The optical, chemical, and electrical properties of the ALD SnO2 layer and its influence on the device performance are investigated. It is found that surface passivation of SnO2 is essential to reduce charge recombination at the perovskite and ETL interface and show that the fabricated planar perovskite solar cells exhibit high reproducibility, stability, and power conversion efficiency of 20%.Planar perovskite solar cells using low‐temperature atomic layer deposition (ALD) of the SnO In this article, we prove that the low‐temperature process for the SnO2 ETL is an indispensable choice to reduce charge recombination for photovoltaic applications.Over the past few years, there have been tremendous research and development in perovskite solar cells.2 films at low temperature, which is based on self‐limiting surface reactions by exposing sequentially on the substrate with various precursors and reactants. It is enabling precise thickness control at the angstrom or monolayer level and deposition on high aspect ratio nanostructures with excellent step coverage.2 layers using the ALD method by modulating deposition or postannealing temperature, and showed how temperature can influence on optical, chemical, and electrical properties of the SnO2 film along with the device performance.The atomic layer deposition (ALD) technique is an efficient way to prepare SnO2 films deposited at 120 °C and the complete perovskite device are displayed in Figure2 layer without pinholes is observed over the fluorine‐doped SnO2 (FTO) top‐surface. The complete cell of a planar structure is composed of FTO/ALD SnO2/perovskite/poly triarylamine (PTAA)/gold layers. In this structure, ALD SnO2 functions as an ETL, while perovskite, PTAA, and gold work as a light absorber, a hole transporting material (HTM), and a counter electrode, respectively. The optical property of compact TiO2 (c‐TiO2) and ALD SnO2 films was compared by measuring transmittance. As shown in Figure 2‐coated film is measured while decreased transmittance is observed from the 20 nm thick TiO2‐coated FTO substrate. The ALD SnO2 ETL gave a better device performance than the c‐TiO2 ETL as shown in the J–V curves of Figure 2 film is likely to have a similar conduction band position, it is reasonable to find a similar Voc with both SnO2 and TiO2.Jsc) and FF obtained from the cell with ALD SnO2 ETL can be surmised by the better light harvesting and electron extraction at the interface. Despite the negligible difference of light absorption at the longer wavelength as seen in Figure 2 and FTO/ALD SnO2 substrates, respectively. Considering both perovskite layers have the same thickness, charge collection can be differentiated by the interfacial condition. Compared with the TiO2/perovskite film, much lower PL intensity, ≈40% reduction, is observed from the SnO2/perovskite film as displayed in Figure 2/perovskite film indicates that the excited electrons in perovskite can be quenched more quickly at the SnO2/perovskite interface than that of TiO2/perovskite. These results strongly support the reasons of the higher efficiency with the ALD SnO2 ETL shown in Figure 2 films.J–V curves of the perovskite cells with postheated films are shown in Figure 2 films are deposited at 100 °C, which is slightly lower than reference temperature of 120 °C. An S‐shaped curve with the as‐prepared film maybe owing to incomplete conversion of the precursor which can cause a high series resistance of the device is observed. As expected, highly enhanced FF and a slightly improved Jsc are displayed after heating the film at 180 °C. However, the film heat‐treated at a higher temperature of 300 °C shows a severe drop of Voc. The observed phenomenon amazingly equals well with our previous results with SnCl4 and water precursors.2 films show a dense form without visible morphology change even after postannealing at 300 °C; thus, we can assume that the ALD SnO2 film prepared at low temperature also has the passivated tin oxide (PTO) structure.2 and ALD SnO2 substrates and found no distinct change by the substrates as seen in Figures S2 and S3 in the Supporting Information, respectively.The microstructures from scanning electron microscope (SEM) of the ALD SnO2/Si substrate and postannealed at 180 and 300 °C were investigated by tip‐enhanced Raman spectroscopy (TERS) as seen in Figure−1, which was assigned to the Raman active Eg mode associated with the αxz polarizability tensor,2 Eg peaks, the TER spectra were normalized to the Si peak at 521 cm−1 since the portion of substrate probed is constant. Raman scattering intensity was weakest in the 100 °C deposited sample and strongest in the 300 °C annealed sample, while the 180 °C annealed sample exhibited more intense Raman scattering than the 100 °C sample. This suggests that the films postannealed at higher temperature are more crystalline and of primarily one orientation than the 100 °C annealed film. As the ALD SnO2 films prepared at low temperature are known to have an amorphous nature, the result of TERS seems to match well with that of X‐ray diffraction (XRD) spectroscopy.4+ ions indicate the formation of SnO2 and small shift according to annealing temperature, which implies that the chemical change of the film is seen in Figure 2 film has been improved, which is consistent with obtained values from TER analysis. A weak asymmetry shown in all spectra can be reasoned by Sn2+ ions originated from oxygen vacancy (Vo) of the SnO2 surface, which is assumed as the origin of the high conductivity of the SnO2 film.4+), while the small one at 531.5 eV can be associated with oxygen impurities such as OH ligands and water adsorption on the film.2, otherwise, the residual tetrakis‐dimethyl‐amine‐tin (TDMASn) remains as an impurity on the film.2 below the temperature.2 ETL as depicted in Figure 2 self‐passivated by the properly controlled residual precursor, which provides good electron mobility and hole‐blocking ability as well as an amorphous nature of the PTO layer. When combining with device results shown in Figure 2 is the key for the high efficiency.To see the influence of postannealing temperature, samples deposited at 100 °C on SiO2 films is displayed in Figure2 films measured by ultraviolet photoelectron spectroscopy (UPS), respectively. The exact VB offset was determined by extrapolating the leading edge of the VB spectrum to the base line. From the spectra, VB offsets of as‐deposited, 180, and 300 °C films are measured as 3.61, 3.51, and 3.30 eV, respectively. We measured bandgaps by reflection electron energy loss spectroscopy (REELS).2 thin films are determined by the difference between elastic peak and onset of inelastic loss spectrum. Hence, we measured bandgap energies using an intercept of the line with a maximum negative slope near the edge to the background level as shown in Figure EF = Ecut‐off – 40.8 eV (irradiation energy of He II source). Thus, Fermi levels for the films can be calculated as −4.16, −4.32, and −4.51, respectively. And the valence band maximum (VBM) was determined by the equation, VBM = EF – VB offset. It should be noted that three different films have similar VBMs of −7.77, −7.83, and −7.81 eV, while the gradual downward shift of EF and conduction band maximum (CBM) of annealed films are observed in Figure 2 films under heterojunction with FTO and perovskite. In the dark condition, Fermi levels of SnO2 films and perovskite (n‐type) are pinned by FTO.EF of SnO2 films. Thus, the result is partially opposite to the general understanding that the lower position of the conduction band is beneficial for electron injection. Instead, we can conclude that the improved efficiency observed from the cells with the annealed SnO2 films at low temperature is dominantly by the reduced series resistance of the SnO2 layer with properly controlled surface passivation.The energy band structure of the SnO2 was placed on enhancing electrical conductivity with high transparency for the conductive film applications. Accordingly, the residual precursor was regarded as rather harmful by increasing resistivity of the film. However, our findings demonstrate that such impurities can be beneficial or essential for photovoltaics by passivating surface defects of the SnO2 layer if it is controlled properly. Passivation of SnO2 can be easily controllable by manipulating the deposition and postannealing temperature as illustrated in Figure2 films, but the result with different deposition temperature displays a remarkably analogous trend as shown in Figure S5 in the Supporting Information. A strong recombination pathway that may occur when the SnO2 film lacks hole‐blocking ability is depicted in Figure S6 in the Supporting Information. For comparison, we fabricated planar type cells with a thin layer of SnO2 nanoparticles,2 layer, which is classified as 4 types as sketched in Figure 2 layer.So far, much of research interest related to ALD SnO2 underlayer with a PTO top layer,J−V curve for the champion cell is shown in FigureJsc of 22.67 mA cm−2, the Voc of 1.13 V, the FF of 0.78, and the PCE of 20.03% under 1 sunlight illumination condition when scanned backward. In the external quantum efficiency (EQE) measurement, we confirmed that the Jsc from the solar simulator  agrees with the integrated Jsc value of 23.03 mA cm−2 as seen in Figure J–V curve hysteresis is still observed as similarly reported in our previous paper.2 and perovskite compared with that of TiO2/perovskite can also result in better stability of the perovskite layer.2 ETL degrades quickly as shown in Figure In this work, we introduced “Type 1” passivation, which combines a thin TiO2 films for perovskite solar cells and found that the SnO2 ETL should be passivated due to metal‐like nature of SnO2. We unveil that the residual precursor, TDMASn, on the ALD SnO2 film can be a good self‐passivating material. It was found that chemical and electrical properties of the ALD SnO2 film were strongly associated with deposition and postannealing temperature. By investigating optical, chemical, and electrical properties of the ALD SnO2 films, we found that the charge collection from perovskite to SnO2 can be less influenced by the downward shift of CBM and EF of SnO2 films, but strongly affected by crystallinity and proper surface passivation of the SnO2 layer. Additionally, the bi‐layered ETL of c‐TiO2/passivated SnO2 was confirmed to provide better hole‐blocking ability than a single‐passivated SnO2 layer, which resulted in the further enhanced PCE. Our findings highlight the importance of surface passivation for SnO2‐based ETLs, and explain why the low‐temperature process is necessary to obtain high PCEs. We suggest the possibility of better PCEs by efficient passivation with diverse materials for high‐efficiency solar cells.In summary, we investigated low‐temperature‐processed ALD SnODevice Fabrication: FTO glass (Nippon Sheet Glass) substrates were partially etched with Zn powder and diluted HCl solution, and sequentially cleaned with detergent solution, water, and ethanol. ALD SnO2 films were prepared with tetrakis‐dimethyl‐amine tin as a Sn precursor and ozone as an oxygen reactant.2 was carried out at 120 or 100 °C, and the films were used as‐prepared or after postannealing. For Type 1 passivation, a compact TiO2 layer was coated on the cleaned FTO substrate by spray pyrolysis deposition at 450 °C with a precursor solution prepared by diluting titanium diisopropoxide (Sigma‐Aldrich) in ethanol. The PTO layer was formed on a c‐TiO2‐coated FTO films by ALD. The deposition was carried out at 100 °C, and the as‐prepared film was postannealed at 180 °C for 1 h. A thin layer of SnO2 nanoparticles was prepared by spin coating the SnO2 colloid precursor . The SnO2 layer was spin coated at 4000 rpm for 30 s, and heat‐treated in the air at 150 °C for 30 min.3)0.85(MAPbBr3)0.15 precursor solution was prepared by mixing PbI2 , FAI , PbBr2 , and MABr  in a mixed solvent of DMF:DMSO = 4:1 (volume ratio). The solution was spin coated at 1000 rpm for 10 s and, continuously at 5000 rpm for 30 s. During the second step, 100 µL of chlorobenzene was poured on the film at 15 s. Films are postannealed at 100 °C for 60 min. The HTM solution was prepared by dissolving 10 mg of PTAA (Emindex) with additives in 1 mL of toluene. As additives, 7.5 µL of Li‐bis(trifluoromethanesulphonyl) imide (Aldrich) from the stock solution (170 mg in 1 mL of acetonitrile), and 4 µL of 4‐tert‐butylpyridine were added. The HTM layer was formed by spin coating the solution at 3000 rpm for 30 s, and followed by the deposition of the 70 nm thick Au electrode by a thermal evaporation.The authors declare no conflict of interest.SupplementaryClick here for additional data file.


