The promotional effect of cations on the CO2 reduction reaction (CO2RR) on Cu is well-established experimentally, yet the underlying mechanism remains debated. This is further complicated by an underexplored factor: in acidic solution, the Cu surface may be covered by a H adlayer rather than being pristine. We employ a multiscale modeling approach to investigate how the H adlayer and electric double layer environment affect CO2RR activity on Cu(100). GC-DFT calculations demonstrate that the H adlayer on Cu lowers the d-band center of Cu, attenuating CO2RR activity and correctly identifying CO2 chemisorption as the rate-limiting step. This H-passivated surface provides a novel lens through which to view the cation effects. Molecular dynamics simulations reveal that the direct Cs+ stabilization of intermediates is a minor effect. More importantly, Cs+ thermodynamically favors the transition to lower H coverage and suppresses H3O+ adsorption on the Cu surface. We thus propose a dual-role mechanism: alkali cations promote CO2RR also by acting as depassivants that reduce H coverage, restoring the catalytic activity of the Cu surface for the CO2RR.

Single-atom catalysts (SACs) have come to the forefront of heterogeneous catalysis, largely built upon the success of an isolated active site model that maximizes metal atom utility and offers excellent catalytic activity. However, the drive toward industrial relevance has spurred synthetic advances that now routinely yield high loadings, pushing SACs into a new high-density regime, where the conventional "isolated site" assumption no longer holds. This Perspective posits that intersite synergy is a tunable emergent property in these systems, shaped by the spatial distance between adjacent active centers. The impacts of site cooperation on heterogeneous catalysis manifest in various forms, including modified linear scaling relationships, alternating reaction pathways, and tunable spin-dependent activities. We conclude by outlining the challenges and opportunities in operando characterization and theoretical modeling of these cooperative catalytic ensembles, charting a course for the next frontier in the study of single-atom catalysis.

Understanding the electrocatalyst–electrolyte interface, including electric double layer (EDL) effects, is critical for CO2 electroreduction (CO2RR). However, modeling the EDL’s full complexity, spanning large spatiotemporal scales (∼10 nm, >100 ps) remains a challenge for conventional simulations. Here, we integrate the grand canonical density functional theory (GC-DFT) with large-scale classical molecular dynamics and free energy perturbation (FEP) methods (30,000+ atoms, ns time scale) to model CO2 reduction to CO on a Ni–N–C/G catalyst under an applied potential of −0.60 VRHE in a 0.5 M KHCO3 electrolyte. The simulations indicate that under these specific conditions, the EDL substantially promotes CO2 adsorption (−0.64 eV) and facilitates the two proton-transfer steps while slightly inhibiting CO desorption. Moreover, the FEP simulation results reveal that the interfacial electric field (EF), rather than cation coordination, is primarily responsible for modulating these reaction energetics. Furthermore, a linear correlation is found between the perpendicular dipole moment change (Δμz) of adsorbed intermediates and the EF-induced free energy shift (ΔGFEP), suggesting a useful descriptor for assessing EDL influences. This work demonstrates the value of a multiscale framework for probing interfacial electrochemical phenomena.

The electrocatalytic reduction of CO₂ to methanol offers a compelling pathway for sustainable fuel synthesis, wherein cations in the electric double layer (EDL) exert a substantial influence on catalytic performance. Although cation modulation of CO₂-to-CO conversion has been extensively documented, its influence on downstream reduction pathways toward CH₃OH has received comparatively little attention. Using multiscale simulation, we establish that methanol synthesis over immobilized cobalt phthalocyanine (CoPc) is kinetically governed by the final proton transfer (*CH₂OH + H₂O → * + CH₃OH + OH⁻). The EDL environment substantially accelerates this rate-determining step (RDS). Moreover, the activity exhibits a clear dependence on cation radius, following the trend Li⁺ > Na⁺ > K⁺ > Cs⁺, with smaller cations systematically lowering the proton transfer barrier. This trend stems from the enhanced accessibility of smaller cations to the transition state, where Li⁺ achieves tighter coordination than Cs⁺, conferring greater electrostatic stabilization and a correspondingly reduced barrier. Conversely, smaller cations attenuate the hydrogen-bond network surrounding OH⁻, potentially impeding OH⁻ transfer from the catalyst surface to the bulk electrolyte. These multifaceted cation effects underscore the complex interplay between kinetic promotion and mass transfer limitations in electrocatalytic systems.

Electrochemical H2O2 production through the two-electron oxygen reduction reaction (2e− ORR) represents a transformative route for sustainable and decentralized chemical synthesis. Nevertheless, conventional catalysts struggle to achieve optimal intermediates adsorption and efficient proton-coupled electron transfer (PCET) under neutral conditions, as the sluggish dissociation of water imposes a severe kinetic bottleneck. Herein, we introduce a lattice hydrogen engineering strategy that confers unprecedented catalytic functionality to traditionally inert metal oxides. Through precise hydrogen implantation into the TiO2 lattice, we establish Ti-O2C-H active centers—a dual-function motif that simultaneously achieves near-ideal OOH* adsorption (positioned at the Sabatier volcano apex) and intrinsic proton reservoir capability. This atomically engineered H-TiO2 catalyst delivers > 95% H2O2 selectivity, operating stably for over 100 h at an industrial current density of 200 mA cm−2. This robust operation yields a high H2O2 production rate of 13,968 mmol g−1 h−1 with an energy efficiency of 41.3%. Crucially, the universality of lattice hydrogen engineering is demonstrated through the activation of WO3, MoO3, and Nb2O5, yielding comparable performance enhancements for neutral 2e− ORR. By unlocking metal oxides as a robust catalyst platform for H2O2 electrosynthesis, this work establishes a scalable pathway toward scalable, green and cost-effective peroxide production. 

