Filament Width Research Articles

Investigation of Gamma-Induced Changes to Screening Currents and AC Losses in Mono- Versus Multi-filamentary REBCO Coated Conductors Using DC and AC Magnetometry

REBCO (rare-earth barium copper oxide) coated conductor tapes are a highly attractive option for magnet materials in future tokamak fusion power plants. However, the threat of intense neutron and gamma radiation, together with AC losses during magnet coil ramping, has raised concerns around magnet coil lifetimes. Irradiation-induced changes to flux creep rate has been identified as a key performance-limiting factor in REBCO tapes at low temperatures and high fields post-irradiation with gamma rays; spontaneous flux creep contributes to hysteretic AC loss in REBCO cables under applied AC fields. Knowing that multi-filamentary tapes are under consideration for tokamaks as an AC loss mitigation, magnetic measurements and gamma irradiation experiments are presented here on striated and mono-filamentary YBCO tapes to investigate the differences in post-irradiation screening currents and AC losses. Reduction in AC losses improved magnetisation critical current density (Jc) retention after 1 MGy in the multi- relative to the mono-filamentary samples. After the 5 MGy dose, striations then made the multi-filamentary tape more susceptible to Jc degradation because of the thinner individual filament width. Scanning transmission electron microscopy analysis on an analogous GdYBCO mono-filamentary tape did not indicate the introduction of nm-scale amorphisation to the active GdYBCO layer after gamma irradiation. A potential theoretical explanation for the underlying mechanism altering the flux-pinning landscape across the REBCO layer surface in gamma-irradiated tapes is discussed. This work concluded that gamma effects on screening current capability should be considered in future tokamak REBCO tape qualification studies.

Automatic Detection and Isolation of Filament Width Deviation During 3-D Printing of Recycled Construction Material

Automatic Detection and Isolation of Filament Width Deviation During 3-D Printing of Recycled Construction Material

Relatedness of hypoxia and hyperthermia tolerances in the Nile tilapia (Oreochromis niloticus) and their relationships with cardiac and gill traits

In fish, thermal and hypoxia tolerances may be functionally related, as suggested by the oxygen- and capacity-limited thermal tolerance (OCLTT) concept, which explains performance failure at high temperatures due to limitations in oxygen delivery. In this study the interrelatedness of hyperthermia and hypoxia tolerances in the Nile tilapia (Oreochromis niloticus), and their links to cardiorespiratory traits were examined. Different groups of O. niloticus (n = 51) were subjected to hypoxia and hyperthermia challenges and the O2 tension for aquatic surface respiration (ASR pO2) and critical thermal maximum (CTmax) were assessed as measurement endpoints. Gill filament length, total filament number, ventricle mass, length and width were also measured. Tolerance to hypoxia, as evidenced by ASR pO2 thresholds of the individual fish, was highly variable and varied between 0.26 and 3.39 kPa. ASR events increased more profoundly as O2 tensions decreased below 2 kPa. The CTmax values recorded for the O. niloticus individuals ranged from 43.1 to 44.8 °C (Mean: 44.2 ± 0.4 °C). Remarkably, there was a highly significant correlation between ASR pO2 and CTmax in O. niloticus (r = −0.76, p < 0.0001) with ASR pO2 increasing linearly with decreasing CTmax. There were, however, no discernible relationships between the measured cardiorespiratory properties and hypoxia or hyperthermia tolerances. The strong relationship between hypoxia and hyperthermia tolerances in this study may be related to the ability of the cardiorespiratory system to provide oxygen to respiring tissues under thermal stress, and thus provides some support for the OCLTT concept in this species, at least at the level of the entire organism.

