Optimal Printing Research Articles

On the optimization of fatigue limit in additively manufactured fiber reinforced polymer composites

Abstract This study uses the Taguchi optimization methodology to optimize the fatigue performance of short carbon fiber-reinforced polyamide samples printed via fused deposition modeling (FDM). The optimal printing properties that maximize the fatigue limit were determined to be 0.075 mm layer thickness, 0.4 mm infill line distance, 50 mm/s printing speed, and 55 °C chamber temperature with layer thickness being the most critical parameter. To qualify fatigue endurance limit, the energy dissipation in uniaxial fatigue was quantified by using hysteresis energy and temperature rise at steady state. From these results, the fatigue limit for a specimen printed with optimized printing parameters was predicted to be 69 and 70 MPa from hysteresis energy and temperature rise at steady state methods, consecutively, and it was experimentally determined to be 67 MPa. This work demonstrates the effectiveness of the Taguchi optimization method when applied to additive manufacturing and the swift ability to predict the fatigue limit of a material with only one specimen to produce optimal additively manufactured components for industrial applications, as validated by experimental fatigue testing.

Impact of disintegrants on rheological properties and printability in SSE 3D printing of immediate-release formulations.

This study investigates the effects of disintegrants sodium starch glycolate (SSG) and crospovidone (CP) on the printability, rheological properties, and disintegration time of agar and hydroxypropyl methylcellulose (HPMC)-based formulations designed for semi-solid extrusion. Printability was assessed by measuring the dimensional accuracy of manually extruded filaments. Rheological analysis was performed using oscillatory measurements. Principal component analysis (PCA) and Spearman correlation analysis identified three key components (phase angle, critical strain, and elastic modulus) that explained the total variance in the rheological dataset. A 2 x 32 factorial design was employed to evaluate the impact of CP, SSG, and HPMC on these rheological parameters, as well as on printability and disintegration time. Results indicated that formulations containing HPMC and SSG generally exhibited better printability. Formulations containing CP achieved satisfactory printability only when SSG or HPMC was included. The optimal printability and rheological properties were achieved with formulations containing 5 % CP and 10 % SSG. Linear regression models correlated geometric volumes of the model and pycnometric volumes of printed objects, with validation showing that predicted masses were within a 95 % confidence interval of measured values for various shapes. All formulations demonstrated immediate-release properties, confirming the successful fabrication of personalised immediate-release dosage forms using semi-solid extrusion technology.

Numerical simulation of radiotherapy beam interaction with soft tissues and PLA plastic for 3D printing of dosimetric phantoms

Introduction. In the development of new methods of radiotherapy, studies of the biological effects of sparsely (photons, electrons) and densely (protons, ions) ionizing radiation are relevant. Reproducibility is a challenge in preclinical studies. Dosimetric phantoms of laboratory animals are an effective tool for dose assessment, facilitating standardization of tests conducted under different conditions. existing phantoms often fail to address radiobiological issues like placing of biological samples or dosimetry detectors. A method for manufacturing dosimetric phantoms must be developed to accurately manufacturing products and modify their design in accordance with the task. Aim. This study develops a numerical model to simulate the interaction of photon, electron and proton therapeutic beams with 3D-printed PLA plastic samples and to determine the optimal 3D printing parameters for imitating soft tissues. Material and Methods. Fused filament fabrication proposed as effective means of creating such devices, given that the majority of polymers exhibit properties closely aligned with those of biological tissues, are employed in the manufacture of standard phantoms. A major advantage of 3D printing is the ability to make items with different specifications. Numerical simulation was employed to investigate the interaction of PLA plastic with an ionizing radiation used in radiotherapy. Results. the calculated depth dose distributions of different types of radiation in soft tissues and PLA plastic of varying densities were obtained. It was demonstrated that for adipose imitation using photons and electrons, it is necessary to utilise PLA plastic 3D-printed samples with a density of 0.91 g/cm³ (fill factor of 75 %); for muscle – 1.06 g/ cm³ (fill factor of 88 %). For proton and carbon ion, the density of PLA plastic samples for adipose imitation was determined to be 0.97 g/cm³ (fill factor of 80 %); for muscle – 1.11 g/cm³ (fill factor of 93 %). Conclusion. The study demonstrates that the interaction of PLA plastic with rarely and densely ionizing radiation may be differed. This is a crucial consideration when planning experiments using solid-state dosimetric phantoms.

