3D Scanning Electron Microscopy Research Articles

Ni-based coating protection of 316L stainless steel at dry, elevated temperature and wet sliding condition

The NiCrSiB coatings are used extensively for wear and oxidation resistance in numerous applications like hot forming industries, power generation plants, petroleum refining, and nuclear power plants. In this paper, NiCrSiB powder deposited by APS (atmospheric plasma spray) and HVOF (high velocity oxy-fuel) process on stainless steel 316L substrate was investigated for the friction and wear at RT (room temperature), 700 °C, at the lubricating condition with clean and contaminated oil with nano alumina particles. The sliding wear tests were carried out on standard tribometer against silicon nitride (1580 HV0.3) counter material following ASTM G99 standard. The coatings characterization was performed using porosity analysis, nano-indentation, 3D non-contact analysis, EDX (energy-dispersive X-ray), SEM (scanning electron microscope) and LRS (Laser Raman Spectrum). The wear, friction and the wear mechanisms were investigated for both coatings at tested conditions. Although the coating wear was substantially affected by the temperature, the specific wear rate of the APS and HVOF coatings lies in the range 10-4 to 10-5 mm3/N.m and hence serviceable up to 700 °C. The coating's wear mechanisms at elevated temperature were a combination of adhesive and tribo-oxidative wear. At the dry, wet, and high-temperature condition, the HVOF coating retains higher wear resistance than APS coating, due to the high dense structure, low porosity, low inflight oxidation and high nano hardness. The nano alumina particles in the contaminated oil reduces the COF significantly for HVOF coating whereas, negligible change in COF has been observed for APS coating.

Interactive Virtual Scanning Electron Microscope Inspired by 3D Game-Design

The scanning electron microscope (SEM) has evolved to become an indispensable tool for research and education in engineering, physics, nanotechnology, geosciences, materials science, biological sciences and other fields. However, training on a physical SEM is costly, time consuming, and often unavailable in economically disadvantaged areas. Advances in computer technology have made interactive three-dimensional (3D) virtual laboratory an effective tool for training in medicine and many engineering and technology fields. In the current work, in order to provide cost-effective hands-on training, a virtual 3D SEM was developed using the game development engine <i>Unity 3D</i>. It contains realistic 3D models of the physical components, created using <i>3ds Max^®</i>, a software for 3D modeling and rendering. The components are manipulated with scripts programmed using C# and JavaScript and then paired with the corresponding model. Users may view and operate the virtual instrument, save images for further analysis, and write a report. The developed virtual SEM was tested on diverse groups of users at multiple institutions, each divided to treatment and control groups. Feedback from these tests was collected and used for improvements in the overall quality of the simulated experience. In addition, users reported the experience of training on the virtual SEM as enjoyable.

Characterizing clay textures and their impact on the reservoir using deep learning and Lattice-Boltzmann simulation applied to SEM images

The presence of clays in hydrocarbon reservoirs challenges the producible amount of oil and gas significantly. Therefore, this study reports a detailed quantitative characterization of clays' specific properties from two fundamental aspects which include clays' type and amount, and their impact on reservoir's fluid flow. We used Scanning Electron Microscopy (SEM) images and respectively adopted deep learning for typing and quantifying clays, and the Lattice-Boltzmann Method (LBM) for flow simulations with and without the presence of clays. The trained deep learning model of the present study was translated into a MATLAB application that is a convenient tool for clay characterization by the future user. This model was trained using 2160 images of different clay minerals based on transfer learning using AlexNet and resulted in more than 95.4% accuracy while applied on the unforeseen images. Moreover, we established the technique of depth-slicing of 2D SEM images, which provides the possibility of 3D processing of the routine SEM images. The results from this technique proved that clays could reduce reservoir porosity and permeability by more than 30% and 400 mD, respectively. The introduced approach of the present study provides new insights into the detailed impacts of clay minerals on the reservoir's quality.

