Chemical and Biomolecular Engineering

As research and industrial interest in anion-exchange membrane water electrolysis (AEMWE) grows, there is an increasing need for reliable baselines and cross-lab validation of results. The wide variety of material sets and operating conditions under consideration for AEMWE has thus far limited efforts for standardization. In this study, round-robin testing was conducted in deionized water and KOH-based supporting electrolyte by 5 institutions from academia, national laboratories, and industry to provide baseline performance data and identify sources of cross-lab variability. Baseline membrane electrode assemblies were fabricated with commercial catalysts, membranes, and transport layers using standard techniques and tested using reagent-grade electrolytes, aiming for accessibility rather than state-of-the-art performance. From all tests, the average voltage at 1 A/cm2 was 2.72 ± 0.17 V and 1.87 ± 0.03 V in deionized water and 0.1 M KOH, respectively. The maximum in-house and cross-lab variations at this current density were 118 mV and 476 mV in water and 60 and 88 mV in 0.1 M KOH. The KOH purity, station contamination, and temperature control were identified as possible factors affecting performance between labs, with in-house specific variation attributed to sample-to-sample differences in fabrication, cell assembly, and station contamination. This work provides a commercial baseline for the field and highlights the need for improved standardization and reproducibility in AEMWE research.

Directed ion transport in liquid electrolyte solutions underlies many phenomena in natural and industrial settings. While nature has evolved structures that drive continuous ion flow without Faradaic redox reactions, establishing this process in synthetic systems has been challenging. Here we report an ion pump that drives aqueous ions against a force using a capacitive ratchet mechanism independent of redox reactions. Modulation of an electric potential between thin metallic layers on either face of a nanoporous alumina wafer immersed in solution results in persistent voltages and ionic currents. This occurs due to the nonlinear capacitive nature of electric double layers, whose repeated charging and discharging sustains a continuous ion flux. Using this approach, we demonstrate ratchet-driven electrodialysis that reaches a 50% decrease in the conductivity of the solution in a dilution cell. These ratchet-based ion pumps can enable continuous desalination and selective ion separation using an electrically powered device with no moving parts.

Of the various water electrolyzer technologies, the proton exchange membrane electrolyzer (PEMWE) is one of the best solutions for producing clean hydrogen without releasing CO2. In order to allow for widespread use of clean hydrogen, it is necessary to decrease its cost, which is intrinsically related to system operation. Current PEMWE plants operate in differential mode, directly pressurizing hydrogen and benefiting from thermodynamic compression, which increases overall system efficiency. However, high differential pressure above 30 bar can cause membrane stress, resulting in membrane creeping and failure. Pressurizing the water and operating at balanced pressure allows hydrogen to be produced at higher pressures while preserving the integrity of the membrane and porous layers. Nevertheless, the impact of pressurizing water on PEMWE performance must be better understood to maximize performance under balanced pressure conditions. This study examined the impact of water pressure on two-phase flow. A high-pressure electrolyzer setup was developed to perform operando X-ray radiography and examine oxygen transport with high temporal resolution. The imaging segmentation process, developed to capture bubble properties in the channel, was applied to a specific experiment. The results clearly showed that as pressure increased up to 30 bars, the initial bubbly flow transitioned to slug flow, which led to channel saturation with oxygen. This work demonstrates that two-phase flow in an electrolyzer can be studied using X-ray radiography, which has the advantages of fast measurements and the ability to probe dense materials, such as those required for pressurized electrolyzers.

Interfacial proton-coupled electron transfer (I-PCET) is typically viewed as a single elementary reaction despite general recognition that analogous solution-phase reactivity requires proton donor-acceptor pre-association. Herein, we examine the role of pre-association in I-PCET to a graphite-conjugated carboxylic acid (GC-COOH) surface by quantifying electrolyte pH and I-PCET kinetics as a function of NaClO4 concentrations up to 17 mol kg−1. In acidic and acetate-buffered media, we observed attenuations in the I-PCET rate relative to those expected given the solution pH. To account for the influence of electrolyte concentration on I-PCET rate, we propose a multiple-step model wherein the exchange of interfacial Na+ for H3O+ to form a hydrogen-bonded pre-association complex precedes rate-limiting concerted proton-electron transfer. In this model, the increased electrolyte concentration inhibits H3O+ pre-association, a phenomenon that is recovered in molecular dynamics simulations. These studies demonstrate the non-innocence of supporting electrolyte and expose the key role that pre-association equilibria play in I-PCET mechanisms.

The development of automated experimental facilities and the digitization of experimental data have introduced numerous opportunities to radically advance chemical laboratories. As many laboratory tasks involve predicting and understanding previously unknown chemical relationships, machine learning (ML) approaches trained on experimental data can substantially accelerate the conventional design-build-test-learn process. This outlook article aims to help chemists understand and begin to adopt ML predictive models for a variety of laboratory tasks, including experimental design, synthesis optimization, and materials characterization. Furthermore, this article introduces how artificial intelligence (AI) agents based on large language models can help researchers acquire background knowledge in chemical or data science and accelerate various aspects of the discovery process. We present three case studies in distinct areas to illustrate how ML models and AI agents can be leveraged to reduce time-consuming experiments and manual data analysis. Finally, we highlight existing challenges that require continued synergistic effort from both experimental and computational communities to address.

