|
|
|
|
|
|
Experimental Collisional Energy Transfer Distributions for Collisions of CO2 With Highly Vibrationally Excited Na2 |
WANG Shu-ying*, YOU De-chang, MA Wen-jia, YANG Ruo-fan, ZHANG Yang-zhi, YU Zi-lei, ZHAO Xiao-fang, SHEN Yi-fan |
Xinjiang Key Laboratory of Solid State Physics and Devices, School of Physical Science and Technology, Xinjiang University, Urumqi 830017, China
|
|
|
Abstract The full state-resolved distribution of scattered CO2(0000) molecules from collisions with highly vibrationally excited Na2(ν″=30 and 45) is reported and investigated how internal energy content impacts the dynamics for collisional quenching of high energy molecules. Stimulated emission pumping was used to excite the Na2(ν″=30, J=11) and Na2(ν″=45, J=11). Under single-collision conditions, rotational levels of the vibrationally relaxed Na2(ν″-1) and Na2(ν″-2) are identified. Levels attributable to upward vibrational transfer could not be observed. The change in Na2 rotational energy was determined. Quantifying the simultaneous population change for low J states is accomplished by transient line profile measurements for individual states. The line width is a measure of the translational energy spread of the scattered molecules and the area under the line profile is a measure of the J-specific population. The nascent translational temperature Tpres (for presence) and Tdep (for depletion) are determined from the measured line widths Δνpres and Δνdep, respectively. The presence line widths Δνpres were obtained by fitting the double-Gaussian function to the transient line profile data at t=1 μs. The lab-frame translational temperature Tpres for the presence of scattered CO2 molecules and the relative (center-of-mass frame) translational temperatures Trel for Na2(ν″) /CO2 collisions were determined based on Δνpres measurements. Average translational energy gains for the presence of CO2(0000, J) following collisions with vibrationally excited Na2 are determined using 〈Erel〉=3/2k(Trel-Tcell). The comparison shows that the Na2 vibrational energy that goes into the translational energy of the CO2 strongly depends on the initial energy: the translational energy of the J-specific collision pruducts increases by 56% or more for a 35% increase in donor vibrational energy. The appearance rate constants for individual CO2 rotational states are determined. The total appearance rate constant for Na2(ν″=30) is kapp=(6.6±1.5)×10-10 cm3·molecule-1·s-1. This result is comparable to that for Na2(ν″=45), where the appearance rate constant is kapp=(5.9±1.3)×10-10 cm3·molecule-1·s-1. The results show that the Na2(ν″)/CO2 collision frequency is not particularly sensitive to the amount of Na2(ν″) vibrational energy. The full energy transfer distributions P(ΔE) for product energy gain confirm that the ΔE distributions broaden rapidly for relatively small increases in donor energy for Na2(ν″)/CO2 collisions. P(ΔE) curves for Na2(ν″=30) are shifted to lower ΔE values compared to Na2(ν″=45) data. The ΔE values in P(ΔE) include the change in CO2 rotational energy and the change in translational energy of Na2(ν″) and CO2 plus the change in rotational energy of Na2(ν″). Numerical integration of P(ΔE) over the full range of ΔE yields 〈ΔE〉trans=590 cm-1; in comparison, 〈ΔE〉trans=880 cm-1 for Na2(ν″=45).
|
Received: 2022-03-22
Accepted: 2022-10-31
|
|
Corresponding Authors:
WANG Shu-ying
E-mail: wsy-smile@163.com
|
|
[1] Yang B H, Balakrishnan N, Zhang P, et al. J. Chem. Phys., 2016, 145: 034308.
[2] Unke O T, Castro-Palacio J C, Bemish R J, et al. J. Chem. Phys., 2016, 144: 224307.
[3] Watanabe N, Takahashi M. J. Chem. Phys., 2020, 152: 164301.
[4] Frerichs H, Lenzer T, Luther K, et al. Phys. Chem. Chem. Phys., 2005, 7: 620.
[5] Lenzer T, Luther K. Phys. Chem. Chem. Phys., 2004, 6: 955.
[6] Yuan L W, Du J, Mullin Amy S. J. Chem. Phys., 2008, 129: 014303.
[7] Castro-Juarez E, Wang X G, Carrington T, et al. J. Chem. Phys., 2019, 151: 084307.
[8] Condoluci J, Janardan S, Calvin AT , et al. J. Chem. Phys., 2017, 147(21): 214309.
[9] Du J, Sassin N A, Havey D K, et al., J. Phys. Chem. A, 2013, 117(46): 12104.
[10] Shen X Y, Wang S Y, Dai K, et al. Spectrochim. Acta A, 2017, 173: 516.
[11] WANG Shu-ying, ZHANG Wen-jun, DAI Kang, et al(王淑英,张文军,戴 康,等). Chinese Journal of Lasers(中国激光), 2015, 42(4): 0408001.
[12] Mu B X, Cui X H, Shen Y F, et al. Spectrochim. Acta A, 2015, 148: 299.
