Printing Ink Research Articles

Ultra-high electrostriction and ferroelectricity in poly (vinylidene fluoride) by ‘printing of charge’ throughout the film

Electrostriction is an important electro-mechanical property in poly (vinylidene fluoride) (PVDF) films, which describes the proportional relation between the electro-stimulated deformation and the square of the electric field. Generally, traditional methods to improve the electrostriction of PVDF either sacrifice other crystalline-related key properties or only influence minimal regions around the surface. Here, we design a unique electret structure to fully exploit the benefits of internal crystal in PVDF films. Through the 3D printing of charged ink, we have obtained the best electrostrictive and ferroelectric properties among PVDF-based materials so far. The optimized electrostrictive coefficient M33 (324 × 10−18 m2 V−2) is 104 times that of normal PVDF films, and the piezoelectric constant d33 (298 pm V−1) is close to 10 times its traditional limit. The proposed 3D electret structure and the bottom-up approach to ‘print the charge’ open up a new way to design and adapt the electroactive polymers in smart devices and systems.

Spatially programmed alignment and actuation in printed liquid crystal elastomers

Liquid crystal elastomers (LCEs) exhibit reversible shape morphing behavior when cycled above their nematic-to-isotropic transition temperature. During extrusion-based 3D printing, LCE inks are subjected to coupled shear and extensional flows that can be harnessed to spatially control the alignment of their nematic director along prescribed print paths. Here, we combine experiment and modeling to elucidate the effects of ink composition, nozzle geometry, and printing parameters on director alignment. From rheological measurements, we quantify the dimensionless Weissenberg number (Wi) for the flow field each ink experiences as a function of printing conditions and demonstrate that Wi is a strong predictor of LCE alignment. We find that director alignment in LCE filaments printed through a tapered nozzle varies radially when Wi < 1, while it is uniform when Wi ≫ 1. Based on COMSOL simulations and in operando X-ray measurements, we show that LCE inks printed through nozzles with an internal hyperbolic geometry exhibit a more uniform director alignment for a given Wi compared to those through tapered nozzles. Concomitantly, the stiffness along the print direction and actuation strain of printed LCEs increases substantially under such conditions. By varying Wi during printing through adjusting the flow rate "on the fly", LCE architectures with uniform composition, yet locally encoded shape morphing transitions can be realized.

Reversible Thixotropic Rheological Properties of Graphene-Incorporated Epoxy Inks for Self-Standing 3D Printing.

As three-dimensional (3D) printing has emerged as a new manufacturing technology, the demand for high-performance 3D printable materials has increased to ensure broad applicability in various load-bearing structures. In particular, the thixotropic properties of materials, which allow them to flow under applied external forces but resist flowing otherwise, have been reported to enable rapid and high-resolution printing owing to their self-standing and easily processable characteristics. In this context, graphene nanosheets exhibit unique π-π stacking interactions between neighboring sheets, likely imparting self-standing capability to low-viscosity inks. Herein, we develop a thermally curable graphene-incorporated epoxy ink system that exhibits shear-thinning characteristics and upright standing capability owing to its high static yield stress (∼1,680 Pa). The reversible liquid-to-solid phase transition of the composite ink, absent in the pristine epoxy ink, is clearly identified by its viscoelastic properties and dynamic yield stress. This thixotropic composite ink enables the continuous filament printing of 10 stacked layers without the spreading of injected filaments. Significantly, the 3D-printed composite structure, post-thermal curing, exhibits robust structural integrity and is free from weld lines or voids at the stacked interfaces. Combined with the clearly elucidated processing-structure-property relationships of the ink system, our results highlight its potential for a wide spectrum of applications.

Unveiling the potential of bean proteins: Extraction methods, functional and structural properties, modification techniques, physiological benefits, and diverse food applications.

