Fused Deposition Modeling Research Articles

Preparation and assessment of a novel hydrated salt PCM applied for intermittent floor radiant heating systems

Intermittent floor radiant heating is widely employed in building heating systems. However, it suffers large indoor air temperature fluctuations due to its intermission. The integration of phase change material (PCM) can significantly mitigate this issue. In this study, Na2HPO4·12H2O and Na2SO4·10H2O were used as raw materials, with expanded perlite (EP) as the porous medium, to prepare a shaped composite phase change material (EPPCM). This material was then blended into mortar to produce a novel phase change mortar (EPPCM-M). Experiments were carried out to evaluate its heat storage performances. Compared to normal mortar, EPPCM-M of 25 mm thickness mitigates temperature fluctuations, with the peak temperature on the cold end reduced by about 2.5 °C and a slower cooling rate on the hot end. To assess the practical application of EPPCM in buildings, a simulation study was conducted. A room model of 4 × 4 × 3 m was built and subjected to radiant floor heating for 8 h daily, under the winter climate conditions of Shanghai from November 15th to March 14th. The results showed that the EPPCM-M can effectively suppress temperature fluctuations in both the floor surface and average indoor air temperatures. From February 27th to March 5th, the maximum fluctuation of floor surface temperature was reduced by 55.4 %, the maximum fluctuation of average indoor air temperature was reduced by 39.5 %. The application of the EPPCM-M in intermittent floor radiant heating not only ensures indoor thermal comfort but also achieves heat's “peak load shifting”, improving indoor comfort, reducing heating energy consumption, and promoting building energy efficiency.

Versatile immobilization of mimicking peptides on additively manufactured functionalized α-amino acid based poly(ester amide)s

α-Amino acid based polyester amides (AA-PEAs) exhibit remarkable properties, including biocompatibility, biodegradability, flexibility, thermal stability, and mechanical integrity. The incorporation of α-amino acids enhances cytocompatibility, hydrogen bonding, and favorable cell-polymer interactions, making AA-PEAs appealing for biomedical applications, notably tissue engineering. However, addressing complex tissue regeneration requires additional enhancements. Introducing biologically instructive factors, like growth factors and peptides, becomes essential to facilitate cell growth, proliferation, and differentiation.This study explores α-amino acid based functionalized polyester amides (AA-FPEAs) for their potential in tissue engineering, focusing on their underexplored role as thermoplastic resources for fused deposition modeling (FDM). Novel AA-FPEAs with alkyne moieties were synthesized and additively manufactured via FDM, highlighting their structure–property correlation. Employing a facile copper-free click chemistry strategy, we successfully attached a CGRGDS mimicking peptide to AA-FPEAs using UV light and a photoinitiator with water as a solvent. UV–Vis analysis confirmed the feasibility of the click reaction, and TOF-SIMS analysis verified CGRGDS attachment on AA-FPEA films and AM scaffolds. In vitro evaluation further demonstrated that AA-FPEAs support cell growth and proliferation, highlighting their biocompatibility. These findings underscore the potential of AA-FPEAs as versatile functionalized biomaterials for tissue engineering applications.

Impact energy absorption in 3D printed bio-inspired PLA structures

3D printing is an effective technique for designing and producing products with unique shapes that cannot be made using traditional methods. Polylactic acid (PLA) filaments, commonly used in 3D printing, are a promised material for fabricating composites and lightweight structures. This study investigates the fracture and damping properties of biodegradable PLA samples with a bio-inspired structure and different density under dynamical (ballistic) loading. PLA samples were fabricated using a 3D printer and a Fusion Deposition Modeling (FDM) method. A unique computer program for cellular samples with Schwartz-Diamond minimal surface topology was developed. The impact absorption energy under ballistic loading of PLA samples with Schwarz-Diamond surface structure was found to depend on their density and impact velocity. The internal structure of 3D-printed PLA cellular samples with a Schwarz-Diamond triply periodic minimal surface and the fracture mechanism of the cellular samples with different densities were demonstrated using scanning electron microscopy. It was found that the fracture mechanism changed from ductile to quasi-brittle with increasing sample density. This work provides a foundation for understanding the fabrication of plastic cellular products using 3D printing.

