Ghulam Ishaq Khan Institute of Engineering Sciences and Technology

A Nonlinear Nonisothermal General Rate Model for Bimolecular Reactive Chromatography: A + B ⇌ C + D

Abstract Equilibrium-limited liquid-phase reactions can be intensified by coupling reaction and selective separation within a chromatographic bed, yet the interaction of reversible bimolecular kinetics with particle-scale mass and heat transport remains insufficiently resolved. F...

Comparative evaluation of long-term corona- and environmentally-aged high-temperature vulcanized silicone rubber nano-composites

This study presents an aging evaluation of high-temperature vulcanized silicone rubber nanocomposites subjected to corona-induced deterioration over different durations, as well as their retardation through the incorporation of nanosized fillers to improve high-voltage insulation...

Analytical Solution and Temporal Moments of the Tempered Prabhakar Fractional General Rate Model for Linear Liquid Chromatography

Abstract Intraparticle transport in packed adsorption and chromatography columns is routinely represented by Fickian pore and surface diffusion, yet disordered pore networks and energetically heterogeneous surfaces frequently produce transport with long-lived memory that a single...

Multifunctional TiO₂-modified cement mortar: experimental investigation, machine learning prediction, and life cycle assessment

Abstract TiO₂-modified cement mortar is a multifunctional construction material that enhances both mechanical performance and environmental remediation. This study investigated the photocatalytic activity, compressive strength, machine learning prediction, and life cycle assessme...

A Regression-Based Machine Learning Approach for Rehabilitation of Corroded RC Culverts Strengthened with SMA

Box culverts are critical components of transportation infrastructure, yet their load-carrying capacity is often compromised by reinforcement corrosion and geometric deterioration. This study proposes an integrated finite element (FEM) and machine learning (ML) framework to evalu...