Bean proteins, known for their sustainability, versatility, and high nutritional value, represent a valuable yet underutilized resource, receiving less industrial attention compared to soy and pea proteins. This review examines the structural and molecular characteristics, functional properties, amino acid composition, nutritional value, antinutritional factors, and digestibility of bean proteins. Their applications in various food systems, including baked goods, juice and milk substitutes, meat alternatives, edible coatings, and 3D printing inks, are discussed. The physiological benefits of bean proteins, such as antidiabetic, cardioprotective, antioxidant, and neuroprotective effects, are also presented, highlighting their potential for promoting well-being. Our review emphasizes the diversity of bean proteins and highlights ultrasound as the most effective extraction method among available techniques. Beyond their physiological benefits, bean proteins significantly enhance the structural, technological, and nutritional properties of food systems. The functionality can be further improved through various modification techniques, thereby expanding their applicability in the food industry. While studies have explored the impact of bean protein structure on their nutritional and functional properties, further research is needed to investigate advanced modification techniques and the structure-function relationship. This will enhance the utilization of bean proteins in innovative and sustainable food applications.

Up-conversion luminescent rare-earth doped ceramics integrated into printable security inks for anti-counterfeiting applications

Up-conversion luminescent rare-earth doped ceramics integrated into printable security inks for anti-counterfeiting applications

Comparative life cycle assessment of traditional and emerging methods for high concentration organic wastewater treatment.

Two traditional methods, including incineration and the sequencing batch reactor activated sludge process (SBR), and two emerging methods, including supercritical water oxidation (SCWO), catalytic wet oxidation (CWO) combined with SBR (CWO-SBR), for high concentration organic wastewater treatment were compared from the view of environmental impact. The printing ink wastewater generated from the surface treatment of electronic products was selected as the typical wastewater and diluted to various concentrations for sensitivity analysis. Simapro 9.3 software was selected to explore the environmental impacts of the four processes with Traci impact assessment method and Ecoinvent 3.8 database. Moreover, two tools including the total environmental impact and comprehensive competitiveness were used for quantitative comparison. The total environmental impacts for the incineration and SCWO processes gradually decrease with increasing chemical oxygen demand (COD) concentration for more steam output and less fuel and electricity consumptions, but opposite trends appear for the CWO-SBR and SBR processes, indicating higher COD concentrations exhibit smaller environmental impacts for the incineration and SCWO processes. The incineration and SBR processes have the slightest and highest total environmental impacts of 0.030 and 1.117 at the base case of COD=234,000mg/L, respectively. The trends of the comprehensive indexes for the four processes with increasing COD concentration are similar to those of the total environmental impacts. The SCWO process has the highest comprehensive index of 0.956 at the base case, followed by the incineration, CWO-SBR, and SBR processes, with values of 0.783, 0.460, and 0.158, respectively.

A Dual Binder Concept for 3D Printing Ink: Triggered Polymerization for Rapid Stiffening and Carbonation for Final Strength

A Dual Binder Concept for 3D Printing Ink: Triggered Polymerization for Rapid Stiffening and Carbonation for Final Strength

Enhanced 3D printing performance of soybean protein isolate nanoparticle-based O/W Pickering emulsion gels by incorporating different polysaccharides.

This work investigated the feasibility of employing soybean protein isolate nanoparticles (SPINPs) as emulsifiers and polysaccharides with different charge properties as thickeners to develop oil-in-water (O/W) Pickering emulsion gels 3D printing inks. The impact of non-covalent interactions between SPINPs and various polysaccharides on the microstructure, rheological properties, and 3D printability of emulsion gels was investigated at pH3 and pH7, respectively. Results showed that Locust bean gum (LBG) and Konjac gum (KG) stabilized emulsion gels mainly by increasing the viscosity of the aqueous phase. Chitosan (CS) and xanthan gum (XG) improved the system's viscosity while combining with SPINPs via electrostatic interactions. Small amplitude oscillatory shear and large amplitude oscillatory shear test results showed the highest recovery rate (97.45%) and gel strength of 7-XG, exhibiting good potential for 3D printing. The Lissajous curves revealed the weakest gel structure and larger dimensional printing deviation (27.57%) of 3-XG. The 3D-printed products of LBG and KG emulsion gels demonstrated smooth and slightly flawed surface texture. The print deformation rate of CS emulsion gels was <5.5%, which was most suitable for developing 3D printing inks. This study offers valuable insights for creating and designing protein-polysaccharide-based 3D printing inks.

