Acoustic Microscopy Imaging Research Articles

3-D Visualization of Atlantic salmon skin through Ultrasound and Photoacoustic Microscopy.

Three-dimensional photoacoustic imaging (PAM) has emerged as a promising technique for non-invasive label-free visualization and characterization of biological tissues with high spatial resolution and functional contrast. The application of PAM and ultrasound as a microscopy technique of study for Atlantic salmon skin is presented here. A custom ultrasound and photoacoustic experimental setup was used for conducting this experiment with a sample preparation method where the salmon skin is embedded in agarose and lifted from the bottom of the petridish. The results of C-scan, B-scan, and overlayed images of ultrasound and photoacoustic are presented. The results are then analyzed for understanding the pigment map and its relation to salmon behavior to external stimuli. The photoacoustic images are compared with the optical images and analyzed further. A custom colormap and alpha map is designed and the matrices responsible for PAM and ultrasound are inserted together to overlay the ultrasound image and PAM image on top of each other. In this study, we propose an approach that combines scanning acoustic microscopy (SAM) images with PAM images for providing a comprehensive understanding of the salmon skin tissue. Overlaying acoustic and photoacoustic images enabled unique visualization of tissue morphology, with respect to identification of structural features in the context of their pigment distribution.

Image segmentation on void regional formation in the flip-chip underfilling process by comparing YOLO and mask RCNN

Purpose This paper aims to identify a suitable convolutional neural network (CNN) model to analyse where void(s) are formed in asymmetrical flip-chips with large amounts of the ball-grid array (BGA) during underfilling. Design/methodology/approach A set of void(s)-filled through-scan acoustic microscope (TSAM) images of BGA underfill is collected, labelled and used to train two CNN models (You Look Only Once version 5 (YOLOv5) and Mask RCNN). Otsu's thresholding method is used to calculate the void percentage, and the model's performance in generating the results with its accuracy relative to real-scale images is evaluated. Findings All discoveries were authenticated concerning previous studies on CNN model development to encapsulate the shape of the void detected combined with calculating the percentage. The Mask RCNN is the most suitable model to perform the image segmentation analysis, and it closely matches the void presence in the TSAM image samples up to an accuracy of 94.25% of the entire void region. The model's overall accuracy of RCNN is 96.40%, and it can display the void percentage by 2.65 s on average, faster than the manual checking process by 96.50%. Practical implications The study enabled manufacturers to produce a feasible, automated means to improve their flip-chip underfilling production quality control. Leveraging an optimised CNN model enables an expedited manufacturing process that will reduce lead costs. Originality/value BGA void formation in a flip-chip underfilling process can be captured quantitatively with advanced image segmentation.

The respective and dependent effects of scattering and bone matrix absorption on ultrasound attenuation in cortical bone

Cortical bone is characterized by a dense solid matrix permeated by fluid-filled pores. Ultrasound scattering has potential for the non-invasive evaluation of changes in bone porosity. However, there is an incomplete understanding of the impact of ultrasonic absorption in the solid matrix on ultrasound scattering. In this study, maps were derived from scanning acoustic microscopy images of human femur cross-sections. Finite-difference time domain ultrasound scatter simulations were conducted on these maps. Pore density, diameter distribution of the pores, and nominal absorption values in the solid and fluid matrices were controlled. Ultrasound pulses with a central frequency of 8.2 MHz were propagated, both in through-transmission and backscattering configurations. From these data, the scattering, bone matrix absorption, and attenuation extinction lengths were calculated. The results demonstrated that as absorption in the solid matrix was varied, the scattering, absorption, and attenuation extinction lengths were significantly impacted. It was shown that for lower values of absorption in the solid matrix (less than 2 dB mm−1), attenuation due to scattering dominates, whereas at higher values of absorption (more than 2 dB mm−1), attenuation due to absorption dominates. This will impact how ultrasound attenuation and scattering parameters can be used to extract quantitative information on bone microstructure.

