Zhang, Zhihua (2023). Development of automatic micromanipulation measurement system to analyse the mechanical strength of micro-sized materials. University of Birmingham. Ph.D.
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Zhang2023PhD.pdf
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Abstract
Biological and nonbiological micro-sized materials are widely used in many industry sectors. Measuring their mechanical strength is essential to optimise their performance from manufacturing, to further processing, storage and end-use applications. Among all available techniques to experimentally determine the mechanical strength of micro-sized materials, the micromanipulation technique originally developed in the University of Birmingham UK, based on diametrical compression of single microparticles between two parallel flats, is very powerful, and has evolved with several different versions of the apparatus and several analytical and numerical mathematical models to determine the intrinsic mechanical properties of the tested materials from the experimental data. The mechanical properties of the tested micro-sized materials determined by the micromanipulation technique, include their rupture strength, elasticity, plasticity and viscoelasticity. However, it is time-consuming, laborious and technically demanding as the micromanipulation and data analysis were mainly undertaken manually. Therefore, it is pivotal to improve the micromanipulation technique to achieve automatic measurement and automatic data analysis, which is the main objective of this PhD project. Moreover, some new micro-sized materials were tested using the enhanced micromanipulation technique with mathematical models to determine their intrinsic mechanical properties for a range of new applications.
In this study, a new control system has been developed based on the existing micromanipulation technique to automatically test single microparticles by modifying the existing hardware system and developing new software to enable autofocusing, auto image processing, and auto micromanipulation. The manually-operated micromanipulator to support the sample stage has been replaced by DC servo linear actuators with motion controllers to achieve automatic motion control. A passive autofocus algorithm based on the sharpness of images and only the sideview camera has been developed to autofocus single microparticles by moving the sample stage from side to side and end to end. An object detection algorithm based on Otsu thresholding, Canny edge detection, and blob detection algorithms has been developed to automatically locate single microparticles from the autofocused images to determine their size and position. Two other essential algorithms have also been developed to automatically determine the magnification of the optical system and to automatically detect possible debris adhered to the force transducer output probe.
In order to achieve automatic data analysis, three algorithms based on the “three-sigma rule”, a moving window and the Hertz model to identify the starting point where the onset of compression begins and an algorithm based on the maximum deceleration to locate the rupture point have been developed, and a software package has been developed incorporated with these algorithms to determine the rupture strength parameters and force-displacement data of single microparticles from the raw voltage-sampling sequence data obtained from micromanipulation experiments.
Some elastic and plastic models used for analysing the data from micromanipulation, indentation, and uniaxial compression and tensile tests have been summarised and general forms of equations for the force versus displacement have been developed, based on which general approaches to extend the elastic and plastic analysis to viscoelastic and viscoplastic analysis, and general principles and strategies to incorporate these models into software have been developed, which can also be used in other related applications. Another software package has been developed incorporated with some mathematical models, including the Hertz model, the plastic model, the viscoelastic model and the core/shell model based on the finite element model (FEM) simulation results, to determine the intrinsic mechanical properties of microparticles from the force-displacement (or force-time) data of micromanipulation.
Some new micro-sized materials, including the self-sensing microcapsules to fabricate smart composites, the fragrance oil microcapsules with low content of formaldehyde, and the porous polystyrene (PS) microspheres and the poly (lactic acid) (PLA) microspheres, which can be potentially used in a variety of applications, have been tested using the conventional micromanipulation technique and their data have been analysed using the developed data analysis software packages to determine their mechanical property parameters as well as to validate the developed data analysis software packages.
Three mathematical models have been developed to determine the mechanical strength parameters corresponding to maximum stress, and the elastic and viscoelastic properties of microneedles from the experimental data of micromanipulation. Six microneedle samples based on hyaluronic acid (HA) have been tested using the micromanipulation technique and their data were analysed using the three developed mathematical models to obtain their intrinsic mechanical property parameters which can be used to predict their penetration efficiency comprehensively and more reliably.
The fragrance oil microcapsules with low content of formaldehyde, and the porous PS microspheres have also been tested using both the developed automatic and conventional micromanipulation systems to validate the former and the results show that the experimental results of the mechanical strength of the tested samples generated from both systems have no significant difference. The developed data analysis software packages can be used both together with the automatic micromanipulation system and alone to analyse the experimental data from either the developed automatic or conventional micromanipulation systems. The data analysis time has been shortened from around 3 hours manually to within 20 minutes automatically using the developed data analysis software package. Moreover, the newly developed micromanipulation system can auto focus, detect and test microparticles with size of 3-1000 μm currently and is much easier to use, needs much less time and labour work to complete the same task. It is believed that the achievements from this project represent a step change in enhancing the capabilities of the micromanipulation technique, which has now been commercialised for being used by more and more users in academic and industry.
| Type of Work: | Thesis (Doctorates > Ph.D.) | ||||||||||||
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| Award Type: | Doctorates > Ph.D. | ||||||||||||
| Supervisor(s): |
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| Licence: | All rights reserved | ||||||||||||
| College/Faculty: | Colleges (2008 onwards) > College of Engineering & Physical Sciences | ||||||||||||
| School or Department: | School of Chemical Engineering | ||||||||||||
| Funders: | Other | ||||||||||||
| Other Funders: | Jiangsu Industrial Technology Research Institute (JITRI), China, Changzhou Institute of Advanced Manufacturing Technology (Institute of Robotics and Intelligent Equipment, JITRI), China, University of Birmingham, UK | ||||||||||||
| Subjects: | Q Science > QA Mathematics > QA76 Computer software T Technology > TJ Mechanical engineering and machinery T Technology > TP Chemical technology |
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| URI: | http://etheses.bham.ac.uk/id/eprint/13437 |
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