Electron Tomography: A Three-Dimensional Analytic Tool for Hard and Soft Materials Research

Chiral Inorganic Nanomaterials Characterized by Advanced TEM: A Qualitative and Quantitative Study

Chiral inorganic nanomaterials (CINMs) have garnered significant interest due to their exceptional optical, electronic, and catalytic properties, offering promising advancements in energy conversion, data storage, catalysis, and biomedicine. While traditional optical spectrophotometers reveal the chiroptical performance of CINMs on an ensemble level, the direct structural visualization for the qualitative and quantitative discernment of their chiral features has become increasingly distinct with the advancements of transmission electron microscopy (TEM) techniques. The need for reasonable and high-standard discrimination requirements of CINMs has driven the progress of chirality-based TEM technologies. Therefore, this review in the good season takes the initiative to summarize the current advancements in TEM technologies for CINMs characterization, emphasizing a qualitative analysis of chiral atomic-level features, 0D, 1D, and 2D nanocrystals, and assembled nanomaterials. Then, the quantitative methods for determining chirality is also highlighted, such as 3D electron tomography, and further address the evolution of chiral structures monitored by the Ex-situ and In-situ TEM technologies. By providing a roadmap for the current challenges and proposing future advancements in TEM technologies for the qualitative, quantitative, and real-time analysis of CINMs, it can drive innovations in the field of chiral nanomaterials as well as the development of TEM technologies.

The beginning of iron corrosion - high-resolution visualization with 3D electron tomography

Understanding the genesis and early-phase reactions of iron corrosion is essential for the early detection, mitigation and prevention of metal degradation. In this work, high-resolution 3D tomography of metallic iron oxidation was acquired using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM). In particular, dendritic capillaries (<0.5 nm) were observed during the initial oxidation of fresh nanoscale zero-valent iron due to the differential oxygen diffusion and iron atoms migration. This observation led to the proposal of a nanoscale "pothole" model for early-phase corrosion, wherein hollowing out of the metal nanoparticle and formation of nanovoids beneath the iron/oxide interface through Kirkendall effect. Coalescence of the nanocapillaries results in the ultimate collapse of metal structure and/or functional failure. Using nanoscale zero-valent iron as a research model, this work provides unprecedented insights into the nano- and atomic-scale mechanisms of iron oxidation, paving the way for advanced detection and prevention strategies for iron corrosion.

Evaluating Cryo-TEM Reconstruction Accuracy of Self-Assembled Polymer Nanostructures

Cryogenic transmission electron microscopy (cryo-TEM) combined with single particle analysis (SPA) is an emerging imaging approach for soft materials. However, the accuracy of SPA-reconstructed nanostructures, particularly those formed by synthetic polymers, remains uncertain due to potential packing heterogeneity of the nanostructures. In this study, the combination of molecular dynamics (MD) simulations and image simulations is utilized to validate the accuracy of cryo-TEM 3D reconstructions of self-assembled polypeptoid fibril nanostructures. Using CryoSPARC software, image simulations, 2D classifications, ab initio reconstructions, and homogenous refinements are performed. By comparing the results with atomic models, the recovery of molecular details is assessed, heterogeneous structures are identified, and the influence of extraction location on the reconstructions is evaluated. These findings confirm the fidelity of single particle analysis in accurately resolving complex structural characteristics and heterogeneous structures, exhibiting its potential as a valuable tool for detailed structural analysis of synthetic polymers and soft materials.

Bone hierarchical organization through the lens of materials science: Present opportunities and future challenges

Multiscale characterization is essential to better understand the hierarchical architecture of bone and an array of analytical methods contributes to exploring the various structural and compositional aspects. Incorporating X-ray tomography, X-ray scattering, vibrational spectroscopy, and atom probe tomography alongside electron microscopy provides a comprehensive approach, offering insights into the diverse levels of organization within bone. X-ray scattering techniques reveal information about collagen-mineral spatial relationships, while X-ray tomography captures 3D structural details, especially at the microscale. Electron microscopy, such as scanning and transmission electron microscopy, extends resolution to the nanoscale, showcasing intricate features such as collagen fibril organization. Additionally, atom probe tomography achieves sub-nanoscale resolution and high chemical sensitivity, enabling detailed examination of bone composition. Despite various technical challenges, a correlative approach allows for a comprehensive understanding of bone material properties. Real-time investigations through in situ and in operando approaches shed light on the dynamic processes in bone. Recently developed techniques such as liquid, in situ transmission electron microscopy provide insights into calcium phosphate formation and collagen mineralization. Mechanical models developed in the effort to link structure, composition, and function currently remain oversimplified but can be improved. In conclusion, correlative analytical platforms provide a holistic perspective of bone extracellular matrix and are essential for unraveling the intricate interplay between structure and composition within bone.

2D vs. 3D Evaluation of Osteocyte Lacunae - Methodological Approaches, Recommended Parameters, and Challenges: A Narrative Review by the European Calcified Tissue Society (ECTS)

PURPOSE OF REVIEW

Quantification of the morphology of osteocyte lacunae has become a powerful tool to investigate bone metabolism, pathologies and aging. This review will provide a brief overview of 2D and 3D imaging methods for the determination of lacunar shape, orientation, density, and volume. Deviations between 2D-based and 3D-based lacunar volume estimations are often not sufficiently addressed and may give rise to contradictory findings. Thus, the systematic error arising from 2D-based estimations of lacunar volume will be discussed, and an alternative calculation proposed. Further, standardized morphological parameters and best practices for sampling and segmentation are suggested.

RECENT FINDINGS

We quantified the errors in reported estimation methods of lacunar volume based on 2D cross-sections, which increase with variations in lacunar orientation and histological cutting plane. The estimations of lacunar volume based on common practice in 2D imaging methods resulted in an underestimation of lacunar volume of up to 85% compared to actual lacunar volume in an artificial dataset. For a representative estimation of lacunar size and morphology based on 2D images, at least 400 lacunae should be assessed per sample.

3D Nanocrystallography and the Imperfect Molecular Lattice

Crystallographic analysis relies on the scattering of quanta from arrays of atoms that populate a repeating lattice. While large crystals built of lattices that appear ideal are sought after by crystallographers, imperfections are the norm for molecular crystals. Additionally, advanced X-ray and electron diffraction techniques, used for crystallography, have opened the possibility of interrogating micro- and nanoscale crystals, with edges only millions or even thousands of molecules long. These crystals exist in a size regime that approximates the lower bounds for traditional models of crystal nonuniformity and imperfection. Accordingly, data generated by diffraction from both X-rays and electrons show increased complexity and are more challenging to conventionally model. New approaches in serial crystallography and spatially resolved electron diffraction mapping are changing this paradigm by better accounting for variability within and between crystals. The intersection of these methods presents an opportunity for a more comprehensive understanding of the structure and properties of nanocrystalline materials.

