the data would increase the risk of not detecting all of the defects. Recently there has been significant progress in the development of methods for automated defect analysis from the UT data. Using such methods the inspection can be performed quicker, but it is still necessary to inspect all of the angles to detect defects. In this work, we test a novel approach for accelerating the analysis by merging the images from various angles. To reduce the information loss during the process of merging, we develop a new model with a weighting module that dynamically determines the importance of each of the scanning angles. Using the proposed module, the loss of information is minimal, so the precision of the detection model is comparable to the model tested on each of the images separately. Using the merged images input, the analysis can be accelerated by almost 15 times.

Non-destructive ultrasonic analysis of materials is a method for assessing the integrity of the inspected components. It is commonly used in monitoring critical parts of the power plants, in aeronautics, oil and gas, and the automotive industry. Since most ultrasonic inspections rely on expert's previous experience they must constantly practice on new, unseen data. Acquiring enough data for training human experts on non- destructive ultrasonic scan analysis can be an expensive and time-consuming task. The only possibility to get new data for practicing is to implant synthetic defects in real metal blocks. Artificial defects are made by temperature strain, electrical discharge, and physical damage. All of those methods are very complicated and expensive to perform. Also metal blocks have to be taken from the components of the power plants to have the same structure and be realistic. In this work, some attempts have been made to generate 3D ultrasonic scans using computer vision and deep learning methods.

The analysis of the data in non-destructive ultrasonic testing of materials is a very time- intensive task. To alleviate the aforementioned strain on the human expert inspectors, a plethora of assisted analysis methods based on deep learning have been developed recently. However, most of these methods are based on the automated detection of flaws in A-scans and B-scans and therefore we propose a method based on the detection of flaws in C-scans that can reduce the complexity of manual detection of flaws in B- scans. The proposed method classifies each row of the C-scan based on whether it contains any flaws or not. Afterward, the positively classified rows are forwarded for further automated (and manual) inspection. The results show that the developed method significantly reduces the number of B-scans that have to be further analyzed.

Non-destructive testing is a group of methods for evaluating the integrity of components. Among them, ultrasonic inspection stands out due to its ability to visualize both shallow and deep sections of the material in the search for flaws. Testing of the critical components can be a tiring and time-consuming task. Therefore, human experts in analyzing inspection data could use a hand in discarding anomaly-free data and reviewing only suspicious data. Using such a tool, errors would be less common, inspection times would shorten and non-destructive testing would be more efficient. In this work, we evaluate multiple state-of-the- art deep-learning anomaly detection methods on the ultrasonic non-destructive testing dataset. We achieved an average performance of almost 82% of ROC AUC. We discuss in detail the advantages and disadvantages of the presented methods.

Analysis of ultrasonic testing (UT) data is a time-consuming assignment. In order to make it less demanding we propose an approach based on a variational autoencoder (VAE) to filter out the scans without anomalies/defects and in doing so, partially automate the procedure. The implemented approach uses an additional encoder network allowing to encode the reconstructed images. The differences in encodings of input and reconstructed images have shown to be good indicators of anomalous data. Anomaly detection results surpass the results of other VAE based anomaly criteria.

Ultrasonic imaging is widely used for non-destructive evaluation in various industry applications. Early detection of defects in materials is the key to keeping the integrity of inspected structures. Currently, there have been some attempts to develop models for automated defect detection on ultrasonic data. To push the performance of these models even further more data is needed to train deep convolutional neural networks. A lot of data is also needed for training human experts. However, gathering a sufficient amount of data for training is a challenge due to the rare occurrence of defects in real inspection scenarios. This is why inspection results heavily depend on the inspector’s previous experience. To overcome these challenges, we propose the use of Generative Adversarial Networks for generating realistic ultrasonic images. To the best of our knowledge, this work is the first one to show that a Generative Adversarial Network is able to generate images indistinguishable from real ultrasonic images. The most thorough statistical quality analysis to date of generated ultrasonic images has been conducted with the participation of human expert inspectors. The experimental results show that images generated using our Generative Adversarial Network provide the highest quality images compared to other published methods.