Impact of Nanoparticle Size and Loading on Printability of Composite Inks for Direct Ink Writing

AbstractDirect ink writing (DIW) using polymer‐particle composite inks is a new research area enabling a wide range of new functionalities. Despite extensive studies, there remains a need for a deeper understanding of how particle size and loading specifically influence printability, especially in the nano range. This work aims to systematically evaluate the effects of SiO2 nanoparticle size (26–847 nm) and loading on printability within a polydimethylsiloxane (PDMS) matrix. For the single‐layer printing process, which is influenced by the substrate properties, a 3D printing line analysis (3D‐PLA) is developed to monitor the top and side views of printed lines. It is found that line width varies with ink composition and substrate, while the line height decreases with solvent evaporation, indicating a strong confinement effect from the substrate. For multilayer structures, dual‐layer printing analysis (DLPA) is utilized to evaluate the printability. It is shown that DLPA is independent of the substrate and can be used to compare the printabilities from different inks. Both 3D‐PLA and DLPA can be correlated to the rheological behavior of the ink through ink rheology analysis (IRA). Finally, this research defined the design space for DIW by benchmarking the minimum and maximum particle loadings for printable composite inks.

Nanoliposome functionalized colloidal GelMA inks for 3D printing of scaffolds with multiscale porosity

Bioprinting has enabled the creation of intricate scaffolds that replicate the physical, chemical, and structural characteristics of natural tissues. Recently, hydrogels have been used to fabricate such scaffolds for several biomedical applications and tissue engineering. However, the small pore size of conventional hydrogels impedes cellular migration into and remodeling of scaffolds, diminishing their regenerative potential. Porous scaffolds have been utilized for their improved diffusion of nutrients, dissolved oxygen, and waste products. However, traditional methods of generating porous structures require multiple processing steps, making them incompatible with bioprinting. Recently, we developed a method to generate multi-scale porous structures by foaming hydrogel precursors prior to printing to form colloidal bioinks. Here, to further improve the biological, mechanical, and physical properties, we functionalize colloidal bioinks with nanoliposomes (NLs), one of the most promising methods for bioactive delivery. We assess the impact of the concentration of NL on the characteristics of bioinks made from gelatin methacryloyl (GelMA) and their resulting scaffolds. Anionic liposomes made from rapeseed lecithin of 110 nm were synthesized and found to be stable over several weeks. Increasing concentrations of NL decreased the zeta potential and increased the viscosity of foamed bioinks, improving their rheological properties for printing. Furthermore, the incorporation of NL allowed for precise adjustment of the macropore size and bulk mechanical properties without any chemical interaction or impact on photocrosslinking. The nanofunctionalized foam bioinks, composed exclusively of natural components, demonstrated significant antioxidant activity and were printed into multilayered scaffolds with high printability. The foam-embedded NL showed remarkable biocompatibility with myoblasts, and cell-laden bioinks were able to be successfully bioprinted. Due to their high biocompatibility, tunable mechanical properties, printability, and antioxidant behavior, the nanofunctionalized porous scaffolds have promise for a variety of biomedical applications, including those that require precise delivery of therapeutic substances and tissue engineering.

A capacitive tactile force sensor with mutual fringe effect and parallel plate design for robot assisted surgery

This paper presents a unique design of a single-axis tactile force sensor by a mutual parallel plate and fringing effect of an electric field that is generated between stationary patterned electrodes in the sensor. The proposed sensor can measure the normal and shear forces with high sensitivity and linear response. The capacitive tactile sensor is fabricated by low-cost rapid prototyping techniques using conductive ink for electrode printing that is printed on a polyethylene terephthalate sheet by an inkjet printer. Ecoflex 00-30 and silicone rubber RTV-528 are used as the dielectric medium and dome for force application. A finite element method analysis is performed for deciding the dimensions of the sensor's stationary electrodes. The force measurement ranges of the sensor for the normal and shear axis are 4 N and 2 N, respectively. The proposed tactile sensor shows a highly linear response, which makes it a suitable match for force feedback in robotic surgery.

