A low-cost, precise piezoelectric droplet-on-demand generator

We present the design of a piezoelectric droplet-on-demand generator capable of producing droplets of highly repeatable size ranging from 0.5 to 1.4 mm in diameter. The generator is low cost and simple to fabricate. We demonstrate the manner in which droplet diameter can be controlled through variation of the piezoelectric driving waveform parameters, outlet pressure, and nozzle diameter.National Science Foundation (U.S.) (Grants CBET-0966452 and CMMI-1333242)National Science Foundation (U.S.) (Fellowship

Adjoint-based optimization for inkjet printing

In this thesis the flow inside inkjet printhead microchannels is analysed using a two- parameter low Mach number expansion of the compressible Navier–Stokes equations and a reduced order model for the free surface flow inside the inkjet nozzle. The channel flow is separated into equations for an incompressible flow with no acoustic oscillations and equations for thermoviscous acoustic oscillations with no mean flow. This thesis concerns two types of optimal control problems. The optimal control problem of the first type is finding a velocity profile of the piezo-electric actuator that eliminates residual oscillations after a droplet is ejected. The cost function is the sum of the acoustic energy in the channel and the surface energy of the spherical cap of ink at the end of the nozzle at a given time. This problem is approached by obtaining the sensitivity of the total energy inside an inkjet microchannel with respect to boundary forcing using the adjoint method. Using gradient-based optimization algorithms, optimal waveforms are found that minimize the objective value at various final times and for geometries with increasing complexity. Physical interpretation to the optimal waveforms profiles is provided, and the exploited mechanisms are revealed. The optimal control problem of the second type is finding a shape of the inkjet printhead channel that maximises dissipation of the acoustic oscillations, without increasing the pressure drop required to drive the steady flow. Similarly, the adjoint approach is used to obtain the sensitivity of the acoustic flow eigenvalues with respect to boundary deformations in Hadamard form. Knowing the shape sensitivity of the incompressible flow viscous dissipation, the constrained optimization problem is solved to find a design that has the same viscous dissipation for the steady flow but a 40% larger decay rate for the oscillating flow. The final shape is not straightforward and would have been difficult to achieve through physical insight or trial and error. It could be improved further by adapting the parameters that describe the shape, but in this case the improvement would be small. The method is general and could be applied to many different applications in microfluidics. In summary, the methods in this thesis are promising techniques in the design and optimization of inkjet printheads. The discussed numerical techniques and the gained physical understanding can be used to automatically find the optimal design parameters, or, at a minimum, accelerate the experimental trial and error processes.This project has received funding from the European Unions Horizon 2020 research and innovation programme under Grant Agreement No. H2020-MSCA-ITN-2015

