Defect-Accommodating Intermediates Yield Selective Low-Temperature Synthesis of YMnO3 Polymorphs
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The selective production of C3+ olefins from renewable feedstocks, especially via C1 and C2 platform chemicals, is a critical challenge for obtaining economically viable low-carbon middle distillate transportation fuels (i.e., jet and diesel). Here, we report a multifunctional catalyst system composed of Zn-Y/Beta and “single-atom” alloy (SAA) Pt-Cu/Al2O3 which selectively catalyzes ethanol-to-olefins (C3+, ETO) valorization in the absence of cofed hydrogen, forming butenes as the primary olefin products. Beta zeolites containing predominately isolated Zn and Y metal sites catalyze ethanol upgrading steps (588 K, 3.1 kPa ethanol, ambient pressure) regardless of cofed hydrogen partial pressure (0-98.3 kPa H2), forming butadiene as the primary product (60% selectivity at 87% conversion). The Zn-Y/Beta catalyst possesses site-isolated Zn and Y Lewis acid sites (at ~7 wt% Y) and Brønsted acidic Y sites, the latter of which has been previously uncharacterized. A secondary bed of SAA Pt-Cu/Al2O3 selectively hydrogenates butadiene to butene isomers at a consistent reaction temperature using hydrogen generated in situ from ethanol-to-butadiene (ETB) conversion. This unique hydrogenation reactivity at near-stoichiometric hydrogen and butadiene partial pressures is not observed over monometallic Pt or Cu catalysts, highlighting these operating conditions as a critical SAA catalyst application area for conjugated diene selective hydrogenation at high reaction temperatures (>573 K) and low H2/diene ratios (e.g., 1:1). Single-bed steady state selective hydrogenation rates, associated apparent hydrogen and butadiene reaction orders, and DFT calculations of the Horiuti-Polanyi reaction mechanisms indicate that the unique butadiene selective hydrogenation reactivity over SAA Pt-Cu/Al2O3 reflects lower hydrogen scission barriers relative to monometallic Cu surfaces and limited butene binding energies relative to monometallic Pt surfaces. DFT calculations further indicate the preferential desorption of butene isomers over SAA Pt-Cu(111) and Cu(111) surfaces while Pt(111) surface favors subsequent butene hydrogenation reactions to form butane over butene desorption events. Under operating conditions without of hydrogen cofeeding, this combination of Zn-Y/Beta and SAA Pt-Cu catalysts can selectively form butenes (65% butenes, 78% C3+ selectivity at 94% conversion) and avoid butane formation using only in situ generated hydrogen, avoiding costly hydrogen cofeeding requirements that hinder many renewable energy processes.
Excellent contact passivation and selectivity are prerequisites to realize the full potential of high-material-quality perovskite solar cells, first to maximize the internal voltage (or quasi-Fermi-level separation) iV within the absorber, then to translate this high internal voltage into a high external voltage V. Experimental quantification of contact passivation and selectivity is, thus, key to improving device performance. Here, open-circuit measurements of iV oc and V oc , combined with surface photovoltage measurements, are used to systematically quantify the passivation—using iVoc as a metric—and the selectivity—defined as Soc=V oc /iV oc —of a range of common carrier transport layers to wide-bandgap (1.67 eV) perovskite absorbers. The resulting solar cells suffer from large voltage deficits, particularly when NiO x is used as the hole transport layer, even though it provides better passivation than its polymer-based counterparts (PTAA and PTAA/PFN). This indicates a poor selectivity of NiO x (Soc<0.81 for NiO x -based devices), whereas devices using polymer-based hole transport layers exhibit high selectivity (S oc =0.94–0.95). In agreement with recent reports, this low selectivity is attributed to the formation of an interlayer of non-perovskite material with high resistance to holes at the perovskite/NiO x interface. These measurements also imply that the selectivity of the C60-based electron transport layers is relatively good.