Development and application of a 3D image analysis strategy for focused ion beam - Scanning electron microscopy tomography of porous soft materials

In recent years, the potential of porous soft materials in various device technologies has increased in importance due to applications in fields, such as wearable electronics, medicine, and transient devices. However, understanding the 3-dimensional architecture of porous soft materials at the microscale remains a challenge. Herein, we present a method to structurally analyze soft materials using Focused Ion Beam - Scanning Electron Microscopy (FIB-SEM) tomography. Two materials, polymethyl methacrylate (PMMA) membrane and pine wood veneer were chosen as test-cases. FIB-SEM was successfully used to reconstruct the true topography of these materials in 3D. Structural and physical properties were subsequently deduced from the rendered 3D models. The methodology used segmentation, coupled with optimized thresholding, image processing, and reconstruction protocols. The 3D models generated pore size distribution, pore inter-connectivity, tortuosity, thickness, and curvature data. It was shown that FIB-SEM tomography provides both an informative and visual depiction of structure. To evaluate and validate the FIB-SEM reconstructions, porous properties were generated from the physical property analysis techniques, gas adsorption analysis using Brunauer-Emmett-Teller (BET) surface area analysis and mercury intrusion porosimetry (MIP) analysis. In general, the data obtained from the FIB-SEM reconstructions was well-matched with the physical data. RESEARCH HIGHLIGHTS: Porous specimens of both synthetic and biological nature, a poly(methyl methacrylate) membrane and a pine veneer respectively, are reconstructed via FIB-SEM tomography without resin-embedding. Different thresholding and reconstruction methods are explored whereby shadowing artifacts are present with the aid of free open-source software. Reconstruction data is compared to physical data: MIP, gas adsorption isotherms which are analyzed via BET and Barrett-Joyner-Halenda (BJH) analysis to yield a full picture of the materials.

Seeing the Supracolloidal Assemblies in 3D: Unraveling High-Resolution Structures Using Electron Tomography

Transmission electron microscopy (TEM) imaging has revolutionized modern materials science, nanotechnology, and structural biology. Its ability to provide information about materials' structure, composition, and properties at atomic-level resolution has enabled groundbreaking discoveries and the development of innovative materials with precision and accuracy. Electron tomography, single particle reconstruction, and microcrystal electron diffraction techniques have paved the way for the three-dimensional (3D) reconstruction of biological samples, synthetic materials, and hybrid nanostructures at near atomic-level resolution. TEM tomography using a series of two-dimensional (2D) projections has been used extensively in biological science, but in recent years it has become an important method in synthetic nanomaterials and soft matter research. TEM tomography offers unprecedented morphological details of 3D objects, internal structures, packing patterns, growth mechanisms, and self-assembly pathways of self-assembled colloidal systems. It complements other analytical tools, including small-angle X-ray scattering, and provides valuable data for computational simulations for predictive design and reverse engineering of nanomaterials with the desired structure and properties. In this perspective, I will discuss the importance of TEM tomography in the structural understanding and engineering of self-assembled nanostructures with specific emphasis on colloidal capsids, composite cages, biohybrid superlattices with complex geometries, polymer assemblies, and self-assembled protein-based superstructures.

Electrifying Energy and Chemical Transformations with Single-Atom Alloy Nanoparticle Catalysts

Single-atom alloys (SAAs) have attracted considerable attention as promising electrocatalysts in reactions central to energy conversion and chemical transformation. In contrast to monometallic nanocrystals and metal alloys, SAAs possess unique and intriguing physicochemical properties, positioning them as ideal model systems for studying structure-property relationships. However, the field is still in its early stages. In this Perspective, we first review and summarize rational synthesis methods and advanced characterization techniques for SAA nanoparticle catalysts. We then emphasize the extensive applications of SAAs in a range of electrocatalytic reactions, including fuel cell reactions, water splitting, and carbon dioxide and nitrate reductions. Finally, we provide insights into existing challenges and prospects associated with the controlled synthesis, characterization, and design of SAA catalysts.

Synthesis of Silver Nanoparticles from Ganoderma Species and Their Activity against Multi Drug Resistant Pathogens

The widespread and indiscriminate use of broad-spectrum antibiotics leads to microbial resistance, which causes major problems in the treatment of infectious diseases. However, advances in nanotechnology using mushrooms have opened up new domains for the synthesis and use of nanoparticles against multidrug-resistant pathogens. Mushooms have recently attracted attention and are exploited for food and medicinal purposes. The current study focuses on the molecular identification, characterization of biologically synthesized silver nanoparticles by X-ray diffraction (XRD) spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), UV-Vis spectroscopy and scanning electron microscopy (SEM) and antibacterial analysis of extract and silver nanoparticles (AgNPs) synthesis from Ganoderma resinaceum against multidrug resistant microbes. Accurate identification of mushrooms is key in utilizing them for the benefit of humans. However, morphological identification of mushrooms is time consuming, tedious and may be prone to error. Molecular techniques are quick and reliable tools that are useful in mushroom taxonomy. Blast results showed that G. resinaceum (GU451247) obtained from Pakistan was 97 % same to the recognized G. resinaceum (GU451247) obtained from China as well as G. resinaceum (GU451247) obtained from India. The antimicrobial potential of mushroom composite and AgNPs showed high efficacy against pathogenic Staphylococcus aureus (ZOI 23 mm) K. pneumonia (ZOI 20 mm), Pseudomonas aeruginosa (ZOI 24 mm) and E. fecalis and A. baumannii (ZOI 10 mm), and multidrug resistant (MDR) A. baumannii (ZOI 24 mm). XRD evaluation revealed the crystalline composition of synthesized NPs with diameter of 45 nm. UV-Vis spectroscopy obsorption peaked of 589 nm confirmed the presence of AgNPs. SEM results showed the cubic morphology of AgNPs. The FTIR analysis of NPs obtained from G. resinaceum containing C=O as well as (O=C-H) stretching revealed presence of hydrogen, carbonyl and amide groups. The synthesized extract and AgNPs showed promising minimum inhibitory concentration (MIC) at 2 mg concentration against the MDR strains. AgNPs are observed to be efficient as they need less quantities to prevent bacterial growth. In the view of challenges for developing antimicrobial NPs of variable shape and size by various other methods, tuning nanoparticles synthesized via mushrooms can be a wonderful approach to resolve existing hurdles.

Cylinders-in-Undulating-Lamellae Morphology from ABC Bottlebrush Block Terpolymers

Block polymer self-assembly affords a versatile bottom-up strategy to develop materials with the desired properties dictated by specific symmetries and dimensions. Owing to distinct properties compared with linear counterparts, bottlebrush block polymers with side chains densely grafted on a backbone have attracted extensive attention. However, the morphologies found in bottlebrush block polymers so far are limited, and only lamellar and cylindrical ordered phases have been reported in diblock bottlebrushes. The absence of complex morphologies, such as networks, might originate from the intrinsically stiff backbone architecture. We experimentally investigated the morphologies of nonfrustrated ABC bottlebrush block terpolymers, based on two chemistries, poly(ethylene-alt-propylene)-b-polystyrene-b-poly(dl-lactic acid) (PEP-PS-PLA) and PEP-b-PS-b-poly(ethylene oxide) (PEP-PS-PEO), synthesized by ring-opening metathesis polymerization of norbornene-terminated macromonomers. Structural characterization based on small-angle X-ray scattering and transmission electron microscopy measurements revealed an unprecedented cylinders-in-undulating-lamellae (CUL) morphology with p2 symmetry for both systems. Additionally, automated liquid chromatography was employed to fractionate the PEP-PS-PLA bottlebrush polymer, leading to fractions with a spectrum of morphologies, including the CUL. These findings underscore the significance of macromolecular dispersity in nominally narrow dispersity bottlebrush polymers while demonstrating the power of this fractionation technique.

