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Improving the Sensitivity and Analytical Power of Electrically Detected Magnetic Resonance Through Hardware and Software.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Improving the Sensitivity and Analytical Power of Electrically Detected Magnetic Resonance Through Hardware and Software./
作者:	Manning, Brian R.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	124 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Contained By:	Dissertations Abstracts International83-03B.
標題:	Silicon. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28841696
ISBN:	9798460447435

Improving the Sensitivity and Analytical Power of Electrically Detected Magnetic Resonance Through Hardware and Software.
Manning, Brian R.

Improving the Sensitivity and Analytical Power of Electrically Detected Magnetic Resonance Through Hardware and Software. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 124 p.

Source: Dissertations Abstracts International, Volume: 83-03, Section: B.

Thesis (Ph.D.)--The Pennsylvania State University, 2021.

This item must not be sold to any third party vendors.

Magnetic resonance techniques offer unparalleled analytical power in the identification of paramagnetic defect centers in semiconductors and insulators. The preliminary technique, electron paramagnetic resonance (EPR), has a typical sensitivity of about 10 billion defects per Gauss of linewidth. The sensitivity of EPR can be improved via electrical detection, known as electrically detected magnetic resonance (EDMR). EDMR is the most sensitive analytical technique for identifying the chemical and physical nature of defects and has proven to be invaluable in elucidating atomic-scale imperfections in nanoscale solid-state semiconducting and insulating materials and devices. Hardware and software improvements can be used in conjunction with electrical detection to further improve the sensitivity of magnetic resonance measurements and develop new techniques. This research includes the development and a demonstration of several magnetic resonance methods: electrically detected electron-nuclear double resonance (EDENDOR), ultra-low field frequency swept EDMR, and electrically detected rapid-scan (EDRS). The importance and application of each technique is also highlighted. In addition to this, software-based filtering techniques have been developed to improve the sensitivity of the magnetic resonance measurements. This work introduces an improved upper-diagonal (UD) decomposition recursive least-squares (RLS) algorithm with an exponential sliding window (UD-SWRLS) for use in adaptive signal averaging (ASA). We also introduce a real-time fast pseudomodulation technique for use in rapid-scan spectroscopy. We believe that these new techniques and methods could serve as a vital tool for the future of material and device research.

ISBN: 9798460447435Subjects--Topical Terms:

669429
Silicon.
Subjects--Index Terms:

Defect centers

Improving the Sensitivity and Analytical Power of Electrically Detected Magnetic Resonance Through Hardware and Software.
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520 $a Magnetic resonance techniques offer unparalleled analytical power in the identification of paramagnetic defect centers in semiconductors and insulators. The preliminary technique, electron paramagnetic resonance (EPR), has a typical sensitivity of about 10 billion defects per Gauss of linewidth. The sensitivity of EPR can be improved via electrical detection, known as electrically detected magnetic resonance (EDMR). EDMR is the most sensitive analytical technique for identifying the chemical and physical nature of defects and has proven to be invaluable in elucidating atomic-scale imperfections in nanoscale solid-state semiconducting and insulating materials and devices. Hardware and software improvements can be used in conjunction with electrical detection to further improve the sensitivity of magnetic resonance measurements and develop new techniques. This research includes the development and a demonstration of several magnetic resonance methods: electrically detected electron-nuclear double resonance (EDENDOR), ultra-low field frequency swept EDMR, and electrically detected rapid-scan (EDRS). The importance and application of each technique is also highlighted. In addition to this, software-based filtering techniques have been developed to improve the sensitivity of the magnetic resonance measurements. This work introduces an improved upper-diagonal (UD) decomposition recursive least-squares (RLS) algorithm with an exponential sliding window (UD-SWRLS) for use in adaptive signal averaging (ASA). We also introduce a real-time fast pseudomodulation technique for use in rapid-scan spectroscopy. We believe that these new techniques and methods could serve as a vital tool for the future of material and device research.
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