ABSTRACT Achieving predictable and reproducible outcomes is a central challenge across synthetic workflows. Design of Experiments (DoE) offers a structured, multivariate framework for exploring complex parameter spaces, yet its wider adoption has been limited by statistical complexity, licensing costs, and steep learning curves. To address these barriers, we introduce DoEIY.app, an open‐access web application that streamlines the experimental design process. The software supports guided design generation, data entry and analysis, and interactive model exploration through an intuitive interface. We illustrate its use in two case studies on gold nanoparticle synthesis, focusing on minimizing size dispersity and controlling mean particle diameter. These examples demonstrate how DoEIY.app enables efficient, reproducible process optimization and highlight its potential to democratize DoE implementation across a broad range of scientific domains.
Fhionnlaoich et al. (2026) studied this question.