RNA silencing (VSRSs) are a diverse group of viral proteins that have evolved to disrupt eukaryotic RNA silencing pathways, thereby contributing to viral pathogenicity. The p19 protein is a VSRS that selectively binds to short interfering RNAs (siRNAs) over microRNAs (miRNAs). Mutational analysis has identified single amino acid substitutions that reverse this selectivity through new high‐affinity interactions with human miR‐122. Herein, we report crystal structures of complexed p19‐T111S (2.6 Å), p19‐T111H (2.3 Å) and wild‐type p19 protein (2.2 Å) from the Carnation Italian ringspot virus with small interfering RNA (siRNA) ligands. Structural comparisons reveal that these mutations do not lead to major changes in p19 architecture, but instead promote subtle rearrangement of residues and solvent molecules along the p19 midline. These observations suggest p19 uses many small interactions to distinguish siRNAs from miRNAs and perturbing these interactions can create p19 variants with novel RNA‐recognition properties.Viral suppressors of 6BJG, 6BJH and 6BJV.Model data are deposited in the PDB database under the accession numbers  AGOArgonauteCIRVCarnation Italian ringspot virusdsRNAdouble‐stranded RNAHis8‐tagocta‐histidine tagmiRNAmicroRNAntnucleotideRISCRNA‐induced silencing complexRNAiRNA interferencesiRNAshort interfering RNAssRNAsingle‐stranded RNATBSVtomato bushy stunt virusVSRSviral suppressor of RNA silencingin vitro and living systems; their specialized binding properties and amenability to engineering and multiplexing have made them powerful tools for probing RNA biology . VSRSs are a diverse group of viral proteins that have evolved to disrupt eukaryotic RNA silencing pathways, thereby contributing to viral pathogenicity The p19 protein is the VSRS expressed by tombusviruses, is the most widely studied of the VSRSs. The unique features of the p19 protein are evident from structural and biochemical studies that demonstrate p19's ability to bind to small dsRNAs with size specificity and independently of the nucleotide sequence of the RNA miRNAs are endogenous small RNAs that are potent regulators of gene expression, are critical in host–pathogen interactions and can serve as biomarkers of disease in vitro and in vivoMismatches and bulges in dsRNA structure are important determinants of intermolecular recognition, as they can cause distortions in the helical backbone which can be specifically recognized by RNA binding proteins in vivo, engineering the p19 binding site to allow enhanced affinity for specific patterns in miRNA secondary structure would broaden p19's applicability for miRNA detection and sequestration.Base pair mismatches in miRNAs alter p19's ability to bind these RNAs with high affinity  We have previously observed that a single point mutation to p19's binding site at the threonine 111 position to either a histidine (p19‐T111H) or a serine (p19‐T111S) leads to a ~50‐fold increase in the binding affinity of p19 for miR‐122  at 25 °C for 4 h. Cells were harvested by centrifugation, resuspended in lysis buffer  and lysed by a single pass through a M‐110P homogenizer .Plasmids were transformed into BL21 DE3 cells, and cultures were grown from single colonies in 150 mL LB+ 100 mm Tris pH 8.0, 0.3 m NaCl and 0.5 mm TCEP) over Nickel resin . The resin was washed with wash buffer . The his‐tagged p19 was eluted with 50mm Tris pH 8.0, 0.3 m NaCl, 0.3 m imidazole and 0.5mm TCEP and was dialysed in buffer (50 mm Tris (pH 8), 300 mm NaCl and 1 mm TCEP) with 2 mg of tobacco etch virus (TEV) protease at 4 °C overnight to remove the N‐terminal 6‐histidine tag. Gravity filtration over Nickel resin  allowed capture of the portion of the his‐tagged p19 molecules which remained uncleaved, as well as the TEV protease (containing a 6‐histidine tag). The tag‐free p19 protein was then concentrated using Amicon Ultra‐5 Centrifugal Filter tubes  to 0.5 mL and purified by size‐exclusion chromatography on a Superdex 200 10/30  in FPLC buffer .Protein purification was performed by gravity filtration of the bacterial lysate suspended in lysis buffer  2000 spectrophotometer, with the calculated extinction coefficient of 34 950 GL2 siRNA is 21 nucleotides long with two nucleotide overhangs, in which we used modified deoxythymidine nucleotides for the overhangs. The RNA was custom‐ordered from Thermo Scientific and was prepared as follows by the manufacturer: the individual strands were 5′ phosphorylated, converted to the 2′ hydroxyl, annealed and desalted, and purified by polyacrylamide gel electrophoresis. The sense strand (CGUACGCGGAAUACUUCGAUU) and antisense strand (UCGAAGUAUUCCGCGUACGUU) were annealed to allow siRNA duplex formation. We resuspended the purchased annealed siRNA duplex in DEPC‐treated water.−1) for 1 h at 4 °C. Crystals of p19–RNA complexes were grown using hanging drop vapour diffusion at 4 °C. Drops contained a 1 : 1 ratio of protein–RNA complex (0.8 μL of 2mg·mL−1) to 0.8 μL reservoir solution containing 3–12% PEG 1500, 100 mm sodium acetate pH 4.6 and 10–40 mm MgCl2. The best crystals were grown from drops that were seeded with smaller crystals, which had been crushed via vortexing with seed beads , and streaked through the drops using one of Cupcake the cat's whiskers. The crystals developed a hexagonal morphology over the course of 1–2 weeks at 4 °C. The crystals were harvested with nylon loops, cryo‐protected in the reservoir solution supplemented with 30% ethylene glycol , and flash‐frozen in liquid N2. Data were collected under cryogenic conditions at beamlines 12‐2 at Stanford Synchrotron Radiation Lightsource (SSRL) Protein–RNA complexes were formed by mixing 1.2 molar equivalents of RNA with 1 molar equivalent of protein (2 mg·mL1RPU) The p19–siRNA crystals diffracted X‐rays to a maximum resolution of 2.3–1.8 angstroms. The data collected from the p19–siRNA complexes  were indexed and scaled using XDS In pursuing structural basis for the high affinity of the p19‐T111X mutants towards the mammalian miR‐122, we first sought to understand the impact of the mutations on the overall architecture of the p19 protein. Crystals of wild‐type CIRV p19 (p19‐WT) and the p19 mutants p19‐T111H and p19‐T111S in complex with a perfectly duplexed siRNA were grown and were found to diffract to 2.2 to 2.6 Å  Next, we examined the structures of the p19‐T111X mutants to assess the impacts of the amino acid substitution on the overall topography of the p19 dimer. As displayed in Fig.−1. This change in the free energy upon binding could be due to the T111H or T111S mutation providing a favourable change in enthalpy (ΔH), through generating increased contacts between the binding site and the miRNA (e.g. ~2 hydrogen bonds). These could be direct interactions with the secondary structure of the miRNA or could be an increase in the number of water‐mediated hydrogen bonds that are prevalent in the p19–RNA binding site. Therefore, the orientation and organization of hydrogen bonds associated with the mutated residues are expected to play a key role in providing the free energy difference associated with binding.In pursuing structural determination of the p19 mutants, we sought to examine specific interactions between the protein and the miRNA which could explain the observed 50‐fold enhancement from WT on miR‐122 binding affinity, without altering the protein's affinity for siRNA ligands The p19 mutants p19‐T111S and p19‐T111H contain two chemically distinct mutations that give rise to nearly identical changes in the RNA binding properties of p19  4JK0), where a glutamine mutation has been introduced at the same 111 site in the p19 protein from the tobacco bushy stunt virus (TBSV). p19 is highly conserved among tombusviruses, and the TBSV p19 and the CIRV p19 share 86% amino acid identity and the same protein architecture The p19‐T111 site of each p19 monomer is positioned on the second beta‐strand (counting the beta‐strands from N‐C termini) and the two T111 sites in the dimer insert into the minor groove of the central region of the bound RNA, in proximity to the RNA backbone Fig.  . Figure Water molecules in protein–RNA binding sites contribute to binding affinity, providing hydrogen bond opportunities between the protein binding site and RNA, as well as shielding of unfavourable charge interactions between the two molecules In comparing the water molecules in the binding site between the p19‐WT and the p19‐T111H mutant, we observe that most of the water molecules shift positions in the binding site. In examining the hydration near the 111 site, we observe that an ordered water molecule engaged by the WT threonine is displaced by the histidine in the p19‐T111H structure Fig. . This ob4KTG, 4J5V, 4KNQ, 4JNX, 4JGN, 4KQO and 4J39) The structures determined here highlight T111 as uniquely positioned for access to the nucleotide bases along the central base pair of the bound RNA duplex, which is the position of the central mismatch of miR‐122. In support of this argument, others have observed in structures of p19 in complex with CNG repeat RNAs containing G:U and U:U mismatches, another form of noncanonical RNA duplex, that p19 is able to influence the geometry of the RNA helix, stabilizing irregular dsRNA geometries into more regular Watson–Crick formations  for influencing miR‐21 activity The authors declare no conflict of interest.DF, IM and JP designed and conceived of the project. DF and NS collected the data. DF, JP and IM interpreted the results. DF wrote the manuscript with conceptual and editing help from JP and IM.


