Assessment on thermal hazards of reactive chemicals in industry: state of the art and perspectives

Q Sun, L Jiang, M Li, J Sun - Progress in Energy and Combustion Science, 2020 - Elsevier
Thermal hazards of reactive chemicals have been a major concern due to the unceasing
occurrences of fire and explosion accidents in industry. Understanding thermal threats of …

Machine learning and deep learning in chemical health and safety: a systematic review of techniques and applications

Z Jiao, P Hu, H Xu, Q Wang - ACS Chemical Health & Safety, 2020 - ACS Publications
Machine learning (ML) and deep learning (DL) are a subset of artificial intelligence (AI) that
can automatically learn from data and can perform tasks such as predictions and decision …

Thermal stability of metal–organic frameworks (MOFs): Concept, determination, and model prediction using computational chemistry and machine learning

HU Escobar-Hernandez, LM Pérez, P Hu… - Industrial & …, 2022 - ACS Publications
The indubitable rise of metal–organic framework (MOF) technology has opened the potential
for commercialization as alternative materials with a versatile number of applications that …

Prediction of methane hydrate formation conditions in salt water using machine learning algorithms

H Xu, Z Jiao, Z Zhang, M Huffman, Q Wang - Computers & Chemical …, 2021 - Elsevier
Predicting formation conditions of gas hydrates in salt water is important for the management
of hydrate in processes such as flow assurance, deep-water drilling, and hydrate-based …

Predictive modeling on the surface tension and viscosity of ionic liquid-organic solvent mixtures via machine learning

Y Lei, Y Shu, X Liu, X Liu, X Wu, Y Chen - Journal of the Taiwan Institute of …, 2023 - Elsevier
Background a comprehensive collection of reliable open-source data was compiled,
encompassing 3454 data points for surface tension and 28,548 data points for viscosity of IL …

Prediction models for flammability limits of syngas/air mixtures based on machine learning approach

B Su, Y Tan, L Zhang, R Hao, L Liu, Z Luo… - International Journal of …, 2025 - Elsevier
Syngas is a promising hydrogen-containing energy source and industrial feedstock.
However, because of its hydrogen content, syngas is prone to explosion if not handled …

Explosion incidents associated with comprehensive studies on methyl ethyl ketone peroxide under thermal decomposition: A review

L Gong, G Yu, J Li, J Chen, R Chen… - Process Safety …, 2024 - Wiley Online Library
This review gathered and discussed the available results on the thermal hazards, thermal
kinetics, decomposition mechanism, autocatalytic behavior, thermal explosion, deflagration …

Experimental and principal component analysis studies on minimum oxygen concentration of methane explosion

B Su, Z Luo, T Wang, J Zhang, F Cheng - International Journal of Hydrogen …, 2020 - Elsevier
Gas explosion has always been one of the leading disasters in chemical and mining
industries, causing tremendous considerable casualties and property damage. It is very …

SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and …

U Arshad, SAA Taqvi, A Buang, A Awad - Process Safety and …, 2021 - Elsevier
Data-driven models for predicting fire and explosion-related properties have been improved
greatly in recent years using machine-learning algorithms. However, choosing the best …

Modelling of the minimum ignition temperature (MIT) of corn dust using statistical analysis and artificial neural networks based on the synergistic effect of concentration …

U Arshad, SAA Taqvi, A Buang - Process Safety and Environmental …, 2021 - Elsevier
Corn dust is a highly energetic substance and frequently found in the food manufacturing
industries. It not only poses occupational safety hazards such as suffocation or lung …