Design of Laser Activated Antimicrobial Porous Tricalcium Phosphate-Hydroxyapatite Scaffolds for Orthopedic Applications.

The field of bone tissue engineering is steadily being improved by novel experimental approaches. Nevertheless, microbial adhesion after scaffold implantation remains a limitation that could lead to the impairment of the regeneration process, or scaffold rejection. The present study introduces a methodology that employs laser-based strategies for the development of antimicrobial interfaces on tricalcium phosphate-hydroxyapatite (TCP-HA) scaffolds. The outer surfaces of the ceramic scaffolds with inner porosity were structured using a femtosecond laser (λ = 800 nm; τ = 70 fs) for developing micropatterns and altering local surface roughness. The pulsed laser deposition of ZnO was used for the subsequent functionalization of both laser-structured and unmodified surfaces. The impact of the fs irradiation was investigated by Raman spectroscopy and X-ray diffraction. The effects of the ZnO-layered ceramic surfaces on initial bacterial adherence were assessed by culturing Staphylococcus aureus on both functionalized and non-functionalized scaffolds. Bacterial metabolic activity and morphology were monitored via the Resazurin assay and microscopic approaches. The presence of ZnO evidently decreased the metabolic activity of bacteria and led to impaired cell morphology. The results from this study have led to the conclusion that the combination of fs laser-structured surface topography and ZnO could yield a potential antimicrobial interface for implants in bone tissue engineering.

Interplay of the forces governing steroid hormone micropollutant adsorption in vertically-aligned carbon nanotube membrane nanopores.

Vertically-aligned carbon nanotube (VaCNT) membranes allow water to conduct rapidly at low pressures and open up the possibility for water purification and desalination, although the ultralow viscous stress in hydrophobic and low-tortuosity nanopores prevents surface interactions with contaminants. In this experimental investigation, steroid hormone micropollutant adsorption by VaCNT membranes is quantified and explained via the interplay of the hydrodynamic drag and friction forces acting on the hormone, and the adhesive and repulsive forces between the hormone and the inner carbon nanotube wall. It is concluded that a drag force above 2.2 × 10-3 pN overcomes the friction force resulting in insignificant adsorption, whereas lowering the drag force from 2.2 × 10-3 to 4.3 × 10-4 pN increases the adsorbed mass of hormones from zero to 0.4 ng cm-2. At a low drag force of 1.6 × 10-3 pN, the adsorbed mass of four hormones is correlated with the hormone-wall adhesive (van der Waals) force. These findings explain micropollutant adsorption in nanopores via the forces acting on the micropollutant along and perpendicular to the flow, which can be exploited for selectivity.

Improvement of Metal-Doped ß-TCP Scaffolds for Active Bone Substitutes via Ultra-Short Laser Structuring.

Various efforts have been made to develop antibacterial biomaterials capable of also sustaining bone remodulation to be used as bone substitutes and reduce patient infection rates and related costs. In this work, beta-tricalcium phosphate (ß-TCP) was chosen due to its known biocompatibility and use as a bone substitute. Metal dopants were incorporated into the crystal structure of the ß-TCP, and disks were produced from this material. Magnesium and strontium, as well as copper and silver, were chosen as dopants to improve the osteogenic and antibacterial properties, respectively. The surface of the ß-TCP samples was further modified using a femtosecond laser system. Grid and line patterns were produced on the plates' surface via laser ablation, creating grooves with depths lower than 20 µm and widths between 20 and 40 µm. Raman and FTIR analysis confirmed that laser ablation did not result in the degradation or phase change of the materials, making it suitable for surface patterning. Laser ablation resulted in increased hydrophilicity of the materials, as the control samples (non-ablated samples) have WCA values ranging from 70° to 93° and become, upon laser ablation, superwicking surfaces. Confocal measurements show an increase in specific surface area of 50% to 200% compared to the control. Overall, the results indicate the potential of laser ablation to improve the surface characteristics of ß-TCP, which may lead to an improvement in the antibacterial and osteogenic properties of the produced materials.

