Fused Deposition Modeling Research Articles

Understanding the Significance of Layer Bonding in Melt Electrowriting.

Melt electrowriting (MEW) is a high-resolution additive manufacturing technology capable of depositing micrometric fibers onto a moving collector to form 3D scaffolds of controlled mechanical properties. While the critical role of layer bonding to achieve mechanical integrity in fused deposition modeling has been widely reported, it remains largely unknown in MEW, in part due to a lack of methods to assess it. Here, a systematic framework is developed to unravel the significance of layer bonding in MEW scaffolds and its ultimate effect on their mechanical properties. Results show that printing parameters, scaffold design, and print path have a strong impact on layer bonding strength of poly(ɛ-caprolactone) MEW scaffolds. This study demonstrates that a small increase of 5µm in fiber diameter can enhance the layer bonding strength by as much as 70%, greatly impacting the overall scaffold properties. A method is also established to control MEW scaffold layer bonding using a heated collector. Importantly, this study reveals that scaffold architecture alone is not responsible for the overall mechanical properties. Finally, a method to obtain tailored layer bond strengths within a given scaffold is established. This has significant implications as provides new possibilities to control mechanical properties of MEW scaffolds through layer bonding.

A promising pullulan/PLA composite: Influence of pullulan in the scaffolds morphology constructed by 3D printing

AbstractManufacturing three‐dimensional scaffolds with significant rough and porous structures is advantageous in tissue regeneration approaches influencing cell growth. Thus, this work aims to study the effect of using different Pullulan contents (PULL) in the poly(lactic) acid (PLA) matrix for 3D printing scaffolds. PLA composites filler with PULL (5 and 10% wt.) were prepared in a thermokinetic mixer, extruded in a machine, and then used to print samples using a fused deposition modeling (FDM) 3D printer. The prepared filaments and scaffolds were characterized using Field emission scanning electron microscopy (FESEM), Fourier‐transform infrared spectroscopy (FTIR), thermogravimetry analyses (TGA), water contact angle (WCA), differential scanning calorimetry (DSC), and hardness techniques. The insertion of PULL into the PLA matrix influenced the increase in diameter and roughness, and density reduction of the composite filaments compared to pristine PLA. Furthermore, the filler promoted an increase in thermal stability, shore hardness, and the development of promising morphological characteristics for cell growth because the walls of the scaffolds are more robust and have more regular‐sized holes. The scaffold fabrication reinforced with 10% PULL presented high surface roughness (up to 1022% if compared with pristine PLA), and open pores can be confirmed successfully compared to pristine PLA. Thus, the use of PULL as a filler in a PLA matrix guarantees the development of composite scaffolds with improved morphological and hardness properties, which could allow the possibility of future research into the application of the proposed material (10% wt. PULL) as an ecologically correct and biocompatible alternative for application in tissue engineering.

Detecting Multi-Scale Defects in Material Extrusion Additive Manufacturing of Fiber-Reinforced Thermoplastic Composites: A Review of Challenges and Advanced Non-Destructive Testing Techniques

Additive manufacturing (AM) defects present significant challenges in fiber-reinforced thermoplastic composites (FRTPCs), directly impacting both their structural and non-structural performance. In structures produced through material extrusion-based AM, specifically fused filament fabrication (FFF), the layer-by-layer deposition can introduce defects such as porosity (up to 10–15% in some cases), delamination, voids, fiber misalignment, and incomplete fusion between layers. These defects compromise mechanical properties, leading to reduction of up to 30% in tensile strength and, in some cases, up to 20% in fatigue life, severely diminishing the composite’s overall performance and structural integrity. Conventional non-destructive testing (NDT) techniques often struggle to detect such multi-scale defects efficiently, especially when resolution, penetration depth, or material heterogeneity pose challenges. This review critically examines manufacturing defects in FRTPCs, classifying FFF-induced defects based on morphology, location, and size. Advanced NDT techniques, such as micro-computed tomography (micro-CT), which is capable of detecting voids smaller than 10 µm, and structural health monitoring (SHM) systems integrated with self-sensing fibers, are discussed. The role of machine-learning (ML) algorithms in enhancing the sensitivity and reliability of NDT methods is also highlighted, showing that ML integration can improve defect detection by up to 25–30% compared to traditional NDT techniques. Finally, the potential of self-reporting FRTPCs, equipped with continuous fibers for real-time defect detection and in situ SHM, is investigated. By integrating ML-enhanced NDT with self-reporting FRTPCs, the accuracy and efficiency of defect detection can be significantly improved, fostering broader adoption of AM in aerospace applications by enabling the production of more reliable, defect-minimized FRTPC components.