Melt electrowriting of hydrophilic/hydrophobic multiblock copolymers for bone tissue regeneration.

Bone-healing complications can occur due to large bone defects or an insufficient bone regeneration capacity. Melt electrowriting (MEW) is a potential candidate for manufacturing synthetic scaffolds that may resolve bone-healing complications. MEW can exploit various biocompatible polymers with a wide range of tissue engineering applications. Poly (ethylene oxide terephthalate)-poly(butylene terephthalate) (PEOT/PBT), a multiblock copolymer family, has emerged as a promising biomaterial to guide cell behavior, particularly in promoting bone differentiation. The polymer is known for its tunability by varying the PEOT/PBT weight ratios to influence the chemical, physical and mechanical properties. Four carefully selected PEOT/PBT compositions investigated in this study with the poly (ethylene oxide terephthalate) content ranging from 36 and 65wt%. Detailed rheological characterization was performed to determine the optimum printing temperature, followed by optimizing the MEW parameters to fabricate a well-defined and layer-by-layer scaffold for each copolymer composition. The effect of distinct physicochemical properties on cell behavior was also investigated using MG63 cells on both 2D films and MEW scaffolds. MEW scaffolds made from each polymer compositions show good cell attachment and proliferation along with flattened cell morphology in contrast with highly varied performance on 2D films. In addition, the in vitro bioactivity test using simulation body fluid reveals the formation of bone-like apatite layer formation on the MEW scaffolds made from high molecular weight and poly (ethylene oxide terephthalate) composition.

Next-generation cybersecurity strategies for 3D printing in high-intensity manufacturing

Abstract This research examines the key factors that influence optimal results in 3D printing, including print speed, temperature, layer thickness and material selection. Specifically, it explores the impact of materials such as acrylonitrile butadiene styrene (ABS), nylon, polylactic acid (PLA), and polyethylene terephthalate glycol (PETG) on the 3D printing process and the decision-making involved in achieving the best results. It provides a comprehensive review of the impact of these variables on print quality, drawing on existing studies and experimental data. The findings indicated that print speed of 66 mm s−1, temperature of 218 °C, layer thickness of 0.2 mm and use of PLA material gave the best results. In addition, the research explores the use of Support Vector Machine (SVM) modeling to predict and improve print quality based on these parameters. Research confirms that through statistical analysis of test data, optimal print settings can be effectively identified. Beyond print quality, the research also addresses critical cybersecurity vulnerabilities in 3D printing systems, particularly related to their integration with IT networks. It highlights the importance of analyzing network traffic to detect vulnerabilities, improve system performance, and strengthen cybersecurity measures. The application of machine learning techniques for anomaly detection is explored as a means of developing risk management strategies and ensuring compliance with auditing standards. Finally, the research discusses the role of blockchain technology in securing machine-to-machine communication (M2M) within the 3D printing environment, as well as ensuring data integrity and confidentiality.

Additively manufactured conductive and dielectric 3D metasurfaces for independent manipulation of broadband orbital angular momentum

Recent developments in conductive and dielectric multi-material additive manufacturing have generated significant interest for their potential to enhance the performance of electronic devices. Lights-out digital manufacturing, a sophisticated multi-material printing technique, facilitates the seamless sintering of silver nanoparticles and acrylate inks, enabling the creation of functional electronic devices. In this study, the LDM process is utilized to prototype intricate 3D metasurface designs. A comprehensive analysis of the properties of the printed materials confirms the practicality of this multi-material printing approach. The research examines various element distributions within multi-metal layer structures, including carbon, phosphorus, oxygen, sulfur, and fluorine, to investigate the interfaces between conductive and dielectric structures. In addition, the conductivities of silver nanoparticle inks at different curing temperatures are studied to identify optimal printing conditions. Both the conductive and dielectric inks exhibit precisely controlled particle sizes and exceptional stability, which are critical for accurate additive manufacturing. Using this sophisticated printing solution, the paper presents a broadband 3D metasurface engineered to independently manipulate two distinct orbital angular momentum states in the V-band (60–70 GHz) and W-band (79–90 GHz), suitable for high-speed wireless communications. The integration of deep neural networks helps reduce the phase coupling between the frequency bands, enabling independent control of the OAM states. The structure of the dual-band metasurface features four distinct silver layers yet is fabricated on a single ultra-thin planar substrate, demonstrating its potential for applications in future wireless communication systems.