In Vitro Analysis of Human Cartilage Infiltrated by Hydrogels and Hydrogel-Encapsulated Chondrocytes.

Osteoarthritis (OA) is a degenerative joint disease causing loss of articular cartilage and structural damage in all joint tissues. Given the limited regenerative capacity of articular cartilage, methods to support the native structural properties of articular cartilage are highly anticipated. The aim of this study was to infiltrate zwitterionic monomer solutions into human OA-cartilage explants to replace lost proteoglycans. The study included polymerization and deposition of methacryloyloxyethyl-phosphorylcholine- and a novel sulfobetaine-methacrylate-based monomer solution within ex vivo human OA-cartilage explants and the encapsulation of isolated chondrocytes within hydrogels and the corresponding effects on chondrocyte viability. The results demonstrated that zwitterionic cartilage-hydrogel networks are formed by infiltration. In general, cytotoxic effects of the monomer solutions were observed, as was a time-dependent infiltration behavior into the tissue accompanied by increasing cell death and penetration depth. The successful deposition of zwitterionic hydrogels within OA cartilage identifies the infiltration method as a potential future therapeutic option for the repair/replacement of OA-cartilage extracellular suprastructure. Due to the toxic effects of the monomer solutions, the focus should be on sealing the OA-cartilage surface, instead of complete infiltration. An alternative treatment option for focal cartilage defects could be the usage of monomer solutions, especially the novel generated sulfobetaine-methacrylate-based monomer solution, as bionic for cell-based 3D bioprintable hydrogels.

Silicone-Based Lubricant-Infused Slippery Coating Covalently Bound to Aluminum Substrates for Underwater Applications.

Wetting of solid surfaces is crucial for biological and industrial processes but is also associated with several harmful phenomena such as biofouling and corrosion that limit the effectiveness of various technologies in aquatic environments. Despite extensive research, these challenges remain critical today. Recently, we have developed a facile UV-grafting technique to covalently attach silicone-based coatings to solid substrates. In this study, the grafting process was evaluated as a function of UV exposure time on aluminum substrates. While short-time exposure to UV light results in the formation of lubricant-infused slippery surfaces (LISS), a flat, nonporous variant of slippery liquid-infused porous surfaces, longer exposure leads to the formation of semi-rigid cross-linked polydimethylsiloxane (PDMS) coatings, both covalently bound to the substrate. These coatings were exposed to aquatic media to evaluate their resistance to corrosion and biofouling. While the UV-grafted cross-linked PDMS coating effectively inhibits aluminum corrosion in aquatic environments and allows organisms to grow on the surface, the LISS coating demonstrates improved corrosion resistance but inhibits biofilm adhesion. The synergy between facile and low-cost fabrication, rapid binding kinetics, eco-friendliness, and nontoxicity of the applied materials to aquatic life combined with excellent wetting-repellent characteristics make this technology applicable for implementation in aquatic environments.

Characterizing Intraindividual Podocyte Morphology In Vitro with Different Innovative Microscopic and Spectroscopic Techniques.

Podocytes are critical components of the glomerular filtration barrier, sitting on the outside of the glomerular basement membrane. Primary and secondary foot processes are characteristic for podocytes, but cell processes that develop in culture were not studied much in the past. Moreover, protocols for diverse visualization methods mostly can only be used for one technique, due to differences in fixation, drying and handling. However, we detected by single-cell RNA sequencing (scRNAseq) analysis that cells reveal high variability in genes involved in cell type-specific morphology, even within one cell culture dish, highlighting the need for a compatible protocol that allows measuring the same cell with different methods. Here, we developed a new serial and correlative approach by using a combination of a wide variety of microscopic and spectroscopic techniques in the same cell for a better understanding of podocyte morphology. In detail, the protocol allowed for the sequential analysis of identical cells with light microscopy (LM), Raman spectroscopy, scanning electron microscopy (SEM) and atomic force microscopy (AFM). Skipping the fixation and drying process, the protocol was also compatible with scanning ion-conductance microscopy (SICM), allowing the determination of podocyte surface topography of nanometer-range in living cells. With the help of nanoGPS Oxyo®, tracking concordant regions of interest of untreated podocytes and podocytes stressed with TGF-ß were analyzed with LM, SEM, Raman spectroscopy, AFM and SICM, and revealed significant morphological alterations, including retraction of podocyte process, changes in cell surface morphology and loss of cell-cell contacts, as well as variations in lipid and protein content in TGF-ß treated cells. The combination of these consecutive techniques on the same cells provides a comprehensive understanding of podocyte morphology. Additionally, the results can also be used to train automated intelligence networks to predict various outcomes related to podocyte injury in the future.