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The metabolomic profiles of Soldiers entering the U.S. Special Forces Assessment and Selection course (SFAS) have not been evaluated. To compare pre-SFAS blood metabolomes of Soldiers selected during SFAS versus those not selected, and explore the relationships between the metabolome, physical performance, and diet quality. Fasted blood samples and food frequency questionnaires were collected from 761 Soldiers prior to entering SFAS to assess metabolomic profiles and diet quality, respectively. Physical performance was assessed throughout SFAS. Between-group differences (False Discovery Rate < 0.05) in 108 metabolites were detected. Selected candidates had higher levels of compounds within xenobiotic, pentose phosphate, and corticosteroid metabolic pathways, while non-selected candidates had higher levels of compounds potentially indicative of oxidative stress (i.e., sphingomyelins, acylcarnitines, glutathione, amino acids). Multiple compounds higher in non-selected versus selected candidates included: 1-carboxyethylphenylalanine; 4-hydroxy-nonenal-glutathione; α-hydroxyisocaproate; hexanoylcarnitine; sphingomyelin and were associated with lower diet quality and worse physical performance. Candidates selected during SFAS had higher pre-SFAS levels of circulating metabolites that were associated with resistance to oxidative stress, higher physical performance and higher diet quality. In contrast, non-selected candidates had higher levels of metabolites potentially indicating elevated oxidative stress. These findings indicate that Soldiers who were selected for continued Special Forces training enter the SFAS course with metabolites associated with healthier diets and better physical performance. Additionally, the non-selected candidates had higher levels of metabolites that may indicate elevated oxidative stress, which could result from poor nutrition, non-functional overreaching/overtraining, or incomplete recovery from previous physical activity.
Abstract For ungulates, it is not well understood how the interaction between habitat and reproduction affects movement behavior, space use, and habitat selection. We used known parturition (farrowing) data to validate First Passage Time (FPT) movement analysis to identify wild pig (Sus scrofa) parturition events from data collected with GPS collars. We examined home range and habitat selection during three physiologically distinct time periods in the reproductive cycle: late-gestation; farrowing; and neonate-care period. Sows exhibited a behavioral change 1-2 days prior to farrowing, suggesting FPT analysis can reliably identify parturition events for wide-ranging species that have a focused birthing area. Home range was smallest during the farrowing period, likely reflective of nest building, parturition, and protection of neonates. Home range size during the neonate-care period was intermediate between the late-gestation and farrowing periods, indicative of offspring care that may restrict maternal movement. Across all periods, sows avoided developed areas that have sparse canopy and ground cover and are associated with human activities. During late-gestation, sows avoided pine forests that have an open understory and less vegetative cover. During late-gestation and neonate-care, sows selected bottomland hardwood forests, habitat associated with ample food, cover, and water. During farrowing and neonate-care periods, sows selected upland hardwood forests, habitat with high quality food and cover for neonates. The physiological requirements of reproduction drive female habitat selection and spatial scale of movement patterns associated with parturition. Our study contributes to delineation of the appropriate scale at which to analyze movement data to provide insight about where individuals chose to place their home range, how much space to use, and how they use resources on the landscape to maximize reproductive success and fitness.