[13] Michaels Chris A, Lin Z, Mullin Amy S, et al. J. Chem. Phys., 1997, 106: 7055.
[14] Grigoleit U, Lenzer T, Luther K, et al. Phys. Chem. Chem. Phys., 2001, 3: 2191.
[15] Hold U, Lenzer T, Luther K, et al. J. Chem. Phys., 2003, 119: 11192.
|
[1] |
CHENG Wen-xuan1, ZHANG Qing-xian1*, LIU Yu1, ZOU Li-kou2*. Study on Detection of Antibiotic Residues in Eggs by Laser-Induced
Fluorescence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(05): 1245-1254. |
[2] |
XIE Bei-bei1, 2, ZHAO Jia-wei1, ZHOU Xuan-yu1, ZHANG Xiao-dan3, LIU Yu-jia4. BRRDF Simulation Study on the Influence of Atmospheric Turbulence on LIF Detection of Sea Surface Oil Spill[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(05): 1379-1385. |
[3] |
ZHANG Xue-jun1, CHEN Qin-gen2, YANG Zhan1, DENG Qin1, HE Shuan-ling3, PENG Zhi-min3*. On Line Simultaneous Measurement of CO/CO2/H2S Concentration Based on Laser Absorption Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(05): 1412-1416. |
[4] |
CAO Zhen1, 2, YU Xin1, 2, PENG Jiang-bo1, 2*, LIU Qiang3, YANG Shun-hua4, ZHANG Shun-ping4, ZHAO Yan-hui4, LI Pei-lin3, GAO Long1, 2, ZHANG Shan-chun1, 2. A Burst-Mode Ultraviolet Laser System for High-Speed PLIF
Measurements in Large-Scale Model Engine[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(04): 932-936. |
[5] |
QI Guo-min1, TONG Shi-qian1, LIN Xu-cong1, 2*. Specific Identification of Microcystin-LR by Aptamer-Functionalized Magnetic Nanoprobe With Laser-Induced Fluorescence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3813-3819. |
[6] |
WANG Yu1, 2, ZHANG Xian-ke1, 2, TAN Tu1, WANG Gui-shi1, LIU Kun1, SUN Wan-qi3*, QIU Zi-chen4, GAO Xiao-ming1, 2. Research on Moving Observation of Typical Greenhouse Gas Sources in Hefei by Using Off-Axis Integrated Cavity[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3293-3301. |
[7] |
KONG De-ming1, LIU Ya-ru1, DU Ya-xin2, CUI Yao-yao2. Oil Film Thickness Detection Based on IRF-IVSO Wavelength Optimization Combined With LIF Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2811-2817. |
[8] |
YUAN Kai-xin, ZHUO Jin, ZHANG Qing-hua, LI Ya-guo*. Study on the Spectral and Laser Damage Resistance of CO2 Laser Modified Sol-Gel SiO2 Thin Films[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1752-1759. |
[9] |
WANG Mei-li1, 2, SHI Guang-hai2*, ZHANG Xiao-hui1, YANG Ze-yu2, 3, XING Ying-mei1. Experimental Study on High-Temperature Phase Transformation of Calcite[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1205-1211. |
[10] |
YUAN Li1, KONG De-ming2*, CHEN Ji-liang3, ZHONG Mei-yu3, ZHANG Xiao-dan3, XIE Bei-bei3, KONG Ling-fu3. Study on an Equivalent Estimation Method of Oil Spill of Water in Oil
Emulsion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 342-347. |
[11] |
ZHANG Xiao-dan1, KONG De-ming2*, ZHONG Mei-yu1, MA Qin-yong1, KONG Ling-fu1. Research on an Equivalent Evaluation Algorithm for the Oil Spill Volume of Oil-in-Water Emulsion on the Sea Surface[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3665-3671. |
[12] |
YAN Peng-cheng1, 2, ZHANG Xiao-fei2*, SHANG Song-hang2, ZHANG Chao-yin2. Research on Mine Water Inrush Identification Based on LIF and
LSTM Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3091-3096. |
[13] |
CHEN Si-ying1, JIA Yi-wen1, JIANG Yu-rong1*, CHEN He1, YANG Wen-hui2, LUO Yu-peng1, LI Zhong-shi1, ZHANG Yin-chao1, GUO Pan1. Classification and Recognition of Adulterated Manuka Honey by
Multi-Wavelength Laser-Induced Fluorescence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(09): 2807-2812. |
[14] |
YUAN Li1, XIE Bei-bei2, CUI Yong-qiang2, ZHANG Xiao-dan2, JIAO Hui-hui2. Research on Oil Spill Status Recognition Based on LIF[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(07): 2018-2024. |
[15] |
YAN Peng-cheng1, 2, ZHANG Chao-yin2*, SUN Quan-sheng2, SHANG Song-hang2, YIN Ni-ni1, ZHANG Xiao-fei2. LIF Technology and ELM Algorithm Power Transformer Fault Diagnosis Research[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1459-1464. |
|
|
|
|