Streptococcus serotypes Ia and Ib capsular polysaccharides are key targets for vaccine development. In spite of their immunospecifity these polysaccharides share high structural similarity. Both are composed of the same monosaccharide residues and differ only in the connection of the Neu5Acα2‐3Gal side chain to the GlcNAc unit, which is a β1‐4 linkage in serotype Ia and a β1‐3 linkage in serotype Ib. The development of efficient regioselective routes for GlcNAcβ1‐3[Glcβ1‐4]Gal synthons is described, which give access to different group B Streptococcus (GBS) Ia and Ib repeating unit frameshifts. These glycans were used to probe the conformation and molecular dynamics of the two polysaccharides, highlighting the different presentation of the protruding Neu5Acα2‐3Gal moieties on the polysaccharide backbones and a higher flexibility of Ib polymer relative to Ia, which can impact epitope exposure.Group B  Glycosylation: A panel of GBS serotype Ia and Ib fragments was prepared by combined regioselective‐stereoselective approaches and used to unravel polysaccharide conformations responsible for immune specificity. B Streptococcus (GBS) is a leading cause of pneumonia, sepsis, meningitis, and death in neonates.Group 1, 3 and linear 2, 4 frameshifts depicted in Figure 3 and 4 share identical monosaccharide composition with milk oligosaccharides, which have recently been proposed to inhibit GBS colonization.The repeating units of CPS Ia and Ib can be described by the branched O‐benzylidene‐protected Gal acceptor was used for glycosylation with a glucosamine trichloroacetimidate donor, and subsequent regioselective ring opening before further glycosylation of position 4 for the construction of the trisaccharide GlcNAcβ1‐3[Glcβ1‐4]Gal could take place. There is need of expeditious procedures for the construction of complex glycans, and regio‐ and stereoselective reactions distinguishing among diverse deprotected hydroxyls are highly desirable to simplify the oligosaccharide assembly.Although the synthesis of the GBS CPS Ia repeating unit has been reported,1 and 3, respectively, and molecular dynamics simulation allowed to shed light on how the variation of a single sugar connection dramatically affects the conformational properties of CPS Ia and Ib polysaccharides, and hence exposition of potential epitopes for antibody recognition.Herein, we report tactics to achieve regioselective syntheses of protected GlcNAcβ1‐3Gal building blocks and the use of these key synthons in convergent routes towards a series of fragments from CPS Ia and Ib repeating units with a built‐in aminopropyl linker amenable for future conjugation to carrier proteins /AgOTf‐mediated activation  and fluorenylmethyloxycarbonyl (Fmoc) were selected for temporary protection of either position 3 or 4. Alternatively, a 4,6‐s Scheme . The pres Scheme  to optimO‐benzyl acceptor 10 with donor 16 by using NIS with either TfOH or AgOTf as co‐promoters gave variable mixtures of the β1‐3 21 a and β1‐4 21 b disaccharides  for the thioglycoside donor or the torsional disarming effect of the benzylidene/silylidene group for the imidate donors appears to favor the regioselectivity of glycosylation at position 3.2612 a and 14 a were performed to furnish trisaccharides 27 a and 27 b in 75 and 68 % yield, respectively .Despite the deactivating effect of the 6‐y Scheme , whereas293030 can be prepared with a higher α stereoselectivity, whereas 29 is easily accessible from a commercial disaccharide precursor.In order to complete the pentasaccharide construction, the sialo‐galactosyl trifluoroacetimidate donor 28 with 29 under TMSOTf activation gave the protected pentasaccharide 31 in 75 % yield, and the use of disaccharide 30 in the presence of NIS/TfOH led to the protected pentasaccharide 32 in a similar yield (73 %). Compound 30 was deprotected by a four‐step procedure,O‐acetates and the NPhth protecting group; 3) reacetylation with acetic anhydride/pyridine to install the acetamide group of the GlcNAc residue along with acetyl esters; 4) methanolysis and final catalytic hydrogenation over Pd/charcoal to provide the target branched pentasaccharide 1.Glycosylation of trisaccharide 32 was first subjected to saponification with NaOH in THF heated to reflux, followed by amine reacetylation with a 2:3 acetic anhydride/methanol mixture.Pentasaccharide 1 equipped with the aminopropyl linker suitable for conjugation. After purification by size exclusion chromatography, the final compound was obtained in 40 % overall yield from 31 and 45 % overall yield from 32, respectively  in the 1H NMR and HSQC spectra of all synthetic intermediates. This confirmed the regioselectivity of the two glycosylations performed. Unexpectedly, reaction of 35 with the tolyl thioglycoside 30 under NIS/TfOH activation at −40 °C yielded only traces of the corresponding pentasaccharide, whereas mainly decomposition of the glycosyl donor was observed, as revealed by LC‐MS analysis. The linear pentasaccharide 36 was subjected to the five‐step deprotection protocol previously described for compound 31. The target oligosaccharide 2 was purified by size exclusion chromatography and obtained in 33 % overall yield  with the trifluoroacetimidate 38, prepared from the known 1‐OH compound 37.5 was obtained in 42 % yield .Differently than the GBS CPS Ia pentasaccharides, the two Ib frameshifts 23 a and 25 a, which differ only in the cyclic protecting group blocking the glucosamine C4,6−OH groups, were selected to be elongated to the branched pentasaccharide 3 , glycosylation with the sialogalactoside donor 29 of the two acceptors 42 and 43 was tested.The C3‐OH of the glucosamine appeared significantly less reactive than the C4‐OH, which is likely due to the presence of the bulky NPhth group that could hinder the glycosylation reaction at the C3−OH. We anticipated that its replacement with a Troc protection would result in a higher nucleophilicity of the vicinal hydroxyl. Disaccharides O‐benzylidene trisaccharide 42 and 29 with TMSOTf as a promoter failed to afford the target pentasaccharide, leading to complete recovery of the unreacted acceptor. In contrast, reaction of acceptor 43, bearing the more flexible 4,6‐O‐silylidene ketal, with 29 in the presence of TMSOTf gave the target pentasaccharide 44 in 80 % yield  saponification with NaOH in THF heated to reflux, for concomitant hydrolysis of the acyl esters, the Troc group, and the 5‐N,4‐O‐oxazolidinone protecting group and Neu5Ac methyl ester, 3) reacetylation of the amines by a 2:3 acetic anhydride/methanol mixture, 4) hydrogenation over Pd/charcoal. The target branched pentasaccharide 3 was obtained in 40 % yield.Reaction of the 4,6‐4 of the GBS serotype Ib repeating unit . Following Fmoc deprotection with piperidine in CH2Cl2, the obtained acceptor 47 was β‐glycosylated with imidate 29 to attain the linear protected pentasaccharide 48 (66 %). Reaction with thioglycoside 30 in TfOH and NIS reaction conditions also provided the analogous pentasaccharide 49 (40 %). The obtained pentasaccharides were deprotected and purified as described above. NMR spectroscopic data of the synthesized CPS Ib fragments were in excellent agreement with NMR spectroscopic data from samples of the bacterial polysaccharide.Finally, we extended our regioselective approach to the synthesis of the linear frameshift t Scheme . For thi1 and 3 were studied by a combination of NMR spectroscopy and modeling tools,1 and 3 were estimated from ROESY spectra. The obtained experimental distances were compared with those derived from a 200 ns molecular dynamics (MD) simulation. Table 1. The comparison reflects a good agreement between the NMR‐ and the MD‐derived distances for the glycosidic linkages GlcNAcβ1‐3Gal and Glcβ1‐4Gal . The Φ/Ψ population analysis from the MD simulation showed a single population for Φ fulfilling the exo‐anomeric effect (exo‐syn‐Φ),ψ for both linkages .The conformational properties of the CPS Ia and Ib branched repeating unit pentasaccharides exo‐syn‐Φ/synΨ conformation, as predicted by the MD simulation.For the Galβ1‐4GlcNAc linkage, there is a perfect agreement for the H1Gal‐H4GlcNAc distance with slight discrepancies for the H1Gal‐H6,H6′GlcNAc ones, which is probably due to the MD bias around the GlcNAc ω torsion angle . These data support the existence of a single population around the exo‐syn‐Φ populations. Indeed, according the NOE‐derived distance, the exo‐anti‐Φ population should be the major one, representing around 75 % of the total ensemble. Two representative conformations for the CPS Ia pentasaccharide 1 are shown in the Supporting Information, differing in the Neu5Acα2‐3Gal linkage . The analysis for the CPS Ib pentasaccharide 3 yielded similar results , although the GlcNAcβ1‐3Gal linkage could not be fully characterized because of the overlapping between the H1GlcNAc and H3Gal protons. The linkage between Gal and GlcNAc, now β1‐3 instead of β1‐4, populates a minimum around the exo‐syn‐Φ/syn(−)‐Ψ conformation . Two representative conformations for the CPS Ib pentasaccharide 3 are shown in the Supporting Information, which also differ in the orientation around the Neu5Acα2‐3Gal Φ torsion . A superimposition of representative 3D structures for the CPS Ia and Ib pentasaccharides 1 and 3, with the major conformation exo‐anti‐Φ around the Neu5Acα2‐3Gal linkage is shown in Figure For the Neu5Acα2‐3Gal linkage, MD simulations predict three different populations, 180°/−30°, −60°/−20°, and −60°/−50°. The interglycosidic interproton distances for each population are gathered in Table The analysis of the glycosidic linkages was carried out for the 49 glycosidic bonds, revealing that the behavior for every glycosidic bond type is reproducible along the polysaccharide Figure .exo‐anti‐Φ (ca. 85 %), whereas for the Ib polysaccharide, there is a larger flexibility, with a major exo‐syn‐Φ form (ca. 55 %). The model structures for the polysaccharides with all Neu5Acα2‐3Gal linkages in exo‐anti‐Φ (Ia) and exo‐syn‐Φ (Ib) are displayed in Figure These populations are comparable to those of the corresponding pentasaccharide for every glycosidic linkage, and thus, the resulting interglycosidic interproton distances are very similar . Remarkably, for both GBS serotype Ia and Ib, the HSQC spectra of the polysaccharide and the pentasaccharide were very similar, with the obvious exception for the Glcβ1‐4 linked moiety (E), which is not glycosylated at O4 in the pentasaccharides Figure  A, B. AtTo have fast access to homogeneous oligosaccharide antigens from GBS serotypes Ia and Ib and to gain insights into the conformational difference among these structurally similar polymers, we developed a highly convergent synthetic strategy based on the regioselective glycosylation of a galactose C3,4‐diol to obtain GlcNAcβ1‐3Gal disaccharide building blocks. Investigation of the different reactivities of the C3‐ and C4‐hydroxyls allowed us to reduce the number of protective group manipulations and synthetic steps to the final fragments, therefore simplifying the overall synthetic design.O‐benzoyl galactose diol resulted in improved regioselectively relative to that of the 2,6‐di‐O‐benzyl counterpart. In addition, mild activation conditions (NIS/AgOTf) for the glucosamine thiol donors or the torsional disarming effect of the benzylidene group for the trichloroacetimidate donors appear to favor the glycosylation reaction. The regioselective glucosamine incorporation was successfully applied to the synthesis of GBS CPS Ia and Ib branched repeating units (1 and 2). Their linear frameshifts (3 and 4) and a non‐sialylated CPS Ia form (5) were also synthesized to achieve an additional regioselective glycosylation of the Gal C3‐OH over the C4‐OH residue.Particularly, the use of a 2,6‐These results support the general applicability of the method to a variety of medically relevant glycans. Importantly, the structures synthesized through regioselective glycosylation appear extendible at the 4‐OH position of the Gal residue, thus potentially enabling the synthesis of longer and more complex GBS oligosaccharide structures.exo‐anti‐Φ for Ia and exo‐syn‐Φ for Ib. These unique structural features are expected to influence antibody recognition and immunospecificity. Studies are ongoing to map the relevant glycoepitopes. Moreover, all glycans were designed with a chemical handle for conjugation to carrier proteins for immunological evaluation. Results on structural and immunogenic studies will be reported in due course.Conformation analysis studies of the prepared oligosaccharides by NMR spectroscopy and MD simulations showed the impact of the GlcNAcβ1‐3Gal versus GlcNAcβ1‐4Gal connectivity in the orientation of the Neu5Acα2‐3Gal branching. The model, established from the single synthetic pentasaccharide repeating units, was used to study the conformational behavior of the GBS Ia and Ib polysaccharides, showing a different preferential shape for each polysaccharide with the Neu5Acα2‐3Gal linkages in L.D.B., D.O., M.M.R., R.C., and R.A. are employees of GSK groups companies. L.D.B. and R.A. are inventors of a patent related to the topic. R.A. is owner of GSK stocks.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.