Nondestructive evaluation (NDE) is a set of techniques used for material inspection and defect detection without causing damage to the inspected component. One of the commonly used nondestructive techniques is called ultrasonic inspection. The acquisition of ultrasonic data was mostly automated in recent years, but the analysis of the collected data is still performed manually. This process is thus very expensive, inconsistent, and prone to human errors. An automated system would significantly increase the efficiency of analysis, but the methods presented so far fail to generalize well on new cases and are not used in real-life inspection. Many of the similar data analysis problems were recently tackled by deep learning methods. This approach outperforms classical methods but requires lots of training data, which is difficult to obtain in the NDE domain. In this work, we train a deep learning architecture EfficientDet to automatically detect defects from ultrasonic images. We showed how some of the hyperparameters can be tweaked in order to improve the detection of defects with extreme aspect ratios that are common in ultrasonic images. The proposed object detector was trained on the largest dataset of ultrasonic images that was so far seen in the literature. In order to collect the dataset, six steel blocks containing 68 defects were scanned with a phased-array probe. More than 4000 VC-B-scans were acquired and used for training and evaluation of EfficientDet. The proposed model achieved 89.6% of mean average precision (mAP) during fivefold cross validation, which is a significant improvement compared to some similar methods that were previously used for this task. A detailed performance overview for each of the folds revealed that EfficientDet-D0 successfully detects all of the defects present in the inspected material.

Non-destructive ultrasonic testing (UT) of materials is used for monitoring critical parts in power plants, aeronautics, oil and gas industry, and space industry. Due to a vast amount of time needed for a human expert to perform inspection it is practical for a computer to take over that task. Some attempts have been made to produce algorithms for automatic UT scan inspection mainly using older, non-flexible analysis methods. In this paper, two deep learning based methods for flaw detection are presented, YOLO and SSD convolutional neural networks. The methods' performance was tested on a dataset that was acquired by scanning metal blocks containing different types of defects. YOLO achieved average precision (AP) of 89.7% while SSD achieved AP of 84.5 %.

This work presents an experimental method for obtaining the best excitation pulse type and width for optimal driving of an industrial non-destructive testing (NDT) ultrasound transducer by using its electrical impedance parameters as input. Within the optimization method, a classic low-voltage frequency sweeping signal and two different types of high-voltage impulse excitation signals (unipolar and bipolar), with different pulse widths, are used for the electromechanical characterization of the transducer. The optimization of the excitation signal is verified by measuring the voltage, current and electrical power of the excitation and received signals obtained by ultrasound pulse reflection from two cracks (2 mm and 3 mm) in a stainless-steel block. Additionally, the influence of the output electrical impedance of the power amplifier on the optimal transfer of electrical power from the amplifier to the loading (the NDT transducer on the block) and vice versa is also discussed in this work. The optimum working point for the ultrasound NDT transducer, regarding the impulse excitation type and its pulse width, is a bipolar impulse excitation with the width and amplitude calculated from maximum values of the measured voltage, electric current and power generated in the transducer receive mode by the reflected ultrasound signals.

Electromechanical and acoustical characterization of PZT piezoceramic elements and high-power ultrasound transducers has been done around resonance frequencies in order to determine the features of the models that describe the considered devices, both as equivalent circuits and as nonlinear oscillators. Several measurement methods have been compared, including the frequency-sweeping method with constant excitation voltage, the magnitude-sweeping method at a constant excitation frequency and the method that uses impulse excitation. The parameters that describe the losses in a coupled nonlinear electro-mechanical-acoustical system greatly depend on the type of excitation and its level. A novel algorithm is tested, designed for tracking the changes of the series resonance frequency and impedance magnitude and phase with the excitation level. It enables a more precise determination of the resonance frequency and impedance changes over different levels of excitation, which is especially important in high-power resonant applications. The characterization based on frequency sweeping at different excitation levels is influenced by changing electrical parameters (current, voltage, power) due to different complex loading of the excitation amplifier and the changes of thermodynamic conditions. The characterization of transducers in loaded condition through frequency sweeping at higher signal levels gives no results when cavitation in front of the horn appears, because the impedance magnitude changes at higher excitation voltages. Using the tracking algorithm, the impedance magnitude at resonance frequency has been determined in a range of different excitation levels up to 35 V RMS . Before the onset of nonlinear effects such as cavitation or acoustic streaming, the impedance magnitude increases due to viscosity effects.