Experimental study of cryogenic treatment of Karaganda coal samples

Karaganda Coal Basin bears the largest undeveloped reserve of coalbed methane (CBM) in Kazakhstan, which lacks water resources for implementing large-volume hydraulic fracturing. Cryogenic fracturing utilizing liquid nitrogen (LN2) has been trialled in fields and is a waterless fracturing technique under intensive research these days. This study aimed to evaluate the cryogenic treatment efficacy of Karaganda coal samples as well as to understand the coal permeability evolution during the thawing period. X-ray fluorescent spectrometry (XRF) and microscope imaging identified the compositional and structural heterogeneities of coal specimens mined from different interlayers. Acoustic emission test, permeability measurement, and microscope imaging comparatively characterized the dry coal structure alteration before and after immersion into LN2. Cryogenic treatment slowed down the S-wave velocity through coal specimens, enhanced permeability by over 65 % after temperature recovery as well as created new fractures, enlarged existing ones, and spalled coal particles. Dynamic permeability evolution against temperature rise during the thawing process has been successfully captured for the first time. Overall, the experimental measurements support that the LN2 cryogenic fracturing technique would be effective in stimulating coalbeds for CBM production in Karaganda Coal Basin.

High frequency acoustic microscopy imaging of pellet cladding interface in nuclear fuel rods

In Pressurized Water Reactors (PWRs), fuel rods play a crucial role in generating nuclear energy. These rods consist of ceramic pellets, such as UO2 or (U,Pu)O2, enclosed in a zircaloy cladding tube, leaving an initial gap between the pellets and the cladding. As the reactor operates and the fuel undergoes irradiation, both the ceramic pellets and the zircaloy cladding experience transformations, causing the gap between them to gradually close. This phenomenon has a significant impact on the thermomechanical behavior of the fuel rod.Understanding the nature of the bonding that occurs during irradiation is essential for ensuring the safe and efficient operation of the reactor. To investigate the evolution of the contact state between the fuel pellets and the cladding during irradiation, a detailed analysis of the pellet-cladding interface after irradiation is necessary. However, traditional examination methods might be destructive or incapable of providing the desired level of precision and resolution.The Institute of Electronic and Systems at the University of Montpellier (IES – UMR CNRS 5214), in collaboration with the Alternative Energies and Atomic Energy Commission (CEA) and Electricité de France (EDF), has developed a specialized high-frequency acoustic microscope for imaging and non-destructively inspecting the pellet/cladding interface. The design of the acoustic microscope takes into account the complexity of the fuel rod's structure and the challenges associated with imaging the pellet/cladding interface by utilizing high-frequency ultrasound.In this paper, we present the ability of this acoustic microscope to acquire 2D images with controlled displacements of the sample rod along both its axial and circumferential directions thanks to a card with a high sampling frequency reaching 2 GHz. This capability is crucial because the geometrical, chemical, and mechanical properties of the fuel pellet-cladding contact are not uniform in these directions. By obtaining detailed acoustic images, we can identify specific regions where the fuel pellets and the cladding were in contact during irradiation. In this research, a resolution study is carried out to validate the microscope's ability to investigate the fuel rod and achieve the desired resolutions.Testing on real samples requires a specific configuration of the microscope, which must be adapted to the irradiation conditions. This is why, before proceeding to this stage, it is necessary to carry out tests on representative samples to validate the achievement of the desired resolution. So we’re also presenting the first acoustic images obtained on the zircaloy alloy claddings.

Deep learning and analytical study of void regional formation in flip-chip underfilling process

PurposeThis paper aims to study the relationship between the ball grid array (BGA) flip-chip underfilling process parameter and its void formation region.Design/methodology/approachA set of top-down scanning acoustic microscope images of BGA underfill is collected and void labelled. The labelled images are trained with a convolutional neural network model, and the performance is evaluated. The model is tested with new images, and the void area with its region is analysed with its dispensing parameter.FindingsAll findings were well-validated with reference to the past experimental results regarding dispensing parameters and their quantitative regional formation. As the BGA is non-uniform, 85% of the test samples have void(s) formed in the emptier region. Furthermore, the highest rating factor, valve dispensing pressure with a Gini index of 0.219 and U-type dispensing pattern set of parameters generally form a lower void percentage within the underfilling, although its consistency is difficult to maintain.Practical implicationsThis study enabled manufacturers to forecast the void regional formation from its filling parameters and array pattern. The filling pressure, dispensing pattern and BGA relations could provide qualitative insights to understand the void formation region in a flip-chip, enabling the prompt to formulate countermeasures to optimise voiding in a specific area in the underfill.Originality/valueThe void regional formation in a flip-chip underfilling process can be explained quantitatively with indicative parameters such as valve pressure, dispensing pattern and BGA arrangement.

