Cold Spray Data is a curated repository of experimental and simulation data on cold spray which is a solid-state deposition process in which metallic or composite particles are accelerated to supersonic velocities and bonded to a substrate upon impact without melting.

The database aggregates data from laboratory experiments, numerical simulations (e.g., FEM, SPH, MD), and literature sources, capturing a wide range of process parameters (gas pressure, temperature, nozzle geometry, standoff distance), feedstock properties (powder morphology, particle size distribution, material composition), and outcome metrics (deposition efficiency, porosity, adhesion strength, hardness, residual stress).

Designed as a versatile resource, the database supports a broad spectrum of downstream tasks including process optimization, surrogate modeling, statistical analysis, and machine learning — enabling data-driven discovery of structure–process–property relationships in cold spray technology.