ZnZrO_x solid solution catalysts have gained considerable attention for their effectiveness in CO₂ hydrogenation and the conversion of methanol to C²⁺ products. However, their performance in high-temperature hydrogenation of CO₂ to methanol needs enhancement. In this study, we present a surface engineering approach for these catalysts by thermally treating a ZnZr hydroxide precursor in a reducing atmosphere (H₂/Ar). This method promoted the migration of Zn from the bulk of ZrO₂ to the surface layer, leading to the formation of abundant asymmetric oxygen vacancy (Zn–O_v–Zr) sites. Consequently, the 11.5ZnZr-500H₂/Ar catalyst (treated in H₂/Ar) exhibited a methanol selectivity of 83.0% at 325 °C, which is significantly higher than the 54% selectivity of 11.5ZnZr-500Air (treated in air) at the same temperature and comparable to the 85.1% selectivity of 11.5ZnZr-500Air at 275 °C. By selectively removing Zn at various levels through acid treatment of the catalysts, we have discovered an almost linear correlation between the concentration of asymmetric oxygen vacancies and the yield of methanol production. DRIFTS measurements and DFT calculations demonstrate that these active sites enhance the CO₂ activation and conversion of formate intermediates during the methanol synthesis process. This study is the first to identify the catalytic function of the asymmetric Zn–O_v–Zr sites, paving the way for the subsequent production of C²⁺ products.

The present work focuses on highlighting bimolecular reactions in the NH3 system involving HO2, an important radical at intermediate combustion temperatures. The Reaction Mechanism Generator (RMG) tool was used to identify potentially significant reactions, and the Automated Rate Calculator (ARC) tool was used to automatically compute rate coefficients at the CCSD(T)-F12a/cc-pVTZ-F12//B2PLYP-D3/aug-ccpVTZ level of theory. Several reactions explored in this work, such as N + HO2 <=> NH + O2, NH + HO2 <=> NH2 + O2, NNH + HO2 <=> N2H2 + O2, and HNO2 + HO2 <=> NO2 + H2O2, have not been thoroughly investigated in the existing literature. Notably, the reaction HNO + HO2 <=> HNOH + O2, though known, lacks a precise rate coefficient in recent chemical kinetic models for ammonia. This study provides a computed rate coefficient for this reaction, shedding light on its role in altering the dominant pathway for the conversion of HNOH to HNO and enhancing the overall flux. Reaction rate coefficients computed here may improve future low and intermediate temperature oxidation modeling of NH3.

Polyelectrolyte complexes (PECs) have emerged as a promising platform for new types of nanofiltration (NF) membranes. While water-soluble polyelectrolytes are usually employed, the recently proposed alternative of using amphiphilic ionomers to form an insoluble first layer, subsequently converted to PEC, offers a simpler two-step preparation. This study investigates PEC formation via this route and, specifically, kinetics and stoichiometry of complexation between the anionic ionomer Nafion and the polycations polyallylamine hydrochloride (PAH) and polydiallyldimethylammonium chloride (PDADMAC). Using ATR-FTIR spectroscopy, we analyzed polycations diffusion from solution into Nafion films and resulting PEC stoichiometry. We observed that the apparent polycation diffusivity increases in more concentrated solutions and the observed kinetics does not fit the model of a purely diffusive transport, likely due to PAH electromigration as additional transport mechanism. The kinetics even become non-monotonic at higher solution concentrations and lower pH, which is attributed to structural rearrangement of the Nafion matrix triggered by complexation that occurs alongside PAH transport. In addition, lower PAH uptake was unexpectedly observed at higher pH, despite lower PAH ionization that should require more PAH for intrinsic charge compensation in the PEC. This result is explained by competition between PAH with Na⁺ counterions, resulting in more extrinsic charge compensation in the film. Finally, based on these findings and conditions supposed to ensure complete complexation, thin-film composite PEC membranes were fabricated via a two-step procedure and tested for separation performance. Flux and rejection measurements demonstrate that nanofiltration performance can be effectively tuned by adjusting the polycation-to-ionomer ratio. This work provides mechanistic insights and a methodology for designing and tuning ionomer-based PEC-NF membranes for water purification.

Volatile organic compounds (VOCs) are air pollutants that harm health and contribute to climate change. This paper demonstrates how a portable VOC measuring device, combined with advanced signal processing, effectively characterizes VOC patterns. A novel methodology is introduced, leveraging deep learning to process temporal profiles from nine-channel nano-sensor technology. This is demonstrated through two use cases: VOC-pattern classification between indoor and outdoor environments, and VOC-pattern classification across different geographical settings—rural, urban, and industrial. For the first use case, the best RNN model achieves F-scores of 90.56% for 50-second window classification and 95.90% for exposure classification. In the second use case, it achieves F-scores of 81.76% and 86.53% for the same metrics. The best model is integrated into a GIS for detecting localized pollution hotspots. This low-cost, portable, calibration-free methodology has applications in industrial leak detection, plant health monitoring, and detection of human health issues.

