Prediction of Minimum Ignition Energy from Molecular Structure Using Quantitative Structure−Property Relationship Models

Significance Statement

Experimental measurements involved in determining one of the parameters used for characterizing hazardous chemicals, minimum ignition energy, is known to be risky as a result of the high volatility of certain chemicals. There also exists some form of unpredictability in experimental measurements coupled with the exorbitant cost it portends during data processing.

In order to provide another alternative, the use of a quantitative structure-property relationship (QSPR) model where physicochemical properties of substances can be mathematically expressed, affords an accurate modeled response of molecular structures. Hence, for the first time, the effectiveness of the quantitative structure-property relationship model can be applied in studying the minimum ignition energy of chemical substances. Researchers led by Professor Qingsheng “Sam” Wang from Oklahoma State University reported in the journal, Industrial & Engineering Chemistry Research the development of two quantitative structure-property relationship models involving multiple linear regression analysis and support vector machine to determine minimum ignition energy values of hydrocarbon fuels.

The authors showed that the multiple linear regression analysis had high goodness-of-fit with experimental data; excellent internal robustness was also achieved coupled with a sizable external predictive ability. Values at which the model can be optimized were also given.

The support vector machine analytical model also had similar features with that of the multiple linear regression model. The two models had comparable values for both the training set and test set, showing their tremendous capacity in overall sensing performance.

Depending on the experimental conditions, an appropriate model could be selected. The multiple linear regression model had better computability and better internal robustness and on the other hand, the support vector machine model possessed better goodness-of-fit and external predictive ability.

The quantitative structure-property relationship models developed in this study can certainly serve as an excellent alternative for determining the minimum ignition energy of hydrocarbon fuels, thereby eliminating any form of danger found in experimental measurements.

Prediction of Minimum Ignition Energy from Molecular Structure Using Quantitative Structure−Property Relationship (QSPR) Models-Advances in Engineering

About The Author

Qingsheng Wang is Dale F. Janes Endowed Associate Professor of Fire Protection & Safety and Graduate Faculty of Chemical Engineering at Oklahoma State University (OSU) in the US. He is Program Director of Fire Protection & Safety at OSU, which is the oldest fire/safety related program in North America and the first ABET accredited program in the fire/safety field in the US. He received his BS and MS degrees in Chemistry with Honors from Zhejiang University and his PhD degree in Chemical Engineering from Texas A&M University with an emphasis in process safety. He is a registered professional engineer (PE) and certified safety professional (CSP).

Dr. Wang has been actively involved in experimental and theoretical studies on chemical reactivity, thermal analysis, and flame retardants for over 10 years. He is the author of 48 referred journal papers, 23 proceedings, and 85 technical presentations in his areas of interest. He has received numerous awards, such as Big 12 Faculty Fellow, Halliburton Outstanding Young Faculty Award, and Certificate of Excellence in Reviewing from Elsevier. He serves as Editor and Editorial Board Member for a number of journals in the field.

About The Author

Beibei Wang received her BS and MS degrees in Safety Engineering from Northeastern University in China. She is now working on her PhD degree at Oklahoma State University in the field of quantitative structure–property relationship (QSPR). Her PhD dissertation is on prediction of chemical hazard properties by using QSPR models.

About The Author

Lulu Zhou received her BS and MS degrees in Safety Engineering from Nanjing Tech University in China. She is now working on her PhD degree in the field of quantitative structure–property relationship (QSPR). Her PhD dissertation is on prediction of critical properties of chemicals (both pure substances and mixtures) by using QSPR models.

About The Author

Kaili Xu received his BS, MS and PhD degrees in Safety Engineering from Northeastern University in China. He is now Professor of Safety Engineering at Northeastern University. His research focuses on theory of system safety, hazard identification and evaluation, hazard control in occupational environment, and safety of biomass energy. He is a first grade registered safety evaluation engineer and a certified training teacher of safety evaluation in China.

Reference

Wang, B.1,2, Zhou, L.2, Xu, K.1, Wang, Q.2,3 Prediction of Minimum Ignition Energy from Molecular Structure Using Quantitative Structure−Property Relationship (QSPR) Models, Industrial & Engineering Chemical Research 56 (2017) 47−51.

Show Affiliations
  1. School of Resources and Civil Engineering, Northeastern University, Shenyang, Liaoning 110819, China
  2. Department of Fire Protection & Safety, Oklahoma State University, Stillwater, Oklahoma 74078, United States
  3. Department of Chemical Engineering, Oklahoma State University, Stillwater, Oklahoma 74078, United States

 

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