Computations were performed using automated ab initio molecular dynamics techniques. High temperature synchrotron X-ray diffraction on laser heated aerodynamically levitated samples provided experimental data on volume change during tetragonal-to-cubic phase transformation (0.55 ± 0.09% for ZrO2 and 0.87 ± 0.08% for HfO2), density and thermal expansion. Fusion enthalpies were measured using drop and catch calorimetry on laser heated levitated samples as 55 ± 7 kJ/mol for ZrO2 and 61 ± 10 kJ/mol for HfO2, compared with 54 ± 2 and 52 ± 2 kJ/mol from computation. Volumetric thermal expansion for cubic ZrO2 and HfO2 are similar and reach (4 ± 1)·10−5/K from experiment and (5 ± 1)·10−5/K from computation. An agreement with experiment renders confidence in values obtained exclusively from computation: namely heat capacity of cubic HfO2 and ZrO2, volume change on melting, and thermal expansion of the liquid to 3127 °C. Computed oxygen diffusion coefficients indicate that above 2400 °C pure ZrO2 is an excellent oxygen conductor, perhaps even better than YSZ.Structure and thermodynamics of pure cubic ZrO ZrO2 and HfO2 are isostructural and exhibit monoclinic-tetragonal-cubic transformations before melting at 2710 and 2800 °C, respectively. Thermodynamic assessments for pure oxides to the melting temperatures are required for prediction of phase composition, stability, and microstructure in multicomponent systems using Calphad type5 approaches, which have proven to be extremely useful in metallurgy and ceramics.Hafnium and zirconium oxides are indispensable constituents for development of the formulations for structural ceramics2 and ZrO2 phases was performed by Wang, Zinkevich and Aldinger in 20066 (referred further as the WZA assessment). It was adopted by most researchers for Calphad modeling for ZrO2- and HfO2- containing systems7. A plethora of computational and experimental investigations has been devoted to the thermodynamics of monoclinic and tetragonal phases9, and the structure of the liquid was studied experimentally and computationally11. However, for the cubic phases we only know unambiguously that they are stable for a few hundred degrees before melting and have unit cell parameters somewhere between 5.1 and 5.3 Å12. Measurements of enthalpy increments for cubic ZrO2 and HfO2 phases were performed by Pears et al. in 196313. However, their samples were exposed to carbon vapor in a graphite furnace and their data were not used in the WZA assessment6. The value for ZrO2 fusion enthalpy (87 kJ/mol) reported in the JANAF tables14 and used by WZA6 can be traced15 to an assessment made by Kelley in 193616 based on the slope of the solidus in early ZrO2-SiO2 and ZrO2-MgO phase diagrams. Thus, we conclude that no direct experimental measurements of fusion enthalpy for ZrO2 and HfO2 have been performed to date.The latest review of experimental data and assessment of the Gibbs free energy functions for all HfO2 and HfO2. The combination of experimental and computational method offers a unique opportunity for corroboration that is essential given the challenges associated with each approaches. On the experimental side, the difficulties lie in thermal gradients unavoidable in conditions of uniaxial laser heating of aerodynamically levitated samples used for calorimetry18 and X-ray diffraction21. On the computational side, the difficulties reside in reaching sufficiently large system sizes and sufficiently long simulation times while still using accurate electronic structure calculations as well as ensuring proper modeling of all forms of excited states . Thermal expansions of cubic ZrO2 and HfO2 and volume change during the transition from the tetragonal phase were measured by high temperature X-ray diffraction experiments. The agreement between computed and measured values for fusion enthalpies and for thermal expansion supports the validity of the heat capacities, diffusion coefficients, and volume change upon melting obtained from the computation.In this work, we sought to fill this gap in the available data by measuring and computing the fusion enthalpies of ZrOab initio computations is presented in Table 2 and HfO2 from computation and experiment are discussed together in the same order as in Tables A summary of the results of 2 and HfO2 were accepted from the WZA6 assessment and were used in this work for the evaluation of the temperature of the diffracted volume of the laser heated samples. Cubic ZrO2 and HfO2 have a fluorite structure with space group Fm3m and 4 formula units per cell (Z = 4). Besides the mineral fluorite (CaF2), which gives the name for the structure type, natural and synthetic uraninite (UO2), thorianite (ThO2), and cerianite (CeO2) are found in this structure. Thermophysical properties of UO2 and ThO2 above 2000 °C were studied extensively for nuclear reactors safety assessments23, and a comparison of the high temperature structures for UO2 with ZrO2 and HfO2 from this work is given at the end of this paper. In the tetragonal  and cubic phases, Zr and Hf are coordinated by eight oxygen atoms, but in the monoclinic structure (P21/c), stable at room temperature, the cation coordination is 7. Unit cell parameters of the tetragonal and cubic ZrO2 and HfO2 at transition temperatures were refined from XRD patterns containing both phases . Our value for the volume of tetragonal ZrO2 at the transition temperature is consistent with the trend of close to linear volume expansion of the tetragonal phase, yielding an average value for of volumetric thermal expansion (αv) of 3.9·10−5 K−1 in the 300–2311 °C range.Temperatures for tetragonal-cubic transition and melting points for ZrOa × c) for tetragonal ZrO2 and HfO2 are 3.690 × 5.337 Å and 3.669 × 5.327 Å, respectively. The variation in cell parameters from Pawley refinements of individual patterns on the same sample is within ±0.001 Å  Å at 2330 °C and for HfO2 as 5.30(1) Å at ~2700–2750 °C. The latter value for cubic HfO2 was cited in reviews by Glushkova27 and Wang12. Considering experimental conditions, these values probably refer to oxygen deficient cubic ZrO2−x and HfO2−x, known to exist in Zr-O and Hf-O systems28, and thus the differences with the results of our work are expected. Passerini29 derived room temperature cell parameters for cubic ZrO2 and HfO2 as 5.065 Å and 5.115 Å by extrapolation from their fluorite solid solutions with CeO2. Combining his values with cell parameters before melting from this work (5.291 and 5.265 Å) gives an average volumetric thermal expansion from room temperature to the melting points of ~5·10−5 K−1 for ZrO2 and ~3·10−5 K−1 for HfO2.We did not locate any previous reports on experimental or computational values for the thermal expansion. There are few reported values for the cell parameters of high temperature cubic ZrO2 and HfO2 as 35.22 and 34.11 Å3 per formula unit, respectively. This compares well with experimental values of 35.15 and 34.57 Å3 per formula unit by Hann30. The density change of cubic ZrO2 and HfO2 with temperature from high temperature XRD data is shown in Tables b initio MD results for volume change upon melting as well as density and thermal expansion of the liquid phases. ZrO2 and HfO2 show similar expansion upon melting, 11 ± 2% and 10 ± 2%, respectively. For the temperature range sampled by computation, volumetric thermal expansions of liquid ZrO2 and HfO2 fall within (8 ± 1)·10−5 – twice that for the cubic phase. Despite known biases in the lattice parameters calculated via DFT methods31, calculated volume changes tend to be much more accurate, due to systematic error cancellations.At 25 °C, our computation gives volume of monoclinic ZrO11. The density of liquid ZrO2 was recently measured by Kohara et al.11 from the dimensions of aerodynamically levitated liquid ZrO2 spheroids. His values, 5.1–4.9 g/cm3 for in 2710–3000 °C, are in good agreement with our results 4.86–4.74 g/cm3 at 2827–3127 °C. The density of liquid HfO2 was refined from PDF measurements by Gallington et al.10 as 8.16 g/cm3, compared with 8.73–8.53 g/cm3 at 2827–3127 °C from our computations.To the best of our knowledge, the volume change on melting has not been previously quantified. There are some published values for the density of liquid phases, since it has to be measured or refined for the analysis of the liquid structure by the pair distribution function (PDF) methodAb initio MD computations resulted in values for fusion enthalpies of (ΔHfus) 54 ± 2 kJ/mol for ZrO2 and 52 ± 2 kJ/mol for HfO2. They agree, within experimental uncertainties, with values from the drop and catch calorimetry from samples levitated in argon flow . This cannot be related to the sample reduction during levitation in Ar flow, as the calorimeter is not enclosed in the chamber, there is enough air entering in the levitation stream through turbulence to prevent ZrO2 and HfO2 reduction, and the samples were white in color after the drop experiments in Ar. We attribute observed differences to possible oxygen dissolution in ZrO2 and HfO2 melts, an effect previously observed by Coutures32 in a number of oxide melts. The possibity of oxygen dissolution in molten ZrO2 has profound implications for Zr-O phase equilibria at high oxygen fugacities and deserves a separate in-depth study.2, reviewed in detail by Wang et