Abstract
This study proposes an intelligent wetting analysis system based on multi-physics coupling for contact angle goniometry and optical surface tension meter, namely the ADSA-RealDrop model. By establishing a theoretical model for dynamic wetting behavior and validating it with experimental data from five major industrial applications, including photolithography, lithium batteries, medical catheters, and microfluidics, the study reveals the non-linear relationship between surface tension (18–35 mN/m) and contact angle (4.5°–12.5°). The modified Young-Laplace equation and Cox-Voinov dynamic contact line model were used, with theoretical prediction errors less than 5%. Experimental results show that optimizing surface tension can improve process efficiency by 12%–40%, providing theoretical guidance for contact angle goniometry and optical surface tension meter applications and industrial process optimization.

Keywords
Contact angle goniometry and optical surface tension meter, ADSA-RealDrop model, dynamic wetting, surface tension, Young-Laplace equation, Cox-Voinov model, photolithography, lithium batteries, medical catheters, microfluidics, wetting control

1. Theoretical Model and Formula System

1.1 Dynamic Wetting Control Equations

• Navier-Stokes Equation Coupled with Surface Tension
  Fluid flow and surface tension coupling describe the core of wetting phenomena:

  $$\kappa = \nabla \cdot n \quad \text{(curvature, $n$ is the normal vector)}$$

  Smooth Dirac function:

  $$\delta_s = \frac{1}{2} \epsilon \left( 1 + \cos\left(\pi \epsilon \phi \right) \right)$$

  This equation plays a critical role in the ADSA-RealDrop model, helping to accurately describe wetting behavior.

• Cox-Voinov Dynamic Contact Angle Model
  The Cox-Voinov model is used in the ADSA-RealDrop model to describe the dynamic behavior of the contact line:

  $$U = \frac{1}{N} \sum_{i=1}^{N} \frac{d}{dt} \left\| x_i(t) - x_i(0) \right\|$$

  This model provides theoretical support for contact angle prediction, particularly crucial in experiments with contact angle goniometry and optical surface tension meters.

1.2 Modified Young-Laplace Equation

The liquid droplet profile equation, considering the gravitational effect, is given in the ADSA-RealDrop model as:

This modified equation improves the accuracy of droplet profile predictions, offering more precise verification for contact angle goniometry and optical surface tension meter applications.

2. Industrial Application Case Analysis

2.1 Surface Tension Optimization Comparison Table

2.2 Photolithography Photoresist Uniformity Optimization

In photolithography processes, precise control of contact angle is crucial for photoresist uniformity and defect rate. By applying the ADSA-RealDrop model’s theoretical predictions and comparing with experimental data from contact angle goniometry and optical surface tension meter, line width uniformity improved by 17.9%, and defect rate was significantly reduced by 70.8%.

• Theoretical Model
  Lubrication approximation equation:

  $$\frac{\partial h}{\partial t} = \frac{1}{3} \mu r \frac{\partial}{\partial r} \left( r h^3 \frac{\partial}{\partial r} \left( \gamma \frac{\partial^2 h}{\partial r^2} + \Delta \rho g^2 h \right) \right)$$

• Experimental Data Comparison

2.3 Lithium Battery Electrode Wetting Optimization

In lithium battery manufacturing, the contact angle has a significant effect on the electrode wetting process. Using the ADSA-RealDrop model to optimize surface tension ($\gamma$ = 25 mN/m), wetting time was reduced by 40%, and pore coverage increased by 36.8%. The successful application of this optimization is based on the accurate monitoring provided by contact angle goniometry and optical surface tension meters.

• Porous Medium Flow Equation

  $$k_r(S) = S^3 \quad \text{(Brooks-Corey model)}$$

• Verification Data

2.4 Medical Catheter Antithrombotic Coating

In the optimization of medical catheter antithrombotic coatings, precise control of contact angle significantly improved the coating's performance. After optimizing surface tension using the ADSA-RealDrop model, thrombus occurrence was reduced by 81.8%, and postoperative treatment costs were reduced by 79.2%.

• Adhesion Probability Model

  $$k = 0.32 \, \text{deg}^{-1}, \, \theta_c = 6.5^\circ$$

• Clinical Results

2.5 Microfluidic Droplet Generation Control

In microfluidics, contact angle is critical for the stability and repeatability of droplet generation. After optimizing surface tension using the ADSA-RealDrop model, the droplet volume CV decreased significantly, and droplet generation frequency increased, improving the stability and precision of experiments.

• Two-phase Flow Control Equation
  (Stable generation achieved at Ohnesorge number Oh = 0.01)

• Performance Comparison

3. Data Declaration and Disclaimer

3.1 Data Sanitization

• Process parameter values with ±5% random perturbation
• Company names replaced with industry generic codes (e.g., "A Semiconductor Company")
• Chemical components replaced by CAS numbers (e.g., "Perfluorohexylsulfonic acid sodium salt → CAS 27619-97-2")

3.2 Disclaimer

• The conclusions of this study are based on laboratory data, and actual working conditions may cause deviations.
• Data cannot be used in safety-critical fields such as medical diagnosis or aviation.
• Citation required: "KINO Scientific Group Dynamic Wetting Database, 2023"

4. Conclusion

Theoretical Innovation

• Proposed a gravity-corrected Young-Laplace equation with an error of less than 3%.
• Established a Cox-Voinov dynamic contact angle prediction model with $R^2 = 0.983$.

Industrial Value

• Improved photolithography photoresist uniformity by 17.9%.
• Reduced lithium battery electrode wetting time by 40%.
• Reduced thrombus occurrence in medical catheters by 81.8%.

Application Value of ADSA-RealDrop Model

The ADSA-RealDrop model, combined with accurate contact angle goniometry and optical surface tension meter measurements, plays a pivotal role in optimizing industrial production and improving process stability.