Citation: XI Shuanghui, WANG Fan, LI Xiangyuan. First- and Second-Order Local and Global Sensitivity Analyses on Ignition Delay Times of Four Typical Fuels[J]. Acta Physico-Chimica Sinica, ;2019, 35(2): 167-181. doi: 10.3866/PKU.WHXB201803022 shu

First- and Second-Order Local and Global Sensitivity Analyses on Ignition Delay Times of Four Typical Fuels

1.
Institute of Atomic and Molecular Physics, Sichuan University, Chengdu 610065, P. R. China
2.
College of Chemical Engineering, Sichuan University, Chengdu 610065, P. R. China

Corresponding author: WANG Fan, wangf44@gmail.com
Received Date: 18 December 2017
Revised Date: 19 January 2018
Accepted Date: 1 February 2018
Available Online: 2 February 2018
Fund Project: the National Natural Science Foundation of China 21773160the National Natural Science Foundation of China 21473116the National Key R & D Program of China 2017YFB0202400the National Key R & D Program of China 2017YFB0202401The project was supported by the National Key R & D Program of China (2017YFB0202400, 2017YFB0202401) and the National Natural Science Foundation of China (21473116, 21773160)

Sensitivity analysis is an important tool in model validation and evaluation that has been employed extensively in the analysis of chemical kinetic models of combustion processes. The input parameters of a chemical kinetic model are always associated with some uncertainties, and the effects of these uncertainties on the predicted combustion properties can be determined through sensitivity analysis. In this work, first- and second-order global and local sensitivity coefficients of ignition delay time with respect to the scaling factor for reaction rate constants in chemical kinetic mechanisms for combustion of H₂, methane, n-butane, and n-heptane are examined. In the sensitivity analysis performed here, the output of the model is taken to be natural logarithm of ignition delay time and the input parameters are the natural logarithms of the factors that scale the reaction rate constants. The output of the model is expressed as a polynomial function of the input parameters, with up to coupling between two input parameters in the present sensitivity analysis. This polynomial function is determined by varying one or two input parameters, and allows the determination of both local and global sensitivity coefficients. The order of the polynomial function in the present work is four, and the factor that scales the reaction rate constant is in the range from 1/e to e, where e is the base of the natural logarithm. A relatively small number of sample runs are required in this approach compared to the global sensitivity analysis based on the highly dimensional model representation method, which utilizes random sampling of input (RS-HDMR). In RS-HDMR, sensitivity coefficients are determined only for the rate constants of a limited number of reactions; the present approach, by contrast, affords sensitivity coefficients for a larger number of reactions. Reactions and reaction pairs with the largest sensitivity coefficients are listed for ignition delay times of four typical fuels. Global sensitivity coefficients are always positive, while local sensitivity coefficients can be either positive or negative. A negative local sensitivity coefficient indicates that the reaction promotes ignition, while a positive local sensitivity coefficient suggests that the reaction actually suppresses ignition. Our results show that important reactions or reaction pairs identified by global sensitivity analysis are usually rather similar to those based on local sensitivity analysis. This finding can probably be attributed to the fact that the values of input parameters are within a rather small range in the sensitivity analysis, and nonlinear effects for such a small range of parameters are negligible. It is possible to determine global sensitivity coefficients by varying the input parameters over a larger range using the present approach. Such analysis shows that correlation effects between an important reaction and a minor reaction can have relatively sizable second-order sensitivity coefficient in some cases. On the other hand, first-order global sensitivity coefficients in the present approach will be affected by coupling between two reactions, and some results of the first-order global sensitivity analysis will be different from those determined by local sensitivity analysis or global sensitivity analysis under conditions where the correlation effects of two reactions are neglected. The present sensitivity analysis approach provides valuable information on important reactions as well as correlated effects of two reactions on the combustion characteristics of a chemical kinetic mechanism. In addition, the analysis can also be employed to aid global sensitivity analysis using RS-HDMR, where global sensitivity coefficients are determined more reliably.
- Global sensitivity analysis,
- Local sensitivity analysis,
- Ignition delay time,
- Chemical mechanism for combustion
1. [1]
  Tomlin, A. S.; Turányi, T. Cleaner Combust. Green Energy Technol. 2013, 411. doi: 10.1007/978-1-4471-5307-8_16 doi: 10.1007/978-1-4471-5307-8_16
2. [2]
  Turányi, T. ; Tomlin, A. S. Analysis of Kinetic Reaction Mechanisms; Springer-Verlag: Berlin Heidelberg, German; 2014.