The development of durable, non-platinum electrocatalysts for the hydrogen oxidation reaction (HOR) in alkaline media is a critical challenge in scaling high-efficiency anion-exchange membrane fuel cells (AEMFCs). Also, designing electrocatalysts exhibiting both high activity and structural stability is essential. In this study, we introduce a novel electrocatalyst composed of cerium oxide-decorated palladium nanoparticles supported on carbon (CeOx-Pd/C), synthesized via controlled surface reaction (CSR), to engineer nanostructures with well-defined CeOx–Pd interfaces and tunable Ce/Pd atomic ratios. The selective deposition of CeOx facilitates hydroxide ion spillover and the adsorption/transfer of oxygenated species to Pd, boosting HOR activity and durability. However, despite its promising catalytic properties, the degradation behavior under electrochemical conditions has not been extensively studied. To evaluate this, we employed identical location transmission electron microscopy (IL-TEM) combined with electrochemical accelerated stress testing (AST), to directly visualize nanoscale structural evolution before and after electrochemical cycling. The results reveal the bifunctional nature of CeOx nano-islands: exhibiting record-high HOR activity (51.5 mA/mg) along with promoting protective and degradation-resistant anchoring mechanisms. Also, comprehensive and advanced STEM-EDS and EELS analyses confirm dominant Ce⁴⁺ valence and the intimate Pd–CeOx contact. Particle size analysis and morphological mapping further demonstrate that CeOx nano-islands suppress nanoparticle migration, agglomeration, and structural deformation under electrochemical stress. Our findings establish a robust structure–function–degradation relationship, positioning CeOx–Pd/C as a solution for next-generation AEMFCs. This work not only offers mechanistic insight into catalyst degradation but also introduces an oxide-mediated design strategy for advancing bifunctional electrocatalyst technologies in alkaline energy systems.

The electrochemical impedance spectroscopy (EIS) technique is applied to study the effect of NO_x contamination on polymer electrolyte fuel cells (PEMFCs). The analysis is done by finding the underlying distribution function of relaxation times (DFRT, a.k.a. DRT) utilizing impedance spectroscopy genetic programming (ISGP). NO₂-contaminated PEMFCs generate negative loops (or “inductive loops”, although that term is inaccurate) in the Nyquist plot. ISGP can resolve these loops into negative peaks in the DFRT, i.e., negative effective resistances and capacitances. It has been suggested that these negative resistances are due to competing reactions during the operation. Here we verify that this is a plausible hypothesis by deriving the impedance equation for fuel cells in the presence of NO₂ contamination and then comparing it with the experimental results. The simulated impedance data interpret the causality of the negative loop due to NO₂ contamination in the air stream. Thus, this study helps us understand each involved electrochemical process in a PEMFC and physically interpret the criteria for the emergence of a negative loop upon contamination.

Biological systems maintain stability of their function in spite of external and internal perturbations. An important challenge in studying biological regulation is to identify the control objectives based on empirical data. Very often these objectives are time-varying, and require the regulation system to follow a dynamic set-point. For example, the sleep-wake cycle varies according to the 24 hours solar day, inducing oscillatory dynamics on the regulation set-point; nutrient availability fluctuates in the organism, inducing time-varying set-points for metabolism. In this work, we introduce a novel data-driven algorithm capable of identifying internal regulation objectives that are maintained with respect to a dynamic reference value. This builds on a previous algorithm that identified variables regulated with respect to fixed set-point values. The new algorithm requires adding a prediction component that not only identifies the internally regulated variables, but also predicts the dynamic set-point as part of the process. To the best of our knowledge, this is the first algorithm that is able to achieve this. We test the algorithm on simulation data from realistic biological models, demonstrating excellent empirical results.

Enhancing the adhesion strength of polymer-based components is a critical challenge in advancing their use as structural and functional materials. Atomic layer deposition (ALD) offers a novel approach to address this challenge by enabling precise surface modifications that improve the adhesion performance. This work studies ALD-based surface modification of 3D-printed acrylonitrile butadiene styrene (ABS)-like single lap shear joints and investigates their adhesion performance. By depositing Al₂O₃, TiO₂, and ZnO layers, we demonstrate significant improvements in shear strength, strain at failure, and toughness. Surface characterizations revealed that these enhancements stem from both chemical and physical modifications, including increased surface energy and the formation of wrinkled patterns that can facilitate mechanical interlocking. Different growth mechanisms led to the formation of distinct wrinkled and crease patterns; while Al₂O₃ and TiO₂ grew on the polymer’s surface, ZnO grew within the ABS-like substrate via vapor phase infiltration (VPI). The surface morphologies and mechanical responses varied depending on the oxide type and number of ALD cycles. This work underscores the potential of ALD as a versatile surface treatment for improving adhesion performance in polymer-based materials and advancing bonding strategies for high-performance applications.

We present a simplified, thermodynamically consistent model of the phase separation of a binary fluid mixture under the effects of a conservative volume force that drives fluid flow. Enforcing conservation of mass provides advection–diffusion equations for the concentrations of the individual components. We propose Darcy-type laws for the velocity and flux of each component, that ensure a nonincreasing free energy functional consistent with the second law of thermodynamics in an isothermal setting. The model is closed by prescribing a free energy in accordance with the Cahn–Hilliard and Flory–Huggins theories. A linear stability analysis of the unforced model yields the range of initial concentrations for which instability occurs and the linear growth rate of perturbations, which are numerically confirmed. We provide fully nonlinear numerical solutions to the model in the specific case of a silicone oil–water mixture, where the conservative force is generated by gravity, or by a surface acoustic wave (SAW) propagating through the underlying substrate. In agreement with recent experimental results, we find that increasing the SAW amplitude or decreasing the SAW attenuation length speeds up total phase separation. This provides a proof-of-principle for modeling phase separation due to the effects of a SAW, within the limitations of our model.