Many countries have worked diligently to establish and implement policies and processes to regulate high consequence pathogens and toxins that could have a significant public health impact if misused. In the United States, the Antiterrorism and Effective Death Penalty Act of 1996 (Public Law 104-132, 1996), as amended by the Bioterrorism Preparedness and Response Act of 2002 (Public Law 107-188, 2002) requires that the Department of Health and Human Services (HHS) [through the Centers for Disease Control and Prevention (CDC)] establish a list of bacteria, viruses, and toxins that have the potential to pose a severe threat to public health and safety. Currently, this list is reviewed and updated on a biennial basis using input from subject matter experts (SMEs). We have developed decision support framework (DSF) approaches to facilitate selection of select toxins and, where toxicity data are known, conducted modelling studies to inform selection of toxin amounts that should be excluded from select agent regulations. Exclusion limits allow laboratories to possess toxins under an established limit to support their research or teaching activities without the requirement to register with the Federal Select Agent Program. Fact sheets capturing data from a previously vetted SME workshop convened by CDC, literature review and SME input were developed to assist in evaluating toxins using the DSF approach. The output of the DSF analysis agrees with the current select toxin designations, and no other toxins evaluated in this study were recommended for inclusion on the select agent and toxin list. To inform the selection of exclusion limits, attack scenarios were developed to estimate the amount of toxin needed to impact public health. Scenarios consisted of simulated aerosol releases of a toxin in high-population-density public facilities and the introduction of a toxin into a daily consumable product supply chain. Using published inhalation and ingestion median toxic dose (TD 50 ) and median lethal dose (LD 50 ) values, where available, a range of toxin amounts was examined to estimate the number of people exposed to these amounts in these scenarios. Based on data generated by these models, we proposed toxin exclusion values corresponding to levels below those that would trigger a significant public health response (i.e., amounts estimated to expose up to ten people by inhalation or one hundred people by ingestion to LD 50 or TD 50 levels of toxin in the modeled scenarios).
Specific-ion selectivity is a highly desirable feature for the next generation of membranes. However, existing membranes rely on differences in charge, size and hydration energy, which limits their ability to target individual ion species. Here we demonstrate a nanocomposite ion-exchange membrane material that enables a reverse-selective transport mechanism that can selectively pass a single ion species. Here we demonstrate this transport mechanism with phosphate ions selectively transporting across negatively charged cation exchange membranes. Selective transport is enabled by the in situ growth of hydrous manganese oxide nanoparticles throughout a cation exchange membrane that provide a diffusion pathway via phosphate-specific, reversible outer-sphere interactions. On incorporating the hydrous manganese oxide nanoparticles, the membrane’s phosphate flux increased by a factor of 27 over an unmodified cation exchange membrane, and the selectivity of phosphorous over sulfate, nitrate and chloride reaches 47,100 and 20, respectively. By pairing ion-specific outer-sphere interactions between the target ions and appropriate nanoparticles, these nanocomposite ion-exchange materials can, in principle, achieve selective transport for a range of ions.
Photocatalytic water splitting is a promising route to low-cost, green H 2 . However, this approach is currently limited in its solar-to-hydrogen conversion efficiency. One major source of efficiency loss is attributed to the high rates of undesired side and back reactions, which are exacerbated by the proximity of neighboring oxidation and reduction sites. Nanoscopic oxide coatings have previously been used to selectively block undesired reactants from reaching active sites; however, a coating encapsulating the entire photocatalyst particle limits activity as it cannot facilitate both half-reactions. In this work, area selective atomic layer deposition (AS-ALD) was used to selectively deposit semipermeable TiO 2 films onto model metallic cocatalysts for enhancing reaction selectivity while maintaining a high overall activity. Pt and Au were used as exemplary reduction and oxidation cocatalyst sites, respectively, where Au was deactivated toward ALD growth through self-assembled thiol monolayers while TiO 2 was coated onto Pt sites. Electroanalytical measurements of monometallic thin film electrodes showed that the TiO 2 -encapsulated Pt effectively suppressed undesired H 2 oxidation and Fe(II)/Fe(III) redox reactions while still permitting the desired hydrogen evolution reaction (HER). A planar model photocatalyst platform containing patterned interdigitated arrays of Au and Pt microelectrodes was further assessed using scanning electrochemical microscopy (SECM), demonstrating the successful use of AS-ALD to enable local reaction selectivity in a dual-reaction-site (photo)electrocatalytic system. Finally, interdigitated microelectrodes having independent potential control were used to show that selectively deposited TiO 2 coatings can suppress the rate of back reactions on neighboring active sites by an order of magnitude compared with uncoated control samples.