al.28, fusion enthalpy was kept fixed to the value 87 kJ/mol from JANAF tables14; it was optimized to 68 kJ/mol in Chen et al.’s33 assessment for the ZrO2-YO1.5 system, while Chevalier et al.34 obtained 90 kJ/mol. The value 87 kJ/mol was also accepted in the WZA6 assessment and used for the calculation of ZrO2 fusion entropy (ΔSfus = ΔHfus/Tm (K) = 29 J/mol/K). The fusion enthalpy for HfO2 was then estimated6 from the melting temperature based on the assumption that it has the same fusion entropy as ZrO2. It must be noted that the widely used value for ΔHfus ZrO2 from the JANAF Thermochemical tables14 can be traced back to the 1951 data compilation by Wagman et al.15 The same value is reported in Glushko’s35 compendium of thermodynamic properties of individual substances with reference to Kelley 193616 who calculated heats of fusions from available freezing point data of the binary systems ZrO2 with SiO2 and MgO. This approach is limited by a lack of information concerning activities in the liquid and solid solutions and by its reliance on the accuracy of the phase diagram determination. It is impressive that Kelley’s16 early assessment held for 80 years without any challenge.In most of the assessments of the thermodynamic functions of cubic ZrO2 and HfO2 in this work (54 ± 2 and 52 ± 2 kJ/mol) are substantially lower than Kelley’s 87 kJ/mol value included in JANAF tables14 and used in the most current thermodynamic assessments36. They agree, within experimental uncertainties, with our drop and catch calorimetry measurements. Using accepted melting temperatures, the entropy of fusion for ZrO2 and HfO2 calculated as 17 J/mol/K, which is substantially lower than ΔSfus 29 J/mol/K value obtained from Kelley’s estimate and used in the WZA6 assessment. While our experiments were in progress, a ΔHfus for ZrO2 was reported by Kim et al.36 as 26–49 kJ/mol from classical MD simulations based on interatomic potentials. We did not locate any reports on the computation of the fusion enthalpy of HfO2.The values computed for the fusion enthalpies of ZrO17, drop and catch calorimetry cannot yet provide reasonably accurate values for the heat capacity due to differences in heat loss by radiation from different temperatures. The heat capacities of cubic ZrO2 and HfO2 obtained from ab initio MD computations are 111 ± 7 J/mol/K and 126 ± 4 J/mol/K, respectively. The values computed for liquid ZrO2 and HfO2 at the modeled temperatures are close to the values for the cubic phase when uncertainties are taken into account  and ZrO2−x – liquid phase boundaries37. Heat capacities of cubic and liquid ZrO2 calculated from different assessments are reviewed by Wang et al.28 and for most models, they are in the range of 75–90 J/mol/K for cubic ZrO2 and 80–100 J/mol/K for the liquid, below 3727 °C. Our computed values are close to 15R (where R is the gas constant) and substantially higher than those used in the assessments and higher than the 9R high temperature limit of Dulong and Petit for the contribution of lattice vibration. With the exception of UO2, which melts at 2874 °C, there are no experimental data for the heat capacity of fluorite type oxides melting in a comparable temperature range. Ronchi et al.39 reported measurements of heat capacity for UO2 from 1600 °C to 5000 °C using a custom-designed laser flash instrumentation. Their results indicate that UO2 heat capacity exceeds 20R before melting, decreases to 15R after melting and decreases further to the 9 R limit only above 4000 °C. The excess heat capacity in UO2 at high temperature is attributed to both electronic transitions and to disorder on the oxygen sublattice. The latter is also known as the Bredig40 transition, which is common among fluorite halides and oxides above 0.8·Tm. Clearly, the high temperature heat capacity needs further study.As previously discussedFm3m) all atoms are located on special equivalent positions – cations on 4(a) at the origin and anions on 8(c) at ¼, ¼, ¼. In stoichiometric HfO2 and ZrO2, both sites are fully occupied, and the structure is uniquely defined by its unit cell parameter and the atomic displacement parameters for Zr or Hf and O atoms. In ab initio MD computations, HfO2 and ZrO2 stoichiometries were preset by the number of atoms in the simulation. High temperature diffraction experiments were performed in oxygen flow, and the samples remained white in color after melting, but the possibility of thermally induced oxygen defects in the cubic phases cannot be ruled out. The quality of the diffraction data did not allow refinement of oxygen occupancies due to the strong correlation with atomic displacement parameters (ADP). Isotropic ADPs were refined from selected XRD patterns as mean square displacement amplitude Uiso (Å2) and estimated from snapshots of MD trajectories (see Supplementary Information). Uiso for Zr and Hf and for oxygen in HfO2 are in agreement from XRD and MD and vary within 0.03–0.05 Å2 for cations and increase from 0.03 to 0.07 for oxygen in hafnia. Both experiment and computation indicate larger displacement amplitudes for oxygen in zirconia: Oxygen Uiso was determined to range from 0.08 to 0.15 Å2 from XRD data, while MD results indicate even larger amplitudes: from 0.19 to 0.29 Å2. It must be noted that, in our related experimental and computational study of lanthanum zirconate41, we also found good agreement in thermal expansion, but higher O displacement amplitudes from ab initio MD compared to those inferred from high temperature XRD data.In the fluorite structure . Both oxides are believed to exhibit Bredig transitons above 0.8·2O3 and Lu2O3 melt at 2435 and 2490 °C, respectively, and are stable in bixbyite or C-type structure , which is often described as a derivative of a defected fluorite structure having ordered vacancies. Their linear thermal expansion was studied21 both in argon and oxygen and was reported to not exceed 8.5·10−6 K−1 with Uiso values for Yb and Lu below 0.05 Å2 up to the melting temperature and Uiso values for O less than 0.07 Å2. Lanthanum zirconate (La2Zr2O7 or LZ) is an example of compound stable up to the melting temperature in the pyrochlore  structure, which is often described as a defected fluorite structure with ordering of both cations and oxygen vacancies. Neutron diffraction in Ar atmosphere indicates that it does not display an anomalous thermal expansion or oxygen mobility indicative of a Bredig transition. The linear thermal expansion of LZ was reported as ~7·10−6 K−1 from above 1650 °C to the melting temperature of 2300 °C, with Uiso values for O and La not exceeding 0.07 Å2 and that of Zr remaining below 0.03 Å2 20.Yb2 and HfO2 (~12·10−6 K−1) are substantially higher than for LZ and C-type Yb2O3 and Lu2O3 (<8.5·10−6 K−1), and lower than that observed before melting in UO2 (~30·10−6 K−1) and defect fluorite YSZ (~25·10−6 K−1)20, and similar to the value accepted44 for ThO2 (14·10−6 K−1). Notably, despite apparently higher oxygen mobility in ZrO2 than in HfO2, their molar heat capacities and volume changes on melting are the same within uncertainties. Computational and experimental results suggest dynamic disorder on the O sublattice in both ZrO2 and HfO2.The linear thermal expansion of fluorite ZrO2 and HfO2 at temperatures where the cubic fluorite phase is stable and into the liquid range, thereby facilitating future assessments. The experimental confirmation of thermal expansion and fusion enthalpies validate the accuracy of computational approaches and open the way for further computational studies of the high temperature thermodynamics of more complex systems. Our combined approaches are easy to generalize from HfO2 and ZrO2 to a broader range of systems. Indeed, we have applied the same combined experimental and computational methods to a wide range of oxides . In addition, the computational method has been employed to study dozens of systems45, including oxides46, carbides, such as the Hf-Ta-C-N system47, and metals48.The performed computations and experiments fill gaps in the available thermodynamic data for pure ZrO49 to model HfO2 and ZrO2. All electronic structures were calculated by the Vienna Ab-initio Simulation Package (VASP)50, with the projector-augmented-wave (PAW)51 implementation and the generalized gradient approximation (GGA) for exchange-correlation energy, in the form known as Perdew-Burke-Ernzerhof (PBE)52. The valence configuration was ([Ar]3d10)4s24p64d25s2 with cutoff radius of 1.625 Å for zirconium, ([Kr]4d104f145s2) 5p65d26s2 with cutoff radius of 1.614 Å for hafnium; for oxygen, the 2 s and 2p electrons were relaxed with cutoff radius of 0.820 Å. This required a plane-wave basis set with the cutoff energy of 400 eV.We employed first-principles density functional theoryk-meshes generation with a k-point density of 153/Å−3 in the Brillouin zone. First-principles molecular dynamics (MD) techniques were utilized to simulate atomic movements and trajectories. The MD simulations were carried out under a constant number of atoms, pressure and temperature condition  with a time step around 2fs. The thermostat was conducted under the Nosé-Hoover chain formalism54. The barostat was realized by adjusting the volume every 80 steps according to average pressure. Although this did not formally generate an isobaric ensemble, this