Fused Deposition 3D Printing Research Articles

Fused deposition 3D printing of bonsai tree guiding mold based on acrylonitrile-butadiene-styrene copolymer

Fused deposition 3D printing of bonsai tree guiding mold based on acrylonitrile-butadiene-styrene copolymer

11. UPDATED VALIDATION OF 3D PRINTING-BASED TRAINING TOOLS FOR TRANSANAL SURGERY

Abstract Introduction Due to the complexity of colorectal surgery, the development of specialised training tools is necessary to improve the technical skills of surgeons in a controlled environment. In the framework of the MIREIA Project, this study proposes an updated design of a toolkit to provide a safe and effective environment for colorectal surgery training. Methods Work was carried out on the design of a silicone colon model using injection moulds, consisting of two components (the colon model and its wrap), using the fused deposition 3D printing technique. Two layers of silicone were added to simulate the mucosal and muscular layers. A group of surgeons evaluated the formative utility of the model in transanal surgery, performing resection and suturing of polyps inside the model. Results According to the results of the validation study, the silicone colon model showed adequate behaviour during insufflation and a positive haptic response to contact with laparoscopic forceps. This model accurately reproduces the layers of the colon and allows customisation for each patient. In addition, polyp removal is realistic and the elastic layers support stitches, providing greater realism during surgery. Conclusion A realistic simulator has been developed for training in transanal laparoscopic surgery, but improvements in the final design are needed for widespread implementation. The application of an aqueous gel on the mucosal layer is proposed to improve the realism of the training.

Degradation behavior of 2D auxetic structure with biodegradable polymer under mechanical stress

Coronary heart disease is serious harm to human health. Vascular scaffold implantation is the main treatment. Biodegradable polymers are widely used in vascular scaffolds for good biodegradability and biocompatibility. However, whether the mechanical properties and radial expansion ability can successfully implant the scaffold without acute elastic retraction remains to be further studied. Because of the unique deformation mechanism, shear resistance, and resilience, auxetic structures can effectively avoid the restenosis of degraded vascular scaffolds. Firstly, the plane isotropic and plane anisotropic auxetic structural scaffolds were designed. The control structures (traditional structures) scaffolds were taken as the contrast. PCL was used to prepare the vascular auxetic by 3D printing. The printing parameters of fused deposition 3D printing, such as printing temperature, printing speed, and printing pressure, were studied to determine the optimal printing parameters of PCL. A self-assembled cyclic tensile stress loading device was used to investigate the degradation behavior of different scaffolds under different sizes of cyclic tensile stress, such as surface morphology, pH changes, mass loss rate, and mechanical properties. The increase of stress, surface roughness, and mass loss rate of the scaffolds all showed an increasing trend. pH gradually decreased from the fifth week, and the decrease was proportional to the stress. A large level of stress loading intensifies the decline of elastic modulus and the ultimate strength of the scaffold. In conclusion, the increase of periodic tensile stress will accelerate the degradation of scaffolds, and the degradation behavior of scaffolds with different configurations is different. The degradation rate of dilatant scaffolds was higher than that of control scaffolds, and the degradation rate of anisotropic auxetic scaffolds was higher than that of isotropic auxetic scaffolds, which provides a theoretical reference for the application of auxetic structure in the degradation of vascular scaffolds.

Optimized Control Method for Fused Deposition 3D Printing Slice Contour Path Based on Improved Hopfield Neural Network

ABSTRACT This paper presents a novel approach for optimizing the contour path of fused deposition 3D printing slices to mitigate the limitations of inefficiency and time consumption associated with the process. The proposed algorithm leverages the Hopfield Neural Network (HNN) and an improved whale optimization algorithm to plan the printing order of each contour and optimize the network parameters, respectively. In particular, the algorithm transforms the running trajectory planning problem of the assembled tool head into a travel problem, which allows for a more efficient path planning approach. The HNN is then employed to determine the optimal path for each contour, with the network optimization process utilizing a nonlinear weight update method to overcome the drawbacks of the traditional HNN that is prone to generating invalid paths and falling into local optimality during operation. The network optimization process is designed to automatically adjust the link weights between neurons within a specific range, thereby ensuring that the network reaches the desired energy minima and outputs the optimal path for 3D printed slice contours. The proposed algorithm was tested in part printing experiments, and the results demonstrated a significant reduction in single-layer contour path lengths, printing times, and an enhancement in dimensional accuracy and surface quality of the printed parts compared to the traditional parallel scanning method. The proposed algorithm represents a significant contribution to the field of 3D printing, as it provides an efficient and effective approach for optimizing the contour path of fused deposition 3D printing slices. The findings of this study hold significant implications for improving the efficiency and quality of 3D printing and could potentially lead to further advancements in the field.