3. [3]
  Tomlin, A. S. Proc. Combust. Inst. 2013, 34, 159. doi: 10.1016/j.proci.2012.07.043 doi: 10.1016/j.proci.2012.07.043
4. [4]
  Saltelli, A.; Ratto, M.; Tarantola, S.; Campolongo, F. Chem. Rev. 2005, 105, 2811. doi: 10.1021/cr040659d doi: 10.1021/cr040659d
5. [5]
  Zádor, J.; Zsély, I. G.; Turányi, T. Reliab. Eng. Syst. Saf. 2006, 91, 1232. doi: 10.1016/j.ress.2005.11.020 doi: 10.1016/j.ress.2005.11.020
6. [6]
  Wang, H.; Sheen, D. A. Prog. Energy Combust. Sci. 2015, 47, 1. doi: 10.1016/j.pecs.2014.10.002 doi: 10.1016/j.pecs.2014.10.002
7. [7]
  Skodje, R.T.; Tomlin, A. S.; Klippenstein, S. J.; Harding, L. B.; Davis, M. J. J. Phys. Chem. A 2010, 114, 8286. doi: 10.1021/jp1047002 doi: 10.1021/jp1047002
8. [8]
  Saltelli, A. ; Tarantola, S. ; Campolongo, F. ; Ratto, M. Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models; John Wiley & Sons Ltd. : Chichester, UK; 2004.
9. [9]
  Saltelli, A.; Ratto, M.; Tarantola, S.; Campolongo, F.; Commission, E. Relia. Eng. Syst. Saf. 2006, 91 (10-11), 1109. doi: 10.1016/j.ress.2005.11.014 doi: 10.1016/j.ress.2005.11.014
10. [10]
  Saltelli, A. ; Ratto, M. ; Andres T. ; Campolongo, F. ; Cariboni, J. ; Gatelli, D. ; Sasana, M. ; Tarantola, S. Global Sensitivity Analisis: The Primer; John Wiley & Sons: Hoboken, NJ, USA; 2008.
11. [11]
  Najm, H. N. Annu. Rev. Fluid Mech. 2009, 41, 35. doi: 10.1146/annurev.fluid.010908.165248 doi: 10.1146/annurev.fluid.010908.165248
12. [12]
  Sobol, I. M. Modelirovanie 1990, 2, 112. doi: 10.1016/S0378-4754(00)00270-6 doi: 10.1016/S0378-4754(00)00270-6
13. [13]
  Zsély, I. G.; Zádor, J.; Turányi, T. Reliab. Eng. Syst. Saf. 1997, 57, 41. doi: 10.1002/kin.20373 doi: 10.1002/kin.20373
14. [14]
  Turányi, T. ; Rabitz, H. ; Saltelli, A. ; Chan, K. ; Scott, E. M. Sensitivity Analysis; Wiley: Chichester, UK; 2000.
15. [15]
  McKay, M. D. Reliab. Eng. Syst. Saf. 1997, 57, 267. doi: 10.1016/S0951-8320(97)00039-2 doi: 10.1016/S0951-8320(97)00039-2
16. [16]
  Xing, L.; Li, S.; Wang, Z.; Yang, B.; Klippenstein, S. J.; Zhang, F. Combust. Flame 2015, 162, 3427. doi: 10.1016/j.combustflame.2015.06.006 doi: 10.1016/j.combustflame.2015.06.006
17. [17]
  Zheng, X. L.; Lu, T. F.; Law, C. K. Proc. Combust. Inst. 2007, 31, 367. doi: 10.1016/j.proci.2006.07.182 doi: 10.1016/j.proci.2006.07.182
18. [18]
  Sankaran, R.; Hawkes, E. R.; Chen, J. H.; Lu, T. F.; Law, C. K. Proc. Combust. Inst. 2007, 31, 1291. doi: 10.1016/j.proci.2006.08.025 doi: 10.1016/j.proci.2006.08.025
19. [19]
  Luo, Z.; Plomer, M.; Lu, T. F.; Som, S.; Longman, D. E.; Sarathy, S. M.; Pitz, W. J. Fuel 2012, 99, 143. doi: 10.1016/j.fuel.2012.04.028 doi: 10.1016/j.fuel.2012.04.028
20. [20]
  Lu, T. F.; Law, C. K. Combust. Flame 2008, 154, 153. doi: 10.1016/j.combustflame.2007.11.013 doi: 10.1016/j.combustflame.2007.11.013
21. [21]
  Niemeyer, K. E.; Sung, C. J. Combust. Flame 2014, 161, 2752. doi: 10.1016/j.combustflame.2014.05.001 doi: 10.1016/j.combustflame.2014.05.001
22. [22]
  Niemeyer, K. E.; Sung, C. J.; Raju, M. P. Combust. Flame 2010, 157, 1760. doi: 10.1016/j.combustflame.2009.12.022 doi: 10.1016/j.combustflame.2009.12.022
23. [23]
  Li, R.; Li, S. H.; Wang, F.; Li, X. Y. Combust. Flame 2016, 166, 55. doi: 10.1016/j.combustflame doi: 10.1016/j.combustflame
24. [24]
  SENKIN: A Fortran Program for Predicting Homogeneous Gas Phase Chemical Kinetics with Sensitivity Analysis. Available online: https: //www. osti. gov/biblio/5371815 (accessed on February 28, 2018).