Numerical Evaluation on Thermal Performance of 3D Printed Concrete Walls: The Effects of Lattice Type, Filament Width and Granular Filling Material

Three-dimensional concrete printing (3DCP) is of great interest to scientists and the construction industry to bring automation to structural engineering applications. However, studies on the thermal performance of three-dimensional printed concrete (3DPC) building envelopes are limited, despite their potential to provide a long-term solution to modern construction challenges. This work is a numerical study to examine the impact of infill geometry on 3DPC lattice envelope thermal performance. Three different lattice structures were modeled to have the same thickness and nearly equal contour lengths, voids, and insulation percentages. Additionally, the effects of filament width and the application of granular insulating materials (expanded polystyrene beads and loose-fill perlite) were also studied. Finally, the efficacy of insulation was established. Results show that void area affects the thermal performance of 3DPC envelopes under stagnant air conditions, while web length, filament width, and contact (intersection) area between the webs and face shells affect the thermal behavior when cavities are filled with insulating materials due to thermal bridging. The thermal efficiency of insulation, which shows the effective use of insulation, varies between 26 and 44%, due to thermal bridges.

Impact of turbidity on the gill morphology and hypoxia tolerance of eastern sand darter (Ammocrypta pellucida).

Anthropogenic stressors such as agriculture and urbanization can increase river turbidity, which can negatively impact fish gill morphology and growth due to reduced oxygen in the benthic environment. We assessed the gill morphology, field metabolic rate (FMR), and two hypoxia tolerance metrics (oxygen partial pressure at loss of equilibrium, PO2 at LOE, and critical oxygen tension, Pcrit) of eastern sand darter (Ammocrypta pellucida), a small benthic fish listed as threatened under the Species at Risk Act in Canada, from rivers in southern Ontario. Field trials were conducted streamside in the Grand River (August 2019; mean NTU 8) and in the comparatively more turbid Thames River (August 2020; mean NTU 94) to test the effect of turbidity on each physiological endpoint. Gills were collected from incidental mortalities and museum specimens, and were assessed using hematoxylin and eosin and immunofluorescent staining. The between-river comparison indicated that turbidity significantly increased interlamellar space and filament width but had no significant influence on other gill morphometrics or FMR. Turbidity significantly increased PO2 at LOE (i.e., fish had a lower hypoxia tolerance) but did not significantly impact Pcrit. Therefore, although turbidity influences hypoxia tolerance through LOE, turbidity levels were not sufficiently high in the study rivers to contribute to measurable changes in gill morphology or metabolism in the wild. Determining whether changes in gill morphology or metabolism occur under higherturbidity levels would help resolve the ecological importance of turbidity on species physiology in urban and agricultural ecosystems.

Developing a data-driven filament shape prediction model for 3D concrete printing

With the growing global need for housing and infrastructure, 3D concrete printing (3DCP) has emerged as an innovative construction method offering several potential benefits including design flexibility, speed, and sustainability. However, enhancing the reliability of 3DCP involves managing a variety of parameters that influence various aspects of the 3D printed structure. Process parameters like nozzle velocity, nozzle diameter, nozzle height, and material flow velocity have a major impact on the structural stability and filament shape. This project aimed to develop fast and accurate data-driven models for predicting and classifying filament shape based on process parameters. A print experiment systematically varied process parameters across 144 samples. The resulting filament geometry (width, height, contact width) was measured and classified by quality. Models were trained on this data to predict filament width, contact width, filament height, and classify filaments. These models can be utilized with any buildable material - a material with a high enough yield stress to bear the weight of upper layers without significant deformation. This condition does not restrict this study’s scope as it is a prerequisite for all 3DCP applications. The models’ robustness and generalizability were confirmed through validation on literature data across various printable materials and setups. These data-driven models can aid in optimizing parameters, generating variable width filaments, and printing non-planar layers. By linking print inputs to filament outputs, this comprehensive modeling approach advances 3DCP research for more reliable and versatile concrete printing.