Determination of electromechanical piezoceramic material parameters is usually done by fitting the measured input electrical impedance of the piezoceramic sample to the theoretical modelling equation for the input electrical impedance of the unloaded free piezoceramic resonator. The input electrical impedance of the sample is usually measured by using low voltage or current magnitude frequency sweeping signals. In this work, the complex material parameters of piezoceramic samples are determined in the real operating conditions by using the high voltage short impulse excitation signals. The input electrical impedance determined in the impulse mode around thickness extensional vibration mode (TE) and calculated piezoceramic parameters (clamped dielectric permittivity, electromechanical coupling factor, elastic stiffness and piezoelectric constant) are compared to the results obtained by using the low voltage magnitude frequency sweeping signals. When impulse excitation is used, the series resonance frequency is decreased and the input electrical impedance magnitude at series resonance is increased, which means that overall losses included in the piezoceramic parameters are increased. The complex material parameters obtained from the input electrical impedances determined by using the low voltage magnitude sweeping signal and high level short impulse signals are included in the KLM theoretical model describing the piezoceramic sample behaviour around TE mode. Better agreement between measured and theoretically determined current magnitude response around TE mode has been obtained, in the KLM model, when piezoceramic parameters determined by using the impulse signal excitations are included in the modelling. The physical reason for increase of the losses in piezoceramic material could lie in the fact that the ferroelectric domains in the piezoceramic respond harder on very short impulse excitation signals than on continuous frequency sweeping signals which are usually used in determination of piezoelectric material parameters.

Electromechanical characterization of piezoceramic bulk elements around resonance is usually done with low-level continuous excitation signals at room temperature, but in real applications such elements are driven with different types of electrical signals, usually at higher levels and at different ambient temperatures. Both homemade and commercial soft and hard PZT piezoceramic elements were characterized using the established characterization methods that include the measurements of electrical admittance and surface displacement of the piezoceramic elements around the series resonance frequencies of two modes of vibration (radial and thickness extensional). The measurements included fast frequency sweeps at constant voltage excitation levels, burst measurements, at different temperatures and at different levels of excitation. A novel method for electromechanical characterization of piezoceramic elements that utilizes the resonance frequency tracking at different excitation levels (electric fields up to 5 kV/m, currents up to 1.3 A at resonance) and temperature conditions (up to 150 °C) has been proposed. The main idea is to keep the investigated element in resonance as the excitation level changes by constant tracking of its resonance frequency. The electromechanical parameters of the considered elements change mostly due to the nonlinear effects and the changes due to different thermodynamic conditions can be neglected when fast algorithm is applied. The decrease of the input electrical admittance magnitude is more expressed than the change of the resonance frequency when algorithm is applied.

High temperature pipe cracks are the root of a steam power failure in the EU typically every 4 years, resulting in loss of human life, serious accidents and massive financial losses. According to IAEA’s Reference Technology Database, such an event on a nuclear power plant has an average cost of €120 million, including outage costs, emergency repair costs, insurance and legal costs. Since only one growing crack is needed to cause a major failure, they have to be inspected and monitored thoroughly. Breakdowns at extreme conditions (e.g. 580°C, 400 bar) are a result of two major weld failure modes: a) creep cracks near pipe welds; b) fatigue cracks on pipe welds. Current maintenance practice is to proceed with repairs on a detected crack according to its severity. For cost reasons, cracks that are not judged as severe enough will not be repaired. Crack severity judgement is based on its probability to cause a failure and this probability is derived taking into account the crack size and operational lifetime. More variables such as operating temperature and vibrations may rarely be found in other studies. Recent data from fracture mechanics statistical studies shows this connection between the size of a crack on a nuclear power plant pipe and its probability to lead to a failure. To deal with the above problems two Structural Health Monitoring (SHM) systems have been developed and they are presented in this work. These systems are able to achieve continuous operation for an extended time period at operating temperatures of nuclear power plants. The developed systems employ novel phased array (PA) ultrasonic and ultrasound guided wave (UGW) probes able to withstand and continuously operate even up to 580 °C. The systems are designed to be permanently mounted on superheated steam pipes, at locations of known defects and to continuously monitor their size. However, this supposes that defects will have already been detected by a traditional method during an outage. The PA transducers are placed according to the Time-of- Flight Diffraction (TOFD) technique’s topology, thus creating a novel configuration, while the UGW transducers are placed on a stainless steel ring in a circular array configuration. These configurations can enable continuous tracking of cracks growth with high accuracy, enabling maintenance crews to estimate the severity directly and not through statistics.

