Electronic Multi-material Fibers and Textiles: Novel Designs and Applications

Chaoqun Dong
EPFL, 2021
EPFL thesis

Abstract

Flexible electronics and particularly soft fibers and textiles are becoming key components in rapidly developing fields such as robotics, health and personal care, sensing, or implantable and wearable devices. Thus far however, the ability to impart soft and stretchable fibers with advanced electronic functionalities, including efficient energy harvesting, remains limited. The recent development of the concept of multi-material fiber drawing has opened novel opportunities in the integration of novel materials and their organization into complex architectures, resulting in unexpected functionalities. Yet, two limitations have resisted this line of research: using fiber-based constructs for advanced microfluidics, and demonstrating state-of-the-art fibers and textiles for energy harvesting and self-powered sensing. In this thesis, via a combination of fundamental understanding and engineering of materials processing, rheology, mechanical and electrical engineering, we significantly advanced the range of materials, architectures and functionalities achievable for multi-material electronic fibers. We in particular achieved three main objectives. First, we demonstrate a uniform capillary-like fiber that integrates an encapsulated micro-channel and an embedded capacitor system within a polymeric cladding. It shows versatile functionalities applicable to microfluidic sensing including the monitoring of the presence and travel distance of a fluid, real-time sensing of a wide range of flowrate, and high-accuracy identification of the static dielectric constant of fluid. We then demonstrate the scalable fabrication of advanced triboelectric fibers that combine a micro-textured elastomer surface with the integration of several liquid metal electrodes. Such fibers exhibit high efficiencies on par with planar systems regardless of repeated large deformations. They can be woven into machine-washable textiles with high electrical outputs up to 490 V, 175 nC. We also demonstrate their self-powered breathing monitoring and gesture sensing capabilities. The third objective arose in the course of the second project Ì¶ attempting to circumvent the limitations associated with single-electrode triboelectric fibers and unravel more activation states of the devices. We design and fabricate a stretchable multi-material contact-separation mode triboelectric fiber that can generate electricity from reversible compression and stretching. The fiber is constituted of two stretchable and conductive composite-based micro-structured triboelectric parts, which are separated by a large gap and surrounded by a water repellent elastomeric cladding. Finite element analysis is performed to deeply understand the kinetic deformations of the fiber system, and show the level of control and engineering of the mechanical behaviors that can be achieved through application-targeted fiber designs. The novel triboelectric fiber designs that we propose, the unprecedented simplicity and throughput of the manufacturing process, together with the inherent deformability and excellent electrical outputs of the demonstrated fibers and textiles, alleviate the challenges associated with the integration of high performance energy-harvesting systems within soft and wearable constructs. With novel sensing and energy harvesting soft fibers, the results of this thesis pave the way towards novel devices and applications in health and personal care, implantable systems and wearable devices.

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https://infoscience.epfl.ch/record/283398?ln=en

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Chaoqun Dong
EPFL, 2021
EPFL thesis

Abstract

Official source

https://infoscience.epfl.ch/record/283398?ln=en

About this result

Related concepts (21)

Related concepts

Related publications (27)

Related publications

Design and Fabrication of Stretchable Photonic Fibers

Nicola Bartolomei

Optical fibers have reshaped the technological landscape, from optical networks and high-speed data communication to in situ imaging and non-invasive surgery methods. The revolution allowed by these fibers has been made possible by its fabrication method, the thermal drawing process, which combines high scalability and nanoscale fabrication accuracy. Despite tremendous successes, silica step-index and photonic crystal fibers have held intrinsic limitations due to their mechanical rigidity and fragility, limiting their possible applications . There is however an increasing demand for optical fibers that could guide light efficiently while sustaining large deformations in fields like robotics, smart textiles and the automotive world. Other fields in sensing, helath care or advanced textiles could benefit from soft fibers that could display tunable optical effects. Techniques like lithography and molding have proven valuable to fabricate complex elastomeric photonic fibers, but their limited scalability intrinsically limits their use in several fields of application. On the other hand, scalable fabrication techniques like extrusion guarantee the desired throughput but fail to deliver the architectural complexity required to realize softfibers advanced optical properties. In this thesis, we propose to exploit the thermal drawing process to realize different types of soft and highly stretchable optical fibers, from the classic step-index architecture to 1D photonic crystal fibers, liquid core fibers and 2D photonic crystal fibers. To achieve this overall objective, we first establish a theoretical framework to evaluate the material requirements from the rheological, optical and mechanical point of view. After selecting the materials, we develop a step-by-step fabrication process that starts from the material pellets and ends with the fabrication of meters of elastomeric photonic fiber via thermal drawing. We then move on to fully characterize the optical and mechanical properties of the fibers and design several fiber-based devices with specific optical effects. More specifically in Chapter 2, we demonstrate the materials selection, innovative fabrication process, and the optical and mechanical characterizations to realize a soft optical wave-guide based on a step-index design. To highlight its optical and mechanical performance, we demonstrate a strain sensing sport gear that integrates this newly developed fiber. In chapter 3, we go one step further in the control over feature size by going about a similar demonstration for a 1D photonic crystal fibers based on all-elastomeric materials, with feature sizes down to sub-100 nm. We show in particular a mechanochromic fiber that can reversibly change color upon stretching. In Chapter 4, we propose a series of other fiber architectures based on our scientific and technological achievements that include a multicore stretchable step-index fiber that form the basis of an advanced demonstrator of a soft fiber with multiple channels and functionalities found in endoscopes. We also present preliminary results on a liquid-core step index fiber, and a stretchable 2D photonic crystal fiber, that pave the way towards highly complex and high-performance soft optical fiber devices.