approach has been shown55 to provide an effective way to change volume smoothly and to avoid the unphysically large oscillation caused by commonly used barostats. MD simulations were carried out with 90 Zr (or Hf) and 180 O atoms in a periodic cell. Employing periodic boundary conditions is a completely standard way to model extended condensed phases in these types of calculations. The cell size is as large as 16 Å to reduce the finite-size effect. The liquid phase was prepared by heating the solid up to 6000 K (about twice the melting temperature) for 0.5 picoseconds. The liquid is then cooled to the simulation temperature. MD simulations were performed for a sufficiently long time to achieve convergence. The length of MD trajectory varies from 14 to 62 picoseconds, depending on convergence, but generally, 30–50 picoseconds were sufficient. On average, computations took about 25,000 CPU hours per data point, which required around two weeks on 64 cores of a computer cluster. Theoretical X-ray diffraction calculations were carried out using the AFLOW package56. MD trajectory was sampled every 80 ionic steps, which formed a set of snapshots that were used to generate X-ray diffraction patterns averaged for the final analysis.The electronic temperature was accounted for by imposing a Fermi distribution of electrons on the energy level density of states. The electronic temperature was set consistently with the ionic temperature. We used automated 2 and HfO2 beads, 2–3 mm in diameter, prepared by melting of powders purchased from Alfa Aesar  with a 400 W CO2 laser. Samples were first melted into oblate spheroids in a copper hearth, followed by melting in an aerodynamic levitator, as described in detail elsewhere17. High temperature XRD experiments were performed with the aerodynamic levitator57 at beamline 6-ID-D at the Advanced Photon Source (APS) at Argonne National Laboratory. Diffraction images were collected with a Perkin Elmer XRD1621 amorphous silicon detector in transmission through the upper part of laser heated beads freely rotating in oxygen flow through a levitator nozzle. The X-ray beam (λ = 0.12359(7) Å) was collimated to 0.5 mm wide, 0.2 mm tall rectangular shape. All images were recorded as a sum of 120 0.1 s exposures. The diffraction images at room temperature with the laser off were recorded first; then the sample was heated by a 400 W CO2 laser in 50–100 °C increments as monitored with a Chino IR-CAS8CS pyrometer with 1 mm spot size set to 0.92 emissivity and 0.85 window transmission corrections. Image calibration, integration, and sequential Pawley and Rietveld refinements of XRD patterns were performed with the GSAS-II software58, backgrounds were fitted manually for each pattern and were not refined. NIST CeO2 SRM674b powder standard was used to calibrate detector tilt and rotation angles, beam center position and sample to detector distance (1036.2 mm). Unit cell parameters for laser melted monoclinic ZrO2, and HfO2 were refined using conventional powder XRD with internal NIST Si640C standard and Bruker D8 instrument. In a sequential refinement of high temperature patterns, sample displacement was refined for each sample bead at room temperature from calibrated cell parameter and fixed for all refinements of high temperature patterns. In Rietveld refinements, sample absorption and oxygen occupancy were not refined to avoid correlation with atomic displacement parameters. Fusion enthalpies for ZrO2 and HfO2 were measured using drop and catch calorimetry. The technique and apparatus were described in detail elsewhere18. Schematic diagrams and photographs are provided in Supplementary Information together with data from all experiments.X-ray diffraction (XRD) and calorimetry experiments were performed on polycrystalline ZrOSupplementary information


The ultimate aim was to identify a parameter based on the T1 relaxation time distribution as a biomarker to biochemical features of osteoarthritis.The multi‐exponential character of T0 = 70 μT to 600 mT. The data were analyzed in terms of T1 distributions on a log‐time scale using inverse Laplace transform, whereas integral properties such as mean T1s and distribution widths were obtained without data inversion from logarithmic moment analysis and a stretched‐exponential fit to the data. Attempts were also made to differentiate between water dynamic components through multi‐Lorentzian decomposition of average relaxation‐rate dispersions.Osteoarthritis conditions were simulated by enzymatic digestion of cartilage with trypsin. Fast‐field cycling NMR relaxometry was carried out in the magnetic field range B1 distribution in bovine articular cartilage was found to be bimodal, with the dominating, long component shifting toward larger values following trypsin digestion. The effect is more prominent toward lower magnetic field strength. This shift leads to an overall increase of the distribution width and an equivalently more pronounced deviation from exponential behavior.T1 distribution functions at fields of 0.5 T and below, and the stretched‐exponential decay fit exponent β, show a significant trend after trypsin digestion of cartilage. These 2 parameters are suggested as possible biomarkers for osteoarthritis in humans and can be acquired entirely in vivo, with increasing significance for lower magnetic field strengths.The logarithmic width of T A statistically significant difference was found between osteoarthritic and healthy cartilage for both the dispersion amplitude and the area of the QRE peaks,1 and T2 when the samples were subject to external load.T1∼B0α at B0 < 25 mT was found to correlate weakly with Mankin grade but significantly with other biomarkers.Articular cartilage (AC) is a thin layer of connective tissue that covers and protects the articular surfaces of bones. One form of degeneration of articular cartilage is called osteoarthritis (OA), which is one of the major causes of mobility disability among the elderly. The MRI techniques developed for early diagnosis of OA exploit spatially resolved measurements of T1 distribution, g(T1), underlying a total magnetization relaxation function totM(t). Our particular goal was to investigate the field dependence of g(T1) and see whether it is affected by the enzymatic treatment of cartilage that mimics the early stage of OA  and thus has the potential of being a biomarker for OA.In this work, we aim to analyze FFC relaxation data in terms of a T1 relaxation in AC can be anticipated from its zonal structure. Indeed, spatially resolved measurements of T1 on bovine hip’s cartilage samples at B0 = 0.27 T1 ranges between 30 ms in the calcified zone and 350 ms in the transitional zone, which is over 1 order of magnitude  over the entire range of B0 covered by a typical FFC instrument (B0 ≤ 0.6 T), or at least below 0.27 T where this observation was made.Nonexponential TM(t) into a histogram of T1, which then can be submitted to further statistical analysis or used as a relaxation metric in itself. In this work, the ILT is used primarily for selective T1‐component monitoring, whereas statistical  properties of distributions such as the geometric mean T1 and the geometric standard deviation gσ are obtained without data inversion from a logarithmic moment analysis (LMA).g(T1) is available from a stretched‐exponential fit to M(t), which gives the arithmetic mean T1 and a stretching exponent as the measure of the degree of nonexponentiality. All 3 methods are complementary to each other and used here in comparison, with the aim of testing their robustness toward routine measurements.In practice, nonexponential NMR relaxation is analyzed using inverse Laplace transform (ILT). A number of ILT algorithms are available1‐relaxation dispersion can assist in probing the multicomponent relaxation in the frequency domain. With a good accuracy, a correlation time distribution, g(cτ), can be obtained through a multi‐Lorentzian decomposition of a given relaxation rate profile. This sort of analysis assumes that the relaxation rate at every B0 is a sum of rates of elementary relaxation processes driven by fluctuations with exponential correlation functions. We will refer to such processes as Bloembergen‐Purcell‐Pound–type relaxation. Such a decomposition is generally possible mathematically, and is expected to be robust, regardless of the underlying correlation functions and detailed molecular dynamics models. The formalism of the multi‐Lorentzian decomposition is introduced here instead of the power‐law approximation to the T1 dispersiong(cτ) and the changes caused by enzymatic treatment of cartilage.A shape analysis of T22.11‐relaxation decays were recorded on a commercial field‐cycling relaxometer Spinmaster FFC2000  in the magnetic field range B0 = 70 μT to 600 mT corresponding to the 1H Larmor frequency ν0 = 3 kHz to 25 MHz. The minimum value of 3 kHz is beyond the lower limit of 10 kHz recommended by the relaxometer manufacturer, given background magnetic fields. However, because dispersion profiles does not exhibit a tendency toward a plateau below 10 kHz, as can be expected if the background fields predominate, it appears appropriate to keep the corresponding data, provided greater care is taken. The magnetic field varied from the highest value downward in logarithmically