臺灣博碩士論文加值系統

物質自反應性危害為發生工業火災與爆炸的重要原因之一，歐盟化學品註冊法規（Registration Evaluation Authorization and Restriction of Chemicals ,REACH）把自反應特性歸類於物理和化學特性的爆炸性特性中，其中化學物質具有自反應特性判斷依據為其分解熱之起始溫度(Onset temperature , Tonst)和分解熱(Exothermic Decomposition energy,△H)，針對物質的分解熱與其起始溫度是自反應性危害研究上的一個重要方向。儘管許多文獻提出分解熱與其起始溫度的預測模式，但大部分預測模式都是只針對某一小族群且數據量少，其預測的範圍是非常有限。物質之起始溫度與分解熱實驗數據之取得需要耗費一定數量的樣本，對於高價稀少的樣品或是具有危害特性之物質，實驗的進行有一定的困難，可靠針對物質自反應性之起始溫度與分解熱特性預測模式是不可或缺的。定量構效關係模式(Quantitative Structure Property Relationship, QSPR)是利用化學物質分子結構的資訊來預測化學物質特定的物化特性，目前已廣泛用來預測各種難以用實驗方法取得的數據，因此REACH法規將此模式列為測試之替代方法。本研究採用定量結構效應的方法，收集歐盟所列舉之具有爆炸性特性官能基實驗數據，利用Dragon與CODESSA Pro軟體計算出各化合物的分子描述符，而後利用逐步回歸法找出與分解熱與其起始溫度具高相關性的描述符，並建立回歸模式。本研究對於分解熱與其起始溫度，針對歐盟的爆炸物特性分類提出氮氧化物(N-O)、硝基化合物(Nitro compounds)與硝基苯(Nitroatomatics)三個群組的預測模式，並與硝基苯之分解熱與其起始溫度預測模式文獻做比較。

Chemical Reactivity hazard has been reported as one of the main causes of fire and explosion in the industries. The reactivity distributes self-reactivity and compatibility. According to EU-REACH regulation, the self-reactivity is categorized into explosive properties which is Physical and chemical properties. Exothermic onset temperature ( T o ) and decomposition energy (Hd) are important self-reactivity parameters. Although many Exothermic onset temperature ( T o ) and decomposition energy (Hd) prediction models are put forward, but most of them are only for small groups and a small amount of data which make the prediction range very limited. However, certain quantities of samples are used in experiments. when chemicals have unknown toxicity or at high prices, it’s difficult to get their To and Hd through experiments. In this regard, taking reliable methods to estimate the To and Hd of compounds is indispensable. Quantitative structure activity relationship (QSAR) approach has been validated to be an effective method for predicting properties of chemical compounds, and it also has been acknowledged worldwide to be one of the predictive methods for providing hazardous information of chemical substances. EU takes this mode of testing as an alternative in REACH regulation.In this work, the To 137 of N-O compounds and Hd 138 of N-O compounds are collected to build up and validate a QSAR model for predicting the To of N-O compounds. Dragon and CODESSA PRO software are adopted to calculate molecular descriptors for each compound. A modified stepwise regression algorithm is applied to find out molecular descriptors that are highly correlated with the To and Hd of N-O compounds.

