Design, Development and Experimental Investigation of E-jet Based Additive Manufacturing Process

This paper discusses a run-to-run iterative learning control (ILC) algorithm for Electrohydrodynamic jet (E-jet) printing. E-jet printing is a nano-manufacturing process that uses electric field induced fluid jet printing through nano-scale nozzles for achieving better control and resolution than traditional jet-printing processes. The printing process is controlled by changing the voltage potential between the nozzle and the substrate. However, it is difficult to maintain constant operating conditions such as stand-off height during a run of the printing process. The change in operating conditions results in fluctuating jet frequency. For stabilizing the jetting frequency across a single run, we propose a proportional ILC algorithm. We determine the jetting frequency by recording the electric current pulses when ink droplets are released from the nozzle. The frequency profile obtained from current measurements is then used to shape the voltage profile across a run to compensate for changing operating conditions. Experimental results are presented to validate the proposed control method.

Parametric Optimization of E-Jet Based Micro Manufacturing System through Hybrid Taguchi Methodology

Electrohydrodynamic jet (E-jet) printing has broad application prospects in the preparation of flexible electronics and optical devices. Ejection cycle time and droplet size are two key factors affecting E-jet-printing quality, but due to the complex process of E-jet printing, it remains a challenge to establish accurate relationships among ejection cycle time and droplet diameter and printing parameters. This paper develops a model based on random forest regression (RFR) for E-jet-printing prediction. Trained with 72 groups of experimental data obtained under four printing parameters (voltage, nozzle-to-substrate distance, liquid viscosity, and liquid conductivity), the RFR model achieved a MAPE (mean absolute percent error) of 4.35% and an RMSE (root mean square error) of 0.04 ms for eject cycle prediction, as well as a MAPE of 2.89% and an RMSE of 0.96 μm for droplet diameter prediction. With limited training data, the RFR model achieved the best prediction accuracy among several machine-learning models (RFR, CART, SVR, and ANN). The proposed prediction model provides an efficient and effective way to simultaneously predict the ejection cycle time and droplet diameter, advancing E-jet printing toward the goal of accurate, drop-on-demand printing.

High-resolution additive direct writing of metal micro/nanostructures by electrohydrodynamic jet printing

High-resolution flexible electronic devices are widely used in the fields of soft robotics, smart human-machine interaction, and intelligent e-healthcare monitoring due to their mechanical flexibility, ductility, and compactness. The electrohydrodynamic jet printing (e-jet printing) technique is used for constructing high-resolution and cross-scale flexible electronic devices such as field-effect transistors (FETs), flexible sensors, and flexible displays. As a result, researchers are paying close attention to e-jet printing flexible electronic devices. In this review, we focused on the latest advancements in high-resolution flexible electronics made by e-jet printing technology, including various materials used in e-jet printing inks, the process control of e-jet printing, and their applications. First, we summarized various functional ink materials available for e-jet printing, including organic, inorganic, and hybrid materials. Then, the interface controlling the progress of e-jet printing was discussed in detail, including the physical and chemical properties of the functional ink, the interfacial wettability between the ink and substrate, and the micro-droplet injection behavior in a high-voltage field. Additionally, various applications of e-jet printing in the fields of flexible electrodes, FETs, flexible sensors, and flexible displays were demonstrated. Finally, the future problems and potential associated with the development of next generation e-jet printing technology for flexible electronic devices were also presented.

This paper reports the use of advanced forms of electrohydrodynamic jet (e-jet) printing for creating micro- and nanoscale patterns of proteins on various surfaces ranging from flat silica substrates to structured plasmonic crystals, suitable for micro/nanoarray analysis and other applications in both fluorescent and plasmonic detection modes. The approaches function well with diverse classes of proteins, including streptavidin, IgG, fibrinogen, and γ-globulin. Detailed study reveals that the printing process does not adversely alter the protein structure or function, as demonstrated in the specific case of streptavidin through measurements of its binding specificity to biotin-modified DNA. Multinozzle printing systems enable several types of proteins (up to four currently) to be patterned on a single substrate, in rapid fashion and with excellent control over spatial dimensions and registration. High-speed, pulsed operational modes allow large-area printing, with narrow statistical distributions of drop size and spacing in patterns that include millions of droplets. The process is also compatible with the structured surfaces of plasmonic crystal substrates to enable detection without fluorescence. These collective characteristics suggest potential utility of e-jet techniques in wide-ranging areas of biotechnology, where its compatibility with various biomaterials and substrates with different topographies and surface chemistries, and ability to form deposits that range from thick films to submonolayer coatings, derive from the remote, noncontacting physical material transfer mode of operation.

