Inferred edges come from two machine sources: sweeps of open repository
metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is
labelled with the one it came from. Neither is a complete citation index — absence here is not
evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
A comprehensive review on mechanical, electromagnetic radiation shielding, and thermal conductivity of fibers/inorganic fillers reinforced hybrid polymer composites
Mechanism of biochar soil pore–gas–water interaction: gas properties of biochar-amended sandy soil at different degrees of compaction using KNN modeling
Predictive modelling of fracture behaviour in silica-filled polymer composite subjected to impact with varying loading rates using artificial neural network
Effect of pH, Volatile Content, and Pyrolysis Conditions on Surface Area and O/C and H/C Ratios of Biochar: Towards Understanding Performance of Biochar Using Simplified Approach
Modeling and Optimization of Alumina Filler-Enhanced Epoxy/Mulberry Fiber Composites Using Stacked Ensemble Modeling and Multi-objective Moth Swarm Algorithm
On quantifying uncertainty in lightning strike damage of composite laminates: A hybrid stochastic framework of coupled transient thermal-electrical simulations
Prediction of microstructural-dependent mechanical properties, progressive damage, and stress distribution from X-ray computed tomography scans using a deep learning workflow
Uncertainty quantification of residual strength post lightning strike: A coupled stochastic thermal–electrical–mechanical simulation framework for composite laminates
Bayesian uncertainty quantification of residual mechanical properties post lightning strike: Stochastic multi-physical simulations of composite laminates including spatially-random void distribution
Analysis of the thermal degradation of Recycled Saudi Coffee and PLA biopolymer blends: Experimentation, kinetics, thermodynamics, and convolutional deep neural networks
Deep learning for predicting partition-level homogenized properties for printed circuit board thermo-mechanical simulation: Edge-density-guided training-set design and cyclic training
Interpretable Multimodal Machine Learning for Sustainable Electret Materials: Deciphering Process-Structure-Property Relationships in PLA Melt-Blown Nonwovens via Integrated CNN and CatBoost
Thermal Degradation of Palm Fronds/Polypropylene Bio-Composites: Thermo-Kinetics and Convolutional-Deep Neural Networks Techniques
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.