3D printing of biodegradable biocomposites based on forest industrial residues by fused deposition modeling

This study investigated the impact of industrial forest residues (IFR) type and proportion on 3D-printed biocomposites (BC). Fused deposition modeling (FDM) produced BC containing up to 20 % Jack pine sawdust, wood ashes, cellulose fibers, and polylactic acid (PLA). The BC thermal stability, surface chemistry, microstructure, and physical and mechanical were investigated. Thermal stability investigations revealed that adding IRF resulted in a decline in the PLA degradation temperature, an increase in the residual mass, a decrease in the glass transition temperature, and an improvement in crystallinity. Add IRF to PLA showed an important reduction in ductility, a consistent reduction of the tensile and flexural strengths with increasing proportion but only a slight or a non-significant reduction the modulus of elasticity. Adding forest waste filler to pure PLA increased the water absorption (WA) and dimensional accuracy (TA) of the biocomposites, which was expected due to the hydrophilic character of fillers. The microstructural analysis demonstrated that a higher filler level resulted in a greater porosity, roughness, and visible filler pull-out on the filament and printed parts surfaces. Surface chemistry analysis suggested poor interactions between the PLA and the fillers and consequently poor interfacial adhesion. Furthermore, the rheological investigations confirmed that the complex viscosity and storage modulus of PLA-Jack pine's sawdust and PLA-cellulose fibers increased with filler. In contrast, the PLA-wood ashes showed opposite results. Using 3D-printed biodegradable biocomposites provided a sustainable option for reducing dependence on non-renewable plastic, valorizing the value chain of forest products, and promoting the circular economy.

Comparative analysis of mechanical and drilling properties: Human skull vs. 3D-printed replicas for neurosurgical training

Neurosurgery is one of the most difficult surgical disciplines, making neurosurgical simulation crucial for learners. 3D printing is increasingly used for this simulation due to its accessibility and cost-effectiveness compared to conventional methods. Previous studies have qualitatively evaluated the efficacy of 3D printing models for burr hole and craniotomy simulation using surgeon feedback. This study quantitatively evaluates the mechanical properties of human skulls and compares them with 3D-printed skulls to identify the necessary materials and technologies for accurate replication in neurosurgical training. Vickers hardness, compression, and drilling simulation tests were conducted on human cadaveric skulls and 3D-printed models manufactured using Fused Filament Fabrication (FFF), Stereolithography (SLA), and Material Jetting (MJ) technologies. Uniaxial force during a simulated burr hole procedure was measured as drilling progressed through the outer table (OT), diploë and inner table (IT) of the skull. The results showed that different 3D printing technologies and materials have qualities corresponding to each of the three layers of the human skull. For instance, the White Resin 40 model was the closest match to the OT of human skull, exhibiting the lowest mean difference of drilling modulus of 1.98. The OT of the human skull had a Vickers hardness of 38.6 ± 5 HV0.05. The closest 3D-printed models were SLA White at 16.6 ± 0.3 HV0.05 and Rigid 10K at 65.7 ± 3 HV0.05. In terms of mechanical properties, the human skull demonstrated a compression modulus that closely matched the SkullSTN 2, PC 60, PEEK 40, and PEEK 60, with differences of less than 0.1 GPa. These findings demonstrate the effectiveness of drilling simulation tests in evaluating various materials and infills to refine models before neurosurgeon evaluation, enabling the identification of an optimal 3D-printed training model for simulating burr hole procedures.