Silylated Carbon Nanofiber/Polydimethylsiloxane Based Printable Electrorheological and Sensor Inks for Flexible Electronics.

Electrorheological fluids (ERF) have garnered significant attention for their potential to provide actuation on demand. Similarly, developing stimuli-responsive printable inks for flexible electronics is also gaining antecedence. However, developing a material that demonstrates bothfunctionalities is far and few. Accordingly, a printable ink is made using silylated carbon nanofiber (SiCNF)-polydimethylsiloxane (PDMS). The viscosity of the ink increased by 43%, when subjected to an electric field (E). Robust stability for 20 cycles under E = 300 Vmm-1 is noted. The yield stress (τy) value increased by 1600% (E = 600 Vmm-1) compared to zero-field yield stress. Applying temperature with E further increased the τy. In the absence of E, applying temperature not only slowed down the relaxation modulus but also counterintuitively augmented the extent of sluggishness with an increase in temperature. A comprehensive study on the waiting time also indicated a structure build-up within the ink composition happening as the waiting time increases. Accordingly, thetime-temperature and time-waiting time superposition principle is applied to predict the long-term behavior of the inks. Further, the printability index of the ink check is studied and used for printing designs using direct ink writing. The printed ink demonstrated pressure sensing capability with a sensitivity of 6.3%/kPa and is stable over 60 cycles.

Near-Field Passive Wireless Sensor for High-Temperature Metal Corrosion Monitoring.

This work focuses on the fabrication and evaluation of a passive wireless sensor for the monitoring of the temperature and corrosion of a metal material at high temperatures. An inductor-capacitor (LC) resonator sensor was fabricated through the screen printing of Ag-based inks on dense polycrystalline Al2O3 substrates. The LC design was modeled using the ANSYS HFSS modeling package, with the LC passive wireless sensors operating at frequencies from 70 to 100 MHz. The wireless response of the LC was interrogated and received by a radio frequency signal generator and spectrum analyzer at temperatures from 50 to 800 °C in real time. The corrosion kinetics of the Cu 110 was characterized through thermogravimetric (TGA) analysis and microscopy images, and the oxide thickness growth was then correlated to the wireless sensor signal under isothermal conditions at 800 °C. The results showed that the wireless signal was consistent with the corrosion kinetics and temperature, indicating that these two characteristics can be further deconvoluted in the future. In addition, the sensor also showed a magnitude- and frequency-dependent response to crack/spallation events in the oxide corrosion layer, permitting the in situ wireless identification of these catastrophic events on the metal surface at high temperatures.

4D Printing of Liquid Crystal Emulsions for Smart Structures with Multiple Functionalities

Abstract3D printing, and more recently 4D printing, has emerged as a transformative technology for fabricating structures with complex geometries and responsive properties. However, employing functional colloidal solutions as inks for printing remains unexplored. In this work, we present a novel and versatile 4D printing approach for fabricating functional and complex‐shaped objects using polymerizable liquid crystal (LC) emulsion droplets. Leveraging a digital light processing (DLP) 3D printing technique, we achieve rapid production of intricate 3D geometries with high resolution. The printed structures retain the LC ordering from the precursor droplets, imparting the final objects with shape memory properties, including shape fixation and recovery upon heating or light exposure. Light‐responsive behavior is introduced post‐printing by embedding an azo dye into the 3D structures. Additionally, we explore the potential to create intrinsically porous 3D structures by selectively removing non‐reactive components from the printed geometries, adding an extra level of functionality to the printed objects. Furthermore, we incorporate chiral nematic LCs into the emulsion droplets, producing 3D objects with tunable reflective properties. To our knowledge, this is the first example of DLP 3D printing with emulsions, offering an effective and versatile pathway for developing 4D‐printed materials with potential applications in optics, robotics, microfluidics, and biomedicine.