The orientation dependence of the longitudinal piezoelectric coefficient, d(33)(*), is investigated as a function of temperature in BaTiO3 and PbTiO3 crystals using the Landau-Ginsburg-Devonshire theory. We show that a presence of the ferroelectric-ferroelectric phase transitions in BaTiO3 leads to enhanced d(33)(*) along nonpolar directions. The reason for this is that in the vicinity of a phase transition temperature at which a polarization vector changes its direction (tetragonal-orthorhombic/monoclinic, orthorhombic/monoclinic-rhombohedral), the shear piezoelectric coefficients become high. It is shown for all ferroelectric phases of BaTiO3 that the shear stress deforms the crystal cell and changes the polarization direction in a similar way as the corresponding temperature-induced phase transition. The influence of the piezoelectric shear effect on the anisotropy of d(33)(*) is particularly pronounced in the orthorhombic/monoclinic phase where the piezoelectric shear coefficients are determined by the presence of both the high-temperature tetragonal and the low-temperature rhombohedral phases. In PbTiO3, which does not exhibit ferroelectric-ferroelectric phase transitions, the shear piezoelectric effect is weak and d(33)(*) has its maximum along the polar axis at all temperatures. These results can be generalized to include phase transitions induced by electric-field and composition variations and are valid for all perovskite materials, including complex relaxor-ferroelectric perovskites that have recently attracted attention for their exceptionally large piezoelectric properties. (C) 2003 American Institute of Physics.

Using recently published experimental data we calculated the piezoelectric response of rhombohedral 0.67Pb(Mg1/3Nb2/3)O-3-0.33PbTiO(3) monodomain single crystals along arbitrary directions. The calculations indicate that the value of the longitudinal piezoelectric coefficient along the [001] axis of the pseudocubic system ([111] axis of the rhombohedral system) of a monodomain crystal is close to the value determined experimentally along the same direction of a multidomain crystal with a so-called "engineered domain state." The results thus show that the large piezoelectric response in this material is dominated by intrinsic crystal lattice effects and that the multidomain state has a relatively minor effect (1900 pC/N for certain directions of the monodomain crystal. (C) 2003 American Institute of Physics.

The main task of every nuclear power plant owner is to establish the balance in taking precautions such as monitoring, inspection and corrective actions, with the aim of retaining the steam generator integrity. The steam generator integrity assessment presents the key factor in achieving the mentioned aim. It is necessary to conduct a wide range of researches for a quality of steam generator integrity assessment. One of the key elements as well as starting point for steam generator structural integrity assessment is establishing burst pressure relationship for each degradation mechanism orientation, type and their location on steam generator tubes. This paper presents the role of burst pressure relationship within VVER steam generator structural integrity assessment and its determination. In addition to this, the results of researches for the axially oriented flaws on the free span will be presented, with the aim of establishing burst pressure relationship., Osnovna zadaća svakog vlasnika elektrane je uspostaviti ravnotežu u poduzimanju prventivnih mjera kao što su praćenje, ispitivanje te korektivne akcije u cilju očuvanja integriteta cijevi parogeneratora. Procjena integriteta cijevi parogeneratora predstavlja ključni čimbenik u ostvarenju navedenog cilja. Potrebno je provesti široki spektar istraživanja za kvalitetnu procjenu integriteta cijevi parogeneratora. Jedan od ključnih elemenata, ali i polazišna točka u procjeni strukturnog integriteta cijevi parogeneratora je uspostavljanje relacijske ovisnosti tlaka pucanja i strukturne varijable za svaki oblik, vrstu i mjesto pojavljivanja degradacijskog procesa na cijevima parogeneratora. Ovaj članku opisuje ulogu ovisnosti tlaka pucanja i strukturne varijable u procjeni strukturnog integriteta cijevi parogeneratora VVER-tipa kao i njeno određivanje. Prikazat će se i rezultati istraživanja za slučaj aksijalno orijentiranih oštećenja na slobodnoj duljini cijevi s ciljem uspostavljanja relacijske ovisnosti tlaka pucanja i strukturne varijable.