The Case for a Defect Genome Initiative

The Materials Genome Initiative (MGI) has streamlined the materials discovery effort by leveraging generic traits of materials, with focus largely on perfect solids. Defects such as impurities and perturbations, however, drive many attractive functional properties of materials. The rich tapestry of charge, spin, and bonding states hosted by defects are not accessible to elements and perfect crystals, and defects can thus be viewed as another class of "elements" that lie beyond the periodic table. Accordingly, a Defect Genome Initiative (DGI) to accelerate functional defect discovery for energy, quantum information, and other applications is proposed. First, major advances made under the MGI are highlighted, followed by a delineation of pathways for accelerating the discovery and design of functional defects under the DGI. Near-term goals for the DGI are suggested. The construction of open defect platforms and design of data-driven functional defects, along with approaches for fabrication and characterization of defects, are discussed. The associated challenges and opportunities are considered and recent advances towards controlled introduction of functional defects at the atomic scale are reviewed. It is hoped this perspective will spur a community-wide interest in undertaking a DGI effort in recognition of the importance of defects in enabling unique functionalities in materials.

Ultrastructural 3D Microscopy for Biomedicine: Principles, Applications, and Perspectives

Modern biomedical research often requires a three-dimensional microscopic analysis of the ultrastructure of biological objects and materials. Conceptual technical and methodological solutions for three-dimensional structure reconstruction are needed to improve the conventional optical, electron, and probe microscopy methods, which to begin with allow one to obtain two-dimensional images and data. This review discusses the principles and potential applications of such techniques as serial section transmission electron microscopy; techniques based on scanning electron microscopy (SEM) (array tomography, focused ion beam SEM, and serial block-face SEM). 3D analysis techniques based on modern super-resolution optical microscopy methods are described (stochastic optical reconstruction microscopy and stimulated emission depletion microscopy), as well as ultrastructural 3D microscopy methods based on scanning probe microscopy and the feasibility of combining them with optical techniques. A comparative analysis of the advantages and shortcomings of the discussed approaches is performed.

Advanced Imaging Techniques for the Characterization of Subcellular Organelle Structure in Pancreatic Islet β Cells

Type 2 diabetes (T2D) affects more than 32.3 million individuals in the United States, creating an economic burden of nearly $966 billion in 2021. T2D results from a combination of insulin resistance and inadequate insulin secretion from the pancreatic β cell. However, genetic and physiologic data indicate that defects in β cell function are the chief determinant of whether an individual with insulin resistance will progress to a diagnosis of T2D. The subcellular organelles of the insulin secretory pathway, including the endoplasmic reticulum, Golgi apparatus, and secretory granules, play a critical role in maintaining the heavy biosynthetic burden of insulin production, processing, and secretion. In addition, the mitochondria enable the process of insulin release by integrating the metabolism of nutrients into energy output. Advanced imaging techniques are needed to determine how changes in the structure and composition of these organelles contribute to the loss of insulin secretory capacity in the β cell during T2D. Several microscopy techniques, including electron microscopy, fluorescence microscopy, and soft X-ray tomography, have been utilized to investigate the structure-function relationship within the β cell. In this overview article, we will detail the methodology, strengths, and weaknesses of each approach. © 2024 American Physiological Society. Compr Physiol 14:5243-5267, 2024.

Ultrastructure and Nanoporosity of Human Bone Shown with Correlative On-Axis Electron and Spectroscopic Tomographies

Mineralized collagen fibrils are the building block units of bone at the nanoscale. While it is known that collagen fibrils are mineralized both inside their gap zones (intra-fibrillar mineralization) and on their outer surfaces (extra-fibrillar mineralization), a clear visualization of this architecture in three dimensions (3D), combining structural and compositional information over large volumes, but without compromising the resolution, remains challenging. In this study, we demonstrate the use of on-axis Z-contrast electron tomography (ET) with correlative energy-dispersive X-ray spectroscopy (EDX) tomography to examine rod-shaped samples with diameters up to 700 nm prepared from individual osteonal lamellae in the human femur. Our work mainly focuses on two aspects: (i) low-contrast nanosized circular spaces ("holes") observed in sections of bone oriented perpendicular to the long axis of a long bone, and (ii) extra-fibrillar mineral, especially in terms of morphology and spatial relationship with respect to intra-fibrillar mineral and collagen fibrils. From our analyses, it emerges quite clearly that most "holes" are cross-sectional views of collagen fibrils. While this had been postulated before, our 3D reconstructions and reslicing along meaningful two-dimensional (2D) cross-sections provide a direct visual confirmation. Extra-fibrillar mineral appears to be composed of thin plates that are interconnected and span over several collagen fibrils, confirming that mineralization is cross-fibrillar, at least for the extra-fibrillar phase. EDX tomography shows mineral signatures (Ca and P) within the gap zones, but the signal appears weaker than that associated with the extra-fibrillar mineral, pointing toward the existence of dissimilarities between the two types of mineralization.

Evaluation of Electron Tomography Capabilities for Shale Imaging

Despite the advantageous resolution of electron tomography (ET), reconstruction of three-dimensional (3D) images from multiple two-dimensional (2D) projections presents several challenges, including small signal-to-noise ratios, and a limited projection range. This study evaluates the capabilities of ET for thin sections of shale, a complex nanoporous medium. A numerical phantom with 1.24 nm pixel size is constructed based on the tomographic reconstruction of a Barnett shale. A dataset of 2D projection images is numerically generated from the 3D phantom and studied over a range of conditions. First, common reconstruction techniques are used to reconstruct the shale structure. The reconstruction uncertainty is quantified by comparing overall values of storage and transport metrics, as well as the misclassification of pore voxels compared to the phantom. We then select the most robust reconstruction technique and we vary the acquisition conditions to quantify the effect of artifacts. We find a strong agreement for large pores over the different acquisition workflows, while a wider variability exists for nanometer-scale features. The limited projection range and reconstruction are identified as the main experimental bottlenecks, thereby suggesting that sample thinning, advanced holders, and advanced reconstruction algorithms offer opportunities for improvement.