中文摘要 I
Abstract II
致謝 IV
目錄 V
圖目錄(一) IX
表目錄(一) XII
第一章 緒論 1
第一節 研究背景 1
第二節 研究目的 6
第三節 名詞界定 7
第二章 文獻回顧 9
第一節 定量構效關係 9
2-1-1 定量結構效應關係發展 9
2-1-2 分子描述符 11
2-1-3 定量構效關係模式 12
2-1-4 OECD 規範模式原則 14
第二節 化學物質自反應性之文獻回顧 16
2-2-1 化學物質自反應性評估之流程 16
2-2-2 現有自反應性化學物質之定量結構效應評論及探討 20
2-2-3 起始溫度預測模式 24
2-2-4 分解熱預測模式 26
第三章 研究方法 30
第一節 研究流程 30
第二節 研究資料收集 34
3-2-1 收集數據官能基之分類狀況 35
3-2-2 定量構效之起始溫度資料收集 39
3-2-3 定量構效之分解熱資料收集 47
第三節 定量結構效應模式建立 55
3-3-1 描述符變量選擇法-逐步回歸法 55
3-3-2 建立模式型態-多元線性回歸法 56
第四節 實驗驗證 58
3-4-1 高效能同步熱重熱焓分析儀TGA/DSC 58
3-4-2 測試藥品 63
第四章 研究結果與討論 64
第一節 起始溫度 64
4-1-1 起始溫度之預測模式 64
4-1-2 起始溫度預測模式之統計結果與性能 74
4-1-3 起始溫度之試驗結果 89
4-1-4 起始溫度之適用範圍 96
4-1-5 現有之起始溫度模式之比較 110
第二節 分解熱 122
4-2-1 氮氧化物 123
4-2-2 硝基化合物 137
4-2-3 硝基苯化合物 151
4-2-4 分解熱模式之離群值 165
4-2-5 現有之分解熱模式之狀況 168
第五章 結論 171
第一節 起始溫度預測模式結論 171
第二節 分解熱預測模式結論 174
第三節 應用與建議 177
參考文獻 178
附錄A - (EC) No1907/2006 183
附錄B-29 CFR Parts 1910, 1915, 1917, 1918, and 1926 Hazard 185
附錄C-Sustainability and the U.S. EPA 189
附錄D-NFPA 704-NR定義 190
附錄E-起始溫度 研究資料 191
附錄F 分解熱 研究資料 199

1.Johnson, R.W., S.W. Rudy, and S.D. Unwin, Introduction and Overview, in Essential Practices for Managing Chemical Reactivity Hazards. 2010, John Wiley & Sons, Inc. p. 1-16.
2.Crowl, D.A. and J.F. Louvar, Chemical Process Safety: Fundamentals with Applications (3rd Edition) (Prentice Hall International Series in the Physical and Chemical Engineering Sciences). 2012.
3.Ando, T., Y. Fujimoto, and S. Morisaki, Analysis of differential scanning calorimetric data for reactive chemicals. Journal of Hazardous Materials, 1991. 28(3): p. 251-280.
4.Registration, E., Authorisation and Restriction of Chemicals (REACH), REGULATION (EC) No 1907/2006 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL, E.C. Agency, Editor. 2006.
5.Administration, O.S.H., 29 CFR Parts 1910, 1915, 1917, 1918, and 1926. 2012.
6.Agency, U.S.E.P., Sustainability and the U.S. EPA. 2011.
7.Agency, U.S.E.P., The Use of Structure-Activity Relationships (SAR) in the High Production Volume Chemicals Challenge Program.
8.中華民國勞動部, 新化學物質登記管理辦法, 中華民國勞動部, Editor. 103年07月01日修正.
9.Agency, E.C., Guidance on information requirements and chemical safety assessment Chapter R.6: QSARs and grouping of chemicals. 2008.
10.Agency, E.C., Guidance on information requirements and Chemical Safety Assessment Chapter R.7a: Endpoint specific guidance, E.C. Agency, Editor. 2014.
11.Fayet, G., et al., Theoretical Study of the Decomposition Reactions in Substituted Nitrobenzenes. The Journal of Physical Chemistry A, 2008. 112(17): p. 4054-4059.
12.Fayet, G., et al., On the use of descriptors arising from the conceptual density functional theory for the prediction of chemicals explosibility. Chemical Physics Letters, 2009. 467(4–6): p. 407-411.
13.Fayet, G., et al., On the prediction of thermal stability of nitroaromatic compounds using quantum chemical calculations. Journal of Hazardous Materials, 2009. 171(1–3): p. 845-850.
