Computational Mass Spectrometry
| dc.contributor.advisor | Brady, David | |
| dc.contributor.author | Chen, Evan Xuguang | |
| dc.date.accessioned | 2015-09-01T19:50:32Z | |
| dc.date.available | 2015-12-08T05:30:07Z | |
| dc.date.issued | 2015 | |
| dc.department | Electrical and Computer Engineering | |
| dc.description.abstract | Conventional mass spectrometry sensing has isomorphic nature, which means measure the input mass spectrum abundance function by a resemble of delta function to avoid ambiguity. However, the delta function nature of traditional mass spectrometry sensing approach imposes trade-offs between mass resolution and throughput/mass analysis time. This dissertation proposes a new field of mass spectrometry sensing which combines both computational signal processing and hardware modification to break the above trade-offs. We introduce the concept of generalized sensing matrix/discretized forward model in mass spectrometry filed. The presence of forward model can bridge the cap between sensing system hardware design and computational sensing algorithm including compressive sensing, feature/variable selection machine learning algorithms, and stat-of-art inversion algorithms. Throughout this dissertation, the main theme is the sensing matrix/forward model design subject to the physical constraints of varies types of mass analyzers. For quadrupole ion trap systems, we develop a new compressive and multiplexed mass analysis approach mutli Resonant Frequency Excitation (mRFE) ejection which can reduce mass analysis time by a factor 3-6 without losing mass spectra specificity for chemical classification. A new information-theoretical adaptive sensing and classification framework has proposed on quadrupole mass filter systems, and it can significantly reduces the number of measurements needed and achieve a high level of classification accuracy. Furthermore, we present a coded aperture sector mass spectrometry which can yield a order-of-magnitude throughput gain without compromising mass resolution compare to conventional single slit sector mass spectrometer. | |
| dc.identifier.uri | ||
| dc.subject | Electrical engineering | |
| dc.subject | Computational mass spectrometry | |
| dc.subject | Computational sensing | |
| dc.subject | magnetic sector spectrometer | |
| dc.subject | Mass spectrometry | |
| dc.subject | Quadrupole ion trap | |
| dc.subject | Quadrupole mass filter | |
| dc.title | Computational Mass Spectrometry | |
| dc.type | Dissertation | |
| duke.embargo.months | 3 |