spaced steps. The number of steps was 20 when scanning over the entire field range and 50 for a separate scan over the QRE region (ν0 = 0.4 MHz‐4 MHz). A pulse sequence with a prepolarization pulse was used at ν0 < 5 MHz, which produced M(t) in a form of decay  was a recovery function. The relaxation delay tev varied from 0.01 to 5‐10 × T1, in 24 logarithmically equidistant steps. With 4 averaging scans per delay, a 20‐point profile was acquired under 2 hours. The FID acquisition field was fixed at 0.4 T (ν0 = 16.7 MHz), the 90° RF pulse length being 7.5 μs. The field‐switching time was set to 3 ms  was performed by the program UPEN.1 with logarithmically sized bins.The inverse Laplace transformation of 1, <T1>g, and the geometric SD of T1, gσ, were calculated without data inversion using an LMA. The LMA algorithm consists, in essence, of a numerical integration of M(t) that is preliminary normalized to , followed by a few elementary operations.The geometric mean TσlnT12 is the variance of T1 on the logarithmic time scale. The lower limit of gσ is 1, which corresponds to a single exponential T1 relaxation. The logarithm of gσ is proportional to the width of a T1 distribution when the latter is plotted against the logarithm of T1. This makes gσ a convenient parameter to be used alongside the ILT histograms with a logarithmical abscissa. For a unimodal, symmetrical histogram, σg-1 is approximately equal to the decadic logarithm of the ratio of the largest to the smallest T1 at half maximum; as such, σg-1 measures the T1 distribution in terms of decades (or orders of magnitude).where The stretched‐exponential fit is a simple phenomenological modelβ   measures the deviation from a single exponential (inversely correlated with gσ). The arithmetic mean T1, <T1>a, can be conveniently calculated from β and Kτ asin which the stretching exponent Γ denotes the gamma function. This stretched‐exponential fit is robust and less demanding for the completeness of the data compared with the LMA; however, it does not suit the case of distributions with well‐resolved and sharp T1 components. Because Equation 2 is a phenomenological model, the parameter β is correlated with gσ only qualitatively, as well as with other measures that depend on the second moment of a distribution.where 2.3<R1>a. By definition, <R1>a=1/<T1>h where <T1>h is the harmonic mean T1. In principle, <T1>h can be calculated from ILT histograms of T1. However, this scheme was found to introduce a large scattering in values and therefore is considered impractical. Instead, we recommend using the approximation <T1>h≈<T1>g2/<T1>a,<T1>g and the arithmetic <T1>g means are taken from the LMA and the stretched‐exponential fit, respectively. Note that the multi‐Lorentzian analysis of dispersion profiles is also applicable when relaxation functions are approximated by a single exponential. Although being of limited utility in case of a T1 distribution, the single‐exponential fit to M(t) gives the least scattered dispersion profiles among the present parameterization methods (see subsequently).This analysis applies to variable‐field measurements of the arithmetic mean relaxation rate a” in <R1>a is omitted for simplicity. The model for R1(ν0) is a weighted sum of N contributions of Bloembergen‐Purcell‐Pound type, representing uncorrelated random processes with correlation times τc,i:Henceforth the brackets and subscript “τ~c=3τc.R1(ν0). First, it is Fourier transformed to represent data as a sum of exponentials in the time domain, and then it is submitted to a multi‐exponential decomposition by means of ILT. Because R1(ν0) is measured at logarithmically equidistant frequencies, a special Fourier‐transform algorithm called FFTLog is used.which is, with a high accuracy, approximated by a sum of single Lorentzian dispersions with an effective correlation time 2.4Samples of bovine articular cartilage were taken from calf knee joints by slicing them to a depth of several centimeters along the bone direction with the aid of a commercially available bow saw. The thickness of the slices was approximately 4 mm. A cartilage layer was separated from the subchondral bone by using a manual cutting machine. The cut chips of cartilage were 5 mm to 10 mm long, depending on the radius of curvature of the joint’s surface. To keep the whole of the calcified zone, which is only a few hundred micrometers thick and has a wavy surface, we had to cover a certain part of the adjacent bone when cutting. Each chip was then visually examined, and those containing a considerable amount of the subchondral bone were discarded. Thus, we do not expect bone marrow, if any, to contribute significantly to the NMR signal. A dozen or so of cartilage chips collected from 1 spot of the knee joint  constituted 1 NMR sample.If no enzymatic treatment was applied, the cartilage chips were kept in pure physiological saline solution  for 24 h under constant agitation at room temperature. The chips were removed from the phosphate buffered saline 2 hours before the NMR measurement, put in a Petri dish, and kept unsealed in the refrigerator to remove excess surface moisture. Then they were packed into a 10‐mm NMR tube and covered with Fluorinert FC‐70 fluid  to preserve the state of the cartilage. Once the NMR relaxometry experiments were complete, the cartilage chips were removed from the NMR tube, washed in pure phosphate buffered saline, and then placed in a phosphate buffered saline containing trypsin , where they were kept at 34°C under constant agitation for 24 hours. Afterward, the cartilage underwent this wash‐and‐dry procedure and was placed back to the NMR tube and covered with Fluorinert for the second run of the FFC measurements.0. Previous measurements,1 in bovine cartilage; thus, the orientation of cartilage specimens in an NMR tube will not introduce any ambiguities in the T1 distribution measurements.The cartilage chips were packed into an NMR tube closely and stacked there nearly parallel to each other. This might give a preference to a particular orientation of collagen fibers with respect to BOverall, 3 calf knees were used that had been supplied by a local butcher on demand. The number of NMR samples made from a given calf knee varied from 2 to 4. No systematic documentation between origin and position of these samples was carried out, so these will be denoted symbolically as “sample A, B, C, …” in the order of their mentioning in the text.33.11 distributions in bovine articular cartilage at a variable ν0. They exhibit two partially overlapping components with significantly dissimilar field dependences (dispersions). The components become fully resolved at ν0 = approximately 2 MHz, at which point they appear to constitute 20% and 80% of the population, respectively. As the field lowered into a sub‐megahertz region, the short‐time edge of the minor peak eventually reaches the instrumental limit of measurable T1 values (approximately 1 ms), which decreases its apparent amplitude down to 10%.Figure 1 components to the constituents of cartilage, we recapitulated the results of the spatially resolved measurements of T1 by Rössler et al1 values from that study across the cartilages . The T1 distributions at this field were found to collapse to an irresolvable narrow peak situated within T1 = 475 ms to 545 ms, depending on the cartilage sample measured.It is apparent from the FFC data that T1 component of the distribution . However, this leads to a shift of the major T1 component toward longer T1 values; thus, it increases the contrast between the two T1 populations . A similar observation has been reported for the transverse relaxation time components.Trypsin digestion of the cartilage does not appear to have an appreciable effect on the minor Ts Figure . The eff3.21 distribution width parameters gσ and β obtained through the LMA and the stretched‐exponential fit to M(t), respectively. Both gσ and β have a prominent extremum at about ν0 = 1 MHz in agreement with preliminary findings.1 component losing its amplitude when approaching the low‐field region. This in turn is a result of an irrevocable relaxation loss of the NMR signal during field switching intervals .Figure s Figure . Supplem1 components, the effect of trypsin treatment is securely detected through the integral distribution parameters gσ and β, indicating the broadening of T1 distributions in the enzymatically degraded cartilage.Despite these instrumental restrictions on quantitation of short T3.31 distribution, the uneven relaxation losses of T1 components on field switching also bias the means, <T1>a and <T1>g, in favor of longer T1s. Using them as such for calculating the arithmetic mean R1 leads to distorted dispersion profiles that can no longer be modeled as a sum of Lorentzian functions (see Equation 4). For this reason, instead of calculating the mean R1, we analyze the reciprocals of <T1>a and <T1>g as individual parameters. The reciprocal of a single‐exponential fit parameter T1,mono has also been considered. Strictly speaking, the multi‐Lorentzian decomposition of such profiles can no longer be interpreted in terms of superposing R1 dispersions. Rather, it is thought of merely as a parameterization technique that might be suitable to trace the changes caused by enzymatic treatment of cartilage.In