Electrohydrodynamic (EHD) inkjet printing has gained widespread attention in electronics, biomedicine, and materials science for its exceptional resolution and printing versatility. However, the droplet formation process is governed by complex interactions between driving waveform parameters and fluid properties, making traditional trial-and-error optimization inefficient. To address this, a hybrid approach combining numerical simulation, machine learning regression, and genetic algorithm optimization is proposed to achieve precise control of droplet diameter. A multiphysics numerical model is established in COMSOL Multiphysics to simulate the complete cycle of Taylor cone formation, jetting, and droplet deposition under pulsed electric fields. Parametric studies are conducted to investigate the influence of waveform characteristics and fluid properties on droplet size and jetting stability. Based on these simulations, a dataset of 912 samples is constructed for machine learning analysis. Among seven regression models evaluated, the artificial neural network (ANN) shows the best predictive performance and is further integrated with a genetic algorithm to optimize the driving parameters for different target droplet diameters. Experimental validation is performed using a Super Inkjet (SIJ) printing system. The results confirm the effectiveness of the proposed method: the average droplet diameter error ranges from 1.00 μm to 1.89 μm, and 84.21% of the droplets fall within ±5% of the target diameter. This study demonstrates a practical and data-driven framework for enhancing precision and process control in EHD printing.

Electrohydrodynamic jet printing (e-jet printing) is a nascent additive manufacturing process most notable for extremely high resolution printing and having a vast portfolio of printable materials. These capabilities make e-jet printing promising for applications such as custom electronics and biotechnology fabrication. However, reliably fulfilling e-jet printing’s potential for high resolution requires delicate control of the volume deposited by each jet. Such control is made difficult by a lack of models that both capture the dynamics of volume deposition and are compatible with the control schemes relevant to e-jet printing. This work delivers such a model. Specifically, this work introduces a definition of “droplet volume” as a dynamically evolving variable rather than a static variable, and uses this definition along with analysis of high speed microscope videos to develop a hybrid dynamical system model of droplet volume evolution. This model is validated with experimental data, which involves the contribution of a novel technique for extracting consistent droplet volume measurements from videos.

Bioelectronic interfaces and biohybrid technologies have emerged as powerful solutions for sensing and manipulation applications. A unique method of underwater chemical sensing via a combination of engineered microbes and bioelectronic interfaces is discussed here with the goal of reporting to autonomous robotics through an electronic nervous system. The fabrication of these interfaces warrants a deposition method capable of precisely implementing the electronic, interfacial, and biological layers necessary for reliable devices. Electrohydrodynamic jet (e-jet) printing has been shown capable of doing so at a biologically relevant scale of 240 ± 50 nm. An e-jet printing system was fabricated and modified to use additive manufacturing to fabricate heterogeneous interfaces for the biological reporters Nitric Oxide and luminescence. These tasks included the fabrication of electronics that typically have multiple materials and thus multiple layers in their architecture; a potential point of failure in this liquid phase deposition method. The implementation of code based ejection modalities and a heated vacuum chuck allow for controlled volume deposition and rapid solvent evaporation, alleviating dissolution events in the sublayer. By eliminating these events, controlling film thickness to deter pinhole formation, and generating inks with solvents that were incompatible with sublayers, multi-layer electrochemical nitric oxide sensors and photosensors were produced. The fabricated multi-layer nitric oxide sensor has a lower limit of detection range of 188.5 nM - 314.5 nM; levels at which RAW 264.7 macrophage depolarization can be monitored in real time. An alternative bioelectronic interface is being studied wherein a modified version of this sensor is interfaced with Shewanella oneidensis to detect aqueous toxins. The photosensor architecture is comprised of a transparent PET substrate, an ITO cathode (pre-deposited), a bulk heterojunction P3HT:PC₇₁BM active layer, and a silver anode, with a final maximum spectral response of 7 mA/W and 90 mA/W/mm² at 514 nm, with a broad visible light spectrum from 400 nm to 620 nm. In interfacing these sensors with Vibrio fischeri, emitting light at 490 nm, the concentration of auto inducers in solution has been monitored in real time. These studies have created a clear path toward the fruition of olfactory guided, underwater autonomous robotics.

Temperature measurement is very important for thermal control, which is required for the advancement of mechanical and electronic devices. However, current temperature sensors are limited by their inability to measure curved surfaces. To overcome this problem, several methods for printing flexible substrates were proposed. Among them, electrohydrodynamic (EHD) inkjet printing technology was adopted because it has the highest resolution. Since EHD inkjet printing technology is limited by the type of ink used, an ink with temperature-sensing properties was manufactured for use in this printer. To confirm the applicability of the prepared ink, its resistance characteristics were investigated, and the arrangement and characteristics of the particles were observed. Then, the ink was printed using the EHD inkjet approach. In addition, studies of the meniscus shapes and line widths of the printed results under various conditions confirmed the applicability of the ink to the EHD inkjet printing technology and the change in its resistance with temperature.