Tuning Mesopore Accessibility of Ce0.18Zr0.64Y0.15La0.03O2-δ by Hydrothermal Post-treatment─A Case Study for Ceria-Based Oxidation Storage Materials

The connectivity and thermal stability of pores in heterogeneous, mesoporous metal oxide catalysts are key properties controlling their (long-term) efficacy. In this study, we investigate the influence of pH and temperature during a common hydrothermal aftertreatment step in the synthesis of mesoporous CexZr1-x-y-zYyLazO2-δ oxides obtained from molecular precursors via hydrothermal synthesis. This study has a strong focus on the methodological approach, elucidating whether and how even the smallest changes in morphology and connectivity may be unraveled and related to the underlying chemical processes to uncover key parameters for the ongoing improvement of material properties. Deep insights into the mesopore space were obtained by state-of-the-art physisorption (including hysteresis scanning), electron tomography, and small-angle X-ray scattering (SAXS) analysis. We also provide a simple tool to simulate SAXS curves from electron tomography data that allow direct comparison to experimentally obtained SAXS curves. Furthermore, the impact on surface-bound nitrate groups and the development during calcination were studied in detail by thermogravimetric analysis coupled with mass spectrometry. The key observations indicate a significant increase in thermal stability at temperatures as high as 1050 °C and improved mesopore accessibility with an increase in pH of the aftertreatment solution. The combined observations from the employed methods suggest a pH-dependent removal of surface-bound nitrate groups as well as a dissolution and reprecipitation-based fusing of the primary particles that constitute the mesopore skeleton. This transformation yields a mechanically and thermally stronger mesopore space with the capability to endure high temperatures.

Cell wall dynamics: novel tools and research questions

Years ago, a classic textbook would define plant cell walls based on passive features. For instance, a sort of plant exoskeleton of invariable polysaccharide composition, and probably painted in green. However, currently, this view has been expanded to consider plant cell walls as active, heterogeneous, and dynamic structures with a high degree of complexity. However, what do we mean when we refer to a cell wall as a dynamic structure? How can we investigate the different implications of this dynamism? While the first question has been the subject of several recent publications, defining the ideal strategies and tools needed to address the second question has proven to be challenging due to the myriad of techniques available. In this review, we will describe the capacities of several methodologies to study cell wall composition, structure, and other aspects developed or optimized in recent years. Keeping in mind cell wall dynamism and plasticity, the advantages of performing long-term non-invasive live-imaging methods will be emphasized. We specifically focus on techniques developed for Arabidopsis thaliana primary cell walls, but the techniques could be applied to both secondary cell walls and other plant species. We believe this toolset will help researchers in expanding knowledge of these dynamic/evolving structures.

Accelerating Quantum Materials Development with Advances in Transmission Electron Microscopy

Quantum materials are driving a technology revolution in sensing, communication, and computing, while simultaneously testing many core theories of the past century. Materials such as topological insulators, complex oxides, superconductors, quantum dots, color center-hosting semiconductors, and other types of strongly correlated materials can exhibit exotic properties such as edge conductivity, multiferroicity, magnetoresistance, superconductivity, single photon emission, and optical-spin locking. These emergent properties arise and depend strongly on the material's detailed atomic-scale structure, including atomic defects, dopants, and lattice stacking. In this review, we describe how progress in the field of electron microscopy (EM), including in situ and in operando EM, can accelerate advances in quantum materials and quantum excitations. We begin by describing fundamental EM principles and operation modes. We then discuss various EM methods such as (i) EM spectroscopies, including electron energy loss spectroscopy (EELS), cathodoluminescence (CL), and electron energy gain spectroscopy (EEGS); (ii) four-dimensional scanning transmission electron microscopy (4D-STEM); (iii) dynamic and ultrafast EM (UEM); (iv) complementary ultrafast spectroscopies (UED, XFEL); and (v) atomic electron tomography (AET). We describe how these methods could inform structure-function relations in quantum materials down to the picometer scale and femtosecond time resolution, and how they enable precision positioning of atomic defects and high-resolution manipulation of quantum materials. For each method, we also describe existing limitations to solve open quantum mechanical questions, and how they might be addressed to accelerate progress. Among numerous notable results, our review highlights how EM is enabling identification of the 3D structure of quantum defects; measuring reversible and metastable dynamics of quantum excitations; mapping exciton states and single photon emission; measuring nanoscale thermal transport and coupled excitation dynamics; and measuring the internal electric field and charge density distribution of quantum heterointerfaces- all at the quantum materials' intrinsic atomic and near atomic-length scale. We conclude by describing open challenges for the future, including achieving stable sample holders for ultralow temperature (below 10K) atomic-scale spatial resolution, stable spectrometers that enable meV energy resolution, and high-resolution, dynamic mapping of magnetic and spin fields. With atomic manipulation and ultrafast characterization enabled by EM, quantum materials will be poised to integrate into many of the sustainable and energy-efficient technologies needed for the 21st century.

Advances in Focused Ion Beam Tomography for Three-Dimensional Characterization in Materials Science

Over the years, FIB-SEM tomography has become an extremely important technique for the three-dimensional reconstruction of microscopic structures with nanometric resolution. This paper describes in detail the steps required to perform this analysis, from the experimental setup to the data analysis and final reconstruction. To demonstrate the versatility of the technique, a comprehensive list of applications is also summarized, ranging from batteries to shale rocks and even some types of soft materials. Moreover, the continuous technological development, such as the introduction of the latest models of plasma and cryo-FIB, can open the way towards the analysis with this technique of a large class of soft materials, while the introduction of new machine learning and deep learning systems will not only improve the resolution and the quality of the final data, but also expand the degree of automation and efficiency in the dataset handling. These future developments, combined with a technique that is already reliable and widely used in various fields of research, are certain to become a routine tool in electron microscopy and material characterization.

Denoising Autoencoder Trained on Simulation-Derived Structures for Noise Reduction in Chromatin Scanning Transmission Electron Microscopy

Scanning transmission electron microscopy tomography with ChromEM staining (ChromSTEM), has allowed for the three-dimensional study of genome organization. By leveraging convolutional neural networks and molecular dynamics simulations, we have developed a denoising autoencoder (DAE) capable of postprocessing experimental ChromSTEM images to provide nucleosome-level resolution. Our DAE is trained on synthetic images generated from simulations of the chromatin fiber using the 1-cylinder per nucleosome (1CPN) model of chromatin. We find that our DAE is capable of removing noise commonly found in high-angle annular dark field (HAADF) STEM experiments and is able to learn structural features driven by the physics of chromatin folding. The DAE outperforms other well-known denoising algorithms without degradation of structural features and permits the resolution of α-tetrahedron tetranucleosome motifs that induce local chromatin compaction and mediate DNA accessibility. Notably, we find no evidence for the 30 nm fiber, which has been suggested to serve as the higher-order structure of the chromatin fiber. This approach provides high-resolution STEM images that allow for the resolution of single nucleosomes and organized domains within chromatin dense regions comprising of folding motifs that modulate the accessibility of DNA to external biological machinery.