Battery Separator Characterization Strategy via Electron Microscopes

Lithium Ion (Li-ion) batteries store energy and power billions of devices globally, so manufacturers face pressure to ensure high energy density while maintaining safety. Among a battery’s components, a thin separator material prevents physical contact between electrodes while directing ion transport within a cell. Both processes impact cell rate performance, cycle life, and safety [1]. Therefore, an in-depth understanding of separator structure is essential to improving batteries [2-4]. 2D and 3D electron microscopy (EM) effectively characterize separator structure; however, due to intrinsic beam sensitivity to most separators, care is needed to accurately characterize separator structure in its native state. Our work tested 2D scanning EM (SEM) and 3D DualBeamTM (Focused Ion Beam-Scanning Electron Microscope, FIB-SEM) imaging conditions to understand their effect on recovered separator structure.We investigated battery separator structure using a Thermo Scientific ApreoTM SEM and Thermo Scientific DualBeam systems equipped with CryoMAT. The SEM assisted with understanding surface-level electron beam damage in 2D and the DualBeam uncovered 3D structure using FIB milling. In the 2D case, we found the accelerating voltage could warp the separator. Low kV imaging is thus recommended to minimize structure damage.Additionally, in 2D SEM cross-section studies, sample preparation could affect separator structure. We tested an Al2O3-coated composite separator by FIB milling at three different temperatures (Figure 1). We found that cryogenic temperatures (-80° C; i.e., cryo-FIB) achieved the highest quality cross-section (Figure 1). FIB milling at either room temperature (25° C) or ultracold temperature (-180° C) both introduced defects on the microstructure.Finally, given the previous result, we collected 3D separator structure via cryo-FIB. With the 3D image stack, we used Thermo Scientific Avizo™ Software to recover structural parameters: open pore volume fraction, closed pore count and volume fraction, pore connectivity, tortuosity, and permeability. Such information should be useful for understanding battery separator performance. It is expected the strategies discussed in this talk will facilitate separator technology development.

Water-Oil Displacement in Shale: New Insights from a Comparative Study Integrating Imbibition Tests and Multiscale Imaging

SummaryWater-oil displacement is an important process that occurs in a shale matrix after hydraulic fracturing and in water-based enhanced oil recovery. Current understanding of this displacement process is limited because of the complicated pore structure and surface properties in shale. In this work, this process and its controlling factors are investigated through a comparative study of three shale samples that have different types of pore systems and wettability. An integrated method of imbibition and multiscale imaging was applied, and a modified oleic tracer that can better represent oil flow was used in imbibition testing and micro-computed tomography (CT) imaging. Scanning electron microscope (SEM) pore characterization was then performed under high magnification with guidance from the micro-CT images showing the changes caused by oil or water imbibition. New insights were obtained on the importance of both wettability and pore size effect on oil recovery and the distribution of residual oil after water-oil displacement. Connectivity of pores with different wettability is also discussed based on 3D analysis and SEM pore characterization. Collectively, these new findings improve the understanding of the complicated process of water-oil displacement and the role of influencing factors. Important implications for improved oil recovery strategy in shale are discussed for different types of reservoir rocks. The integrated imaging and imbibition technique provides a new path for further investigation of improved oil recovery in shale.

Descriptor-based method combined with partition to reconstruct three-dimensional complex microstructures.

A descriptor-based method combined with a partition approach is proposed to reconstruct three-dimensional (3D) microstructures based on a set of two-dimensional (2D) scanning electron microscopy (SEM) images. The features in the SEM images are identified and partitioned into small features using the watershed algorithm. The watershed algorithm first finds the local gray-level maxima, and partitions the features through the gray-level local minima. The 3D size distribution and radial distribution of the small spherical elements are inferred, respectively, based on the 2D size distribution and radial distribution using stereological analysis. The 3D microstructures are reconstructed by matching the inferred size distribution and radial distribution through a simulated annealing-based procedure. Combining with the proposed partition approach, the descriptor-based method can be applied to complex microstructures and the computational efficiency of the reconstruction can be largely improved. A case study is presented using a set of 2D SEM images with nanoscale pore structure from the low-density CSH (calcium silicate hydrate) phase of a hardened cement paste. Cross sections were randomly selected from the reconstructed 3D microstructure and compared with the original SEM images using the pore descriptors and the two-point correlation function with satisfactory agreement. Using the 3D reconstructed model, the properties of the sample material can be investigated on such a small scale as demonstrated in this paper on quantifying the absolute permeability.