4D Printing of Liquid Crystal Emulsions for Smart Structures with Multiple Functionalities.

3D printing, and more recently 4D printing, has emerged as a transformative technology for fabricating structures with complex geometries and responsive properties. However, employing functional colloidal solutions as inks for printing remains unexplored. In this work, we present a novel and versatile 4D printing approach for fabricating functional and complex-shaped objects using polymerizable liquid crystal (LC) emulsion droplets. Leveraging a digital light processing (DLP) 3D printing technique, we achieve rapid production of intricate 3D geometries with high resolution. The printed structures retain the LC ordering from the precursor droplets, imparting the final objects with shape memory properties, including shape fixation and recovery upon heating or light exposure. Light-responsive behavior is introduced post-printing by embedding an azo dye into the 3D structures. Additionally, we explore the potential to create intrinsically porous 3D structures by selectively removing non-reactive components from the printed geometries, adding an extra level of functionality to the printed objects. Furthermore, we incorporate chiral nematic LCs into the emulsion droplets, producing 3D objects with tunable reflective properties. To our knowledge, this is the first example of DLP 3D printing with emulsions, offering an effective and versatile pathway for developing 4D-printed materials with potential applications in optics, robotics, microfluidics, and biomedicine.

3D Printing and Biocementation of Hierarchical Porous Ceramics

AbstractCeramics with controlled porosity are used as bio‐scaffolds, insulators, electrodes and lightweight materials. While their high surface area and low weight are attractive functionalities, such porous ceramics often suffer from poor mechanical properties and need energy‐intensive, high‐temperature sintering for manufacturing. The present work reports a low‐temperature approach for the manufacturing of mechanically efficient porous ceramics. The process relies on the 3D printing of inks loaded with ceramic hollow spheres, which are biocemented by the precipitation of calcium carbonate induced by ureolytic bacteria. Electron microscopy, thermogravimetric analysis and mechanical tests are performed to study the kinetics of the biocementation process and its effect on the calcification and mechanical properties of extruded and printed samples. Hierarchical porous ceramics with a grid‐like architecture and filament sizes in the order of one millimeter are effectively biocemented at ambient temperature after 2 days of calcification. The calcified structures display higher mechanical efficiency than previously reported monoliths of comparable porosity, thus demonstrating the potential of 3D printing and bacteria‐driven biocementation for the low‐temperature fabrication of hierarchical porous ceramics.

A low-cost, open-source cylindrical Couette rheometer

Rheology describes the flow of fluids from food and plastics, to coatings, adhesives, and 3D printing inks, and is commonly denoted by viscosity alone as a simplification. While viscometers adequately probe Newtonian (constant) viscosity, most fluids have complex viscosity, requiring tests over multiple shear rates, and transient measurements. As a result, rheometers are typically large, expensive, and require additional infrastructure (e.g., gas lines), rendering them inaccessible for regular use by many individuals, small organizations, and educators. Here, we introduce a low-cost (under USD$200 bill of materials) Open Source Rheometer (OSR), constructed entirely from thermoplastic 3D printed components and off-the-shelf electromechanical components. A sample fluid rests in a cup while a micro stepping motor rotates a tool inside the cup, applying strain-controlled shear flow. A loadcell measures reaction torque exerted on the cup, and viscosity is calculated. To establish the measurement range, the viscosity of four Newtonian samples of 0.1–10 Pa.s were measured with the OSR and compared to benchmark values from a laboratory rheometer, showing under 23% error. Building on this, flow curves of three complex fluids – a microgel (hand sanitizer), foam (Gillette), and biopolymer solution (1% Xanthan Gum) – were measured with a similar error range. Stress relaxation, a transient test, was demonstrated on the biopolymer solution to extract the nonlinear damping function. We finally include detailed exposition of measurement windows, sources of error, and future design suggestions. The OSR cost is ∼1/25th that of commercially available devices with comparable minimum torque (200 µN.m), and provides a fully open-source platform for further innovation in customized rheometry.