Research Progress on Metal-Organic Frameworks by Advanced Transmission Electron Microscopy

Metal-organic frameworks (MOFs), composed of metal nodes and inorganic linkers, are promising for a wide range of applications due to their unique periodic frameworks. Understanding structure-activity relationships can facilitate the development of new MOFs. Transmission electron microscopy (TEM) is a powerful technique to characterize the microstructures of MOFs at the atomic scale. In addition, it is possible to directly visualize the microstructural evolution of MOFs in real time under working conditions via in situ TEM setups. Although MOFs are sensitive to high-energy electron beams, much progress has been made due to the development of advanced TEM. In this review, we first introduce the main damage mechanisms for MOFs under electron-beam irradiation and two strategies to minimize these damages: low-dose TEM and cryo-TEM. Then we discuss three typical techniques to analyze the microstructure of MOFs, including three-dimensional electron diffraction, imaging using direct-detection electron-counting cameras, and iDPC-STEM. Groundbreaking milestones and research advances of MOFs structures obtained with these techniques are highlighted. In situ TEM studies are reviewed to provide insights into the dynamics of MOFs induced by various stimuli. Additionally, perspectives are analyzed for promising TEM techniques in the research of MOFs' structures.

Chirality Analysis of Complex Microparticles using Deep Learning on Realistic Sets of Microscopy Images

Nanoscale chirality is an actively growing research field spurred by the giant chiroptical activity, enantioselective biological activity, and asymmetric catalytic activity of chiral nanostructures. Compared to chiral molecules, the handedness of chiral nano- and microstructures can be directly established via electron microscopy, which can be utilized for the automatic analysis of chiral nanostructures and prediction of their properties. However, chirality in complex materials may have multiple geometric forms and scales. Computational identification of chirality from electron microscopy images rather than optical measurements is convenient but is fundamentally challenging, too, because (1) image features differentiating left- and right-handed particles can be ambiguous and (2) three-dimensional structure essential for chirality is 'flattened' into two-dimensional projections. Here, we show that deep learning algorithms can identify twisted bowtie-shaped microparticles with nearly 100% accuracy and classify them as left- and right-handed with as high as 99% accuracy. Importantly, such accuracy was achieved with as few as 30 original electron microscopy images of bowties. Furthermore, after training on bowtie particles with complex nanostructured features, the model can recognize other chiral shapes with different geometries without retraining for their specific chiral geometry with 93% accuracy, indicating the true learning abilities of the employed neural networks. These findings indicate that our algorithm trained on a practically feasible set of experimental data enables automated analysis of microscopy data for the accelerated discovery of chiral particles and their complex systems for multiple applications.

Quantitative analysis of the structural evolution in Si anode via multi-scale image reconstruction

Despite the high theoretical capacity, silicon (Si) anode suffers from dramatical capacity loss, due to its massive volume swings (up to 300%) during cycling. Hence, thorough understanding of the structural evolution mechanism is necessary and essential for performance optimization of Si anode. Herein, a multi-scale three-dimensional (3D) image reconstruction technique is firstly applied to visualize the structural evolution process of Si anodes. Three key components (Si particles, inactive components, and voids) in the electrode are quantitatively analyzed by the focused ion beam and scanning electron microscope (FIB-SEM) technology. Furthermore, the average sizes of Si particles were run statistics during the cycling. By combining the componential observation within the electrode (macroscopic information) and the 3D models of the particle with solid electrolyte interphase (SEI) layer (microscopic information), the failure mechanism of Si anode is vividly demonstrated. This work establishes a new methodology to quantitatively analyze the structural and compositional evolution of Si anode, which could be further applied for the studies of many other electrode materials with similar issues.

High-Resolution Electron Tomography of Ultrathin Boerdijk-Coxeter-Bernal Nanowire Enabled by Superthin Metal Surface Coating

The rapid advancement of transmission electron microscopy has resulted in revolutions in a variety of fields, including physics, chemistry, and materials science. With single-atom resolution, 3D information of each atom in nanoparticles is revealed, while 4D electron tomography is shown to capture the atomic structural kinetics in metal nanoparticles after phase transformation. Quantitative measurements of physical and chemical properties such as chemical coordination, defects, dislocation, and local strain have been made. However, due to the incompatibility of high dose rate with other ultrathin morphologies, such as nanowires, atomic electron tomography has been primarily limited to quasi-spherical nanoparticles. Herein, the 3D atomic structure of a complex core-shell nanowire composed of an ultrathin Boerdijk-Coxeter-Bernal (BCB) core nanowire and a noble metal thin layer shell deposited on the BCB nanowire surface is discovered. Furthermore, it is demonstrated that a new superthin noble metal layer deposition on an ultrathin BCB nanowire could mitigate electron beam damage using an in situ transmission electron microscope and atomic resolution electron tomography. The colloidal coating method developed for electron tomography can be broadly applied to protect the ultrathin nanomaterials from electron beam damage, benefiting both the advanced material characterizations and enabling fundamental in situ mechanistic studies.

Molecular organization of the early stages of nucleosome phase separation visualized by cryo-electron tomography

It has been proposed that the intrinsic property of nucleosome arrays to undergo liquid-liquid phase separation (LLPS) in vitro is responsible for chromatin domain organization in vivo. However, understanding nucleosomal LLPS has been hindered by the challenge to characterize the structure of the resulting heterogeneous condensates. We used cryo-electron tomography and deep-learning-based 3D reconstruction/segmentation to determine the molecular organization of condensates at various stages of LLPS. We show that nucleosomal LLPS involves a two-step process: a spinodal decomposition process yielding irregular condensates, followed by their unfavorable conversion into more compact, spherical nuclei that grow into larger spherical aggregates through accretion of spinodal materials or by fusion with other spherical condensates. Histone H1 catalyzes more than 10-fold the spinodal-to-spherical conversion. We propose that this transition involves exposure of nucleosome hydrophobic surfaces causing modified inter-nucleosome interactions. These results suggest a physical mechanism by which chromatin may transition from interphase to metaphase structures.

Microscopic Visualization of Cell-Cell Adhesion Complexes at Micro and Nanoscale

Considerable progress has been made in our knowledge of the morphological and functional varieties of anchoring junctions. Cell-cell adhesion contacts consist of discrete junctional structures responsible for the mechanical coupling of cytoskeletons and allow the transmission of mechanical signals across the cell collective. The three main adhesion complexes are adherens junctions, tight junctions, and desmosomes. Microscopy has played a fundamental role in understanding these adhesion complexes on different levels in both physiological and pathological conditions. In this review, we discuss the main light and electron microscopy techniques used to unravel the structure and composition of the three cell-cell contacts in epithelial and endothelial cells. It functions as a guide to pick the appropriate imaging technique(s) for the adhesion complexes of interest. We also point out the latest techniques that have emerged. At the end, we discuss the problems investigators encounter during their cell-cell adhesion research using microscopic techniques.