What determines accuracy of chemical identification when using microspectroscopy for the analysis of microplastics?

Fourier transform infrared (FTIR) and Raman microspectroscopy are methods applied in microplastics research to determine the chemical identity of microplastics. These techniques enable quantification of microplastic particles across various matrices. Previous work has highlighted the benefits and limitations of each method and found these to be complimentary. Within this work, metadata collected within an interlaboratory method validation study was used to determine which variables most influenced successful chemical identification of un-weathered microplastics in simulated drinking water samples using FTIR and Raman microspectroscopy. No variables tested had a strong correlation with the accuracy of chemical identification (r = ≤0.63). The variables most correlated with accuracy differed between the two methods, and include both physical characteristics of particles (color, morphology, size, polymer type), and instrumental parameters (spectral collection mode, spectral range). Based on these results, we provide technical recommendations to improve capabilities of both methods for measuring microplastics in drinking water and highlight priorities for further research. For FTIR microspectroscopy, recommendations include considering the type of particle in question to inform sample presentation and spectral collection mode for sample analysis. Instrumental parameters should be adjusted for certain particle types when using Raman microspectroscopy. For both instruments, the study highlighted the need for harmonization of spectral reference libraries among research groups, including the use of libraries containing reference materials of both weathered plastic and natural materials that are commonly found in environmental samples.

Quantitative assessment of visual microscopy as a tool for microplastic research: Recommendations for improving methods and reporting.

Microscopy is often the first step in microplastic analysis and is generally followed by spectroscopy to confirm material type. The value of microscopy lies in its ability to provide count, size, color, and morphological information to inform toxicity and source apportionment. To assess the accuracy and precision of microscopy, we conducted a method evaluation study. Twenty-two laboratories from six countries were provided three blind spiked clean water samples and asked to follow a standard operating procedure. The samples contained a known number of microplastics with different morphologies (fiber, fragment, sphere), colors (clear, white, green, blue, red, and orange), polymer types (PE, PS, PVC, and PET), and sizes (ranging from roughly 3-2000 µm), and natural materials (natural hair, fibers, and shells; 100-7000 µm) that could be mistaken for microplastics (i.e., false positives). Particle recovery was poor for the smallest size fraction (3-20 µm). Average recovery (±StDev) for all reported particles >50 µm was 94.5 ± 56.3%. After quality checks, recovery for >50 µm spiked particles was 51.3 ± 21.7%. Recovery varied based on morphology and color, with poorest recovery for fibers and the largest deviations for clear and white particles. Experience mattered; less experienced laboratories tended to report higher concentration and had a higher variance among replicates. Participants identified opportunity for increased accuracy and precision through training, improved color and morphology keys, and method alterations relevant to size fractionation. The resulting data informs future work, constraining and highlighting the value of microscopy for microplastics.

Single-Step Process for Titanium Surface Micro- and Nano-Structuring and In Situ Silver Nanoparticles Formation by Ultra-Short Laser Patterning.