The electrical excitation dependence of working parameters of a normal beam non-destructive evaluation ultrasound transducer has been investigated. Noteworthy differences between the transducer input electrical impedance and acoustic properties at low excitation voltages (~1V), most often used in electromechanical characterizations by performing frequency sweeps, and at high excitation voltages (~250V), generally used to drive ultrasound transducers in non-destructive evaluation applications, were emphasized. For the purpose of this work, a circular normal beam ultrasound transducer of centre frequency 2 MHz was constructed by using a PZT piezoelectric disk, epoxy- based acoustically passive front matching and backing layers, an electrical impedance matching element, housing and coaxial cable. The transducer was characterized around the thickness extensional vibration mode both by using low and high voltage electrical excitation signals. The characterization of the electromechanical properties was conducted at several different stages of the transducer construction and for several excitation signal waveforms and levels., Svojstva i ponašanje radnih parametara ultrazvučnog pretvarača (izlaznog kuta ultrazvučnog snopa 0°) za kontrolu bez razaranja ispitani su u ovisnosti o vrsti električne pobude. Pokazane su zamjetne razlike između ulazne električne impedancije i akustičnih svojstava pretvarača pri malim električnim pobudnim amplitudama (~1V), koje se u pravilu koriste u elektromehaničkim karakterizacijama mjerenjem frekventne ovisnosti impedancije pretvarača, te pri visokim pobudnim nivoima (~250V), u pravilu korištenih za radnu pobudu ultrazvučnih pretvarača pri obavljanju kontrole bez razaranja. Za ovaj rad konstruiran je osnosimetrični ultrazvučni pretvarač izlaznog kuta ultrazvučnog snopa od 0°, središnje frekvencije 2MHz; u izradi su korišteni akustički aktivan piezoelektrični PZT (olovo-cirkonij-titanat) keramički disk, akustički pasivni prednji i prigušni slojevi na bazi epoksidnih smola, elektronički element za prilagodbu električne impedancije, kućište od nehrđajućeg čelika i koaksijalni kabel. Svojstva pretvarača karakterizirana su oko longitudinalnog ekstenzijskog titrajnog moda korištenjem električnih pobudnih signala i malih i velikih amplituda. Ispitivanje elektromehaničkih svojstava pretvarača napravljeno je pri nekoliko različitih stadija njegove konstrukcije i za nekoliko valnih oblika pobudnih električnih valnih oblika.

This paper discusses the mechanisms that can contribute to the enhanced longitudinal piezoelectric effect along nonpolar directions in perovskite crystals, such as BaTiO3, PbTiO3, KNbO3, Pb(Mg1/3Nb2/3)O-3-PbTiO3 and Pb(Zn1/2Nb2/3)O-3-PbTiO3. Piezoelectric anisotropy is discussed in relation to temperature induced phase transitions, compositional variation in solid solutions with morphotropic phase boundaries, applied electric fields, the domain wall structure and domain wall displacement. (c) 2006 Springer Science + Business Media, Inc.

The question of the origin of the piezoelectric properties enhancement in perovskite ferroelectrics is approached by analyzing the Gibbs free energy of tetragonal $\mathrm{Ba}\mathrm{Ti}{\mathrm{O}}_{3}$, $\mathrm{Pb}\mathrm{Ti}{\mathrm{O}}_{3}$, and $\mathrm{Pb}(\mathrm{Zr},\mathrm{Ti}){\mathrm{O}}_{3}$ in the framework of the Landau-Ginzburg-Devonshire theory. The flattening of the Gibbs free-energy profile appears as a fundamental thermodynamic process behind the piezoelectric enhancement. The generality of the approach is demonstrated by examining the free-energy flattening and piezoelectric enhancement as a function of composition, temperature, electric field, and mechanical stress. It is shown that the anisotropy of the free-energy flattening is the origin of the anisotropic enhancement of the piezoelectric response, which can occur either by polarization rotation or by polarization contraction. Giant enhancement of the longitudinal piezoelectric response $({d}_{33}\ensuremath{\propto}{10}^{3}\phantom{\rule{0.3em}{0ex}}\mathrm{pC}∕\mathrm{N})$ is predicted in $\mathrm{Pb}\mathrm{Ti}{\mathrm{O}}_{3}$ under uniaxial compression.