Measurements of conductive film

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonPrinted electronics is a combination of electronics and printing technologies commonly used in the publication industry such as screen, inkjet, and roll to roll printing. The measurements of conductive film particularly the conductive paste is the main objective of this thesis. The conductive paste consists of conductive filler, adhesive and solvent. Each component affects the electrical, and mechanical properties of the finished conductive film product. The measurements of conductive film have three field of study. The first category is the lifetime performance measurement of conductive film using environmental testing. A screen printed carbon, silver and a developmental paste were categorised to environmental testing and third harmonic measurement. The second category is the measurement AC Impedance and DC resistance of conductive ink during cure. During the curing of the pastes, the AC impedance and DC resistance were monitored. A LabVIEW program was developed to control the AC impedance analyser, DC resistance ohmmeter, and convection oven. Samples were measured whilst curing at different curing temperatures and for a range of particle loadings. Particle loading is the percentage of conductive filler against the rest of the chemical in the conductive paste. The last category was defect detection using the combination of electromechanical testing, a Scanning Electron Microscope (SEM) and an Infrared (IR) imaging technique. Printed carbon and silver were mechanically aged by bending the printed structure up to 100 k times. The results from the lifetime performance measurements on carbon, silver and the developmental paste showed the polymer resin behaviour in high humidity and high temperature environments. The increased oxidation rate due to the elevated temperatures affected the conductive particle of certain pastes. The third harmonic testing technique was able to detect failures on conductive film in the form of width reduction. The AC impedance measurement technique could indicate the final resistivity value. The AC impedance measurement was affected by the test frequency used while the ink is in liquid state. Correct test frequency setting will have less noise and less impedance value, vital in predicting the final cured resistance of the printed paste. The curing temperature affects the final cured resistance value while the particle loading affects the rate of curing of conductive film. The electrical measurement on mechanically aged samples showed that the carbon prints have its resistance readings below its initial value while the silver prints resistance increased. SEM images shows that the carbon print indicates no visual damage on the surface after 100 k bent cycle, while physical defects were observed in silver prints. The infrared measurements on carbon prints showed an increase in temperature while developments of heat patches were observed on silver prints. Difference in emissivity values of materials used provided the contrast effect which plays an important role in detecting defect using infrared imaging technique because. Third harmonic application to the printed electronics is new to this field. Normally, testing is done using environmental testing to determine the lifetime performance of the conductive film. This is effective however requires a lot of time and effort to produce a result. AC Impedance is used widely and the application can be seen on cured printed electronics. The application and measurement of AC impedance during cure and DC resistance measurement has indicated initial resistivity values. The measurement has further the effect of using AC impedance on different curing temperature and particle loading. The phase measurement as well has brought insight of degree of curing. The application of infra-red imaging technique to the mechanically aged device has produced a result that DC resistance and SEM imaging failed to detect. Normally DC resistance measurement was used as quality assessment tool but test shows on mechanically aged product failed to detect increase in resistance due to mechanical aging techqnique

Inkjet printing digital image generation and compensation for surface chemistry effects

Additive manufacturing (AM) of electronic materials using digital inkjet printing (DIJP) is of research interests nowadays because of its potential benefits in the semiconductor industry. Current trends in manufacturing electronics feature DIJP as a key technology to enable the production of customised and microscale functional devices. However, the fabrication of microelectronic components at large scale demands fast printing of tight features with high dimensional accuracy on substrates with varied surface topography which push inkjet printing process to its limits. To understand the DIJP droplet deposition on such substrates, generally requires computational fluid dynamics modelling which is limited in its physics approximation of surface interactions. Otherwise, a kind of “trial and error” approach to determining how the ink spreads, coalesce and solidifies over the substrate is used, often a very time-consuming process. Consequently, this thesis aims to develop new modelling techniques to predict fast and accurately the surface morphology of inkjet-printed features, enabling the optimisation of DIJP control parameters and the compensation of images for better dimensional accuracy of printed electronics devices. This investigation explored three categories of modelling techniques to predict the surface morphology of inkjet-printed features: physics-based, data-driven and hybrid physics-based and data-driven. Two physics-based numerical models were developed to reproduce the inkjet printing droplet deposition and solidification processes using a lattice Boltzmann (LB) multiphase flow model and a finite element (FE) chemo-mechanical model, respectively. The LB model was limited to the simulation of single tracks and small square films and the FE model was mainly employed for the distortion prediction of multilayer objects. Alternatively, two data-driven models were implemented to reconstruct the surface morphology of single tracks and free-form films using images from experiments: image analysis (IA) and shape from shading (SFS). IA assumed volume conservation and minimal energy drop shape to reconstruct the surface while SFS resolved the height of the image using a reflection model. Finally, a hybrid physics-based and data-driven approach was generated which incorporates the uncertainty of droplet landing position and footprint, hydrostatic analytical models, empirical correlations derived from experiments, and relationships derived from physics-based models to predict fast and accurately any free-form layer pattern as a function of physical properties, printing parameters and wetting characteristics. Depending on the selection of the modelling technique to predict the deformed geometry, further considerations were required. For the purely physics-based and data-driven models, a surrogate model using response surface equations was employed to create a transfer function between printing parameters, substrate wetting characteristics and the resulting surface morphology. The development of a transfer function significantly decreased the computational time required by purely physics-based models and enabled the parameter optimisation using a multi-objective genetic algorithm approach to attain the best film dimensional accuracy. Additionally, for multilayer printing applications, a layer compensation approach was achieved utilizing a convolutional neural network trained by the predicted (deformed) geometry to reduce the out of plane error to target shape. The optimal combination of printing parameters and input image compensation helped with the generation of fine features that are traditionally difficult for inkjet, improved resolution of edges and corners by reducing the amount of overflow from material, accounted for varied topography and capillary effects thereof on the substrate surface and considered the effect of multiple layers built up on each other. This study revealed for the first time to the best of our knowledge the role of the droplet location and footprint diameter uncertainty in the stability and uniformity of printed features. Using a droplet overlap map which was proposed as a universal technique to assess the effect of printing parameters on pattern geometry, it was shown that reliable limits for break-up and bulging of printed features were obtained. Considering droplet position and diameter size uncertainties, predicted optimal printing parameters improved the quality of printed films on substrates with different wettability. Finally, a stability diagram illustrating the onset of bulging and separation for lines and films as well as the optimal drop spacing, printing frequency and stand-off distance was generated to inform visually the results. This investigation has developed a predictive physics-based model of the surface morphology of DIJP features on heterogeneous substrates and a methodology to find the printing parameters and compensate the layer geometry required for optimum part dimensional accuracy. The simplicity of the proposed technique makes it a promising tool for model driven inkjet printing process optimization, including real time process control and paves the way for better quality devices in the printed electronics industry