Numerical analysis on performance of two-phase vortex-tube

R41 gas and R1234yf droplets are used in the study as working fluids. Three-dimensional computational fluid dynamics is utilized to investigate the behavior of fluids in single-phase and two-phase vortex tubes, as well as the influence of cold flow fraction on the performance of them. The results show that small addition of droplets does not change the special working mechanism of the vortex tube. Two-phase vortex tubes are effective devices that can separate high pressure flow into cold flow and hot flow. But temperature difference at both cold and hot ends in the case of two-phase vortex tube is less than that of single-phase vortex tube at the same cold flow fraction. The maximum cold temperature differences of the single-phase and two-phase vortex tubes are 11.97 K and 10.54 K respectively when μ = 0.3. A maximum hot temperature difference of 29.54 K is achieved in the single-phase vortex tube when μ = 0.9. In contrast, a two-phase vortex tube exhibits a maximum hot temperature difference of 17.11 K at μ = 0.8. Additionally, the peak refrigerating capacity of the single-phase and two-phase vortex tube are 40.47 W and 38.51 W at μ = 0.7.

Combining Micro and Macro Relative Density: An Experimental and Computational Study on Hierarchical Porous 3D‐Printed Polylactic Acid Structures

Polymer foams and cellular solids have gained significant interest due to their enhanced properties. This study introduces a novel approach by employing foamed fused filament fabrication printing of cellular solids. A composite polylactic acid filament containing chemical blowing agents is used to create structures with varying micro relative density, which is examined through scanning electron microscopy and tensile testing, with comparisons made to a Mori Tanaka analytical model and representative volume elements investigation. Two different types of cellular solid structures, specifically body‐centered cubic and Gyroid triple periodic minimal surface structures, have been created with different thicknesses and printed at various temperatures. This is done to attain a range of micro‐ and macroporosity, leading to samples with equal total relative densities. Compression tests, coupled with finite element analysis, provide insights into the influence of each type of porosity. The fabricated specimens exhibit compressive strengths ranging from 1.07 to 79.14 MPa and elastic moduli ranging from 0.064 to 3.35 GPa. The findings suggest that porous structures relying on macroporosity exhibit higher compressive strength, while those relying on microporosity demonstrate more appealing energy absorption properties, particularly under stresses approaching the plateau region.

Hybrid 3D bioprinting for advanced tissue-engineered trachea: merging fused deposition modeling (FDM) and top–down digital light processing (DLP)

In this present study, we introduce an innovative hybrid 3D bioprinting methodology that integrates fused deposition modeling (FDM) with top-down digital light processing (DLP) for the fabrication of an artificial trachea. Initially, polycaprolactone (PCL) was incorporated using an FDM 3D printer to provide essential mechanical support, replicating the structure of tracheal cartilage. Subsequently, a chondrocyte-laden glycidyl methacrylated silk fibroin hydrogel was introduced via top-down DLP into the PCL scaffold (PCL-Sil scaffold). The mechanical evaluation of PCL-Sil scaffolds showed that they have greater flexibility than PCL scaffolds, with a higher deformation rate (PCL-Sil scaffolds: 140.9% ± 5.37% vs. PCL scaffolds: 124.3% ± 6.25%) and ability to withstand more force before fracturing (3.860 ± 0.140 N for PCL-Sil scaffolds vs. 2.502 ± 0.126 N for PCL scaffolds, ***P< 0.001). Both types of scaffolds showed similar axial compressive strengths (PCL-Sil scaffolds: 4.276 ± 0.127 MPa vs. PCL scaffolds: 4.291 ± 0.135 MPa). Additionally, PCL-Sil scaffolds supported fibroblast proliferation, indicating good biocompatibility.In vivotesting of PCL-Sil scaffolds in a partial tracheal defect rabbit model demonstrated effective tissue regeneration. The scaffolds were pre-cultured in the omentum for two weeks to promote vascularization before transplantation. Eight weeks after transplantation into the animal, bronchoscopy and histological analysis confirmed that the omentum-cultured PCL-Sil scaffolds facilitated rapid tissue regeneration and maintained the luminal diameter at the anastomosis site without signs of stenosis or inflammation. Validation study to assess the feasibility of our hybrid 3D bioprinting technique showed that structures, not only the trachea but also the vertebral bone-disc and trachea-lung complex, were successfully printed.