An end-to-end convolutional neural network for automated failure localisation and characterisation of 3D interconnects

The advancement in the field of 3D integration circuit technology leads to new challenges for quality assessment of interconnects such as through silicon vias (TSVs) in terms of automated and time-efficient analysis. In this paper, we develop a fully automated high-efficient End-to-End Convolutional Neural Network (CNN) model, utilizing two sequentially linked CNN architectures, suitable to classify and locate thousands of TSVs as well as provide statistical information. In particular, we generate interference patterns of the TSVs by conducting a unique concept of Scanning Acoustic Microscopy (SAM) imaging. Scanning Electron Microscopy (SEM) is used to validate and also disclose the characteristic pattern in the SAM C-scan images. By comparing the model with semi-automated machine learning approaches its outstanding performance is illustrated, indicating a localisation and classification accuracy of 100% and greater than 96%, respectively. The approach is not limited to SAM-image data and presents an important step towards zero defect strategies.

Adaptive enhancement of acoustic resolution photoacoustic microscopy imaging via deep CNN prior

Acoustic resolution photoacoustic microscopy (AR-PAM) is a promising medical imaging modality that can be employed for deep bio-tissue imaging. However, its relatively low imaging resolution has greatly hindered its wide applications. Previous model-based or learning-based PAM enhancement algorithms either require design of complex handcrafted prior to achieve good performance or lack the interpretability and flexibility that can adapt to different degradation models. However, the degradation model of AR-PAM imaging is subject to both imaging depth and center frequency of ultrasound transducer, which varies in different imaging conditions and cannot be handled by a single neural network model. To address this limitation, an algorithm integrating both learning-based and model-based method is proposed here so that a single framework can deal with various distortion functions adaptively. The vasculature image statistics is implicitly learned by a deep convolutional neural network, which served as plug and play (PnP) prior. The trained network can be directly plugged into the model-based optimization framework for iterative AR-PAM image enhancement, which fitted for different degradation mechanisms. Based on physical model, the point spread function (PSF) kernels for various AR-PAM imaging situations are derived and used for the enhancement of simulation and in vivo AR-PAM images, which collectively proved the effectiveness of proposed method. Quantitatively, the PSNR and SSIM values have all achieve best performance with the proposed algorithm in all three simulation scenarios; The SNR and CNR values have also significantly raised from 6.34 and 5.79 to 35.37 and 29.66 respectively in an in vivo testing result with the proposed algorithm.

Reliability Inspection for Bilayer Nanosilver Paste Ensemble Pressureless Sintered Embedded Cooling SiC Power Module

Various hollowing substrates have been invented to equipped in the embedded cooling power modules. Through a lower stress residue, multilayer nanosilver paste ensemble pressureless sintering to obtain the qualified thermal interface material (TIM) joints becomes an essential process for those fragile stacking packages. As the Anand viscoelastic constitutive model prediction, the maximum residual stress inside the TIM joints is only 63.18 MPa, far below the encapsulated materials’ tensile strengths. From all the scanning electron microscope (SEM), X-ray, and scanning acoustic microscope (SAM) image investigations, the upper and beneath nanosilver paste ensemble pressureless sintered TIM joints (50 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pm ~10~\mu \text{m}$ </tex-math></inline-formula> thickness) contained few cracks and delamination (only 1.6% ± 0.1% and 8.5% ± 0.1% void ratios, respectively). The measured upper and beneath sintered TIM joints’ bond strengths were up to 38 ± 2 and 63.8 ± 2 MPa, higher than the industry requirement (30 MPa), respectively. After 21 000 power cycles, the upper and beneath sintered TIM joints’ thermal resistance increased only by 10.3% and 5.3%, far underneath the failure standard (20%), respectively. This presented multilayer nanosilver paste ensemble pressureless sintering process is a promising technology for the embedded cooling power module stacking package.

Condition monitoring indicators for Si and SiC power modules

The reliability of power modules plays a crucial role in developing safer and smarter generations of electric vehicles. Condition monitoring represents a possible solution to predict the possible occurrence of catastrophic failures and avoid unexpected breakdowns. More specifically, power modules for inverter applications are a technology requiring condition monitoring indicators to detect ongoing degradation mechanisms. In this work, both silicon IGBT and silicon carbide MOSFET power modules are thermally stressed through the application of a pulsed direct current until reaching end-of-life limits. As a result, two main failure mechanisms occurring at package level are observed: chip solder degradation and bond-wire damages. In addition, on-state voltage, junction temperature, and thermal resistance are measured during the power cycling as parameters to monitor the device states of health. After the test, the chip solder conditions and bond-wires robustness are checked through scanning acoustic microscope images and optical inspections, respectively. The novelty of this work lies in refining and comparing health indicators for silicon and silicon carbide power modules.