A recent analysis shows aquatic productivity  is an important driver of CH4 emissions from lentic waters. Considering that aquatic productivity will increase over the next century due to climate change and a growing human population, a concomitant increase in aquatic CH4 emissions may occur. We simulate the eutrophication of lentic waters under scenarios of future nutrient loading to inland waters and show that enhanced eutrophication of lakes and impoundments will substantially increase CH4 emissions from these systems (+30–90%) over the next century. This increased CH4 emission has an atmospheric impact of 1.7–2.6 Pg C-CO2-eq y−1, which is equivalent to 18–33% of annual CO2 emissions from burning fossil fuels. Thus, it is not only important to limit eutrophication to preserve fragile water supplies, but also to avoid acceleration of climate change.Lakes and impoundments are an important source of methane , a potent greenhouse gas, from these systems over the next century. Local, regional, and global emission estimates of the carbonic greenhouse gases (GHGs), methane (CH4) and carbon dioxide (CO2), are reported regularly5 with estimates of nitrous oxide (N2O), another potent GHG produced in aquatic systems, also occasionally reported6. One of the most recent estimates of global GHG emissions from lakes and impoundments7 found that while absolute emission of CO2 is 5–10 times more than that of CH4 and N2O (in Tg of carbon (C) or nitrogen (N) per year), about 72% of the climatic impact of GHG emissions  from lakes and impounded waters is due to CH4. This is because CH4 is up to 34-times more potent as a GHG than CO2 and is responsible for approximately 20% of the overall additional atmospheric radiative forcing observed since 17508.The importance of lakes and rivers in the global carbon cycle is well established4 emissions7 contradicts earlier reports that CH4 and CO2 contributed equally to the global warming potential of GHG emissions from lakes and impoundments6. These previous estimates, however, were based on a simplistic upscaling method of extrapolating average observed emission rates to global lake and impoundment surface area without regard for driving mechanisms. The use of this type of upscaling, rather than a process-based approach, may be the cause for the large uncertainties surrounding global aquatic CH4 emissions9.This recent finding regarding the importance of aquatic CH4 emission rates are known to be controlled by a wide range of factors including lake depth10 and sedimentation rates11, to name a few, incorporation of drivers into approaches for estimating CH4 emissions has been limited by the lack of world-wide data on these factors. Remote sensing approaches are beginning to fill data gaps, however, and global datasets are now available for lake size and productivity, two important drivers of CH4 emissions12. DelSontro et al.7 used these global datasets, along with >8000 GHG flux measurements, and modeled emission rates as a function of system productivity and lake size. They found, as did a smaller study of impoundments13, that not only was CH4 the most important GHG emitted from aquatic systems in terms of climate impact, but that it rises exponentially with lake and impoundment chlorophyll a (chla) concentration, a proxy for productivity7. This is consistent with multiple lake studies showing that CH4 emissions positively correlate with productivity variables such as total phosphorus (TP) and chla16. Ultimately, these relationships reflect the link between an increase in organic substrate and enhanced rates of methanogenesis in productive aquatic systems18. This is an important finding because the productivity of inland waters is projected to increase in the coming decades.While CH19) will augment the release of sewage and agricultural fertilizers to inland waters by an estimated 1.23×–1.97×  by 2050 and 1.41×–3.19× by 2100 22. On a global scale, the spatial distribution of agricultural nutrient use correlates with that of surface water23, presumably because sustained crop growth requires both nutrients and ample water; therefore, increased global nutrient use is likely to affect inland surface waters. Second, increased storms and runoff will enhance nutrient losses from land by a mean 1.14× over the same period25, further increasing nutrient delivery to inland waters. Third, warming surface waters will increase global aquatic primary production by ~1.30× by 2100 26. These increases in eutrophication and consequent CH4 production will be augmented by the 1.10× net global expansion in lakes and impoundment spatial extent27 expected over the 21st century, resulting in more CH4-emitting surface waters. A further increase we cannot assess is enhanced nutrient concentrations in warm regions resulting from increased evaporation, which may be regionally important28, but has not been estimated globally. Projected increases in lake eutrophication are supported by a recent report that the fraction of lakes in the US that are oligotrophic decreased  from 25% of all surveyed lakes to 7% over just a 5-year period (2007–2012)29. Depending on the trajectory of human population growth and changes in climate and weather, multiplying nutrient effects by exacerbating factors  that are conservatively within the magnitude of increase predicted by diverse authors and models through 2100  up to 45 Tg CH4-C y−1, representing a 60% increase in emissions. Ebullition and total (diffusive + ebullitive) CH4 emission rates are more sensitive to enhanced eutrophication and will nearly double (mean increase of 1.86×) in a future environment with 3× greater nutrient loading to lakes and impoundments  are approximately 25% higher than the latest global estimates for lakes and impoundments (88.7 Tg C-CH4 y−1)9, which was based on a synthesis of measurements from mostly northern systems (>50°N) that used the traditional upscaling approach. Under a scenario of a tripling of nutrient loading, we could find the aggregate of global lakes and impoundments emitting more than double the current global estimate. More concerning yet is that even at the smallest increase in TP suggested by the literature (1.5×) we would see total global lake CH4 emissions rise to 141 Tg C-CH4 y−1, equivalent to global emissions from wetlands, which is the current single largest source of atmospheric CH4 (139 Tg C-CH4 y−1)9. A tripling of nutrient loading could result in total lake CH4 emissions being 1.5× higher than the current wetland emission estimate. It is possible, though unlikely, that improved nutrient management practices could reverse the eutrophication of lakes and impoundments, thereby reducing CH4 emissions. For example, a 25% reduction in global TP loading (0.75×) could prevent the emissions of 17 Tg CH4-C y−1  or up to half of the global oceanic and land carbon sinks (Table 34). The projected CH4 emission increases reported here  should be considered minimal because they do not account for the synergistic interaction between nutrients and water temperature on CH4 production rates39, future increases in impounded area27, or the effect of eutrophication on CH4 emissions from streams, rivers, small ponds, and wetlands. Eutrophication is considered to be one of the world’s most pressing environmental issues35 and, if it continues, will exacerbate global climate change.Our literature review indicates that global TP loading of inland waters will increase over the 21st century, stimulating aquatic productivity and CH36). Changes in TP concentration were translated to changes in chlorophyll a (chla) concentration using the non-linear TP—chla relationship derived from the data in McCauley et al.30  resulted in future chla concentrations that are, on average, 0.8×, 1.3×, 1.7×, 2.0×, and 2.2× that of the current global chla distribution. We propagated each of these chla distributions across the joint lake-size by chla distribution, resulting in five new distributions reflecting differing levels of eutrophication  for each lake-size by chla bin. Next, we multiplied the predicted areal emission rate for each bin by the total water body surface area corresponding to the bin. Finally, we summed the emissions across bins and scaled the result to an annual emission estimate for each emission mechanism .We calculated global CHnt Table . First, −1 and 5.7–216 µg L−1, respectively) were well within the range of values included in the literature used to parameterize the statistical models7  because of insufficient data coverage across the range of covariates for both system types. There is little evidence in the literature that suggests CH4 emission rates differ between natural lakes and impoundments, after system size and productivity are accounted for. Furthermore, impoundments constitute a small fraction of total inland water surface area31, therefore any systematic difference in the response of CH4 emission rate to size or productivity between natural lakes and impoundments will likely have little effect on cumulative global CH4 emissions from lentic waters.The statistical models used to predict CH4) emissions are presented in DelSontro et al.7 and are reproduced in Table 4 emission rates (mg CH4-C m−2 d−1) from lake size (km2) and/or chla (µg L−1).The models used to upscale lake and impoundment methane (CHSupplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1


The double shell structure design is thought to protect the magnetic Fe2O3 cores, and also act as a platform for depositing a second shell of TiO2, SnO2 or CeO2 metal oxide. To obtain a homogeneous metallic dispersion, the incorporation of 5 wt % of Pt was carried out over Fe2O3–SiO2–MeO2  structures modified with (3-aminopropyl)triethoxysilane by successive impregnation-reduction cycles. The full characterization by HR-TEM, STEM-EDX, XRD, N2 adsorption isotherm at −196 °C, TPR-H2 and VSM of the catalysts indicates that homogeneous core-shell structures with controlled nano-sized magnetic cores, multi-shells and metallic Pt were obtained. The nature of the metal oxide affects the Pt nanoparticle sizes where the mean Pt diameter is in the order: –TiO2–Pt > –SnO2–Pt > –CeO2–Pt. Among the catalysts studied, –CeO2–Pt had the best catalytic performance, reaching the maximum of conversion at 240 min. of reaction without producing hydrocinnamaldehyde (HCAL). It also showed a plot volcano type for the production of cinnamic alcohol (COL), with 3-phenyl-1-propanol (HCOL) as a main product. The –SnO2–Pt catalyst showed a poor catalytic performance attributable to the Pt clusters’ occlusion in the irregular surface of the –SnO2. Finally, the –TiO2–Pt catalyst showed a continuous production of COL with a 100% conversion and 65% selectivity at 600 min of reaction.The type of metal oxide affects the activity and selectivity of Fe Thectronics . Effortsctronics .2 as reducing agent, of the carbonyl bonds in α,β-unsaturated aldehydes towards the formation of non-thermodynamically favored unsaturated alcohols, which are valuable intermediates in pharmaceutical, cosmetic, agrochemical and resin industries is still a challenge [The selective catalytic hydrogenation of organic substrates containing a number of unsaturated functional groups is an important step in the industrial preparation of fine chemicals, increasing their relevancy for fundamental research in catalysis . The hethallenge . As a rehallenge , as showhallenge .2 [2 [2 [Among the transition metals, platinum (Pt) is the most-reported active phase in the hydrogenation of CAL. The selectivity of this active phase towards the formation of unsaturated alcohols has been attributed to the geometric and electronic defects of the metal  and can 2 , SnO2 [12 [2 , CeO2 [12 [2 [2 , ZnO [202 [2 [2 ,22,23,24core-shell catalysts