14.Fayet, G., et al., QSPR modeling of thermal stability of nitroaromatic compounds: DFT vs. AM1 calculated descriptors. Journal of Molecular Modeling, 2010. 16(4): p. 805-812.
15.Fayet, G., et al., Predicting explosibility properties of chemicals from quantitative structure-property relationships. Process Safety Progress, 2010. 29(4): p. 359-371.
16.Fayet, G., et al., Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanisms. Journal of Molecular Modeling, 2011. 17(10): p. 2443-2453.
17.Fayet , G., et al., Predicting the Thermal Stability of Nitroaromatic Compounds Using Chemoinformatic Tools. Molecular Informatics, 2011. 30(6-7): p. 623-634.
18.Baatia, N., et al., Quantitative Structure-Property Relationships for Thermal
Stability and Explosive Properties of Chemicals. CHEMICAL ENGINEERING, 2013. 31: p. 841-846.
19.Li, J., et al., Structure-Activity Relationship Analysis of the Thermal Stabilities of Nitroaromatic Compounds Following Different Decomposition Mechanisms. Molecular Informatics, 2013. 32(2): p. 193-202.
20.Mathieu, D., Significance of Theoretical Decomposition Enthalpies for Predicting Thermal Hazards. Journal of Chemistry, 2015. 2015: p. 12.
21.Baati, N., et al., Predictive Models for Thermal Behavior of Chemicals with Quantitative Structure-Property Relationships. Chemical Engineering & Technology, 2015. 38(4): p. 645-650.
22.Zhang, Y., et al., Prediction of thermal stability of some reactive chemicals using the QSPR approach. Journal of Environmental Chemical Engineering, 2014. 2(2): p. 868-874.
23.Brown, A.C. and T.R. Fraser, On the Connection between Chemical Constitution and Physiological Action; with special reference to the Physiological Action of the Salts of the Ammonium Bases derived from Strychnia, Brucia, Thebaia, Codeia, Morphia, and Nicotia. Journal of Anatomy and Physiology, 1868. 2(2): p. 224-242.
24.Biography, R., Physiological research on alcohols. Medical Times and Gazette, 1869. 2: p. 703-706.
25.PORTIER, P. and C.R. RICHET, Del’action anaphylactique de certain venins. Comptes Rendus Des Seances De La Societe De Biologie Et De Ses Filiales, 1902. 54: p. 170-172.
26.Meyer, H., Zur Theorie der Alkoholnarkose. Archiv für experimentelle Pathologie und Pharmakologie, 1899. 42(2-4): p. 109-118.
27.Overton, E., Ueber die osmotischen Eigenschaften der Zelle in ihrer Bedeutung für die Toxikologie und Pharmakologie Zeitschrift für Physikalische Chemie, 1987. 22: p. 189–209.
28.Hammett, L.P., Some Relations between Reaction Rates and Equilibrium Constants. Chemical Reviews, 1935. 17(1): p. 125-136.
29.Hammett, L.P., The Effect of Structure upon the Reactions of Organic Compounds. Benzene Derivatives. Journal of the American Chemical Society, 1937. 59(1): p. 96-103.
30.Hansch, C., et al., Correlation of Biological Activity of Phenoxyacetic Acids with Hammett Substituent Constants and Partition Coefficients. Nature, 1962. 194(4824): p. 178-180.
31.Hansch, C., et al., The Correlation of Biological Activity of Plant Growth Regulators and Chloromycetin Derivatives with Hammett Constants and Partition Coefficients. Journal of the American Chemical Society, 1963. 85(18): p. 2817-2824.
32.Free, S.M. and J.W. Wilson, A Mathematical Contribution to Structure-Activity Studies. Journal of Medicinal Chemistry, 1964. 7(4): p. 395-399.
33.王鵬, 定量結構關係及研究方法. 2011, 哈爾濱工業大學.
