Dynamic electromechanical behavior of a triple-layer piezoelectric composite cylinder with imperfect interfaces

AbstractThe dynamic electromechanical behavior of a triple-layer piezoelectric composite cylinder with imperfect interfaces is investigated. The composite cylinder is constructed by two elastic layers and an embedded piezoelectric layer. A linear spring model is adopted to describe the weakness of imperfect interface. The exact analysis is performed by the state space method and normal mode expansion method. The determining procedure for the eigenfunction and the proof of the orthogonal property of the eigenfunction is presented for an imperfectly bonded triple-layer piezoelectric composite cylinder. The obtained solution is valid for analyzing the dynamic electromechanical behavior of composite cylinder with arbitrary thickness for both elastic and piezoelectric layers. Numerical results show that the weakness of imperfect interface has significant effect on the transient electromechanical responses of piezoelectric composite cylinder

Analysis and Computational Modelling of Drop Formation for Piezo-Actuated DOD Micro-Dispenser

Master'sMASTER OF ENGINEERIN

Water droplet machining and droplet impact mechanics

Water Droplet Machining (WDM) is a new manufacturing process, which uses a series of high-velocity, pure-water droplets to impact and erode metal workpieces, for the purpose of through-cutting, milling and surface profiling. The process is conducted within a vacuum environment to suppress aerodynamic drag and atomization of the waterjet and droplet stream. This preserves droplet momentum and allows for a more efficient transfer of energy between the water and workpiece, than in standard atmospheric pressure. As a new manufacturing technique, parameter-specific details and characteristics of this process are absent from the scientific literature. Furthermore, the erosion mechanisms involved in droplet-solid interactions are not well-understood. Therefore, this research aims to elucidate the capabilities of WDM, and uncover the mechanics involved in droplet impact. This is done by investigating the force imparted by liquid droplets across a wide range of impact parameters, where a novel force model is developed for inertial-dominated impacts. A force comparison is made between continuous jet and droplet train impacts, where the findings show that a droplet train has a higher erosive potential than its continuous jet counterpart, owing to the higher forces exerted by individual droplets. In addition, the stress state inside of a material subject to a Hertzian contact, which is connected to this research as it emulates the axisymmetric nature of a droplet-like loading, is explored using integrated photoelasticity. Finally, the process parameters and erosion characteristics of WDM are investigated using a custom-fabricated machine, where a range of waterjet-types (and droplet trains) are produced. The industrial efficacy of this process is evaluated by manufacturing a diverse array of engineering materials

Electric and Magnetic Manipulation of Liquid Metals

Over the past decade, gallium-based liquid metals have attracted enormous attention, emerging as a new cutting-edge multi-functional material for reconfigurable electronics, soft robotics, microfluidics, and biomedical applications, based on utilizing the intrinsic advantages of liquid metal. These unique advantages that combine high electrical conductivity, thermal conductivity, biocompatibility, low mechanical compliance, and viscosity all-in-one make the liquid metal applicable for a tremendous number of applications. Moreover, the self-passivating oxide skin of the liquid metal in an ambient environment forms a unique core (oxide skin)-shell (liquid metal) structure and provides a new strategy for two-dimensional thin films with a thickness of a few nanometers. The reports on the liquid metal can be mainly divided into three categories: 1) liquid-metal-based composite structures; 2) the core-shell strategy for thin films; and 3) electrochemical manipulation of the liquid metal in electrolyte. The liquid metal (LM) composites represent material systems in which LM alloys are either suspended as small droplets within a soft polymer matrix or mixed with metallic nanoparticles to form a biphasic composition, through which the electrical, dielectric, and thermal properties of composites can be controlled, thus enabling their applications in soft-matter sensing, actuation, and energy harvesting. Moreover, the fluidity and conductivity of the liquid metal make it suitable to be directly patterned (i.e., liquid metal ink) on various soft substrates (e.g., polydimethylsiloxane (PDMS) for ultra-stretchable electronics. Compared to the traditional electronics, which are typically composed of intrinsically rigid materials that have limited deformability, the liquid metal based soft electronics are highly flexible, stretchable, and conformable. Most importantly, they are capable of electrical self-healing, enabling their electrical functionality, even under severe damage. These properties and applications of liquid metal composites show great potential for practical usage

The Generation And Experimental Study Of Microscale Droplets In Drop-On-Demand Inkjet Printing

Ph.DDOCTOR OF PHILOSOPH

Electrospray and Superlens Effect of Microdroplets for Laser-Assisted Nanomanufacturing