Inkjet printing digital image generation and compensation for surface chemistry effects

Additive manufacturing (AM) of electronic materials using digital inkjet printing (DIJP) is of research interests nowadays because of its potential benefits in the semiconductor industry. Current trends in manufacturing electronics feature DIJP as a key technology to enable the production of customised and microscale functional devices. However, the fabrication of microelectronic components at large scale demands fast printing of tight features with high dimensional accuracy on substrates with varied surface topography which push inkjet printing process to its limits. To understand the DIJP droplet deposition on such substrates, generally requires computational fluid dynamics modelling which is limited in its physics approximation of surface interactions. Otherwise, a kind of “trial and error” approach to determining how the ink spreads, coalesce and solidifies over the substrate is used, often a very time-consuming process. Consequently, this thesis aims to develop new modelling techniques to predict fast and accurately the surface morphology of inkjet-printed features, enabling the optimisation of DIJP control parameters and the compensation of images for better dimensional accuracy of printed electronics devices. This investigation explored three categories of modelling techniques to predict the surface morphology of inkjet-printed features: physics-based, data-driven and hybrid physics-based and data-driven. Two physics-based numerical models were developed to reproduce the inkjet printing droplet deposition and solidification processes using a lattice Boltzmann (LB) multiphase flow model and a finite element (FE) chemo-mechanical model, respectively. The LB model was limited to the simulation of single tracks and small square films and the FE model was mainly employed for the distortion prediction of multilayer objects. Alternatively, two data-driven models were implemented to reconstruct the surface morphology of single tracks and free-form films using images from experiments: image analysis (IA) and shape from shading (SFS). IA assumed volume conservation and minimal energy drop shape to reconstruct the surface while SFS resolved the height of the image using a reflection model. Finally, a hybrid physics-based and data-driven approach was generated which incorporates the uncertainty of droplet landing position and footprint, hydrostatic analytical models, empirical correlations derived from experiments, and relationships derived from physics-based models to predict fast and accurately any free-form layer pattern as a function of physical properties, printing parameters and wetting characteristics. Depending on the selection of the modelling technique to predict the deformed geometry, further considerations were required. For the purely physics-based and data-driven models, a surrogate model using response surface equations was employed to create a transfer function between printing parameters, substrate wetting characteristics and the resulting surface morphology. The development of a transfer function significantly decreased the computational time required by purely physics-based models and enabled the parameter optimisation using a multi-objective genetic algorithm approach to attain the best film dimensional accuracy. Additionally, for multilayer printing applications, a layer compensation approach was achieved utilizing a convolutional neural network trained by the predicted (deformed) geometry to reduce the out of plane error to target shape. The optimal combination of printing parameters and input image compensation helped with the generation of fine features that are traditionally difficult for inkjet, improved resolution of edges and corners by reducing the amount of overflow from material, accounted for varied topography and capillary effects thereof on the substrate surface and considered the effect of multiple layers built up on each other. This study revealed for the first time to the best of our knowledge the role of the droplet location and footprint diameter uncertainty in the stability and uniformity of printed features. Using a droplet overlap map which was proposed as a universal technique to assess the effect of printing parameters on pattern geometry, it was shown that reliable limits for break-up and bulging of printed features were obtained. Considering droplet position and diameter size uncertainties, predicted optimal printing parameters improved the quality of printed films on substrates with different wettability. Finally, a stability diagram illustrating the onset of bulging and separation for lines and films as well as the optimal drop spacing, printing frequency and stand-off distance was generated to inform visually the results. This investigation has developed a predictive physics-based model of the surface morphology of DIJP features on heterogeneous substrates and a methodology to find the printing parameters and compensate the layer geometry required for optimum part dimensional accuracy. The simplicity of the proposed technique makes it a promising tool for model driven inkjet printing process optimization, including real time process control and paves the way for better quality devices in the printed electronics industry

