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MEMS based heavy metal detector
Water pollution by toxic heavy metals is one of the most serious environmental hazards to humans’ health. As they are emitted into the water resources and adsorbed by soil, plants, fish and animals and eventually accumulate in human bodies causing a variety of serious diseases. Therefore, the...
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| Format: | Thesis |
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2013
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| _version_ | 1867613417351675904 |
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| access_status_str | Open Access |
| author | Ramsis, Inas |
| author_browse | Ramsis, Inas |
| author_facet | Ramsis, Inas |
| author_sort | Ramsis, Inas |
| collection | Thesis |
| dc_rights_str_mv | The author retains all rights with regard to copyright. The author certifies that written permission from the owner(s) of third-party copyrighted matter included in the thesis, dissertation, paper, or record of study has been obtained. The author further certifies that IRB approval has been obtained for this thesis, or that IRB approval is not necessary for this thesis. Insofar as this thesis, dissertation, paper, or record of study is an educational record as defined in the Family Educational Rights and Privacy Act (FERPA) (20 USC 1232g), the author has granted consent to disclosure of it to anyone who requests a copy. |
| description | Water pollution by toxic heavy metals is one of the most serious environmental hazards to humans’ health. As they are emitted into the water resources and adsorbed by soil, plants, fish and animals and eventually accumulate in human bodies causing a variety of serious diseases. Therefore, there is an urgent need to develop a continuous, rapid, automatic, and on-site heavy metals environmental monitoring system for the online detection of heavy metals pollution at various water resources and industrial waste networks. In this thesis the main objective is to develop a microfluidic platform for heavy metal analyte sensing in which a variety of sensing schemes can be applied. The proposed platform contains microfluidic microchannels for the handling and separation of heavy metal analytes to improve the selectivity, integrated with a sensing device for the optical detection and monitoring of various heavy metal analytes and concentrations. In this context, the design and micro-fabrication of polymer based microchannels were conducted as the microfluidic platform on which the integration of the various optical sensing materials can take place. Afterward a novel design of MEMS based Fourier transform spectrometer is proposed, in which a new scheme for input Gaussian beam splitting into symmetrically two semi Gaussian beam is introduced using V shape mirror. The design is fully integrated and can operate in the Infrared and visible region. The analysis shows that, a minimum resolution of 9nm at a wavelength of 1.45μm and a mechanical displacement of 160μm is achievable. Unlike the traditional Michelson interferometer which returns half of the optical power to the source, this design uses the full optical power to get the interference pattern using movable reflecting mirrors thus enhancing the signal to noise ratio, and allowing the use of differential moving scheme for the mirrors which increase the optical path difference by a factor of four. An analytical model that describes the beams propagation and interference is derived using Fourier optics techniques and verified using Finite Difference Time Domain (FDTD) method. Then, a mechanical model that describes the mirror displacement to produce optical pass difference is derived and verified using finite element method (FEM). Finally, the effect of different design parameters on the interference pattern, interferograme and resolution are also shown. |
| format | Thesis |
| id | oai:fount.aucegypt.edu:etds-2282 |
| institution | American University in Cairo (Egypt) |
| last_indexed | 2026-06-10T12:35:48.888Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from AUC Knowledge Fountain — bepress |
| publishDate | 2013 |
| publishDateRange | 2013 |
| publishDateSort | 2013 |
| publisher | AUC Knowledge Fountain |
| publisherStr | AUC Knowledge Fountain |
| record_format | dspace |
| source_str | AUC Knowledge Fountain — bepress |
| spelling | oai:fount.aucegypt.edu:etds-2282 MEMS based heavy metal detector Ramsis, Inas Water pollution by toxic heavy metals is one of the most serious environmental hazards to humans’ health. As they are emitted into the water resources and adsorbed by soil, plants, fish and animals and eventually accumulate in human bodies causing a variety of serious diseases. Therefore, there is an urgent need to develop a continuous, rapid, automatic, and on-site heavy metals environmental monitoring system for the online detection of heavy metals pollution at various water resources and industrial waste networks. In this thesis the main objective is to develop a microfluidic platform for heavy metal analyte sensing in which a variety of sensing schemes can be applied. The proposed platform contains microfluidic microchannels for the handling and separation of heavy metal analytes to improve the selectivity, integrated with a sensing device for the optical detection and monitoring of various heavy metal analytes and concentrations. In this context, the design and micro-fabrication of polymer based microchannels were conducted as the microfluidic platform on which the integration of the various optical sensing materials can take place. Afterward a novel design of MEMS based Fourier transform spectrometer is proposed, in which a new scheme for input Gaussian beam splitting into symmetrically two semi Gaussian beam is introduced using V shape mirror. The design is fully integrated and can operate in the Infrared and visible region. The analysis shows that, a minimum resolution of 9nm at a wavelength of 1.45μm and a mechanical displacement of 160μm is achievable. Unlike the traditional Michelson interferometer which returns half of the optical power to the source, this design uses the full optical power to get the interference pattern using movable reflecting mirrors thus enhancing the signal to noise ratio, and allowing the use of differential moving scheme for the mirrors which increase the optical path difference by a factor of four. An analytical model that describes the beams propagation and interference is derived using Fourier optics techniques and verified using Finite Difference Time Domain (FDTD) method. Then, a mechanical model that describes the mirror displacement to produce optical pass difference is derived and verified using finite element method (FEM). Finally, the effect of different design parameters on the interference pattern, interferograme and resolution are also shown. 2013-02-01T08:00:00Z thesis application/pdf https://fount.aucegypt.edu/etds/1283 https://fount.aucegypt.edu/context/etds/article/2282/viewcontent/Inas_20Raafat.pdf The author retains all rights with regard to copyright. The author certifies that written permission from the owner(s) of third-party copyrighted matter included in the thesis, dissertation, paper, or record of study has been obtained. The author further certifies that IRB approval has been obtained for this thesis, or that IRB approval is not necessary for this thesis. Insofar as this thesis, dissertation, paper, or record of study is an educational record as defined in the Family Educational Rights and Privacy Act (FERPA) (20 USC 1232g), the author has granted consent to disclosure of it to anyone who requests a copy. Theses and Dissertations AUC Knowledge Fountain Heavy metals Environmental monitoring |
| spellingShingle | Heavy metals Environmental monitoring Ramsis, Inas MEMS based heavy metal detector |
| title | MEMS based heavy metal detector |
| title_full | MEMS based heavy metal detector |
| title_fullStr | MEMS based heavy metal detector |
| title_full_unstemmed | MEMS based heavy metal detector |
| title_short | MEMS based heavy metal detector |
| title_sort | mems based heavy metal detector |
| topic | Heavy metals Environmental monitoring |
| url | https://fount.aucegypt.edu/etds/1283 https://fount.aucegypt.edu/context/etds/article/2282/viewcontent/Inas_20Raafat.pdf |
| work_keys_str_mv | AT ramsisinas memsbasedheavymetaldetector |