We determine energies for the interacting longitudinal optical phonon modes to be 11.5 and 15.3 meV, and Fröhlich coupling constants of ∼40 and 60 meV for the lead iodide and bromide perovskites, respectively. Our findings correlate well with first-principles calculations based on many-body perturbation theory, which underlines the suitability of an electronic band-structure picture for describing charge carriers in hybrid perovskites.Phonon scattering limits charge-carrier mobilities and governs emission line broadening in hybrid metal halide perovskites. Establishing how charge carriers interact with phonons in these materials is therefore essential for the development of high-efficiency perovskite photovoltaics and low-cost lasers. Here we investigate the temperature dependence of emission line broadening in the four commonly studied formamidinium and methylammonium perovskites, HC(NH Phonon scattering limits charge transport in perovskite solar cells, yet the interactions involved are still poorly understood. Here, Wright et al. show by photoluminescence measurements and first-principles calculations that longitudinal optical phonons dominate the electron-phonon coupling at room temperature. FAPbI3 has the advantage of a smaller bandgap than MAPbI3 (1.48 versus 1.57 eV), making it more suited for use in single-junction solar cells3 in its perovskite phase at room temperature78− and Br− have been investigated for use in tandem solar cells56Hybrid lead halide perovskites have attracted intense research activity following their first implementation as light absorbers in thin-film solar cellsium (HCNH or FA+),ium (HCNH or FA+),The success of hybrid perovskites in photovoltaic applications has been widely attributed to their high absorption coefficients across the visible spectrum413416μ, which was found212223Tm with m in the range between −1.4 and −1.6. Several groups161718μ∝T−3/2. Although such behaviour may be adopted by non-polar inorganic semiconductors such as silicon or germanium182718Despite the importance of electron–phonon interactions to the optoelectronic properties of these materials, currently no clear picture has emerged of which mechanisms are active. To address this issue, a number of studies have examined the temperature dependence of the charge-carrier mobility ab initio calculations for MAPbI3. To elucidate how charge-carrier–phonon interaction strengths depend on perovskite composition, we examine FAPbI3, FAPbBr3, MAPbI3 and MAPbBr3, which represent a comprehensive set of the most commonly implemented organic and halide ingredients in hybrid perovskites. We show that although the choice of organic cation has relatively little effect on the Fröhlich interactions, bromide perovskites exhibit higher Fröhlich coupling than iodide perovskites as a result of their smaller high-frequency values of the dielectric function. Overall, our results conclusively demonstrate that electron–phonon coupling in hybrid lead halide perovskites follows a classic bandstructure picture for polar inorganic semiconductors, which are dominated by Fröhlich coupling between charge carriers and LO phonon modes in the high-temperature regime.Here we clarify the relative activity of different charge-carrier scattering mechanisms in hybrid lead halide perovskites by investigating charge-carrier scattering through an analysis of the photoluminescence (PL) linewidth as a function of temperature between 10 and 370 K. By carefully examining the low-temperature regime in which thermal energies fall below those of high-energy LO phonon modes, we are able to clearly separate competing contributions from charge-carrier interactions with acoustic and optical phonons. We are therefore able to show unambiguously that Fröhlich coupling to LO phonons is the predominant cause of linewidth broadening in these materials at room temperature, with scattering from acoustic phonons and impurities being a minor component. We further demonstrate excellent agreement between the experimentally determined temperature dependence of the PL linewidth and theoretical values derived from 3, FAPbBr3, MAPbI3 and MAPbBr3 thin films over temperatures from 10 to 370 K in increments of 5 K  on temperature, which can be expressed as the sum over the various contributions42Analysis of temperature-dependent emission broadening has long been used to assess the mechanisms of electron–phonon coupling in a wide range of inorganic semiconductorsГ0 is a temperature-independent inhomogeneous broadening term, which arises from scattering due to disorder and imperfections42Гac and ГLO) are homogeneous broadening terms, which result from acoustic and LO phonon (Fröhlich) scattering2842γac and γLO, respectively. Electron–phonon coupling is in general proportional to the occupation numbers of the respective phonons, as given by the Bose–Einstein distribution function45ELO is an energy representative of the frequency for the weakly dispersive LO phonon branch18kBT over the typical observation range, a linear dependence on temperature is generally assumed46Ab initio calculations of the relevant phonon energies and occupation numbers are shown in Гimp, phenomenologically accounts for scattering from ionized impurities with an average binding energy Eb  is very small; thus, homogeneous broadening in this regime predominantly results from acoustic phonons18In general, the two major mechanisms governing the electron–phonon coupling in inorganic semiconductors are deformation potential scattering, in which distortions of the lattice change the electronic band structure, and electromechanical or piezoelectric interactions, in which lattice-related electric fields modify the electronic HamiltonianГimp could not produce the observed linear variation with T of the linewidths at high temperatures. Therefore, we conclude that scattering with ionized impurities does not play any major role here, in agreement with findings based on recent analyses of the temperature-dependence of the charge-carrier mobility in this regime212223Гimp≈0 for the rest of the analysis.To establish qualitatively which electron–phonon scattering mechanisms contribute in hybrid lead halide perovskites, we compare the temperature-dependent PL linewidth plotted in 3 and FAPbBr3 approach a PL linewidth of the order of 20 meV towards T=0, which can therefore be identified as the temperature-independent inhomogeneous broadening term Г0 arising from disorder. To qualitatively assess the relative importance of acoustic versus optical phonon contributions, an inspection of the gradient of these curves in the low-temperature regime is essential. Although the optical phonon terms lead to a gradient of zero in the regime for which ELO<kBT, the smaller energies of acoustic phonons should result in a non-zero gradient given by γac here. However, visual inspection of the graphs in γac≈0). Indeed, we find that fits of γac→0. This result is not surprising, given that in polar inorganic semiconductors the contribution of acoustic phonons to the broadening at room temperature is typically dwarfed by that of the LO phonons and indeed several studies ignore the contribution of acoustic phonons in such systemsγac by careful examination of the data in the low-temperature regime in which acoustic phonons are still expected to contribute significantly. Here we may fit Г(T)=Г0+γacT to the data in the low-temperature (T<60 K) regionT=0 K from differentiation. Both methods yield upper limits around γac=60±20 μeV K−1 for FAPbI3 and FAPbBr3; therefore, acoustic phonons will only contribute up to ∼18 meV to the linewidth broadening at 300 K. Hence, our analysis illustrates that the majority of broadening in the room-temperature regime arises from charge-carrier interactions with optical phonons, as would be expected for a polar semiconductor.To separate the contributions from acoustic and optical phonon modes, we first focus on an analysis of the PL linewidth for perovskites containing FA as the organic cation. As Г(T)=Г0+ГLO to the PL linewidth data are plotted in ELO=11.5 meV for FAPbI3, with the value for FAPbBr3 (15.3 meV) being 1.3 times larger, which is only slightly greater than the factor of 1.2 expected from a crude model of the frequency of a diatomic harmonic oscillator. These LO phonon energies of hybrid lead halide perovskites are somewhat lower than those typically measured for a range of inorganic semiconductors =Г0+ГLO  additional broadening see . Howeverovskites . We may Finally, we comment on the extent to which excitonic effects may influence the coupling between charge carriers and phonons. Although the exact values for the exciton-binding energies in these systems are still a matter of debate, most reported values fall into the range of a few to a few tens of milli-electronvolts (see ref. 13143 (see details in Methods section and in the Σ), projected on the quasiparticle band structure of MAPbI3; 2 Im(Σ) represents the linewidth of electrons and holes arising from the electron–phonon interaction before accounting for many-body effects (see Methods) and is therefore directly comparable to the experimentally determined FWHM of the PL emission linewidth. Σ) as a function of electron energy, together with the density of electronic states. This figure indicates that the increase in the linewidth is linked to the phase-space availability for electronic transitions, that is, Im(Σ) increases with increasing density of electronic states, because each state can scatter into a higher number of states by absorbing or emitting a phonon. Our calculations show that the dominant contribution to the electron–phonon self-energy arises from the coupling with the LO mode at 3.We further corroborate our analysis with first-principles calculations of the electron–phonon coupling in MAPbIΣ), whereas the red triangles were obtained by using Brillouin–Wigner perturbation theoryZ, that is 2 Z Im(Σ) (see Methods). The comparison between calculations and experiments shows that the experimental data are most accurately described by fully taking into account the many-body renormalization of the electron lifetime. Taken together, the impressive agreement between (1) our measured and calculated characteristic phonon energy scale , (2) the magnitude of our measured and calculated linewidth broadening at room temperature , and (3) the phonon energy scale identified here and the LO phonon identified between 10 and 13 meV in our previous study3 . We note, however, that although electron–phonon coupling generally leads to charge-carrier mobilities that increase with decreasing temperature, the exact functional dependence is usually a composite of many different scattering mechanisms that can be hard to attribute uniquelyEk is occupied at any temperature T. Such calculations result in predicted variations in mobility following μ∝T−3/2 for acoustic phonon deformation potential scattering25μ∝T−1/2 for acoustic phonon piezoelectric scatteringμ∝T−3/2, the converse may not necessarily also hold. In addition, the rapid energy loss of electrons observed following non-resonant excitation194μ∝T−3/2 relationship is not wholly attributable to acoustic deformation potential scattering. It is also clear that for these high-quality materials, scattering from ionized impurities is a negligible component at room temperature, with both our PL linewidth data and earlier charge-carrier mobility measurements2122Our analysis of the experimentally determined emission linewidth broadening and our first-principles calculations strongly support the notion that Fröhlich coupling to LO phonons is the predominant charge-carrier scattering mechanism in hybrid lead halide perovskites. As already discussed above, such behaviour is in many ways to be expected for these materials, because the lead-halide bond is sufficiently polar −1)15γLO≈40 meV and γLO≈60 meV we extract from our data for the respective iodide and bromide perovskites  was dissolved in anhydrous N,N-dimethylformamide at 1 M. This was then spin-coated onto the quartz substrates at 5,000 r.p.m. for 25 s. During spin coating, after 7 s an excess of anhydrous chlorobenzene was rapidly deposited onto the spinning film. After spin-coating, films were annealed at 100 °C for 10 min.MA perovskite films were deposited in a nitrogen-filled glovebox using a solvent quenching method wherein an excess of antisolvent is deposited onto the wet substrate while spin-coating2  were dissolved in anhydrous N,N-dimethylformamide in a 1:1 molar ratio at 0.55 M. Immediately before film formation, small amounts of acid were added to the precursor solutions, to enhance the solubility of the precursors and allow smooth and uniform film formation. Thirty-eight microlitres of hydroiodic acid (57% mass/mass) was added to 1 ml of the 0.55 M FAPbI3 precursor solution and 32 μl of hydrobromic acid (48% mass/mass) was added to 1 ml of the 0.55 M FAPbBr3 precursor solution. Films were then spin coated from the precursor plus acid solution on warm (85 °C) oxygen plasma-cleaned substrates at 2,000 r.p.m. in a nitrogen-filled glovebox and subsequently annealed in air at 170 °C for 10 min.FA perovskite films were deposited using an acid-addition method to produce smooth and uniform pinhole-free films−2. The resultant PL was collected and focused into a grating spectrometer , which directed the spectrally dispersed PL onto an iCCD . The sample was mounted under vacuum (P<10−6 mbar) in a cold-finger liquid helium cryostat . An associated temperature controller  monitored the temperature at two sensors mounted on the heat exchanger of the cryostat and the end of the sample holder, respectively; the reading from the latter was taken as the sample temperature. PL measurements were taken as the sample was heated in increments of 5 K between 10 and 370 K.Each sample was photoexcited by a 398-nm picosecond pulsed diode laser  with a repetition rate of 10 kHz and a fluence of 490 nJ cmab initio calculations on MAPbI3 in the orthorhombic phase using the crystallographic data in ref. d states taken explicitly into account in the case of Pb and I. Ground-state calculations were converged with a plane-wave cutoff of 100 Ry and a 6 × 6 × 6 unshifted Brillouin-zone grid. The electronic quasiparticle energies were calculated with the SS-GW method described in ref. 68Σnk, was calculated as:We carried out nqv are the Fermi–Dirac and the Bose–Einstein occupations, respectively, ɛnk and ɛmk+q are electron energies, ℏωqv is the energy of a phonon with wavevector q and polarization ν, and η is a small broadening .Supplementary Figures 1-4, Supplementary Tables 1-2, Supplementary Note 1, Supplementary Equation 1 and Supplementary References


