A review on cone calorimeter for assessment of flame-retarded polymer composites

Y Quan, Z Zhang, RN Tanchak, Q Wang - Journal of Thermal Analysis and …, 2022 - Springer
The cone calorimeter is an efficient instrument used to evaluate the reaction-to-fire
properties of measured materials via simulating a forced combustion bench-scale fire …

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 …

Accelerated design of flame retardant polymeric nanocomposites via machine learning prediction

Z Zhang, Z Jiao, R Shen, P Song… - ACS Applied Engineering …, 2022 - ACS Publications
Improving the flame retardancy of polymeric materials used in engineering applications is an
increasingly important strategy for limiting fire hazards. However, the wide variety of flame …

Finding the right solvent: A novel screening protocol for identifying environmentally friendly and cost-effective options for benzenesulfonamide

P Cysewski, T Jeliński, M Przybyłek - Molecules, 2023 - mdpi.com
This study investigated the solubility of benzenesulfonamide (BSA) as a model compound
using experimental and computational methods. New experimental solubility data were …

A Systematic Review on Intensifications of Artificial Intelligence Assisted Green Solvent Development

H Wen, S Nan, D Wu, Q Sun, Y Tong… - Industrial & …, 2023 - ACS Publications
Solvents are indispensable components of chemical processes, and the application of
ecofriendly, safe, and efficient solvents is vital for building green chemical processes …

[HTML][HTML] Developing risk assessment framework for wildfire in the United States–A deep learning approach to safety and sustainability

P Hu, R Tanchak, Q Wang - Journal of Safety and Sustainability, 2024 - Elsevier
The frequency and intensity of wildfires have significantly increased in the United States
over recent decades, posing profound threats to community safety and ecological …

A perspective on data-driven screening and discovery of polymer membranes for gas separation, from the molecular structure to the industrial performance

E Ricci, MG De Angelis - Reviews in Chemical Engineering, 2023 - degruyter.com
In the portfolio of technologies available for net zero-enabling solutions, such as carbon
capture and low-carbon production of hydrogen, membrane-based gas separation is a …

Machine learning based quantitative consequence prediction models for toxic dispersion casualty

Z Jiao, Z Zhang, S Jung, Q Wang - Journal of Loss Prevention in the …, 2023 - Elsevier
Incidental release of toxic chemicals can pose extreme danger to life in the vicinity.
Therefore, it is crucial for emergency responders, plant operators, and safety professionals …

Dynamic NOx Prediction Model for SCR Denitrification Outlet of Coal-Fired Power Plants Based on Hybrid Data-Driven and Model Ensemble

B An, M Tang, J Qiu, Z Li, W Wang… - Industrial & …, 2023 - ACS Publications
Aiming at the difficulty of accurate modeling of selective catalytic reduction (SCR) systems in
coal-fired power plants, this paper proposes a modeling scheme based on hybrid data …

Biological activity predictions of ligands based on hybrid molecular fingerprinting and ensemble learning

M Li, M Zeng, H Zhang, H Chen, L Guan - ACS omega, 2023 - ACS Publications
The biological activity predictions of ligands are an important research direction, which can
improve the efficiency and success probability of drug screening. However, the traditional …