Determination of the Feature Resolution of Processed Image Data via Statistical Analysis.

A method is presented to determine the feature resolution of physically relevant metrics of data obtained from segmented image sets. The presented method determines the best-fit distribution curve of a dataset by analyzing a truncated portion of the data. An effective resolvable size for the metric of interest is established when including parts of the truncated dataset results in exceeding a specified error tolerance. As such, this method allows for the determination of the feature resolution regardless of the processing parameters or imaging instrumentation. Additionally, the number of missing objects that exist below the resolution of the instrumentation may be estimated. The application of the developed method was demonstrated on data obtained via 2D scanning electron microscopy of a pressed explosive material and from 3D micro X-ray computed tomography of a polymer-bonded explosive material. It was shown that the minimum number of pixels/voxels required for the accurate determination of a physically relevant metric is dependent on the metric of interest. This proposed method, utilizing the prior knowledge of the distribution of metrics of interest, was found to be well suited to determine the feature resolution in applications where large datasets can be achieved.

Структурные особенности нанопористых мембран на основе оксидов титана и алюминия

Nanoporous membranes based on metal oxides are widely used for the formation of nanostructured materials, since it is possible to create materials with predetermined structural properties. In this research work, the structural features of nanoporous membranes based on titanium and aluminum oxides, which are combined by the production process, but differ in the growth of pores and their structure. Membranes based on metal oxides were synthesized at a voltage of U=80-140V, at room temperature T=17°C, in an acidic environment. The structural features of the synthesized membranes were studied using Quanta 200i 3D scanning electron microscopy (FEI). It was found that titanium dioxide films have a narrow pore distribution, the sizes of which are in the range of 40-115 nm. Structural differences between titanium oxide and aluminum oxide nanomembranes make it possible to be widely used in the field of nanotechnology and materials science.

RockFlow: Fast Generation of Synthetic Source Rock Images Using Generative Flow Models

Image-based evaluation methods are a valuable tool for source rock characterization. The time and resources needed to obtain images has spurred development of machine-learning generative models to create synthetic images of pore structure and rock fabric from limited image data. While generative models have shown success, existing methods for generating 3D volumes from 2D training images are restricted to binary images and grayscale volume generation requires 3D training data. Shale characterization relies on 2D imaging techniques such as scanning electron microscopy (SEM), and grayscale values carry important information about porosity, kerogen content, and mineral composition of the shale. Here, we introduce RockFlow, a method based on generative flow models that creates grayscale volumes from 2D training data. We apply RockFlow to baseline binary micro-CT image volumes and compare performance to a previously proposed model. We also show the extension of our model to 2D grayscale data by generating grayscale image volumes from 2D SEM and dual modality nanoscale shale images. The results show that our method underestimates the porosity and surface area on the binary baseline datasets but is able to generate realistic grayscale image volumes for shales. With improved binary data preprocessing, we believe that our model is capable of generating synthetic porous media volumes for a very broad class of rocks from shale to carbonates to sandstone.

Microstructure reconstruction of battery polymer separators by fusing 2D and 3D image data for transport property analysis

A new approach to generate high-fidelity 3D microstructure reconstructions by leveraging resolution and sample volume characteristics from 2D and 3D microscopy methods is presented. This approach is employed to model the microstructure of a highly orthotropic polypropylene separator used in lithium-ion batteries, which have challenging multi-scale features of fibrils (<100 nm) and lamellae (>100 nm) to resolve in 3D. Phase contrast nano X-ray computed tomographic data are used to reconstruct the lamellae phase, while 2D scanning electron microscopy data are used to characterize sub-100 nm microstructure features such as the thin fibrils that are beyond the effective resolution of X-ray computed tomography. Fibril geometries are reconstructed stochastically based on the 2D higher resolution data, and integrated with the lamellae geometries in 3D space. Transport property analyses are performed to investigate the bias of microstructure models without considering the fibrils. A sensitivity study is also conducted to facilitate understanding of the relationship between microstructure characteristics and transport properties.