Examples include the global warming potential (GWP), the global temperature change potential (GTP) and the absolute sustained emission temperature (aSET). Despite the importance of biomass as a primary energy supplier in existing and future scenarios, emission metrics for CO2 from forest bioenergy are only available on a case-specific basis. Here, we produce global spatially explicit emission metrics for CO2 emissions from forest bioenergy and illustrate their applications to global emissions in 2015 and until 2100 under the RCP8.5 scenario. We obtain global average values of 0.49 ± 0.03 kgCO2-eq. kgCO2−1 (mean ± standard deviation) for GWP, 0.05 ± 0.05 kgCO2-eq. kgCO2−1 for GTP, and 2.14·10−14 ± 0.11·10−14 °C (kg yr−1)−1 for aSET. We explore metric dependencies on temperature, precipitation, biomass turnover times and extraction rates of forest residues. We find relatively high emission metrics with low precipitation, long rotation times and low residue extraction rates. Our results provide a basis for assessing CO2 emissions from forest bioenergy under different indicators and across various spatial and temporal scales.Emission metrics aggregate climate impacts of greenhouse gases to common units such as CO Bioenergy is currently the most important renewable energy option in the global primary energy mix22452 uptake by vegetation re-growth. Harvesting forests alters the net exchange of CO2 between the land and atmosphere, with consequences for the CO2 atmospheric concentration and climate system102 emissions from heterotrophic respiration (Rh) exceed carbon sequestration in new trees via net primary productivity (NPP)1112The climate change impacts of forest bioenergy systems are frequently assessed in Life-Cycle Assessment (LCA) studiesth IPCC Assessment Report162 fluxes sum to zero over time. Such impacts can be assessed at different points of the carbon-climate cause-effect chain2 fluxes1820722232 emissions with those from other GHGs in terms of CO2-equivalents. Emission metrics are simplified measures of the climate system response to GHG emissions and are based on outcomes from complex models1625262 taken as the reference gas, hence CO2-equivalents) values taken at a specific time horizon (TH). Different emissions have different climate system responses, and a metric that establishes equivalence with regard to one effect cannot guarantee equivalence with regard to other effects. Various metrics are therefore available, and the choice of a metric should depend on the aspect of climate change that is identified as the most important in a particular application1616252622. GWP and GTP thus differ in the indicator (radiative forcing vs. temperature change) and time dimension (time-integrated vs. instantaneous). By contrast, aSET is an absolute metric that refers to the contribution to a global mean temperature peak (ΔTpeak), with no time dimensions. This metric is used for emission scenarios of shorter-lived climate forcers, with which bioenergy CO2 emissions can be grouped because they cause ΔTpeak values dependent on emission rates rather than cumulative emissionsHuman-induced forest disturbances typically involve within-class land conversion  that can affect the global climate as much as conversion to a different type of land cover class112 emissions from forest bioenergy at a global scale. Emission metrics are computed at 0.25° spatial resolution by coupling a global forest carbon model (G4M)31162 emissions from bioenergy in 2015 and until 2100 under the Representative Concentration Pathway (RCP) 8.5 scenarioEmission metrics for forest bioenergy are currently available for only a handful of specific locations181922232-eq. kgCO2−1 (mean ± standard deviation), a GTP −1 for a case in which 50% of harvest residues are extracted. The 5th and 95th percentile variation spans between 0.43 and 0.62 kgCO2-eq. kgCO2−1 for GWP, −0.03 and 0.24 kgCO2-eq. kgCO2−1 for GTP, and 1.90·10−14 and 2.64·10−14 °C (kg yr−1)−1 for aSET. As observed in previous studies19302-eq. kgCO2−1 for GWP, 0.04 ± 0.04 and 0.07 ± 0.07 kgCO2-eq. kgCO2−1 for GTP, and 1.81·10−14 ± 8.94·10−16 °C (kg yr−1)−1 and 2.81·10−14 ± 1.85·10−15 °C (kg yr−1)−1 for aSET, respectively.The spatially explicit emission metrics GWP, GTP, and aSET are presented in ), a GTP  of 0.05  an aSET  of 2.14·2 exchange relative to the growth cycle of biomass. This mechanism is described in previous studies20th IPCC assessment reportGTPs generally have lower values than GWPs, with negative values resulting from the fast time scale of atmospheric-ocean CO2-eq. kgCO2−1, with a density maximum at approximately 25 °C. In the GWP vs. precipitation correlation, the highest density of points occurs between 500 and 1000 mm. The lowest GWP values occur around a mean annual temperature between approximately 10 and 20 °C and for annual precipitation greater than approximately 1000 mm . Similarly, the GWP of 0.42 kgCO2-eq. per kg CO2The results aggregated at a country level are plotted against the mean annual increment (MAI) in 2 emissions from forest bioenergy that are compatible with the RCP 8.52 emissions up to 2100 are available from the land-use harmonization project2 emissions from global forests in 2015. The metric aSET (2 emission flows (2 emissions from forest bioenergy in 2015 correspond to 1.36 (−0.22/+0.44) Gt CO2-equivalents using GWPs. By contrast, we calculate a global cooling contribution in 2100 of −0.037 (−0.0025/+0.002) Gt CO2-equivalents using GTPs. With the aSET metric, we quantify a contribution to the temperature peak from the entire scenario of 0.17 (−0.3/+0.6) °C. In comparison, the gross CO2 emission flows in 2015 amount to 2.99 Gt, and the contribution to the temperature peak would be 0.26 ± 0.07 °C if the emissions from 2015 to 2100 stemmed from fossil fuels. The major forest bioenergy producing regions in 2015 are Southeast Asia, the Indian Peninsula, and Southeast Africa. When GWPs are used  to nearly climate neutral (with GTP).We apply these spatially explicit emission metrics to the global COric aSET  is applion flows  and the on flows  are avaiare used , these rn metric . In Soutn metric , thus yise areas . The int2 emission scenarios, which is proportional to the maximum rate at which emissions occur and is insensitive to the total amount of emissions. This metric does not explicitly capture the timing of the different temperature peaks and post-peak dynamics, which significantly differ between short- and long-lived climate forcers. For CO2 emissions from bioenergy systems, the effect gradually dissipates over time, and the temperature decreases if emission rates decrease2 from fossil fuels, the effect persists over time, and the temperature continues to increase for each additional unit of emission and does not decline even after the emissions cease4128The large differences in the results after applying GWPs or GTPs stem from the different characteristics of the two metrics. We recall that GWP is a time-integrated measure that considers the total forcing added to the climate system until the TH. The corresponding results in 2 emissions to those from other forcing agents into common units. The values of the metrics reflect regional differences in climate and forest management. The maps have geographical patterns that relate to local climate variables and forest characteristics. Metrics are generally lower in regions with favourable growing conditions and when forest residues are extracted rather than left to oxidize on the plantation ground. On the other hand, we find relatively high emission metrics with low precipitation, long rotation times and low residue extraction rates. The availability of this dataset is a timely and easy-to-use option that offers the possibility to integrate the climate change contributions of CO2 emissions from forest bioenergy with the variety of applications in which emission metrics are used. Applications can span from local projects to global emission scenarios, in which the role of forest bioenergy can be assessed under different objectives using the related climate change impact indicators.This study is the first to offer global spatially explicit emission metrics for forest bioenergy. The metrics are formulated following the same IPCC approach that is commonly applied for other GHGs and thus allow to aggregate climate impacts from bioenergy CO2 are expected to cause substantial changes in vegetation structure and function over large fractions of the global land surface. Understanding the net effect of climate feedbacks on terrestrial vegetation is complex because of the variety of factors involved. Changes in NPP, Rh and NEE occur primarily through enhanced growth because of CO2 fertilization effects, nitrogen availability, faster decay rates of residues, and higher soil respiration444547482 atmospheric concentrations will also increase the fraction of CO2 remaining airborne over time because of saturation in the oceans and land carbon stocks22 radiative forcing at increasing atmospheric CO2 concentrations2950Emission metrics have been successfully applied to illustrate the basic physics of the response of the climate system to emissions and are widely used in the scientific community and legislative frameworks. However, there are a number of uncertainties and limitations associated with metrics that are primarily connected to the definition of background climate conditions and the treatment of feedbacks2, such as surface reflectivity , water fluxes, and surface roughness622 fluxes642 climate forcing mechanisms following a forest disturbance can be producedFollowing our approach, alternative emission metrics can be computed. For instance, GWPs and GTPs can be based on a different TH, or other climate impact indicators can be considered, such as sea level rise3654456565758This work reflects the complex interactions between forest ecosystem responses, climate change, and the role of the selected metric used to inform policy. In-depth multidisciplinary research between foresters, climate scientists and emission scenario developers will further consolidate a consistent understanding of the implications associated with forest resource use in the context of climate change mitigation.G4M is a geographically explicit vegetation model that simulates global forest characteristics and is frequently used to model forest carbon dynamics associated with human-induced disturbances24313231h response to the harvest event is obtained from reproducing YASSO07h response to be scaled to the grid-specific amount of forest residues remaining on site after harvest. Post-harvest net CO2 exchanges are estimated for each grid cell after combining the NPP and Rh profiles. These NEEs represent the ecosystem carbon response to the harvest event and are used as the basis for the computation of emission metrics for forest bioenergy1822The Rth IPCC Assessment Report2 atmospheric concentration from bioenergy CO2 emissions and the associated site-specific NEE profiles are computed for each grid cell after the integration with the global carbon cycle through a mathematical convolutionEmission metrics are computed following the standard protocolf(t) is the grid-specific impulse response function of the perturbation and y(t) is the impulse response function to a CO2 emission, simulated using a multi-model mean2where 2 is the background atmospheric CO2 concentration  increase in the atmospheric abundance of CO2, called the radiative efficiency, where COThe instantaneous RF is then computed as the product of equation The global surface temperature responds to changes in radiative forcing on a spectrum of timescales. We use a temperature response function that is the sum of two exponentials:ci is the climate sensitivity, and di represents two different timescales. We use the factors c1 = 0.631 K/(Wm2), c2 = 0.429 K/(Wm2), d1 = 8.4 yr, and d2 = 409.5 yr from a previous publication2) (or 3.9 °C for CO2 doubling). The temperature response to a radiative forcing pulse, called the Absolute Global Temperature Change Potential  is the CO2 emission flow from forest bioenergy in grid cell i and M(i) is the corresponding emission metric. For GWP and GTP, E(i) are the emissions in 2015  is the maximum emission rate from 2015 to 2100 occurring in each grid cell .