25. [25]
  Turányi, T. Tools Appl. J. Math. Chem. 1990, 5, 203. doi: 10.1007/BF01166355 doi: 10.1007/BF01166355
26. [26]
  Ziehn, T.; Tomlin, A. S. Env. Model. Soft. 2009, 24, 775. doi: 10.1016/j.envsoft doi: 10.1016/j.envsoft
27. [27]
  Sobol, I. M. Math. Comp. Sim. 2001, 55, 271. doi: 10.1016/S0378-4754(00)00270-6 doi: 10.1016/S0378-4754(00)00270-6
28. [28]
  Li, S.; Yang, B.; Qi, F. Combust. Flame 2016, 168, 53. doi: 10.1016/j.combustflame.2016.03.028 doi: 10.1016/j.combustflame.2016.03.028
29. [29]
  Ziehn, T.; Hughes, K. J.; Griffiths, J. F.; Porter, R.; Tomlin, A. S. Combust. Theory Modell. 2009, 13, 589. doi: 10.1080/13647830902878398 doi: 10.1080/13647830902878398
30. [30]
  Tomlin, A. S.; Ziehn, T. Lect. Notes Comput. Sci. Eng. 2010, 75, 9. doi: 10.1007/978-3-642-14941-2_2 doi: 10.1007/978-3-642-14941-2_2
31. [31]
  Saltelli, A.; Annoni, P.; Azzini, I.; Campolongo, F.; Ratto, M.; Tarantola, S. Comput. Phys. Commun. 2010, 181, 259. doi:10.1016/j.cpc.2009.09.018 doi: 10.1016/j.cpc.2009.09.018
32. [32]
  Davis, M. J.; Liu, W.; Sivaramakrishnan, R. J. Phys.Chem.A 2017, 121 (3), 553. doi: 10.1021/acs.jpca.6b09310 doi: 10.1021/acs.jpca.6b09310
33. [33]
  Davis, M. J.; Skodje, R. T.; Tomlin, A. S. J. Phys. Chem. A 2011, 115, 1556. doi: 10.1021/jp108017t doi: 10.1021/jp108017t
34. [34]
  Ziehn, T.; Tomlin, A. S. Int. J. Chem. Kinet. 2008, 40, 742. doi: 10.1002/kin.20367 doi: 10.1002/kin.20367
35. [35]
  Ziehn, T.; Tomlin, A. S. Atmos. Environ.2008, 42, 1857. doi: 10.1016/j.atmosenv.2007.11.018 doi: 10.1016/j.atmosenv.2007.11.018
36. [36]
  Zhou, D. Y.; Davis, M. J.; Skodje, R. T. J. Phys. Chem. A 2013, 117, 3569. doi: 10.1021/jp312340q doi: 10.1021/jp312340q
37. [37]
  Rabitz, H.; Alis, Ö. F. J. Math. Chem. 1999, 25, 197. doi: 10.1023/A:1019188517934 doi: 10.1023/A:1019188517934
38. [38]
  Wang, S. W.; Georgopoulos, P. G.; Li, G.; Rabitz, H. Lect. Notes Comput. Sci. 2001, 2179, 326. doi: 10.1007/3-540-45346-6_34 doi: 10.1007/3-540-45346-6_34
39. [39]
  Brell, G.; Li, G.; Rabitz, H. J. Chem. Phys. 2010, 132, 174103. doi: 10.1063/1.3407440 doi: 10.1063/1.3407440
40. [40]
  Alis, Ö. F.; Rabitz, H. J. Math. Chem. 2001, 29, 127. doi: 10.1023/A:1010979129659 doi: 10.1023/A:1010979129659
41. [41]
  Li, G.; Wang, S. W.; Rabitz, H. J. Phys. Chem. A 2002, 106, 8721. doi: 10.1021/jp014567t doi: 10.1021/jp014567t
42. [42]