The quality study of composite galvanic coatings, obtained using electroerosive powders

Actual is the task of creating the so-called composite galvanic coatings (CGC), introducing hardening additives in the form of finely dispersed powder into the solution. During the experiments, a coating was applied using a standard composition, and then a coating with the addition of EED powder in an amount of 5 g/l of solution. The microstructure of the obtained coatings was investigated using a Quanta 200 3D scanning electron microscope. Testing the hardness of the samples along the transverse section was carried out using the DM – 8 automatic microhardness analysis system. It was experimentally established that the composite galvanic coating has a clear boundary with the substrate and a transition friable layer of up to 30 μm. In this case, the presence of vertical cracks up to 50 μm in size was noted. It was shown that a composite coating obtained with the addition of an electroerosive powder in an amount of 5 g/l of solution has a microhardness 12% higher than a coating using a standard electrolyte composition.

Multiscale cardiac imaging spanning the whole heart and its internal cellular architecture in a small animal model.

Cardiac pumping depends on the morphological structure of the heart, but also on its subcellular (ultrastructural) architecture, which enables cardiac contraction. In cases of congenital heart defects, localized ultrastructural disruptions that increase the risk of heart failure are only starting to be discovered. This is in part due to a lack of technologies that can image the three-dimensional (3D) heart structure, to assess malformations; and its ultrastructure, to assess organelle disruptions. We present here a multiscale, correlative imaging procedure that achieves high-resolution images of the whole heart, using 3D micro-computed tomography (micro-CT); and its ultrastructure, using 3D scanning electron microscopy (SEM). In a small animal model (chicken embryo), we achieved uniform fixation and staining of the whole heart, without losing ultrastructural preservation on the same sample, enabling correlative multiscale imaging. Our approach enables multiscale studies in models of congenital heart disease and beyond.

MORPHOLOGY AND ELEMENT COMPOSITION POWDER ALLOY POWDER VNZH-95, OBTAINED BY ELECTROEROSION DISPERSION IN KEROSIN

Residence permits pseudo-alloys are used for the manufacture of cylinder parts, bushings, complex-shaped blanks with curved surfaces: gyroscope rotors, inertial masses, erosion-resistant electrodes, funnel for cumulative charges, biological protection from gamma radiation. Recycling of tungsten pseudo-alloys residence permit is relevant and necessary due to the shortage of tungsten. A promising method of processing waste into fine powders is the method of electroerosive dispersion (EED) that we have chosen. The purpose of the work is to study the morphology and elemental composition of the powder of the VNZh-95 pseudo-alloy obtained by electroerosive dispersion in kerosene. In order to process the waste of the W-Ni-Fe alloy into powder, we used waste in the form of chips from the core of the VNZh-95 pseudo-alloy (Ni ̶ 3.2-3.7, Fe ̶ 1.5-2.0, W ̶ the rest). Kerosene is used as a working fluid. The EED process was carried out on the installation for obtaining powders from conductive materials (patent for the invention of the Russian Federation No. 2449859). The process was carried out at a voltage on the electrodes of 100 ... 110 V, the capacitance of the discharge capacitors 50 μF and a pulse repetition rate of 120 ... 130 Hz. The microstructure of the samples (along the transverse section) was studied using a Quanta 200 3D electron-ion scanning microscope. The powder obtained by the EED method for waste of VNZh-95 alloy in kerosene consists of particles of regular spherical shape (or elliptical) and irregular shape (conglomerates). Microanalysis of particles of electroerosive powder of pseudo-alloy VNZh-95 was carried out using an EDAX energy-dispersive x-ray analyzer built into the Quanta 200 3D scanning electron microscope. As a result of studying the elemental composition of the VNZh-95 pseudo-alloy powder obtained by EED in kerosene, it was found that the main elements are tungsten, nickel, iron, carbon and oxygen.

