Abstract: The increasing production of nitrogen-containing fertilizers is crucial to meet the global food demand, yet high losses of reactive nitrogen associated with the food production/consumption chain progressively deteriorate the natural environment. Currently, mesophilic nitrogen-removing microbes eliminate nitrogen from wastewaters. Although thermophilic nitrifiers have been separately enriched from natural environments, no bioreactors are described that couple these processes for the treatment of nitrogen in hot wastewaters. Samples from composting facilities were used as inoculum for the batch-wise enrichment of thermophilic nitrifiers (350 days). Subsequently, the enrichments were transferred to a bioreactor to obtain a stable, high-rate nitrifying process (560 days). The community contained up to 17% ammonia-oxidizing archaea (AOAs) closely related to 'Candidatus Nitrososphaera gargensis', and 25% nitrite-oxidizing bacteria (NOBs) related to Nitrospira calida. Incorporation of C-13-derived bicarbonate into the respective characteristic membrane lipids during nitrification supported their activity as autotrophs. Specific activities up to 198 +/- 10 and 894 +/- 81 mg N g(-1) VSS per day for AOAs and NOBs were measured, where NOBs were 33% more sensitive to free ammonia. The NOBs were extremely sensitive to free nitrous acid, whereas the AOAs could only be inhibited by high nitrite concentrations, independent of the free nitrous acid concentration. The observed difference in product/substrate inhibition could facilitate the development of NOB inhibition strategies to achieve more cost-effective processes such as deammonification. This study describes the enrichment of autotrophic thermophilic nitrifiers from a nutrient-rich environment and the successful operation of a thermophilic nitrifying bioreactor for the first time, facilitating opportunities for thermophilic nitrogen removal biotechnology.

Abstract: Paintings are complex objects containing many different chemical compounds that can react over time. The degradation of arsenic sulfide pigments causes optical changes in paintings. The main degradation product was thought to be white arsenolite (As2O3), but previous research also showed the abundant presence of As(V) species. In this study, we investigate the influence of the presence of a medium on the degradation mechanism of orpiment (As2S3) using synchrotron radiation (SR)-based tomographic transmission X-ray microscopy, SR-based micro-X-ray fluorescence, and Xray absorption near edge structure spectroscopy. Upon direct illumination of dry orpiment powder using UV-visible light, only the formation of As2O3 was observed. When As2S3 was surrounded by a medium and illuminated, As2O3 was only observed in the area directly exposed to light, while As(V) degradation species were found elsewhere in the medium. Without accelerated artificial light aging, As(V)(aq) species are formed and migrate throughout the medium within weeks after preparation. In both scenarios, the As(V) species form via intermediate As(III)(aq) species and the presence of a medium is necessary. As(V)(aq) species can react with available cations to form insoluble metal arsenates, which induces stress within the paint layers (leading to, e.g., cracks and delamination) or can lead to a visual change of the image of the painting.

Abstract: The organic components in metal-organic frameworks (MOFs) are unique: they are embedded in a crystalline lattice, yet, as they are separated from each other by tunable free space, a large variety of dynamic behavior can emerge. These rotational dynamics of the organic linkers are especially important due to their influence over properties such as gas adsorption and kinetics of guest release. To fully exploit linker rotation, such as in the form of molecular machines, it is necessary to engineer correlated linker dynamics to achieve their cooperative functional motion. Here, we show that for MIL-53, a topology with closely spaced rotors, the phenylene functionalization allows researchers to tune the rotors' steric environment, shifting linker rotation from completely static to rapid motions at frequencies above 100 MHz. For steric interactions that start to inhibit independent rotor motion, we identify for the first time the emergence of coupled rotation modes in linker dynamics. These findings pave the way for function-specific engineering of gear-like cooperative motion in MOFs.