Study of the Interplay Among Melt Morphology, Rheology and 3D Printability of Poly(Lactic Acid)/Poly(3-Hydroxybutyrate-Co-3-Hydroxyvalerate) Blends.

Polymeric materials made from renewable sources that can biodegrade in the environment are attracting considerable attention as substitutes for petroleum-based polymers in many fields, including additive manufacturing and, in particular, Fused Deposition Modelling (FDM). Among the others, poly(hydroxyalkanoates) (PHAs) hold significant potential as candidates for FDM since they meet the sustainability and biodegradability standards mentioned above. However, the most utilised PHA, consisting of the poly(hydroxybutyrate) (PHB) homopolymer, has a high degree of crystallinity and low thermal stability near the melting point. As a result, its application in FDM has not yet attained mainstream adoption. Introducing a monomer with higher excluded volume, such as hydroxyvalerate, in the PHB primary structure, as in poly(hydroxybutyrate-co-valerate) (PHBV) copolymers, reduces the degree of crystallinity and the melting temperature, hence improving the PHA printability. Blending amorphous poly(lactic acid) (PLA) with PHBV enhances further PHA printability via FDM. In this work, we investigated the printability of two blends characterised by different PLA and PHBV weight ratios (25:75 and 50:50), revealing the close connection between blend microstructures, melt rheology and 3D printability. For instance, the relaxation time associated with die swelling upon extrusion determines the diameter of the extruded filament, while the viscoelastic properties the range of extrusion speed available. Through thoroughly screening printing parameters such as deposition speed, nozzle diameter, flow percentage and deposition platform temperature, we determined the optimal printing conditions for the two PLA/PHBV blends. It turned out that the blend with a 50:50 weight ratio could be printed faster and with higher accuracy. Such a conclusion was validated by replicating with remarkable fidelity high-complexity objects, such as a patient's cancer-affected iliac crest model.

Maximizing sorghum proteins printability: Optimizing gel formulation and 3D-printing parameters to develop a novel bioink.

The objective of this study was to form sorghum protein gels and explore their application in 3D food printing. Sorghum proteins were used to prepare gels with concentrations of 15 %, 20 %, 25 %, 30 %, and 35 % (w/w) in 70 % ethanol. The gels were evaluated for their rheological and textural properties and utilized as bioinks for 3D printing. Gels with 35 % and 15 % (w/w) protein concentrations exhibited poor texture and rheological properties, while gels with 20-30 % (w/w) showed better 3D printability. The optimal printing speed was 20 mm/s, which improved shape accuracy and reduced fusion issues compared to lower speeds. The best results were achieved with a 25 % protein and a 0.64 mm nozzle size, aligning closely with the digital design. SEM images confirmed gel network formation, chemical analysis showed increased β-sheet structure after gelation, and X-ray diffraction indicated an amorphous structure. These findings highlight the influence of protein concentration on gel texture and rheological properties, and the impact of printing speed and nozzle size on the printability and structural integrity of sorghum-protein gels. Overall, this study developed a novel hydrophobic bioink based on sorghum proteins for 3D food printing for the first time, which can find various food and pharmaceutical applications.

Mechanical behavior analysis of additively manufactured parts using the Taguchi method and artificial neural networks

Purpose Acrylonitrile butadiene styrene is an important material in 3D printing due to its strength, durability, heat resistance and cost-effectiveness. These properties make it suitable for various applications, from functional prototypes to end-use products. This study aims to model and predict the mechanical properties of acrylonitrile butadiene styrene parts produced using the fused deposition modeling process. Design/methodology/approach The experiment was carefully designed to determine the optimal print parameters, including layer thickness, nozzle temperature and infill density. Tensile tests were performed on all printed samples following industry standards to gauge the mechanical properties such as elastic modulus, ultimate tensile strength, yield strength and breakpoint. Taguchi optimization and variable analysis were used to explore the relationship between mechanical properties and print parameters. Furthermore, an artificial neural network (ANN) regression model was implemented to predict mechanical properties based on varying print conditions. Findings The results demonstrated that layer thickness has the most significant influence on mechanical properties when compared to other print conditions. The optimization approaches indicated a clear relationship between the selected print parameters and the material’s mechanical response. For acrylonitrile butadiene styrene material, the optimal print settings were determined to be a 0.25 mm layer thickness, a 270 °C nozzle temperature and a 30 % infill density. Moreover, the ANN model notably excelled in predicting the yield strength of the material with greater accuracy than other mechanical properties. Originality/value Comparing the accuracy and capabilities of the Taguchi and ANN models in analyzing mechanical properties, it was found that both models closely matched the experimental data. However, the ANN model showed superior accuracy in predicting tensile outcomes. In conclusion, while the ANN model offers higher predictive accuracy for tensile results, both Taguchi and ANN methods are effective in modeling the mechanical properties of 3D-printed acrylonitrile butadiene styrene materials.