Machine learning-driven prediction of tensile strength in 3D-printed PLA parts

Additive manufacturing (AM) has become a transformative technology in modern production, enabling complex geometric designs with minimal material waste. A significant aspect of AM, particularly in fused deposition modeling (FDM), is the need for precise prediction of mechanical properties, such as ultimate tensile strength (UTS), which is crucial for industrial applications. This study examines whether simple machine learning (ML) algorithms can accurately predict the UTS of 3D-printed polylactic acid (PLA) parts, and evaluates the effectiveness of ML techniques, especially ensemble methods, in enhancing prediction accuracy. To this end, the study compares simple ML algorithms to identify the most accurate model for predicting the UTS of 3D-printed PLA parts. Subsequently, an average ensemble technique combines four ML algorithms, namely categorical boosting (CatBoost), extreme gradient boosting (XGBoost), gradient boosting machine (GBM), and light gradient boosting machine (LGBM), to predict UTS. In this technique, the average predicted UTS values of CatBoost, XGBoost, GBM, and LGBM are taken as the final predicted UTS value. Additionally, 11 ensemble configurations of these algorithms are analyzed to determine the optimized ensemble configuration. The results show that the CatBoost algorithm, with an R2 of 94.46%, achieved the highest predictive accuracy among individual ML algorithms. Moreover, the CatBoost-XGBoost-GBM-LGBM ensemble was the most accurate configuration, achieving an R2 of 98.05% with less than 10% error in predicting 37 external data points not included in the training and testing sets. This study advances predictive modeling in AM by demonstrating that ML, particularly ensemble techniques, can reliably predict material properties, paving the way for more robust applications of AM in industry

Mechanical regulation strategy for heterogeneous piezoelectric semiconductor thermoelectric structure based on energy conversion

The piezoelectric properties inherent in piezoelectric semiconductors facilitate the manipulation of charge carrier redistribution, enabling the fabrication of electronic devices with adjustable characteristics. However, despite this capability, our understanding of the energy conversion and transfer mechanisms within such devices remains limited. By discarding the assumption of low injection and the approximation of depletion layer, a nonlinear model was developed on piezoelectric semiconductor thermoelectric structure (PS-TES), considering the penetration of hot electrons and regulation of mechanical loadings. The presented model reveals that the input electric energy is partitioned, with a portion being converted into electric potential energy stored (EPES) in non-equilibrium carriers and another portion being the energy dissipation (ED) due to the electrothermal action. Furthermore, from an energy conservation standpoint, a interesting competitive phenomenon between electric potential energy conversion and energy dissipation is obtained. The power of external electric energy input and internal electric energy conversion can be manipulated via mechanical loadings, thereby adjusting the energy conversion process of PS-TES. Finally, we found that the compressive loadings can increase EPES and reduce ED, thereby optimizing the cooling effect at cold end. While tensile loadings can reduce EPES and increase ED, thus causing the PS-TES to locally heat up and produce a heating effect. This study potentially offers a means to switch the performance of TES and provides fresh insights into energy conversion processes within piezoelectric semiconductors.

A 3D-printed sensing element based on fiber Bragg grating technology for grasping force measurement in surgical forceps

This study introduced a 3D-printed sensing element based on fiber Bragg grating (FBG) technology to measure grasping forces when integrated into surgical forceps during minimally invasive surgery (MIS). Its design mainly consists of an octagonal-shaped structure with a single FBG suspended within, the first to use fused deposition modeling technique in this application scenario. This novel solution allows improving the design customization and the structural robustness of the proposed sensing element. A finite element model was developed to study the mechanical behavior of the structure under transversal force (F) values experienced during grasping. Thermoplastic polyurethane material as printing filament enhanced the deformation capabilities of the sensor, thereby optimizing its response to F as evidenced by the value of sensitivity to F (i.e., 0.11 nm·N−1). Additionally, the sensing element exhibited a low hysteresis error (always below 14 %). Tests in controlled conditions confirmed the sensor capability to discriminate materials with different stiffness. Furthermore, the sensor was used as the sensing core of a surgical forceps prototype and tested during ex vivo experiments on hepatic, myocardial and spleen tissues simulating a MIS environment. The system was able to measure F during tissue grasping and the real-time feedback improved the tissue holding stability, important for reducing tissue damage risk during MIS procedures.