Ab initio study of quantized conduction mechanism in trilayered heterostructure for scaled down memory device applications

Interface of the layered heterostructure revealing the quantized conductance phenomena which cannot be achieved with either semiconducting layer alone in absence of externally applied electric field has wide range of applications in electronic industry of RRAM devices. A comprehensive analysis of electronic properties of CeO2/Ta2O5/CeO2 trilayered heterostructure has been carried out using first principle calculation employing VASP to explore the state of art of RRAM including barrier height, barrier width, conducting filament width and shape. For better understanding of conduction mechanism involved in RS, the influence of crystalline and amorphous phase of Ta2O5 sandwiched between CeO2 layers is analyzed by potential energy lineups, DOS, isosurface and integrated charge density plots. Origin of quantized states formed near the Fermi level in DOS is provided physically by growth of charge conducting filaments in isosurface charge density plots, and charge redistribution from Bader charge analysis. Outcomes of this study confirmed that with more quantized charge, crystalline Ta2O5 is better for interfacial RRAM devices. Apart from previously available findings, results of this study will provide new route to the potential application of this layered material in electronics especially storage devices.

Advancing scaffold porosity through a machine learning framework in extrusion based 3D bioprinting

Three Dimensional (3D) bioprinting holds great promise for tissue and organ regeneration due to its inherent capability to deposit biocompatible materials containing live cells in precise locations. Extrusion-based 3D bioprinting (EBP) method stands out for its ability to achieve a higher cell release rate, ensuring both external and internal scaffold structures. The systematic adjustment of key process parameters of EBP, including nozzle diameter, printing speed, print distance, extrusion pressure, material fraction, and viscosity allows for precise control over filament dimensions, ultimately shaping the desired scaffold porosity as per user specifications. However, managing these factors with all possible interactions simultaneously to achieve the desired filament width can be intricate and resource intensive. This study presents a novel framework designed to construct a predictive model for the filament width of 3D bioprinted scaffolds for various process parameters. A total of 157 experiments have been conducted under various combinations of process parameters and biomaterial’s weight fraction for this study purpose. A regression-based machine learning approach is employed to develop the predictive model utilizing Adj. R2, Mallow’s Cp, and Bayesian Information Criterion (BIC). Following model development, rigorous experimental validations are conducted to assess the accuracy and reliability of the model. Based on the cross-validation of randomly split test data, Adj. R2 model emerges as the highest performing machine learning model (Mean Squared Error, MSE = 0.0816) compared to Mallow’s Cp and BIC (MSE = 0.0841 and 0.0877, respectively) models. The comparative analysis results between the experimental and model’s data demonstrate that our predictive model achieves an accuracy of approximately 85% in filament width prediction. This framework presents a significant advancement in the precise control and optimization of 3D bioprinted scaffold fabrication, offering valuable insights for the advancement of tissue engineering and regenerative medicine applications.

3D printed piezoelectric composite filament width and height prediction using individual and stacking ensemble of machine learning algorithms

The dimensions of extrusion printed filament determine its processing resolution and efficiency. Filament width and height are related to printing process parameters. BaTiO3/PDMS piezoelectric composite was selected to study the effects of four key process parameters, namely nozzle diameter, nondimensional height, extrusion pressure, and printing speed, on the filament width and height. Five individual machine learning models are established to predict the dimension of printed lines. For the models demonstrating good prediction performance, an ensemble learning model based on stacking method is established. The findings indicate that the prediction performance of ensemble learning surpasses that of individual models. Specifically, the coefficient of determination for predicting filament width and height reaches 0.9370 and 0.9646, respectively.

Design and Fabrication of Flexible Woodpile Structured Nanocomposite for Microwave Absorption Using Material Extrusion Additive Technique