Influence of Oligomeric Lactic Acid and Structural Design on Biodegradation and Absorption of PLA-PHB Blends for Tissue Engineering

The advancing development in biomaterials and biology has enabled the extension of 3D printing technology to the bioadditive manufacturing of degradable hard tissue substitutes. One of the key advantages of bioadditive manufacturing is that it has much smaller design limitations than conventional manufacturing and is therefore capable of producing implants with complex geometries. In this study, three distinct blends of polylactic acid (PLA) and polyhydroxybutyrate (PHB) were produced using Fused Deposition Modeling (FDM) technology. Two of these blends were plasticized with oligomeric lactic acid (OLA) at concentrations of 5 wt% and 10 wt%, while the third blend remained unplasticized. Each blend was fabricated in two structural modifications: solid and porous. The biodegradation behavior of the produced specimens was examined through an in vitro experiment using three different immersion solutions: saline solution, Hank’s balanced salt solution (HBSS), and phosphate-buffered saline (PBS). All examined samples were also subjected to chemical analysis: atomic absorption spectroscopy (AAS), scanning electron microscopy (SEM), and energy-dispersive spectrometry (EDS). The results of the degradation experiments indicated a predominantly better absorption capacity of the samples with a porous structure compared to the full structure. At the same time, the blend containing a higher concentration of OLA exhibited enhanced pH stability over the evaluation period, maintaining relatively constant pH values before experiencing a minor decline at the end of the study. This observation indicates that the increased presence of the plasticizer may provide a buffering effect, effectively mitigating the acidification associated with material degradation.

Analysis of Geometrical Accuracy and Surface Quality of Threaded and Spline Connections Manufactured Using MEX, MJ and VAT Additive Technologies

This paper presents the process of manufacturing mechanical joint components using additive manufacturing (AM) techniques such as Material Extrusion (Fused Deposition Modelling (FDM)), Material Jetting (PolyJet), and Vat Photopolymerization (VAT)/Stereolithography (SLA). Using the PolyJet technique and a photopolymer resin, spline and threaded joint components were produced. For comparative analysis, the threaded joint was also fabricated using FDM and SLA techniques. PLA material was used for the FDM technique, while photopolymer resin was utilized for the SLA process. The components produced underwent a surface analysis to evaluate the accuracy of the dimensions in relation to the nominal dimensions. For the spline connection components, the dimensional deviations recorded by a 3D scanner ranged from −0.11 to +0.18 mm for the shaft and up to 0.24 mm for the sleeve. Measurements of screw and nut diameters showed the highest accuracy for screws produced using the PolyJet technique, while the nuts exhibited the best accuracy when fabricated with the SLA method. The profile of the screw threads using a contour gauge revealed the most accurate thread profile on the screw manufactured with the PolyJet technique.

Deformation Evolution and Perceptual Prediction for Additive Manufacturing of Lightweight Composite Driven by Hybrid Digital Twins

This paper proposes a deformation evolution and perceptual prediction methodology for additive manufacturing of lightweight composite driven by hybrid digital twins (HDT). In order to improve manufacturing quality of irregular lightweight composite through boosting conceptual design in aeronautic and aerospace engineering, the HDT meaning hybridization of physical and digital domains, including deformation and energy efficiency can be built, where the essential parameters can be perceptually predicted in advance, by virtue of the fusion of physical sensors and digital information. The long short term memory (LSTM) can be employed to void vanishing gradient problem and improve predicting precision via Recurrent Neural Networks, thereby laying a foundation for the HDT. The diverse manufacturing requirements of different regions are integrated into the parameters designing phase by attaching region weights confirmed via empiricism and in-service simulation. The effects of slicing strategy and external support structures on manufacturing quality are considered from the perspective of improving dimensional accuracy. The manufacturing efficiency and comprehensive costs are accounted as consideration factors, which are perceptually predicted via LSTM. The designed manufacturing parameters through HDT were virtually examined by evaluating the deformation and equivalent stress distributions of fabricated lightweight component with composite material through AM process simulation. The physical experiments were conducted to verify the HDT-based pre-designing and optimization method of manufacturing parameters via fused deposition modeling (FDM). The energy consumption of actual manufacturing process was measured via digital power meter and applied to evaluate accuracy of perceptual prediction outcomes. The dimensional accuracy and distortion distribution of the manufactured lightweight prototype made with composite material were measured through the coordinate measuring machine (CMM) and 3D optical scanner. The proposed method demonstrates effectiveness in improving manufacturing quality and accurately predicting energy consumption, which have been verified with a three-way solenoid valve element, in which the maximum deformation was reduced by 39.78% and the mean absolute percentage error for perceptual prediction was 3.76%.

