Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Noisy Light Spectroscopy: Putting noise to good use Darin J. Ulness Department of Chemistry Concordia College Moorhead, MN 1 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Outline I. Introduction II.Theory III. Experiment • Coherent Raman Scattering IV. Connections 2 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Spectroscopy Using light to gain information about matter Information •Lineshape function •Transition frequencies •Cross-sections •Susceptibilities Uses of information •In Chemistry •In Biology •In Engineering 3 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Modern Spectroscopy Frequency Domain Time Domain •Measure Spectra •Examples •IR, UV-VIS, Raman •Material response •Spectrally narrow •Temporally slow •Response to light pulse •Examples •PE, transient abs. •Material response •Spectrally broad •Temporally fast 4 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Modern Spectroscopy Frequency Domain Time Domain •Measure Spectra •Examples •IR, UV-VIS, Raman •Material response •Spectrally narrow •Temporally slow •Response to light pulse •Examples •PE, transient abs. •Material response •Spectrally broad •Temporally fast 4 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Modern Spectroscopy Frequency Domain Time Domain •Measure Spectra •Examples •IR, UV-VIS, Raman •Material response •Spectrally narrow •Temporally slow •Response to light pulse •Examples •PE, transient abs. •Material response •Spectrally broad •Temporally fast Is there another useful technique? Noisy light? YES! 4 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Light Electromagnetic radiation •Focus on electric field part Spectrum One frequency (or color) frequency time 5 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Noisy Light: Definition Time resolution on the order of the correlation time, tc E letric F ield S trength Noisy Light Spectrum •Broadband •Phase incoherent •Quasi continuous wave Frequency T im e 6 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Noisy Light: Alternative •Its cw nature allows precise measurement of transition frequencies. •Its ultrashort noise correlation time offers femtosecond scale time resolution. •It offers a different way to study the lineshaping function. •It is particularly useful for coherent Raman scattering. •Other spectroscopies: photon echo, OKE, FROG, polarization beats… 7 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Theory Noisy Light Spectroscopy Optical coherence theory Perturbation theory: Density operator 8 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Theoretical Challenges •Complicated Mathematics •Complicated Physical Interpretation Difficulty •The cw nature requires all field action permutations. The light is always on. •The proper treatment of the noise cross-correlates chromophores. 9 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Bichromophoric Model a Noisy light (3) P(t) (3)* b P(s) Solution •Factorized time correlation (FTC) diagram analysis <> 10 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 FTC Diagram Analysis Messy integration and algebra Set of intensity level terms (pre-evaluated) Construction Rules Set of FTC diagrams Evaluation Rules Set of evaluated intensity level terms easy hard hard Physics 11 Darin J. Ulness, Concordia College Noisy Light Spectroscopy Example: a b U Toronto, February 18, 2011 (2) I CARS P(t,{ti}) arrow segments: t-dependent correlation line segments: P(s,{si}) t-independent correlation 12 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Experiment •Coherent Raman Scattering: e.g., CARS •Frequency resolved signals •Spectrograms •Molecular liquids 13 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Nonlinear Optics Material