addition to the apparent narrowing of the Tg(τ~c) for sample A. The thus‐measured distributions cover more than 1 order of magnitude, from several to a hundred nanoseconds. The interpretation of the obtained g(τ~c) is out of scope of this work. We can only assume that a peak at τ~c≈10ns, corresponding to a dispersion midpoint frequency ν0 10 MHz, reflects internal motions in the aqueous gel (“bulk water”) or in the protein network,τ~c components account for relaxation of protein‐entrapped water (see subsequently).Figure g(τ~c), we calculated the mean τ~c for all 3 cases of <T1>a, <T1>g, and T1,mono  at the QRE frequencies.Figure 1H–14N cross relaxation in the protein amide groups.1H dispersion profile. Magnetization transfer from amide protons to the bulk water relies on diffusion and chemical proton exchange. If those processes are slow on the T1 time scale, one may indeed expect to observe an additional T1‐relaxation broadening at the QRE frequencies.The QRE is caused by a 1 distribution on its own. We will use this argument in the Discussion to assess various sources of multiple T1 relaxation in cartilage.In general, the magnitude of the QRE peaks—of which often only the two high‐field peaks are sufficiently well pronounced to allow quantitative analysis—provide information about the number density and mobility of amide moieties, hence the concentration and mobility of proteins. It is a well‐known fact that proteoglycans are depleted during OA, and trypsin digestion is considered a suitable model for this aspect of OA degradation. This has been exploited to quantify the effect of trypsin digestion by measuring the QRE peak areas.41 distribution has the potential of being a biomarker for OA, provided that a suitable parameterization procedure is used. The result shown in Figure 1, which is securely detected over the entire ν0 range through the parameters gσ and β. On the ILT histograms .1H relaxation enhancement in tissue to the proton exchange between bulk water and a pool of protons (termed intermediary protons) consisting of labile macromolecular groups and entrapped water molecules. The efficiency of this mechanism relies on the residence time exτ of intermediary protons falling in the microsecond range. In this range, a low‐field water‐1H relaxation rate attains its maximum due to a cross‐relaxation coupling between intermediary protons and immobilized protein protons , the efficiency of the EMOR mechanism decreases, and the water‐1H relaxation is dominated by a local reorientation of water molecules that has a substantial spectral density at those frequencies. We believe that unlike exτ, the local reorientation rate is rather insensitive to the variation of the protein/water composition across morphological zones of cartilage, hence the tendency to a single T1 at high fields.To address the observed tendency of TThe EMOR model predicts a virtually exponential evolution of the water magnetization after nonselective excitation (the case of FFC). In particular, for the bovine pancreatic trypsin inhibitor as a representative biopolymer system, the deviation from single‐exponential evolution was found to be insignificant at an intermediary proton fraction of 0.01 and hardly detectable at that of 0.1.1 relaxation distribution, as it is securely detected through the parameters gσ and β at all B0. On ILT histograms, it manifests as a shift of the long‐T1 peak toward larger values, which is assigned to the transitional and the radial zones of cartilage  on the time scale . Our approach is quite opposite: We want to discriminate between components on the frequency scale through decomposition of the average relaxation rate dispersion, <R1>(ν0), which calls for estimates of <R1>. We analyze such a dispersion as a sum of simple Lorentzian dispersions, which give us access to the correlation time distributions, g(τ~c), according to Equation 4. Although we do not have a dynamic model to verify the obtained g(τ~c), we expect consistent, general direction in which the mean value <τ~c> may be changing on enzymatic treatment of cartilage. Such a trend was indeed found for dispersion profiles based on the geometric mean T1  using the FFC technique. The early‐stage OA conditions were simulated by enzymatic digestion of cartilage with trypsin.1 relaxation‐time distribution that is attributed to morphological zones of articular cartilage—a benefit of the low‐field relaxometry as opposed to the single‐exponential T1 relaxation typically observed in stronger fields of 1 T and above.Relating NMR relaxation behavior to osteoarthritis‐induced cartilage degradation requires a thorough understanding of relevant biochemical features of OA. According to Ref 23, the early‐stage OA can be characterized “as increased water contents, slightly decreased PGs and reorganized collagens.” Seeking a suitable relaxation characteristic that would be sensible to these particular changes in cartilage biochemistry, we investigated T1 distribution width increased significantly after trypsin digestion of cartilage. A general discussion of this result led us to the conclusion that it could indeed be explained by the biochemical changes that are characteristic of the early‐stage OA—particularly by the depletion of PGs. We should recall that this conclusion has the underlying assumption that trypsin treatment reproduces early‐stage OA conditions. Further research on the potential of this parameter (the T1 distribution width) to be a biomarker of OA requires validation in trials on articular cartilage in vitro and in vivo; corresponding experiments are currently planned.It was found that the T1 distribution measurements performed on a low‐field MRI scanner equipped with a permanent magnet. The advantage of the FFC relaxometry over the steady‐field relaxometry is that it introduces through varying B0 the second dimension that can be exploited in a complementary way or in its own right to monitor the OA‐induced changes in cartilage.1 dispersion profiles before and after trypsin digestion in terms of elementary Bloembergen‐Purcell‐Pound–type relaxation processes with individual correlation times. The presence in the T1 spectrum of the components that are comparable or even shorter than the field‐switching time of the FFC instrument makes the results of such analysis ambiguous; thus, its potential in providing information on molecular mobility in cartilage in terms of cτ remained limited. However, its feasibility is likely to be demonstrated for most other tissues that possess much longer relaxation times.The FFC technique is not uniquely suitable for such a type of research; one can envisage T1 dispersion of human tissue in vivo. Recently, whole‐body FFC‐MRI scanners have been demonstrated and are now capable of imaging at 0.06 T and 0.2 T, with the relaxation field varying down to 10 kHz.1 relaxation.The methods that use FFC relaxometry in combination with MRI offer access to spatially resolved T


Controlled directional transport of molecules is essential to complex natural systems, from cellular transport up to organismal circulatory systems. In contrast to these natural systems, synthetic systems that enable transport of molecules between several spatial locations on the macroscopic scale, when external stimuli are applied, remain to be explored. Now, the transfer of a supramolecular cage is reported with controlled directionality between three phases, based on a cage that responds reversibly in two distinct ways to different anions. Notably, circulatory phase transfer of the cage was demonstrated based on a system where the three layers of solvent are arranged within a circular track. The direction of circulation between solvent phases depended upon the order of addition of anions. Transport of molecules between several spatial locations is essential to the functioning of complex natural systems. On a macroscopic scale, a circulatory system allows blood to transport nutrients throughout an organism. Scaled down to cellular transport, molecules are continuously transported between organelles, and in and out of the cell.Supramolecular cagesII4L4 tetrahedral cage containing tricoordinated boron atoms at the center of each face . The reaction of 1 (4.0 equiv), p‐toluidine (12 equiv), and iron(II) bis(trifluoromethanesulfonyl)imide (iron(II) triflimide or FeII(NTf2)2, 4.0 equiv) yielded FeII4L4 assembly 2[NTf2]8  oluidine  equiv, a− by 2[NTf2]8, F− was titrated into a solution of 2[NTf2]8 , consistent with the formation of a B−F− adduct.1H NMR peaks, corresponding to inward‐ and outward‐facing methyl groups , a 1H–19F HOESY experiment was undertaken to elucidate the geometry of the F− group . A NOE correlation was only observed between the externally‐oriented methyl resonance and the F− signal, allowing us to conclude that all four F− ions faced outward. ESI‐MS  and UV/Vis titration  also confirmed the binding of F− to 2.To investigate the binding of F3⋅Et2O was observed to immediately remove F− from the boron atoms of 2,2 were observed in the 1H NMR spectrum after the reaction . F− binding can thus be used as a stimulus to reversibly change the structure and charge of 2, which is the key feature allowing the circulatory phase transfer of 2.Treatment with 4 equiv of BF6F13 chains , perfluoro‐1,3‐dimethylcyclohexane, and perfluorohexane. Notably, this is the first example of a coordination cage that is soluble in fluorous solvents; we anticipate that the use of BArf6− could provide a general strategy to solubilize other cationic cages in fluorous phases.To construct a system composed of three mutually immiscible solvents, fluorous solvents were investigated as one of the solvent phases, since they are known to be immiscible with both water and many organic solvents.