Fused deposition modeling process parameter optimization on the development of graphene enhanced polyethylene terephthalate glycol

This study investigates the production of graphene-enhanced polyethylene terephthalate glycol (G-PETG) components using fused deposition modeling (FDM) and evaluates their mechanical properties, contributing to the advancement of additive manufacturing. Trials demonstrated notable improvements in mechanical performance, with optimal printing parameters identified using the Spice Logic Analytical Hierarchy Process (AHP). The effectiveness of this methodology is further compared with the Fuzzy Analytic Hierarchy Process (FAHP) combined with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The study revealed significant enhancements, with the ultimate tensile strength (UTS) reaching 69.1 MPa, an average Young’s modulus of 735.6 MPa, and an ultimate compressive strength (UCS) of 85.3 MPa. These findings provide valuable insights into optimizing techniques for improving the mechanical performance of G-PETG components, advancing material applications in various industries.

Interlayer temperature optimisation: an approach to maximising strength in the large-scale additive manufacture of fibre-reinforced PETG

Purpose The purpose of this study is to establish a reproducible method for quantifying the anisotropy between printed layers based on interlayer temperature and, using this information, provide recommendations for maximising print strength. Fibre-reinforced polymers are gaining popularity in large-scale material extrusion, which involves the layer-by-layer deposition of melted polymeric granulates. However, the mechanical performance of 3D printed components is highly influenced by the quality of the interfacial bond between layers. Material data sheets often do not report the extent of this anisotropy, thereby making it challenging to account for during the design stage without mechanical characterisation. Design/methodology/approach This study investigates the effect of the temperature at the interface between layers on the ultimate tensile strength of 3D printed parts made with post-industrial polyethylene terephthalate glycol. Findings This study identifies an optimal previous layer temperature (Tp) of 130 ± 10°C, where interlayer bonding and material properties are maximised. An upper limit of 150°C is identified to avoid material sagging and a critical lower bound of approximately 113°C for achieving at least 80% of the maximum part strength. Moreover, this study underscores the importance of considering the effective cross-sectional area due to the ridged surface of printed samples. Recommendations include the use of infrared heat lamps for temperature control to ensure sustained interlayer bonding. Research limitations/implications The research does not address long-term effects and environmental factors affecting material properties, suggesting these as areas for future research. Originality/value This study’s findings are instrumental in establishing optimal printing parameters for large-scale material extrusion, thereby improving the reliability of 3D printed parts in industries like manufacturing and civil engineering.

Optimization of process parameters in 3D-nanomaterials printing for enhanced uniformity, quality, and dimensional precision using physics-guided artificial neural network

Pneumatic 3D-nanomaterial printing, a prominent additive manufacturing technique, excels in processing advanced materials like MXene, crucial for applications in nano-energy, flexible electronics, and sensors. A key challenge in this domain is optimizing process parameters—applied pressure, ink concentration, nozzle diameter, and printing velocity—to achieve uniform, high-quality prints with the desired filament diameter. Traditional trial-and-error methods often result in significant material waste and time consumption. To address this, our study introduces a comprehensive pipeline that initially assesses whether the selected process parameters yield uniform, high-quality MXene prints. Subsequently, it employs a Physics-Guided Artificial Neural Network (PGANN) to predict the filament diameter based on these parameters, integrating fundamental physical principles of the printing process with experimental data. Our findings demonstrate that using an XGBoost classifier, we can classify printed filament quality with an accuracy of 90.44%. Furthermore, the PGANN model shows exceptional performance in predicting the filament diameter, achieving a Pearson Correlation Coefficient (PCC) of 0.9488, a Mean Squared Error (MSE) of 0.000092 mm2, and a Mean Absolute Error (MAE) of 0.00711 mm. This pipeline significantly streamlines the process for researchers, facilitating the selection of optimal printing parameters to consistently achieve high-quality prints and accurately produce the desired filament diameter tailored to specific applications.