as single unit with different components has been previously reported [2 nanocatalyst achieving over 95% conversion with 87% selectivity to HCAL in 5 h under 1 atm H2 pressure [III-based MIL-100) as a catalyst to produce COL at 96% selectivity and 95% of conversion of CAL in 4 h of reaction. However, the preparation process of MOF catalysts is relatively cumbersome, uneconomical and inapplicable in mass production.In the field of heterogeneous catalysis, the use of reported ,26,27. Fpressure . In the core-shell configuration, including a magnetic core isolated by a layer of oxide shell, which could act as support for Pt-metal nanoparticles (Pt NPs). The magnetic core-shell structure catalysts could provide the additional property of easy removal of the nanostructured catalyst by an external magnetic field [4 units with shared vertices [One way to produce improved Pt-based catalysts is to employ a ic field . The magic field . Moreoveic field . An altevertices .The surface physiochemical properties of small crystallites change dramatically at sizes lower than 5.0 nm, where the metal or metal oxide particles have low-coordinated surfaces, improving the catalytic activity . The dev2O3–SiO2–MeO2–Pt  nanomaterials as catalysts to be used in the selective hydrogenation of CAL. One of the most important steps to obtain the desired nanocatalyst structured microspheres is the coating process with TEOS for the formation of a silica shell as a protection layer for the magnetic core and a growth platform to provide for a homogeneous dispersal of a metal oxide shell on the Fe2O3–SiO2 surface. The synthesis of the catalysts, while employing stepwise impregnation-reduction deposition, provides highly dispersed Pt catalysts in a core-shell structure. The effect of the nature of the metal oxide MeO2  on well-stabilized magnetic core double shell structures in the selective hydrogenation of CAL was also described in this experiment.The aim of this work is to provide new magnetic multifunctional Fe®  and Merck®  Company and used without purification or treatment. These included iron chloride hydrate (FeCl3·6H2O), ethylene glycol, sodium acetate, poly(vinylpyrrolidinone) (PVP-K30), thetraethoxysilane (TEOS), ammonium hydroxide (NH3 28 wt %), ethanol, tetrabutyl orthotitanate (TBOT), Cerium nitrate (III) hexahydrate (Ce(NO3)3·6H2O), tin(IV) tert-butoxide (TTB), urea, D-xylose, toluene, (3-aminopropyl)trimethoxysilane (APTMS), K2PtCl6 and NaBH4.Reagents were provided by Sigma3O4–SiO2 structures were synthesized starting from Fe3O4–NPs coated with TEOS using the Stöber method in basic media [3·6H2O) was dissolved in an ethylene glycol and PVP-K30 mixture, and sodium acetate was added as a nucleating agent under vigorous magnetic stirring for 5 h. The solution was transferred to a Teflon-autoclave reactor  and heated at 200 °C for 8 h to produce a homogeneous and stabilized Fe3O4–NPs dispersion. Using magnetic separation, the dispersion was washed several times with an ethanol–water mixture before the coating procedure with Fe3O4–NPs and TEOS as silica precursor. Then, 2 mL of TEOS was added drop-wise to 300 mg of Fe3O4–NPs dispersed in a 180 mL ethanol, 60 mL water and 10 mL NH3 mixture, while stirring with mechanical agitation for 6 h at room temperature. The solid was separated by magnetization, washed three times with an ethanol–water mixture and dried at 50 °C for 12 h to produce Fe3O4–SiO2 nanostructures.The Feic media . The iro3O4–SiO2 particles dispersed in 200 mL of ethanol and 1 mL ammonium solution, which was stirred for 1 h at 300 rpm under mechanical agitation. The condensation of the respective alkoxides was carried out by the addition drop-by-drop of 40 mL of ethanol with 5% by volume of the (Ti or Sn) alkoxide precursor to the dispersion and heating to 60 °C for 4 h. The coating process with Ce was carried out using a solvothermal methodology, as previously reported [3O4–SiO2 particles dispersed in 300 mL of absolute ethanol sonicated for 30 min at room temperature. The addition drop-by-drop of 60 mL of an aqueous dissolution of 1.2 g urea, 6.0 g D-xylose and 1.0 g cerium nitrate was carried out under mechanical agitation for 3 h. The mixture of the Ce precursor was transferred to a Teflon-autoclave reactor  and heated at 160 °C for 20 h. Finally, the Ti, Sn and Ce containing dispersions with Fe3O4–SiO2–shells were washed three times with ethanol, dried overnight at 50 °C and calcined at 500 °C for 6 h. For comparison purposes, Fe3O4 NPs and Fe3O4–SiO2 structures were also submitted to the calcination process at 500 °C for 6 h to produce Fe2O3 and Fe2O3–SiO2 structures.The coating process with titanium and tin was carried out with a modified Stöber method , with 30reported , with 302O3–SiO2–MeO2  structures with APTMS under reflux in toluene for 24 h, was washed with a 3:1 mixture of acetone:toluene and dried at 50 °C for 12 h. Then, the deposition of Pt–NPs was carried out using an aqueous dissolution of K2PtCl6 as a precursor and NaBH4 as a reducing agent by successive impregnation-reduction steps until reaching a metallic loading of nominally ≈5 wt % Pt.To better-control metallic dispersion, the incorporation of Pt was carried out on functionalized APTMS structures. The functionalized procedure that was carried out contacted the Fe3:HCl mixtures and diluting them with doubly distilled water. The surface and pore size distributions by nitrogen adsorption isotherms were obtained using a Micromeritics apparatus Model ASAP 2010 at −196 °C . X-ray powder diffraction (XRD) pattern measurements were carried out with nickel-filtered CuK1 radiation (λ = 1.5418 Å) collected on a Rigaku diffractometer  in the 2θ range of 10°–80°. Temperature programmed reduction (TPR-H2) profiles were obtained on Micromeritics TPR/TPD2900 equipment  provided with a thermal conductivity detector in 5% H2/Ar flow at a rate of 40 mL·min−1 from room temperature to 800 °C and a 5 °C·min−1 heating rate. The surface charges of materials were determined by zeta potential in a Zetasizer NanoZS Marvern instrument  with a provided electrode tray. Magnetic measurements were carried out at room temperature in a vibrating sample magnetometer (VSM) Lakeshore 7400 series  with a maximum applied field of 20 kOe. The VSM had been previously calibrated with a pure nickel sphere.The synthesis of the core-shell structures was studied by high-resolution transmission electron microscopy (HR-TEM) measurement. Morphology was examined using a FEI Tecnai G2 F20 S-Twin microscope , and the microanalysis was performed using a scanning transmission electron microscope  and energy-dispersive X-ray spectroscopy (STEM-EDS) . The total Pt and Fe content was determined by inductively coupled plasma-optical emission spectrometry ) after dissolving the samples in 1:3 HNO® 5513 model reactor using 30 mg of catalyst weight and mechanical agitation up to 700 rpm. The reaction was performed at 100 °C, 2000 kPa of H2, with a substrate/catalyst mole ratio equal to 600 in a volume of 30 mL of cyclohexane. The reaction was monitored by taking non-invasive samples periodically from the reaction mixture at different reaction times until total cinnamaldehyde conversion. The product quantifications were carried out using a gas chromatograph  equipped with a capillary column (HP-5) and a flame ionization detector (FID).The catalytic activity evaluation of cinnamaldehyde was performed in a batch compact Parr2O3–SiO2–MeO2–Pt  catalysts were carefully designed and the main stages are shown in 3O4 nanoparticles were coated with TEOS to produce the starting core–SiO2 structure. The first layer of silica between the iron species in the core and the further deposition of the metal MeO2  oxide was designed to: (1) provide a regular, homogeneous and inert surface of SiO2 for metal oxide deposition, (2) inhibit the effect of the metal oxides changing the magnetic behavior of the iron species in the core and (3) evaluate the effect of the metal oxide in the catalytic performance of Pt without the effect of the iron species present in the core. Furthermore, the surface of the Fe2O3–SiO2–MeO2  structures were functionalized with APTMS before the impregnation of Pt, to enhance the metallic dispersion and to carefully control the Pt particle size with successive impregnation-reduction cycles.The different steps carried out to produce well-defined Fe3O4–NPs  at 200 °C during the solvothermal synthesis [3O4 nanoparticles are then coated by a first SiO2 shell by means of Stober’s method, generating a structure Fe3O4–SiO2core-shell  structures are shown in 2 oxides , the Fe3O4 core was completely oxidized to γ-Fe2O3, in all of the samples, with almost no changes in the morphology. The Fe2O3–SiO2–TiO2 and Fe2O3–SiO2–CeO2 structures showed regular spherical shapes, which were indicative of a uniform metal oxide deposition on the surface of –SiO2. The Fe2O3–SiO2–SnO2 displayed an irregular surface attributable to the presence of larger SnO2 crystals. This trend is in agreement with the tin-based core-shell reported by Pang et al. [2 on the titanium dioxide core surface.The HR-TEM micrographs of Feg et al. , where t2O3–SiO2–MeO2  structures appeared in the EDS signals. The presence of the respective metal oxides at the edges of the structures is indicative of a well-coated thin double shell. The thickness of the metal oxide shell is estimated by the differences in the average particle diameter of Fe2O3–SiO2  structures after counting more than 500 particles. The results obtained indicated a thickness of an average of ~20 nm for TiO2, ~30 nm for SnO2 and ~15 nm for CeO2. The similar thicknesses for TiO2 and SnO2 materials were a consequence of the reported modified-Stöber method [2 coating materials added with the solvothermal method.In 2O3–SiO2  in relatr method ,38 that 2O3–SiO2–MeO2–Pt  catalysts are shown in 2O3–SiO2–CeO2–Pt < Fe2O3–SiO2–SnO2–Pt < Fe2O3–SiO2–TiO2–Pt. This effect is mainly attributable to the nature of the metal oxide during the Pt deposition. In the catalyst syntheses, the Fe2O3–SiO2–MeO2  were contacted with the metal precursor (K2PtCl6) dissolved in aqueous solution to deposit the active phase on the shells . The core-shell materials can accumulate PtCl62− by a ligand-exchange process from the –NH2 surface group and/or adsorb the metal precursor on the surface of the metal oxide by electrostatic interaction. In 2O3–SiO2–MeO2  aqueous dispersion are displayed. For all of the solids, ZP is a positive value, ascribable mainly to the presence of protonated amine groups from APTMS on the core-shell surface (–NH3+), because the apK of APTMS is 10.6 [The HR-TEM micrographs of the Fe is 10.6 .TiO2 = 5.9 [SnO2 = 6.4–7.3 [CeO2 = 6.8–8.3 [+ and OH− with the solid and water [4, the nucleation of PtCl62− to produce Pt NPs was enhanced in Fe2O3–SiO2–CeO2, mainly by the positive surface charge of –CeO2 at pH = 6.5. In the case of Fe2O3–SiO2–SnO2, the IEP of –SnO2 was close to the pH of the materials’ dispersion . The Fe2O3–SiO2–TiO2–Pt prepared in one step showed a mean Pt crystal size of 13.4 nm with a wide particle size distribution, which confirmed the irregular nucleation when this metal was loaded on the TiO2 shell surface during the Pt deposition. Moreover, the multi-step metal precursor addition provided for, in the first cycle, the nucleation of smaller Pt NPs, which grew uniformly in every cycle as shown in the Moreover, the metal oxides in the surface have different isoelectric point values (IEP): where IEPO2 = 5.9 , IEPSnO2 6.4–7.3  and IEPC 6.8–8.3 . The IEPnd water . In our sion see  which is2O3–SiO2–MeO2–Pt  catalysts was determined by ICP spectroscopy and the results are in The elemental composition of the FeThe adsorption–desorption nitrogen isotherms of