Tailored composite microstructures via direct ink writing with acoustophoresis

Additive manufacturing techniques which enable control over the placement and orientation of particles within composite inks can produce structures with tailored gradients in structural and functional properties. One such technique is direct ink writing with acoustophoresis (DIWA), wherein a composite ink is extruded through a direct-write nozzle containing a standing bulk acoustic wave which aligns and positions particles. Driving force-based scaling relationships contextualize processing-structure relationships in DIWA. In a series of experiments which progress in geometric complexity from basic primitives to complete structures, a physical framework is constructed for controlling filament microstructures and external geometries in DIWA. In isolated filaments, there are trade-offs between focusing and form holding. Increasing the ink viscosity, increasing the print speed, and decreasing the acoustic wave amplitude widen the spatial distribution of particles in agreement with scaling relationships for acoustophoresis, but more viscous inks improve form holding. In the print bead between the nozzle and substrate, digital image analysis is used to measure filament stability, nozzle wetting, and rotational flows in the low-viscosity inks required for acoustophoresis. Viscocapillary lubrication theory accurately predicts the bounds of stability, and the contact line position and angle can be used to detect the beginnings of filament rupture, allowing for algorithms which prevent rupture in-situ. In polygonal prisms, the internal structure of filaments changes during deposition into layer-by-layer and bath support gels. Filament microstructures change during deposition, during relaxation, and when the nozzle returns to write neighboring lines. Experimental flow fields and particle distributions suggest that inertia and viscoplasticity influence the filament microstructure just after deposition and the microstructure of neighboring filaments, and interfacial energy and gravity cause filaments to spread after deposition. An analytical model is proposed to diagnose sources of direction dependent microstructures as a function of acoustics, inertia, viscous dissipation, and stage calibration. The support geometry can be used to accentuate or suppress aspects of this direction dependence. Finally, inertia swells written corners, and capillarity smooths written corners, leading to distortions in filament microstructures at corners. Bath support suppresses these corner defects

Laser diagnosis of gas turbine fuel sprays; scaling effects on NOx emissions and stability