Digitally Programmable Microphase Separation in Polymer Network Generates Microstructure Pattern.

Polymers with microstructure patterns are crucial to many applications, such as separation, optics, electronics, metamaterials, etc. However, introducing microstructure patterns with diverse morphologies and feature sizes ranging from nanometers to micrometers into large-area polymers remains a significant challenge. Here, we design a material system that enables digital programming microphase separation in a polymer network to generate microstructure patterns. The polymer network is engineered to allow digital programming of local modulus, which arrests the length scale of microphase separation to generate various microstructures. These local modulus-regulated microstructures exhibit either bicontinuous or sea-island morphology and have various feature sizes ranging from ∼100 nm to several micrometers. Using household devices of an ink printer and an ultraviolet light lamp, the microstructure patterns can be programmed with fine resolutions (∼100 μm) over large areas (≫100 mm). The locally varied microstructures have different capabilities to scatter light and result in a visible pattern. We further demonstrate this design with a soft anticounterfeiting device. This approach of digital programming microphase separation in polymer networks is applicable to various polymers and provides a platform for designing many other functional devices.

Synergistic stabilization of oil-in-water emulsion gels by pea protein isolate and cellulose nanocrystals: Effects of pH and application to 3D printing.

In this study, pea protein isolate (PPI) and cellulose nanocrystals (CNC) were used to prepare oil-in-water emulsions, and the effects of pH and the oil content on the properties of the emulsions were investigated. The microstructural analysis revealed that PPI and CNC formed complexes by electrostatic attraction at pH3.0 and 4.5, which assembled a dense interfacial layer around the oil droplets, improving emulsification performance. Moreover, the emulsions at these pH conditions exhibited semi-solid gel properties when the oil content was increased to 75wt%, with better viscoelasticity compared to pH8.0 and high thixotropic recovery rates in rheological experiments. Printing of flat stacked models with these high internal phase emulsions had a deformation rate of around 5%, indicating desirable shear resistance and fidelity. These findings would offer valuable insights for developing fat substitutes and their application as edible inks for 3D printing.

A novel data driven formulation for predicting jetting states and printing zone of high-viscosity nanosilver ink in inkjet-based 3D printing

Inkjet printing offers significant benefits for additive manufacturing (AM) and printed electronics, such as cost-effectiveness, scalability, non-contact printing, and the flexibility for ad-hoc customization. However, some challenges such as stable jetting states and defined printing zone still needs attention. Data driven modeling such as machine/deep learning (ML/DL) as a predictive methodology has proven to reduce the experimental cost and workload in AM for low-viscosity inks. However, there is an oversight in ML extension to high-viscosity inks due to some inherit challenges such as irregular shape formation, and adhesiveness. Therefore, this study is focused on the prediction of jetting states and defining the printing zone for three-dimensional (3D) inkjet printing of high-viscosity ink. The experimental data is comprised of equipment parameter settings, material properties, and camera-captured features. The jetting behavior is recorded with a high-speed camera and carefully categorized into five classes: no jetting, orifice adhesion, droplet jetting, orifice tail, and beads hanging. A robust and efficient high-viscosity 3D printing U-Net (HV3DP-UNet) model is proposed, that achieved the jetting state and printing zone prediction accuracy of 97.98% and 100% respectively. For the fair comparison, three traditional ML and two more DL models are tested and analyzed in detail. The robustness and efficacy of the proposed model is supplemented with four performance metrics, i.e., accuracy, precision, recall and f1-score. The models’ efficacy has been proved by achieving improved results on the public dataset, the proposed model has achieved overall prediction accuracy of 92.95%. The presented data-driven approach serves as a systematic framework for enhancing quality of inkjet-based 3D printing utilizing high-viscosity ink.