− and BArf6− were added, 2 was no longer soluble in the fluorous phase and became soluble in DCP , and water containing 25 % acetonitrile was constructed, as shown in Figure P Figure  b. It wa2 from any of the phases of Figure 2[BArf6]8 in fluorous PFMC, addition of TBAF (4.0 equiv) to the triphasic system resulted in 2 transferring to organic DCP , and MgSO4 (2.0 equiv) resulted in transfer of 2 to the aqueous phase, with the color changing back to violet  was added to the initial state of the triphasic system, cage 2 transferred to the aqueous phase ), then to DCP following the addition of TBAF (8.0 equiv) and NaBArf6 ). This cycle could also be repeated following the successive additions of the different salts –(vi)). These results demonstrate that cage 2 underwent directional and reversible transport within the triphasic system depending on the order of addition of anions. Further details of the transfer process including the efficiency are presented in the Supporting Information, Sections S7.1–S7.3.Conversely, when TBA2[BArf6]8 in fluorous PFMC, TBAF (4.0 equiv) was added  and MgSO4 (2.0 equiv) resulted in the transfer of 2 to the aqueous phase  was first added, followed by TBAF (8.0 equiv) with NaBArf6 (8.9 equiv), 2 circulated in an anticlockwise direction . Th2. Directional control over circulatory phase transfer depends upon the responsiveness of 2 to three stimuli: fluoride, the highly fluorinated anion BArf6−, and sulfate. The selective fluoride binding to the borane centers is the key feature enabling the phase preference of 2 to be switched. Notably, we present the first example of a coordination cage solubilized in fluorous solvents by utilizing BArf6−, which could form the basis of a general strategy for other polycationic cages, which may enable the exploration of new guest recognition phenomena in fluorous solvents. Larger cages than 2, which would show the ability to bind a range of guest molecules, could be constructed by incorporating the central borane motif of 1 into larger ligand panels. Such larger cages could be built into more sophisticated circulatory guest transport systems. The ability to transit reversibly between three different phases could allow 2 and its analogues to be directed along complex pathways within a fluid network of linked rings, or circulatory phase transfer could be used to pick up a guest in one phase, then move it to another where the cage might open to release its cargo.This study thus establishes the circulatory phase transfer of stimuli‐responsive coordination cage The authors declare no conflict of interest.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.


The type of organic carbon (OC) present in lakes is a key factor controlling CH4 production at anoxic conditions, but the studies investigating the methanogenic potential of the main OC types are fragmented. We incubated different types of allochthonous OC  and autochthonous OC  in an anoxic sediment during 130 d. We tested if (1) the supply of fresh alloOC and autoOC to an anoxic refractory sediment would fuel CH4 production and if (2) autoOC would decompose faster than alloOC. The addition of fresh OC greatly increased CH4 production and the δ13C‐CH4 partitioning indicated that CH4 originated exclusively from the fresh OC. The large CH4 production in an anoxic sediment fueled by alloOC is a new finding which indicates that all systems with anoxic conditions and high sedimentation rates have the potential to be CH4 emitters. The autoOC decomposed faster than alloOC, but the total CH4 production was not higher for all autoOC types, one aquatic plant species having values as low as the terrestrial leaves, and the other one having values as high as phytoplankton. Our study is the first to report such variability, suggesting that the extent to which C fixed by aquatic plants is emitted as greenhouse gases or buried as OC in sediment could more generally differ between aquatic vegetation types.An important question in the context of climate change is to understand how CH For that, we incubated several types of allochthonous and autochthonous organic matter together with a refractory sediment under anoxic conditions, and monitored the production and isotopic composition of CO2 and CH4 over a 130 d period.In this study, we hypothesized that (1) the supply of fresh OC to an anoxic refractory sediment will increase CH13C) of the materials used for the incubation experiment. We then describe the monitoring of CO2, CH4, and O2 in the headspace during the incubation experiment, and the calculations of the cumulative TCO2 (headspace CO2 + dissolved inorganic carbon (DIC)) and CH4 concentrations, as well as of the OC remaining after C mass loss during degradation. An exponential decay model was applied to the remaining OC to compare the dynamics of decomposition between the different added types of OC. Finally, we describe how CO2 and CH4 were analyzed for δ13C and the method and calculations used to partition the OC sources fueling CH4 production during incubation.We performed anoxic incubations of sediment from a drinking water reservoir with and without additions of OC from various sources. Four different types of OC were added to the sediment: aquatic plant leaves from two different species, phytoplankton, and a mixture of land plant leaves. The following part describes first the collection and the analyses , total nitrogen (TN), δThe different potential sources for methanogenesis (sediment and different types of added OC) were sampled as follows.−1 and mean TN 452 μg L−1; J. Paranaíba et al. The sediment was sampled in an oligotrophic drinking water reservoir situated in the sub‐tropical Atlantic Forest region of Brazil  12 μg L2 and mixed. As autoOC sources, we used two different aquatic plants and phytoplankton. Senescent leaves of two C3 aquatic plant species, Salvinia auriculata, a free floating species, and Nymphoides indica, a rooted species with floating leaves, both common in Central and South‐American lakes . The leaves were washed with tap water to remove sediment and invertebrates and for N. indica, the leaves were also cut to ca. 1 cm2, which is approximately the size of S. auriculata's leaves. Phytoplankton was collected during a bloom in another reservoir in the Atlantic Forest region  with a 20 μm plankton net. The species were identified as a mixture of the blue green algae Microcystis aeruginosa, Dolichospermum sp., and Cylindrospermopsis raciborskii.Senescent leaves of 17 different tree and shrub species, having contrasting thickness and size, were collected close to the reservoir, in order to be used as an alloOC source in the experiment. Leaves were cut to approximately 1 cm−1 of KH2PO4 and 4.57 mg L−1 of NH4NO3) was prepared according to Attermeyer et al.  were incubated fresh as drying affects the decomposition dynamics Gessner , and werS. auriculata, (B) sediment mixed with N. indica, (C) sediment mixed with phytoplankton, (D) sediment mixed with terrestrial leaves, and (E) sediment without any OC addition  of added OC source, plus 24.4 ± 4.2 mg C of sediment, and the treatment with sediment‐only (E) contained 47.8 ± 8.3 mg C (Table We incubated five different treatments: (A) sediment mixed with ion Fig. . One hun C Table . All tre C Table .2 and then closed with gas‐tight butyl‐rubber septa (thickness of 12 mm) and aluminum crimp seals. The bottles were flushed again 24 h after closing to remove any O2 trace  and divided the replicates for gas concentration or for isotopic analyses to limit the number of samplings per bottle. The bottles were flushed twice with N2, at days 30 and 121 (first batch) or 103 (second batch), to restore atmospheric pressure and to avoid methanogenesis inhibition which can be caused by the accumulation CH4, CO2, or other volatile metabolic end products in the headspace  was incubated for 136 d and the second batch with alloOC (treatment D) for 118 d.To create anaerobic conditions, the bottles were initially flushed with NS. auriculata and terrestrial leaves). The dry material of each OC type was weighed  into separate tin capsules for TC, TN, and δ13C analyses. In addition, for sediment, OC content and its δ13C signature were measured after removing inorganic carbon by the addition of acid (20 μL of deionized water and 150 μL of HCl 5%) to ca. 50 mg of sediment samples in silver capsules and after overnight drying at 50°C .A part of the materials prepared for the incubation was used for elemental and isotope analyses, dried in the oven at 70°C during 48–72 h and ground with a mortar and a pestle, or finely cut with scissors and then ground, when grinding was difficult . For all treatments, anoxic conditions were reached and maintained throughout the experiment.Gaseous O2 and CH4 concentrations in the headspace of the bottles were measured by intracavity laser absorption spectroscopy with an Ultra‐Portable Gas Analyzer  using a discrete sample measurement method adapted from Gonzalez‐Valencia et al. . Ambient outdoor air was used as carrier gas, with a CO2 absorber containing soda lime connected upstream of the inlet, which decreased the CO2 and CH4 baselines to below 1 ppm and 1.8 ppm, respectively. Injections into the sample inlet via a plastic syringe equipped with a three‐way valve led to peaks (concentration in ppm over time) that were integrated with the R software. A calibration curve was made by injecting 0.5–1 mL of gases with known CO2 and CH4 concentrations, prepared from the dilution of a standard (5.05% of CH4 and 20% of CO2). For the measurement of CO2 and CH4 concentrations in the headspace, the bottles were shaken before gas sampling to release CH4 bubbles and to equilibrate with the headspace. 