Upscaling Reservoir Rock Porosity by Fractal Dimension Using Three-Dimensional Micro-Computed Tomography and Two-Dimensional Scanning Electron Microscope Images

Abstract Scaling porosity of sedimentary rocks from the scale of measurement to the scale of interest is still a challenge. Upscaling of porosity can assist to accurately predict other petrophysical properties of rock at multiple scales. In this study, we use the two-dimensional (2D) scanning electron microscope (SEM) and three-dimensional (3D) X-ray micro-computed tomography (micro-CT) image to upscale porosity from the image scale to the core plug scale. A systematic imaging plan is deployed to capture rock properties of a carbonate and a sandstone sample, which are sensitive to the fractal nature of these rocks. Image analysis records wider pore spectrum (0.12–50 µm) in the carbonate sample than in sandstone (0.12–30 µm). The fractal dimensions are also higher in the carbonate than in the sandstone sample. Median, volume-weighted average of pore radius, and fractal dimensions derived from the image analysis are used as inputs in this equation. The results of the present study using this equation yielded to the best results on a resolution of 2.5 µm/voxel in the sandstone and 2.01 µm/voxel resolution in the carbonate sample for 3D micro-CT images, where fractal-scaling porosity matches well with the porosity measured at the core plug scale. The 2D SEM images provided a good estimation of porosity in the sandstone sample, where micro-CT imaging techniques could not capture the full pore spectrum. The fractal porosity equation showed promising results and offers a potential alternative way to estimate porosity when there are no routine core measurements available.

Digital Analysis of Geo-Referenced Concrete Scanning Electron Microscope (SEM) Images

Abstract The microstructural evaluation of complex cementitious materials has been made possible by the microscopic imaging tools such as Scanning Electron Microscope (SEM) and X-Ray Microanalysis. Particularly, the application of concrete SEM imaging and digital image analysis have become common in the analysis and mapping of concrete technology. In this study, six samples of two-dimensional (2D) SEM images were spatially resampled to produce Geo-referenced SEM sample images. Subsequently, they were analyzed and the intensity histogram plot was produced to facilitate visual interpretation. The consecutive digital image analysis performed was the enhancement and noise removal process using two filtering methods i.e. median and adaptive box filter. The filtered resampled images, then undergone the unsupervised K-Means classification process to collectively separate each individual pixel corresponds to the spectral data. By spatial segmentation of K-Means algorithms, the cluster groups generated were carefully reviewed before proceeding to the final analysis. From the resulting data, the mapping of the spatial distribution of k-cluster and the quantification of micro-cracks (voids) were performed. The results of the SEM images (1st - 4th sample) showed a higher percentage of k-cluster data indicating a good correlation with the major elemental composition of EDX analysis, namely Oxide (O), Silicon (Si) and Carbon (C). Meanwhile, the subjective visual assessment of the image (5th and 6th sample) has confirmed the micro-crack developments on the concrete SEM images upon which the crack density was 3.02 % and 1.30 %, respectively.

3D pore system reconstruction using nano-scale 2D SEM images and pore size distribution analysis for intermediate rank coal matrix

This paper comprises the analysis of scanning electron microscopy (SEM) images, nuclear magnetic resonance (NMR) and mercury injection capillary pressure (MICP) data to quantify the pore distribution in coal matrix. We first generate the 3D pore system in the coal matrix based on the statistics of pore distribution obtained from 2D SEM images, and then extract the pore network using the maximal ball method. The influence of the reconstructed cube size and the 2D image resolution on the accuracy of the reconstructed 3D coal sample was analysed when generate the 3D digital coal smaple. It was observed that the highest resolution which was achieved for the studied samples (6 nm) resulted in the underestimation of porosity of the studied sample, and it is recommended for future to create several models with different resolution to find the most representative model, instead of apriori using the highest possible resolution. The extracted pore network was then used to analyse pore size distribution and perform capillary pressure simulation using pore network modeling. A comparison of the pore network analysis with NMR and measured MICP data demonstrated that the pore network extraction method simplified the results of distribution and underestimated the size of elongated pores and microfractures. The simulated and laboratory measured MICP shows significant difference partically bucease the network extraction method was not suitable for the studied samples and this could be overcomed by our future study of model MICP using direct simulation method in the reconstructed 3D model.