The Earth’s surface comprises minerals diagnostic of weathering, deposition and erosion. The first continental-scale mineral maps generated from an imaging satellite with spectral bands designed to measure clays, quartz and other minerals were released in 2012 for Australia. Here we show how these satellite mineral maps improve our understanding of weathering, erosional and depositional processes in the context of changing weather, climate and tectonics. The clay composition map shows how kaolinite has developed over tectonically stable continental crust in response to deep weathering during northwardly migrating tropical conditions from 45 to 10 Ma. The same clay composition map, in combination with one sensitive to water content, enables the discrimination of illite from montmorillonite clays that typically develop in large depositional environments over thin (sinking) continental crust such as the Lake Eyre Basin. Cutting across these clay patterns are sandy deserts that developed <10 Ma and are well mapped using another satellite product sensitive to the particle size of silicate minerals. This product can also be used to measure temporal gains/losses of surface clay caused by periodic wind erosion (dust) and rainfall inundation (flood) events. The accuracy and information content of these satellite mineral maps are validated using published data. The Earth’s regolith comprises all surface materials between “fresh rock and fresh air” where oxidation, hydration, biological and mechanical processes have caused some degree of mineralogical change (weathering) and porosity generation of underlying rock13452O3/(Al2O3 + CaO* + Na2O + K2O)] × 100; where CaO* is the amount of CaO incorporated in silicate minerals}. The CIA was designed to estimate the amount and composition of clay minerals based on the assumption that kaolin [Al2Si2O5(OH)4] is associated with intense weathering that is typical of warmer, wetter conditions, such as the subtropical monsoonal belt. In contrast, illite [24O10[(OH)2·(H2O)] and montmorillonite [0.332(Si4O10)(OH)2·nH2O] are indicative of less intense weathering typical of cooler, temperate conditions562). Quartz grains are generally equant in shape and large in diameter  and so are less vulnerable to erosion by windThe intensity of weathering has been gauged using laboratory geochemical techniques like loss-on-ignition (LOI)Australia is a flat, dry, deeply weathered continent reflecting its low rates of erosion and long-lived tectonic stability associated with its mosaic of Precambrian blocks1131417Airborne geophysical methods like gamma-ray spectrometry2223242526ASTER is a polar orbiting (<83° latitude) system with a 60 km imaging swath designed to sense across fourteen spectral bands at a pixel resolution between 15 and 90 m. These spectral bands include: (a) three in the visible and near infrared  wavelength region where green vegetation and iron oxides have diagnostic spectral features; (b) six in the shortwave infrared , where clay minerals have diagnostic features related to the vibration of hydroxyl groups; and (c) five in the thermal infrared , where non-hydroxyl bearing silicate minerals like quartz have diagnostic features though particle size also has a pronounced effect30This paper focuses on three of the available seventeen published ASTER geoscience maps2 content323336The four ASTER mineral maps selected for mapping Australia’s regolith include: (i) “Clay Composition” or “CC”  and inversely correlated with % clay and LOI; and (iv) no significant correlations with respect to LOI, % clay and/or % sand for the ASTER CI, CIA and the gamma-ray spectrometry analogues K, Th and U.The NGSA is a public suite of physicochemical data  measured from unconsolidated, flood-overbank samples collected at 0–10 cm and ~60–80 cm depths from over 1000 river catchments across Australia3233The ASTER CC image is plotted with the NGSA ASTER CC in 2 = 0.29, N = 1069). Clay mineralogy is expected to be a key driver in understanding a given sample’s water content as there is a 100-fold increase in absorption/adsorption of water as the clay mineralogy changes from kaolinite to illite to montmorillonite, which relates to their respective cation-exchange capacities and typical crystallite sizes2 = 0.35, N = 165) and to a lesser degree Si/(Si + Al) , which suggests a role for silicic acid in the formation and stability of kaolinThe significant correlation between the NGSA ASTER CC and LOI  is consiSimilar to the laboratory results  and otheThe ASTER CI shows a close relationship with the rainfall pattern  with the43The correlation between the NGSA ASTER SI with % sand  of suspended river sediment samples63643The highest correlation with NGSA particle size is provided by the TIR-based ASTER SI . However111147th September 2000, 22nd October 2005 and 9th October 2006) used in the published ASTER SI mosaicth October 2006 satellite path (Y). This clay-rich band (interpreted by the cool tones in the ASTER SI), which is not evident in either earlier or later dates of ASTER imagery for the same path/area, cross-cuts sand dunes to the west-northwest before truncating against the 13th September 2000 scene. This clay band also shows a decreasing SI gradient (increasing clay content) towards Cooper Creek where it terminates (originates).The three satellite overpasses (dated 13th of October 2006 shows an average (over 9 hours) wind speed of 33 km/hr from the direction 134°. This wind event is towards the upper limit of wind activity for this region between 2000 to 2008 and thus could be responsible for this trail of clay material in the 9th October 2006 ASTER SI image  speed of 40.7 km from a direction of 108°. Note that other satellite observationsMeteorological data recorded from the weather station at Etadunna StationSI image . Howeverth October 2006 was only 76.4 mm, which was significantly less than the 2000–2008 annual average of 129.5 mm. These meteorological data support the hypothesis that the cross-cutting clay band in the 9th October 2006 ASTER SI track is the result of a dust event that occurred either during the satellite overpass or more likely three months previously.Ground-based nephelometer aerosol data were recorded 100 km to the east-southeast at Tinga TinganaThe non-linear relationship between ASTER SI and particle size  means th47th October 2004 (100 mm over one day) and 11th and 12th February 2000 (111.6 mm in two days). The SI ~ 1.1 peak is interpreted to be related to more poorly-sorted, medium grained (~silt size) material. This peak also appears to follow the three most intense rainfall events  and SI2006/SI2005 (2005/SI2004 (2004/SI2002 (2).To understand what regolith units  are driving these changes in the SI histograms , ratios  subarea . These s6/SI2005  products5/SI2004  and SI204/SI2002  products4/SI2002 . Note th4/SI2002 , can be Previous studiesThe most stable SI temporal ratio values  are assoThe surface mineralogy measured using ASTER is consistent with a changing Cenozoic climate. Given kaolinite formation is an indicator for sub-tropical conditions1Recent geophysical data and derived models reveal considerable variability in the thickness of Australia’s crust down to at least the Mohorovičić discontinuity (MOHO)The pronounced gradient in crustal thickness between the Precambrian blocks and the Lake Eyre basin is also a locus for earthquake activityImportantly, ASTER shows that illite-montmorillonite characterises the sediments across the Lake Eyre basin as well as other large depositional basins developed over relatively thin crust like the Eucla and Canning Basins  of the CC, CI, CWI and SI products for the entire Earth’s land surface (<80° latitude). Given that ASTER’s SWIR module ceased operating in 2008, then the CC, CI and CWI products are no longer a monitoring option though similar SWIR clay mapping is possible through access to Worldview-3 (WV-3) satellite data which was launched in August 2014. Importantly, WV-3 comprises the same SWIR-2 bands as ASTER (except for band 9 which impacts on the CWI product) but at higher spatial resolution (7.5 m pixel) and lower volumes/rates of spatial coverage. ASTER’s TIR module continues to operate such that monitoring using an SI type product remains a global opportunity. Similarly, the Japanese HIMAWARI-8 satellite launched in October 2014 is now in geostationary orbit over the equator at 140° East  and is imaging multispectral data every 10 minutes, including bands similar to ASTER’s TIR bands 10 and 13 albeit at 2 km pixel resolution. Thus routine detection of the loss or gain of surface clay during large-area dust activity or flood events is possible. Unfortunately though, ASTER’s integrated VNIR + SWIR + TIR spectral band configuration has not been matched by either WV-3 or HIMAWARI-8 such that future global mapping and monitoring the mineral complexity of Earth’s regolith and related processes must wait for new satellite systems.From the 0–10 cm depth NGSA sample suite, 165 random samples were taken and measured for their reflectance signatures across the 0.4 to 20 μm wavelength. The TIR spectra were measured using an integrating sphere attached to a Bruker Vertex 70 instrument which provide directional-hemispherical reflectance. The SWIR spectra were measured using an Analytical Spectral Devices (ASD) Fieldspec Pro 3 spectrometer, which provides bi-directional reflectance only. These two types of spectral measurements were then convolved using the published ASTER band-pass response functionsThe ASTER “Clay-Water Index” (CWI) is designed to be sensitive to water, including water vapour and bound or unbound molecular water associated with surface clays and other minerals. The CWI measures the slope of SWIR reflectance wing to the fundamental stretching vibration (symmetric and asymmetric) absorption of water at ~2.9 μm. The CWI is calculated using:2 = 0.90) and area (R2 = 0.91) of the water combination (stretching plus bending vibration) absorption at ~1.9 μm for the full spectral resolution (~10 nm) ASD reflectance spectra of the NGSA 2 mm sample fractionswhere B is the reflectance of a given ASTER band. The efficacy of the CWI is shown by its significant, linear correlations with the depth  by water vapour whereas ASTER bands 6 and 7 span wavelengths of near complete atmospheric transmission . Water vapour is currently not corrected for in the Australian ASTER products, which helps explain why there are generally high CWI responses across the kaolinite-rich, tropical belt at lower latitudes .