Bone mineral organization at the mesoscale: A review of mineral ellipsoids in bone and at bone interfaces

Much debate still revolves around bone architecture, especially at the nano- and microscale. Bone is a remarkable material where high strength and toughness coexist thanks to an optimized composition of mineral and protein and their hierarchical organization across several distinct length scales. At the nanoscale, mineralized collagen fibrils act as building block units. Despite their key role in biological and mechanical functions, the mechanisms of collagen mineralization and the precise arrangement of the organic and inorganic constituents in the fibrils remains not fully elucidated. Advances in three-dimensional (3D) characterization of mineralized bone tissue by focused ion beam-scanning electron microscopy (FIB-SEM) revealed mineral-rich regions geometrically approximated as prolate ellipsoids, much larger than single collagen fibrils. These structures have yet to become prominently recognized, studied, or adopted into biomechanical models of bone. However, they closely resemble the circular to elliptical features previously identified by scanning transmission electron microscopy (STEM) in two-dimensions (2D). Herein, we review the presence of mineral ellipsoids in bone as observed with electron-based imaging techniques in both 2D and 3D with particular focus on different species, anatomical locations, and in proximity to natural and synthetic biomaterial interfaces. This review reveals that mineral ellipsoids are a ubiquitous structure in all the bones and bone-implant interfaces analyzed. This largely overlooked hierarchical level is expected to bring different perspectives to our understanding of bone mineralization and mechanical properties, in turn shedding light on structure-function relationships in bone. STATEMENT OF SIGNIFICANCE: In bone, the hierarchical organization of organic (mainly collagen type I) and inorganic (calcium-phosphate mineral) components across several length scales contributes to a unique combination of strength and toughness. However, aspects related to the collagen-mineral organization and to mineralization mechanisms remain unclear. Here, we review the presence of mineral prolate ellipsoids across a variety of species, anatomical locations, and interfaces, both natural and with synthetic biomaterials. These mineral ellipsoids represent a largely unstudied feature in the organization of bone at the mesoscale, i.e., at a level connecting nano- and microscale. Thorough understanding of their origin, development, and structure can provide valuable insights into bone architecture and mineralization, assisting the treatment of bone diseases and the design of bio-inspired materials.

Recent Development of MOF-Based Photothermal Agent for Tumor Ablation

Metal-organic frameworks (MOFs) are 3D-architecture compounds of metal ions and organic molecules with sufficient and permanent porosity, showing great potential as a versatile platform to load various functional moieties to endow the hybrid materials with specific applications. Currently, a variety of photothermal nanometals have been embedded into organic ligands for integrating the unique photothermal effects with the merits of MOFs to improve their performances for cancer therapy. In this review, we have summarized a series of novel MOF-based photothermal materials for this unique therapeutic modality against tumors from three main aspects according to their chemical compositions and structures, i) metal-doped MOF, ii) organic-doped MOF, and iii) polymer-coated MOF. In addition, we have summarized the latest developments and characteristics of MOF-based photothermal agents, such as good biocompatibility, low toxicity, and responsive photothermal conversion without destroying the structure of hybrid photothermal agent. At last, we addressed the future perspectives of MOF-based photothermal agent in the field of phototherapy.

Electron microscopy for imaging organelles in plants and algae

Recent developments in both instrumentation and image analysis algorithms have allowed three-dimensional electron microscopy (3D-EM) to increase automated image collections through large tissue volumes using serial block-face scanning EM (SEM) and to achieve near-atomic resolution of macromolecular complexes using cryo-electron tomography (cryo-ET) and sub-tomogram averaging. In this review, we discuss applications of cryo-ET to cell biology research on plant and algal systems and the special opportunities they offer for understanding the organization of eukaryotic organelles with unprecedently resolution. However, one of the most challenging aspects for cryo-ET is sample preparation, especially for multicellular organisms. We also discuss correlative light and electron microscopy (CLEM) approaches that have been developed for ET at both room and cryogenic temperatures.

Cryogenic electron tomography to determine thermodynamic quantities for nanoparticle dispersions

Here we present a method to extract thermodynamic quantities for nanoparticle dispersions in solvents. The method is based on the study of tomograms obtained from cryogenic electron tomography (cryoET). The approach is demonstrated for gold nanoparticles (diameter < 5 nm). Tomograms are reconstructed from tilt-series 2D images. Once the three-dimensional (3D) coordinates for the centres of mass of all of the particles in the sample are determined, we calculate the pair distribution function g(r) and the potential of mean force U(r) without any assumption. Importantly, we show that further quantitative information from 3D tomograms is readily available as the spatial fluctuation in the particles' position can be efficiently determined. This in turn allows for the prompt derivation of the Kirkwood-Buff integrals with all their associated quantities such as the second virial coefficient. Finally, the structure factor and the agglomeration states of the particles are evaluated directly. These thermodynamic quantities provide key insights into the dispersion properties of the particles. The method works well both for dispersed systems containing isolated particles and for systems with varying degrees of agglomerations.

Traditional Microscopic Techniques Employed in Dental Adhesion Research-Applications and Protocols of Specimen Preparation

Microscopy is a traditional method to perform ex vivo/in vitro dental research. Contemporary microscopic techniques offer the opportunity to observe dental tissues and materials up to nanoscale level. The aim of this paper was to perform a literature review on four microscopic methods, which are widely employed in dental studies concerning the evaluation of resin-dental adhesive interfaces-confocal laser scanning microscopy (CLSM), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and atomic force microscopy (AFM). The literature search was performed using digital databases: PubMed, Web of Science and Scopus. On the basis of key words relevant to the topic and established eligibility criteria, finally 84 papers were included in the review. Presented microscopic techniques differ in their principle of operation and require specific protocols for specimen preparation. With regard to adhesion studies, microscopy assists in the description of several elements involved in adhesive bonding, as well as in the assessment of the condition of enamel surface and the most appropriate etching procedures. There are several factors determining the quality of the interaction between the substrates which could be recognized and a potential for further implementation of microscopic techniques in dental research could be recognized, especially when these techniques are used simultaneously or combined with spectroscopic methods. Through such microscopy techniques it is possible to provide clinically relevant conclusions and recommendations, which can be easily introduced for enamel-safe bonding and bonding protocols, as well as optimal pretreatments in dentine preparation.

Measurement of Temporal Coherence of Free Electrons by Time-Domain Electron Interferometry

The temporal properties of an electron beam are decisive for modern ultrafast electron microscopy and for the quantum optics of the free electron in laser fields. Here, we report a time-domain interferometer that measures and distinguishes the pure and ensemble coherences of a free-electron beam in a transmission electron microscope via symmetry-breaking shifts of photon-order sideband peaks. This result is a free-electron analog to the reconstruction of attosecond busts and photoemission delays in optical attosecond spectroscopy. We find a substantial pure electron coherence that is connected to the thermodynamics of the emitter material and a lower ensemble coherence that is governed by space-charge effects. Pure temporal coherences above 5 fs are measured at >10^{9} electrons per second in a high-brightness beam.

