The identification and optimization of electrode materials is of great importance in the study of (flow and solid state) batteries, industrial electrocatalysis and analytical devices such as sensors. To identify useful materials from a virtually unbound set of metals, alloys and semiconductors, high-throughput techniques are of vital importance. In this paper we present a high-throughput setup that consists of 64 parallel plate electrochemical flow cells, with the anode and cathode compartments separated by a membrane. These cells can be operated sequentially or batch-wise in parallel, using a matrix-addressing approach that allows for scaling up to larger electrode matrices with minimal instrumentation cost. The setup was validated for the preparation and screening of electrode materials under hydrodynamic conditions at industrially relevant current densities, which showed that it could be used to identify optimal catalysts and the robustness of catalyst preparation. The results of the small scale experiments followed theoretical predictions and were used to optimize larger scale experiments.