Experimental and finite element simulation of natural rubber foams using real 3D structures

Natural rubber (NR) foams were prepared via a one-step foaming process, the effect of density and morphology on micro-level and macro-level mechanical properties was studied. In particular, experimental data were used to validate different numerical models based on actual three-dimensional (3D) foam structures built using a combination of 2D scanning electron microscopy (SEM) images. Then the uniaxial compression behavior was simulated at two levels (micro-scale and macro-scale) with finite element methods (FEM). The FEM results were finally compared with experimental data and different hyper-elastic models. SEM images showed that increasing the relative foam density from 0.3 to 0.5 led to a 55% decrease in cell size and a 1000% increase in cell number. The real 3D structures showed that foams with higher density have a more homogenous structure with lower structural defects or cell connections. The results also revealed that FEM at the macroscopic level is in good agreement with experimental results, especially for high density foams. On the other hand, FEM at the microscopic level showed that the maximum stress concentration and related micro-strain substantially decreased with increasing foam density.

Energy Dispersive X-ray Spectrometry in Combination with 3D SEM Facilitates the Identification and Segmentation of Cells and Organelles

An ongoing challenge in the field of three-dimensional (3D) scanning electron microscopy (SEM) of biological materials is the identification and subsequent segmentation of datasets rich in complex information. Techniques such as serial block face SEM (SBFSEM) and array tomography produce increasingly large amounts of data and a major resource bottleneck is the amount of research time used for processing and analysing this information (Peddie and Collinson, 2014). Selective staining techniques can aid in rapid analysis by enabling researchers to threshold data based on stain intensity (Kittelmann et al., 2016), but there are a limited range of stains that can specifically target regions or organelles of interest and the technique is hampered by the inclusion of artefacts at similar greyscale thresholds. The aim of this investigation was to test if elemental analysis using energy dispersive X-ray spectrometry (EDS) could be used to identify endogenous elements and stains in biological samples and separate them from common artefacts. Array tomography and SBFSEM was used to collect 3D data of several model systems, including animal and plant tissue, prepared using standard fixation, staining and embedding techniques for electron microscopy. Array tomography and SBFSEM was used to collect BSE images and EDS maps of tissues, cells and organelles. Serial sections were cut at a thickness of 100nm and collected onto carbon coated Kapton tape for array tomography. Blocks of resin embedded samples were serially sectioned using SBFSEM at a thickness of 100-150nm. EDS was used to generate element-based maps, which were used as masks and applied to 3D datasets. EDS maps enabled fast identification of regions of interest, helped to remove imaging artefacts and enabled rapid volumetric and quantitative analysis compared to the equivalent manual segmentation.

Nanoscale pore structure and mechanical property analysis of coal: An insight combining AFM and SEM images

Scanning Electron Microscopy (SEM) and Atomic Force Microscope (AFM), two easily acquired and widely applied image acquisition and analysis methods, have rarely been combined to study the pore structure for unconventional natural gas reservoir rocks. In this work, we present an investigation of nanoscale detection of the pore distribution and mechanical properties of coals using SEM and AFM observations, and conduct quantitative analyses on pore structure distribution, surface roughness and mechanical properties. The morphological characteristics of the coal surface can be revealed by both SEM and AFM methods, and the mechanical parameters of the selected position were obtained under the peakforce quantitative nano-mechanics (PF-QNM) AFM mode, including the Young's modulus, peak force error, deformation, and adhesion forces. By fusing 800 high resolution SEM images into one single image (named as MAPS), the pores morphology and distribution of different scales were acquired. And the studied coal shows different types of cellular pores and gas pores with multiresolution. The mechanical property difference between the matrix and minerals of coal are clearly observed, with the Young’s modulus of organic component around 2 GPa, and that of the minerals generally higher than 10 GPa. The maximum adhesion force values range between 20 and 50 nN. The high values occurred where pores are developed. This work demonstrated that the combination of two dimensional (2D) SEM and three dimensional (3D) AFM results is effective in detection of surface properties, and is of significance in revealing the pore structure and mechanical properties at nanoscale.

