Filament Spreading Research Articles

Machine learning assisted evaluation of the filament spreading during extrusion-based 3D food printing: Impact of the rheological and printing parameters

This study explores the complex relationship between ink properties and process parameters in controlling material spreading during extrusion-based 3D printing, using pectin as model inks. Rheological parameters significantly affect the spreading ratio, with high-concentration inks (above 10 wt%) exhibiting reduced spreading of the printed filament. The study also examines the influence of printing parameters (nozzle diameter, pressure, and speed) on filament spreading. By leveraging machine learning techniques with a range of decision tree models, the relative effect of these factors on the filament spreading is determined. It reveals that viscoelastic parameters account for over 92% importance in the spreading ratio prediction. Extra Trees Regressor (with four features) model possessed the best predictive ability with R2 of 0.9775 (training) and 0.9441 (testing). This novel, multidimensional perspective, which combines experimental insights and predictive modeling, provides a robust framework for precise control over ink deposition. This approach could be highly beneficial for 3D food printing, integrating the power of machine learning into the fabrication of food products with precisely controlled dimensions.

Leading edge maintenance in migrating cells is an emergent property of branched actin network growth.

Animal cell migration is predominantly driven by the coordinated, yet stochastic, polymerization of thousands of nanometer-scale actin filaments across micron-scale cell leading edges. It remains unclear how such inherently noisy processes generate robust cellular behavior. We employed high-speed imaging of migrating neutrophil-like HL-60 cells to explore the fine-scale shape fluctuations that emerge and relax throughout the process of leading edge maintenance. We then developed a minimal stochastic model of the leading edge that reproduces this stable relaxation behavior. Remarkably, we find lamellipodial stability naturally emerges from the interplay between branched actin network growth and leading edge shape - with no additional feedback required - based on a synergy between membrane-proximal branching and lateral spreading of filaments. These results thus demonstrate a novel biological noise-suppression mechanism based entirely on system geometry. Furthermore, our model suggests that the Arp2/3-mediated ~70-80° branching angle optimally smooths lamellipodial shape, addressing its long-mysterious conservation from protists to mammals.

High-resolution extrusion printing of Ti3C2-based inks for wearable human motion monitoring and electromagnetic interference shielding

This work addresses two major challenges of MXene-based printing; that is, its low printing resolution (i.e., filament spreading >120%) and its inability to create structures with simultaneously high electrical conductivity and mechanical flexibility. We first report high-resolution extrusion printing of Ti3C2 and composite of Ti3C2/poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS). The printing has a negligible filament spreading (<25%) and low thickness and width variations (<20%) compared to their average values. We then fabricate Ti3C2/PEDOT:PSS composite structures that possess simultaneously exceptional electrical conductivity and flexibility (conductivity of 1600 ± 400 S/cm for 80 wt% Ti3C2, which can withstand up to 3000 bending cycles). Addressing the two challenges expands the applications of MXene-based printing. For instance, micrometer-thick grids printed with our method show excellent EMI shielding effectiveness and superior specific EMI shielding effectiveness, reaching 38.4 dB and 43,000 dB cm2 g−1 in the case of pure Ti3C2 and 28.1 dB and 32,000 dB cm2 g−1 for the composite containing 80 wt% Ti3C2. The printed structures of pure Ti3C2 also perform as highly-sensitive strain sensors with a gauge factor of 11,300 at a strain of 4%. The prepared sensors are capable of monitoring various human activities, including breathing, facial muscles movements, and talking.

Functional Optimality of the Highly Conserved Arp2/3‑Mediated 70° Branching Angle

Actin-based motility is widespread among eukaryotic cells. Many distinct cell types must undergo migration reliably in order to perform a variety of biological functions. However, the fundamental mechanism by which actin produces force, the Brownian ratchet, carries with it an inherent stochasticity. We aimed to understand how robust migration behavior can arise from stochastic actin polymerization in the context of lamellipodial motility. In previous experimental and theoretical efforts, we developed a stochastic model of the leading edge that faithfully recapitulates the stable lamellipodial shape dynamics observed in migrating cells. The stability of this minimal model, in the absence of additional feedback mechanisms, necessarily implies that lamellipodial maintenance is an intrinsic property of branched actin growth against a membrane. In the present work, we performed a theoretical exploration into the biophysical mechanisms underlying stability in our model. Surprisingly, we find that membrane tension is dispensable for maintaining a stable leading edge, and instead identify lateral filament spreading, mediated by the inherent geometry of branched actin growth, as the critical contributor to lamellipodial stability. Furthermore, we find that the genetically encoded branch geometry (the Arp2/3-mediated 70-80° branching angle, conserved from protists to mammals) maximally suppresses leading edge shape and actin density fluctuations. Taken together, these results contextualize two long-standing experimental observations: First, they suggest that the essential lamellipodial maintenance role of the Arp2/3 complex is rooted in its ability to facilitate filament spreading and suppress stochastic fluctuations. Second, the results hint that the high conservation of the Arp2/3-mediated branching angle may stem from its capacity to optimally perform this smoothing effect. In conclusion, we find that the branched structure of actin at the leading edge naturally quells stochastic fluctuations, thereby representing a novel biological noise-suppression mechanism based entirely on system geometry.