Staphylococcus aureus in vitro. Using transgenic mouse models, we established that immune cell production of fibronectin contributes to phagocytosis, more so than circulating plasma fibronectin, and that accentuated release of EDB-containing fibronectin by immune cells improved phagocytosis. In line with this, administration of EDB fibronectin enhanced in vitro phagocytosis to a larger extent than plasma fibronectin. This enhancement was mediated by αvβ3 integrin as shown using inhibitors or cells from β3 integrin knockout mice. Thus, we identified both a novel function for EDB fibronectin in augmenting phagocytosis over circulating plasma fibronectin, as well as the mediating receptor. Our data also establish for the first time, a direct role for β3 integrin in bacterial phagocytosis in mammals.Plasma fibronectin is a circulating protein that facilitates phagocytosis by connecting bacteria to immune cells. A fibronectin isoform, which includes a sequence of 90 AA called extra-domain B (EDB), is synthesized de novo at the messenger RNA (mRNA) level in immune cells, but the reason for its expression remains elusive. We detected an 80-fold increase in EDB-containing fibronectin in the cerebrospinal fluid of patients with bacterial meningitis that was most pronounced in staphylococcal infections. A role for this isoform in phagocytosis was further suggested by enhanced EDB fibronectin release after internalization of • Fibronectin containing an extra domain called EDB is released in bacterial meningitis.• EDB-containing fibronectin enhances phagocytosis more than plasma fibronectin.• The enhancement is mediated by activation of αvβ3 integrin in the presence of EDB.The online version of this article (doi:10.1007/s00109-015-1373-0) contains supplementary material, which is available to authorized users. Fibronectin is an extracellular matrix protein that is produced by almost all mammalian cells . It affeStaphylococcus aureus for example express several molecules such as fibronectin-binding proteins (Fnbp) that enable bacteria to attach to and invade tissues . De. De26]. Mβ2 is involved in this effect. Therefore, inhibiting either one diminishes phagocytosis but does not suppress it back to baseline, while phagocytosis mediated by the Fcγ receptor could also be enhanced by EDB fibronectin.Taken together, these data show that EDB fibronectin interacts with αvβ3 to enhance phagocytosis, and αMβ2 stimulation [Phagocytosis requires actin microfilament formation and the activation of intracellular signaling cascades . To invemulation  failed tThus, EDB fibronectin enhances phagocytosis by activating β3 integrin and increasing ERK phosphorylation, without marked effects on AKT phosphorylation.The principal findings of this study are (1) EDB-containing fibronectin is released in the cerebrospinal fluid of patients with bacterial meningitis, especially during infections with staphylococcal species. (2) Phagocytosis is associated with the production and release of EDB-containing fibronectin. (3) The presence of the EDB domain in fibronectin augments phagocytosis by acting on αvβ3 integrin. (4) This effect is independent of the presence of β1 integrin. (5) β2 seems to cooperate with β3 to enhance phagocytosis mediated by EDB fibronectin.Fibronectin is elevated in the cerebrospinal fluid of patients with bacterial meningitis . It was We evaluated the role of fibronectin produced by the immune cells themselves. The Mx promoter deletes fibronectin and β1 integrin in hematopoietic cells. However, it also deletes fibronectin in the liver. For this reason, we used as the control the albumin promoter to delete fibronectin in hepatocytes and hence in the circulation , 26. ThiThe presence of the EDB domain affects vasculogenesis, but some overlap exists with EDA in that function , 5. No sIntegrins consist of α and β subunits that diffuse freely in the membrane and between an intracellular and a surface pool, making the integrin pool very dynamic. α and β subunits need to combine in heterodimers to affect intracellular signals . Each β S. aureus strain Wood 46, which expresses relatively low amounts of fibronectin binding proteins. Nevertheless, it is able to bind fibronectin effectively as shown by others [E. coli used in the experiment in Fig. S. aureus, but did not affect the phagocytosis of E. coli. This therefore suggests that protein A is not required for EDB effects.In our experiments, we used y others , 55 and S. aureus, and clearly indicates that EDB fibronectin released during phagocytosis, especially of staphylococcus species enhances bacterial removal by mammalian immune cells through activating αvβ3 integrin. The experiments furthermore establish β3 integrin as the receptor mediating EDB fibronectin enhancement of phagocytosis. Our findings highlight that this mechanism acts in addition to other mechanisms of phagocytosis, but cannot be completely replaced by other phagocytic systems, at least in vitro. Lastly, this apparently important role played by αvβ3 integrin in phagocytosis needs to be taken into account in studies examining inhibitors of αvβ3 in cancer treatment.Because of the importance of phagocytosis for survival, its control evolved such that much overlap exists and many possible pathways for activating phagocytosis can be simultaneously involved. Indeed, multiple receptors participate in phagocytosis, including Fc receptors, complement receptors, and pattern recognition receptors. For most bacteria species, opsonization with IgG and engagement of the Fc receptors is a prerequisite for efficient phagocytosis, while the other receptor-ligand interactions exert various modulatory roles . FurtherESM 1(PDF 59 kb)Below is the link to the electronic supplementary material.


We studied carbon and nitrogen acquisition and water-use efficiency across the ontogeny of a rare cycad in relation to environmental gradients. Increased water-use efficiency at lower drier elevations and nitrogen fixation at upper elevations with nutrient poor soils may help maintaining the lower and upper altitudinal species range limits Functional traits can drive plant responses to short- and long-term stressful conditions, with potential effects on species persistence in local habitats, changes in population size and structure, and potential species range shifts in changing environments. We investigated whether ecophysiological traits in a rare cycad vary along environmental gradients and with ontogeny to understand intra-specific resource-use variation  and possible species adaptations for different environments. Environmental gradients were characterized with 14 soil and topographic variables. Nitrogen- and water-use efficiency improved with ontogeny (from seedling to juvenile and adult stages) but declined as soil fertility decreased with increasing elevation. Conversely, reliance on symbiotic nitrogen fixation increased with elevation and varied slightly with ontogeny. Improved water-use efficiency at lower elevation and nitrogen fixation at higher elevation may represent key functional strategies for maintaining the lower and upper altitudinal species range limits, especially in arid environments where stressful conditions are intensifying due to climatic and land-use changes. In addition to facilitation linked to the regeneration niche, improved resource-use efficiency linked to the adult niche may strongly influence cycad distribution and persistence in contemporary environments. A functional approach to conservation of rare or endangered plant species may be needed in order to target the most sensitive stages to changing environmental conditions and to better understand potential range shifts and adaptive responses to global land-use and climate changes. Functional traits can drive plant responses to short- and long-term stressful environmental conditions, such as water or nutrient stress, which represent two major environmental filters in arid environments ; Current gymnosperm  distribution is thought to be related to the contraction to refuge habitats due to past climatic changes and the poor competition with angiosperm species due to reproductive and physiological constraints . Leaf shPlant functional traits are usually studied at the regeneration niche because higher mortality rates during early ontogeny make this phase a critical period for selection of plant traits . During Assuming that the quantification of species functional traits by life stage can help us to gain insights into intra-specific resource-use variation and possible species adaptations for different environments during their ontogeny, we specifically asked: does the lower resource use in seedlings and juveniles more strongly reflect an adaptation of the younger life stages to different environmental conditions or developmental constraints that prevent them from achieving more advantageous trait values? We expect carbon assimilation and nitrogen- and water-use efficiency to be positively related to soil fertility, while symbiotic nitrogen fixation should be related negatively to soil fertility. However, as ontogeny progresses plants should become more efficient  given the potential adaptive significance of these key functional strategies for long-lived gymnosperms inhabiting water- and nutrient-limited environments.Dioon sonorense  Chemnick and T.J. Greg. and Salas-Morales  is an endemic endangered cycad of northwestern Mexico  are known to grow very slowly, reaching considerable age . Rare, small populations are particularly vulnerable to climate extremes; for example, the heavy rains from hurricane Norbert in October 2008 washed down one of the populations (∼90% of plants) at higher elevation .n Mexico . Dioon sD. sonorense occurs) are tropical dry forest at low elevations, oak forest at mid-elevation , where agroforestry is widespread and represents the main economic activity for local communities. The climate is warm and semi-arid, with a total annual precipitation of 712 mm and marked seasons; the dry season is from November to June and the wet season from June to October, when ∼80% of annual precipitation occurs . The thr2 assimilation (A) and transpiration (E) rates were performed on the same 81 plants used for leaf tissue collection prior to collecting leaf samples. We obtained 10 readings (per plant per life stage) from three fully developed and exposed leaflets placed within the chamber. Gas-exchange measurements were conducted at ambient conditions of (chamber) temperature (34.02 ± 5.63°C), CO2 (391.27 ± 22.66 ppm) and photosynthetically active radiation (925.57 ± 483.81 photosynthetic photon flux density) between 10.00 and 12.00 h at the beginning of the rainy season (June/July) using an LCpro+ Portable Photosynthesis System .We collected a total of 81 leaf samples from the 27 study plots located along an elevation gradient (500–1000 m above sea level) where the nine study populations occur (i.e. three plots per population). We collected one composite leaf sample from three different leaflets from a randomly selected plant per life stage . Life-stage classification was based on individual height and reproductive characteristics (N) and for δ13C and δ15N composition. Standard procedures were followed to process and analyse 2.5–3.0 mg of solid samples for carbon and nitrogen concentrations and carbon (δ13C) and nitrogen (δ15N) stable isotope composition using a Costech Elemental Analyzer coupled to a ThermoFinnigan Delta XL Plus stable isotope ratio mass spectrometer via ThermoFinnigan Conflo III interface (13C and atmospheric nitrogen for δ15N) were verified using National Institute of Standards and Technology RM8573 [δ13C = −26.4 ± 0.1‰ (n = 38) and δ15N = −4.5 ± 0.3‰ (n = 38)], RM8574 [δ13C = +37.6 ± 0.2‰ (n = 38) and δ15N = +47.6 ± 0.3‰ (n = 38)]. Daily precision of the instrument was verified by repeated analyses of internal laboratory standards, including acetanilide [δ13C = −29.9 ± 0.1‰ and δ15N = −0.1 ± 0.4‰ (n = 9)], valine  and daphnia , during the sample runs. We also analysed one composite leaf sample at each plot from a species without the ability to fix atmospheric nitrogen (i.e. 27 plants sampled from the oak Quercus chihuahuensis Trel.) to be used as reference values for biological atmospheric nitrogen fixation estimates (15N abundance method to estimate the percentage of nitrogen fixation in D. sonorense (2 fixation = (δ15N(reference) − δ15N(N-fixing)/δ15N(reference) − B) × 100, where δ15N(reference) is the mean value of the Q. chihuahuensis, δ15N(N-fixing) is the mean value of D. sonorense per life stage, and B represents the mean value for N2-fixing plants when grown totally depending on N2. In the absence of B values for D. sonorense, we used a