A Survey of Fused Deposition Modeling (FDM) Technology in 3D Printing

This survey provides a thorough examination of Fused Deposition Modeling (FDM), a prevalent 3D printing technology known for its accessibility and versatility. FDM has emerged as a transformative tool across various industries, including healthcare, aerospace, automotive, and education. This paper reviews recent advancements in FDM technology, focusing on material innovations, process optimization, and application areas. We analyze the benefits and limitations of FDM, including print quality, speed, cost-effectiveness, and environmental impact. Furthermore, we explore emerging trends and future directions in FDM research, highlighting the potential for enhanced customization, sustainability, and integration with other manufacturing technologies. This survey aims to provide a comprehensive understanding of FDM's current landscape and its implications for future developments in 3D printing.

Evaluating the impact of post-processing on the wear and friction properties of polyamide 6 carbon fiber composites produced by fused deposition modeling

The current research addresses the challenges encountered in polyamide 6 carbon fiber composites synthesized by fused deposition modeling. It specifically investigates issues such as inadequate interlaminar bonding and increased void content compared to conventionally manufactured composite components and as-built printed parts. The study focuses on printing pin samples via fused deposition modeling and explores various thermal post-processing methods to reduce void content while preserving dimensional accuracy. To evaluate wear and friction behavior, a pin-on-disc tester was used to test both as-built samples and samples post-heat-treated at 70 °C, 140 °C, and 210 °C. The results indicate that as the applied load increases from 5 to 20 N, both wear rates and friction coefficients increase across all speeds (1–5 m/s). Heating the samples to 70 °C and 140 °C strengthens the interlayer bonding. This significantly improves the maximum wear rates and friction coefficients compared to the as-built samples. However, samples heated to 210 °C do not show much of a change in wear rates or friction coefficients. Samples heated to 210 °C exhibit a decrease in wear rate of 16.87%, 15.82%, and 15.73% for loads ranging from 5 to 20 N, at speeds of 1, 3, and 5 m/s, respectively. This is likely due to pores sealing off and structures binding tightly. The worn surfaces were analyzed using a scanning electron microscope and measured the Shore D hardness of the samples before and after wear testing and documented the results for further analysis. In a scanning electron microscope, samples treated at 210 °C displayed smoother, less worn surfaces. Shore D hardness tests revealed a slightly higher hardness in samples heated to higher temperatures, followed by higher loads and sliding speeds in tribometer tests. This showed that the material was more stable. These post-processing methods significantly advance the development of functional composite elements for superior structural or dynamic performance.

Quasi-static indentation characteristics of foam-filled sandwich composite structures with additively manufactured CFRP and GFRP corrugated cores

This paper presents an experimental investigation on the quasi-static indentation performance of polyurethane (PU) foam-filled carbon fibre-reinforced polymer (CFRP) and glass fibre-reinforced polymer (GFRP) corrugated sandwich composite structures (SCSs) under different indenter tip geometries (conical, trapezoidal, hemispherical, pyramidal, and cylindrical shapes). The SCSs were produced using hybrid manufacturing methods: (1) the facesheets were fabricated using the vacuum-assisted resin infusion (VARI) process, (2) the CFRP and GFRP corrugated cores were additively manufactured using the fused filament fabrication (FFF) process, and (3) the self-expanding PU foam-filled the open spaces in the core. The results elucidated that the indenter tip geometry and core material have a large influence on the indentation performance of SCSs. The cylindrical indenter showed the highest peak load, bending stiffness, and damage severity, while the conical indenter offered the lowest peak load, energy absorption, and damage severity. Among different core materials, CFRP corrugated core SCSs exhibited higher peak loads, specific energy absorption, and damage severity compared to ones with GFRP core. The primary damage modes were observed using an optical microscope, showing facesheet rupture, debonding between facesheets and core, core crushing, foam densification, and shear plugging. Shear plugging is a unique failure mode observed with cylindrical indenter tip geometry due to the blunt edges of the indenter, which induced large damages in SCSs. These findings provide new insight into the design and development of lightweight additively manufactured SCSs, which will benefit a wide range of industries and applications.