The explosive growth of electronics and the widespread use of transient power sources have given rise to an undesirable and uncontrolled consequence of electromagnetic interference (EMI). It is crucial to address and mitigate the issues caused by EMI by developing effective shielding techniques. The material extrusion additive technique provides a solution through its versatile 3D printing of polymeric ink, offering advantages such as design flexibility, structural complexity, and environmental sustainability. The primary objective of this study is to investigate the rheological properties, electromagnetic properties, and thermal stability of nanocomposites consisting of Polydimethylsiloxane (PDMS) and Multi-Walled Carbon Nanotubes (CNTs). The aim is to utilize these findings for the design and 3D printing of a microwave absorber with high efficiency. Composite inks containing 50 vol% (C50) and 60 vol% (C60) of CNTs exhibit favorable shear-thinning behavior and shape retention. On the other hand, lower CNT percentages result in inconsistent viscosity, rendering the inks non-printable. Thermogravimetry analysis reveals that an increase in CNT vol% leads to a decrease in the thermal stability of 3D-printed PDMS-CNT nanocomposites. Higher CNT proportion enhances electric polarization, and attenuation capacity, as evidenced by measurements of complex permittivity and dielectric loss tangent. X-Ray Diffraction analysis was employed to examine the effect of CNT inclusion in the composites. A woodpile-structured metamaterial microwave absorber based on gradient index (GWMMA) was designed by manipulating geometric parameters and CNT vol%. Fifteen unit cell configurations were generated and subsequently chosen based on their exceptional attenuation capabilities, low impedance, and narrower filament width for simulations. The GWMMA demonstrates exceptional absorption performance, surpassing reflection loss values of −10dB. Incorporating a third filament stacking into the woodpile structure augments its efficacy, yet further additions of stackings result in diminishing returns. Experimental validation of a selected 3D-printed GWMMA structure of C60 with a width of 0.75 mm confirms its absorption capabilities, closely aligning with the simulated results. The GWMMA exhibits promising performance for microwave absorption, with absorption values exceeding 90%. Simulations indicate the adjustability of the GWMMA's bandwidth and absorption capabilities through alterations in array periodicity and cell size. Its spatial scale aligns with sub-wavelength structures, establishing it as a representative Metamaterial Absorber (MMA).

Modulation of thermal stress response by prostaglandins in gills of the blue mussel Mytilus edulis

Mytilus edulis has experienced massive mortality events associated with thermal stress that have been documented in wild as well as cultivated organisms, since this species is traditionally farmed in intertidal areas that are exposed to temperature variations. The stress responses linked to changes in temperature are modulated by prostaglandins (PG), which induce apoptosis, synthesis of heat shock proteins and antioxidant enzymes, among others. PG are mainly synthesized from arachidonic (ARA), eicosapentaenoic (EPA) and docosahexaenoic (DHA), but PG-like compounds can be produced through non-enzymatic oxidation of fatty acids in response to increased reactive oxygen species (ROS). In this study, we applied acute (a single temperature increase of 13 °C, from 12 °C to 25 °C) or chronic (cyclical temperature increases and decreases of 13 °C for eight days) thermal stress to mussels fed a microalga mix of Nannochloropsis oculata and Pavlova lutheri. The response was quantified by measuring PG produced enzymatically by cyclooxygenase (COX) from ARA, EPA, and DHA (PGE2, PGE3, 13-HDHA, respectively), non-enzymatic PG (13,14-dihydro-15-keto-PGE2 PGF3α and 8-isoprostane). PGE2, PGE3, and 13-HDHA levels were higher in the gills of mussels exposed to acute stress compared to chronic stress while 3,14-dihydro-15-keto-PGE2 showed no significant differences as a result of chronic or acute stress. PGF3α had lower levels in mussels exposed to chronic stress compared to those under acute stress. In contrast, 8-isoprostane was significantly higher in mussels exposed to chronic stress compared to acute stress. Mussels exposed to acute stress showed an increase in hemocyte infiltration in the gills, while those exposed to chronic stress showed a decrease in gill filament width compared to mussels submitted to acute stress; both effects are associated with PG modulation. These findings suggest that acute and chronic stressors have distinct effects on lipid composition, prostaglandin levels, and gill filament morphology, highlighting potential adaptations or responses to different stress conditions. Understanding the mechanisms by which PG and PG-like compounds modulate the thermal stress response in mussels will contribute to the understanding of climate change impacts on bivalves and the possible adaptation processes involved.

Material Extrusion Filament Width and Height Prediction via Design of Experiment and Machine Learning.