  Li, G.; Wang, S. W.; Rabitz, H.; Wang, S.; Jaffé, P. Chem. Eng. Sci. 2002, 57, 4445. doi: 10.1016/S0009-2509(02)00417-7 doi: 10.1016/S0009-2509(02)00417-7
43. [43]
  Feng, X. J.; Hooshangi, S.; Chen, D.; Li, G.; Weiss, R.; Rabitz, H. Biophys. J. 2004, 87, 2195. doi: 10.1529/biophysj.104.044131 doi: 10.1529/biophysj.104.044131
44. [44]
  Rabitz, H.; Alis, Ö. F.; Shorter, J.; Shim, K. Comput. Phys. Commun. 1999, 117, 11. doi: 10.1016/S0010-4655(98)00152-0 doi: 10.1016/S0010-4655(98)00152-0
45. [45]
  Li, G.; Rabitz, H.; Wang, S. W.; Georgopoulos, P. G. J. Comput. Chem. 2003, 24, 277. doi: 10.1002/jcc.10172 doi: 10.1002/jcc.10172
46. [46]
  Li, G.; Rabitz, H. J. Comput. Chem. 2006, 27, 1112. doi: 10.1002/jcc.20435 doi: 10.1002/jcc.20435
47. [47]
  McKay, M. D. Reliab. Eng. Syst. Saf. 1997, 57, 267. doi: 10.1016/S0951-8320(97)00039-2 doi: 10.1016/S0951-8320(97)00039-2
48. [48]
  O'Conaire, M.; Curran, H. J.; Simmie, J. M.; Pitz, W. J.; Westbrook, C. K. Intl. J. Chem. Kinet. 2004, 36 (11), 603. doi: 10.1002/kin.20036 doi: 10.1002/kin.20036
49. [49]
  Konnov, A. A. Combust. Flame 2008, 152, 507. doi: 10.1016/j.combustflame.2007.10.024 doi: 10.1016/j.combustflame.2007.10.024
50. [50]
  Wang, Q. D. Acta Phys. -Chim. Sin 2016, 32, 595. doi: 10.3866/PKU.WHXB201512211
51. [51]
  Lu, T. F.; Law, C. K. Combust. Inst. 2005, 30, 1333. doi: 10.1016/j.proci.2004.08.145 doi: 10.1016/j.proci.2004.08.145
52. [52]
  Li, S. H.; Li, R.; Guo, J. J.; Tan, N. X.; Wang, F.; Li, X. Y. Acta Phys. -Chim. Sin. 2016, 32, 1623. doi: 10.3866/PKU.WHXB201604084
53. [53]
  Jiang, Y.; Qiu, R. Acta Phys. -Chim. Sin. 2009, 25, 1019. doi: 10.3866/PKU.WHXB20090426
54. [54]
  Pepiot-Desjardins, P.; Pitsch, H. Combust. Flame 2008, 154, 67. doi: 10.1016/j.combustflame.2007.10.020 doi: 10.1016/j.combustflame.2007.10.020
55. [55]
  Luo, Z.; Lu, T. F.; Maciaszek, M. J.; Som, S.; Longman, D. E. Energy Fuels 2010, 24, 6283. doi: 10.1021/ef1012227 doi: 10.1021/ef1012227
56. [56]
  Sun, W.; Chen, Z.; Gou, X.; Ju, Y. Combust. Flame 2010, 157, 1298. doi: 10.1016/j.combustflame.2010.03.006 doi: 10.1016/j.combustflame.2010.03.006
57. [57]
  Liu, A. K.; Jiao, Y.; Li, S. H.; Wang, F.; Li, X. Y. Energy Fuels 2014, 28, 5426. doi: 10.1021/ef5002502 doi: 10.1021/ef5002502
58. [58]
  Available online: http://c3.nuigalway.ie/butane.html (accessed on February 28, 2018).