The expanded backbone chemistries of xeno-nucleic acids (XNAs) hold significant promise for emerging areas of synthetic biology and nanomaterials, but metal-mediated XNA interactions remain largely unexplored. Here, we use a combination of circular dichroism spectroscopy and mass spectrometry to show that XNAs can form Ag+-mediated duplex structures resembling their DNA counterparts. XNAs with a range of different backbone compositions are found to stabilize photoluminescent silver nanoclusters with spectral properties that can be tuned based on their respective backbone chemistry. The resistance of silver nanoclusters to nuclease digestion is also compared for DNA and XNAs. These results show that XNA backbone chemistry provides a new tool beyond nucleobase sequence for controlling and expanding the properties of nucleic acid-stabilized silver nanoclusters and metal-mediated DNA duplexes.

A systematic catalyst loading study reveals the higher catalytic activity of amorphous iridium oxide arises from bulk participation via suggested electrochemical descriptors, while identifying loading-independent intrinsic electrochemical properties. Proton exchange membrane water electrolyzers (PEMWEs) are promising zero-emission technologies. However, their high cost remains a barrier to widespread adoption. Iridium oxide is commonly used as an oxygen evolution reaction (OER) catalyst, and its cost and scarcity make it essential to reduce its loading while increasing its activity. Evaluation of iridium oxide activity should be carried out in the membrane electrode assembly (MEA) configuration to replicate realistic operating conditions. Herein, we present a comprehensive benchmarking framework to accurately evaluate the amorphous and crystalline iridium oxides at the MEA level. By systematically varying the catalyst loading, this study confirmed that each MEA was utilized uniformly, presenting intrinsic electrochemical properties independent of the loading. Through intrinsic charge density determined by voltammetry, we established two electrochemical descriptors to evaluate catalyst redox reactions. The mass activity was evaluated by correlating current vs. loading, and the slope provides loading-independent mass activity. The effect of the porous transport layer on OER activity was discussed, identifying a ‘background’ current at zero-loading. This study highlights potential pitfalls in MEA-level catalyst screening and underscores the importance of the loading study for reliable results.

In the field of water electrolysis, the proton exchange membrane water electrolyzer (PEMWE) is currently the most advanced technology for producing hydrogen without emitting CO2. Although PEMWE plants are already in operation, further research is needed to improve cell efficiency and reduce the use of rare materials, such as iridium oxide catalysts for the oxygen evolution reaction (OER). One of the main causes of performance loss in PEMWE is the relatively low electric conductivity of the porous transport layer (PTL) and of the anode catalyst layer, which results in ohmic losses and low catalyst utilization during high current density operation. The objective of this study is to investigate how optimization of the PTL and electrode interface can increase the cell performance. To this end, we tested different cell assemblies using fibrous and sintered PTLs, decreasing membrane thickness, reducing iridium loading, and inserting a microporous layer to increase contact surface area. Electrochemical characterization of each cell configuration was systematically performed at various compression levels as the pressure is a crucial parameter influencing the electrode/PTL contact area. In parallel, X-ray microcomputed tomography (micro-CT) was employed to investigate the effects of cell hydration and compression on the structure of PEMWE components. This study combining electrochemistry and micro-CT imaging presents how optimizing the electrode/PTL contact surface area, minimizes ohmic losses, and enables PEMWE operation with low iridium loading at high current densities.

Recent experiments [ Romolini ; Small Structures 2025, 2500022 ] uncovered the crystallographic structure of a near-infrared (NIR) emitting DNA-stabilized silver nanocluster, DNA2Ag28Cl2, which has two chloridos bound to the silver core. Here, we study the role of the halido in the cluster’s photophysical properties by replacing X = Cl with X = Br, I, H2O, or OH in a computational model for density functional theory (DFT) calculations. The calculations predict a systematic red shift of the NIR absorption and enhancement of a negative circular dichroism (CD) signal in the range of 810–860 nm when Cl, Br, and I are used as halide ligands, respectively. Leaving the two halido sites empty but coordinated by water molecules blue-shifts the linear absorption and CD signal from 810 nm and dramatically switches the CD sign. The explanations for this behavior are found by a detailed analysis of the electronic structure and the impact of the X ligands to the frontier orbitals. We directly verify the DFT predictions experimentally in the case of X = Br by performing a series of experiments with a controlled Cl-to-Br exchange. These findings demonstrate the importance of the halide ligands in controlling the near-infrared optical and chiroptical response of DNA-stabilized silver nanoclusters.

ABSTRACT Near‐infrared (NIR) emitters with chiroptical properties are a novel class of materials with significant promise for chiral sensing and optoelectronic applications. Chiral nanoparticles, in particular, offer distinct advantages over molecular chiral agents. However, their practical applications remain significantly hindered due to challenges to precisely control nanoparticle chirality and reduce heterogeneity. Here, we investigate one‐photon (1P) and two‐photon (2P) chiroptical properties of DNA‐stabilized silver nanoclusters (DNA‐Ag N ) as atomically defined, water‐soluble chiral nanoprobes. We perform a detailed analysis of 1P and 2P circular dichroism (1P‐CD and 2P‐CD, respectively) and circularly polarized luminescence (CPL) of (DNA) 2 [Ag 16 Cl 2 ] 8+ , a NIR emissive DNA‐Ag N with solved crystal structure, over a broad wavelength range. We observe that (DNA) 2 [Ag 16 Cl 2 ] 8+ exhibits 2P‐CD two orders of magnitude higher than 1P anisotropy factor, with additional CD bands in the NIR range. Interestingly, (DNA) 2 [Ag 16 Cl 2 ] 8+ also presents CPL with high anisotropy factors, upon both 1P and 2P excitation, with significant 2P CPL brightness. These findings demonstrate that DNA‐Ag N exhibits significant 1P‐ and 2P‐ excited chiroptical properties, highlighting their potential for chiral sensing and bioimaging at NIR wavelengths in the tissue transparency window.