Signal P= c E Light field Perturbation series approximation P(t) = P(1) + P(2) + P(3) … P(1) = c (1)E, P(2) = c (2)EE, P(3) = c (3)EEE 14 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 CARS Coherent Anti-Stokes Raman Scattering w1 wR w2 w1 wCARS w1-w2= wR wCARS= w1 +wR 15 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 CARS with Noisy Light •I(2)CARS •We need twin noisy beams B and B’. •We also need a narrowband beam, M. •The frequency of B (B’) and M differ by roughly the Raman frequency of the sample. •The I(2)CARS signal has a frequency that is anti-Stokes shifted from that of the noisy beams. B M B’ I(2)CARS 16 Darin J. Ulness, Concordia College Noisy Light Spectroscopy (2) I CARS: U Toronto, February 18, 2011 Experiment Computer CCD Interferometer Monochromator B’ Sample t B I(2)CARS M Lens Narrowband Source Broadband Source (noisy light) 17 Darin J. Ulness, Concordia College Noisy Light Spectroscopy (2) I CARS: Spectrogram Computer CCD Interferometer Monochromator B’ Sample t B I(2)CARS M Lens Narrowband Source U Toronto, February 18, 2011 Broadband Source •Signal is dispersed onto the CCD •Entire Spectrum is taken at each delay •2D data set: the Spectrogram 18 Darin J. Ulness, Concordia College Noisy Light Spectroscopy (2) I CARS: U Toronto, February 18, 2011 Spectrogram A Pixel A Pixel B B C Pixel C Dark regions: high intensity Light regions: low intensity Oscillations: downconversion of Raman frequency. Decay: Lineshape function 19 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Spectrogram No new information can be extracted. However… •Huge oversampling gives much enhanced precision. •Visually appealing presentation of data gives much insight. 20 Darin J. Ulness, Concordia College Noisy Light Spectroscopy (2) I CARS: U Toronto, February 18, 2011 Data Processing BenzeneT22 BenzeneT22 150 2 125 1 Fourier 0 100 75 -1 Transformation -2 50 25 18000 18100 18200 18300 18400 0 0 100 200 300 200 400 600 800 400 0.8 0.6 0.4 0.2 X-Marginal 1000 1200 21 Darin J. Ulness, Concordia College Noisy Light Spectroscopy Virtues of U Toronto, February 18, 2011 (2) I CARS •Less expensive. •Easier experiment to perform. •Signals are more robust. •Immune to dispersion effects. •Exquisitely sensitive to relative changes in the vibrational frequency and dephasing rate constant. 22 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Pyridine and Water Pyridine Pyridine Neat Pyridine 400 400 200 200 0 0 FT -200 -200 -400 -400 17300 17400 17500 17600 17300 ave x .45 pyr_water 400 Pyridine/ Water Xw= 0.55 200 0 -200 -400 17300 17400 17500 17600 17400 17500 17600 23 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Pyridine and Water 1.2 1 0.8 pure pyr 0.6 x=.15 x=0.3 0.4 x=0.45 x=0.75 0.2 0 955 -0.2 975 995 1015 Wavenumber / cm-1 1035 1055 24 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Pyridine and Water 1 .0 P y rid in e /w a te r s o lu tio n : X (p y )= 0 .6 0 .8 N orm alized X -m arginal T = -4 T = 3 o o T = 23 0 .6 T = 32 T = 42 T = 52 0 .4 T = 62 T = 72 T = 76 o o o o o o o 0 .2 0 .0 960 970 980 990 1000 1010 W avenum ber / cm -1 1020 1030 1040 25 Darin J. Ulness, Concordia College Noisy Light Spectroscopy 26 U Toronto, February 18, 2011 Halogen bonding 3.5 0.2 3 0.3 3 0.4 2.5 0.5 2 2.5 2 1.5 0.6 1 0.7 C6F13I and Pyridine 4 0.1 3.5 Neat Normalized Intesity Normalized Intensity Pyridine and C3F7I 4 0.1 0.2 0.3 0.4 0.5 1.5 0.6 0.7 1 .8 0.9 0.5 0.8 0 900 920 940 960 980 1000 1020 Frequency (cm-1) 1040 1060 1080 1100 0.9 Neat 0.5 0 900 920 940 960 980 1000 1020 Frequency (cm-1) 1040 1060 1080 1100 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Prospectus Summary: •Noisy light provides an alternative method for probing ultrafast dynamics of the condensed phase. •Experimentally it is relatively easy. •Theoretically it is relatively hard. •FTC diagram analysis helps with theoretical understanding. 