Abstract: As recently highlighted by the SARS-CoV-2 pandemic, viruses have become an increasing burden for health, global economy, and environment. The control of transmission by contact with contaminated materials represents a major challenge, particularly in hospital environments. However, the current disinfection methods in hospital settings suffer from numerous drawbacks. As a result, several medical supplies that cannot be properly disinfected are not reused, leading to severe shortages and increasing amounts of waste, thus prompting the search for alternative solutions. In this work, we report that non-thermal plasma (NTP) can effectively inactivate SARS-CoV-2 from non-porous and porous materials commonly found in healthcare facilities. We demonstrated that 5 min treatment with a dielectric barrier discharge NTP can inactivate 100% of SARS-CoV-2 (Wuhan and Omicron strains) from plastic material. Using porcine respiratory coronavirus (surrogate for SARS-CoV-2) and coxsackievirus B3 (highly resistant non-enveloped virus), we tested the NTP virucidal activity on hospital materials and obtained complete inactivation after 5 and 10 min, respectively. We hypothesize that the produced reactive species and local acidification contribute to the overall virucidal effect of NTP. Our results demonstrate the potential of dielectric barrier discharge NTPs for the rapid, efficient, and low-cost disinfection of healthcare materials.

Abstract: The use of a photocatalyst (photosensitizer) which produces singlet oxygen instead of enzymes for oxidizing analytes creates opportunities for designing cost-efficient and sensitive photoelectrochemical sensors. We report that perfluoroisopropyl-substituted zinc phthalocyanine (F64PcZn) interacts specifically with a complex phenolic compound, the antibiotic rifampicin (RIF), but not with hydroquinone or another complex phenolic compound, the antibiotic doxycycline. The specificity is imparted by the selective preconcentration of RIF in the photocatalytic layer, as revealed by electrochemical and optical measurements, complemented by molecular modeling that confirms the important role of a hydrophobic cavity formed by the iso-perfluoropropyl groups of the photocatalyst. The preconcentration effect favorably enhances the RIF photoelectrochemical detection limit as well as sensitivity to nanomolar (ppb) concentrations, LOD = 7 nM (6 ppb) and 2.8 A.M-1.cm(-2), respectively. The selectivity to RIF, retained in the photosensitizer layer, is further enhanced by the selective removal of all unretained phenols via simple washing of the electrodes with pure buffer. The utility of the sensor for analyzing municipal wastewater was demonstrated. This first demonstration of enhanced selectivity and sensitivity due to intrinsic interactions of a molecular photocatalyst (photosensitizer) with an analyte, without use of a biorecognition element, may allow the design of related, robust, simple, and viable sensors.

Abstract: This work reports the first study on the possible application of nanodiamond-derived onion-like carbons (OLCs), in comparison with conductive carbon black (CB), as an electrode platform for the electrocatalytic detection of tramadol (an important drug of abuse). The physicochemical properties of OLCs and CB were determined using X-ray diffraction (XRD), Raman, scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET), and thermogravimetric analysis (TGA). The OLC exhibits, among others, higher surface area, more surface defects, and higher thermal stability than CB. From the electrochemical analysis (interrogated using cyclic voltammetry, differential pulse voltammetry, and electrochemical impedance spectroscopy), it is shown that an OLC-modified glassy carbon electrode (GCE-OLC) allows faster electron transport and electrocatalysis toward tramadol compared to a GCE-CB. To establish the underlying science behind the high performance of the OLC, theoretical calculations (density functional theory (DFT) simulations) were conducted. DFT predicts that OLC allows for weaker surface binding of tramadol (Ead = -26.656 eV) and faster kinetic energy (K.E. = -155.815 Ha) than CB (Ead = -40.174 eV and -305.322 Ha). The GCE-OLC shows a linear calibration curve for tramadol over the range of similar to 55 to 392 mu M, with high sensitivity (0.0315 mu A/mu M) and low limit of detection (LoD) and quantification (LoQ) (3.8 and 12.7 mu M, respectively). The OLC-modified screen-printed electrode (SPE-OLC) was successfully applied for the sensitive detection of tramadol in real pharmaceutical formulations and human serum. The OLC-based electrochemical sensor promises to be useful for the sensitive and accurate detection of tramadol in clinics, quality control, and routine quantification of tramadol drugs in pharmaceutical formulations.