Ultra-short laser (USL)-induced surface structuring combined with nanoparticles synthesis by multiphoton photoreduction represents a novel single-step approach for commercially pure titanium (cp-Ti) surface enhancement. Such a combination leads to the formation of distinct topographical features covered by nanoparticles. The USL processing of cp-Ti in an aqueous solution of silver nitrate (AgNO3) induces the formation of micron-sized spikes surmounted by silver nanoparticles (AgNPs). The proposed approach combines the structuring and oxidation of the Ti surface and the synthesis of AgNPs in a one-step process, without the use of additional chemicals or a complex apparatus. Such a process is easy to implement, versatile and sustainable compared to alternative methodologies capable of obtaining comparable results. Antimicrobial surfaces on medical devices (e.g., surgical tools or implants), for which titanium is widely used, can be realized due to the simultaneous presence of AgNPs and micro/nano-structured surface topography. The processed surfaces were examined by means of a scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDX), atomic force microscopy (AFM) and Raman spectroscopy. The surface morphology and the oxidation, quality and quantity of AgNPs were analyzed in relation to process parameters (laser scanning speed and AgNO3 concentration), as well as the effect of AgNPs on the Raman signal of Titanium oxide.

Calibration by differentiation - Self-supervised calibration for X-ray microscopy using a differentiable cone-beam reconstruction operator.

High-resolution X-ray microscopy (XRM) is gaining interest for biological investigations of extremely small-scale structures. XRM imaging of bones in living mice could provide new insights into the emergence and treatment of osteoporosis by observing osteocyte lacunae, which are holes in the bone of few micrometres in size. Imaging living animals at that resolution, however, is extremely challenging and requires very sophisticated data processing converting the raw XRM detector output into reconstructed images. This paper presents an open-source, differentiable reconstruction pipeline for XRM data which analytically computes the final image from the raw measurements. In contrast to most proprietary reconstruction software, it offers the user full control over each processing step and, additionally, makes the entire pipeline deep learning compatible by ensuring differentiability. This allows fitting trainable modules both before and after the actual reconstruction step in a purely data-driven way using the gradient-based optimizers of common deep learning frameworks. The value of such differentiability is demonstrated by calibrating the parameters of a simple cupping correction module operating on the raw projection images using only a self-supervisory quality metric based on the reconstructed volume and no further calibration measurements. The retrospective calibration directly improves image quality as it avoids cupping artefacts and decreases the difference in grey values between outer and inner bone by 68-94%. Furthermore, it makes the reconstruction process entirely independent of the XRM manufacturer and paves the way to explore modern deep learning reconstruction methods for arbitrary XRM and, potentially, other flat-panel computed tomography systems. This exemplifies how differentiable reconstruction can be leveraged in the context of XRM and, hence, is an important step towards the goal of reducing the resolution limit of in vivo bone imaging to the single micrometre domain.

Ultralow-parameter denoising: Trainable bilateral filter layers in computed tomography.

BACKGROUND: Computed tomography (CT) is widely used as an imaging tool to visualize three-dimensional structures with expressive bone-soft tissue contrast. However, CT resolution can be severely degraded through low-dose acquisitions, highlighting the importance of effective denoising algorithms. PURPOSE: Most data-driven denoising techniques are based on deep neural networks, and therefore, contain hundreds of thousands of trainable parameters, making them incomprehensible and prone to prediction failures. Developing understandable and robust denoising algorithms achieving state-of-the-art performance helps to minimize radiation dose while maintaining data integrity. METHODS: This work presents an open-source CT denoising framework based on the idea of bilateral filtering. We propose a bilateral filter that can be incorporated into any deep learning pipeline and optimized in a purely data-driven way by calculating the gradient flow toward its hyperparameters and its input. Denoising in pure image-to-image pipelines and across different domains such as raw detector data and reconstructed volume, using a differentiable backprojection layer, is demonstrated. In contrast to other models, our bilateral filter layer consists of only four trainable parameters and constrains the applied operation to follow the traditional bilateral filter algorithm by design. RESULTS: Although only using three spatial parameters and one intensity range parameter per filter layer, the proposed denoising pipelines can compete with deep state-of-the-art denoising architectures with several hundred thousand parameters. Competitive denoising performance is achieved on x-ray microscope bone data and the 2016 Low Dose CT Grand Challenge data set. We report structural similarity index measures of 0.7094 and 0.9674 and peak signal-to-noise ratio values of 33.17 and 43.07 on the respective data sets. CONCLUSIONS: Due to the extremely low number of trainable parameters with well-defined effect, prediction reliance and data integrity is guaranteed at any time in the proposed pipelines, in contrast to most other deep learning-based denoising architectures.