The dimensions of material extrusion 3D printing filaments play a pivotal role in determining processing resolution and efficiency and are influenced by processing parameters. This study focuses on four key process parameters, namely, nozzle diameter, nondimensional nozzle height, extrusion pressure, and printing speed. The design of experiment was carried out to determine the impact of various factors and interaction effects on filament width and height through variance analysis. Five machine learning models (support vector regression, backpropagation neural network, decision tree, random forest, and K-nearest neighbor) were built to predict the geometric dimension of filaments. The models exhibited good predictive performance. The coefficients of determination of the backpropagation neural network model for predicting line width and line height were 0.9025 and 0.9604, respectively. The effect of various process parameters on the geometric morphology based on the established prediction model was also studied. The order of influence on line width and height, ranked from highest to lowest, was as follows: nozzle diameter, printing speed, extrusion pressure, and nondimensional nozzle height. Different nondimensional nozzle height settings may cause the extruded material to be stretched or squeezed. The material being in a stretched state leads to a thin filament, and the regularity of processing parameters on the geometric size is not strong. Meanwhile, the nozzle diameter exhibits a significant impact on dimensions when the material is in a squeezing state. Thus, this study can be used to predict the size of printing filament structures, guide the selection of printing parameters, and determine the size of 3D printing layers.

Formability of curved multilayer laminates via 3D printing using twisted continuous fiber composites

3D printers can print free-form 3D shapes; however, their mechanical properties are unsatisfactory. 3D printers can print 3D shapes freely but the resulting products exhibit unsatisfactory mechanical properties. 3D printing using CFRTP enables the formation of 3D structures with improved mechanical properties. When molding a structure with curved parts using a continuous carbon-fiber-reinforced thermoplastic (CFRTP) 3D printer, the difference in the inner and outer paths of the filament width during arc printing causes the CFRTP filament to become twisted, resulting in poor molding accuracy. In this study, we evaluated the formability of laminates via 3D printing with twisted CFRTP filaments to reduce the inner and outer path differences. And the maximum change in the filament width, which is defined as the maximum width minus the minimum width in one round of fibers, was defined as the forming accuracy. In the case of single-layer printing, the filament width decreased as the twist angle increased, and the forming accuracy (variation in the filament width) decreased. However, when stacking multiple layers, the maximum change in the filament width was the least when the twist angle was 6°. The discovery of the optimum twist angle at 1 K is the most significant aspect of this study and indicates the possibility of an optimum twist angle for various values of K.

Image-based assessment and machine learning-enabled prediction of printability of polysaccharides-based food ink for 3D printing

Despite the growing demand and interest in 3D printing for food manufacturing, predicting printability of food-grade materials based on biopolymer composition and rheological properties is a significant challenge. This study developed two image-based printability assessment metrics: printed filaments’ width and roughness and used these metrics to evaluate the printability of hydrogel-based food inks using response surface methodology (RSM) with regression analysis and machine learning. Rheological and compositional properties of food grade inks formulated using low-methoxyl pectin (LMP) and cellulose nanocrystals (CNC) with different ionic crosslinking densities were used as predictors of printability. RSM and linear regression showed good predictability of rheological properties based on formulation parameters but could not predict the printability metrics. For a machine learning based prediction model, the printability metrics were binarized with pre-specified thresholds and random forest classifiers were trained to predict the filament width and roughness labels, as well as the overall printability of the inks using formulation and rheological parameters. Without including formulation parameters, the models trained on rheological measurements alone were able to achieve high prediction accuracy: 82% for the width and roughness labels and 88% for the overall printability label, demonstrating the potential to predict printability of the polysaccharide inks developed in this study and to possibly generalize the models to food inks with different compositions.