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In this report the feasibility of a site-selective hydration strategy that enables site-selective atomic layer deposition (ALD) is investigated among four rutile TiO 2 facets [(110), (100), (101) and (001)] and their most prevalent step edges. First-principles simulations of asymmetric slab models were utilized to create accurate representations of pristine terrace and step edge sites. The adsorption free energies for molecular and dissociative adsorption of H 2 O were calculated to evaluate this strategy as a viable route to step edge selectivity. We predict that selective hydroxylation is possible on the 110 and 001 step edges and further computationally evaluate three metalorganic ALD precursors for their compatibility with the selective hydration strategy. Experimental evidence for delayed nucleation of ALD on rutile (001), (110), and (100) TiO2 single crystals corroborates predictions of the dehydration of the surface and suggests the possibility of site-selective ALD.
Abstract not provided
Hydrogenolysis of C–C bonds over Ru-based catalysts has emerged as a deconstruction strategy to convert single-use polyolefin waste to liquid alkanes at relatively mild conditions, but this approach exhibits limitations, including methane formation resulting from terminal C–C bond scission. In this study, a variety of catalysts were investigated for the reductive deconstruction of polyethylene (PE) and polypropylene (PP) to identify supports that promote nonterminal C–C bond scission. We found that Ru nanoparticles supported on Brønsted-acidic zeolites with the faujasite (FAU) and Beta (BEA) topologies were highly active for the cleavage of C–C bonds in PE and PP, exhibiting improved liquid yields and suppressed methane formation. For the deconstruction of PE, supporting ruthenium nanoparticles (5 wt %) on FAU increased the yields of liquid alkanes to 67% compared to 33% over an inert silica support (5 wt % Ru/SiO 2 ) at 200 °C, 16 h, under 30 bar of H2. A dramatic selectivity enhancement toward liquid hydrocarbons was also observed for PP over Ru/FAU and Ru/BEA compared to Ru/SiO 2 . To understand the origin of this selectivity improvement, a combination of ex situ and operando characterization techniques were used to reveal that both catalyst structure and acidity play key roles in PE and PP conversion. Operando X-ray absorption spectroscopy studies with model polyolefins over Ru-supported catalysts with varying acidity levels revealed that the local chemical environment of Ru [0] during the reaction is consistent across multiple acidic supports, although the onset of reduction during synthesis of the nanoparticles varies across different supports. These results, combined with reactivity data, demonstrate the importance of the acid-noble metal cooperativity in promoting selective C–C bond scission toward liquid alkanes that shifts the mechanism from hydrogenolysis to ideal hydrocracking.
Oxygen reduction reaction (ORR) is one of the most important electrochemical reactions. Starting from a common reaction intermediate *–O–OH, the ORR splits into two pathways, either producing hydrogen peroxide (H 2 O 2 ) by breaking the *–O bond or leading to water formation by breaking the O–OH bond. However, it is puzzling why many catalysts, despite the strong thermodynamic preference for the O–OH breaking, exhibit high selectivity for hydrogen peroxide. Moreover, the selectivity is dependent on the potential and pH, which remain not understood. Here, for this work, we develop an advanced first-principles model for effective calculation of the electrochemical reaction kinetics at the solid–water interface, which were not accessible by conventional models. Using this model to study representative catalysts for H 2 O 2 production, we find that breaking the O–OH bond can have a higher energy barrier than breaking *–O, due to the rigidity of the O–OH bond. Importantly, we reveal that the selectivity dependence on potential and pH is rooted into the proton affinity to the former/later O in *–O–OH. For single cobalt atom catalyst, decreasing potential promotes proton adsorption to the former O, thereby increasing the H 2 O 2 selectivity. In contrast, for the carbon catalyst, the proton prefers the latter O, resulting in a lower H 2 O 2 selectivity in acid condition. These findings explain the experiments and highlight the kinetic origins of the selectivity. Our work improves the understanding of ORR by uncovering the proton affinity as a new factor and provides a new model to effectively simulate the atomic-level kinetics of heterogeneous electrochemistry.