Exploring the potential of supercritical carbon dioxide for eugenol impregnation in 3D printed polylactic acid structures

Biocompatible implants are essential for improving human health and longevity. Incorporating bioactive compounds, such as eugenol, into implant materials can improve biocompatibility and therapeutic efficacy. This study examines the effects of supercritical eugenol impregnation on the physical properties of 3D-printed polylactic acid samples produced by Fused Deposition Modeling. Impregnation was performed using a lab-scale high-pressure system, evaluating the impact of impregnation time on eugenol loading, distribution, and morphology. Fourier Transform Infrared spectroscopy confirmed homogeneous eugenol distribution with impregnation times exceeding 1 h, achieving loadings up to 12 wt%. Eugenol was released slowly over extended periods in a phosphate-buffered solution. Impregnated samples displayed more amorphous thermal behavior, with decreased Tg due to the plasticizing effect of the CO₂-eugenol mixture. Mechanical properties were slightly altered, with reduced stiffness and increased toughness. Microscopic deformations induced by impregnation could potentially enhance cellular adhesion, improving biocompatible material performance.

Three-point-supported 2-DOF large-area tilting mirror inspired by a playground facility.

In this paper, we demonstrate a three-point-supported 2D optical scanner designed to enhance the field of view (FoV) and optical scanning angles, and facilitate the development of large mirrors (>10c m). By integrating fused deposition modeling (FDM) 3D printing with electromagnetic driving, we present a cost-effective, large-sized scanning mirror with two-dimensional scanning capabilities. The mirror has an area of 144c m 2, enabling greater light capture for enhanced scanning performance. Under DC driving, the maximum optical scanning angles are 5.99° in the x direction and 12.61° in the y direction. For AC driving, the resonant scanning frequencies are 18.2Hz for the x scan and 19Hz for the y scan, with maximum scanning angles of 7.87° for the x scan and 7.19° for the yscan.

Experimental investigations on metallization in the surface modified additively manufactured plastic substrates using DC sputtering

The application of copper surface coating to plastic structures offers numerous advantages, including high thermal and electrical conductivity, improved mechanical properties, good corrosion resistance, decorative applications, and enhancements in working temperatures. Besides these advantages, producing plastic structures with 3D printing and applying surface coating enables the final structures to become functional plastic structures adaptable to different fields. In this study, 3D plastic structures were produced using the fused deposition modeling method. Pristine, dichloromethane dipping, dichloromethane vapor, cold oxygen plasma, and mechanical abrasion surface treatments were applied to determine the optimal surface treatment between copper and the plastic substrate before copper coating. Subsequently, copper coating on plastic structures was completed using the DC sputtering technique. The surface topography, optical, electrical, and structural properties of the produced plastic structures were examined. According to X-ray diffraction analysis results, the (111), (200), (220), and (311) crystal planes confirm the presence of copper. The electrical conductivity values of the plastic structures reached 7.87 × 105 S/m. Contact angle measurement results indicate that the applied surface treatments increased the contact angles to 88.309°, leading the coated plastic structures to exhibit a more hydrophobic behavior.

Fused Deposition Modeling of Chemically Resistant Microfluidic Chips in Polyvinylidene Fluoride.

Fused deposition modeling (FDM) is well suited for microfluidic prototyping due to its low investment cost and a wide range of accessible materials. Nevertheless, most commercial FDM materials exhibit low chemical and thermal stability. This reduces the scope of applications and limits their use in research and development, especially for on-chip chemical synthesis. In this paper, we present FDM fabrication of microfluidic chips with polyvinylidene fluoride (PVDF) for applications that require high thermal or chemical resistance. Embedded microchannels with a minimum channel width and heights of ~200 µm × 200 µm were fabricated, and the resistance against common solvents was analyzed. A procedure was developed to increase the optical transmission to result in translucent components by printing on glass. Chips for fluid mixing were printed, as well as microreactors that were packed with a catalytically active phase and used for acetal deprotection with a conversion of more than 99%. By expanding the use of fluorinated polymers to FDM printing, previously challenging microfluidic applications will be conducted with ease at the lab scale.

