🧪 Formulation Time Machine

Predictive Kinetic Modeling for Dermatological Stability

The Formulation Time Machine is a computational tool designed to simulate the shelf-life and molecular integrity of L-Ascorbic Acid (Vitamin C) under varying thermal conditions. By blending the Arrhenius Equation with First-Order Kinetics, this app provides formulators with a "Digital Twin" to stress-test their antioxidant networks.

🚀 Live Demo

View the Live Web App on Streamlit

🧬 Scientific Methodology

1. Thermal Acceleration

The engine utilizes the Arrhenius-derived $Q_{10}$ coefficient to model thermal stress. For every 10°C increase in storage temperature, the reaction rate effectively doubles: $$k = A e^{-E_a / RT} \approx 2^{\frac{T_{storage} - 25}{10}}$$

2. Degradation Kinetics

Molecular decay is modeled as a pseudo-first-order reaction, where integrity ($C$) is a function of time ($t$) and the specific decay constant ($k$): $$C(t) = C_0 e^{-kt}$$

3. Synergistic Stabilization

The model accounts for Antioxidant Cascades. By introducing Ferulic Acid as a stabilizer, the engine reduces the effective reactivity of the system, simulating the "regeneration" of Vitamin C molecules.

📂 Project Architecture

• app.py: The main Streamlit dashboard.
• engine/: Simulation and visualization logic.
• data/: Chemical constant database.

👨‍🔬 Author

Shehan Makani