common value for tree legumes (−2‰) to test the potential importance of extreme B values (2 fixation was highly (linearly) correlated with D. sonorense δ15N values (Pearson's r = −0.87); we therefore focused on interpreting potential trends of biological fixation using D. sonorense δ15N raw values instead of the calculated percentages because these are not always accurate and are thus highly debated  relationship with long-term water-use efficiency ; N, time-integrated leaf nitrogen concentration (expressed as a percentage); PNUE, the instantaneous photosynthetic nitrogen-use efficiency, the ratio of carbon assimilation rate per unit leaf nitrogen ; and δ13C and δ15N, the time-integrated carbon and nitrogen stable isotope ratios (expressed per mille).In summary, although our sample size was limited by the nature of our rare species, we obtained seven key ecophysiological traits related to carbon assimilation, water-use efficiency and nitrogen fixation in three different life stages occurring at nine different populations . The traits included in our analysis are as follows: (in micromoles of carbon dioxide per second per square metre); N) using the Kjeldahl method, bulk density using the paraffin method, and soil pH was determined with a potentiometer. The content of clay, silt and sand (texture) was determined by the Bouyoucos method. Cation exchange capacity (CEC) and cation concentrations  were estimated by the ammonium acetate method. The data set with two topographical variables and 12 soil variables for each of the 27 plots was used to run a principal component analysis (PCA) to simplify the correlation structure among variables and extract the main environmental gradients  to be used in subsequent analysis  and confirmed with topographic maps. We recorded steepness of the slope at each plot using a clinometer. We sampled soils by stratifying each plot into upper, middle and lower slope sections. We collected nine soil samples per plot (three from each stratum) from a depth of 0–30 cm (soil core of 10 cm in diameter) and combined them into one composite soil sample per plot. Soils were characterized by measuring 12 physical and chemical soil variables using methods from A, E and WUE. In all statistical tests, we set the significance level to be α = 0.05. Finally, a PCA was performed to determine the nature and number of relevant axes of functional resource-use differentiation among life stages. All analyses were run in R  followed by Tukey's HSD tests. We performed stepwise analysis of covariance (ANCOVA) models with each functional trait as a response variable, life stage as a factor and the environmental gradients (Grad1 and Grad2) as covariates. A weighted least-squares model was performed between each response variable and the parameters that minimized the Akaike's Information Criteria score in the stepwise model. We used the relative abundance of each life stage per plot as weights for each of the models to account for life-stage variation. Given that the order of factor levels  could potentially affect the ANCOVA outcome, we altered the order of life stages , and similar statistical significance was obtained for adult and seedling parameters. Juvenile stage remained in the middle in both model runs; this makes biological sense because juveniles are an intermediate stage in life history of the species. Response variable transformation was performed (i.e. Log10) to achieve variance homogeneity and normality of model residuals in instantaneous measurements of run in R .N concentration, trait values related to carbon assimilation and water-use efficiency increased with life stage (Table A and PNUE), instantaneous water-use efficiency (WUE), δ13C (positively related to long-term WUE) increased, whereas transpiration rate and leaf N concentration (E and N) decreased with ontogeny  showed an upward trend with ontogeny, but differences among life stages were not significant (P > 0.05). Interestingly, although leaf N was the highest in seedlings, their carbon assimilation rate was the lowest and their transpiration rate the highest  and long-term water use efficiency  increased with Grad2, i.e. increasing slope steepness and coarse-texture soils  and minimizing water loss by transpiration (E). Water-use efficiency increased with ontogeny due to the higher photosynthetic rates and lower transpiration rates of adults and juveniles. The three life stages were differentiated by their predominant resource-use strategy along axis 1 (PNUE and WUE). Adults and seedlings showed the greatest separation , followed by juveniles and seedlings . Adults and juveniles showed no significant differentiation along axis 1 . This distinction of life stages in the ordination space suggests that the first axis represents a resource-use strategy where adults  in adult plants should be particularly favoured and relevant for their persistence in arid ecosystems given their considerable longevity . Seedlings from another cycad species from dry environments (D. edule) showed a higher probability of dehydration during intense drought when their sclerophyllous leaves were not fully developed  was consistently more efficient in more advanced ontogenetic stages. The long lifespan of D. sonorense; D. sonorense (and possibly in other cycads from arid environments) could be related to a reduction in seedling transpiration rates. Facilitation may then increase resource-use efficiency (i.e. WUE and PNUE) and therefore promote higher seedling survival and faster growth rates  suggested an ontogenetic increase in carbon assimilation rates , which is probably related to their high annual mortality rates  increased at lower elevations with more fertile soils, whereas reliance on biological nitrogen fixation  increased at higher elevations with less fertile soils. In contrast to humid regions, drought stress in our study system can systematically increase leaf δ13C values because of higher temperatures and potential water loss at lower elevations where drought-deciduous species predominate  in contemporary environments are the contraction to refuge habitats due to past climatic changes and the poor competition with angiosperm species due to reproductive and physiological constraints (


The brain’s myelin content can be mapped by T2-relaxometry, which resolves multiple differentially relaxing T2 pools from multi-echo MRI. Unfortunately, the conventional fitting procedure is a hard and numerically ill-posed problem. Consequently, the T2 distributions and myelin maps become very sensitive to noise and are frequently difficult to interpret diagnostically. Although regularization can improve stability, it is generally not adequate, particularly at relatively low signal to noise ratio (SNR) of around 100–200. The purpose of this study was to obtain a fitting algorithm which is able to overcome these difficulties and generate usable myelin maps from noisy acquisitions in a realistic scan time. To this end, we restrict the T2 distribution to only 3 distinct resolvable tissue compartments, modeled as Gaussians: myelin water, intra/extra-cellular water and a slow relaxing cerebrospinal fluid compartment. We also impose spatial smoothness expectation that volume fractions and T2 relaxation times of tissue compartments change smoothly within coherent brain regions. The method greatly improves robustness to noise, reduces spatial variations, improves definition of white matter fibers, and enhances detection of demyelinating lesions. Due to efficient design, the additional spatial aspect does not cause an increase in processing time. The proposed method was applied to fast spiral acquisitions on which conventional fitting gives uninterpretable results. While these fast acquisitions suffer from noise and inhomogeneity artifacts, our preliminary results indicate the potential of spatially constrained 3-pool T2 relaxometry. Differential transverse relaxation rate (T2) of water in different brain tissues enables sensitive estimation of structural changes The prevalent fitting method, non-negative least squares (NNLS) The challenges in NNLS-based T2 relaxometry arise not only from the innate ill-posedness of the inverse problem multi-voxel spatial regularization approach which imposes two constraints:In this paper, we eschew the underdetermined but linear NNLS approach in favor of a non-linear formulation that recognizes only 3 distinct T2 compartments in the brain, each exhibiting not a single T2 but a wide peak distributed within a small disjoint T2 range. This drastically reduces the number of unknowns, greatly improves the conditioning of the inverse problem and circumvents the biologically unrealistic and numerically indefensible need for 50 or 100 T2 compartments. A previous comparison between a similar 3-pool fit and NNLS demonstrated significant improvement in simulations There are only 3 distinct T2 pools in the brain – a fast relaxing myelin water pool, a slower intra/extra-cellular water pool, and a very long relaxing cerebrospinal fluid (CSF) pool. Based on numerous observations of T2 distributions, we model the first two pools by Gaussian distributions, whose parameters  are unknown and to be determined. The long CSF pool is modeled as a single pool with a single unknown T2 and strength. See T2 characteristics of constituent water compartments change smoothly within coherent brain regions such as healthy WM while the boundary sharpness between distinctive regions should also be preserved. These spatial constraints are imposed separately on each parameter in the above multi-Gaussian model.around 5 times faster than a local implementation of NNLS. However, we stress that the main objective of the new method is not a faster algorithm, but one that overcomes the limitations of ill-conditioning by utilizing spatial and model-based constraints.Previously, a single Gaussian distribution was found to outperform monoexponential models in brain tissue We thoroughly exercise and numerically characterize the proposed algorithm using a variety of numerical lesion and whole brain simulations, MR phantoms and in vivo brain data acquired with the multi-echo spin echo (MESE) sequence. We demonstrate our method on a small number of normal subjects and a very large cohort of 154 MS patients, and demonstrate significant improvement over conventional fitting. We also present preliminary results on a new 3D multi-echo fast T2-prepared spiral imaging sequence k in a voxel measured at echo times TEk , a set i = 1,…,N of discrete sub-components are hypothesized to exist, each producing an exponentially decaying signal αiexp(-TEk/T2(i)) with a known T2 constant of T2(i) and an unknown volume fraction of αi. Assuming a slow exchange regime Given MR signals yy  =  Ax + ε, with y is a collection of data ky acquired at echo time kTE, x is a vector of the unknown iα, and ε denotes instrumentation noise. This system of linear equations is typically under-determined (N>K) and ill-posed, making a direct inversion either impossible or prone to extreme noise sensitivity, instability and non-uniqueness or equivalently, Tλ is a regularization parameter. We follow the approach and notation of a recent spatially constrained multi-voxel Bayesian minimization for each voxel using the non-negative least squares (NNLS) algorithm. Here x, y are collected in multi-voxel vectors, and the expanded  matrix Aex is defined similarly. The last term penalizes spatially non-smooth solutions via the first-difference operator and corresponds to the convolution of the T2 distribution image with a high-pass filter. W is a diagonal weighting matrix which allows for variable penalties associated with T2 points.where single-voxel quantities j-th voxel we wish to determine the following set of unknown parameters , and T2 distribution is over variable τ. The T2 distribution above resulting from the multi-Gaussian model is evaluated on the 40-point range of T2 values, and the delta function above turns into a discrete delta. Collecting multi-voxel parameters in the vector θ  =  {j), jθ , we minimize Each Gaussian is denoted by the shorthand SD. The global regularization parameters Nλ and Sμ are unknown a priori and their optimal values are chosen by a semi-supervised procedure (see Method). Once minimization has concluded, we obtain the final T2 distributionThe 3rd term enforces spatial consistency constraint #2 above, separately on each parameter of the model, via the first difference operator matrix Since we model pools explicitly, MWF calculation does not involve integration: under the constraint that should be in the range during the minimization of Eq (6). The operator Eq (8) is merely a reframing of Eq (5), and is intended