Exploring advanced materials: Harnessing the synergy of inverse gas chromatography and artificial vision intelligence

PK Basivi, T Hamieh, V Kakani, VR Pasupuleti… - TrAC Trends in …, 2024 - Elsevier
Inverse gas chromatography (IGC) has emerged as a highly sensitive, adaptable, and
effective technology for material analysis. Through employing thermochemical approaches …

A systematic study of the relationship between the high-frequency dielectric dissipation factor and water adsorption of polyimide films

R Bei, K Chen, Y He, C Li, Z Chi, S Liu, J Xu… - Journal of Materials …, 2023 - pubs.rsc.org
Low dissipation factor (Df) at high-frequencies is crucial for the application of dielectric
materials in next generation mobile communication. However, the relationship between the …

[HTML][HTML] Multi-scale design of MOF-based membrane separation for CO2/CH4 mixture via integration of molecular simulation, machine learning and process modeling …

X Cheng, Y Liao, Z Lei, J Li, X Fan, X Xiao - Journal of Membrane Science, 2023 - Elsevier
Metal-organic framework (MOF) membranes have demonstrated high efficiency for CO 2
capture due to their wide range of pore sizes, high surface area, high porosity, and open …

Advances in data‐assisted high‐throughput computations for material design

D Xu, Q Zhang, X Huo, Y Wang… - Materials Genome …, 2023 - Wiley Online Library
Extensive trial and error in the variable space is the main cause of low efficiency and high
cost in material development. The experimental tasks can be reduced significantly in the …

High-throughput screening and prediction of high modulus of resilience polymers using explainable machine learning

T Yue, J He, L Tao, Y Li - Journal of Chemical Theory and …, 2023 - ACS Publications
The ability to store and release elastic strain energy, as well as mechanical strength, are
crucial factors in both natural and man-made mechanical systems. The modulus of …

PXLink: A simulation program of polymer crosslinking to study of polyamide membrane

C Zhang, G Bu, MSJ Sajib, L Meng, S Xu… - Computer Physics …, 2023 - Elsevier
Crosslinked network polymers have numerous important applications in engineering,
biomedicine, and the environment. Establishing a crosslinked polymer network is an …

Thermal properties and mechanical behavior of functionalized carbon nanotube-filled polypropylene composites using molecular dynamics simulation

Y Guo, D Zhang, X Zhang, Y Wu - Materials Today Communications, 2023 - Elsevier
Polypropylene (PP) is widely recognized as an environmentally friendly material for cable
insulation due to its good insulation performance and environmental friendliness. One …

Machine Learning for Polymer Design to Enhance Pervaporation-Based Organic Recovery

M Yang, JJ Zhu, AL McGaughey… - Environmental …, 2024 - ACS Publications
Pervaporation (PV) is an effective membrane separation process for organic dehydration,
recovery, and upgrading. However, it is crucial to improve membrane materials beyond the …

Machine learning for layer-by-layer nanofiltration membrane performance prediction and polymer candidate exploration

C Wang, L Wang, H Yu, A Soo, Z Wang, S Rajabzadeh… - Chemosphere, 2024 - Elsevier
In this study, machine learning-based models were established for layer-by-layer (LBL)
nanofiltration (NF) membrane performance prediction and polymer candidate exploration …

Machine learning–Driven surface grafting of thin-film composite reverse osmosis (TFC-RO) membrane

A Tayyebi, AS Alshami, E Tayyebi, C Buelke… - Desalination, 2024 - Elsevier
Modifying reverse-osmosis (RO) membrane performance is challenging and time-
consuming due to the complex interplay of various factors that influence the membrane's …