0.5–2 mL of gas was sampled in the headspace with the syringe and directly injected into the sample inlet connected to the gas analyzer.COa et al. . The gas2 and CH4 concentrations in the headspace were converted into molar units according to the ideal gas law. CO2 and CH4 concentrations in the water were calculated from their concentration in the headspace, the volume of artificial lake water and the water content of the sediment, and the specific gas solubility of CO2  is noted TCO2 production hereafter. Flushing with N2 removed on average 94% of CO2 and 99% of CH4 concentrations. Cumulative TCO2 and CH4 productions were calculated by adding the concentrations removed by flushing to the concentration measured after flushing and are used throughout the manuscript. TCO2 and CH4 productions rates were calculated as the difference in TCO2 and CH4 concentrations between two consecutive dates of concentration measurement (when no flushing occurred between the two dates) divided by the time interval between the two dates.COO2 Weiss  and CH4 t (tC) was calculated as the subtraction of the initial C mass (Ci) by the C lost as TCO2 and CH4. Hence, remaining OC included particular OC (POC) as well as dissolved OC (DOC). The production of CO2 and CH4 over time from added OC were estimated by removing sediment production of CO2 and CH4 obtained with the sediment‐only treatment . Remaining OC was divided by the initial C mass to obtain a fraction of remaining OC (tC/Ci). The initial C mass was that of the added OC for treatments with sediment and added OC, and the initial C mass was that of the sediment for the treatments with sediment‐only. In the same way, TCO2 and CH4 production over time and production rates were normalized by the initial C mass of added OC for the treatments with sediment and added OC, or by the initial C mass of sediment for the treatments with sediment‐only.The remaining amount of OC at time  CtCi is the fraction of remaining OC at time t (unitless), a is the initial fraction of the degradable pool, (1−a) is that of the residual pool (unitless), and k is the first‐order decay constant . Therefore, a refers to the proportion of the degradable pool while k refers to the reactivity of the degradable pool.Exponential models are the most common models used for sediment and litter decomposition (Westrich and Berner a and k) was tested with an analysis of variance (ANOVA), and the relevance of the model was checked with visual examination of data against fitted values and with residual plots. We tested if the parameters differed between treatments by comparing different sets of parameter models with the ANOVA method  being pre‐evacuated and thereafter flushed‐filled with N2 at atmospheric pressure  used for methanogenesis. The great variability in C fractionation factors associated with methanogenesis (between 10‰ and 70‰) is often a main difficulty partition the sources of CH4  according to Conrad et al. , fadded OC  is the contribution of the added OC to the CH4 produced, δCH4, added OC 13 is the theoretical δ13C of CH4 derived from the added OC, and δCH4, SOC 13 the theoretical δ13C of CH4 derived from the sediment OC.For each mixture:δCH4, added OC 13 is unknown, the formula can be rewritten using ɛadded OC, CH4, the isotopic enrichment factor involved in the conversion of added OC into CH4 :Since δCH4, mixture 13 of two different types of OC to determine their contribution to the CH4 produced relative to the sediment (1) if we assume the same contribution fadded OC  and the same isotopic fractionation factor εadded OC, CH4 for the two types added OC, and (2) if the two types of OC have sufficiently different δCadded OC 13 values. The added OC contribution to the CH4 produced may be calculated by subtracting Eq. We can compare the fadded OC 1  = fadded OC 2  = fadded OC  and εadded OC 1, CH4 =εadded OC 2, CH4.Here, 4 produced in the mixture treatments is:δCH4, mixture 1 13 and δCH4, mixture 2 13 are the δ13C of CH4 originating from the mixtures with the first type of added OC (added OC 1) and the second type of added OC (added OC 2), respectively.Hence the contribution (in %) of the added OC to the CH4 is originating exclusively from the added OC:Furthermore, if CH4 formation  having different C fractionation . For all mixture treatments (treatments A–D with added OC + sediment), CH4 production started right after the beginning, while there were a few days delay for the sediment‐only treatment (treatment E). The total CH4 production  in the sediment‐only treatment was similar independent of sampling occasion . CH4 and TCO2 production of the sediment‐only treatments was very low compared to that of the mixtures treatments  that of S. auriculata and terrestrial leaves , it increased quickly and reached a plateau around day 60. For the terrestrial leaves (treatment D), the increase seemed more constant and slower  were very close to those measured in the replicates used for concentration measurements  throughout the incubation, it increased during the first 30 d of the incubation to reach 0.5–0.7 for the three autoOC types and 0.9 for the terrestrial leaves, and then stayed relatively constant or slightly decreased to 0.6 for the terrestrial leaves , no CHa, Table N. indica than for terrestrial leaves and S. auriculata. The speed of decay of the degradable pool  using an exponential decay model, the fraction of the degradable pool  and sediment‐only (E) but varied with time for autoOC + sediment (A–C), with a rapid enrichment in 13C at day 18, followed by a decrease in 13C at day 40. In contrast to all other types of added OC, autoOC derived from phytoplankton produced higher δ13C‐CH4 and δ13C‐CO2 signals  phytoplankton and N. indica had different δ13C‐OC , thus fadded OC , the contribution of added OC to CH4 was only calculated for day 18 and day 40. According to Eq. fadded OC =116% ± 33% at day 18 and 121% ± 12% at day 40, meaning that essentially all the CH4 produced in these mixtures was derived from the added OC.δd OC Eq. . The δ134 production can result from the addition of fresh OC to anoxic sediments, particularly from autoOC, but also from alloOC, within timescales of weeks to months. CH4 production from the pre‐existing sediment only (treatment E) was very low compared to the large CH4 production resulting from the addition of fresh autoOC (treatments A–C) and alloOC . The CH4 partitioning results derived from isotopic analyses supported the mass balance approach, indicating that CH4 production from sediment OC was very low also in presence of added OC  support our first hypothesis that the supply of fresh OC to an anoxic refractory sediment will increase CH4 production, and that CH4 will be fueled mainly by fresh OC. Our study is the first to partition CH4 production in an anoxic sediment, therefore, other studies with different sediment OC reactivity and different availability of inorganic electron acceptors   and terrestrial leaves + sediment (treatment D) varied little  Fig. . The 13C2 and CH4 production rates. The speed of decay of the degradable pool was indeed significantly faster for the mixtures with autoOC (treatments A–C) than for the mixture with terrestrial leaves (treatment D) according to the exponential decay model , while for alloOC, CO2, and CH4 production rates were more constant over time, indicating a more progressive decomposition of the degradable pool . Even though all added OC types were able to fuel methanogenesis, the decomposition dynamics greatly differed between the types of OC that were added to the sediment. We hypothesized that autoOC would decompose faster than alloOC and thus would sustain higher COool Fig.  or POC , as hypothesized, but one aquatic plant had similar decomposition yield as the terrestrial leaves (79% of OC remaining for S. auriculata), and the other aquatic plant similar decomposition yield as the phytoplankton  and total CHt et al.  comparint et al.  and a poton Fig. b. These 4 rhizospheric oxidation , are generally regarded as C sinks, because of frequent CO2 undersaturation and/or high OC burial (Pacheco et al. 4, the CH4 emissions could offset the C sink in terms of global warming potential (Bastviken et al. 4 is released through ebullition and plant transport (Schütz et al. 4 that is returned to the atmosphere through these two pathways.The addition of fresh OC to anoxic sediment resulted in large CHNone declared.Supporting InformationClick here for additional data file.