Achieving product selectivity in multistep electrocatalysis requires delicately tuning the stability of key reaction intermediates to modulate the energetics of competing pathways. The conversion of CO₂ by cobalt phthalocyanine (CoPc) presents a stark puzzle in this context; while solution-phase CoPc exclusively produces CO, its immobilization on carbon nanotube support triggers a substantial and unusual switch to methanol. Here, using multiscale simulations, we resolve this outstanding puzzle. We demonstrate that the carbon support is not a passive anchor but an active modulator of the catalytic environment. It functions by shielding one face of the CoPc molecule from the aqueous solvent, which substantially lowers the kinetic barrier for protonation while having little effect on CO desorption, thereby activating methanol production. Interfacial electric fields (EF) and cations further enhance this effect. Our findings establish support-induced desolvation as a new, rational design guideline for kinetically steering complex electrocatalytic reactions, providing a clear mechanistic basis for the unique reactivity of heterogenized molecular catalysts.

Industrial dinitrogen (N-2) reduction to ammonia in the Haber-Bosch synthesis is essential for producing fertilizers and, consequently, food. Methods wherein the energy for nitrogen activation is supplied by light could provide more sustainable alternatives to existing ones. The combination of a photosensitizer and a lanthanide catalyst is reported for an effective >2e(-) reduction of N-2 in what is the first transition-metal-free molecular photocatalyst for ammonia synthesis. The lanthanide is Earth-abundant Sm. The reaction proceeds at ambient pressure and temperature, with high turnover numbers (up to 98), with visible light irradiation in aqueous solvent mixtures and even pure water, and it uses an environmentally benign non-metallic sacrificial reductant. Nitrite and nitrate were also efficiently reduced to ammonia. Thus, the first photocatalytic co-reduction of nitrite and bicarbonate to urea using an Sm-based photocatalyst was achieved.

The interplay of cations and anions within the electric double layer (EDL) under an applied potential is crucial for the activity and selectivity of CO2 electroreduction (eCO(2)RR). Yet, first-principles level modeling of the EDL's complex structure on large spatiotemporal scales remains challenge. Here, we combine grand canonical ensemble density functional theory with classical molecular dynamics to investigate ion effects under constant potential. Our simulation revealed a critical yet subtle link between cation and anion effects, uncovering an unexpected mechanism for the known size-dependent cation effects. We found that cation modulation of near-surface anion distribution, rather than direct intermediate stabilization of a *COO- intermediate, is the dominant factor. Larger cations, such as Cs+, more effectively shield anions from the cathode and thereby reduce their inhibition of CO2 adsorption. Our operando-mimicking simulations not only reveal the multiple roles of alkali metal cations in eCO(2)RR through their hydration dynamics and anion shielding effects but also provide insight into their size dependence, guiding the precise modulation of EDL for enhanced eCO(2)RR performance.

Identifying the adsorption states of intermediates in the oxygen evolution reaction (OER) is crucial for revealing the potential-determining step and further optimizing catalytic systems. Infrared (IR) spectroscopy serves as an effective tool for probing oxygen-containing intermediates on electrode surfaces. However, extracting spectral characteristics and establishing a quantitative correlation between these features and the adsorption states of intermediates remains a significant challenge. In this letter, we present a machine learning framework tailored for single-atom catalysts to learn from the infrared spectra of OER intermediates and construct a “spectrum-property” relationship. This enables accurate prediction of the adsorption states, namely adsorption free energy and charge of key intermediates (*OH, *O, and *OOH). Notably, the pretrained model demonstrates efficient transferability across commonly reported single-atom OER systems and provides interpretable attention maps of infrared signals based on vibrational mode analysis. By quantitatively linking spectral features to the adsorption states of oxygen-containing intermediates via machine learning, our framework is expected to provide valuable insights for guiding the optimization of single-atom OER catalysts.

Ascorbic Acid (AA) has been the center of controversial dialogues and studies when it comes to cancer research, though recently it has gained interest as an anti-tumor agent. Here, we present an electroanalytical concept to determine AA based on a new fundamental finding: the reversible interaction of AA with carbon nanotubes (CNTs) under zero-current measurements (potentiometry). This interaction is systemically studied under several experimental conditions, aiming to provide specificity with the combination of a thin film of CNTs with a nanometer-sized plasticized polymeric membrane (ca. 300 nm in thickness). The resulting sensor shows a consistent sensitivity to AA of –33.53 ± 2.57 mV/decade (n = 17), presenting a linear range of response that includes from normal physiological to pharmacological AA concentrations (10–200 μM and 0.2–1 mM, respectively). Importantly, interferences such as uric acid (UA), sodium ion and lactate have a limited influence on the potentiometric response, in contrast to previously published sensors. In addition to the experimental evidence, computational simulations on the interactions of AA and UA with a graphene-based model were performed to provide insights in describing the very distinct experimental responses that were observed. Thus, the formulated hypothesis is supported by both experimental data and simulations, which has not been reported before, to the best of our knowledge. Furthermore, we demonstrate the suitability of the developed sensor for real sample analysis (undiluted human serum, saliva and urine). The significance of the developed sensor is three-fold: 1) analytical performance addressing several applications, 2) enhanced selectivity, specially towards UA, 3) simplicity of the concept in terms of materials and preparation that makes it compatible with micro- and nano-electrodes for further analytical applications never explored until now (e.g., intracellular measurements, nanoelectrochemistry, etc.)