Electrocatalysis is transitioning from catalyst discovery toward device-relevant operation, where meaningful benchmarking demands high current densities, extended durations, and realistic architectures such as membranes, gas diffusion electrodes (GDEs), and flow cells. In this regime, a fundamental measurement mismatch becomes dominant: the electrical variables we control (applied potential or current) are not necessarily those experienced at the catalytic interface. Significant, and often time-dependent, voltage losses arise outside the electrode surface, most notably through uncompensated solution resistance (IR drop). These losses can drift during operation, obscuring intrinsic activity and selectivity trends, distorting integrated charges and Faradaic efficiencies, and undermining reproducibility across experiments and laboratories.

We argue that robust electrolyser experimentation requires a shift in instrumentation philosophy—from traditional single–working-electrode-centric control toward electrolyser-native observability combined with closed-loop stabilisation. The first step in this transition is reliable IR compensation under high-current conditions [1]. We present a fully software-based strategy that achieves effectively 100% dynamic IR compensation using commercially available potentiostats. The method continuously determines high-frequency resistance and instantaneous DC current, and adaptively updates the applied setpoint such that the IR-corrected electrode potential remains constant throughout electrolysis.

A key advantage of this approach is its intrinsic stability under dynamically evolving conditions. In practical systems, resistance often decreases over time due to factors such as Joule heating, electrolyte redistribution, or the emergence of multiphase flow. These conditions are precisely where conventional analogue positive-feedback compensation becomes unstable, forcing users to under-compensate and accept systematic error. In contrast, our digital control strategy remains oscillation-free across such regimes, enabling accurate potential control even under strong drift.

We demonstrate the impact of this methodology in nitrate-to-ammonia electrolysis at high current density. Under conventional static partial compensation, apparent currents and inferred selectivities exhibit artefacts that can lead to erroneous mechanistic conclusions. By contrast, adaptive IR compensation stabilises operation and provides reliable potential-dependent performance metrics, directly linking observed activity to the true interfacial driving force. This establishes dynamic IR control not merely as a technical refinement, but as a prerequisite for quantitative electrocatalysis under industrially relevant conditions.

While adaptive IR compensation addresses the limitations of single-electrode measurements, practical electrolysers are inherently multi-domain systems in which cathode, separator, and anode jointly determine efficiency, stability, and failure modes. The next stage of the proposed roadmap is therefore multi-nodal electrometry: the simultaneous measurement of cathode and anode potentials relative to local reference electrodes, together with separator-associated losses and full-cell voltage. This approach enables real-time partitioning of voltage contributions, revealing where energy is dissipated as operating conditions evolve, and providing a foundation for diagnosing performance bottlenecks across the device.

Building on this enhanced observability, we outline a concept for electrolyser-centric control instrumentation that operates directly in system-relevant modes. Beyond conventional constant-current or constant-voltage control, such platforms should enable constraints aligned with practical operation, including constant-power regulation and adaptive setpoints under changing resistance or mass transport conditions. 

A further enabling component is the integration of bias-under-load, frequency-aware diagnostics into the control framework. By superimposing controlled AC perturbations—including multi-tone signals—onto the DC operating point, it becomes possible to extract impedance-informed signatures in real time during electrolysis. These dynamic measurements allow early detection of evolving transport limitations, interfacial degradation, or separator failure. 

Together, these elements define a pathway toward quantitatively reliable, system-aware electrocatalysis, bridging the gap between laboratory measurements and scalable electrochemical technologies.