Processing Parameter Setting Procedure for a Commercial Bowden Tube FDM Printer

Additive manufacturing (AM), especially fused deposition modeling (FDM), has experienced great development and diffusion during recent years. However, it still faces some limitations, such as poor dimensional accuracy or surface defects, the improvement of which motivates the elaboration of the present work. Contrary to an approach based on the optimization of parameters to obtain a single invariant value, the main objective of this study is the design of a procedure that anyone can follow to generate a printing profile for their specific FDM printer, environment, and imposed constraints through the adjustment of some selected parameters in the popular slicing software UltiMaker Cura. The resulting procedure consists of four ad hoc designed specimens and their analysis algorithms, all connected by a general workflow that ensures the correct execution of the procedure. Its applicability and effectiveness have been proved in a case study where a printing profile was developed for the real manufacturing project of a custom 3D object in polylactic acid (PLA), obtaining an improvement of 50% in tolerances and proving that the proposed parameter setting procedure represents a reduction in the setting time and material consumption versus conventional trial and error methodologies.

Evaluating the efficacy of a cost-effective, fully three-dimensional-printed vertebra model for endoscopic spine surgery training for neurosurgical residents.

A fused deposition modeling three-dimensional (3D)-printed model of the L4-5 vertebra for lumbar discectomy was designed. The model included separately printed dura mater, spinal cord, ligamentum flavum, intervertebral disc (from thermoplastic polyurethane), and bony structures (from polylactic acid), and the material cost approximately US$ 1 per model. A simple plumbing endoscope was used for visualization. Dura mater injury was assessed by painting two layers on the dura mater, which peeled off with trauma. Endoscopic spine surgery is a subject of high interest in neurosurgery given its minimally invasive nature; however, it has a steep learning curve. This study evaluated the effectiveness of a cost-efficient 3D-printed model when teaching this technique to neurosurgery residents. Only a few studies have investigated the efficacy of such a model. Eight residents with >2 years of training participated. Residents performed the procedure bilaterally and twice at 1-week intervals. From the 32 surgeries, four were excluded because of facet removal (as it widened the surgical corridor), leaving 28 surgeries for analysis. Initial surgeries demonstrated a mean operation time of 21 minutes 18 seconds (standard deviation [SD], 2 minutes 32 seconds), which improved to a mean of 6 minutes 45 seconds (SD, 37 seconds) in the fourth surgery (F(3, 17)=19.18, p <0.0001), demonstrating a significant reduction in surgical time over successive surgeries. The median area with the paint removed decreased, from 161.80 (85.55-217.83) to 95.13 mm2 (12.62-160.54), (F(2.072, Inf)=2.04, p =0.128); however, this was not significant. Resident feedback indicated high satisfaction with the educational value of the model. The developed fully 3D-printed model provides a viable and scalable option for neurosurgical training programs, enhancing the learning experience while maintaining low costs. This model may be an excellent stepping stone for learning lumbar spine endoscopy, acclimating to the two-dimensional view, progressing to cadaver models, and, eventually, independent surgery.

Investigation of Effect of Part-Build Directions and Build Orientations on Tension-Tension Mode Fatigue Behavior of Acrylonitrile Butadiene Styrene Material Printed Using Fused Filament Fabrication Technology.

This article explores the fatigue characteristics of acrylonitrile butadiene styrene (ABS) components fabricated using fused filament fabrication (FFF) additive manufacturing technology. ABS is frequently used as a polymeric thermoplastic material in open-source FFF machines for a variety of engineering applications. However, a comprehensive understanding of the mechanical properties and execution of FFF-processed ABS components is necessary. Currently, there is limited knowledge regarding the fatigue behavior of ABS components manufactured using FFF AM technology. The primary target of this study is to evaluate the results of part-build directions and build orientation angles on the tensile fatigue behavior exhibited by ABS material. To obtain this target, an empirical investigation was carried out to assess the influence of building angles and orientation on the fatigue characteristics of ABS components produced using FFF. The test samples were printed in three distinct directions, including Upright, On Edge, and Flat, and with varying orientation angles ([0°, 90°], [15°, 75°], [30°, 60°], [45°]), using a 50% filling density. The empirical data suggest that, at each printing angle, the On-Edge building orientation sample exhibited the most prolonged vibrational duration before fracturing. In this investigation, we found that the On-Edge printing direction significantly outperformed the other orientations in fatigue life under cyclic loading with 1592 loading cycles when printed with an orientation angle of 15°-75°. The number of loading cycles was 290 and 39 when printed with the same orientation angle for the Flat and Upright printing directions, respectively. This result underscores the importance of orientation in the mechanical performance of FFF-manufactured ABS materials. These findings enhance our comprehension of the influence exerted by building orientation and building angles on the fatigue properties of FFF-produced test samples. Moreover, the research outcomes supply informative perspectives on the selection of building direction and building orientation angles for the design of 3D-printed thermoplastic components intended for fatigue cyclic-loading applications.