Self-supported amorphous TaNx(Oy)/nickel foam thin film as an advanced electrocatalyst for hydrogen evolution reaction.

Chemical vapor deposited (CVD) amorphous tantalum-oxy nitride film on porous three-dimensional (3D) nickel foam (TaNx(Oy)/NF) utilizing tantalum precursor, tris(diethylamino)(ethylimino)tantalum(V), ([Ta(NEt)(NEt2)3]) with preformed Ta-N bonds is reported as a potential self-supported electrocatalyst for hydrogen evolution reaction (HER). The morphological analyses revealed the formation of thin film of core-shell structured TaNx(Oy) coating (ca. 236 nm) on NF. In 0.5 M H2SO4, TaNx(Oy)/NF exhibited enhanced HER activity with a low onset potential as compared to the bare NF (-50 mV vs. -166 mV). The TaNx(Oy)/NF samples also displayed higher current density (-11.08 mA cm-2vs. -3.36 mA cm-2 at 400 mV), lower Tafel slope (151 mV dec-1vs. 179 mV dec-1) and lower charge transfer resistance exemplifying the advantage of TaNx(Oy) coating towards enhanced HER performance. The enhanced HER catalytic activity is attributed to the synergistic effect between the amorphous TaNx(Oy) film and the nickel foam.

Ultra-Short Laser Surface Properties Optimization of Biocompatibility Characteristics of 3D Poly-ε-Caprolactone and Hydroxyapatite Composite Scaffolds.

The use of laser processing for the creation of diverse morphological patterns onto the surface of polymer scaffolds represents a method for overcoming bacterial biofilm formation and inducing enhanced cellular dynamics. We have investigated the influence of ultra-short laser parameters on 3D-printed poly-ε-caprolactone (PCL) and poly-ε-caprolactone/hydroxyapatite (PCL/HA) scaffolds with the aim of creating submicron geometrical features to improve the matrix biocompatibility properties. Specifically, the present research was focused on monitoring the effect of the laser fluence (F) and the number of applied pulses (N) on the morphological, chemical and mechanical properties of the scaffolds. SEM analysis revealed that the femtosecond laser treatment of the scaffolds led to the formation of two distinct surface geometrical patterns, microchannels and single microprotrusions, without triggering collateral damage to the surrounding zones. We found that the microchannel structures favor the hydrophilicity properties. As demonstrated by the computer tomography results, surface roughness of the modified zones increases compared to the non-modified surface, without influencing the mechanical stability of the 3D matrices. The X-ray diffraction analysis confirmed that the laser structuring of the matrices did not lead to a change in the semi-crystalline phase of the PCL. The combinations of two types of geometrical designs-wood pile and snowflake-with laser-induced morphologies in the form of channels and columns are considered for optimizing the conditions for establishing an ideal scaffold, namely, precise dimensional form, mechanical stability, improved cytocompatibility and antibacterial behavior.

Synthetic Image Rendering Solves Annotation Problem in Deep Learning Nanoparticle Segmentation.

Nanoparticles occur in various environments as a consequence of man-made processes, which raises concerns about their impact on the environment and human health. To allow for proper risk assessment, a precise and statistically relevant analysis of particle characteristics (such as size, shape, and composition) is required that would greatly benefit from automated image analysis procedures. While deep learning shows impressive results in object detection tasks, its applicability is limited by the amount of representative, experimentally collected and manually annotated training data. Here, an elegant, flexible, and versatile method to bypass this costly and tedious data acquisition process is presented. It shows that using a rendering software allows to generate realistic, synthetic training data to train a state-of-the art deep neural network. Using this approach, a segmentation accuracy can be derived that is comparable to man-made annotations for toxicologically relevant metal-oxide nanoparticle ensembles which were chosen as examples. The presented study paves the way toward the use of deep learning for automated, high-throughput particle detection in a variety of imaging techniques such as in microscopies and spectroscopies, for a wide range of applications, including the detection of micro- and nanoplastic particles in water and tissue samples.