Methodology for computed tomography characterization of commercially available 3D printing materials for use in radiology/radiation oncology.

3D printing in medical physics provides opportunities for creating patient-specific treatment devices and in-house fabrication of imaging/dosimetry phantoms. This study characterizes several commercial fused deposition 3D printing materials with some containing nonstandard compositions. It is important to explore their similarities to human tissues and other materials encountered in patients. Uniform cylinders with infill from 50 to 100% at six evenly distributed intervals were printed using 13 different filaments. A novel approach rotating infill angle 10o between each layer avoids unwanted patterns. Five materials contained high-Z/metallic components. A clinical CT scanner with a range of tube potentials (70, 80, 100, 120, 140 kVp) was used. Density and average Hounsfield unit (HU) were measured. A commercial GAMMEX phantom mimicking various human tissues provides a comparison. Utility of the lookup tables produced is demonstrated. A methodology for calibrating print materials/parameters for a desired HU is presented. Density and HU were determined for all materials as a function of tube voltage (kVp) and infill percentage. The range of HU (-732.0-10047.4 HU) and physical densities (0.36-3.52g/cm3 ) encompassed most tissues/materials encountered in radiology/radiotherapy applications with many overlapping those of human tissues. Printing filaments doped with high-Z materials demonstrated increased attenuation due to the photoelectric effect with decreased kVp, as found in certain endogenous materials (e.g., bone). HU was faithfully reproduced (within one standard deviation) in a 3D-printed mimic of a commercial anthropomorphic phantom section. Characterization of commercially available 3D print materials facilitates custom object fabrication for use in radiology and radiation oncology, including human tissue and common exogenous implant mimics. This allows for cost reduction and increased flexibility to fabricate novel phantoms or patient-specific devices imaging and dosimetry purposes. A formalism for calibrating to specific CT scanner, printer, and filament type/batch is presented. Utility is demonstrated by printing a commercial anthropomorphic phantom copy.

Fabrication of a simple 3D-printed microfluidic device with embedded electrochemiluminescence detection for rapid determination of sibutramine in dietary supplements.

Thedesign and fabrication of a simple 3D-printed platform with embedded electrochemiluminescence (ECL) detection for sibutramine determination is described. The microfluidic platform was fabricated by the fused deposition 3D-printing technique with polylactic acid filament, facilitated by computer-aided design (CAD). A three-electrode system was integrated into the device using graphene carbon paste as a working electrode, Ag/AgCl wire as a reference, and a graphite rod as a counter electrode. A further modification was carried out by applying bimetallic Au-Pt nanoparticle-supported multi-walled carbon nanotubes (MWCNT-Au-Pt) on the working electrode surface to enhance the electrocatalytic performance by exploiting the unique properties of nanomaterials. The analytical feasibility of the CAD-ECL sensor was tested through its application for the determination of sibutramine in dietary supplements. Under the optimized conditions, based on the enhancing effect of luminol emission, the device exhibited a linear calibration curve of the logarithmic sibutramine concentration versus ECL intensityin the range 5 × 10-3 to 1ngmL-1. The limit of detection was 3pgmL-1 with a relative standard deviation of 1.7% (n = 15). The 3D-printed prototype can be successfully applied to a small-scale analysis in a simple and cost-effective approach.