3D reconstruction and characterization of reef limestone pores based on optical and acoustic microscopic images

The pore network in reef limestone provides an important resource for fluid storage and flow. Three-dimensional (3D) reconstruction and characterization of the spatial structure of reef limestone pores offers a valuable way of identifying its physical and mechanical properties. This paper reports on a study where optical and acoustic microscope images were used to combine the advantages of the high resolution of optical testing with the high penetration capabilities of acoustic testing. This overcomes existing problems with multi-scale structural imaging of the pores in reef limestone caused by the small penetration depth of traditional optical imaging and the low resolution of ultrasonic imaging. First of all, a correlation function between the shallow and deep pore structure of reef limestone is established. This draws on high-resolution data from shallow optical microscopic images and deep acoustic microscopic images with a multi-layered cross-section. The contours of the shallow and deep pore structure are then digitized. After this, horizontal section control points and vertical transition contours are constructed that enable a deep integration of information about the multi-dimensional geometric morphology of the pore structure to be realized, providing in turn for a fine-grained 3D reconstruction of the pore structure at different scales. Finally, factors governing the characterization of contour similarity and center deviation are proposed that make it possible to generate spatial representations of the pore structure across multiple dimensions. A real-world case analysis is then used to verify the feasibility and reliability of the proposed method. The results show that the method can provide abundant data for the establishment of a reef limestone pore network and physical model, making it possible to improve the quality of 3D reconstructions of the pore structure and improve the 3D imaging of reef limestone pore networks. The proposed method can underpin new approaches to analysis of the pore structure of reef limestone and support a wide range of potential applications in the field of pore visualization and characterization.

The effects of nominal absorption in bone on the extinction lengths for scattering, absorption, and overall attenuation

In cortical bone, the effect of absorption in the solid matrix on ultrasound scattering and propagation is not well understood, and for absorption, it is not easily incorporated into simulations and is difficult to measure independently from scattering attenuation. In this study, finite-difference time-domain simulations were conducted in maps derived from scanning acoustic microscopy images of human femur cross-sections. These maps were modified by controlling pore density (fixed at 10 pores/mm2) and diameter distribution (ranging between 30 and 100 μm). Eight nominal absorption values, ranging from 0 to 100 dB/cm, were attributed to the solid matrix. Absorption in the pores was set to 0.01 dB/cm. Propagation of ultrasound pulses centered at 8 MHz was simulated in both backscattering and through-transmission configurations. The scattering, absorption, and overall attenuation extinction lengths were obtained. T-tests demonstrated that varying the absorption significantly impacts the extinction lengths for scattering, overall attenuation, and absorption. The differences in values for the scattering, attenuation, and absorption extinction lengths when absorption varied from 20 to 40 dB/cm are statistically significant (respective p-values: 9.1 × 10−14, 3.3 × 10−5, and 8.8 × 10−5). It was also demonstrated that attenuation due to scattering dominates overall attenuation at low-nominal absorption values, whereas the converse is true at higher absorption values.

Effect of Defects Part I: Degradation of Constitutive Coefficients as an Input to the Composite Failure Model with Microvoids and Porosity

It is always challenging to provide appropriate material properties for a composite progressive failure model. The nonstandard percentage reduction method that is commonly used to degrade the material constants with micro-scale defects generates tremendous uncertainty in failure prediction. The constitutive matrix is composed of multiple material constants. It is not necessary that all constants degrade either equally or linearly due to a certain state of material defects. With this very concern in mind, this article presents a guideline for using a quantified perturbation for each coefficient appropriately. It also presents distribution of effective material properties (EMPs) in unidirectional composite materials with different states of defects such as voids. Irrespective of resin transfer molding (RTM) or chemical vapor infiltration (CVI) processes, manufacturers’ defects such as voids of different shapes and sizes are the most common that occur in composite materials. Hence, it is important to quantify the ‘effects of defects’ void content herein on each material coefficient and EMP. In this article, stochastically distributed void parameters such as the void content by percent, size, shape, and location are considered. Void diameters and shapes were extracted from scanning acoustic microscope (SAM) images of 300,000 cycles of a fatigued composite. The EMPs were calculated by considering unit cells, homogenization techniques, and micromechanical concepts. The periodic boundary conditions were applied to unit cells to calculate the EMPs. The result showed that EMPs were degraded even when there was a small percentage of the void content. More importantly, the constitutive coefficients did not degrade equally but had a definitive pattern.