Multifunctional 3D-Printed Thermoplastic Polyurethane (TPU)/Multiwalled Carbon Nanotube (MWCNT) Nanocomposites for Thermal Management Applications

In this work, multiwalled carbon nanotubes (MWCNTs) were melt-compounded into a novel thermal energy storage system consisting of a microencapsulated paraffin, with a melting temperature of 6 °C (M6D), dispersed within a flexible thermoplastic polyurethane (TPU) matrix. The resulting materials were then processed via Fused Filament Fabrication (FFF), and their thermo-mechanical properties were comprehensively evaluated. After an optimization of the processing parameters, good adhesion between the polymeric layers was obtained. Field-Emission Scanning Electron Microscopy (FESEM) images of the 3D-printed samples highlighted a uniform distribution of the microcapsules within the polymer matrix, without an evident MWCNT agglomeration. The thermal energy storage/release capability provided by the paraffin microcapsules, evaluated through Differential Scanning Calorimetry (DSC), was slightly lowered by the FFF process but remained at an acceptable level (i.e., &gt;80% with respect to the neat M6D capsules). The novelty of this work lies in the successful integration of MWCNTs and PCMs into a TPU matrix, followed by 3D printing via FFF technology. This approach combines the high thermal conductivity of MWCNTs with the thermal energy storage capabilities of PCMs, creating a multifunctional nanocomposite material with unique thermal management properties.

Integrated substrate and adsorbent layer additive manufacturing for asymmetrically operating minichannel adsorbent bed

Adsorption heat pumps (AHP) have conventionally used packed bed design, making their operation sluggish leading to difficulty in using heat for the adsorbent regeneration. While thin adsorbent coatings improve the performance of AHPs when implemented in microscale geometries like minichannels, integrating the adsorbent coating procedure into the scaled-up adsorbent bed manufacturing has been impractical because of the finite time required for the coating process. Meanwhile, separately coated plates manifest sealing issues. This research details an innovative avenue to fabricate a unified adsorbent bed integrated with thin adsorbent coatings. Here, a compact adsorbent bed was fabricated through the integration of additive manufacturing using a fused deposition modeling (FDM) 3D printer for the substrate and resin curing for the MIL-101 (Cr) adsorbent layer. The multi-layered bed was designed to exchange heat between heat transfer fluid (HTF) and the passages through which the refrigerant vapor flows. The vapor channels were coated with a MIL-101 (Cr) adsorbent. The research incorporated both experiments and computational models to evaluate the operation of this adsorbent bed through the measurement of pressure during the adsorption and desorption stages for this component. Various HTF temperatures (80 °C − 90 °C) and flow rates (0.125 kg min−1 – 0.25 kg min -1) were tested. The findings revealed the much-desired asymmetrical operation with long adsorption (75–80 % of the cycle time) and short desorption stages (20 %-25 % of the cycle time), opening the possibility of employing a single bed in adsorption cooling systems to produce a near continuous cooling effect leading to more compact AHPs. The computational model developed for this test setup using MATLAB strongly aligned with experimental findings, with an error margin of 4–12 %.

The Abrasive Water Jet Cutting Process of Carbon-Fiber-Reinforced Polylactic Acid Samples Obtained by Additive Manufacturing: A Comparative Analysis

Carbon-fiber-reinforced polymer (CFRP) composites are widely used across industries due to their enhanced strength and stiffness properties. Fused deposition modeling (FDM) enables the cost-effective production of polymer samples, such as carbon-fiber-reinforced PLA (CFR-PLA). However, CFRP’s hardness and anisotropic nature present significant challenges in conventional machining, including rapid tool wear and thermal sensitivity. Consequently, abrasive water jet machining (AWJM) has proven to be an effective alternative for machining CFRP materials, offering benefits such as reduced tool wear, minimized thermal damage, and improved cutting quality. This study focuses on a comparative analysis of the effects of AWJM parameters on PLA and CFR-PLA samples, specifically to evaluate the influence of carbon fiber reinforcement on machining performance. The findings highlight the critical role of reinforcements in machining behavior. The results suggest that optimizing cutting parameters significantly reduces taper formation and improves machining accuracy. In particular, adjustments to process parameters resulted in lower taper angles and reduced surface roughness in the cutting zones of the CFR-PLA samples.

