Machine Learning Flowability Prediction: What Constituent-Property Models Can and Can’t Replace

A Pharmaceutical Research study trained Random Forest and XGBoost classifiers on particle size, shape, surface energy, and silica dry-coating data to predict powder blend flowability category. The accuracy holds up as a screening tool and breaks down in specific, predictable places.

Material Characterization with AI-Assisted Analytics

AI-assisted material characterization speeds testing, strengthens models, and [...]

Tribological Powder Properties: Friction, Wear, and Lubrication

Tribology, the study of friction, wear, and lubrication, [...]

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