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dc.contributor.advisorSanjiv, Sambandan
dc.contributor.authorAvula, Benzamin
dc.date.accessioned2022-12-13T06:45:02Z
dc.date.available2022-12-13T06:45:02Z
dc.date.submitted2022
dc.identifier.urihttps://etd.iisc.ac.in/handle/2005/5947
dc.description.abstractOpen circuit faults are common circuit failure mechanism in Thin Film Transistor (TFT) integrated circuits or Printed Circuit Boards (PCBs). Thin film Transistors are widely used in flexible electronics and are manufactured using roll-to-roll methods for application in flexible displays and image sensors, energy harvesters and wearable electronics. Circuits and systems on flexible substrates experience open circuit failures due to mechanical causes such as bending and stretching and electrical causes such as electro-static discharge. It is therefore important to address the problem of open circuit faults. The above problem has been conventionally addressed by the use of new interconnect geometries and stretchable materials. However, these are passive methods and do not solve the problem for non-mechanical causes of open faults. Another approach has been the self-healing of interconnects using a dispersion of conductive particles in an insulating medium. This dispersion is packaged over the interconnect. When a current carrying interconnect experiences and open-fault, the conductive particles of the dispersion are polarized and experience dipole-dipole attractive forces. This eventually leads to the particles chaining up to form a bridge that heals the fault. So far, the models are based on the macroscopic or system level behavior of the dispersion in response to an electric field. These models assume that there are two main forces at play – the dipole-dipole attractive force aiding the healing, and the viscous drag in the fluid inhibiting the motion of particles. In this work, we perform a microscopic analysis of each particle using image processing techniques. The image processing technique used is a robust pixel wise classification algorithm and a convolutional auto-encoder based image segmentation algorithm for particle segmentation. Essentially, the motion of each particle is tracked and the force versus inter-particle distance profile is obtained. This indicates the kind of forces at play. Experiments indicate the force roughly varies as the inverse fourth power of distance thereby corroborating with the model of dipole-dipole interaction.en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesIISc - Masters Thesis Processing;masters-2022-0043.R1
dc.rightsI grant Indian Institute of Science the right to archive and to make available my thesis or dissertation in whole or in part in all forms of media, now hereafter known. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertationen_US
dc.subjectSelf healing circuits, Digital image processingen_US
dc.subject.classificationImage analysisen_US
dc.subject.classificationFlexible Electronicsen_US
dc.titleMicroscopic Analysis of Self Healing Circuits Using Image Processingen_US
dc.typeThesisen_US
dc.degree.nameMTech (Res)en_US
dc.degree.levelMastersen_US
dc.degree.grantorIndian Institute of Scienceen_US
dc.degree.disciplineEngineeringen_US


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