Zwitterionic polymer-based soft composites in sensing applications
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School of Science |
Doctoral thesis (article-based)
| Defence date: 2025-08-18
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en
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71 + app. 97
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Aalto University publication series Doctoral Theses, 148/2025
Abstract
Functional soft materials that respond to external stimuli to control electrical, volumetric, optical, or biological properties are promising in, e.g., in biotechnical, actuation, soft robotic, and flexible sensing applications. As a hydrophilic polymer, zwitter-ionic poly[2-(methacryloyloxy) ethyl] dimethyl-(3-sulfopropyl) ammonium hydroxide (PDMAPS) and its derivatives are attractive candidates for functional soft materials due to their salt-responsive behaviors and affinity to other functional moieties by dynamic electrostatic interactions. In this thesis, we first explore the synthesis and properties of various PDMAPS-based hydrogels, organogels, and their soft composites, followed by investigations of their functionalities for chemical, electrical, and shape sensing applications. Publication 1 introduces a hydrogel incorporating both zwitterionic 2-(methacryloyloxy) ethyl dimethyl-(3-sulfopropyl) ammonium hydroxide (DMAPS) and nonionic 2-hydroxyethyl methacrylate (HEMA) monomers, aiming at gustatory sensing. This hydrogel enables the detection of sweetness, saltiness, and sourness through two distinct responses, i.e., electrical conductivity and volumetric changes, offering a novel approach in the design of artificial taste sensing. Publication 2 reports PDMAPS-based organogels and their composites with tunable electric and magnetic properties by incorporating titanium carbide 2D nanosheets (MXenes) and Neodymium Iron Boron magnet particles (NdFeBPs), respectively. PDMAPS acts as a soft matrix to confine these functional materials, enabling promoted stability and programmability of the resulting composites in mechano-modulation and sensing applications. Publication 3 introduces magnetic soft composites (MSCs) from PDMAPS-based organogels and NdFeBPs. The MSCs are (re)programmable in their shapes, viscoelasticity, and magnetism, enabling a machine learning assisted electromagnetic induction sensing system which can realize magnetic shape detection and magnetic information encryption and decoding. These three works provide strategies for utilizing PDMAPS as a soft matrix in functional soft materials to achieve various sensing applications.Description
Supervising professor
Ikkala, Olli, Distinguished Prof., Aalto University, Department of Applied Physics, FinlandThesis advisor
Peng, Bo, Prof., Fudan University, ChinaLyu, Zhongpeng, Dr., Aalto University, Department of Applied Physics, Finland
Other note
Parts
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[Publication 1]: Ziyue Miao; Hongwei Tan; Lotta Gustavsson; Yang Zhou; Quan Xu; Olli Ikkala; Bo Peng. 2023. Gustation-inspired dual-responsive hydrogels for taste sensing enabled by machine learning. Small, 20(7), 2305195.
Full text in Acris/Aaltodoc: https://urn.fi/URN:NBN:fi:aalto-202412177852DOI: 10.1002/smll.202305195 View at publisher
- [Publication 2]: Ziyue Miao; Xiaodan Hong; Olli Ikkala; Zhongpeng Lyu(Lv); Bo Peng. 2025. Polyzwitterionic Soft Composite with Tunable Sol-Gel Properties Enabling On-Demand Functional Integration. (Submitted)
- [Publication 3]: Ziyue Miao; Xichen Hu; Kai Liu; Shanming Hu; Guihua Yan; Hongwei Tan; Olli Ikkala; Zhong-Peng Lv; Bo Peng. 2025. Bioinspired signal transduction for magnetic profile recognization. (Submitted)