Microlens arrays (MLAs) are essential for light collection, extraction, and high-resolution imaging. However, most reported MLAs have a limited filling factor. Here, we demonstrate MLAs using three different UV-curing optical adhesives based on the electrohydrodynamic inkjet (E-jet) printing technique. The highest filling factor of 89.91% is achieved. By controlling the curvature of the microlens via the surface treatment of the substrate, a series of MLAs with different numerical apertures can be obtained. With the high-consistency printing technique, the demonstrated high filling factor MLAs could be potentially useful to improve the performance of optical imaging and sensing systems.

Electrohydrodynamic jet (E-jet) printing is a recent technique for high resolution additive micromanufacturing. With high resolution comes sensitivity to small disturbances, which has kept this technique from reaching its industrial potential. Closed loop control of E-jet printing can overcome these disturbances, but it requires an improved understanding of ink droplet spreading on the substrate and a physical model to predict printed feature locations and geometries from process inputs and disturbances. This manuscript examines a model of ink droplet spreading that uses assumptions that are important to the e-jet process. Our model leverages previous energy balance models that were derived for larger length scale droplets. At the smaller length scale, we find that viscous losses are a significant portion of the energy budget and must be accounted for; this is in contrast to models at length scales two orders of magnitude larger. Our model predicts the droplet height, base radius and contact angle in time from an initial volume and E-jet printing control parameters. The model is validated with published droplet spreading data and new measurements of E-jet printed droplets of diameter 8 μm. The viscous friction calculated in the new model is found to be significant compared to surface energy.

Here, we suggest simple method for multi value slope In‐Ga‐Zn O (IGZO) thin‐film transistors (TFTs) using electrohydrodynamic (EHD) jet printing. To induce multi value slope, parasitic channel was intentionally formed on top of IGZO main channel using EHD jet printing. By precisely controlling parasitic channel regime with EHD jet printing, multi value slope could be realized without degradation in electrical performance of original IGZO TFTs.

Paper-based microchannels are important components in paper-based microfluidic devices. Paper-based microchannels are usually manufactured by creating lines with hydrophobic patterns enclosing an area of hydrophilic paper inside. Among the many techniques for making hydrophobic lines, the printing method in general and inkjet printing in particular have become more common because of their advantages in terms of material saving, high precision, low-cost, etc. In this paper, the electrohydrodynamic (EHD) inkjet printing method, which has been studied and developed in recent years, has been used to drop glycol ether solvent-based ink onto a nitrocellulose paper. The results of the field emission scanning electron microscope (FE-SEM) show that the solvent based ink could dissolve through membrane and form a transparent hydrophobic layer on the created space. The width of the barrier lines can be controlled from about 200 μm to 260 μm, which is quite small when compared to other manufacturing methods. Based on this fabrication process, paper-based microfluidic analytical devices have been designed and fabricated for use in analytical biochemistry assays. Human chorionic gonadotropin (hCG) was selected as the biological target for this assay. Initial results have shown that the target for hCG can be quantitatively determined by these devices with a coefficient of determination (R2) of approximately 0.99. Therefore, EHD inkjet printing technology can be used for the manufacture of paper-based microfluidic analytical devices (μPADs) that may be applied in the future for analytical biochemistry assays.

In the dc voltage-applied electrohydrodynamic (EHD) jet printing of metal nanoparticles, the residual charge of droplets deposited on a substrate changes the electrostatic field distribution and interrupts the subsequent printing behaviour, especially for insulating substrates that have slow charge decay rates. In this paper, a sinusoidal ac voltage was used in the EHD jet printing process to switch the charge polarity of droplets containing Ag nanoparticles, thereby neutralizing the charge on a polyethylene terephthalate (PET) substrate. Printed Ag lines with a width of 10 µm were invisible to the naked eye. After sintering lines with 500 µm of line pitch at 180 °C, a grid-type transparent electrode (TE) with a sheet resistance of ∼7 Ω sq−1 and a dc to optical conductivity ratio of ∼300 at ∼84.2% optical transmittance was obtained, values that were superior to previously reported results. In order to evaluate the durability of the TE under bending stresses, the sheet resistance was measured as the number of bending cycles was increased. The sheet resistance of the Ag grid electrode increased only slightly, by less than 20% from its original value, even after 500 cycles. To the best of our knowledge, this is the first time that Ag (invisible) grid TEs have been fabricated on PET substrates by ac voltage applied EHD jet printing.