The influence of the uniaxial bias stress on the piezoelectric properties of tetragonal BaTiO3 and PbTiO3 monodomain crystals is modeled in the framework of the phenomenological Landau-Ginzburg-Devonshire theory. It is shown that tensile and compressive stresses, both applied along the spontaneous polarization direction, reduce and enhance the piezoelectric response, respectively. The enhancement effect is due to the flattening of the free-energy profile and the corresponding dielectric softening of crystals, caused by the compressive stress. In BaTiO3 crystals, at temperatures close to the tetragonal-orthorhombic phase transition temperature, the free-energy profile flattening and dielectric softening are the largest along axes perpendicular to the polarization direction, facilitating thus the polarization rotation away from the [001](c) polar axis. The resulting enhancement of the shear piezoelectric coefficient is directly responsible for the increase of the longitudinal piezoelectric coefficient along the [111](c) axis. At temperatures deep within the tetragonal phase in BaTiO3, and over the whole ferroelectric region of PbTiO3, the flattening of the free-energy profile and the dielectric softening by compressive stress are the strongest along the polar axis. The resulting enhancement of the longitudinal piezoelectric coefficient is thus the largest along the polar [001](c) direction. These results, which can be applied to other perovskite crystals, have broad implications.

The orientation dependence of the longitudinal piezoelectric coefficient is investigated as a function of temperature in BaTiO/sub 3/ and PbTiO/sub 3/ crystals using Landau-Ginsburg-Devonshire theory. We show that a presence of the ferroelectric - ferroelectric phase transitions in BaTiO/sub 3/ leads to an enhanced piezoelectric longitudinal response along nonpolar directions. The reason for this is the abrupt increase of the shear piezoelectric coefficients in the vicinity of a FE - FE phase transition temperature. In PbTiO/sub 3/, which does not exhibit such phase transitions, the shear piezoelectric effect is weak and the longitudinal piezoelectric coefficient has its maximum along the polar axis at all temperatures. These results can be generalized to include phase transitions induced by electric-field and composition variation and are valid for all perovskite materials. Further, using Landau-Ginzburg-Devonshire theory and tetragonal BaTiO/sub 3/ as an example, we demonstrate that a strong electric bias fields applied anti-parallel to the spontaneous polarization may lead to a large enhancement of piezoelectric properties in monodomain perovskite crystals. The enhancement is due to the field-induced dielectric softening of the crystal.

We have measured the thermal conductivity of (TaSe4)2I in the chain and perpendicular to chain directions. A strong anisotropy is observed in the temperature range of 80–320 K. The detailed analysis of the temperature dependence in both of directions confirms that in addition to the lattice and free carriers there are very anisotropic contributions to the thermal conductivity coming from the phase fluctuations.

Piezoelectric properties of ferroelectric crystals can be greatly enhanced in the proximity of electric and mechanical coercive fields. While the thermodynamic origin of the enhancement in both cases can be traced to the flattening of a free energy profile, we show using the Landau–Ginzburg–Devonshire theory that there is a qualitative difference in how the proximity of 90° and 180° polarization switching affects the piezoelectric response and its anisotropy. Taking as an example PbTiO3 monodomain single crystals biased by near-coercive electric and stress fields applied along the polar axis, it is shown that the antiparallel electric field softens the material along the polar direction while the compressive stress softens the crystal along nonpolar directions. In the former cases the piezoelectric enhancement is dominated by the polarization contraction along the polar axis while in the latter case it is dominated by the polarization rotation away from the polar axis. An analogy is made between the effec...