EPFL2021

Modeling and Simulation of Energy Efficient Milling Process Plans for Prismatic Parts

Nenad Nesic

The milling process has been continuously optimized from many aspects: forces, velocities, stability, quality. Numerous papers have been published that report results in the domain of toolpath optimization with criteria such as raising the quality of the machined part, obtaining a stable machining process and maximizing the material removal rate. However, only recently researchers have started investigating the ecological impact of machining processes. With the constantly increasing prices of electrical energy and all environmental problems caused by the production and waste of the energy, it has become indispensable to look for ways to optimize machining processes from the energy consumption aspect, too. It is in this domain, then, that the work described in this dissertation contributes – to add a new criterion for the sustainable operation of machine tools: reducing the energy consumption during the use phase of the machine tool. The total energy spent in a machining process is the sum of power spent by all machine tool subsystems multiplied by the time that they are working. Therefore, the operating strategies for increasing energy efficiency for the high-speed machining processes must be oriented towards the reduction of the total machining time (productive and unproductive) and reduction of instantaneous consumed power in the machining process or, preferably, both. There are many causes for milling process time and energy inefficiency. The major sources of potential time reductions include: (i) the issues related to the geometry and topology of the toolpath („air-time”, overlapping segments, gouge and uncut regions, orientation of the toolpath), (ii) the issues related to the kinematics of the feed drives (the feed velocity/acceleration profile). The possible domains for power consumption reduction are related to the forces that exist in the machining process (cutting, inertial, gravitational and friction forces). The power invested to overcome the cutting force is necessary for the machining process but its consumption should be optimized through constant cutting engagement and feedrate scheduling strategies. The other forces are responsible for the pure mechanical power loss and they should be minimized. The optimization variables for inertial and gravitational forces include the feed motion profile and moving mass configuration, while friction losses are load and/or velocity dependent. In addition, there are some power losses in the electric components of machine tool drives (electrical power losses), whose dependency on velocity and mechanical load can also be modeled. Despite many research efforts to analyze and model the phenomena causing inefficiency of the machining process, they are usually not taken into account during milling process planning. In fact, rare are the attempts to use this knowledge to optimize the milling process with more than one of the above mentioned criteria. The reason for that lies in the fact that increasing the instantaneous values of tool engagement and feedrate in order to minimize total machining time also increases the consumed power and, indirectly, deteriorates the tool and/or destabilizes the cutting process. The existence of conflicting criteria in the objective functions imposes the use of evolutionary algorithms for multiobjective optimization. The process of experimental validation of such an optimization model requires costly and complex external hardware setup and it is also time consuming. Hence, there is an emerging need for the development of an accurate model, which would be used for the simulation of the milling process and testing the competing optimization strategies. The ultimate goal of contemporary manufacturing science and engineering is the development of a holistic virtual machine tool system. The motivation of this PhD research is to contribute to this objective by developing the “virtual milling process for prismatic parts (produced by 2.5D milling)”. This category of objects is selected, because the majority of CNC milling tasks can be performed using 2.5D milling. A very large number of mechanical parts are prismatic (their geometry consists exclusively of features that represent 2D contours extruded in a perpendicular direction). Parts that are even more complex are usually produced from a blank by a 2.5D roughing and 3D–5D finishing. Therefore, development of an accurate model of a 2.5D milling process represents a significant contribution to manufacturing engineering. Starting with above given problem description, we have defined the following research objectives: 1. Model power and energy consumption of a 2.5D milling machine as a function of the toolpath geometry (curvature and continuity), cutting engagement, real feedrate profiles and spindle rotational speed, taking into account moving mass configuration, all power losses (mechanical and electrical) in feed-axis and spindle drives and electromechanical constraints of servo drives; 2. Design an integrated software environment for simulation of the developed models; 3. Validate the model experimentally; 4. Demonstrate the potential of its use for multi-objective process optimization. Cutting engagement calculation is performed by using two competing methodologies, in order to make a comparison of their performances. The first one, the pixel based method, is based on discrete image processing, while the other, the exact method, is based on Boolean operations and vector geometry. The tests performed in more than 20 feature/toolpath combinations demonstrate that the exact method is more precise whereas the pixel-based method is computationally much faster. The machine tool operator commands a constant feedrate value. During the process, based on his/her subjective judgment, he/she can manually tune it to keep the process in the desired boundaries. One of the objectives of this research is to predict the real feedrate values so that they can be integrated in the part program before the process start. The feasible profiles of feed velocities for each toolpath segment are analyzed by answering the following questions: can the commanded feedrate be achieved and with what sequence of acceleration and deceleration phases, how much the tool has to slow down in corners and how does the feedrate profile degenerate in segments where the commanded feedrate cannot be reached? In order to determine all forces and torques, a machine tool model is developed. The following subsystems are modeled as rigid bodies (without vibrations): feed motor shaft, transmission, lead screw/nut pair, lead screw bearings, guides (sliding and rolling design), table with the workpiece and electrospindle (rotor, stator and bearings). All kinetic variables (linear and angular speeds; cutting, inertial and friction forces and torques) are then calculated in the joints of this multi-body system. The modeling of all speeds, forces and torques that occur in the machine tool system during the machining process, allows for calculation of various indicators of process time and energy efficiency: material removal rate, total machining time, useful power (invested in cutting), power loss due to the friction in the joints, power losses in electrical motors, electrical energy consumption of feed and spindle drives. In order to assess the accuracy and the reliability of the developed model two sets of experiments have been performed. The model validation is performed on several subsystem levels and the simulation results show a very good compliance with the experimental results. The first experimental setup consists of the force dynamometer, to measure cutting force components in linear axis directions, two laser optical position sensors, to measure the real feedrate and the power sensor, to measure the total power consumption of the machine tool electrical motors. The machining process was performed on the 6-axis machining center C.B. Ferrari A152 and the data acquisition platform was developed in LabVIEW 2010. The second experimental setup consists of the torque dynamometer, to measure the cutting torque directly on the spindle, the built-in current sensor that measures the motor current proportional to the electrical power consumed by the spindle and, again, the power sensor, to measure the total power consumption of the machine tool electrical motors. This time, MIKRON HPM 600U, a 5-axis milling machine equipped with the controller iTNC530, was used for the experimentation. The developed model is ready for practical implementation. Several examples have been prepared to demonstrate its capabilities in the domains of milling process simulation, sensitivity analysis and prospective optimization strategies. These examples include the prediction of various kinetostatic variables for given toolpaths, choice of the optimum machining strategy (minimization of machining time, moving mass and energy consumption) and process optimization by feedrate scheduling (reduction of cutting force fluctuation). As a conclusion, the major contribution of this PhD research is the development of a comprehensive rigid-body dynamics model of a machine tool system, aimed for the generation, simulation and optimization of 21⁄2D milling process plans. The model features several novelties compared to existing approaches: (i) it takes into account the machine tool rigid body dynamics and real tool kinematics in toolpath planning, (ii) it predicts all mechanical and electrical power losses in the machine tool system (iii) it allows the modeling of machine tool system electromechanical constraints. The model was experimentally validated on two real machine tools in different workshops and its capabilities for the simulation of different toolpath patterns and optimization of process parameters were successfully demonstrated using several examples.