Scanning acoustic microscopy imaging of cellular structural and mechanical alterations from external stimuli

Cells incur structural and functional damage from external stimuli. Under scanning acoustic microscopy (SAM), speed of sound (SOS), attenuation, and thickness values are plotted to visualize cellular stiffness, viscosity, and size. The obtained digital data are then compared using statistical analysis. In the present study, we aimed to investigate the alterations in the mechanical and structural characteristics of cancer cells in response to anticancer drugs, acidic fluids, and microwave burdens using SAM. We found that active untreated cells showed increased thickness and reduced SOS and attenuation, whereas dying treated cells displayed reduced thickness and increased SOS. Tannic and acetic acid treatments and microwave irradiation all increased SOS and attenuation and reduced thickness, which meant that these treatments made cells thinner, stiffer, and more viscous. Furthermore, the different anticancer drugs interacted with cancer cells to induce characteristic changes in SAM values. These structural and mechanical alterations induced in cells were difficult to observe under light microscopy. However, under SAM, cancer cell activity and function corresponded consistently with changes in SAM values. Cellular damage parameters were statistically compared between the different treatments, and time-dependent cellular changes were established. SAM observation can therefore reliably evaluate cancer cell damage and recovery after chemotherapy and physical therapy. These results may help evaluate the therapeutic efficacy of various treatments.

Towards virtual twin for electronic packages in automotive applications

The piezoresistive silicon based stress sensor has the potential to be part of the Digital Twin implementation in automotive electronics. One solution to enforce reliability in digital twins is the use of Machine Learning (ML). One or more physical parameters are being monitored, while other parameters are projected with surrogate models, just like virtual sensors. Piezo-resistive stress sensors are employed to measure the internal stresses of electronic packages, an Acquisition Unit (AU) to read out sensor data and a Raspberry Pi to perform evaluation. Accelerated tests in air thermal chamber are performed to get time series data of the stress sensor signals, with which we can know better about how delamination develops inside the package. In this study stress measurements are performed in several electronic packages during the delamination. The delamination is detected by the stress sensor due to the continuous change of the stiffness and the local boundary conditions causing the stresses to change. Although, the stress change in multiple cells can give enough information if it is delaminated or not, its delamination area location is unknown. Surrogate models built upon Neural Networks (NN) and Finite Element Method (FEM) are developed to predict the out of plane stresses at the delaminated layer. FEM simulation models are calibrated with Moiré measurements and validated at the component and PCB level with stress difference measurements. Simulation delamination areas are constructed based on the Scanning Acoustic Microscope (SAM) images, and are also validated with the equivalent stress measurements. In the end the surrogate model is predicting the out of plane stress in the adhesive layer. The results show good correlation when compared to the SAM images.

Low-Temperature (260 °C) Solderless Cu–Cu Bonding for Fine-Pitch 3-D Packaging and Heterogeneous Integration

Low-temperature solderless Cu–Cu bonding is an important technology for advanced packaging, such as fine-pitch 3-D packaging and heterogeneous integration. In this study, we prepared an oxidation-free Cu surface using an optimized N2 plasma process in a two-step Ar/N2 plasma treatment based on the design of the experiment method, to improve direct Cu–Cu bonding quality at 260 °C. The N2 plasma treatment process was optimized using the Minitab optimizer with chemical state results obtained by X-ray photoelectron spectroscopy (XPS) analysis. The Cu surface treated under the two-step Ar/N2 plasma with optimized N2 plasma conditions not only formed Cu nitride well, but the surface remained without further oxidation for at least one week at room temperature. The Cu–Cu bonding was performed at the low bonding temperature of 260 °C and low bonding pressure of 0.9 MPa for 1 hour, and the bonded interface was evaluated using scanning acoustic tomography (SAT) and field emission scanning electron microscope (FE-SEM) images. We measured shear strength to estimate the bonding interface quality of the oxidation-free Cu–Cu bonding specimen. A maximum shear strength of 62.6 MPa was obtained. Our bonding results demonstrated remarkably improved Cu–Cu bonding quality compared with other previous Cu–Cu joint studies that used Sn, Cu/Ag nanoparticles, or Cu composites.