ADDITIVE TECHNOLOGIES IN CONSTRUCTION: TECHNICAL, ECONOMIC AND MANAGEMENT ANALYSIS

The study is devoted to a comprehensive analysis of the introduction of additive technologies into modern construction production, revealing the technical, economic, and managerial aspects of concrete 3D-printing of architectural structures. The work systematically analyzes the evolution of additive manufacturing technologies and identifies the main structural types of 3D-printers (an additive machine for layer-by-layer construction of objects), including portal, robotic, mobile, and hybrid systems. A detailed study of the technological parameters of concrete 3D-printing with concrete mixtures is presented, in particular, optimal printing speed modes, layer parameters, criteria for shaping and quality of building structures. A comparative analysis of the technological capabilities of leading world equipment manufacturers, such as ICON, COBOD International, Apis Cor, and WinSun, is conducted. The economic analysis demonstrates significant advantages of additive technologies: reduction of construction time by 2-6 times, reduction of construction cost by 20-35%, and increase in the load-bearing capacity of structures. The study comprehensively explores the structure of capital and operational expenses associated with technology implementation. Special emphasis is placed on the management aspects of introducing additive technologies, highlighting the critical need for an interdisciplinary approach and knowledge integration across architecture, engineering, management, and computer modeling. The study determines the prospects for the development of concrete 3D-printing technology in the construction industry and outlines the main directions of further scientific research and practical implementation of innovative solutions. This study was developed between the Department of "Integrated Technologies of Mechanical Engineering" named after M. Semko of NTU "KhPI" and "Geopolimer" LTD to implement innovative technologies in the construction industry.

Assessing 3D-printed concrete process parameters through Discrete Element Modeling

Three-dimensional concrete printing (3DCP) has emerged as a promising manufacturing technique in the civil engineering sector, offering myriad advantages over traditional construction methods. Despite its potential, challenges persist in optimizing the manufacturing stage of 3DCP, including determining optimal fresh concrete rheology, layer thickness, print path, and nozzle characteristics. In this study, we incorporate the Discrete Fresh Concrete model (DFC) into our Discrete Element Method (DEM) code to simulate the rheological behavior of fresh printable concrete during printing, aiming to explore a comprehensive range of process parameters and their combinations to enhance understanding and optimization 3DCP process. Through a series of simulations, we systematically vary some of the process variables such as concrete mix design, nozzle specifications, and printing speed to investigate their influence on the printed output quality. By the obtained results, we aim to identify the key parameters that significantly affect the process, offering insights for refining 3DCP technologies and helping guide their development. We believe methodologies of the type as shown here may be an efficient tool for advancing 3DCP technologies.

Optimization of chitosan-gelatin-based 3D-printed scaffolds for tissue engineering and drug delivery applications

The combination of biocompatible materials and advanced three-dimensional (3D) additive manufacturing technologies holds great potential in the development of finely tuned complex scaffolds with reproducible macro- and micro-structural characteristics for biomedical applications, such as tissue engineering and drug delivery. In this study, biocompatible printable inks based on chitosan, collagen and gelatin were developed and 3D-printed with a pneumatic-based extrusion printer. The printability of various chitosan–gelatin (CS-Gel) hydrogel inks was assessed by evaluating the quality of the printed constructs. The inks required an extrusion pressure of 150 ± 40 MPa with G22 and G25 nozzles for optimal printing. Inks with low chitosan concentrations (<4% w/v) exhibited poor printability, while inks with 4 % w/v chitosan and 1 % w/v gelatin (CG) demonstrated satisfactory extrusion and printing quality. The addition of collagen (0.1 % w/v) to the optimized ink (CGC) did not compromise printability. Post-printing stabilization using KOH produced self-supporting scaffolds with consistent morphological integrity, while weaker bases like NaOH/EtOH and ammonia vapors resulted in lower pore sizes and reduced structural stability. Water evaporation studies showed that neutralized samples had slower evaporation rates due to the strong intermolecular interactions formed during the neutralization process, contributing to a stable crosslinked network. FTIR spectra confirmed the formation of polyelectrolyte complexes in the CS-Gel and CS-Gel-Collagen blends, further enhancing structural stability. Swelling tests indicated that neutralized constructs maintained stability in different pH environments, with KOH-treated samples exhibiting the lowest swelling ratios and the highest structural stability. After optimizing the ink composition, 10 wt% Levofloxacin was loaded in the constructs as a model antibiotic and it’s in vitro release rate was quantified. Drug loading was approximately 4 % for both ink compositions GC and CGC. CG Levo released over 80 % of levofloxacin within the first hour, reaching full release in 24 h, indicating inadequate control, while CGK Levo exhibited slower initial release (55 % in 15 min) followed by stabilized release after 4 h, likely due to controlled diffusion from expanded constructs. These findings demonstrate that the developed hydrogel inks and optimized printing parameters can produce scaffolds suitable for tissue engineering applications. Finally, the cell compatibility of the 3D-printed constructs was confirmed with MTT assay on fibroblasts and the antimicrobial activity of the drug-loaded constructs was tested against E. coli and S. aureus, showing an increase of the bacteria free zone from 8 ± 0.4 mm of the control against E. coli up to 16.4 ± 0.37 mm in the presence of the KOH-treated CG Levo printed construct.

