Proton exchange membrane water electrolyzers (PEMWEs) coupled with renewable energy resources are considered to be a key technology for producing green hydrogen. However, the high current density PEMWE operation features remarkable voltage losses. A significant part of these losses is due to the mass transport resistance in the PEMWE. Even though the importance of mass transport resistance is widely recognized, it is still poorly understood. Currently, the two-phase transport through the anode porous transport layer (PTL) and catalyst layer is considered to be the main cause of the mass transport losses. In this work, a dynamic macroscopic mathematical model, coupling electrochemical reaction with mass transport through the PTL and flow channels, has been developed to study the two-phase flow in the PTL and mass transport losses of a PEMWE. The influence of the current density, inlet water flow rate, PTL structural parameters, and capillary pressure curve was evaluated. The existence of the critical current density was observed, as well as its dependence on the operating parameters and PTL structure. Even though the results show that the PTL structure has a significant influence on the PEMWE performance, they indicate that a better mathematical description of the two-phase flow in the PTL is necessary.

The dynamic optimization of promising forced periodic processes has always been limited by time-consuming and expensive numerical calculations. The Nonlinear Frequency Response (NFR) method removes these limitations by providing excellent estimates of any process performance criteria of interest. Recently, the NFR method evolved to the computer-aided NFR method (cNFR) through a user-friendly software application for the automatic derivation of the functions necessary to estimate process improvement. By combining the cNFR method with standard multi-objective optimization (MOO) techniques, we developed a unique cNFR–MOO methodology for the optimization of periodic operations in the frequency domain. Since the objective functions are defined with entirely algebraic expressions, the dynamic optimization of forced periodic operations is extraordinarily fast. All optimization parameters, i.e., the steady-state point and the forcing parameters (frequency, amplitudes, and phase difference), are determined rapidly in one step. This gives the ability to find an optimal periodic operation around a sub-optimal steady-state point. The cNFR–MOO methodology was applied to two examples and is shown as an efficient and powerful tool for finding the best forced periodic operation. In both examples, the cNFR–MOO methodology gave conditions that could greatly enhance a process that is normally operated in a steady state.

The effect of forced periodic modulation of several input parameters on the rate of photocatalytic decomposition of formic acid over a TiO₂ thin film catalyst has been investigated in a continuously stirred tank reactor. The kinetic model was adopted based on the literature and it includes acid adsorption, desorption steps, the formation of photocatalytic active sites and decomposition of the adsorbed species over the active titania sites. A reactor model was developed that describes mass balances of reactive species. The analysis of the reactor was performed with a computer-aided nonlinear frequency response method. Initially, the effect of amplitude and frequency of four input parameters (flowrate, acid concentration, temperature and light intensity) were studied. All single inputs provided only a minor improvement, which did not exceed 4%. However, a modulation of two input parameters, inlet flowrate and the acid molar fraction, considerably improved the acid conversion from 80 to 96%. This is equivalent to a factor of two increase in residence time at steady-state operation at the same temperature and acid concentration.

The intensification of an electrochemical process by forced periodic operation was studied for the first time using the computer-aided Nonlinear Frequency Response method. This method enabled the automatic generation of frequency response functions and the DC components (Faradaic rectification) of the cost (overpotential) and benefit (current density) indicators. The case study, oxygen reduction reaction, was investigated both experimentally and theoretically. The results of the cost–benefit indicator analysis show that forced periodic change of electrode potential can be superior when compared to the steady-state regime for specific operational parameters. When the electrode rotation rate is changed periodically, the process will always deteriorate as the dynamic operation will inevitably lead to the thickening of the diffusion layer. This phenomenon is explained both from a mathematical and a physical point of view.

The direct electrochemical reduction of nicotinamide adenine dinucleotide (NAD⁺) results in various products, complicating the regeneration of the crucial 1,4‐NADH cofactor for enzymatic reactions. Previous research primarily focused on steady–state polarization to examine potential impacts on product selectivity. However, this study explores the influence of dynamic conditions on the selectivity of NAD⁺ reduction products by comparing two dynamic profiles with steady‐state conditions. Our findings reveal that the main products, including 1,4‐NADH, several dimers, and ADP‐ribose, remained consistent across all conditions. A minor by–product, 1,6‐NADH, was also identified. The product distribution varied depending on the experimental conditions (steady state vs. dynamic) and the concentration of NAD⁺, with higher concentrations and overpotentials promoting dimerization. The optimal yield of 1,4‐NADH was achieved under steady–state conditions with low overpotential and NAD⁺ concentrations. While dynamic conditions enhanced the 1,4‐NADH yield at shorter reaction times, they also resulted in a significant amount of unidentified products. Furthermore, this study assessed the potential of using pulsed electrochemical regeneration of 1,4‐NADH with enoate reductase (XenB) for cyclohexenone reduction.