Magnetic Fields and Fragmentation of Filaments in the Hub of California-X

We present 850 μm polarization and C18O (3-2) molecular line observations toward the X-shaped nebula in the California molecular cloud using James Clerk Maxwell Telescope (JCMT)’s SCUBA-2/POL-2 and HARP instruments. The 850 μm emission shows that the observed region includes two elongated filamentary structures (Fil1 and Fil2) having chains of regularly spaced cores. We measured the mass per unit length of the filaments and found that Fil1 and Fil2 are thermally super- and subcritical, respectively, but both are subcritical if nonthermal turbulence is considered. The mean projected spacings () of the cores in Fil1 and Fil2 are 0.13 and 0.16 pc, respectively. is smaller than 4× the filament width expected in the classical cylinder fragmentation model. The large-scale magnetic field orientations shown by Planck are perpendicular to the long axes of Fil1 and Fil2, while those in the filaments obtained from the high-resolution polarization data of JCMT are disturbed, but those in Fil1 tend to have longitudinal orientations. Using the modified Davis–Chandrasekhar–Fermi method, we estimated the magnetic field strengths (B pos) of the filaments, which are 110 ± 80 and 90 ± 60 μG, respectively. We calculated the gravitational, kinematic, and magnetic energies of the filaments, and found that the fraction of magnetic energy is larger than 60% in both filaments. We propose that the dominant magnetic energy may lead the filament to be fragmented into aligned cores as suggested by Tang et al., and the shorter core spacing can be due to a projection effect via the inclined geometry of the filaments or due to nonnegligible longitudinal magnetic fields in the case of Fil1.

3D printing of cementitious mortar with milled recycled carbon fibres: Influences of filament offset on mechanical properties

This study investigates the effects of layer offset on the mechanical strengths of 3D-printed mortar containing milled recycled carbon fibres (rCF). Compared to previous works, the printing scale of carbon-fibre reinforced mortar is increased to move closer to the stage of practical engineering application. For different fibre content, 1.5 vol% is recommended as the optimum fibre dosage for the mortar printing. Three degrees of layer offset are designed for the unidirectional printing pattern, including 0%, 25% and 50% of the filament width as the nozzle drifting distance. X-ray micro-computed tomography analysis demonstrates the internal pore structures in printed specimens consist of channel pores between filaments and micro pores within filaments. The channel pores are generally less geometrically regular than micro pores. Increasing the offset degree leads to improved compressive and flexural strengths along different loading directions. The increase in the compressive strength is more substantial along the direction of layer deposition and lateral expansion compared to the printing direction. Printed specimens with 25% and 50% layer offset also exhibit a much lower level of anisotropy in compression than those without offset. As the degree of layer offset rises, the total porosity decreases and the volume percentage of micro pores in total pores increases, thereby rendering less severe stress concentration around defects and strengthening the mechanical performance of printed specimens. The experiment results show the 3D-printed mortar containing milled rCF with layer offset, normally serving for self-sensing purpose, has the potential to achieve decent mechanical properties for large-scale industrial printing.

Identifying Suitable Three-Dimensional Bio-Printed Scaffold Architectures to Incubate in a Perfusion Bioreactor: Simulation and Experimental Approaches

Abstract Traditional cell culturing methods are limited in their ability to supply growth medium to cells within scaffolds. To address this, we developed a custom perfusion bioreactor that allows for dynamic medium supply to encapsulated or seeded cells. Our custom-designed bioreactor improves the in vivo stimuli and conditions, which may enhance cell viability and proliferation performance. Some of the efforts include using dual medium tanks to replace the medium without stopping perfusion and a newly designed perfusion chamber that can accommodate an array of cassettes allowing for a wide assortment of scaffold shapes and sizes. In this paper, we explored the response of fluid flow to certain types of scaffold pore geometries and porosities using simulation and experimental approaches. Various pore geometries were considered, such as uniform triangular, square, diamond, circular, and honeycomb having uniform and variable sizes. Finally, bone tissue architecture was mimicked and simulated to identify the impact of fluid flow. Based on the results, optimum pore geometry for scaffolds were determined. We explored real-time fluid flow response on scaffolds fabricated with 8% Alginate, 4% Alginate-4% Carboxymethyl Cellulose (CMC), and 2% Alginate-6% CMC incubated, allowing a constant fluid flow for various periods such as 1, 2, 4, and 8 h. The change of fabricated scaffolds was determined in terms of swelling rate, i.e., change of filament width and material diffusion, i.e., comparison of dry material weight before and after incubation. This comparative study can assist in application-based materials selection suitable for incubating in a perfusion bioreactor.