Implementation of succinylated lactoferrin-luteolin nanocomplex-based 3D printing inks in nutritional and textural customization for dysphagia diets: Printing mechanism, improved bioactivity and in vitro bioaccessibility

There is a great demand for dysphagia diets as the number of old dysphagic patients is increasing rapidly with the aging population trend. This study is aimed to develop attractive dysphagia diets using 3D printing based on succinylated lactoferrin-luteolin nanocomplexation incorporated with combinations of low acyl gellan gum (LAG), high acyl gellan gum (HAG) and gelatin (GL). Rheological, textural, and gel strength of tested inks were examined to assess the potential of the inks for dysphagic diets. The combination of 0.2 g/100 g HAG, 2 g/100 g LAG, and 2 g/100 g GL displayed the optimal printing quality, self-supporting ability, and stability. Concomitantly, it had exceptional water holding capacity and water content. The feasibility of inks as dysphagia diets was evaluated using IDDSI tests, which showed HAG\\LAG\\GL can be classified as level 4-puree/extremely thick foods and was specifically designed for dysphagic individuals. Radical scavenging assays and in vitro digestion simulations demonstrated the HAG\\LAG\\GL possessed substantial antioxidant capabilities and maximally enhanced the bioaccessibility of luteolin. Correlation analysis showed quite significant difference between the control and HAG\\LAG\\GL. These findings underscore the importance of precise colloidal content and types in ensuring optimal printability in 3D printing applications, and provide insights on the development of attractive 3D printing dysphagia diets.

3D Printing Conductive Filament for Fuel Cell Bipolar Plates

Fuel cell bipolar plates are commonly manufactured from graphite or stainless steel. The current production method requires machining intricate channels into these materials which is a costly and time-consuming process. Utilizing a material other than graphite or stainless steel, while still adhering to the standards set by the U.S. Department of Energy for bipolar plate electrical conductivity, could greatly reduce production costs and time. 3D printing bipolar plates could have benefits that include weight reductions as well as ease of testing different flow field designs. However, very few 3D printing filaments are electrically conductive. In this work, conductive samples were printed with Electrifi filament (Multi3D, resistivity: 0.006 Ωcm). This filament is a proprietary metal-polymer composite that has been used to print electronic components such as resistors, capacitors, and inductors [1].Using Electrifi filament, samples were printed at various conditions to determine optimal print settings for geometric accuracy and maximum electrical conductivity. Printing parameters such as nozzle temperature, flow rate, infill pattern, and infill percentage were varied to affect sample density and conductivity. Several combinations of print conditions led to conductivities that exceeded the US DOE technical target for bipolar plate conductivity. SEM imaging was also performed to better understand the structure of the Electrifi filament. In addition, an Energy-dispersive X-ray spectroscopy scan provided details on the elemental composition of printed samples. F. Flowers, C. Reyes, S. Ye, M. J. Kim and B. J. Wiley, "3D printing electronic components and circuits with conductive thermoplastic filament," Additive Manufacturing, vol. 18, pp. 156-163, 2017.

Advanced 3D-Printed Flexible Composite Electrodes of Diamond, Carbon Nanotubes, and Thermoplastic Polyurethane.