Nanoparticles of various materials are known to exhibit excellent mechanical, chemical, electrical, and optical properties. However, it is difficult to deposit and transform nanoparticles into large two-dimensional and three-dimensional structures, such as thin films and discrete arrays. Electrospray technology and laser heating enable the deposition of these nanoparticles through the dual role of microdroplets as nanoparticle carriers and superlenses. The main goals of this dissertation are to delineate the electrospray modes, to achieve subwavelength focusing, and to enable a process for the deposition of nanoparticles into microlayers and discrete nanodots (a nanodot is a cluster of nanoparticles) on rigid and flexible substrates. This additive manufacturing process is based on the electrospray generation of water microdroplets that carry nanoparticles onto a substrate and the laser sintering of these nanoparticles. The process involves injecting nanoparticles (contained inside electric field-driven water microdroplets) into a hollow laser beam. The laser beam heats the droplets, causing the water to evaporate and the nanoparticles to sinter and form deposit of material on the substrate. The electrohydrodynamic inkjet printing of nanoparticle suspensions has been accomplished by the operation of an electrospray in microdripping mode and it allows the deposition of monodisperse microdroplets containing nanoparticles into discrete nanodot arrays, narrow lines, and thin films. For flow rates with low Reynolds number, the mode changes from dripping to microdripping mode, and then to a planar oscillating microdripping mode as the electric capillary number, Cae increases. The microdripping mode which is important for depositing discrete array of nanodots is found to occur in a narrow range, 2 ≤ Cae ≤ 2:5. The effect of the physical properties on the droplet size and frequency of droplet formation is more precisely described by the relative influence of the electric, gravity, viscous, and capillary forces. A scaling analysis is derived from a fundamental force balance and has yielded a parameter based on the electric capillary number, capillary number, and Bond number. Results for different nanoparticle suspensions with a wide range of physical properties show that the normalized radius of droplet, can be correlated using this parameter in both dripping and microdripping modes. The same parameter also correlates the normalized frequency of droplet formation, N*d as an increasing function in the microdripping mode. Viscosity affects the shape of the cone by resisting its deformation and thus promoting a stable microdripping mode. Reduction in surface tension decreases the droplet size in the electrospray modes. However, the capillary size and electrical conductivity have minimal effect on the size of the ejected droplets. Electrical conductivity affects the transition between microdripping and oscillating microdripping modes. Based on this analysis, it is possible to design the electrospray to produce uniform monodisperse droplets by manipulating the voltage at the electrode, for any desired nanoparticle concentration of a suspension to be sintered on a substrate. For the fabrication of nanodots, a laser beam of wavelength λ = 1064 nm was focused to a diameter smaller than its wavelength. When the microdroplets did not carry nanoparticles, the subwavelength focusing of the laser yielded nanoholes smaller than its wavelength. Results show that tiny features with high resolution can be created by loading microdroplets with nanoparticles and squeezing the laser beam to subwavelength regions. Nanodots of silicon and germanium with diameters between 100 - 500 nm have been deposited on a silicon substrate. This study demonstrates an interdisciplinary mechanism to achieve subwavelength focusing in a laser process. In this process, the microdroplets serve as both a nanoparticle carrier and a superlens that focuses a laser beam to subwavelength diameters up to λ/10, thus overcoming the diffraction limit. The microdroplets are generated from a suspension of nanoparticles using an electrospray technique and the superlens characteristic of these microdroplets is attributed to three optical phenomena such as Maxwell\u27s fish eye lens or Luneberg lens, evanescent waves by laser scattering, and evanescent waves by the total internal reflection principle. A microfluidic cooling effect can also contribute to creating subwavelength features. In summary, this work describes a new laser-assisted additive manufacturing process for the fabrication of nanodots and microlayers using nanoparticles of different materials. In this process, microdroplets from an electrospray are used as nanoparticle carriers and superlenses to focus the laser to a diameter smaller than its wavelength. While this process is demonstrated to produce subwavelength holes and nanodots, the process is scalable to produce narrow lines and thin films of semiconductor materials by an additive manufacturing technique. This process extends the application of infrared lasers to the production of nanostructures and nanofeatures, and, therefore, provides a novel technology for nanomanufacturing

Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018

Micro/Nano Structures and Systems

Micro/Nano Structures and Systems: Analysis, Design, Manufacturing, and Reliability is a comprehensive guide that explores the various aspects of micro- and nanostructures and systems. From analysis and design to manufacturing and reliability, this reprint provides a thorough understanding of the latest methods and techniques used in the field. With an emphasis on modern computational and analytical methods and their integration with experimental techniques, this reprint is an invaluable resource for researchers and engineers working in the field of micro- and nanosystems, including micromachines, additive manufacturing at the microscale, micro/nano-electromechanical systems, and more. Written by leading experts in the field, this reprint offers a complete understanding of the physical and mechanical behavior of micro- and nanostructures, making it an essential reference for professionals in this field

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