Diversifying Composition Leads to Hierarchical Composites with Design Flexibility and Structural Fidelity

Although significant progress has been made in the self-assembly of nanostructures, present successes heavily rely on precision in building block design, composition, and pair interactions. These requirements fundamentally limit our ability to synthesize macroscopic materials where the likelihood of impurity inclusion escalates and, more importantly, to access molecular-to-nanoscopic-to-microscopic-to-macroscopic hierarchies, since the types and compositions of building blocks vary at each stage. Inspired by biological blends and high-entropy alloys, we hypothesize that diversifying the blend's composition can overcome these limitations. Increasing the number of components increases mixing entropy, leading to the dispersion of different components and, as a result, enhances interphase miscibility, weakens the dependence on specific pair interactions, and enables long-range cooperativity. This hypothesis is validated in complex blends containing small molecules, block copolymer-based supramolecules, and nanoparticles/colloidal particles. Hierarchically structured composites can be obtained with formulation flexibility in the filler selection and blend composition. It is worth noting that, by adding small molecules, we can solve the size constraint that plagues traditional block copolymer/nanoparticle blends. Detailed characterization and simulation further confirm that each component is distributed to locally mediate unfavorable interactions, cooperatively mitigate composition fluctuations, and retain structural fidelity. Furthermore, the blends have sufficient mobility to access tunable microstructures without compromising the order of the nanostructure. Besides establishing a kinetically viable pathway to release current constraints in the composite design and to navigate uncertainties during structure formation over multiple length scales, the present study demonstrates that entropy-driven behaviors can be realized in systems beyond high-entropy alloys despite inherent differences between metal alloys and organic/inorganic hybrids.

From tissue retrieval to electron tomography: nanoscale characterization of the interface between bone and bioactive glass

The success of biomaterials for bone regeneration relies on many factors, among which osseointegration plays a key role. Biogran (BG) is a bioactive glass commonly employed as a bone graft in dental procedures. Despite its use in clinical practice, the capability of BG to promote osseointegration has never been resolved at the nanoscale. In this paper, we present the workflow for characterizing the interface between newly formed bone and BG in a preclinical rat model. Areas of bone-BG contact were first identified by backscattered electron imaging in a scanning electron microscope. A focused ion beam in situ lift-out protocol was employed to prepare ultrathin samples for transmission electron microscopy analysis. The bone-BG gradual interface, i.e. the biointerphase, was visualized at the nanoscale with unprecedented resolution thanks to scanning transmission electron microscopy. Finally, we present a method to view the bone-BG interface in three dimensions using electron tomography.

A Close Look at Molecular Self-Assembly with the Transmission Electron Microscope

Molecular self-assembly is pervasive in the formation of living and synthetic materials. Knowledge gained from research into the principles of molecular self-assembly drives innovation in the biological, chemical, and materials sciences. Self-assembly processes span a wide range of temporal and spatial domains and are often unintuitive and complex. Studying such complex processes requires an arsenal of analytical and computational tools. Within this arsenal, the transmission electron microscope stands out for its unique ability to visualize and quantify self-assembly structures and processes. This review describes the contribution that the transmission electron microscope has made to the field of molecular self-assembly. An emphasis is placed on which TEM methods are applicable to different structures and processes and how TEM can be used in combination with other experimental or computational methods. Finally, we provide an outlook on the current challenges to, and opportunities for, increasing the impact that the transmission electron microscope can have on molecular self-assembly.

Visualization of Collagen-Mineral Arrangement Using Atom Probe Tomography

Bone is a functional material comprised of mainly two phases: an organic collagenous phase and an inorganic mineral phase. Collagen-mineral arrangement has implications for bone function, aging, and disease. However, theories on collagen-mineral arrangement have been confined to studies with low spatial and/or compositional resolution resulting in an extensive debate over the location of mineral with respect to collagen. Herein, a strategy is developed to extract a single mineralized collagen fibril from bone and analyze its composition and structure atom-by-atom with 3D sub-nanometer accuracy and compositional clarity using atom probe tomography (APT). It is shown for the first time a method to probe fibril-level mineralization and collagen-mineral arrangement from an in vivo system with both the spatial and compositional precision required to comment on nanoscale collagen-mineral arrangement. APT of leporine bone shows distinct and helical collagen fibrils with mineralized deposits both encapsulating and incorporated into the collagenous structures. This study demonstrates a novel fibril-level detection method that can be used to probe the composition of bone and contribute new insights to the structure and organization of mineralized materials such as bones and teeth.

Electron Tomography to Study the Three-dimensional Structure of the Reovirus Egress Pathway in Mammalian Cells

Mammalian orthoreoviruses (reoviruses) are nonenveloped, double-stranded RNA viruses that replicate and assemble in cytoplasmic membranous organelles called viral inclusions (VIs). To define the cellular compartments involved in nonlytic reovirus egress, we imaged viral egress in infected, nonpolarized human brain microvascular endothelial cells (HBMECs). Electron and confocal microscopy showed that reovirus mature virions are recruited from VIs to modified lysosomes termed sorting organelles (SOs). Later in infection, membranous carriers (MCs) emerge from SOs and transport new virions to the plasma membrane for nonlytic egress. Transmission electron microscopy (TEM) combined with electron tomography (ET) and three-dimensional (3D) reconstruction revealed that these compartments are connected and form the exit pathway. Connections are established by channels through which mature virions are transported from VIs to MCs. In the last step, MCs travel across the cytoplasm and fuse with the plasma membrane, which facilitates reovirus egress. This bio-protocol describes the combination of imaging approaches (TEM, ET, and 3D reconstruction) to analyze reovirus egress zones. The spatial information present in the 3D reconstructions, along with the higher resolution relative to 2D projections, allowed us to identify components of a new nonlytic viral egress pathway.

Unraveling Structural Details in Ga-Pd SCALMS Systems Using Correlative Nano-CT, 360° Electron Tomography and Analytical TEM

We present a comprehensive structural and analytical characterization of the highly promising supported catalytically active liquid metal solutions (SCALMS) system. This novel catalyst shows excellent performance for alkane dehydrogenation, especially in terms of resistance to coking. SCALMS consists of a porous support containing catalytically active low-melting alloy particles (e.g., Ga-Pd) featuring a complex structure, which are liquid at reaction temperature. High-resolution 3D characterization at various length scales is required to reveal the complex pore morphology and catalytically active sites’ location. Nano X-ray computed tomography (nano-CT) in combination with electron tomography (ET) enables nondestructive and scale-bridging 3D materials research. We developed and applied a correlative approach using nano-CT, 360°-ET and analytical transmission electron microscopy (TEM) to decipher the morphology, distribution and chemical composition of the Ga-Pd droplets of the SCALMS system over several length scales. Utilizing ET-based segmentations of nano-CT reconstructions, we are able to reliably reveal the homogenous porous support network with embedded Ga-Pd droplets featuring a nonhomogenous elemental distribution of Ga and Pd. In contrast, large Ga-Pd droplets with a high Ga/Pd ratio are located on the surface of SCALMS primary particles, whereas the droplet size and the Ga/Pd ratio decreases while advancing into the porous volume. Our studies reveal new findings about the complex structure of SCALMS which are required to understand its superior catalytic performance. Furthermore, advancements in lab-based nano-CT imaging are presented by extending the field of view (FOV) of a single experiment via a multiple region-of-interest (ROI) stitching approach.