Physical Insights Into the ESD Behavior of Drain Extended FinFETs (DeFinFETs) and Unique Current Filament Dynamics

Single and multi-Fin behavior of drain-extended FinFET (DeFinFET) devices under low and high current injection conditions is studied using detailed 3-D TCAD simulations. For completeness, electrostatic discharge (ESD) behavior of both shallow trench isolation (STI)-type and non-STI-type DeFinFET devices is studied. Under low current injection, junction breakdown, parasitic bipolar turn-on, as well as the onset of space charge modulation and its implications on high current behavior are explored. Under high current injection, the role of space charge modulation in electrothermal instability and filament formation is discussed. Unique filament spreading behavior has been discovered in DeFinFETs. Fin-based construction was found responsible for filament spreading. The interplay among bipolar turn-on, bipolar efficiency, filament density, and nature of filament spreading is explained.

Physics of Current Filamentation in ggNMOS Devices Under ESD Condition Revisited

This paper revisits the physics of current filamentation in grounded-gate NMOS (ggNMOS) devices and presents new physical insights which were not addressed in earlier works. A clear distinction between electrical and thermal instabilities is presented. Moreover, filament dynamics under electrical and thermal instability in both silicided and silicide blocked devices is discussed while highlighting observations which contradict with established theory of current ballasting. Interplay between electrical and thermal instabilities and its dependence on the presence or absence of silicide blocking is explored further. Filament spreading in ggNMOS devices and it is dependence on silicide blocking is discussed. Finally, while using the developed physical insights, missing correlation between TLP and HBM extracted failure current of silicided ggNMOS device is explained.

VOLCO: A predictive model for 3D printed microarchitecture

Material extrusion additive manufacturing is widely used for porous scaffolds in which polymer filaments are extruded in the form of log-pile structures. These structures are typically designed with the assumption that filaments have a continuous cylindrical profile. However, as a filament is extruded, it interacts with previously printed filaments (e.g. on lower 3D printed layers) and its geometry varies from the cylindrical form. No models currently exist that can predict this critical variation, which impacts filament geometry, pore size and mechanical properties. Therefore, expensive time-consuming trial-and-error approaches to scaffold design are currently necessary. Multiphysics models for material extrusion are extremely computationally-demanding and not feasible for the size-scales involved in scaffold structures.This paper presents a new computationally-efficient method, called the VOLume COnserving model for 3D printing (VOLCO). The VOLCO model simulates material extrusion during manufacturing and generates a voxelised 3D-geometry-model of the predicted microarchitecture. The extrusion-deposition process is simulated in 3D as a filament that elongates in the direction that the print-head travels. For each simulation step in the model, a set volume of new material is simulated at the end of the filament. When previously 3D printed filaments obstruct the deposition of this new material, it is deposited into the nearest neighbouring voxels according to a minimum distance criterion. This leads to filament spreading and widening.Experimental validation demonstrates the ability of VOLCO to simulate the geometry of 3D printed filaments. In addition, finite element analysis (FEA) simulations utilising 3D-geometry-models generated by VOLCO demonstrate its value and applicability for predicting mechanical properties. The presented method enables structures to be validated and optimised prior to manufacture. Potential future adaptations of the model and integration into 3D printing software are discussed.

Effect of Filament Spread Behavior on the Structure of Composite Yarns

In this study, three defined spreading types of polyester filaments— evenly divided, one-sided, and tight section types—are adopted to analyze the twisting of model assem blies. The experimental results reveal that filament spreading behavior is the main factor influencing the structure of composite yams. If the polyester multifilament spreads effectively and divides evenly after passing through a spreading electrode, the percentage of the uniformly distributed area of the composite yam structure will be 43.0%.

Characterizing and Modeling Bending Properties of Multiaxial Warp Knitted Fabrics

The bending behavior of multiaxial warp knitted (MWK) fabrics is quite different from that of plain weaves and other apparel materials. According to the bending hysteresis curves obtained from KES-FB-2 (Kawabata's evaluation system), MWK fabric bending involves not only the spreading of filaments in inserting yarns, but also the buckling of inserting yams, which accounts for the more remarkable irregularity and nonsymmetry of MWK fabric bending hysteresis curves compared with those of plain weaves. Furthermore, the inserting yarns not completely parallel to the applied bending moment direction will undergo both bending and torsional deformation during a bending cycle. Experimental observation and theoretical study has shown that the bending paths of those non- orthogonally bent yarn systems follow different cylindrical helices. In this paper, a predictive bending model proves to be applicable in assessing the bending behavior of MWK fabrics in different bending directions, and the bending rigidity corresponding to an arbitrary curvature can be calculated with this model as well. Frictional restraint within fabrics is also discussed.