(Invited) Latest Advances in 2D and 3D Microstructural Characterization of Fuel Cell Components

Fuel cells are complex systems whose performance and degradation depend on a number of factors spreading over multiple scales. At the lowest spatial scale are nano-sized Pt-group or Pt-group-metal-free (PGM-free) catalysts, various types of catalyst supports, proton-conducting nanometer-thin ionomer film, and gas-transporting nano-pores, all contained within the electrodes of a membrane electrode assembly (MEA). Their properties, composition and spatial distribution largely determine fuel cell performance and affect degradation trends. At the next scale are electrodes, membrane and gas diffusion layer, dictating mass, electrical and thermal transport at the micron-scale. Finally, millimeters-thick flow field plates and larger system components affect the gas transport, water and overall system management. Understanding how all of these factors affect fuel cell performance and degradation is of crucial importance, and it is only possible by applying highly correlated efforts in testing, structural characterization and mathematical modeling. The focus of this talk is to present the latest advancements in the structural characterization approaches for fuel cells at multiple scales. In the recent years, a whole suite of novel 2D and 3D characterization approaches have been developed to provide information ranging from nano-sized catalysts used in the electrodes to macro-level flow field plates. This talk will give an overview of a number of advanced characterization techniques used for fuel cell analysis, starting from some more typically used, such as scanning electron microscopy (SEM), to highly sophisticated techniques such as 3D electron tomography. Techniques such as 2D and 3D high-resolution transmission electron microscopy (HR-TEM), 2D and 3D scanning transmission electron microscopy with energy dispersive spectroscopy (STEM-EDS), 3D focused-ion beam SEM (FIB-SEM), electron energy loss spectroscopy (EELS), scanning transmission X-ray microscopy (STXM), atomic force microscopy (AFM), and micro- and nano-computed tomography (CT), as well as developed in-situ techniques will be discussed. Challenges in characterization, ranging from sample preparation, ionomer and water imaging, image processing and quantification will be addressed. Finally, the author’s work on advanced characterization of fuel cells will be reported. Multi-scale approach in 3D imaging and property modeling, utilizing electron tomography, FIB-SEM and micro-CT, will be presented with encountered challenges [1]. Advanced 2D STEM characterization with quantification and its application for analysis of fuel cell degradation will be discussed [2]. Lastly, a collaborative work on in-situ water imaging using X-ray synchrotron imaging and revealed effect on membrane changes during operation at high current densities will be shown [3]. The talk will close by discussing the challenges and plan forward for continuing development of fuel cell characterization approaches. Jankovic, S. Zhang, A. Putz, M. S. Saha, D. Susac, Multi-scale imaging and transport modeling for fuel cell electrodes, (invited) Journal of Materials Research, 34 (4) (2019).Kneer, J. Jankovic, D. Susac, A. Putz, N. Wagner, M. Sabharwal, M. Secanell, Correlation of changes in electrochemical and structural parameters due to voltage cycling induced degradation in PEM fuel cells, Journal of The Electrochemical Society, 165 (6) F3241-F3250 (2018).N. Ge, R. Banerjee, D. Muirhead, J. Lee, H. Liu, P. Shrestha, A.K.C. Wong, J. Jankovic, M. Tam, D. Susac, J. Stumper, A. Bazylak, Membrane dehydration with increasing current density at high inlet gas relative humidity in polymer electrolyte membrane fuel cells, Journal of Power Sources, 422 (2019) 163-174.