Note: Damjanovic, D Swiss Fed Inst Technol, EPFL, Dept Mat, Ceram Lab, CH-1015 Lausanne, Switzerland Swiss Fed Inst Technol, EPFL, Dept Mat, Ceram Lab, CH-1015 Lausanne, Switzerland721TJTimes Cited:6Cited References Count:3 Reference LC-ARTICLE-2003-009View record in Web of Science Record created on 2006-08-21, modified on 2017-05-10

The importance of a high shear coefficient d15 (or d24) to the piezoelectric properties of domain-engineered and polycrystalline ferroelectrics is discussed. The extent of polarization rotation, as a mechanism of piezoelectric response, is directly correlated to the shear coefficient. The terms "rotator" and "extender" are introduced to distinguish the contrasting behaviors of crystals such as 4mm BaTiO3 and PbTiO3. In "rotator" ferroelectrics, where d15 is high relative to the longitudinal coefficient d33, polarization rotation is the dominant mechanism of piezoelectric response; the maximum longitudinal piezoelectric response is found away from the polar axis. In "extender" ferroelectrics, d15 is low and the collinear effect dominates; the maximum piezoelectric response is found along the polar axis. A variety of 3m, mm2 and 4mm ferroelectrics, with various crystal structures based on oxygen octahedra, are classified in this way. It is shown that the largest piezoelectric anisotropies d15/d33 are always found in 3m crystals; this is a result of the intrinsic electrostrictive anisotropy of the constituent oxygen octahedra. Finally, for a given symmetry, the piezoelectric anisotropy increases close to ferroelectric-ferroelectric phase transitions; this includes morphotropic phase boundaries and temperature induced polymorphic transitions., Comment: accepted in J. Appl. Phys

Using Landau-Ginzburg-Devonshire theory and tetragonal BaTiO3 as an example, this letter demonstrates that strong electric bias fields applied antiparallel to spontaneous polarization may lead to a large enhancement of piezoelectric properties in monodomain perovskite crystals with multiple phase transitions. At temperatures close to tetragonal-orthorhombic phase transition, the largest enhancement is approximately along the [111] axis. The enhancement is due to the field induced dielectric softening of the crystal. (C) 2004 American Institute of Physics.

Today, high crystal quality in sufficient size with high crystal growth yield appears to be a key point for a wide dissemination and use in ferroelectrics applications. So, this paper is related to the growth of PZN-PT solid solution compound like (1-x)(PbZn/sub 1/3/Nb/sub 2/3/O/sub 3/)-xPbTiO/sub 3/ and PMN-PT compound like (1-y)(PbMg/sub 1/3/Nb/sub 2/3/O/sub 3/)-yPbTiO/sub 3/. For these two relaxor ferroelectric single crystals promising properties are obtained near the Morphotropic Phase Boundary (MPB) transition which occurred at values closed to x=0.09 for PZN-PT and y=0.34 for PMN-PT. The complex unit cell phase transition combined with an adequate applied electric field, oriented in the pseudo /sub c/ direction; confer to these single crystals some interesting piezoelectric properties. We present some crystal growth results obtained by the Vertical Gradient Freeze-Solution Growth method (VGF-SG) for PZN-PT and by a pseudo Kyropoulos method developed for PMN-PT. The obtained single crystals, up to 120 g for PZN-PT and 160 g for PMN-PT are then analysed in term of composition and structure. Both PMN-PT and PZN-PT perovskite crystals are rhombohedral (@RT), they show a good global homogeneity. Samples demonstrate ferroelectric behaviour, and after polarisation process, dielectric constants up to 48000 near the Curie temperature (Tc /spl sim/174/spl deg/C @ 1kHz) are obtained for PZN-PT and respectively 74000 for PMN-PT (Tc /spl sim/ 142/spl deg/C @ 100 Hz). The piezoelectric coefficient d/sub 33/ gives values up to /spl sim/2200 pC/N (@RT 9 kV/cm) for PZN-PT and 1700 pC/N(@RT) for PMN-PT. A value up to 94% is measured for the electromechanical coupling coefficient k/sub 33/.

While in the paralectric phase of ferroelectrics, and in centrosymmetric materials in general, the dielectric tunability is symmetrical for positive and negative electric bias fields, in noncentrosymmetric materials this is not the case. By using the thermodynamic theory, and tetragonal phase of monodomain single-crystal perovskites BaTiO3 and Pb(Zr,Ti)O-3, as examples, we show that the theoretical tunability region of ferroelectrics may, in principle, be considerably broadened and tunability greatly enhanced by applying electric-bias field antiparallel to polarization. Available experimental data are in qualitative agreement with the theoretical predictions. (c) 2006 American Institute of Physics.