In this work, we pioneered the preparation of diamond-containing flexible electrodes using 3D printing technology. The herein developed procedure involves a unique integration of boron-doped diamond (BDD) microparticles and multi-walled carbon nanotubes (CNTs) within a flexible polymer, thermoplastic polyurethane (TPU). Initially, the process for the preparation of homogeneous filaments with optimal printability was addressed, leading to the development of two TPU/CNT/BDD composite electrodes with different CNT:BDD weight ratios (1:1 and 1:2), which were benchmarked against a TPU/CNT electrode. Scanning electron microscopy revealed a uniform distribution of conductive fillers within the composite materials with no signs of clustering or aggregation. Notably, increasing the proportion of BDD particles led to a 10-fold improvement in conductivity, from 0.12 S m-1 for TPU/CNT to 1.2 S m-1 for TPU/CNT/BDD (1:2). Cyclic voltammetry of the inorganic redox markers, [Ru(NH3)6]3+/2+ and [Fe(CN)6]3-/4-, also revealed a reduction in peak-to-peak separation (ΔE p) with a higher BDD content, indicating enhanced electron transfer kinetics. This was further confirmed by the highest apparent heterogeneous electron transfer rate constants (k 0 app) of 1 × 10-3 cm s-1 obtained for both markers for the TPU/CNT/BDD (1:2) electrode. Additionally, the functionality of the flexible TPU/CNT/BDD electrodes was successfully validated by the electrochemical detection of dopamine, a complex organic molecule, at millimolar concentrations by using differential pulse voltammetry. This proof-of-concept may accelerate development of highly desirable diamond-based flexible devices with customizable geometries and dimensions and pave the way for various applications where flexibility is mandated, such as neuroscience, biomedical fields, health, and food monitoring.

Integrated manufacturing method of multimaterial sand mold by binder jetting

PurposeThis paper aims to develop a flexible manufacturing method for multimaterial sand molds to realize efficient additive manufacturing of multimaterial sand molds.Design/methodology/approachTo study the influence of multimaterial sand laying process parameters on the quality of powder bed and optimize the design of multimaterial sand laying device. Numerical simulation and X-ray Computed Tomography are used to study the penetration behavior and curing morphology of resin in different sand particles.FindingsThe surface roughness and porosity of the multimaterial powder bed that meet the requirements of sand-based additive manufacturing can be obtained under the optimal printing process, that is, the sanding speed of 140.0 mm/s and sanding roller diameter of 15.0 mm. The resin penetration process of the multimaterial sand molds shows a pattern of transverse expansion and longitudinal penetration. In terms of the resin curing morphology, the maximum thickness of the resin film layer of zircon sand reaches 30.5 ± 1.0 µm, which has the best tensile property, followed by silica sand and the thinnest resin film layer of chromite sand.Originality/valueIn this work, a highly flexible integrated combined sand-laying device suitable for multimaterial sand-laying tests is developed, which can obtain a multimaterial powder bed that meets the needs of sand additive manufacturing. Subsequent casting print tests also verify that the program can meet the needs of multimaterial sand mold additive manufacturing.

Rapid Prototyping for Accelerated Establishment of Film Processing‐Performance Relationships in Silicon Phthalocyanine OFETs

AbstractUnderstanding the complex relationships underlying the performance of organic electronic devices, such as organic field‐effect transistors (OFETs), requires researchers to navigate a multi‐dimensional parameter space that includes material design, solution formulation, fabrication parameters, and device geometry. Herein, a recently developed materials acceleration platform is demonstrated, named the RoboMapper, to perform direct on‐chip fabrication of OFETs by ultrasonic meniscus printing using silicon phthalocyanine (SiPc) derivatives as the semiconductor. OFETs using bis(tri‐n‐butylsilyl oxide) SiPc ((3BS)2‐SiPc) exhibited the best device performance characterized by the highest electron field‐effect mobility (µe). Through optical microscopy and grazing‐incidence wide‐angle X‐ray scattering (GIWAXS), the favorable performance of (3BS)2‐SiPc is attributed to the specific film morphology and molecular packing achieved with optimal print conditions. Investigating the impact of deposition parameters reveals the crucial role of solvent evaporation rate and print speed in achieving high‐quality film formation. Overall, optimal fabrication conditions for (3BS)2‐SiPc devices include slow print speeds and fast evaporating solutions achieved by using a mixture of co‐solvents and an elevated substrate temperature. The results of this work reveal distinct relationships between deposition conditions, film properties, and device performance for each SiPc derivative and emphasize the necessity of high throughput experimentation to comprehensively understand process‐performance relationships in organic semiconductors.