to stress that our chosen approach relies on solving the non-linear least squares problem (8) rather than the general problem (5), and takes advantage of the 2-norm structure available to us. This approach can take advantage of the fact that at each iteration, the minimization problem is a least squares problem around a local Jacobian A synthetic MRI brain image and its white, gray and CSF probabilistic masks obtained from the Montreal Neurological Institute (MNI) were used to simulate multi-echo T2 data, each tissue class having a unique T2 signature. The myelin fraction was set at 14.5% for pure white matter, 4.5% for pure gray matter, and 0% for CSF. The myelin, intra/extra and long-T2 pools were simulated as Gaussians centered at 25 ms and 100 ms, respectively, and the CSF peak was set at 1800 ms. These pure T2 components were weighted by the probabilistic masks to get the actual components. Additive white Gaussian noise was introduced at SNR level varying from 100 to 1000; SNR is defined for this purpose with respect to the signal at first echo.10 test tubes filled with water doped with varying concentrations of Gadolinium and MnCl2 were scanned using the MESE sequence at 1.5T over 8 slices and processed using the propsoed algorithm. The nominal T2 relaxation times were measured by fitting a single exopnential onto the averaged signal curves from all voxels in each test tube.Spin echo: axial FOV = 30 cm, matrix size = 256×128 (interpolated to 256×256), partial phase FOV factor  = 0.6, slice thickness  = 5 mm, number of slices  = 12, TR = 2500 ms, echo spacing  = 5 ms, number of TEs  = 32 ), scan time  = 38 min. 3D T2prep spiral: axial FOV  = 24–30 cm, matrix size  = 192×192 (interpolated to 256×256), slice thickness  = 5 mm, number of slices  = 32, TR = 2500 ms, flip angle = 10°, number of TEs = 15–26, scan time  = 10–26 min. Two end slices were discarded to account for imperfect slab excitation profile. Skull (very short T2) and fluid (very long T2) signals were removed using BrainSuite v09.Human study with full informed consent was approved by Weill Cornell Medical College Institutional Review Board. Consent was obtained both in oral and written form with detailed documentation. Spin echo T2 data were obtained from 2 healthy volunteers at 1.5T, and a recent whole brain 3D T2prep spiral scans 154 MS patients was undertaken at 3T under the 3D T2prep spiral sequence. This cohort was used in this paper for the purpose of obtaining whole brain statistics and assessment of variability – a detailed study of pathological discrimination on MS will be carried out in future work. To this end, a regional parcellation was imposed on T2 images using the labeled Freesurfer atlas Next, a large study of lsqnonlin algorithm V variables – a daunting memory requirement. Fortunately, J(θ) is highly sparse due to the structure of q(θ), and its sparsity pattern was pre-computed and passed to lsqnonlin. Memory requirements for storing voxel neighborhood system and Jacobian was minimized by using sparse data types and a rewrite of the vendor-supplied lsqnonlin-related functions involving pre-allocating some large arrays. The final code was able to achieve 10–20 times speed improvement over a direct call to lsqnonlin.The list of 8 parameters are shown in Tsλ spaced logarithmically within  for each voxel, and one that gave residual norm between 102.0%–102.5% of the non-regularized residual norm was selected, as specified in previous NNLS reports Unfortunately choice of regularization parameter greatly affects the outcome, hence our NNLS implementation evaluated the chi-square criterion n we introduce the following rescaling:are held constant throughout the minimization, as follows. We start with nd term is the fully rescaled version which maintains constant, but in order to reduce the potential for instability or oscillations, we introduce a small step size to prevent large discontinuous jumps. This approach completely obviates the need for testing large ranges of regularization. We tested all cases with the same prior ratios γN = 0.1, γS = 0.1 and this gave consistent results across subjects, however in some cases slight tweaks to these presets produced somewhat better results.The 2Masks of WM and GM tissue classes were obtained using SPM8 software VN is the total number of voxels, and trueMWF and algMWF are the true and estimated MWF. There is little evidence of edge blurring, in fact we see higher tissue contrast than conventional map. Figure S1 and S2 in Sμ at various SNR levels, exhibiting the typical U-shaped behavior: low Sμ gives too much noise, high Sμ too much smoothing; an intermediate value provides the best numerical and visual compromise – here this is achieved at S = 0.01μ. The corresponding MWF maps visually reinforce this impression. Contrary to expectation, the highest Sμ did not produce the smoothest image, probably due to the realization of a different local minimum of the non-convex cost. Note that this simulation was not designed to investigate intra-tissue spatial variations; although it is possible to construct numerical phantoms for this purpose, we feel this is best investigated via in vivo data. Further, the use of 3 pools in the simulation might appear to inherently favor the multi-Gaussian model, but the comparison with conventional NNLS, which is agnostic to the number of pools, is still valid – the experiment was designed precisely to test the additional benefit of applying a realistic multi-pool model.Our purpose was to quantify error rate and to explore the blurring effect of spatial regularization at tissue boundaries. MWF maps in th echo image (40 ms), the average within each test tube of our MWF, and their measured T2 in parentheses. Note that this doped water phantom does not produce multiple pools – only differentially shortened single T2 pool. Thus, the purpose of this experiment is to assess accuracy and bias when the multi-pool assumption is violated. Clearly, our algorithm achieved quite good accuracy on this data, yet a small bias exists which is more prominent for T2 values close to the 40 ms myelin cutoff.Numerical convergence shows a classic pattern  is substantially reduced. White matter coverage is significantly larger, including frontal and lateral projection fibers which are frequently silent in NNLS. In MS patients the visual depiction and statistical discrimination of lesions is substantially enhanced.quality whole brain myelin maps in under 10 minutes when applied to fast but noisy T2 prep spiral sequences on which NNLS fails. The spiral results meet the clinical goal of whole brain MWF maps in under 10 minutes scan time, and can be invaluable in diagnosis, prognosis and longitudinal monitoring of efficacy of treatment-induced remyelination. Fast processing time could enhance clinical and routine applicability – however this was not the focus of current work. Implementation on high-end multi-core server hardware could potentially reduce processing time to just a few minutes – which would open up several interesting clinical applications which are currently impeded due to overly long execution time of existing algorithms. While simulation, phantom and in vivo results on conventional MESE scans indicate little bias, our MWF maps from fast spiral scans show upward bias in GM and spatial inhomogeneity, which merit further effort in sequence design. A modest level of residual bias, where a non-zero myelin fraction is reported when there is none, is expected behavior for model- and constraint-based methods when the model assumptions are violated severely.Our work provides a clear path to practical utility in applying quantitative relaxometry in the clinic, as compared to traditional visual assessment on FLAIR images, which are not quantitative. Our algorithm has the potential to produce What if there are more than 3 compartments, for instance a slowly relaxing component between 300 ms and 800 ms Although our method can easily accommodate any parsimoniously parameterized peak shape, the choice of Gaussian was motivated by simplicity, ubiquity and prior reports improve the definition of small lesions by preventing noise from occluding the lesion, as shown later by our results on demyelinating diseases. Additive noise model. In this work we have assumed Gaussian white additive noise, but a strong case can be made for Rician noise, especially in late echoes which have generally low signal levels. However, as is well-known, such models result in more challenging objective functions, necessitating more advanced minimization strategies which may not be amenable to least squares formulation used here. Given that spatial constraints already increase the numerical complexity of our approach manifold, we chose to stay with the Gaussian assumption in the interest of computational cost. This is in keeping with the vast majority of prior work in this area, where Gaussian assumption is routinely and successfully employed even in cases where it might be sub-optimal.These may potentially blur edges and small lesions or other pathology, but this can be prevented by a conservative choice of regularization parameter. On the contrary, spatial constraints can *Models involving 2 or 3 pure relaxing T2 components already exist Unlike the whole brain coverage we demonstrate, previous T2 relaxometry studies of MS are generally reported on selected slices during the fitting process by incorporating spatial constraints directly into the solution -e.g. see Spatial constraints are prevalent in image processing 2. Thus our method has far fewer degrees of freedom, where we have traded an unconstrained but quadratic cost function with guaranteed global minimum for a highly constrained but non-convex cost whose minimization is challenging. The risk of entrapment within inappropriate local minima and undesirable sensitivity to initial guess exist, but are outweighed by considerable gains, like unique solutions, better conditioning, and noise resistance. Our processing time and memory usage are a fraction of The spatially constrained optimization proposed here is similar to our prior work Our 3T spiral results suffer from apparent bias in GM, where we report higher numbers than previously reported. We attribute this to the spiral sequence rather than algorithmic issues, since the bias is not appreciable in simulations , phantomCertainly, bias and gradient issues result from the tradeoffs involved in speedy spiral acquisitions, but it is possible that the non-linear nature of our constrained model might be exacerbating it. Our approach requires explicitly fitting a fast and a slower relaxing component, hence in the presence of noise or artifacts could be more predisposed to finding a myelin signal even when one may not be present. We will consider other penalty functions to prevent this. Bayesian model order selection will be implemented to determine whether the data supports multiple peaks or single peaks. The proposed algorithm can be improved in other ways: replacing global, spatially invariant high-pass filter in the spatial term with locally adaptive smoothness penalties might better preserve tissue boundary. Plans to exploit edge-preserving spatial priors File S1Sμ at SNR  =  100 and 300 (Nμ  = 0.013). The optimal value was found at 0.01 for both noise levels. Figure S2, Visual results for spatial constrained (Nμ = 0.013) on brain simulation at SNR of 100 (top) and 300 (bottom), where Sμ = 0.0001, 0.001, 0.01, 0.02, 0.1, respectively, from left to right. The ones within red boxes provide the best visual and numerical result, and show that the optimal value of this parameter is not overly sensitive to SNR. Figure S3, Convergence of the proposed algorithm. Left: MWF maps computed after 20, 30, 80 and 100 iterations on an in vivo example. Right: The numerical convergence of the cost function shows a classic pattern, whereby convergence is reached at 20 iterations, and further iterations do not appreciably reduce the cost. Although MWF maps begin looking reasonable in as few as 20 iterations, we chose 30 iterations to provide a margin of error. Figure S4, MWF maps computed from another in vivo MS patient scan. Top to bottom are MWF maps from conventional method, spatial constrained method and FLAIR images. Arrows in FLAIR images point to lesions. Figure S5, Left to right, single axial slice of a MS patient showing A] T2-weighted image, B] MWF map from conventional NNLS method, C] MWF map from spatially constrained Gaussian method, and D] MWF map reconstructed from sparse L1-regularized method.Contains Figure S1, rMSE of MWF computed using proposed method on brain simulation with different (DOCX)Click here for additional data file.