Effects of absorption on the tribological properties of carbon fiber reinforced PA 6 composites manufactured by fused deposition modeling

Abstract The present work studied the water absorption behavior of polymeric composite materials fabricated using 3D printing technology, as well as its effect on their tribological properties. The results showed that the moisture absorption would impair the mechanical properties of polymer matrix and interface bonding between fiber and matrix. As a result, the tensile strength of the fiber reinforced polymer composites (FRPCs) decreases with water absorption. Nevertheless, the effects of moisture absorption on the wear properties of FRPCs are more complicated, which are depending on the fiber length and sliding conditions. With the short fiber reinforcements, moisture absorption deteriorated the wear resistance under all the testing conditions. With the increase of moisture level, more severe fiber damage/removal was observed, associated with the higher wear loss. With a relative high volume fracture of continuous carbon fiber (∼ 35 vol.%), however, the wear resistance of the FRPC increased with moisture level, especially under a relatively low load. Based on microscopic observations, it was proposed that water inside FRPC specimens is able to provide the lubricating and cleaning effects, which contribute to a lower friction and smooth worn surfaces. The work provides new insights into designing and selecting printed polymer materials, subjected to different loading conditions.

Development of Mathematical Function Control-Based 3D Printed Tablets and Effect on Drug Release.

The application of 3D printing technology in drug delivery is often limited by the challenges of achieving precise control over drug release profiles. The goal of this study was to apply surface equations to construct 3D printed tablet models, adjust the functional parameters to obtain multiple tablet models and to correlate the model parameters with the in vitro drug release behavior. This study reports the development of 3D-printed tablets using surface geometries controlled by mathematical functions to modulate drug release. Utilizing fused deposition modeling (FDM) coupled with hot-melt extrusion (HME) technology, personalized drug delivery systems were produced using thermoplastic polymers. Different tablet shapes (T1-T5) were produced by varying the depth of the parabolic surface (b = 4, 2, 0, -2, -4mm) to assess the impact of surface curvature on drug dissolution. The T5 formulation, with the greatest surface curvature, demonstrated the fastest drug release, achieving complete release within 4h. In contrast, T1 and T2 tablets exhibited a slower release over approximately 6h. The correlation between surface area and drug release rate was confirmed, supporting the predictions of the Noyes-Whitney equation. Differential Scanning Calorimetry (DSC) and Scanning Electron Microscope (SEM) analyses verified the uniform dispersion of acetaminophen and the consistency of the internal structures, respectively. The precise control of tablet surface geometry effectively tailored drug release profiles, enhancing patient compliance and treatment efficacy. This novel approach offers significant advancements in personalized medicine by providing a highly reproducible and adaptable platform for optimizing drug delivery.

Silver-Doped Reduced Graphene Oxide/PANI-DBSA-PLA Composite 3D-Printed Supercapacitors.

This study presents a novel approach to the development of high-performance supercapacitors through 3D printing technology. We synthesized a composite material consisting of silver-doped reduced graphene oxide (rGO) and dodecylbenzenesulfonic acid (DBSA)-doped polyaniline (PANI), which was further blended with polylactic acid (PLA) for additive manufacturing. The composite was extruded into filaments and printed into circular disc electrodes using fused deposition modeling (FDM). These electrodes were assembled into symmetric supercapacitor devices with a solid-state electrolyte. Electrochemical characterization, including cyclic voltammetry (CV) and galvanostatic charge-discharge (GCD) tests, demonstrated considerable mass-specific capacitance values of 136.2 F/g and 133 F/g at 20 mV/s and 1 A/g, respectively. The devices showed excellent stability, retaining 91% of their initial capacitance after 5000 cycles. The incorporation of silver nanoparticles enhanced the conductivity of rGO, while PANI-DBSA improved electrochemical stability and performance. This study highlights the potential of combining advanced materials with 3D printing to optimize energy storage devices, offering a significant advancement over traditional manufacturing methods.