Effects of pressure and height on printability for soft materials

Extrusion-based printing with soft materials is an additive manufacturing technology, which is widely used in biomedical fields such as skin reconstruction, muscle repair, and cartilage regeneration, etc. Constructing high-precision printed structures and maintaining high cellular bioactivity are key issues in the in vitro construction of tissues and organs using extrusion bioprinting. There are some printing paraments such as pressure, height, nozzle type (eg, length and inner diameter), translational speed, etc. can have a huge influence on the structural fidelity. In this work, we put forward a quantitative test method to evaluate the printing accuracy is influenced by pressure and height. The results show that higher pressure can benefit uniformity (the filament width is equal everywhere), and higher height leads to higher uniformity only in low pressure for paste. This study can provide researchers with the tunning suggestions of printing paraments, which may promote the development of printing accuracy in the future.

Histomorphometric evaluation of 3D printed graphene oxide-enriched poly(ε-caprolactone) scaffolds for bone regeneration

ObjectiveRestoring large boney defects using bone grafts alone is an unpredictable procedure. Biodegradable polymeric scaffolds suffer rapid biodegradation and lack sufficient osteo-conductivity. The aim of this study was to histomorphometrically evaluate three-dimensional printed graphene oxide-enriched poly(ε-caprolactone) (PCL) scaffolds for bone regeneration in a rabbit defect model using two different concentrations of graphene oxide. Basic characteristic properties and mount of new bone regeneration formation were evaluated. Methodstwo concentrations of graphene oxide (1 and 3 wt%) were added to PCL scaffolds using hot blind technique while pure PCL scaffolds served as a control. Laboratory characterization included scanning electron microscopy (SEM), x-ray diffraction analysis (XRD), contact angle, internal porosity, in addition to density measurements. All scaffolds were subjected to biodegradation evaluation and cell cytotoxicity test. In vivo bone regeneration was evaluated in the tibia defect of a rabbit model by measuring the amount of new bone formation (n = 15, ά = 0.05). ResultsSEM images showed slight reduction in pore size and increase in filament width of scaffolds with increasing GO contents. However, the printed scaffolds matched well with the dimensions of the original design. XRD patterns revealed characteristic peaks identifying microstructure of scaffolds. Addition of GO increased crystallinity of the scaffolds. The contact angle and porosity readings indicated reduction in measurements with increased content of GO indicating improved wetting properties while the density followed an opposing pattern. Higher biodegradability values were associated with higher GO content resulting in acceleration of observed biodegradation. The results of cytotoxicity test showed reduction in cell viability with higher GO content. Bone regeneration was significantly enhanced for 1 wt% GO scaffolds compared to other groups as was evident by higher bone density observed in x-ray images and higher amount of new bone formation observed at different time intervals. SignificanceGraphene oxide improved the physical and biological properties of PCL scaffolds and significantly enhanced new bone regeneration.

Characteristic length scales of the electrically induced insulator-to-metal transition

Some correlated materials display an insulator-to-metal transition as the temperature is increased. In most cases, this transition can also be induced electrically, resulting in volatile resistive switching due to the formation of a conducting filament. While this phenomenon has attracted much attention due to potential applications, many fundamental questions remain unaddressed. One of them is its characteristic lengths: What sets the size of these filaments, and how does this impact resistive switching properties? Here, we use a combination of wide-field and scattering-type scanning near-field optical microscopies to characterize filament formation in ${\mathrm{NdNiO}}_{3}$ and ${\mathrm{SmNiO}}_{3}$ thin films. We find a clear trend: Smaller filaments increase the current density, yielding sharper switching and a larger resistive drop. With the aid of numerical simulations, we discuss the parameters controlling the filament width and, hence, the switching properties.