The blood-brain barrier (BBB) dysfunction represents an early feature of Alzheimer’s disease (AD) that precedes the hallmarks of amyloid beta (amyloid β) plaque deposition and neuronal neurofibrillary tangle (NFT) formation. A damaged BBB correlates directly with neuroinflammation involving microglial activation and reactive astrogliosis, which is associated with increased expression and/or release of high-mobility group box protein 1 (HMGB1) and thrombin. However, the link between the presence of these molecules, BBB damage, and progression to neurodegeneration in AD is still elusive. Therefore, we aimed to profile and validate non-invasive clinical biomarkers of BBB dysfunction and neuroinflammation to assess the progression to neurodegeneration in mild cognitive impairment (MCI) and AD patients.We determined the serum levels of various proinflammatory damage-associated molecules in aged control subjects and patients with MCI or AD using validated ELISA kits. We then assessed the specific and direct effects of such molecules on BBB integrity in vitro using human primary brain microvascular endothelial cells or a cell line.We observed a significant increase in serum HMGB1 and soluble receptor for advanced glycation end products (sRAGE) that correlated well with amyloid beta levels in AD patients (vs. control subjects). Interestingly, serum HMGB1 levels were significantly elevated in MCI patients compared to controls or AD patients. In addition, as a marker of BBB damage, soluble thrombomodulin (sTM) antigen, and activity were significantly (and distinctly) increased in MCI and AD patients. Direct in vitro BBB integrity assessment further revealed a significant and concentration-dependent increase in paracellular permeability to dextrans by HMGB1 or α-thrombin, possibly through disruption of zona occludins-1 bands. Pre-treatment with anti-HMGB1 monoclonal antibody blocked HMGB1 effects and leaving BBB integrity intact.Our current studies indicate that thrombin and HMGB1 are causal proximate proinflammatory mediators of BBB dysfunction, while sTM levels may indicate BBB endothelial damage; HMGB1 and sRAGE might serve as clinical biomarkers for progression and/or therapeutic efficacy along the AD spectrum. Besides astrogliosis, activation and transmigration of blood-borne substances and circulating immune cells into the CNS is a less studied and underappreciated area in AD research [Despite overarching evidence, the amyloid hypothesis in Alzheimer’s disease (AD) first elaborated in 1991, has yet to provide positive outcomes notwithstanding the billions spent on clinical trials . In assoresearch –16. The Thrombin and high-mobility group box protein 1 (HMGB1) are key molecules of two most potent host defense systems that converge on the innate immune system, coagulation, and inflammation. We postulated that they may play significant roles in the BBB disruption since both are proinflammatory and both are known to disrupt vascular barriers in other tissues –20. ThroRelevant to our studies, HMGB1 impairs memory behavior in mice that is mediated via Toll-like receptor 4 (TLR4) and the receptor for advanced end product glycation (RAGE) . These pThe human study was approved by the institutional review board at the University of Kansas Medical Center (KUMC) and was performed in compliance with the Helsinki Declaration. All subjects were recruited from the KU Alzheimer Disease Center (ADC) following a written informed consent, and all demographic information was de-identified. Subjects in the AD, MCI, and aged control cohorts met the criteria as outlined in the 2011–2012 NIA/Alzheimer’s Association Guidelines for AD by McKhann et al.  and for Venous blood collection was performed with BD Vaccutainer® blood collection tubes and centrifuged. The serum samples were aliquoted and stored at −80 °C until analysis. Demographic information for these patient groups is shown in Table 2 exposure. In preliminary experiments, primary human brain microvascular endothelial cells (HBMEC) were cultured in Dr. KY Kim’s laboratory (KUMC) as described previously [The human cerebromicrovascular endothelial cell line (hCMEC/D3) was a gift from Dr. P.O. Couraud . This cell line has been widely used as a representative model of human BBB in vitro for mechanistic studies involving the molecular regulation of BBB integrity . Cells beviously .Human serum samples were thawed on ice and analyzed by enzyme-linked immunosorbent assay (ELISA) for quantification of HMGB1 , s100β , amyloid β (aa 1-42), and soluble receptor for advanced glycation end products (sRAGE) from R&D Systems , according to the manufacturers’ instructions. Soluble thrombomodulin (sTM) antigen (TMa) levels were assayed by kit , and sTM activity was measured as described previously .2) and phase contrast microscopy, respectively. Cells were maintained in treatment media  overnight prior to treatment with human recombinant HMGB1 protein (rHMGB1) with endotoxin levels lower than 0.1 EU per microgram of the protein . Following 3 h of treatment with rHMGB1 , α-thrombin  or control media, inserts were transferred to new 12-well plates and transport buffer added (pre-warmed HBSS buffer with antibiotics and 0.5 % BSA) to the apical (500 μL) and basal compartment (1000 μL). After incubation for 20 min at 37 °C under 5 % CO2 exposure, a mixture of florescent dextrans of increasing molecular sizes -70 kDa, 10 mg/mL) was added to the apical compartment. Dextran permeability  was measured at 30 min following the addition of dextrans. Apparent permeability coefficients  were calculated and expressed as percent control [Cells were seeded on Corning Transwell® polyester membrane inserts  as previously described . Monolay control . For phaImmunocytochemistry (ICH) for zona occludin-1 (ZO-1) was performed using primary anti-ZO-1 antibody , Alexa Fluor 488-conjugated secondary antibody and 4,6-diamidino-2-phenylindole  as described in .P value was set to less than 0.05 for statistical significance.Data were expressed as mean ± SEM or SD. Data were analyzed by one-way analysis of variance (ANOVA) followed by Dunnett’s or Tukey’s post hoc multiple comparison tests using GraphPad Prism Software Inc. . Part of the criteria for AD and MCI due to AD infers that other more likely diagnoses are less likely than AD. Although it does not totally eliminate, it clearly should limit contamination by other diagnoses such as vascular dementia, Parkinson’s disease with dementia, and primary systemic inflammatory diseases.Levels of various proinflammatory markers including Aβ, sRAGE, HMGB1, and S100β in serum samples derived from control subjects (NL), AD, or MCI patients  and TM activity . We also observed that the magnitude of dextran flux was more pronounced with the duration of exposure to HMGB1  when compared to dextran permeability resulting from exposure to 0.5 or 1 nM (p < 0.001). However, we did not observe a further elevation in thrombin-induced BBB dextran flux with longer exposure time (3 vs. 6 h), suggesting a maximum and sustained response following 3 h of exposure. The negative impact of HMGB1 and thrombin on BBB integrity is further confirmed by corresponding immunostaining of HBMECs that demonstrated a significant downregulation of ZO-1 expression at intercellular tight junctions (TJs)  Fig. .p < 0.05 and p < 0.05, respectively; Fig. We next determined the extent of BBB disruption following exposure to HMGB1 by assessing the permeability to florescent dextrans of increasing molecular sizes 4–70 kDa) across the hCMEC/D3 monolayers see “” section–70 kDa aAlthough rigorous methods are used by the KU ADC to enroll subjects in AD, MCI, MCI due to AD and normal cohorts, one can never fully eliminate other systemic illnesses that escaped notice. Such recruitment methods are part of the approach that our colleagues at the KU ADC take, quite similar to methods taken at other institutional ADCs. In this regard, our current results indicate that three potent proinflammatory and damage/danger-associated macromolecules are elevated in MCI and AD sera: Aβ, sRAGE, and HMGB1. They further suggest that one or more may herald the conversion of MCI to AD  can serve as surrogate biomarkers for diffuse microvascular damage . We had As with other vascular barriers , 18, humThe proinflammatory DAMP, HMGB1, dramatically enhanced BBB permeability to various molecular weight dextrans in primary HBMEC or hCMEC/D3 cultures, following incubation for 3 or 6 h. These BBB changes including the significant downregulation of ZO-1 expression at intercellular (TJs) clearly mirror what has been observed in vivo in animal studies that suggest the presence of amyloid beta is a factor in the “breach” of the BBB . In expeOthers have also shown that BBB dysfunction in rats, whether due to experimental stroke or traumatic brain injury (TBI), can be prevented by a neutralizing antibody to HMGB1 , 50. Outsource and target of proinflammatory factors is supported by numerous studies showing that the cerebral microcirculation is in an “activated proinflammatory” stage in neurodegenerative diseases such as AD [target for various proinflammatory factors. PAUSE Circulating Aβ is a proinflammatory cytokine-induced DAMP that binds to RAGE and TLR2 [source of these proinflammatory factors, and the axis in AD has attracted considerable attention [Over the last 15 years, the concept that the BBB might function both as ch as AD  and is aand TLR2 . Like S1and TLR2 , making ttention . Solublettention . The S10ttention . InteresJust in the last decade, it has become increasingly appreciated that inflammation and coagulation are linked evolutionary defense systems , a fact Also attesting to evolutionary linkage, direct relationships also exist between thrombin and HMGB1. HMGB1 is involved in a number of systemic vascular diseases , is incrFinally, we have envisioned our present data in corroboration with previous findings schematically in Fig. An increased understanding of the role of HMGB1 and thrombin in BBB dysfunction as well as activation and transendothelial migration of WBCs contributing to neuroinflammation in AD may allow for the discovery of novel therapeutic targets and treatment strategies. Not only might these facilitate treatment to halt progression in AD but these might also aid in means to detect the conversion from MCI to pre-clinical AD, as well as in other neurological disorders that display BBB dysfunction.