EPFL2012

Some fields such as the Monitoring of Civil Engineering Structures, need very sensitive acceleration and inclination sensors with a high resolution at low accelerations (typically less than 1G) and moderate frequencies (typically less than 20 Hz) or very small inclinations (typically less than 1°). The instruments currently available for such measurements are either very high precision instruments (hence very costly), used in seismology and globe physics or cheaper products lacking the sensitivity needed and having inadequate measurements ranges both in frequency and intensity. Such a situation hinders considerably the updating of construction codes in seismic zones as well as the study of the complex soil-structure interaction phenomenon in risk areas. This thesis proposes to study the utilization of magnetic levitation for designing acceleration and inclination sensors, simple and sensitive enough to meet the needs of particular applications like the monitoring of civil engineering works. Levitating the seismic mass of an inertial sensor does free its design of all the constraints created by a mechanical link between the inertial mass and the base of the instrument, which render present instruments so complex and so expensive. Two levitation techniques have been investigated and used for designing and testing two prototypes. A triaxial acceleration sensor using the Active Magnetic Bearings technique and an uniaxial inclination sensor using passive diamagnetic levitation have thus been implemented and tested. Experimental results obtained with these prototypes are not better than those obtained with instruments currently available, but they do validate the concept. As part of this research, active magnetic levitation has been investigated under an angle somewhat different from its classical application since its use for the design of sensors is subject to constraints rather different from those inherent to its use as a bearing. Furthermore, since up to now, diamagnetism has found very few applications in engineering, the present study proposes an analytical model along with design criteria that can be used as a starting point for the study and implementation of micro-mechatronic systems based on diamagnetic levitation.