Abstract: High-entropy materials are an emerging pathway in the development of high-activity (electro)catalysts because of the inherent tunability and coexistence of multiple potential active sites, which may lead to earth-abundant catalyst materials for energy-efficient electrochemical energy storage. In this report, we identify how the multication composition in high-entropy perovskite oxides (HEO) contributes to high catalytic activity for the oxygen evolution reaction (OER), i.e., the key kinetically limiting half-reaction in several electrochemical energy conversion technologies, including green hydrogen generation. We compare the activity of the (001) facet of LaCr0.2Mn0.2Fe0.2Co0.2Ni0.2O3-delta with the parent compounds (single B-site in the ABO3 perovskite). While the single B-site perovskites roughly follow the expected volcano-type activity trends, the HEO clearly outperforms all of its parent compounds with 17 to 680 times higher currents at a fixed overpotential. As all samples were grown as an epitaxial layer, our results indicate an intrinsic composition-function relationship, avoiding the effects of complex geometries or unknown surface composition. In-depth X-ray photoemission studies reveal a synergistic effect of simultaneous oxidation and reduction of different transition metal cations during the adsorption of reaction intermediates. The surprisingly high OER activity demonstrates that HEOs are a highly attractive, earth-abundant material class for high-activity OER electrocatalysts, possibly allowing the activity to be fine-tuned beyond the scaling limits of mono-or bimetallic oxides.

Abstract: The Stark effect is one of the most efficient mechanisms to manipulate many-body states in nanostructured systems. In mono- and few-layer transition metal dichalcogenides, it has been successfully induced by optical and electric field means. Here, we tune the optical emission energies and dissociate excitonic states in MoSe2 monolayers employing the 220 MHz in-plane piezoelectric field carried by surface acoustic waves. We transfer the monolayers to high dielectric constant piezoelectric substrates, where the neutral exciton binding energy is reduced, allowing us to efficiently quench (above 90%) and red-shift the excitonic optical emissions. A model for the acoustically induced Stark effect yields neutral exciton and trion in-plane polarizabilities of 530 and 630 x 10(-5) meV/(kV/cm)(2), respectively, which are considerably larger than those reported for monolayers encapsulated in hexagonal boron nitride. Large in-plane polarizabilities are an attractive ingredient to manipulate and modulate multiexciton interactions in two-dimensional semiconductor nanostructures for optoelectronic applications.

Abstract: Urine nitrification is pH-sensitive due to limited alkalinity and high residual ammonium concentrations. This study aimed to investigate how the pH affects nitrogen conversion and the microbial community of urine nitrification with a pH-based feeding strategy. First, kinetic parameters for NH3, HNO2, and NO2– limitation and inhibition were determined for nitrifiers from a urine nitrification reactor. The turning point for ammonia-oxidizing bacteria (AOB), i.e., the substrate concentration at which a further increase would lead to a decrease in activity due to inhibitory effects, was at an NH3 concentration of 12 mg-N L–1, which was reached only at pH values above 7. The total nitrite turning point for nitrite-oxidizing bacteria (NOB) was pH-dependent, e.g., 18 mg-N L–1 at pH 6.3. Second, four years of data from two 120 L reactors were analyzed, showing that stable nitrification with low nitrite was most likely between pH 5.8 and 6.7. And third, six 12 L urine nitrification reactors were operated at total nitrogen concentrations of 1300 and 3600 mg-N L–1 and pH values between 2.5 and 8.5. At pH 6, the AOB Nitrosomonas europaea was found, and the NOB belonged to the genus Nitrobacter. At pH 7, nitrite accumulated, and Nitrosomonas halophila was the dominant AOB. NOB were inhibited by HNO2 accumulation. At pH 8.5, the AOB Nitrosomonas stercoris became dominant, and NH3 inhibited NOB. Without influent, the pH dropped to 2.5 due to the growth of the acid-tolerant AOB “Candidatus Nitrosacidococcus urinae”. In conclusion, pH is a decisive process control parameter for urine nitrification by influencing the selection and kinetics of nitrifiers.