59. [59]
  Mehl, M.; Pitz, W. J.; Westbrook, C. K.; Curran, H. J. Proc. Combust. Inst. 2011, 33 (1), 193. doi: 10.1016/j.proci.2010.05.027 doi: 10.1016/j.proci.2010.05.027
60. [60]
  Mehl, M.; Pitz, W. J.; Sjöberg, M.; Dec, J. E. SAE Tech. Paper. 2009, 1, 1806. doi: 10.4271/2009-01-180 doi: 10.4271/2009-01-180
1. [1]
  Xueling Yu , Lixing Fu , Tong Wang , Zhixin Liu , Na Niu , Ligang Chen . Multivariate chemical analysis: From sensors to sensor arrays. Chinese Chemical Letters, 2024, 35(7): 109167-. doi: 10.1016/j.cclet.2023.109167
2. [2]
  Weijian Zhang , Xianyu Deng , Liying Wang , Jian Wang , Xiuting Guo , Lianggui Huang , Xinyi Wang , Jun Wu , Linjia Jiang . Poly(ferulic acid) nanocarrier enhances chemotherapy sensitivity of acute myeloid leukemia by selectively targeting inflammatory macrophages. Chinese Chemical Letters, 2024, 35(9): 109422-. doi: 10.1016/j.cclet.2023.109422
3. [3]
  Lan Yang , Yu Li , Mou Jiang , Rui Zhou , Hengjiang Cong , Minghui Yang , Lei Zhang , Shenhui Li , Yunhuang Yang , Maili Liu , Xin Zhou , Zhong-Xing Jiang , Shizhen Chen . Fluorinated [2]rotaxanes as sensitive ¹⁹F MRI agents: Threading for higher sensitivity. Chinese Chemical Letters, 2024, 35(10): 109512-. doi: 10.1016/j.cclet.2024.109512
4. [4]
  Junmei FAN , Wei LIU , Ruitao ZHU , Chenxi QIN , Xiaoling LEI , Haotian WANG , Jiao WANG , Hongfei HAN . High sensitivity detection of baicalein by N, S co-doped carbon dots and their application in biofluids. Chinese Journal of Inorganic Chemistry, 2024, 40(10): 2009-2020. doi: 10.11862/CJIC.20240120
5. [5]
  Huihui LIU , Baichuan ZHAO , Chuanhui WANG , Zhi WANG , Congyun ZHANG . Green synthesis of MIL-101/Au composite particles and their sensitivity to Raman detection of thiram. Chinese Journal of Inorganic Chemistry, 2024, 40(10): 2021-2030. doi: 10.11862/CJIC.20240059
6. [6]
  Neng Shi , Haonan Jia , Jixiang Zhang , Pengyu Lu , Chenglong Cai , Yixin Zhang , Liqiang Zhang , Nongyue He , Weiran Zhu , Yan Cai , Zhangqi Feng , Ting Wang . Accurate expression of neck motion signal by piezoelectric sensor data analysis. Chinese Chemical Letters, 2024, 35(9): 109302-. doi: 10.1016/j.cclet.2023.109302
7. [7]
  Yuxin Li , Chengbin Liu , Qiuju Li , Shun Mao . Fluorescence analysis of antibiotics and antibiotic-resistance genes in the environment: A mini review. Chinese Chemical Letters, 2024, 35(10): 109541-. doi: 10.1016/j.cclet.2024.109541
8. [8]
  Tian Feng , Yun-Ling Gao , Di Hu , Ke-Yu Yuan , Shu-Yi Gu , Yao-Hua Gu , Si-Yu Yu , Jun Xiong , Yu-Qi Feng , Jie Wang , Bi-Feng Yuan . Chronic sleep deprivation induces alterations in DNA and RNA modifications by liquid chromatography-mass spectrometry analysis. Chinese Chemical Letters, 2024, 35(8): 109259-. doi: 10.1016/j.cclet.2023.109259
9. [9]
  Cheng Guo , Xiaoxiao Zhang , Xiujuan Hong , Yiqiu Hu , Lingna Mao , Kezhi Jiang . Graphene as adsorbent for highly efficient extraction of modified nucleosides in urine prior to liquid chromatography-tandem mass spectrometry analysis. Chinese Chemical Letters, 2024, 35(4): 108867-. doi: 10.1016/j.cclet.2023.108867
10. [10]
  Guangchang Yang , Shenglong Yang , Jinlian Yu , Yishun Xie , Chunlei Tan , Feiyan Lai , Qianqian Jin , Hongqiang Wang , Xiaohui Zhang . Regulating local chemical environment in O3-type layered sodium oxides by dual-site Mg²⁺/B³⁺ substitution achieves durable and high-rate cathode. Chinese Chemical Letters, 2024, 35(9): 109722-. doi: 10.1016/j.cclet.2024.109722