An Atomic Force Acoustic Microscopy Image Fusion Method Based on Grayscale Inversion and Selection of Best-Fit Intensity

Atomic force acoustic microscopy (AFAM) can provide surface morphology and internal structures of the samples simultaneously, with broad potential in non-destructive imaging of cells. As the output of AFAM, morphology and acoustic images reflect different features of the cells, respectively. However, there are few studies about the fusion of these images. In this paper, a novel method is proposed to fuse these two types of images based on grayscale inversion and selection of best-fit intensity. First, grayscale inversion is used to transform the morphology image into a series of inverted images with different average intensities. Then, the max rule is applied to fuse those inverted images and acoustic images, and a group of pre-fused images is obtained. Finally, a selector is employed to extract and export the expected image with the best-fit intensity among those pre-fused images. The expected image can preserve both the acoustic details of the cells and the background’s gradient information well, which benefits the analysis of the cell’s subcellular structure. The experiments’ results demonstrated that our method could provide the clearest boundaries between the cells and background, and preserve most details from the morphology and acoustic images according to quantitative comparisons, including standard deviation, mutual information, Xydeas and Petrovic metric, feature mutual information, and visual information fidelity fusion.

Collective Die Bonding: An Enabling Toolkit for Heterogeneous Integration

The increasing demand for high performance devices with increased functionality onto a single device/package and with reduced form factor were the main factors driving the development of heterogeneous integration technology. Heterogeneous integration (HI) refers to the assembly and packaging of multiple separately manufactured components onto a single chip in order to increase functionality. Components with different functionality, substrate materials and process technologies are joined in a single package in a System in Package (SIP) approach. The functionality of the components could vary throughout the entire device supply chain starting from signal processors to memory, micro-electro-mechanical systems (MEMS) and silicon photonics. The possibility to join multiple functionalities onto a die enables new packaging architectures and design concepts. One such concept is based on the not new concept of die-to-wafer bonding but allows for bonding multiple dies to a wafer in a single process. Such technological approach requires a reliable local multiple-dies bonding technology compliant also to state of the art optical alignment accuracy. Packaging is the final manufacturing process transforming devices into functional products for the end user. Packaging must provide electrical and photonic connections for signal input and output, power input, and voltage control. It also provides for thermal dissipation and the physical protection required for increased product reliability.In this work we report results using a method and process flow enabling local die bonding compatible with the highest alignment accuracy and cleaning requirements to support a very high yield. A customized temporary carrier with alignment features was utilized to place known good dies (KGD) on the carrier and enable die processing prior to the final bonding process. Such carriers with KGD’s (figure 1) were successfully processed using direct bonding, hybrid bonding, adhesive bonding and metal bonding using as bonding partner different substrate materials like silicon and III-V semiconductor. The process success was verified by the final transfer rate, scanning acoustic microscope imaging and TEM cross section analysis (figure 2). In addition other metrology methods have been identified to monitor the process stability. Figure 1

Stochastic excitation for high-resolution atomic force acoustic microscopy imaging: a system theory approach.

In this work, a high-resolution atomic force acoustic microscopy imaging technique is developed in order to obtain the local indentation modulus at the nanoscale level. The technique uses a model that gives a qualitative relationship between a set of contact resonance frequencies and the indentation modulus. It is based on white-noise excitation of the tip–sample interaction and uses system theory for the extraction of the resonance modes. During conventional scanning, for each pixel, the tip–sample interaction is excited with a white-noise signal. Then, a fast Fourier transform is applied to the deflection signal that comes from the photodiodes of the atomic force microscopy (AFM) equipment. This approach allows for the measurement of several vibrational modes in a single step with high frequency resolution, with less computational cost and at a faster speed than other similar techniques. This technique is referred to as stochastic atomic force acoustic microscopy (S-AFAM), and the frequency shifts of the free resonance frequencies of an AFM cantilever are used to determine the mechanical properties of a material. S-AFAM is implemented and compared with a conventional technique (resonance tracking-atomic force acoustic microscopy, RT-AFAM). A sample of a graphite film on a glass substrate is analyzed. S-AFAM can be implemented in any AFM system due to its reduced instrumentation requirements compared to conventional techniques.

Metal pitting corrosion characterized by scanning acoustic microscopy and binary image processing

To evaluate the residual life and safe operation of metallic materials, it is crucial to accurately identify the intensity and depth of corrosion pits. Scanning acoustic microscopy (SAM) using tomographic acoustic microimaging (TAMI) under C-mode was employed to determine corrosion pit morphology and depth on aluminum alloy 7050, and the reults were cross-checked by optical microscopy. Maximum and average pitting depths of 204 μm and 80 μm, respectively, were determined by multilayer scannning, and a pitted area of 30 ∼ 40 % was calculated using binary image processing.