Abstract: Atmospheric pressure plasmas have shifted in recent years from being a burgeoning research field in the academic setting to an actively investigated technology in the chemical, oil, and environmental industries. This is largely driven by the climate change mitigation efforts, as well as the evident pathways of value creation by converting greenhouse gases (such as CO2) into useful chemical feedstock. Currently, most high technology readiness level (TRL) plasma-based technologies are based on volumetric and power-based scaling of thermal plasma systems, which results in large capital investment and regular maintenance costs. This work investigates bringing a quasi-thermal (so-called “warm”) plasma setup, namely, a gliding arc plasmatron, from a lab-scale to a pilot-scale capacity with an increase in throughput capacity by a factor of 10. The method of scaling is the parallelization of plasmatron reactors within a single housing, with the aim of maintaining a warm plasma regime while simultaneously improving build cost and efficiency (compared to separate reactors operating in parallel). Special attention is also given to the safety and control features implemented in the setup, a key component required for integration into industrial systems. The performance of the multi-reactor gliding arc plasmatron (MRGAP) reactor is investigated, focusing on the influence of flow rate and the number of active reactors. The location of active reactors was deemed to have a negligible effect on the monitored metrics of conversion, energy efficiency, and energy cost. The optimum operating conditions were found to be with the most active reactors (five) at the highest investigated flow rate (80 L/min). Analysis of results suggests that an optimum conversion (9%) and plug power-based energy efficiency (19%) can be maintained at a specific energy input (SEI) around 5.3 kJ/L (or 1 eV/molecule). The concept of parallelization of plasmatron reactors within a singular housing was demonstrated to be a viable method for scaling up from a lab-scale to a prototype-scale device, with performance analysis suggesting that increasing the power (through adding more reactor channels) and total flow rate, while maintaining an SEI around 5.3 or 4.2 kJ/L, i.e., 1.3 or 1 eV/molecule (based on plug power and plasma-deposited power, respectively), can result in increased conversion rate without sacrificing absolute conversion or energy efficiency.

Abstract: Metal-air batteries and fuel cells show a great deal of promise in advancing low-cost, high-energy-density charge storage solutions for sustainable energy applications. To improve the activities and stabilities of electrocatalysts for the critical oxygen reduction and evolution reactions (ORR and OER, respectively), a greater understanding is needed of the catalyst/carbon interactions and carbon stability. Herein, we report how LaNiO3 (LNO) supported on nitrogen-doped carbon nanotubes (N-CNT) made from a high-yield synthesis lowers the overpotential for both the OER and ORR markedly to enable a low bifunctional window of 0.81 V at only a 51 mu g cm(-2) mass loading. Furthermore, the addition of LNO to the N-CNTs improves the galvanostatic stability for the OER by almost 2 orders of magnitude. The nanoscale geometries of the perovskites and the CNTs enhance the number of metal-support and charge transfer interactions and thus the activity. We use rotating ring disk electrodes (RRDEs) combined with Tafel slope analysis and ICP-OES to quantitatively separate current contributions from the OER, carbon oxidation, and even anodic iron leaching from carbon nanotubes.