27 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Prospectus Future of noisy light at Concordia: •I(2)CARS is an exquisitely sensitive probe of vibrational frequency shifts •A principle goal is to explore halogen bonding. I(2)CARS is one tool available to us. 28 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Connections Coherent Energy Transfer: •Noisy light can produce a nonlinear response. •Noisy light is “incoherent.” •Amplitude level correlation. 29 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Connections Stimulus P(s) P(t) “Reaction Center” <> 30 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Acknowledgements Former Students Theory Jahan Dawlaty Dan Biebighauser John Gregiore Duffy Turner Method Development Pye Phyo Aung Tanner Schulz Lindsay Weisel Krista Cosert Perrie Cole Alex Harsh Britt Berger Zach Johnson Thao Ta Hydrogen/Halogen bonding Eric Berg Jeff Eliason Diane Moliva Jason Olson Scott Flancher Danny Green Other Group Members Funding NSF CAREER Grant CHE-0341087 Henry Dreyfus Teacher/Scholar program Concordia Chemistry Research Fund Dr. Mark Gealy, Department of Physics Dr. Eric Booth, Post-doctoral researcher Dr. Haiyan Fan, Post-doctoral researcher 31 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 Utility of FTC Diagrams •Organize lengthy calculations •Error checking •Identification of important terms •Immediate information of about features of spectrograms •Much physical insight that transcends the choice of mathematical model. A1 Darin J. Ulness, Concordia College Noisy Light Spectroscopy Example: U Toronto, February 18, 2011 (2) I CARS FTC analysis •Each diagram with arrows has a topologically equivalent partner diagram containing only lines: 2:1 dynamic range •Each diagram with arrows has a topologically equivalent partner diagram that has arrows pointing in the opposite direction: signal must be symmetric in t a P(t,{ti}) b P(s,{si}) arrow segments: B, B’ correlation t-dependent line segments: B, B or B’,B’ correlation t-independent A2 Darin J. Ulness, Concordia College Noisy Light Spectroscopy Example: U Toronto, February 18, 2011 (2) I CARS A Pixel A Pixel B B C Pixel C The I(2)CARS data shows • 2:1 dynamics range • t symmetry A3 Darin J. Ulness, Concordia College (a) Noisy Light Spectroscopy U Toronto, February 18, 2011 0.30 0.25 sg 0.20 0.15 0.10 0.05 (b) 0.25 0.00 0 0.20 1 2 3 S/N sw 0 D 0.15 0.10 0.05 0.00 0 1 2 3 S/N 4 5 4 5 A4 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 A5 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 A6 Darin J. Ulness, Concordia College Noisy Light Spectroscopy U Toronto, February 18, 2011 1 .5 F it R e s u lts : Free pyr. to H -bound pyr 1 .4 ra tio = 0 .0 0 7 8 3 T + 0 .9 0 5 R = 0 .9 9 4 2 1 .3 1 .2 1 .1 1 .0 0 .9 0 .8 -2 0 0 20 40 60 o T e m p e ra tu re (C ) - ∆G° Product Favored - ∆H° Exothermic - ∆S° Entropically unfavorable 80 A7 Darin J. Ulness, Concordia College pyridine Noisy Light Spectroscopy A8 U Toronto, February 18, 2011 with .4g AgNO3 1 .0 P y rid in e / A g N O 3 400 g A g N O 3 /m l p y 0 .0 0 0 .8 N o rm a lize d X -m a rg in a l 0 .0 6 1 200 0 -200 -400 0 .0 9 7 0 .1 2 1 0 .6 0 .1 7 0 0 .2 3 8 0 .2 9 8 0 .3 4 1 0 .4 0 .4 0 9 0 .2 0 .0 17300 17400 17500 -0 .2 17600 960 970 980 990 1000 1010 W avenum ber / cm 1 .4 P y rid in e /A g N O 3 R a tio Free pyridined C om plexed pyridine to 2 7 .1 X e ff 0 .8 2 1030 1040 -1 c(3)complex = Icomplex c(3)free xfree Icomplex = Ifree at 0.21 mole fraction c(3)complex = 1 c(3)free .79 1 .2 1 .0 1020 -.9 7 X e ff + 0 .0 1 3 c(3)complex = 3.76 c(3)free 0 .6 0 .4 0 .2 0 .0 -0 .2 0 .0 0 0 .0 5 0 .1 0 0 .1 5 0 .2 0 E ffe c tiv e m o le fra c tio n A g N O 3 0 .2 5