Study of stress distribution in the various interfaces present in the 3D printing microelectronic systems: Applies to boxes produced by additive manufacturing

Additive manufacturing (AM), also known as 3D printing, enables the construction of customized packaging microelectronic systems that are perfectly tailored to component dimensions and specifications. In fused deposition 3D printing technology (FDM), residual stresses are influenced by printing conditions, which reduce material performance and can lead to geometric distortions. During printing, time and temperature affect the thermomechanical properties and crystallization kinetics of the polymer used in FDM. The aim of this work is to evaluate the residual stress in a sample based on the printing conditions (ambient temperature, printing speed and layer thickness). Six points were selected to calculate and compare the residual stress in the sample, with three points in the first layer and three points in the second. Simulation and modeling are utilized to study the effects of printing conditions on the thermomechanical behavior of semicrystalline polymer for an effective assessment.

Prediction and Analysis of Energy Consumption in Fused Deposition Processing Based on G-code

In order to solve the problem of energy consumption prediction in the fused deposition process, an energy consumption prediction method is proposed by associating G-code files with fused deposition hardware. This method systematically studies the energy consumption in the process of fused deposition 3D printing by analyzing the relationship between G code files and fused deposition 3D printers. Starting from the energy consumption mechanism, a prediction model of fused deposition energy consumption for G code files is proposed. By obtaining the specific parameters of the fused deposition processing equipment and the selected experimental model, the experimental process parameter level is designed, and the orthogonal experiment is carried out to predict the energy consumption of the fusion processing in detail. The verification shows that the method can not only predict an accuracy rate of more than 90%, but also effectively predict the optimal process parameter value, which fully proves that the prediction method has high prediction accuracy and good practicability, and can be used for model processing. Provide tool support for energy consumption prediction before processing, saving production costs.

Experimental Analysis of Polycaprolactone High-Resolution Fused Deposition Manufacturing-Based Electric Field-Driven Jet Deposition

Polycaprolactone (PCL) scaffolds have been widely used in biological manufacturing engineering. With the expansion of the PCL application field, the manufacture of high-resolution complex microstructure PCL scaffolds is becoming a technical challenge. In this paper, a novel PCL high-resolution fused deposition 3D printing based on electric field-driven (EFD) jet deposition is proposed to manufacture PCL porous scaffold structures. The process principle of continuous cone-jet printing mode was analyzed, and an experimental system was constructed based on an electric field driven jet to carry out PCL printing experiments. The experimental studies of PCL-fused deposition under different gas pressures, electric field voltages, motion velocities and deposition heights were carried out. Analysis of the experimental results shows that there is an effective range of deposition height (H) to realize stable jet printing when the applied voltage is constant. Under the stretching of electric field force and viscous drag force (FD) with increasing movement velocities (Vs) at the same voltage and deposition height, the width of deposition lines was also gradually decreased. The width of the deposition line and the velocity of the deposition platform is approximately a quadratic curve. The bending phenomenon of deposition lines also gradually decreases with the increase of the movement velocities. According to the experiment results, a single layer linear grid structure was printed under the appropriate process parameters, with compact structure, uniform size and good straightness. The experimental results verify that the PCL porous scaffold structure can be accurately printed and manufactured.

Polylactide/Carbon Black Segregated Composites for 3D Printing of Conductive Products.

One of the most important directions in the development of additive manufacturing or three-dimensional (3D) printing technologies is the creation of functional materials, which allow not only prototyping but also the manufacturing of products with functional properties. In this paper, poly-lactide acid (PLA) /carbon black (CB) composites with segregated (ordered) structure have been created. Computer simulation based on the Mamunya geometrical model showed that the CB content within φ = 2.5–5 vol.% in the polylactide matrix leads to the formation of a continuous electrically conductive phase with an increase of electrical conductivity σdc above the percolation threshold. The simulation results were experimentally confirmed by optical microscopy and studies of the electrical conductivity of the composites. It was found that increasing CB content from φ = 1 vol.% to φ = 7 vol.% in the composites causes insignificant (due to the segregated structure) phase changes in the polylactide matrix and improves the thermal properties of composites. Electrically conductive filaments for Fused Deposition 3D Printing (FDM) were developed from PLA/CB composites and then 3D printed. A correlation between the electrical conductivity σdc and the CB content φ for base composites, filaments produced from them, and final 3D samples, has been found. Conductivity varies within σdc = 3.1·10−11 − 10·10−3 S/cm for the filaments and σdc = 3.6·10−11 − 8.1·10−4 S/cm for the final 3D-products.