the materials presented a type II IUPAC classification , which w2O3 (JCPDS 39-1356) as crystalline phases with an absence of Fe3O4 (JCPDS 65-3107) completely oxidized to Fe(III)  structures, it can be seen that the coating process with the double shell of the metal oxide almost did not change the chemical composition of the crystalline Fe2O3 cores. There was only the apparition of segregated phases for the SnO2 structures, and the lack of detection of crystalline structures for TiO2 and CeO2 indicated that they were present with a high degree of dispersion . It has been reported for –TiO2 [2 coating process. On the other hand, for –SnO2, the appearance of segregated phases of SnO2 rutile with a tetragonal crystal system [2 diffraction peaks is in agreement with the HR-TEM results, regarding a more heterogeneous second coating process attributable to the behavior of the tin precursor to form polycrystalline SnO2 nanoparticles [The XRD profiles of the Pt and non-Pt content structures are shown in  Fe(III) . For thel system  has alsoarticles .2O3–SiO2–MeO2–Pt  showed the same XRD profile as that of the pristine core-shell materials. This confirmed that the NaBH4 used to perform the reduction of the metal precursor had no effect on the structure of the Fe2O3–SiO2–MeO2 . However, the diffraction line at 39.6°, which corresponded to the metallic Pt(111) with a face-centred cubic structure, was too weak to be used to determine particle size in the case of Fe2O3–SiO2–MeO2–Pt . Indeed, it is well recognized that the XRD technique is limited by the size of the particles. In this case, the size of the particle is less than 5 nm, which was in agreement with the HR-TEM characterization  catalysts in 2O3–NPs is also shown. The additional experiment to produce Fe2O3–NPs was carried out on non-coated Fe3O4–NPs submitted to an oxidation treatment. The Fe2O3–NPs profiles indicated a first reduction step at 370 °C from hematite Fe2O3 to Fe3O4, followed by a broad reduction process started above 400 °C that can be deconvoluted into two peaks attributable to the Fe3O4→FeO and FeO→Fe steps [2O3–SiO2–MeO2–Pt;  catalysts to the Fe2O3–NPs profile was a consequence of the larger content of Fe2O3 compared to the TiO2, SnO2 and CeO2 oxides; the reduction process of TiO2, SnO2 and CeO2 was masked by the reduction process of Fe2O3. Unfortunately, the broadening of the peaks of 4 at room temperature is the metallic state. To support this result, after the TPR of the –CeO2–Pt system, an oxidation process in air at 300 °C for 1 h was carried out before a second TPR profile  structures display a ferromagnetic behavior with a magnetic saturation of ~40 emu·µg−1. The remanence and coercivity properties of the hysteresis loop  catalysts are shown in The selective catalytic hydrogenation of CAL to COL is an ambitious challenge and aspects such as the nanometric size (1–10 nm) of the active sites, surface structure, metal-support interactions and electronic effects become more important in achieving it , and the2O3−SiO2−CeO2–Pt was used as catalyst, while the Fe2O3−SiO2−TiO2–Pt system only reached 78% conversion and 65% selectivity for COL during the same time of reaction. In contrast, the conversion decreased to 40% and the selectivity value lowered to 50% for the Fe2O3−SiO2−SnO2–Pt system.The calculated pseudo-1st-order reaction rate constants, the initial reaction rates, maximum conversions at 500 min. and selectivity are shown in 2, –SnO2 and –CeO2 as shells was designed with the aim to increases the selectivity towards COL product, due to they have been reported as non-inert supports which could provide SMSI effect even at room temperature [For the selective hydrogenation of CAL, it is well-documented that the particle size of active metal species can exert vital impacts on their catalytic performance . Generalperature .2O3–SiO2–CeO2–Pt had the best catalytic performance. Due to the different sizes of Pt particles, there was a size dependence of hydrogenation activity among these catalysts. However, the pseudo-1st-order reaction rate constant follows the trend k–CeO2 > k–TiO2 >> k–SnO2, which is different from the trend for the Pt mean particle size, where –CeO2–Pt > –SnO2–Pt > –TiO2–Pt. This behavior can be explained by the nature of the –SnO2 shell in the Fe2O3–SiO2–SnO2–Pt. The –SnO2 shell possess an irregular surface with evident formations of SnO2 clusters with particle sizes larger than the Pt NPs, as was demonstrated by HR-TEM and XRD characterization. Despite the production of Pt NPs with a mean size of 3.5 nm  results from the HCAL hydrogenation with non-consumption of COL at 180 min which are in agreement with the preferred C=O adsorption on the catalyst surface.In the selective hydrogenation of CAL, it has been reported that the adsorption of the C=O bond towards the formation of the unsaturated alcohol is favored on larger metallic particle sizes ,48,49,502O3–SiO2–SnO2–Pt catalyst, the competitive adsorption of the substrate by the SnO2 crystallites and the homogeneous and narrow Pt particle sizes produced HCAL and COL in almost the same proportion. Moreover, although CAL hydrogenation does not require acid sites, in the smallest Pt nanoparticles, the Lewis acid properties of SnO2 influenced the reaction rate and the selectivity of the process by modifying the adsorptive properties of Pt because of surface electron density [Finally, for the Fe density . Therefo density .2O3–SiO2–MeO2–Pt  magnetic core-shell catalysts were successfully prepared. The use of –SiO2 shells provided a protected magnetic core, and its structure ensured the deposition of a second metal oxide shell, which preserved the shape of the Fe2O3–SiO2 structure. The Pt metal nanoparticles deposited in continuous cycles provided support to the catalyst with a homogeneous metal dispersion on the –MeO2 surface . In addition, the nature of the metal oxide affected the Pt mean particle diameters in the order of –TiO2–Pt > –SnO2–Pt > –CeO2–Pt. This trend was attributed to the IEP of the solids, which affected the interaction of metal precursors with the surfaces of the metal oxide shells. Consequently, the catalytic activity showed the trend of –CeO2–Pt > –TiO2–Pt > –SnO2–Pt, which is line with the physicochemical properties of the core-shell catalysts. In the case of –CeO2–Pt, an excellent activity and a continuous decrease in the production of COL was attributed to the Pt mean particle size (2.6 nm), which enhanced the consumption of both CAL and COL to produce of HCOL at a higher CAL conversion. In the opposite direction, –SnO2–Pt showed a minor activity in comparison with the other catalysts, mainly attributed to the irregular SnO2 shell surface, which allowed for the formation of Pt nanoparticles inside the SnO2 crystals, thereby blocking the active phase, which decreased the catalytic performance. The large stability towards the production of the unsaturated cinnamic alcohol of the –TiO2–Pt catalyst is attributed to particle size (4.9 nm) and the chemical properties of the TiO2 loading shell favoring the adsorption of CAL by the C=O bond, inhibiting the coplanar adsorption of CAL to produce HCAL and/or HCOL. This study suggests both Pt nanoparticles size and SMSI effects have resulted beneficial in selective hydrogenation of CAL to produce COL as the main product.Fe


The system was tested in a sugarcane field continuously monitoring N2 and N2O fluxes for 7 days following fertilization using a fully automated measuring cycle. The detection limit of the Field-IRMS proved to be highly sensitive for N2 (54 g ha−1 day−1) and N2O (0.25 g ha−1 day−1) emissions. The main product of denitrification was N2 with total denitrification losses of up to 1.3 kg N ha−1 day−1. These losses demonstrate sugarcane systems in Australia are a hotspot for denitrification where high emissions of N2O and N2 can be expected. The new Field-IRMS allows for the direct and highly sensitive detection of N2 and N2O fluxes in real time at a high temporal resolution, which will help to improve our quantitative understanding of denitrification in fertilized cropping systems.The use of synthetic N fertilizers has grown exponentially over the last century, with severe environmental consequences. Most of the reactive N will ultimately be removed by denitrification, but estimates of denitrification are highly uncertain due to methodical constraints of existing methods. Here we present a novel, mobile isotope ratio mass spectrometer system (Field-IRMS) for  As a result, the global N cycle is even more severely altered by human activity than the global carbon (C) cycle, and excess N pollution has been identified as one of the three global environmental issues whose ‘planetary boundary’ has been surpassed1. Once an N atom is in a reactive form (Nr), it cascades through different eco-system compartments, contributing to a number of environmental problems2. Most of the anthropogenic Nr will be removed by denitrification, the reduction of oxidized forms of inorganic N to N2O and, ultimately, inert N2. However, estimates of terrestrial sinks for Nr are highly uncertain and the magnitude of total denitrification losses (N2 + N2O) is virtually unknown for the vast majority of agricultural soils. While there is increasing research investigating the soil-atmosphere exchange of N2O in fertilized agro-ecosystems, information on N2 emissions and related N2:N2O partitioning data is still scarce3. The main reasons for this uncertainty are that denitrification exhibits a very high spatial and temporal variability, but foremost that it is extremely difficult to measure N2 emissions against the huge atmospheric N2 background4.In the last 50 years, the use of synthetic nitrogen (N) fertilizers, cultivation of leguminous crops, and fossil fuel combustion have more than doubled the input of reactive nitrogen (N2 and N2O in the field: (1) the Acetylene Inhibition Technique (AIT) and (2) the 15N-gas flux method. The AIT is historically the most widely applied method to quantify denitrification in the field due to its relatively simple and inexpensive application. However, in recent years it has been shown that the AIT leads to a systematic and irreproducible underestimation of denitrification rates due a number of limitations6, which preclude reliable estimates of total denitrification losses7. The shortcomings of the AIT therefore demand the use of alternative methods when quantifying denitrification losses from agro-ecosystems. The 15N-gas flux method avoids the problems of the AIT, but requires expensive equipment as well as the costly application of highly 15N enriched fertilizer. 