34.Consonni, V. and R. Todeschini, Multivariate Analysis of Molecular Descriptors, in Statistical Modelling of Molecular Descriptors in QSAR/QSPR. 2012, Wiley-VCH Verlag GmbH & Co. KGaA. p. 111-147.
35.Maran, U. and S. Slid, QSAR Modeling of Genotoxicity on Non-congeneric Sets of Organic Compounds. Artificial Intelligence Review, 2003. 20(1-2): p. 13-38.
36.Development, O.f.E.C.-o.a., GUIDANCE DOCUMENT ON THE VALIDATION OF (QUANTITATIVE)STRUCTURE-ACTIVITY RELATIONSHIPS [(Q)SAR] MODELS, O.E.H.a.S.P.S.o.T.a. Assessment, Editor. 2007.
37.中華民國勞動部, 職業安全衛生設施規則, 中華民國勞動部, Editor. 103年07月01日修正.
38.Association, N.F.P., NFPA704:STANDARD SYSTEM FOR THE IDENTIFICATION OF THE HAZARDS OF MATERIALS FOR EMERGENCY RESPONSE
2012.
39.NATIONS, U., Recommendations on the TRANSPORT OF DANGEROUS GOODS
Model Regulations. 2013.
40.Dearden, J.C., P. Rotureau, and G. Fayet, QSPR prediction of physico-chemical properties for REACH. SAR and QSAR in Environmental Research, 2013. 24(4): p. 279-318.
41.Saraf, S.R., W.J. Rogers, and M.S. Mannan, Prediction of reactive hazards based on molecular structure. Journal of Hazardous Materials, 2003. 98(1–3): p. 15-29.
42.Saraf, S.R., et al., Integrating molecular modeling and process safety research. Fluid Phase Equilibria, 2004. 222–223: p. 205-211.
43.Inc, H., HyperChem Release 8.0 for Windows. Molecular Modeling System, 2008.
44.Lewars, E., COMPUTATIONAL CHEMISTRY-Introduction to the Theory and Applications of Molecular and Quantum Mechanics. 2004.
45.srl, T., Dragon for Windows (Software for molecular Descriptor Calculations). Version 6.0. (http://www.talete.mi.it/). 2013.
46.Katritzky, A.R., M. Karelson, and R. Petrukhin, CODESSA PRO, Version 1.0RC2. 2005.
47.Duh, Y.-S., et al., Chemical incompatibility of nitrocompounds. Journal of Hazardous Materials, 1997. 53(1–3): p. 183-194.
48.陸立明. 熱分析應用基礎. 2010.
49.Materials, A.S.F.T.a., Standard Test Method for The Thermal Stability of Chemicals by Differential Scanning Calorimetry. 2015.
50.Sahigara, F., et al., Comparison of Different Approaches to Define the Applicability Domain of QSAR Models. molecules, 2012. 17: p. 4791-4810.
51.Netzeva, T., et al., Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop 52. Altern Lab Anim, 2005. 33: p. 155 - 173.
52.Sahigara, F., et al., Defining a novel k-nearest neighbours approach to assess the applicability domain of a QSAR model for reliable predictions. Journal of Cheminformatics, 2013. 5(1): p. 27.
53.Jaworska, J., N. Nikolova-Jeliazkova, and T. Aldenberg, QSAR applicabilty domain estimation by projection of the training set descriptor space: A review. Altern Lab Anim, 2005. 33: p. 445 - 459.
54.Sahigara, F., et al., Assessing the validity of QSARs for ready biodegradability of chemicals: an applicability domain perspective. Current Computer Aided-Drug Design, 2014. 10(2): p. 137-147.
55.Group, M.C.a.Q.R., Applicability Domain toolbox for MATLAB version 1.0. 2014.
56.Amin, J.S., S. Nikkhah, and M. Veiskarami, A statistical method for assessment of the existing correlations of hydrate forming conditions. Journal of Energy Chemistry, 2015. 24(1): p. 93-100.