This pipeline provides a complete solution for analyzing MD trajectories and visualizing the free energy landscape through principal component analysis (PCA) and free energy surface (FES) generation.

This project analyzes sales data to identify patterns, trends, and seasonal effects. It also builds a forecasting model to predict future sales using machine learning techniques.

Reinforcing soft aluminum alloys with hard ceramic particles leads to aluminum metal matrix composites (AMMCs), which exhibit superior mechanical, thermal, and tribological properties. These ...

Optimization of lipase production by Enterobacter aerogenes was carried out using response surface methodology (RSM) where the statistical model was obtained by fractional factorial central composite ...