Predicting flammability-leading properties for liquid aerosol safety via machine learning

Development of novel combustion risk index for flammable liquids based on unsupervised clustering algorithms

(2021) Chenxi Ji et al.   JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES

Development of Flammable Dispersion Quantitative Property–Consequence Relationship Models Using Extreme Gradient Boosting

(2020) Zeren Jiao et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

A Quantitative Structure Activity Relationship Model for Predicting Minimum Ignition Energy of Organic Substance

(2020) Hsu-Fang Chen et al.   JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES

Development of machine learning based prediction models for hazardous properties of chemical mixtures

(2020) Zeren Jiao et al.   JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES

A data-driven study of IMO compliant fuel emissions with consideration of black carbon aerosols

(2020) Chenxi Ji et al.   OCEAN ENGINEERING

A review of aerosol flammability and explosion related incidents, standards, studies, and risk analysis

(2020) Shuai Yuan et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Experimental and thermodynamic study of aerosol explosions in a 36 L apparatus

(2019) Shuai Yuan et al.   FUEL

Review of recent developments of quantitative structure-property relationship models on fire and explosion-related properties

(2019) Zeren Jiao et al.   PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

Accelerated Design of Catalytic Water-Cleaning Nanomotors via Machine Learning

(2019) Minxiang Zeng et al.   ACS Applied Materials & Interfaces

Liquid flammability ratings predicted by machine learning considering aerosolization

(2019) Shuai Yuan et al.   JOURNAL OF HAZARDOUS MATERIALS

Mordred: a molecular descriptor calculator

(2018) Hirotomo Moriwaki et al.   Journal of Cheminformatics

Prediction of upper flammability limits for fuel mixtures using quantitative structure–property relationship models

(2018) Beibei Wang et al.   CHEMICAL ENGINEERING COMMUNICATIONS

Gibbs energy additivity approaches to QSPR in modeling of high pressure density and kinematic viscosity of FAME and biodiesel

(2017) Thinnaphop Chum-in et al.   FUEL PROCESSING TECHNOLOGY

Prediction of Minimum Ignition Energy from Molecular Structure Using Quantitative Structure–Property Relationship (QSPR) Models

(2016) Beibei Wang et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Can we treat ab initio atomic charges and bond orders as conformation-independent electronic structure descriptors?

(2016) T. Yu. Nikolaienko et al.   RSC Advances

A Comparative Study of Conditional Moment Closure Modelling for Ignition of iso-octane and n-heptane in Thermally Stratified Mixtures

(2015) Fatemeh Salehi et al.   FLOW TURBULENCE AND COMBUSTION

Extreme Learning Machine for Regression and Multiclass Classification

(2011) Guang-Bin Huang et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS

Advantages of support vector machine in QSPR studies for predicting auto-ignition temperatures of organic compounds

(2008) Yong Pan et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Applying a QSPR correlation to the prediction of surface tensions of ionic liquids

(2008) Ramesh L. Gardas et al.   FLUID PHASE EQUILIBRIA