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Abstract Early phases of green material development can be accelerated by identifying driving factors that control material properties to understand potential tradeoffs. Full investigation of fabrication variables is often prohibitively expensive. We propose a pared‐down design of experiments (DOE) approach to identify driving variables in limited data scenarios using tunable polydimethylsiloxane (PDMS) foams made via sacrificial templating as an example system. This new approach systematically determines the dependencies of porosity, transparency, and fluid flow by varying the template particle size and packing while using a more sustainable solvent. Factor screening identified template particle size and packing density as the driving factors for foam performance by controlling pore size and interconnectivity. The framework developed provides a robust, foundational understanding of how to green and tune a novel material's properties using an efficient and effective exploration of the design space. Recommendations for applying this method to a broad suite of experiments are provided. 

Abstract To efficiently design new adsorption systems, industrial scale fixed beds are often scaled down to bench‐top experiments and/or modeled using computational fluid dynamics (CFD). While there has been considerable work exploring adsorption of volatile organics onto activated carbon fixed beds in the literature, this article attempts to reckon with the high variability of adsorption capacities observed at small scales and improve small‐scale experiments for industrial scale reactor design. This study integrates experimental results with CFD simulations, which can explicitly model system heterogeneities and their influence on adsorption by resolving local packing densities and flow paths. Activated carbon physical properties were determined through surface area analysis, proximate analysis, and toluene adsorption (measured via mass spectroscopy). Variability in the small‐scale systems was not attributed to surface area or carbon content, as is often stated, but instead was due to local packing density variations and the heterogeneity of particle size distributions.