Biocatalytic C–H activation has the potential to merge enzymatic and synthetic strategies for bond formation. Fe II /αKG-dependent halogenases are particularly distinguished for their ability both to control selective C–H activation as well as to direct group transfer of a bound anion along a reaction axis separate from oxygen rebound, enabling the development of new transformations. In this context, we elucidate the basis for the selectivity of enzymes that perform selective halogenation to yield 4-Cl-lysine (BesD), 5-Cl-lysine (HalB), and 4-Cl-ornithine (HalD), allowing us to probe how site-selectivity and chain length selectivity are achieved. We now report the crystal structure of the HalB and HalD, revealing the key role of the substrate-binding lid in positioning the substrate for C 4 vs C 5 chlorination and recognition of lysine vs ornithine. Targeted engineering of the substrate-binding lid further demonstrates that these selectivities can be altered or switched, showcasing the potential to develop halogenases for biocatalytic applications.
Earth system models (ESMs) and general circulation models (GCMs) are heavily used to provide inputs to sectoral impact and multisector dynamic models, which include representations of energy, water, land, economics, and their interactions. Therefore, representing the full range of model uncertainty, scenario uncertainty, and interannual variability that ensembles of these models capture is critical to the exploration of the future co-evolution of the integrated human–Earth system. The pre-eminent source of these ensembles has been the Coupled Model Intercomparison Project (CMIP). With more modeling centers participating in each new CMIP phase, the size of the model archive is rapidly increasing, which can be intractable for impact modelers to effectively utilize due to computational constraints and the challenges of analyzing large datasets. In this work, we present a method to select a subset of the latest phase, CMIP6, featuring models for use as inputs to a sectoral impact or multisector dynamics models, while prioritizing preservation of the range of model uncertainty, scenario uncertainty, and interannual variability in the full CMIP6 ensemble results. This method is intended to help impact modelers select climate information from the CMIP archive efficiently for use in downstream models that require global coverage of climate information. This is particularly critical for large-ensemble experiments of multisector dynamic models that may be varying additional features beyond climate inputs in a factorial design, thus putting constraints on the number of climate simulations that can be used. We focus on temperature and precipitation outputs of CMIP6 models, as these are two of the most used variables among impact models, and many other key input variables for impacts are at least correlated with one or both of temperature and precipitation (e.g., relative humidity). Besides preserving the multi-model ensemble variance characteristics, we prioritize selecting CMIP6 models in the subset that preserve the very likely distribution of equilibrium climate sensitivity values as assessed by the latest Intergovernmental Panel on Climate Change (IPCC) report. This approach could be applied to other output variables of climate models and, possibly when combined with emulators, offers a flexible framework for designing more efficient experiments on human-relevant climate impacts. It can also provide greater insight into the properties of existing CMIP6 models.
The tradeoff between selectivity and throughput presents fundamental challenges to improve desalination and charge storage, salinity gradient-based energy harvesting, memory device/circuit development, and so forth. The well-known ion-current rectification and the recently resolved time-dependent transport hysteresis in conical nanopores or asymmetric nanointerfaces offer new opportunities for the selective transport of matter. This report shows that electro-osmotic flow (EOF) is an overlooked factor that increases ion selectivity while maintaining enhanced transport throughput in rectified nanoscale electrokinetic transport. The increased selectivity originates primarily from the suppression of anion flux by the fluid flow in the opposite direction under the applied electrical field. By solving the Poisson and Nernst–Planck (PNP) equations without and with coupled Navier–Stokes (PNP–NS) equations, the EOF effects on cation and anion transport are unequivocally revealed in asymmetric nanopipettes. The flux of cations and anions as well as the transference number and flow velocity are elucidated using the models and boundary conditions validated by previous experiments. A dimensionless parameter, radius over the Debye length, reveals optimal ion selectivity and energy cost at intermediate ion concentrations and nanopore sizes, up to hundreds of millimolars and tens of nanometers under time-dependent potential stimulus. Furthermore, the fundamental insights into EOF at nanointerfaces suggest new routes/strategies for better separation, analysis, and energy applications.