Review of computer‐aided methods in fat crystallization studies

Abstract

With recent improvements in computer performance, computer‐aided studies have become increasingly important. Computer‐aided methods have been applied in fat crystallization studies for modeling, simulation, optimization, data analysis and visualization. In this paper, various methods, such as molecular dynamic simulation, Monte Carlo, cellular automata modeling, finite element analysis, machine learning and computer vision, are introduced. Applications and advances in mechanism explanation, behavior prediction, process optimization, and so forth, are reviewed for fat crystallization. As a powerful and essential tool, computer‐aided study should play an important role in the field of lipid research in the future.

Machine Learning Methods to Improve Crystallization through the Prediction of Solute–Solvent Interactions

“…The burgeoning field of engineered nanoparticles and crystals for the electronics industry also relies heavily on crystallization, integral in advancing technologies in areas like semi-conductors [7,8] and battery production [9]. Additionally, biotechnology products, such as protein and fat crystals, are gaining prominence due to their applications in drug design and medical research [10,11]. The precise control of crystallization conditions-including temperature, concentration, and pressure-allows these industries to enhance product quality, efficiency, and cost-effectiveness.…”