This thesis first provided strategic recommendations for the research sponsor, Rolls- Royce plc (RR) and then applied optical diagnostics to measure aero gas turbine fuel spray properties in order to predict Oxides of Nitrogen (NOx) emissions and combustion instability. Analysis of the large civil aero engine sector suggested possible courses of action for RR to protect itself from short-term market volatilities and also prepare for three long term changes in strategic operating context: air traffic growth; tighter United Nations enforced aero engine combustion emissions legislation and entry of civil aviation into the European Union Emissions Trading Scheme. A collaborative game theoretic approach was explored during the pre-competitive, pre-technology, capability acquisition aero engine design phase on unproven future technologies to reduce R&D expenditures, development times and the costs of failure. Lean Prevapourised Premixed combustion demands excellent spray atomisation quality to sustain combustion efficiency, stability and to minimise pollutants. Post development of an improved procedure to calibrate laser signals, methodology to predict NOx and technique to optimise rig operating conditions that minimised fractional discrepancies in two-phase flow behaviour with corresponding engine conditions, this thesis applied quantitative Planar Laser Induced Fluorescence (PLIF) and Laser Sheet Dropsizing (LSD) to measure the fuel placement and dropsize distribution in the near nozzle regions of RR liquid-fuelled hybrid, airblast and pressure-swirl sprays. Measurements were made under non-combusting, low pressure conditions and results were processed to identify fuel injector designs that exhibited low emissions and high stability for the Affordable Near Term Low Emissions (ANTLE) and Instability Control of Low Emission Aero-Engine Combustors (ICLEAC) engine demonstrator programmes. Results also provided validation data and boundary conditions for spray computational codes. Research findings will improve RR core competencies in fuel injection research to accelerate the development and deployment of low emissions aero engine technology

NASA Tech Briefs, April 1997

Topics covered include: Video and Imaging; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery/Automation; Manufacturing/Fabrication; Mathematics and Information Sciences; Life Sciences; Books and Reports

Advanced ultrasonic ambient ionisation sources for mass spectrometry and microdroplet accelerated reactions

This PhD thesis presents two related projects, linked because both benefit from the use of a specific kind of ultrasonic nebulizer. The first project describes the development and subsequent application of a novel droplet-on-demand ionisation source which provides a solution to some of the limitations currently associated with performing mass calibration for mass spectrometry. After an initial development phase using a commercially available piezoelectric droplet-on-demand device, the system chosen for use was a Porous Ultrasonic Piezoelectric Plate (PUPP) device coupled to a conventional micro/nano-electrospray system. The PUPP system was used in the analysis of a highly complex organic matter sample, Suwannee River Fulvic Acid, and used encoded internal recalibration to generate high confidence automated peak assignment. Due to the droplet-on-demand nature of the PUPP device, calibrant could be introduced whenever needed during analysis, and the intensity of the calibrant peak relative to sample peaks could be adjusted through the system’s ability to modulate the volume of calibrant sprayed, in real time. Although the analysis of the samples using encoded internal recalibration showed no improvement in the peak assignment as expected, the workflow to get to the same stage is significantly simplified. The system is entirely automated, meaning that large batches of samples could be analysed, calibrated, and processed without the need for manual input by a user for each individual spectrum. Further beneficial applications of the PUPP ionisation source are also presented, including the capability to perform rapid analysis of samples, component confirmation analysis and real-time adduct modification. Additional tasks which were undertaken to support the development process of each project are presented, including the development of a 3D printed fused silica capillary grinding system to make custom electrospray needles and the software written to process the complex data generated for the ionisation source. Finally, recommendations for further development and other potential applications of the ionisation source are presented, which were beyond the scope of this project. The second project, aimed to use the PUPP system to perform chemical synthesis in microdroplets, by taking advantage of the significantly enhanced chemical reaction rates observed inside microdroplets reported in the literature. The Hydrazone reaction is shown to proceed offline using the PUPP system. However, the reaction is shown to preferentially form the E isomer when performed inside a microdroplet, whilst during bulk synthesis the Z isomer is preferentially formed. Evidence for this is given, including the subsequent photorelaxation of the E isomer to form the more stable Z isomer. Results indicated that the Pechmann condensation would be a new and suitable reaction which undergoes this reaction rate enhancement. However, this same success could not be achieved away from the mass spectrometer, and this was later discovered to be because of the difference in ionisation efficiencies of the reactants and products, which masked the true picture of the acceleration effect. Therefore, the decision was taken to shift the focus of the project towards establishing a robust screening method for microdroplet accelerated reactions which could be suitable for scale-up investigations, which is presented within this thesis