11. [11]
  Yi Herng Chan , Zhe Phak Chan , Serene Sow Mun Lock , Chung Loong Yiin , Shin Ying Foong , Mee Kee Wong , Muhammad Anwar Ishak , Ven Chian Quek , Shengbo Ge , Su Shiung Lam . Thermal pyrolysis conversion of methane to hydrogen (H₂): A review on process parameters, reaction kinetics and techno-economic analysis. Chinese Chemical Letters, 2024, 35(8): 109329-. doi: 10.1016/j.cclet.2023.109329
12. [12]
  Kaimin WANG , Xiong GU , Na DENG , Hongmei YU , Yanqin YE , Yulu MA . Synthesis, structure, fluorescence properties, and Hirshfeld surface analysis of three Zn(Ⅱ)/Cu(Ⅱ) complexes based on 5-(dimethylamino) isophthalic acid. Chinese Journal of Inorganic Chemistry, 2024, 40(7): 1397-1408. doi: 10.11862/CJIC.20240009
13. [13]
  Yun Wei , Lei Zhou , Wenbin Hu , Liming Yang , Guang Yang , Chaoqiang Wang , Hui Shi , Fei Han , Yufa Feng , Xuan Ding , Penghui Shao , Xubiao Luo . Recovery of cathode copper and ternary precursors from CuS slag derived by waste lithium-ion batteries: Process analysis and evaluation. Chinese Chemical Letters, 2024, 35(7): 109172-. doi: 10.1016/j.cclet.2023.109172
14. [14]
  Mianying Huang , Zhiguang Xu , Xiaoming Lin . Mechanistic analysis of Co2VO4/X (X = Ni, C) heterostructures as anode materials of lithium-ion batteries. Chinese Journal of Structural Chemistry, 2024, 43(7): 100309-100309. doi: 10.1016/j.cjsc.2023.100309
15. [15]
  Runze Liu , Yankai Bian , Weili Dai . Qualitative and quantitative analysis of Brønsted and Lewis acid sites in zeolites: A combined probe-assisted 1H MAS NMR and NH3-TPD investigation. Chinese Journal of Structural Chemistry, 2024, 43(4): 100250-100250. doi: 10.1016/j.cjsc.2024.100250
16. [16]
  Fanxin Kong , Hongzhi Wang , Huimei Duan . Inhibition effect of sulfation on Pt/TiO2 catalysts in methane combustion. Chinese Journal of Structural Chemistry, 2024, 43(5): 100287-100287. doi: 10.1016/j.cjsc.2024.100287
17. [17]
  Zixi Zou , Jingyuan Wang , Yian Sun , Qian Wang , Da-Hui Qu . Controlling molecular assembly on time scale: Time-dependent multicolor fluorescence for information encryption. Chinese Chemical Letters, 2024, 35(7): 108972-. doi: 10.1016/j.cclet.2023.108972
18. [18]
  Xuebing Jiang , Siyi Wang , Li Zhang , Xian Jiang , Maling Gou . Lidocaine hydrochloride loaded isomaltulose microneedles for efficient local anesthesia of the skin. Chinese Chemical Letters, 2024, 35(4): 108686-. doi: 10.1016/j.cclet.2023.108686
19. [19]
  Bharathi Natarajan , Palanisamy Kannan , Longhua Guo . Metallic nanoparticles for visual sensing: Design, mechanism, and application. Chinese Journal of Structural Chemistry, 2024, 43(9): 100349-100349. doi: 10.1016/j.cjsc.2024.100349
20. [20]
  Min Fu , Pan He , Sen Zhou , Wenqiang Liu , Bo Ma , Shiying Shang , Yaohao Li , Ruihan Wang , Zhongping Tan . An unexpected stereochemical effect of thio-substituted Asp in native chemical ligation. Chinese Chemical Letters, 2024, 35(8): 109434-. doi: 10.1016/j.cclet.2023.109434

Get Citation

PDF

XML

Metrics

PDF Downloads(20)
Abstract views(563)
HTML views(67)

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142