Chemokine/Cytokine Levels Correlate with Organ Involvement in PR3-ANCA-Associated Vasculitis.

BACKGROUND: ANCA-associated vasculitis (AAV) is a rare small vessel disease characterized by multi-organ involvement. Biomarkers that can measure specific organ involvement are missing. Here, we ask whether certain circulating cytokines and chemokines correlate with renal involvement and if distinct cytokine/chemokine patterns can differentiate between renal, ear/nose/throat, joints, and lung involvement of AAV. METHODS: Thirty-two sets of Birmingham vasculitis activity score (BVAS), PR3-ANCA titers, laboratory marker, and different cytokines were obtained from 17 different patients with AAV. BVAS, PR3-ANCA titers, laboratory marker, and cytokine concentrations were correlated to different organ involvements in active AAV. RESULTS: Among patients with active PR3-AAV (BVAS > 0) and kidney involvement we found significant higher concentrations of chemokine ligand (CCL)-1, interleukin (IL)-6, IL21, IL23, IL-28A, IL33, monocyte chemoattractant protein 2 (MCP2), stem cell factor (SCF), thymic stromal lymphopoietin (TSLP), and thrombopoietin (TPO) compared to patients without PR3-ANCA-associated glomerulonephritis. Patients with ear, nose, and throat involvement expressed higher concentrations of MCP2 and of the (C-X-C motif) ligand-12 (CXCL-12) compared to patients with active AAV and no involvement of these organs. CONCLUSION: We identified distinct cytokine patterns for renal manifestation and for ear, nose and throat involvement of PR3-AAV. Distinct plasma cytokines might be used as non-invasive biomarkers of organ involvement in AAV.

Photon Statistics of Incoherent Cathodoluminescence with Continuous and Pulsed Electron Beams.

Photon bunching in incoherent cathodoluminescence (CL) spectroscopy originates from the fact that a single high-energy electron can generate multiple photons when interacting with a material, thus, revealing key properties of electron-matter excitation. Contrary to previous works based on Monte Carlo modeling, here we present a fully analytical model describing the amplitude and shape of the second order autocorrelation function (g (2)(τ)) for continuous and pulsed electron beams. Moreover, we extend the analysis of photon bunching to ultrashort electron pulses, in which up to 500 electrons per pulse excite the sample within a few picoseconds. We obtain a simple equation relating the bunching strength (g (2)(0)) to the electron beam current, emitter decay lifetime, pulse duration, in the case of pulsed electron beams, and electron excitation efficiency (γ), defined as the probability that an electron creates at least one interaction with the emitter. The analytical model shows good agreement with the experimental data obtained on InGaN/GaN quantum wells using continuous, ns-pulsed (using beam blanker) and ultrashort ps-pulsed (using photoemission) electron beams. We extract excitation efficiencies of 0.13 and 0.05 for 10 and 8 keV electron beams, respectively, and we observe that nonlinear effects play no compelling role, even after excitation with ultrashort and dense electron cascades in the quantum wells.

Novel diagnostic and therapeutic techniques reveal changed metabolic profiles in recurrent focal segmental glomerulosclerosis.

Idiopathic forms of Focal Segmental Glomerulosclerosis (FSGS) are caused by circulating permeability factors, which can lead to early recurrence of FSGS and kidney failure after kidney transplantation. In the past three decades, many research endeavors were undertaken to identify these unknown factors. Even though some potential candidates have been recently discussed in the literature, "the" actual factor remains elusive. Therefore, there is an increased demand in FSGS research for the use of novel technologies that allow us to study FSGS from a yet unexplored angle. Here, we report the successful treatment of recurrent FSGS in a patient after living-related kidney transplantation by removal of circulating factors with CytoSorb apheresis. Interestingly, the classical published circulating factors were all in normal range in this patient but early disease recurrence in the transplant kidney and immediate response to CytoSorb apheresis were still suggestive for pathogenic circulating factors. To proof the functional effects of the patient's serum on podocytes and the glomerular filtration barrier we used a podocyte cell culture model and a proteinuria model in zebrafish to detect pathogenic effects on the podocytes actin cytoskeleton inducing a functional phenotype and podocyte effacement. We then performed Raman spectroscopy in the < 50 kDa serum fraction, on cultured podocytes treated with the FSGS serum and in kidney biopsies of the same patient at the time of transplantation and at the time of disease recurrence. The analysis revealed changes in podocyte metabolome induced by the FSGS serum as well as in focal glomerular and parietal epithelial cell regions in the FSGS biopsy. Several altered Raman spectra were identified in the fractionated serum and metabolome analysis by mass spectrometry detected lipid profiles in the FSGS serum, which were supported by disturbances in the Raman spectra. Our novel innovative analysis reveals changed lipid metabolome profiles associated with idiopathic FSGS that might reflect a new subtype of the disease.