15N is added as highly enriched (20–80 atom %) fertilizer to a designated plot of soil which is then enclosed with a chamber prior to gas sampling. N2 and N2O gas production following denitrification is measured by quantifying the increase in 15N-labelled gases in the headspace using Isotope Ratio Mass Spectrometry (IRMS)8. The major challenges of the 15N tracing technique are (1) achieving and assessing uniform distribution of the isotopically labelled N in the soil (2) artificial stimulation of denitrification by the added tracer (3) high detection limits for N2 fluxes due to analytical limitations in the m/z 30 measurements with the IRMS. The uniform distribution of 15N in the soil nitrate (NO3−) pool is usually achieved by applying 15N enriched fertilizers with water, resulting in increased soil moisture. Under field conditions it is unlikely to achieve homogeneity of the added 15N tracer with the soil NO3− pool, but it has been shown that accurate estimates of gaseous N losses can be made without uniform distribution of 15N in the soil when large amounts of highly enriched N fertilizer are applied9. Consequently, the 15N gas flux method is most applicable for fertilized cropping systems where large amounts of enriched N fertilizer with water can be applied and high fluxes of N2 and N2O can be expected.Currently, there are only two main approaches for the direct quantification of denitrification N gas formation including N2O fluxes it has been shown that daily sampling is required to achieve annual N2O fluxes within 10% of the best estimate, while weekly to monthly sampling in cropping systems with highly episodic emission events can result in an overestimation of 256% and 935%, respectively10. To address this problem more and more studies are using automated static chamber systems that can capture highly episodic emissions, and the characteristic diurnality in emissions, by multiple sampling events over any 24-hour period. Such “high-frequency” measurements of N2O have significantly improved N2O flux estimates. However, such instrumentation has not been available for both N2 and N2O measurements.Another constraint for field measurements of denitrification is the high temporal  variability of N gas emissions that compromise flux estimates if not carried out with an adequate frequency. For N2 and N2O fluxes in real time at a sub-daily resolution. The Field-IRMS is housed in an air-conditioned trailer and can be transported to the desired field location. We tested the performance of the Field-IRMS investigating the effect of two different fertilizer rates on the magnitude and N2:N2O partitioning of denitrification losses from a sugarcane field in subtropical Australia.Here we present a novel, mobile isotope ratio mass spectrometer (Field-IRMS) coupled to a fully automated chamber system, measuring N2 and N2O fluxes in real time at a sub-daily resolution. The measuring principle is based on the 15N gas flux method and uses highly 15N enriched (20–80 atom % 15N) fertilizer added to the soil which is then enclosed with a chamber for a designated time period. N2 and N2O gas production from denitrification is measured by quantifying the increase in 15N-labelled gases in the chamber atmosphere using IRMS8.The new Field-IRMS was developed by the Queensland University of Technology (QUT) in collaboration with Sercon  and is housed in an air-conditioned trailer which can be transported to the desired field location. The system uses a standard continuous flow IRMS coupled to a fully automated chamber system, measuring NThe new Field-IRMS comprises three main parts: The automated chambers, the sampling unit, and a Sercon Continuous Flow 20–22 IRMS with a custom built trace gas preparation unit (TGP) Fig. .Figure 12 and N2O fluxes from soils. It consists of eight automated acrylic static chambers (500 mm × 500 mm × 150 mm) that are fixed on stainless steel bases inserted permanently into the soil to a depth of 100 mm and sealed air-tight during sampling by two lids that open and close via pneumatic actuators. It was assumed that molecular diffusion created homogeneous gas concentrations in the chamber headspace at sampling and no fan to mix the air inside the chamber was installed. To limit the temperature increase in the chambers during the closure times the acrylic panels on the side of the chambers were tinted while the panels on the two lids of each chamber were covered with reflective foam insulation. Each chamber is connected to a sampling control system by a non-reactive Teflon coated sample line and two pneumatic air lines (for lid open and shut operation).The system utilises the static closed chamber technique  to capture N2 analyser for the measurement of soil CO2 fluxes , and a filtering system  to the TGP from the chamber selected. For reference gas injection a three port valve is used to isolate the chamber valves from the reference gas valve stream. An adjustable flow meter  ensures constant flow from the sampled chamber headspace. A heated 0.1 micron coalescing filter and Nafion™ dryer filter system  removes particulate and water vapour from the gas sample.The sampling system houses the sample pump, sample valves, reference gas valves, sample flow meter, an infra-red COtem Fig. . It is d2O sample loop and 50 µL N2 sample loop  of the TGP, along two separate pathways: an N2 + N2O path and an N2O path.The custom built TGP works on the same principle as the standard Sercon Cryoprep trace gas module , which isolates and purifies discreet amounts of trace gases to be transferred to the IRMS for isotopic analysis. The installation of two six-port Valco valves  allows the incoming sample flow to fill a 200 mL Noop Fig. . Once th2 + N2O path, the sample is passed through a Nafion™ tube, a reduction oven and a GC column  packed GC column with a diameter of ¼” and length of 20 cm separates N2 from any remaining O2.Along the Numn Fig. . The Naf2O path, a Nafion™ tube, CO to CO2 converter, CO2 scrubber, and zeolite N2O trapping system are installed. Once the N2O sample is transferred to the helium carrier flow it first passes through the nafion tube to remove any residual water. The sample then passes through a two-part carbon scrubber: any CO in the sample is converted to CO2 using a Schuetze reagent column, followed by a CarbosorbTM packed column removing CO2  trap. This requires a constant supply of LN which is not practical at remote field sites. The LN trap has therefore been replaced with a zeolite-based N2O trapping system. The sample is passed through a cooled zeolite column for 423 seconds which effectively traps N2O. Once the N2O is trapped, the zeolite trap is isolated from the helium carrier stream by switching the respective Valco valve. The zeolite trap is then heated for 125 seconds, releasing the trapped N2O. The now concentrated N2O is then directed back into the helium carrier and transferred to the IRMS. To trap the N2O, the zeolite is cooled to near 0 °C by using Peltier CPU coolers . Standard cartridge heaters  are used to rapidly heat the zeolite column to 150 °C and release the N2O from the zeolite trap.In commercially available trace gas preparation units, the isolation and concentration of N2 and N2O fluxes are measured using a fully automated sampling cycle during which four gas samples are taken sequentially from each chamber over a 201.67 min period with a total closure time of 221.83 min. During each of the sampling runs different reference standards are analysed alternating with the samples. The reference standards consisted of ambient air samples and a 1 ppm N2O standard, injected from a certified calibration gas cylinder . The ambient air samples were used to provide an isotopic reference for the N2 measurements, and the N2O calibration standard was used to provide a reference for the N2O measurements. More details of the automated sampling cycle are provided in the Supporting Information.The N2O (N2 + N2O) are measured as N2 in the IRMS, while N2O is measured directly as N2O. For N2O, the ion currents (I) at m/z 44, 45 and 46 enabled the calculation of the molecular ratios 45R (45I/44I) and 46R (46I/44I), giving the fraction of N2O derived from the NO3− pool undergoing denitrification of the enrichment aD11. The concentration of N2O is calculated based on measured  and calculated  ratios of N2O isotopologues in each sample compared to those in of the 1 ppm reference12. For N2, the I at m/z 28, 29 and 30 enabled 29R (29I/28I) and 30R (30I/28I) to be calculated, with differences between ambient and enriched atmospheres expressed as Δ29R and Δ30R. The flux of N2 + N2O was calculated using Δ30R and aD13, assuming that both N2O and N2 were produced from a single source pool. Flux rates of N2O were calculated from the slope of the linear increase in gas concentration during the closure period. Fluxes of N2 were then calculated as the difference between N2 + N2O and N2O fluxes. The coefficient of determination (r2) was used for both N2 + N2O and N2O as a quality check for linearity and flux rates were discarded if r2 was <0.80 . Fertilizer  was applied to the chamber bases at a rate of 50 kg N ha−1 (50 N) and 100 kg N ha−1 (100 N), with four replicates arranged randomly along two sugarcane rows. The fertilizer was dissolved into 1 L of water and applied by hand, to each chamber, to ensure even distribution. Prior to the application of the fertilizer 3 L of water was applied to each chamber to ensure a wet soil profile while minimizing the potential for leaching losses of 15N labelled fertilizer. Following the application of the fertilizer, a 5 cm thick layer of sugarcane trash was placed in each chamber and irrigated with a further 6 L of rainwater. Therefore, a total of 10 L irrigation was added to each chamber, which simulated a 50 mm rain event to completely saturate the soil. The addition of the sugarcane trash is consistent with farming practices in the growing region. More details of the experimental site are given in the Supporting Information.To test the performance of the novel system under field conditions we investigated the effect of two different fertilizer rates on the magnitude and the partitioning of N2 and N2O flux measurements, final soil samples were taken from the profile in 10 cm increments to a depth of 50 cm.Initial soil samples were taken to 10 cm depth before fertilizer application and after four days from each edge and the centre of each soil frame using a 5 cm soil auger. One day after the final N4+ and NO3− in a 20 g subsample of soil. The subsamples were mixed in 100 mL of KCl (1:5 solutions) and shaken for one hr before being filtered through Whatman no. 42 filter paper. The KCl extracts were then analysed for N-NH4+ and N-NO3− on an AQ2+ discrete analyser .The soil samples were analysed for total mineral N by extracting the NH15N enrichments of the N-NO3− and N-NH4+ was determined for the 0–10 cm samples by the diffusion method15. After the diffusion process was complete, the samples were analysed on a Sercon 20–22 IRMS.The Soil moisture and temperate was measured at a depth of 10 cm in four of the eight chambers using automatic probes . These probes collected moisture and temperature reading every 5 seconds for the duration of the experiment. Chamber temperature was also recorded in one chamber of each set.2 and N2O fluxes were examined by analysis of variance (ANOVA) (P < 0.05). Changes over time were analysed using one way repeated measures ANOVA (P < 0.05), where time was the repeated factor. Values in the figures represent means ± standard error of the mean.Statistical analyses were conducted with SPSS 22.0 . Treatment effects on N2 analysis was evaluated using the between – batch standard deviation of ambient air samples (n = 126) included in the sampling run over the seven-day experimental period. The detection limit (DL) of N2 was calculated based on the standard deviation (SD) of these atmospheric air samples. The SD was 2.85 * 10−07 and 8.55 * 10−07 for the true mass ratios 29R (29/28) and 30R (30/28), respectively. The detection limit was calculated using equation where T is the student’s t value at a 95% confidence level at n-1 degrees of freedom and SD is the respective standard deviation. The between batch DL of the Field-IRMS at the 95% confidence interval (n = 126) for 29R was 4.70 * 10−07 and for 30R was 1.41 * 10−06. This equates to a method DL (MDL) for N2 fluxes of 54 g ha−1 day−1 of N2 based on a NO3− 15N pool enrichment of 50% and a closure time of 201 minutes.The precision of the Field-IRMS for Nples n = 26 includ2O measurements was determined based on repeated analyses of an N2O gas standard (n = 12) with a concentration of 1 ppm at natural abundance injected into the TPG unit. The SD was 3.79 * 10−04 and 9.08 * 10−05 for the true mass ratios 45R (45/44) and 46R (46/44), respectively. The SD of the N2O concentration