Surface wettability is a key interfacial property in many engineering applications, including thermal protection and anti-icing in aerospace systems, flow control and heat-transfer enhancement in microchannel reactors, and surface functionalization in biomedical and microfluidic devices. Despite its importance, the teaching of surface wettability in materials science and engineering still primarily emphasizes macroscopic observations, such as static contact-angle measurements, while giving limited attention to the microscopic mechanisms that govern hydrophilicity and hydrophobicity. This gap prevents students from developing a coherent understanding of how molecular-scale interactions and surface energy translate into macroscopic wetting behavior. This study aims to develop a micro–macro-coupled teaching framework that integrates molecular dynamics (MD) simulations with experimental surface modification. This integration bridges frontier research methods with traditional laboratory teaching and strengthens students’ multiscale understanding of surface wettability.

The pedagogical design consists of two complementary modules: a computational simulation module and a physical experimental module, following a “virtual–real combination” strategy. In the simulation component, students utilize MD software to model the wetting behavior of water nanodroplets on solid substrates. The curriculum guides students through the construction of simulation boxes containing solid atoms, representing metal or silicon plates, and water molecules. Students learn to define interatomic potentials, such as the Lennard–Jones potential for van der Waals forces and Coulombic interactions for electrostatic forces. By systematically adjusting the interaction parameters between the fluid and solid atoms, students simulate surfaces with varying surface energies. The process includes system equilibration under a specific thermodynamic ensemble, such as the canonical ensemble, followed by analysis of density profiles to calculate microscopic contact angles. In parallel, the experimental module focuses on macroscopic verification. Students prepare flat plate samples and apply different surface modification techniques to alter their wettability. The static contact angles of droplets on these modified surfaces are measured using a standard optical contact angle goniometer via the sessile drop method. Furthermore, the experiment includes measurements of the thermal conductivity of the plates, allowing students to investigate how surface characteristics influence heat transfer performance.

MD simulations visually demonstrate wetting phenomena at the atomic scale. The simulations show that the microscopic contact angle depends strongly on the solid–liquid interaction strength. Increasing the interaction strength decreases the contact angle and enhances hydrophilicity. Droplet morphology also varies with surface microstructure. Hydrophobic conical structures promote droplet fragmentation, whereas hydrophilic conical structures attract water molecules. Furthermore, changes in wettability alter the measured thermal conductivity of the modified plates, highlighting the coupling between interfacial properties and heat-transfer performance. Comparative analysis of the simulation and experimental results reveals consistent trends between the two approaches.

This study presents a micro–macro coupled experimental teaching framework for surface wettability analysis by integrating MD simulations with surface modification and characterization experiments. The proposed approach overcomes the limitations of traditional single-scale experimental teaching and provides an intuitive, reliable, and easy-to-operate learning platform. It enables students to systematically understand hydrophilicity and hydrophobicity from both microscopic and macroscopic perspectives while fostering critical thinking regarding the discrepancies between idealized theoretical models and real engineering systems. This framework presents a novel methodology for experimental education in materials science and serves as a model for incorporating advanced computational techniques into modern laboratory curricula.