Adaptive Layering Algorithm for FDM-3D Printing Based on Optimal Volume Error.

The characteristics of fused deposition 3D printing lead to the inevitable step effect of surface contour in the process of forming and manufacturing, which affects molding accuracy. Traditional layering algorithms cannot take into account both printing time and molding accuracy. In this paper, an adaptive layering algorithm based on the optimal volume error is proposed. The angle between the normal vector and the layering direction is used for data optimization. The layer thickness is determined by calculating the volume error, and based on the principle of the optimal volume error, the unequal thickness adaptive layering of each printing layer of the model is realized. The experimental results show that the self-adaptive layering algorithm based on the optimal volume error has a better layering effect, greatly improves the forming efficiency and surface forming accuracy, and has a good adaptability to models with complex surfaces.

Numerical Simulations of Components Produced by Fused Deposition 3D Printing.

Three-dimensional printing technology using fused deposition modeling processes is becoming more and more widespread thanks to the improvements in the mechanical properties of materials with the addition of short fibers into the polymeric filaments. The final mechanical properties of the printed components depend, not only on the properties of the filament, but also on several printing parameters. The main purpose of this study was the development of a tool for designers to predict the real mechanical properties of printed components by performing finite element analyses. Two different materials (nylon reinforced with glass or carbon fibers) were investigated. The experimental identification of the elastic material model parameters was performed by testing printed fully filled dog bone specimens in two different directions. The obtained parameters were used in numerical analyses to predict the mechanical response of simple structures. Blocks of 20 mm × 20 mm × 160 mm were printed in four different percentages of a triangular infill pattern. Experimental and numerical four-point bending tests were performed, and the results were compared in terms of load versus curvature. The analysis of the results demonstrated that the purely elastic transversely isotropic material model is adequate for predicting behavior, at least before nonlinearities occur.

3D printed graphene/polyurethane wearable pressure sensor for motion fitness monitoring

The structural design of three-dimensional (3D) flexible wearable sensors using conductive polymer composites is a hot spot in current research. In this paper, honeycomb-shaped flexible resistive pressure sensors with three different support structures were manufactured by using thermoplastic polyurethane and graphene nanoplatelets composites based on fused deposition 3D printing technology. Based on the various 3D conductive network of the sensors, the flexible sensor exhibit excellent piezoresistive performance, such as adjustable gauge factor (GF) (13.70–54.58), exceptional durability and stability. A combination of representative volume element and finite element simulations was used to simulate the stress distribution of sensors with different structures to predict the structure’s effect on the sensor GF. In addition, the sensor can be attached to human body to monitor the body’s swallowing and walking behaviors. The sensor has prospective process applications for intelligent wearable devices.

Experimental updating of a segmented wind turbine blade numerical model using the substructure method

During the development of the wind turbine system, blades are considered as the most critical components. The blades’ dynamic characteristics must be investigated during the design process to improve their mechanical performance. This work presents an experimental updating of a segmented wind turbine blade numerical model. For this purpose, the blade segments were manufactured using the fused deposition 3D printing technology and assembled using a threaded spar and nut. For different values of the segments assembly load, the natural frequencies and damping ratios were identified using the eigensystem realization algorithm method. The dynamic behavior of the segmented blade was examined numerically using the three-node shell element, taking into consideration the additional stiffness generated by the applied assembly load. In this study, numerical and experimental modal analysis were used to identify the first five eigenfrequencies of the blade. To update the numerical model parameters, through the identified experimental results, an iterative method was developed based on the Craig–Bampton substructure approach. Results show that the blade natural frequencies are proportional to the segments assembly load. The application of the proposed method on the segmented blade numerical model updating shows that the present method is computationally efficient.

3D printed bioactive composite scaffolds for bone tissue engineering

Bone health and regeneration is crucial to human survival. With the advancement in the bone research area, bone implants have been under scrutiny to find a better material that could help in bone regeneration and growth. A wide range of material has been studied and examined to find the ideal combination. In this paper, a new blend of Tri-calcium phosphate (TCP), polycaprolactone (PCL) and bovine hydroxyapatite (BHA) was introduced to create scaffolds with fused deposition 3d printing. Effect of BHA concentration as a naturally derived and newcomer 3d printing material was investigated via FTIR, XRD, and SEM analyses. In vitro studies were exhibited that 15% (wt/wt) BHA fabricated composite scaffolds possessed more bioactivity than other cases with increasing proliferation and growth rates.

