High-throughput evaluation of hardness dependence on composition and temperature in Ni–Co binary alloy systems

To accelerate the design of multicomponent alloys, it is of key importance predicting required properties and identifying specific compositions from numerous element combinations. Prediction techniques, including theoretical strengthening models, numerical simulations, and machine learning approaches, offer promising avenues for accelerating alloy development. However, achieving high-precision predictions requires large experimental composition–process–structure–property (CPSP) datasets, which demand significant time and effort to acquire. This study introduces a high-throughput evaluation approach for generating composition–process–structure–high-temperature property datasets by combining diffusion couples with high-temperature nanoindentation. Applied to a Ni–Co binary alloy system containing face-centered cubic (fcc) and hexagonal close-packed (hcp) phases, this approach efficiently obtains 1144 data points, capturing the hardness across temperatures from 300 to 773 K and Co concentrations from 2 to 98 at%. These datasets facilitate data-driven analyses of empirical formulas for solid-solution strengthening. Based on a high-temperature yielding model that separates the thermal (Peierls stress) and athermal components, a prediction equation is established for the high-temperature hardness and thermal/athermal components of solid-solution strengthening in the fcc phase of Ni–Co alloys. The temperature dependence of the hardness is divided into thermal and athermal components, which is expressed as a function of the solute concentration, revealing that the thermal component is highly dependent on the Co concentration, whereas the athermal component remains nearly independent. These findings indicate that solid-solution strengthening in Ni–Co alloys is primarily governed by thermal activation within a short-range stress field across all composition ranges. • High-throughput method using diffusion couples and nanoindentation. • Large datasets for composition–process–structure–high-temperature property obtained. • Prediction equation proposed for solid-solution strengthening in Ni-Co alloys. • Strengthening analysis as a function of solute concentration and temperature. • Thermal and athermal components determined using the prediction equation.