Mathematical model for biomolecular quantification using surface-enhanced Raman spectroscopy based signal intensity distributions

Mirko Palla; Filippo Giacomo Bosco; Jaeyoung Yang; Tomas Rindzevicius; Tommy Sonne Alstrøm; Michael Stenbæk Schmidt; Qiao Lin; Jingyue Ju; Anja Boisen

doi:10.1109/ICSENS.2015.7370388

Mathematical model for biomolecular quantification using surface-enhanced Raman spectroscopy based signal intensity distributions

Mirko Palla, Filippo Giacomo Bosco, Jaeyoung Yang, Tomas Rindzevicius, Tommy Sonne Alstrøm, Michael Stenbæk Schmidt, Qiao Lin, Jingyue Ju, Anja Boisen

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

This paper presents the development of a novel statistical method for quantifying trace amounts of biomolecules by surface-enhanced Raman spectroscopy (SERS) using a rigorous, single molecule (SM) theory based mathematical derivation. Our quantification framework could be generalized for planar SERS substrates, in which the nanostructured features can be approximated as a closely spaced electromagnetic dimer problem. The potential for SM detection was also shown, which opens up an exciting opportunity in the field of SERS quantification.

Original language	English
Title of host publication	Proceedings of IEEE Sensors 2015
Publisher	IEEE
Publication date	2015
Pages	1-4
ISBN (Print)	978-1-4799-8202-8
DOIs	https://doi.org/10.1109/ICSENS.2015.7370388
Publication status	Published - 2015
Event	14th IEEE Sensors 2015 - Busan, Korea, Republic of Duration: 1 Nov 2015 → 4 Nov 2015 Conference number: 14 http://ieee-sensors2015.org/

Conference

Conference	14th IEEE Sensors 2015
Number	14
Country	Korea, Republic of
City	Busan
Period	01/11/2015 → 04/11/2015
Internet address	http://ieee-sensors2015.org/

Keywords

Surface-enhanced Raman spectroscopy
Theoretical modeling
Statistical quantification
Signal intensity distribution
Raman mapping
Biosensing

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Cite this

@inproceedings{978906d6dd2b44d6bc85d732b58a1ad9,

title = "Mathematical model for biomolecular quantification using surface-enhanced Raman spectroscopy based signal intensity distributions",

abstract = "This paper presents the development of a novel statistical method for quantifying trace amounts of biomolecules by surface-enhanced Raman spectroscopy (SERS) using a rigorous, single molecule (SM) theory based mathematical derivation. Our quantification framework could be generalized for planar SERS substrates, in which the nanostructured features can be approximated as a closely spaced electromagnetic dimer problem. The potential for SM detection was also shown, which opens up an exciting opportunity in the field of SERS quantification.",

keywords = "Surface-enhanced Raman spectroscopy, Theoretical modeling, Statistical quantification, Signal intensity distribution, Raman mapping, Biosensing",

author = "Mirko Palla and Bosco, {Filippo Giacomo} and Jaeyoung Yang and Tomas Rindzevicius and Alstr{\o}m, {Tommy Sonne} and Schmidt, {Michael Stenb{\ae}k} and Qiao Lin and Jingyue Ju and Anja Boisen",

year = "2015",

doi = "10.1109/ICSENS.2015.7370388",

language = "English",

isbn = "978-1-4799-8202-8",

pages = "1--4",

booktitle = "Proceedings of IEEE Sensors 2015",

publisher = "IEEE",

address = "United States",

note = "14th IEEE Sensors 2015 ; Conference date: 01-11-2015 Through 04-11-2015",

url = "http://ieee-sensors2015.org/",

}

Palla, M, Bosco, FG, Yang, J, Rindzevicius, T , Alstrøm, TS, Schmidt, MS, Lin, Q, Ju, J & Boisen, A 2015, Mathematical model for biomolecular quantification using surface-enhanced Raman spectroscopy based signal intensity distributions. in Proceedings of IEEE Sensors 2015. IEEE, pp. 1-4, 14th IEEE Sensors 2015, Busan, Korea, Republic of, 01/11/2015. https://doi.org/10.1109/ICSENS.2015.7370388

Mathematical model for biomolecular quantification using surface-enhanced Raman spectroscopy based signal intensity distributions. / Palla, Mirko; Bosco, Filippo Giacomo; Yang, Jaeyoung; Rindzevicius, Tomas ; Alstrøm, Tommy Sonne; Schmidt, Michael Stenbæk; Lin, Qiao; Ju, Jingyue; Boisen, Anja.

Proceedings of IEEE Sensors 2015. IEEE, 2015. p. 1-4.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Mathematical model for biomolecular quantification using surface-enhanced Raman spectroscopy based signal intensity distributions

AU - Palla, Mirko

AU - Bosco, Filippo Giacomo

AU - Yang, Jaeyoung

AU - Rindzevicius, Tomas

AU - Alstrøm, Tommy Sonne

AU - Schmidt, Michael Stenbæk

AU - Lin, Qiao

AU - Ju, Jingyue

AU - Boisen, Anja

N1 - Conference code: 14

PY - 2015

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N2 - This paper presents the development of a novel statistical method for quantifying trace amounts of biomolecules by surface-enhanced Raman spectroscopy (SERS) using a rigorous, single molecule (SM) theory based mathematical derivation. Our quantification framework could be generalized for planar SERS substrates, in which the nanostructured features can be approximated as a closely spaced electromagnetic dimer problem. The potential for SM detection was also shown, which opens up an exciting opportunity in the field of SERS quantification.

AB - This paper presents the development of a novel statistical method for quantifying trace amounts of biomolecules by surface-enhanced Raman spectroscopy (SERS) using a rigorous, single molecule (SM) theory based mathematical derivation. Our quantification framework could be generalized for planar SERS substrates, in which the nanostructured features can be approximated as a closely spaced electromagnetic dimer problem. The potential for SM detection was also shown, which opens up an exciting opportunity in the field of SERS quantification.

KW - Surface-enhanced Raman spectroscopy

KW - Theoretical modeling

KW - Statistical quantification

KW - Signal intensity distribution

KW - Raman mapping

KW - Biosensing

U2 - 10.1109/ICSENS.2015.7370388

DO - 10.1109/ICSENS.2015.7370388

M3 - Article in proceedings

SN - 978-1-4799-8202-8

SP - 1

EP - 4

BT - Proceedings of IEEE Sensors 2015

PB - IEEE

T2 - 14th IEEE Sensors 2015

Y2 - 1 November 2015 through 4 November 2015

ER -