3D Printed Injection Molding for Prototyping Batch Fabrication of Macroscale Graphene/Paraffin Spheres for Thermal Energy Management

Paraffin is a phase change material that can store thermal energy, and it has been used in a variety of applications. However, the low thermal conductivity of paraffin hinders the further expansion of its use in many applications. Thus, it is of great interest to identify and develop composites that can improve the thermal conductivity of paraffin to maximize its heat capacity. Here, we report a facile fabrication method for producing spherical paraffin/graphene composites with thermal conductivities enhanced by 57%. We used fused deposition 3D printing to build a prototype mold in which spherical paraffin/graphene composites were successfully fabricated.

3D Printing Technology in Design of Pharmaceutical Products.

Three-dimensional printing (3DP) is a novel technology for fabrication of personalized medicine. As of late, FDA affirmed 3D printed tranquilize item in August 2015, which is characteristic of another section of Pharmaceutical assembling. 3DP incorporates a wide range of assembling procedures, which are altogether founded on computer-aided design (CAD), and controlled deposition of materials (layer-by-layer) to make freestyle geometries. Conventionally, many pharmaceutical processes like compressed tablet have been used from many years for the development of tablet with established regulatory pathways. But this simple process is outdated in terms of process competence and manufacturing flexibility (design space). 3DP is a new technology for the creation of plan, proving to be superior for complex products, customized items and items made on-request. It creates new opportunities for improving efficacy, safety, and convenience of medicines. There are many of the 3D printing technology used for the development of personalized medicine on demand for better treatment like 3D powder direct printing technology, fused-filament 3D printing, 3D extrusion printer, piezoelectric inkjet printer, fused deposition 3D printing, 3D printer, ink-jet printer, micro-drop inkjet 3DP, thermal inkjet printer, multi-nozzle 3D printer, stereolithographic 3D printer. This review highlights features how item and process comprehension can encourage the improvement of a control technique for various 3D printing strategies. It is concluded that the 3D printing technology is a novel potential for manufacturing of personalized dose medicines, due to better patient compliance which can be prepared when needed.

Improved part strength for the fused deposition 3D printing technique by chemical modification of polylactic acid

Fused deposition method (FDM) is popular as a plastic 3D printing technique. One of the drawbacks of this technology is its low bonding strength between layers, reducing through‐plane mechanical properties of a part compared with in‐plane strength within the layers themselves. This study focuses on altering the molecular structure of a polylactic acid by chain extension to increase the adhesion strength between layers, quantified by peel testing, in order to increase overall part strength. Four different samples were prepared in a high shear mixer, processed into filament and printed by a FDM‐type 3D printer. These samples were characterized for their thermal, rheological, mechanical and adhesion properties. The findings showed that the chain extender‐modified resins exhibited higher layer‐to‐layer adhesion strength as well as increased viscosity corresponding to an increasing degree of branching. The interlayer diffusion and entanglement of newly created branch chain ends improved bonding between the printed layers resulting in higher tensile properties. POLYM. ENG. SCI., 59:E59–E64, 2019. © 2018 Society of Plastics Engineers

용융 적층식 3D 프린팅의 형태 왜곡현상 유형화를 통한 재현성 향상 방향

용융 적층식 3D 프린팅의 형태 왜곡현상 유형화를 통한 재현성 향상 방향

Phase transitions and structural formation of PEG-PCL-PEG copolymer in the processes of fused deposition 3D printing

In present work the analysis of thermal field distribution and thermal analysis were used to study phase and structural transformations in the block copolymer of polycaprolactone and polyethylene glycol in the process of scaffolds fabrication for tissue engineering using fused deposition modeling. It was shown that the intact polymer has a noticeable thermal history and formed degree of crystallinity which is close to its equilibrium value, while the microstructure of the polymer stays unchanged.