Artificial Neural Network for Benchmarking the Dimensional Accuracy of the PLA Fused Flament Fabrication Process

Fused Deposition Modeling (FDM) is an additive manufacturing technique that uses a 3D printer to extrude molten filament through a nozzle, which moves along the X, Y, and Z axes to create parts with the desired geometry. FDM offers numerous advantages, especially for producing parts with complex shapes, due to its ability to enable rapid and cost-effective manufacturing compared to traditional methods. This study implemented an Artificial Neural Network (ANN) to optimize process parameters aimed at minimizing dimensional inaccuracies in the FDM process. Key parameters considered for optimization included the number of shells, infill percentage, and nozzle temperature. The ANN utilized three algorithms: Scaled Conjugate Gradient, Bayesian Regularization, and Levenberg-Marquardt. Model performance was evaluated based on dimensional deviations along the X and Y axes, with a hidden layer of 25 neurons. Among the algorithms, Scaled Conjugate Gradient provided the most accurate results in minimizing dimensional errors.

Refined dimensional accuracy in FDM components via ensemble weight-optimized surrogates and hybrid NSGA-II-TOPSIS optimization

ABSTRACT In this paper, a novel approach was developed to predict the geometrical deviation and density of fused deposition modeling (FDM) parts and to optimize these outcomes by fine-tuning the relevant process variables. The prediction process utilized an ensemble approach, combining the optimized weighted sum of three individual surrogate models. These models correlate the input variables – nozzle temperature (NT), infill fraction (IF), and print speed (PS) – with the output responses of density, internal ovality (IO), and external ovality (EO). According to the results, the ensemble outperformed the individual surrogates, exhibiting enhanced predictive accuracy. Subsequently, non-dominated sorting genetic algorithm II (NSGA-II), a multi-objective optimization technique, was integrated with the technique for order of preference by similarity to ideal solution (TOPSIS), a multi-criteria decision-making method, to optimize the ensemble of surrogates (EoS) and generate a ranked set of Pareto-optimal solutions. The outcomes from the EoS, combined with the NSGA-II-TOPSIS hybrid optimization process, revealed that the most effective optimal control parameters were approximately 195°C for NT, 50% for IF, and a range of 55–66 mm/min for PS. This hybrid approach affirmed the reliability and robustness of the identified processing parameters for the production of top-quality FDM parts with desired dimensional accuracy and density.

Effect of fused deposition modeling bioprinting variables on damping factor in shape memory structures for in vitro applications

ABSTRACT The aim of this study is to investigate the variation in the shape memory effect in the Tan Delta output parameter of shape memory polymeric stents, fabricated by the bio-FDM process, during a reversible endothermic cycle with changes in the input parameters. Pure polycaprolactone polymer was directly used in this study. The Damping Factor, or Tan Delta, is a key factor in expressing the shape memory effect of the memory stents. For a more accurate evaluation of this effect, SEM tests, uniaxial tensile tests, and dynamic mechanical and thermal analyses were employed. The Tan Delta of the shape memory stents was approximately 18.81%. Surface morphology changes led to approximately a 14.18% variation in elastic properties, as the dynamic molecular motion and polymer chain constraints resulted in increased pressure. It was found that the fabrication input parameters led to approximately a 20% change in the shape memory effect.

Quality Improvement on Mechanical Properties of FDM 3D Printed Triply Periodic Minimal Surfaces (TPMS) Structure for Tissue Engineering Scaffold

Bone tissue engineering is the best alternative to treat large-scale bone defects by developing a scaffold. Many attempts have been made, but mechanical properties are still a significant concern in producing a feasible scaffold. This study aims to optimize the parameters of Fused Deposition Modeling (FDM) 3D printing, specifically layer thickness, flow rate, filling density, and filling pattern. The objective was to improve the compressive strength and Young's modulus of the scaffolds, which are crucial for the effective regeneration of bone tissue. Through this study, it has been found that the significant parameters to develop a feasible scaffold are layer thickness, flow rate, and filling density. By optimizing the parameters to a layer thickness of 0.05 mm, a flow rate of 50%, and a filling density of 100%, the resulting scaffolds exhibited a compressive strength of 0.8329 MPa and a Young's modulus of 16.42 MPa. These values exhibit extraordinary mechanical durability. The study's importance lies in its contribution to advancing more efficient bone scaffolds. These tailored scaffolds, which balance mechanical strength and biological functions, can potentially enhance bone repair and regeneration. This study establishes a foundation to produce more dependable and effective scaffolds, ultimately improving bone regeneration treatments.