We analyze the motion of viscous and incompressible liquids in the annular space of controllable hydraulic resistances with a cylindrical linear slide-valve. This theoretical study focuses on the turbulent and steady-state motion regimes. The hydraulic resistances mentioned above are the most frequent type of hydraulic resistances used in hydraulic actuators and automation systems. To study the liquids' motion in the controllable hydraulic resistances with a linear cylindrical slide-valve, the report proposes an original analytic method. This study can similarly be applied to any other type of hydraulic resistance. Another purpose of this study is to determine certain mathematical relationships useful to approach the theoretical functionality of hydraulic resistances with magnetic controllable fluids as incompressible fluids in the presence of a controllable magnetic field. In this report, we established general analytic equations to calculate (i) velocity and pressure distributions, (ii) average velocity, (iii) volume flow rate of the liquid, (iv) pressures difference, and (v) radial clearance. Constant or controllable/laminar or turbulent hydraulic resistances are components of hydraulic machinery or hydraulic elements, which comprise hydrostatic actuation or automation systems –3. The hGenerally, the study of hydraulic resistances considers both the constructive/geometrical –6, 9 andThis report theoretically analyzes the motion of viscous incompressible fluids in the annular space of controllable hydraulic resistances using a cylindrical linear slide-valve in turbulent and stationary regimes. These hydraulic resistances are the most frequent type of hydraulic resistances used in hydraulic actuators and automation systems. In the existing literature, the information refers almost strictly to the laminar motion regime , 11, 13.p, which is necessary for the flow of the flow rate Q through the annular space between the piston  and the cylinder (body), and vice versa. This annular space/radial clearance is almost always the unique solution to seal these subensembles from the hydraulic actuation, automation elements, and machineries ). Additionally, in actual functional conditions, the annular space δ has different values in either axial or radial directions :for Umed, Vmed, and Wmed and the fluid unitary flow rates as Qθ, Qy, and Qz, which cross the space δ of unitary width in θ, y(r), and z directions, respectively:We can consider that the resultant motion between the slide-valve and the body is a predominant Poiseuille motion, and we can introduce the average velocities for the fluid as Equation  describekxo and kzo, which can be formally defined by the following relationships  and ReP ∈ , when the cylindrical linear slide-valve is concentrically placed in the hydraulic resistance body.Equation  offers aIn  we find p and the unitary volume flow rate Qz.For an established hydraulic resistance and a function of the served hydrostatical actuating and automation systems, we can determine all the parameters except for the pressure difference ΔThe mathematical relationships from the literature  and 16)16)) were16)) wereQz) and  and  can be uD /2 = (δ∗∗ + δ∗)/2, and the flow coefficient in the turbulent regime kz can be determined using ,,p from 33) allowp are imposed; thus, , a, a31), aη≅5 · 10−2 [(N/m2) · s ≡ Pa · s]  [ρ≅905 [kg/m3] [l≅0.020 [m] [δ∗≅ [mm] [δ∗∗≅ [mm] [P≅1500  [−] [Pcr≅1000 [−]  (δ < 5 [μm]). In fact, normal operation of the hydraulic resistance (avoiding blocked movement) always imposes the existence of a minimum clearance (δ ~ 10−6 [m]) and implies a unitary volume flow rate Qz > 0 that is as small as possible.The theoretical and experimental results presented above show that the unitary volume flow rate


D), texture coefficients (TC), dislocation density, and microstrain have been determined using X-ray diffraction data. Surface morphological studies were carried out using scanning electron microscopy (SEM) technique. The strong absorption bands at ~816 cm−1, 641 cm−1, and 482 cm−1 are associated with the coupling mode between Nb–O stretching modes observed in FTIR studies. The electromagnetic transmittance, absorption, studies of barium niobates in the X band frequency range frequencies using waveguide reflectometer technique are reported.The structural and microwave studies of lead-free barium niobates ceramics prepared by the high temperatures solid state reaction technique are reported. The structural parameters such as the lattice constants, average crystallite size ( Materials that can absorb microwaves will eliminate electromagnetic radiation pollution. Wide unfolding applications of electromagnetic absorbers have affected engineers to explore relating to optimum design without their algorithms . Ferroel devices , 4. Recetructure .2O6 ceramics using simple low cost solid state technique from simple inorganic materials. A detailed significant investigation of the structural, microstructural, and mechanical properties of barium niobate has been reported. Electromagnetic transmittance and absorption of samples in the X band frequency range frequencies using waveguide reflectometer technique are reported.The purpose of this study was to prepare BaNb3 (99.95%)) and niobium penta-oxide (Nb2O5 (99.999%)) were used as starting materials. This powder was again mixed in stoichiometric proportion and ground for 4 hours in acetone medium to obtain the desired compound. This mixture was initially sintered at 1200°C for 10 hrs and further at 1000°C for 24 hours in a muffle furnace (given by (2O6) ceramic is shown in α radiations (Philips Diffract meter PW 3710). The structural parameters such as the lattice constants, average crystallite size, and texture coefficients have been determined using X-ray diffraction data. This powder was pressed into pellets in a hydraulic press at 10 ton/cm2 for 10 minutes. The surface morphology was studied using scanning electron microscope (SEM JEOL-JSM 6360). Transmission of microwaves due to bulk sample was measured point by point using transmission/reflection method with rectangular waveguide, consisting of the X band generator, isolator, attenuator, directional coupler, and RF detector.AR grade chemicals of high purity barium carbonate , θ is Bragg's angle, and β is full-width half maxima (FWHM) in radians.X-ray diffraction technique is a powerful tool to analyze the crystalline nature of the materials. If the material to be investigated is crystalline, well defined peaks will be observed. X-ray diffractogram of barium niobate 2= 3.89 Å . NanocryρD). The term lattice microstrain (ε) is more frequently used in materials engineering. It is defined as the deformation of an object divided by its effective-length. The dislocation density (ρD) and microstrain (ε) were calculated as [ε) and particle size of the sample graphically given by [ε is the lattice microstrain, D is the grain size (in Å), λ is the wavelength of the radiation (in Å), θ is the Bragg angle, and β is full-width half maxima (FWHM) of a XRD peak in degree.The defects distort the regular atomic array of a perfect crystal. Dislocations are 1D crystalline defects marking the boundary between slipped and unslipped regions of material. The amount of defects in the as-deposited film is assessed by dislocation density (lated as (3)Dislogiven by , 12(5)βD) and the slope represents the strain (ε). Microstrain (ε), crystallite size (nm), and dislocation density (D) are tabulated in Using a linear extrapolation fit to Williamson-Hall analysis plot shown in , the intTexture is perceived in almost all engineered materials which can have a great influence on properties of materials. Diffraction patterns from samples containing a random orientation of crystallites have predictable relative peak intensities. Texture frequently represents a pole figure, in which a defined axis  from each of a representative number of crystallites is mapped in a stereographic projection. Texture is the distribution of crystallographic orientations of a polycrystalline sample in materials science. Quantitative data concerning the preferential crystal orientation can be obtained from the texture coefficient (TC) :(6)TChkhkl) increases, the preferential growth of the crystallites in the direction perpendicular to the hkl plane is greater  is like typical pebble (beach stone) structure  is larger than of the crystallite size obtained from Scherrer's equation. Thus, a single grain can be composed of several crystallites [The morphology of barium niobate  result from surface-adsorbed atmosphere (like moisture and humidity) [−1 and 1755 cm−1 may be attributed to O–H bending vibrations. The strong absorption bands at ~816 cm−1, 641 cm−1, and 482 cm−1 are associated with the coupling mode between Nb–O stretching modes [The infrared spectral analysis is effectively used to understand the chemical bonding and it provides information about molecular structure of the synthesized compound. The characteristic absorption peaks in the range from 400 to 4000 cmumidity) . Peaks aThe insertion loss (transmission) and absorption loss of barium niobate sample were measured by the rectangular waveguide reflectometer setup shown in 5+↔Nb4+ also because the frequency of the hopping ions could not follow the applied field frequency and it lags behind.The variation of insertion loss and absorption loss of barium niobate is a function of frequency in the X band (8–12 GHz) which exhibits trivial wavy like nature shown in Absorption is the heat loss under the action between electric dipole or magnetic dipole in material and the electromagnetic field. Low absorption loss in a large band of frequencies indicates potential for microwave applications . These ba = b = 12.343 Å and c = 3.889 Å, and average particle size was 37.5 nm with preferred (210) textured orientation. Pebble (beach stone) like morphology with grain size varied within the range of 2–4 μm, confirmed by SEM. The robust absorption bands at ~816 cm−1, 641 cm−1, and 482 cm−1 are related to the coupling mode between Nb–O stretching modes. Microwave studies (absorbance and reflectance) depict periodical behaviour which can be used to perform like sensors, actuators, detectors, and filters.Lead-free ferroelectric barium niobate that has been synthesized by the solid state reaction method was investigated. It absolutely was shown by X-ray diffraction that the space temperature shows tetragonal structure, lattice parameters