Electron Crystallographic Investigation of Crystals on the Mesostructural Scale

The precise structural solution of crystals on a mesostructural scale is challenging due to the difficulties in obtaining electron diffraction and the complicated relationship between the crystal structure factors (CSFs) and the conventional underfocus phase-contrast transmission electron microscopy (TEM) images due to the large unit cell and the complex structures. Here, we present the structural investigation of mesostructured crystals via the combination of electron crystallographic Fourier synthesis and high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) that only relies on the mass-thickness contrast. The three-dimensional electrostatic potential is reconstructed from the amplitudes and phases extracted from the Fourier transforms of the corresponding HAADF-STEM images and merged into a set of CSFs. This method is verified on silica scaffolds following a shifted double-diamond surface network with space group I41/amd. The results indicate that electron crystallography reconstruction by HAADF-STEM images is more suitable and accurate in determining the structure in comparison with conventional TEM electron crystallography reconstruction. This approach transfers the contrast of mesostructured crystals to images more accurately and the relationship between the Fourier transforms of HAADF-STEM images and the CSFs is more intuitive. It shows great advantages for the structural solution of crystals on the mesostructural scale.

Insights into the intraparticle morphology of dendritic mesoporous silica nanoparticles from electron tomographic reconstructions

HYPOTHESIS

Although many synthetic pathways allow to fine-tune the morphology of dendritic mesoporous silica nanoparticles (DMSNs), the control of their particle size and mesopore diameter remains a challenge. Our study focuses on either increasing the mean particle size or adjusting the pore size distribution, changing only one parameter (particle or pore size) at a time. The dependence of key morphological features (porosity; pore shape and pore dimensions) on radial distance from the particle center has been investigated in detail.

EXPERIMENTS

Three-dimensional reconstructions of the particles obtained by scanning transmission electron microscopy (STEM) tomography were adapted as geometrical models for the quantification of intraparticle morphologies by radial porosity and chord length distribution analyses. Structural properties of the different synthesized DMSNs have been complementary characterized using TEM, SEM, nitrogen physisorption, and dynamic light scattering.

FINDINGS

The successful independent tuning of particle and pore sizes of the DMSNs could be confirmed by conventional analysis methods. Unique morphological features, which influence the uptake and release of guest molecules in biomedical applications, were uncovered from analyzing the STEM tomography-based reconstructions. It includes the quantification of structural hierarchy, identification of intrawall openings and pores, as well as the distinction of pore shapes (conical vs. cylindrical).

Crystallization of nanoparticles induced by precipitation of trace polymeric additives

Orthogonal to guided growth of nanoparticle (NP) crystals using DNA or supramolecules, a trace amount of polymeric impurities (<0.1 wt.%) leads to reproducible, rapid growth of 3D NP crystals in solution and on patterned substrates with high yield. When polymers preferentially precipitate on the NP surfaces, small NP clusters form and serve as nuclei for NP crystal growth in dilute solutions. This precipitation-induced NP crystallization process is applicable for a range of polymers, and the resultant 3-D NP crystals are tunable by varying polymeric additives loading, solvent evaporation rate, and NP size. The present study elucidates how to balance cohesive energy density and NP diffusivity to simultaneously favor nuclei formation energetically and kinetic growth in dilute solutions to rapidly crystalize NPs over multiple length scales. Furthermore, the amount of impurities needed to grow NP crystals (<0.1%) reminds us the importance of fine details to interpret experimental observations in nanoscience.

On Plug-and-Play Regularization Using Linear Denoisers

In plug-and-play (PnP) regularization, the knowledge of the forward model is combined with a powerful denoiser to obtain state-of-the-art image reconstructions. This is typically done by taking a proximal algorithm such as FISTA or ADMM, and formally replacing the proximal map associated with a regularizer by nonlocal means, BM3D or a CNN denoiser. Each iterate of the resulting PnP algorithm involves some kind of inversion of the forward model followed by denoiser-induced regularization. A natural question in this regard is that of optimality, namely, do the PnP iterations minimize some f+g , where f is a loss function associated with the forward model and g is a regularizer? This has a straightforward solution if the denoiser can be expressed as a proximal map, as was shown to be the case for a class of linear symmetric denoisers. However, this result excludes kernel denoisers such as nonlocal means that are inherently non-symmetric. In this paper, we prove that a broader class of linear denoisers (including symmetric denoisers and kernel denoisers) can be expressed as a proximal map of some convex regularizer g . An algorithmic implication of this result for non-symmetric denoisers is that it necessitates appropriate modifications in the PnP updates to ensure convergence to a minimum of f+g . Apart from the convergence guarantee, the modified PnP algorithms are shown to produce good restorations.

Molecular Characterization of Polymer Networks

Polymer networks are complex systems consisting of molecular components. Whereas the properties of the individual components are typically well understood by most chemists, translating that chemical insight into polymer networks themselves is limited by the statistical and poorly defined nature of network structures. As a result, it is challenging, if not currently impossible, to extrapolate from the molecular behavior of components to the full range of performance and properties of the entire polymer network. Polymer networks therefore present an unrealized, important, and interdisciplinary opportunity to exert molecular-level, chemical control on material macroscopic properties. A barrier to sophisticated molecular approaches to polymer networks is that the techniques for characterizing the molecular structure of networks are often unfamiliar to many scientists. Here, we present a critical overview of the current characterization techniques available to understand the relation between the molecular properties and the resulting performance and behavior of polymer networks, in the absence of added fillers. We highlight the methods available to characterize the chemistry and molecular-level properties of individual polymer strands and junctions, the gelation process by which strands form networks, the structure of the resulting network, and the dynamics and mechanics of the final material. The purpose is not to serve as a detailed manual for conducting these measurements but rather to unify the underlying principles, point out remaining challenges, and provide a concise overview by which chemists can plan characterization strategies that suit their research objectives. Because polymer networks cannot often be sufficiently characterized with a single method, strategic combinations of multiple techniques are typically required for their molecular characterization.

Electrodiffusion Phenomena in Neuroscience and the Nernst–Planck–Poisson Equations

This work is aimed to give an electrochemical insight into the ionic transport phenomena in the cellular environment of organized brain tissue. The Nernst–Planck–Poisson (NPP) model is presented, and its applications in the description of electrodiffusion phenomena relevant in nanoscale neurophysiology are reviewed. These phenomena include: the signal propagation in neurons, the liquid junction potential in extracellular space, electrochemical transport in ion channels, the electrical potential distortions invisible to patch-clamp technique, and calcium transport through mitochondrial membrane. The limitations, as well as the extensions of the NPP model that allow us to overcome these limitations, are also discussed.

Deep learning in electron microscopy

Deep learning is transforming most areas of science and technology, including electron microscopy. This review paper offers a practical perspective aimed at developers with limited familiarity. For context, we review popular applications of deep learning in electron microscopy. Following, we discuss hardware and software needed to get started with deep learning and interface with electron microscopes. We then review neural network components, popular architectures, and their optimization. Finally, we discuss future directions of deep learning in electron microscopy.