Abstract: WO3 isa 5d compound that undergoes severalstructuraltransitions in its bulk form. Its versatility is well-documented,with a wide range of applications, such as flexopiezoelectricity,electrochromism, gating-induced phase transitions, and its abilityto improve the performance of Li-based batteries. The synthesis ofWO(3) thin films holds promise in stabilizing electronicphases for practical applications. However, despite its potential,the electronic structure of this material remains experimentally unexplored.Furthermore, its thermal instability limits its use in certain technologicaldevices. Here, we employ tensile strain to stabilize WO3 thin films, which we call the pseudotetragonal phase, and investigateits electronic structure using a combination of photoelectron spectroscopyand density functional theory calculations. This study reveals theFermiology of the system, notably identifying significant energy splittingsbetween different orbital manifolds arising from atomic distortions.These splittings, along with the system's thermal stability,offer a potential avenue for controlling inter- and intraband scatteringfor electronic applications.

Abstract: Assemblies of closely separated gold nanoparticles exhibit a strong collective plasmonic response due to coupling of the plasmon modes of the individual nanostructures. In the context of self-assembly of nanoparticles, close-packed two-dimensional (2D) clusters of spherical nanoparticles present an important composite system that promises numerous applications. The present study probes the collective plasmonic characteristics and resulting photothermal behavior of close-packed 2D Au nanoparticle clusters to delineate the effects of the cluster size, interparticle distance, and particle size. Smaller nanoparticles (20 and 40 nm in diameter) that exhibit low individual scattering and high absorption were considered for their relevance to photothermal applications. In contrast to typical literature studies, the present study compares the optical response of clusters of different sizes ranging from a single nanoparticle up to large assemblies of 61 nanoparticles. Increasing the cluster size induces significant changes to the spectral position and optophysical characteristics. Based on the model outcome, an optimal cluster size for maximum absorption per nanoparticle is also determined for enhanced photothermal effects. The effect of the particle size and interparticle distance is investigated to elucidate the nature of interaction in terms of near-field and far-field coupling. The photothermal effect resulting from absorption is compared for different cluster sizes and interparticle distances considering a homogeneous water medium. A strong dependence of the steady-state temperature of the nanoparticles on the cluster size, particle position in the cluster, incident light polarization, and interparticle distance provides new physical insight into the local temperature control of plasmonic nanostructures.

Abstract: Although the heterogeneity of pyrolyzed Fe???N???C materials is known and has been reported previously, the atomic structure of the active sites and their detailed reaction mechanisms are still unknown. Here, we identified two pyridinic Fe???N4-like centers with different local C coordinates, i.e., FeN4C8 and FeN4C10, and studied their electrocatalytic activity for the nitrogen reduction reaction (NRR) based on density functional theory (DFT) calculations. We also discovered the influence of the adsorption of NH2 as a functional ligand on catalyst performance on the NRR. We confirmed that the NRR selectivity of the studied catalysts is essentially governed either by the local C coordination or by the dynamic structure associated with the FeII/FeIII. Our investigations indicate that the proposed traditional pyridinic FeN4C10 has higher catalytic activity and selectivity for the NRR than the robust FeN4C8 catalyst, while it may have outstanding activity for promoting other (electro)catalytic reactions. <comment>Superscript/Subscript Available</comment

Abstract: Direct experimental measurement of thermal expansion coefficient without substrate effects is a challenging task for two-dimensional (2D) materials, and its accurate estimation with large-scale ab initio molecular dynamics is computationally very expensive. Machine learning-based interatomic potentials trained with ab initio data have been successfully used in molecular dynamics simulations to decrease the computational cost without compromising the accuracy. In this study, we investigated using Gaussian approximation potentials to reproduce the density functional theory-level accuracy for graphene within both lattice dynamical and molecular dynamical methods, and to extend their applicability to larger length and time scales. Two such potentials are considered, GAP17 and GAP20. GAP17, which was trained with pristine graphene structures, is found to give closer results to density functional theory calculations at different scales. Further vibrational and structural analyses verify that the same conclusions can be deduced with density functional theory level in terms of the reasoning of the thermal expansion behavior, and the negative thermal expansion behavior is associated with long-range out-of-plane phonon vibrations. Thus, it is argued that the enabled larger system sizes by machine learning potentials may even enhance the accuracy compared to small-size-limited ab initio molecular dynamics.