was 0.013 ppm, which equates to a DL at a 95% confidence interval of 0.02 ppm  and from 15N2 were not significantly different, except for two days in each treatment  accounted for 78% (50 N) and 91% (100 N) of total N2O emissions. N2 was the main product of denitrification in both treatments, with an N2/(N2 + N2O) product ratio of 0.93 and 0.90 of the total in the 50 N and 100 N treatment, respectively. Cumulative N2 emissions exceeded N2O emissions by a factor of 10 ± 2 in the 50 N treatment and a factor of 17 ± 5 in the 100 N treatment. Of the cumulative denitrification losses (N2 + N2O) 77% and 80% were fertilizer derived in the 50 N and 100 N treatments, respectively.Total N2 fluxes shows a pulse of N2 emissions after fertilization and of irrigation  shows N2 as the main product of denitrification over the entire course of the experiment in both treatments  was slightly lower than the theoretical 15N enrichment calculated from the addition of labelled fertilizer at 60% atom 15N-NO3− to the existing soil mineral N pool (1.92 kg NO3− N ha−1) at natural abundance 20; but higher than those reported by a recent study that adapted the 15N gas flux method for application in unfertilized land use systems (1.0 g N ha−1 day−1 for N2 and 0.05 * 10−3 g N ha−1 day−1 for N2O)21. However, it needs to be noted that the MDL of the 15N gas flux method not only depends on the sensitivity of the IRMS and can potentially be lowered by (1) using a higher 15N enrichment of the applied fertilizer (2) decreasing the chamber volume and (3) increasing the closure time of the static chamber. All these parameters need to be adjusted according to the experimental set-up, in particular the expected N2 and N2O emission range.This precision of the IRMS translates to a detection limit of 53.9 g ha23. We chose to use relatively large chambers , to reduce the error associated with environmental variables such as temperature, the N2O diffusion gradient within the soil and potential gas leaks into the chamber24. Furthermore, the larger chambers account better for spatial variation, known to be one of the great challenges in measuring denitrification in the field25, but require rather large amounts of costly 15N fertilizer.To ensure high-quality measurements are provided, our automated chambers were designed using state of the art quality protocols15N gas flux method in fertilized cropping systems typically only take two gas samples (t0 and t1) from the chamber over a 1 to 3 h closure time27, but in unfertilized systems closure times up to 20 h have been reported28. Long closure times have been shown to lead to an underestimation of denitrification rates due to decreasing concentration gradients between soil and chamber atmosphere, causing lowering of surface fluxes with increasing chamber deployment time and ideally, closure times should not exceed one hour29. This means that for field measurements closure times should be minimised according to the expected N2 and N2O emission range but must be long enough so that sensitivity is not compromised. Our systems offers the advantage that four samples are taken over a closure period of 201 min which a) allows to check for the linearity of the evolved N2 and N2O gases over the deployment time of each individual chamber, b) increases the precision of the flux determination and c) enables a better quality control of the calculated flux including the detection of outliers.Field studies using the 2 fluxes from fertilized cropping systems typically used a sampling regime for N2 measurements ranging from daily to weekly measurements, which cannot fully account for the high temporal variation of denitrification. Consequently, the use of an automated system will significantly improve estimates of denitrification from fertilized cropping systems. Such data is urgently needed for the identification of sustainable cropping practices that reduce GHG emissions and N pollution from agricultural systems while increasing food security under the auspices of climate change.Another key advantage of the Field-IRMS is that it eliminates any errors associated with the manual extraction, transport, storage and injection of gas samples and accounts for diurnal variations of the measured N gas fluxes. The limited amount of studies that reported N15N gas flux method needs to be revisited since recent research shows that field surface fluxes of 15N-labelled N2 and N2O emitted from 15N-labelled soil NO3− can severely underestimate denitrification due to subsoil flux and accumulation in pore space29, suggesting that denitrification in fertilised cropping systems could even be more important than previously thought. Ideally, future studies on denitrifcation using the 15N-gas flux method can be combined with an estimation of subsoil fluxes.However, the accuracy of the 2 and N2O fluxes could be observed in both fertilizer treatments with 100% of the N2O measurements and 93% of the N2 measurements showing a significant linear increase in the chamber headspace, demonstrating the suitability of the new Field-IRMS to continuously measure N2 and N2O emissions in fertilized cropping systems. Denitrification was identified as a major loss pathway of fertilizer N with total denitrification losses (N2 + N2O) of 2.10 ± 0.46 kg ha−1 and 6.12 ± 0.99 kg ha−1 over the seven-day period for the 50 N and 100 N treatments. These high N losses are in the range of previously reported values from sugarcane cropping systems in Australia30. The only other study that used the 15N gas flux method in a sugarcane field reported total denitrification losses ranging from 7.6 to 9.2 kg ha−1 over nine days after the application of 160 kg N ha−1 K15NO3 (98.5 atom %)27. These results highlight that sub-tropical sugarcane systems in Australia can be a hotspot for soil denitrification where high denitrification losses can be expected in particular, since the high denitrification events occurred after 50 mm and 25 mm irrigation, respectively. Such rainfall events are characteristic for the humid subtropical summers in the study region and generally occur numerous times during the sugarcane growing season.Over the 7-day field campaign, significant N2 and N2O emissions. High WFPS and NO3− availability together with soluble C from the sugarcane trash created conditions favouring denitrification, resulting in emissions of up to 1.25 kg N ha−1 day−1 of N2 and N2O combined. Following this first irrigation N2 and N2O emissions decreased over the first three days as the soil dried, while the N2:N2O ratio shifted towards N2 in the 50 N treatment. A second irrigation on the night of the third day resulted in a significant increase of N2 while there was only a minor effect on N2O emissions. Such a burst of N2 and N2O emissions following irrigation and fertilization has been observed in other cropping systems and is typically caused by O2 depletion due to increased WFPS26, and further amplified by increased N substrate availability and the formation of anaerobic microsites due to enhanced microbial activity and subsequent O2 consumption32. The increase in the N2/N2 + N2O product ratio over time reflects increasing anaerobic conditions in the soil matrix along with enhanced N2O reductase activity, causing a shift towards complete denitrification to N2. The lower N2/(N2 + N2O) product ratio in the 100 N treatment can probably be attributed to higher soil NO3− concentrations33  product ratio of 0.93 and 0.90 in the 50 N and 100 N treatment, respectively. These ratios are within the range of reported product ratios from other field studies that used the 15N gas flux method in fertilized cropping systems26, and agree well with the average product ratio of 0.85 ± 0.061 for fertilized agricultural soils by a recent meta-analysis that summarized available datasets where N2 emissions have been either measured by 15N-labelling approaches or with the gas-flow helium incubation method35. However, it needs to be noted that the magnitude and the N2/(N2 + N2O) product ratio of denitrification is known to vary substantially depending on soil conditions and is primarily influenced by the soil nitrate content, the availability of easily degradable C substrates, soil moisture, soil oxygen content, the genetic potential for N2O reduction and soil pH39. Consequently, longer-term measurements from different sugarcane sites are ideally required to come up with robust estimates of N2/(N2 + N2O) product ratios and total denitrification losses for sugarcane cropping systems.Denitrification was dominated by N15N gas flux method is the determination of the 15N enrichment of the source pool (NO3−). We used the isotopic signatures of 45N2O:44N2O and 46N2O:44N2O in the headspace gas to calculate the 15N enrichment of the NO3− pool undergoing denitrification aD. While there was no statistically significant difference between the 15NO3− pool undergoing denitrification derived from 15N2O (aD) and from 15N2 (XN15)  Fig. , XN15 wa15N fertilizer aD was 0.44 and 0.47 for the 50 N and 100 N treatment, respectively. This was lower than the theoretical value of 0.55 calculated by mass balance from the soil NO3− content before fertilizer application and the amount and enrichment of the labelled fertilizer added to soil, indicating increasing nitrification or heterogeneity in the initial NO3− distribution, and thus a higher contribution of non-fertilizer NO3− to the denitrifying NO3− pool. There was no significant change in aD over the course of the seven-day experiment, while measurements of the NO3− pool enrichment determined by the diffusion method following KCl extraction on day 4 and 8 of the experiment showed significantly lower values and a declining trend over time. The results of the diffusions show a dilution of the soil NO3− pools, most likely from nitrification of unlabelled NH4+. However, this did not change the enrichment of the active denitrifying pool, which indicates a spatial separation of denitrification and nitrification, occurring in different micro-sites within the soil matrix. It has been shown that direct measurement of 15N-NO3− using extraction and diffusion does not reflect the enrichment of the active NO3− pool undergoing denitrification, and the use of these data in denitrification rate calculations has been shown to result in unrealistically high N2 flux rates41.On the first sampling day after application of 29R, Δ30R and aD, allowing to (a) test key assumptions of the 15N gas flux method and (b) to calculate N2 fluxes based on 4 point measurements. This approach represents a significant improvement compared to two point measurements and increases the precision of the flux determination. There is however still room for improvement regarding the sensitivity of the IRMS and the time needed per sample. Further improvements of the TGP and the sampling cycle including the integration of reference gas pulses injected directly into the IRMS and an adaption of the closure time in high emitting agro-ecosystems could further increase the temporal resolution of the Field-IRMS. Another promising approach could be to use this system with a reduced N2 atmosphere in the chamber headspace. This method has recently been used in field and lab studies and shown that it can significantly reduce the detection limit for N2 fluxes42. However, it requires a rather complex set-up involving flushing of the headspace and the sub-soil with an artificial gas mixture that needs to be coupled to the automated sampling system. Improving and combining these novel approaches to measure N2 could significantly improve our understanding of denitrification in fertilized and even natural agroecosystems.The automated sampling cycle of the Field-IRMS provides robust estimates of ΔSupporting Info