The first part of this two-part review focused on the fundamental and diagnostics aspects of laser-induced plasmas, only touching briefly upon concepts such as sensitivity and detection limits and largely omitting any discussion of the vast panorama of the practical applications of the technique. Clearly a true LIBS community has emerged, which promises to quicken the pace of LIBS developments, applications, and implementations. With this second part, a more applied flavor is taken, and its intended goal is summarizing the current state-of-the-art of analytical LIBS, providing a contemporary snapshot of LIBS applications, and highlighting new directions in laser-induced breakdown spectroscopy, such as novel approaches, instrumental developments, and advanced use of chemometric tools. More specifically, we discuss instrumental and analytical approaches (e.g., double- and multi-pulse LIBS to improve the sensitivity), calibration-free approaches, hyphenated approaches in which techniques such as Raman and fluorescence are coupled with LIBS to increase sensitivity and information power, resonantly enhanced LIBS approaches, signal processing and optimization (e.g., signal-to-noise analysis), and finally applications. An attempt is made to provide an updated view of the role played by LIBS in the various fields, with emphasis on applications considered to be unique. We finally try to assess where LIBS is going as an analytical field, where in our opinion it should go, and what should still be done for consolidating the technique as a mature method of chemical analysis.

https://journals.sagepub.com/doi/pdf/10.1366/11-06574

Laser-induced breakdown spectroscopy (LIBS), part II: review of instrumental and methodological approaches to material analysis and applications to different fields.

Polymer based MEMS and microfluidic devices have the advantages of mechanical flexibility, lower fabrication cost and faster processing over silicon based ones. Also, many polymer materials are considered biocompatible and can be used in biological applications. A valuable class of polymers for microfabricated devices is piezoelectric functional polymers. In addition to the normal advantages of polymers, piezoelectric polymers can be directly used as an active material in different transduction applications. This paper gives an overview of piezoelectric polymers based on their operating principle. This includes three main categories: bulk piezoelectric polymers, piezocomposites and voided charged polymers. State-of-the-art piezopolymers of each category are presented with a focus on fabrication techniques and material properties. A comparison between the different piezoelectric polymers and common inorganic piezoelectric materials (PZT, ZnO, AlN and PMN?PT) is also provided in terms of piezoelectric properties. The use of piezopolymers in different electromechanical devices is also presented. This includes tactile sensors, energy harvesters, acoustic transducers and inertial sensors.

https://iopscience.iop.org/article/10.1088/0964-1726/23/3/033001/pdf

A review of piezoelectric polymers as functional materials for electromechanical transducers

A review provided about non-destructive testing (NDT) methods for the evaluation of composites. The review considers the capabilities of most common methods in composite NDT applications such as Visual Testing (VT or VI), Ultrasonic Testing (UT), Thermography, Radiographic Testing (RT), Electromagnetic Testing (ET), Acoustic Emission (AE), and Shearography Testing with respect to advantages and disadvantages of these methods. Then, methods categorized based on their intrinsic characteristics and their applications.

https://cyberleninka.org/article/n/593997.pdf

A review of non-destructive testing methods of composite materials

Texture measurement approaches in fresh and processed foods — A review

Nanorods, nanowires, and nanotubes of ferroelectric perovskites have recently been studied with increasing intensity due to their potential use in non-volatile ferroelectric random access memory, nano-electromechanical systems, energy-harvesting devices, advanced sensors, and in photocatalysis. This Review summarizes the current status of these 1D nanostructures and gives a critical overview of synthesis routes with emphasis on chemical methods. The ferroelectric and piezoelectric properties of the 1D nanostructures are discussed and possible applications are highlighted. Finally, prospects for future research within this field are outlined.

One-dimensional nanostructures of ferroelectric perovskites.

The dielectric properties of Korean short-grain rough rice, brown rice and barley with moisture content ranges of 11% to 27%, 11% to 18%, and 11 to 21%, wet basis, respectively, were characterized to develop a prototype grain moisture meter using microwave attenuation at 10.5 GHz and moisture density. A third-order polynomial regression model was proposed to describe the relationship between dielectric properties and moisture density. The prototype grain moisture meter consisted of a dielectric resonator type oscillator of 10.5 GHz, horn antenna, rectangular sample holder, load cell, temperature sensor, detector, and digital voltmeter. The calibration equation for measurement of grain moisture content was developed and estimated with Korean short-grain rough rice (12% to 26%). The coefficient of determination, standard error of prediction (SEP), and bias were 0.986, 0.52% moisture content and 0.07% moisture content, respectively.

Measurement of grain moisture content using microwave attenuation at 10.5 GHz and moisture density

Fabrication and comparison of PMN-PT single crystal, PZT and PZT-based 1-3 composite ultrasonic transducers for NDE applications.

Determination of apple firmness by nondestructive ultrasonic measurement

Carbon fiber reinforced polymers (CFRPs) are widely used for various structural materials because of their high stiffness and strength. Detecting damages in CFRP composites is important for structural safety. This study was conducted to detect impact damage in CFRP specimens using the millimeter-wave of 65–67 GHz. The impact damage was artificially produced by impact energies of 3.63 J, 8.89 J and 13.21 J, respectively. Since the CFRP composites are electrically anisotropic materials, reflection coefficients are affected by the angle between the electrical field vector direction of the electromagnetic wave and the carbon fiber direction in the CFRP surface. When this angle was 0°, reflection coefficients on the surface with and without damage were easily distinguished. Accordingly, imaging the CFRP specimens including the impact damage was conducted using changes of the reflection coefficient. In addition, in order to obtain better image, the edge detection image processing technique was applied to the original image, and a more natural image was obtained. The magnitude of impact energy producing damage could also be distinguished through the image.

Non-contact detection of impact damage in CFRP composites using millimeter-wave reflection and considering carbon fiber direction

An artificial neural (ANN) network was trained to recognize the stress intensity factor in the interval from microcrack to fracture from acoustic emission (AE) measurements on compact tension specimens. The specimens were made from structural steel SWS490B whilst the ANN had a 5-14-1 structure. The number of neurons in the input layers was five inputs of the AE parameters such as ring-down counts, rise time, energy, event duration and peak amplitude. The performance of the ANN was tested using a specific set of the AE data. The ANN is a promising tool for predicting the stress intensity factor of material using AE data.

Ki-Bok Kim

Papers

Measurement of grain moisture content using microwave attenuation at 10.5 GHz and moisture density

Fabrication and comparison of PMN-PT single crystal, PZT and PZT-based 1-3 composite ultrasonic transducers for NDE applications.

Determination of apple firmness by nondestructive ultrasonic measurement

Non-contact detection of impact damage in CFRP composites using millimeter-wave reflection and considering carbon fiber direction

Determining the stress intensity factor of a material with an artificial neural network from acoustic emission measurements