Microscopic Deformation Modes and Impact of Network Anisotropy on the Mechanical and Electrical Performance of Five-fold Twinned Silver Nanowire Electrodes.

Silver nanowire (AgNW) networks show excellent optical, electrical, and mechanical properties, which make them ideal candidates for transparent electrodes in flexible and stretchable devices. Various coating strategies and testing setups have been developed to further improve their stretchability and to evaluate their performance. Still, a comprehensive microscopic understanding of the relationship between mechanical and electrical failure is missing. In this work, the fundamental deformation modes of five-fold twinned AgNWs in anisotropic networks are studied by large-scale SEM straining tests that are directly correlated with corresponding changes in the resistance. A pronounced effect of the network anisotropy on the electrical performance is observed, which manifests itself in a one order of magnitude lower increase in resistance for networks strained perpendicular to the preferred wire orientation. Using a scale-bridging microscopy approach spanning from NW networks to single NWs to atomic-scale defects, we were able to identify three fundamental deformation modes of NWs, which together can explain this behavior: (i) correlated tensile fracture of NWs, (ii) kink formation due to compression of NWs in transverse direction, and (iii) NW bending caused by the interaction of NWs in the strained network. A key observation is the extreme deformability of AgNWs in compression. Considering HRTEM and MD simulations, this behavior can be attributed to specific defect processes in the five-fold twinned NW structure leading to the formation of NW kinks with grain boundaries combined with V-shaped surface reconstructions, both counteracting NW fracture. The detailed insights from this microscopic study can further improve fabrication and design strategies for transparent NW network electrodes.

Critical Review of Processing and Classification Techniques for Images and Spectra in Microplastic Research.

Microplastic research is a rapidly developing field, with urgent needs for high throughput and automated analysis techniques. We conducted a review covering image analysis from optical microscopy, scanning electron microscopy, fluorescence microscopy, and spectral analysis from Fourier transform infrared (FT-IR) spectroscopy, Raman spectroscopy, pyrolysis gas-chromatography mass-spectrometry, and energy dispersive X-ray spectroscopy. These techniques were commonly used to collect, process, and interpret data from microplastic samples. This review outlined and critiques current approaches for analysis steps in image processing (color, thresholding, particle quantification), spectral processing (background and baseline subtraction, smoothing and noise reduction, data transformation), image classification (reference libraries, morphology, color, and fluorescence intensity), and spectral classification (reference libraries, matching procedures, and best practices for developing in-house reference tools). We highlighted opportunities to advance microplastic data analysis and interpretation by (i) quantifying colors, shapes, sizes, and surface topologies with image analysis software, (ii) identifying threshold values of particle characteristics in images that distinguish plastic particles from other particles, (iii) advancing spectral processing and classification routines, (iv) creating and sharing robust spectral libraries, (v) conducting double blind and negative controls, (vi) sharing raw data and analysis code, and (vii) leveraging readily available data to develop machine learning classification models. We identified analytical needs that we could fill and developed supplementary information for a reference library of plastic images and spectra, a tutorial for basic image analysis, and a code to download images from peer reviewed literature. Our major findings were that research on microplastics was progressing toward the use of multiple analytical methods and increasingly incorporating chemical classification. We suggest that new and repurposed methods need to be developed for high throughput screening using a diversity of approaches and highlight machine learning as one potential avenue toward this capability.