Exploring the Impact of 3D Printing Parameters on the THz Optical Characteristics of COC Material.

In terahertz (THz) optical systems, polymer-based manufacturing processes are employed to ensure product quality and the material performance necessary for proper system maintenance. Therefore, the precise manufacturing of system components, such as optical elements, is crucial for the optimal functioning of the systems. In this study, the authors investigated the impact of various 3D printing parameters using fused deposition modeling (FDM) on the optical properties of manufactured structures within the THz radiation range. The measurements were conducted on 3D printed samples using highly transparent and biocompatible cyclic olefin copolymer (COC), which may find applications in THz passive optics for "in vivo" measurements. The results of this study indicate that certain printing parameters significantly affect the optical behavior of the fabricated structures. The improperly configured printing parameters result in the worsening of THz optical properties. This is proved through a significant change in the refractive index value and undesirable increase in the absorption coefficient value. Furthermore, such misconfigurations may lead to the occurrence of defects within the printed structures. Finally, the recommended printing parameters, which improve the optical performance of the manufactured structures are presented.

Comparative study of blending techniques in polylactic acid/cellulose nanofibrils green composites for benchtop 3D printing filaments

AbstractAdditive manufacturing for polylactic acid (PLA) reinforced with cellulose nanofibrils (CNF) could unlock fabrication of specialized and user‐specific biomedical devices. However, the process of combining PLA and CNF is challenging and proves complicated with possible irreversible CNF agglomeration and organic solvents leftover, particularly when involving solvent‐casting technique. Direct melt‐blending can mitigate these issues, but there are few reports of a single‐step melting and extrusion process to produce ready‐to‐use 3D printing filaments. This study compares the distribution of CNF fillers within the PLA matrix in PLA/CNF composites made by direct melt‐blending into filaments using a benchtop filament maker, and by solvent‐casting followed by extrusion into filaments. The filaments were 3D‐printed via fused deposition modeling (FDM), followed by tensile testing, morphology, and other characterizations. Uneven filament diameters were observed for the composite filaments prepared via solvent‐casting because of severe agglomeration, resulted in poor printability and tensile properties of filaments and 3D‐printed samples. Direct melt‐blended filament diameters were consistent, resulted in only slight decrease of tensile properties compared to pure PLA, contributing to the highest maximum tensile strength of 3D‐printed sample of 51.47 ± 1.73 MPa at 5% CNF loading. Morphology revealed good integration of CNF into PLA matrix starting at 3% CNF loading. Direct melt‐blending was comparable to the conventional methods, which enables simpler PLA/CNF composite preparation especially for 3D printing.Highlights Better dispersibility achieved by direct melt‐blending than by solvent‐casting. PLA/CNF filaments produced via solvent‐casting suffered severe agglomeration. Direct melt‐blended PLA/CNF5% yielded the highest maximum tensile strength. Morphology reveals good CNF‐PLA integration starting at 3% of CNF loading. Worsened agglomeration causing increased number of voids observed at 10% CNF.

Graphene Microflower by Photothermal Marangoni-Induced Fluid Instability for Omnidirectional Broadband Photothermal Conversion.

2-D carbon-based materials are well-known for their broadband absorption properties for efficient solar energy conversion. However, their high reflectivity poses a challenge for achieving efficient omnidirectional light absorption. Inspired by the multilevel structures of the flower, a Graphene Microflower (GM) material with gradient refractive index surface was fabricated on polymer substrates using the UV-intense laser-induced phase explosion technique under the synergistic design of the photothermal Marangoni effect and the fluid instability principle. The refractive index gradient reduces light reflection and absorbs at least 96% of light at incident angles of 0-60° across the entire solar wavelength range (200-2500 nm). Over 90% absorption even at 75° angle of incidence. The light absorption is enhanced by the multiple interferometric phase cancelation and localized surface plasmon resonance, resulting in a steady-state temperature 60 °C higher than ambient conditions under one solar irradiation. The max rate of temperature rise can reach up to 62 °C s-1. The device is then integrated at the hot end of the temperature difference generator at high altitude to ensure continuous and efficient power generation, producing a steady-state power of 196 mW.