The experimental evaluation of inhibitory activity against seven related isoforms of JMJD3 highlighted an unprecedented selectivity toward the biological target of interest.The quinoline‐5,8 dicarboxylic acid scaffold has been identified by a fragment‐based approach as new potential lead compound for the development of JMJD3 inhibitors. Among them, 3‐quinoline‐5,8‐dicarboxylic acid (compound  Both enzymes play key roles in the epigenetic regulation of gene expression, altering cellular memory, and reprogramming cellular fate. These proteins share a highly homologous Jumonji C domain endowed with Fehttps://www.rcsb.org/structure/4ASK as Model A and https://www.rcsb.org/structure/2XXZ as Model B), as structural experiments revealed different spatial rearrangements of some residues and of the Fe2+ ion upon GSK‐J1 binding.3–68, Scheme 3–12, Scheme In detail, by using an in silico approach, we screened a fragment library of metal chelators  that was previously proposed to develop metalloprotein inhibitors.3–12 into Model A highlighted the respect of a pattern of similar interactions by the common structural portion. Indeed, they coordinate the Fe2+ ion in a bidentate manner by the carboxylate group at C5, whereas the second carboxylic function establishes ionic interactions with K1381 and forms H‐bonds with T1387 and N1400. Notably, these interactions were observed in the co‐crystal structure with GSK‐J1.3–12 differ in terms of the interaction given by the substituent at C3 , respectively, accept two H‐bonds from R1246 and N1331. The pyridazine ring of 6 is H‐bonded to N1331 and establishes van der Waals contacts with F1328 and P1388 . Compound 7 accepts an H‐bond by methoxy group and fluorine from N1331 and R1246 . Compound 8 orthogonally interacts with N1331 by fluorine and establishes van der Waals interactions with F1328 and P1388 by a methoxy group . The linear chain oxygen atom of 9 accepts an H‐bond from R1246, and the 2‐methoxyethylphenyl moiety undergoes van der Waals interactions with P1388 and H1390 . The substituent at C3 of 10–12 establishes van der Waals contacts with F1328, T1387, P1388, H1390, and L1433 . Concerning the theoretical results on Model B, we observed that 3 is well accommodated into the binding pocket  we found only partial accommodation into the protein cavity, where some contacts with T1330 and F1328 are lost, especially for 9–12, which are endowed with bulky substituents at C3 . In greater detail, we observed that 4–12 coordinate the Fe2+ ion in a monodentate manner . Although 4 and 5 establish π–cation interactions with R1246, they do not correctly orient the sulfonamide and carboxylic groups to interact with R1246, as observed for Model A . Compounds 6 and 7 are H‐bonded with R1246, by a pyridazine ring and methoxy group, respectively .An interaction is observed between the pyrimidine ring and N1246 .3 gives a high number of contacts with protein residues, and it maintains most of the contacts observed from the docked pose during the entire simulation (>50 %) with both protein models , whereas the remaining compounds showed large fluctuations during the simulation . Large deviations from their initial positions were observed for 4–12‐Model B complexes . Compounds 4–12 bound to both models give a lower number of contacts during the simulations relative to 3 . Overall, the comparison of docking results on both models, integrated by molecular dynamics, suggested higher activity of compound 3 with respect to 4–12 as experimentally confirmed (see below).To evaluate the stability of the complexes between JMJD3 and compounds 1 was prepared by bromination of acrolein with two moles of bromine in dichloroethane . Addition of the brominated aldehyde to aminoterephtalic acid in glacial acetic acid at 110 °C afforded 3‐bromo‐5,8‐dicarboxy‐quinoline 2. The quinoline ring was further functionalized at position 3 by Suzuki–Miyaura coupling reaction3)4 as catalyst to give 3–12 (Scheme 3–12 were obtained in moderate to high yields (53–75 %). Reactions proceeded in lower yields with electron‐deficient heterocyclic boronic acids, which are known to be susceptible to protodeboronation.A modification of the Skraup reaction was used to synthesize the core structure Scheme .23 2,2,33–12 were investigated for inhibition of JMJD3 (at 25 μm) by using AlphaScreen . Compounds 4 and 5 also appreciably decrease enzyme activity by 65 % and 60 %, respectively. Lower enzyme modulation was observed for 6 (≈25 %) and 7 (≈12 %), whereas the remaining analogues 8–12 presented very low or no inhibitory activity. Notably, these experimental data are in good qualitative agreement with the theoretical outcomes, highlighting the structural features of substituents at C3 as responsible for the binding affinity for the macromolecule. We proceeded to investigate the inhibitory activity of 3 further by evaluation of its IC50 value against JMJD3. The results highlighted a low micromolar activity of compound 3 against JMJD3  was observed against UTX. Similar outcomes were obtained for 3 versus JMJD2C and JMJD2D  should be addressed to the authors.SupplementaryClick here for additional data file.


The frequency component with η = 0 and which enhances to ~52% at 373 K can be attributed to the cubic austenite phase. The predominant component (~52%) found at room temperature has been attributed to monoclinic martensitic phase of TiNi and the third component with values of ωQ and η similar to those for the martensitic phase is attributed to the intermediate orthorhombic phase. At 77 K, no intermediate and austenite phases have been found but only the martensite phase is observed at this temperature. From XRD measurements at room temperature also, three phases of TiNi have been observed.From temperature dependent perturbed angular correlation (PAC) measurements (77–873 K) in equiatomic TiNi intermetallic alloy, martensitic phase transformations have been observed. Three frequency components corresponding to three different phases of TiNi have been found in the temperature range 298–873 K. The results of quadrupole frequency and asymmetry parameters at room temperature are found to be:  The extraordinary shape memory power of SMA to preserve its original shape under thermal or mechanical stress and also the superelastic properties are exploited in these technological applications. In TiNi SMA, a thermoelastic diffusionless martensitic transformation (MT) occurs at slightly above room temperature which was first observed by Buehler et al.6. Upon cooling, the SMAs undergo a first order structural transition from the high temperature austenite phase to the low temperature martensite phase. The martensitic transformation is a displacive phase transition and it occurs by coordinated shifts of atoms but, there is no long range diffusion during the phase change. This structural transition can proceed through an intermediate phase. In nearly equiatomic TiNi shape memory alloy, three different phases have been reported as a function of temperature. The high temperature phase is a high symmetry cubic B2 7. The low temperature phase is a monoclinic B19′ 8 with a lower symmetry and the intermediate premartensitic R-phase (R) is a hexagonal  on Ni site or with excess of Ni to alter the MT temperature and to modify its functional properties25. The details of TiNi shape memory alloy was reviewed by Otsuka et al.26 The MT temperature was found to decrease with increase of point defects. It was found that in doped alloy, MT can takes place through the B2-B19-B19′. In this case, the B19 is an orthorhombic phase (space group Pmmb)25. The crystal structure properties and formation energies of B2, B19 and B19′ phases were calculated theoretically for TiNi by Huang et al.27 and for TiNi, TiPd and TiPt by Ye et al.28.The TiNi shape memory alloys (SMA) have been widely studied for the last few decades due to its immense technological applications in actuators, robotics, aerospace, condensed matter and in biomedical industries29 using 111In probe. The MT was found near 340 K where, below this temperature, a single quadrupole frequency due to monoclinic structure was found. At T = 400 K, the spectrum was found to be unperturbed due to the structural change to cubic. In the present work, TiNi has been studied by PAC spectroscopy using 181Hf probe in the temperature range 77–873 K in order to investigate the structural phase transitions with temperature. The X-ray diffraction studies in TiNi have also been carried out to confirm the phase components.The equiatomic TiNi was studied earlier by perturbed angular correlation (PAC) spectroscopy32 for the studies of structural and magnetic phase transition of a material. In this technique, the angular correlation of a γ-γ cascade of the probe nucleus is perturbed due to the interactions of electromagnetic moments of intermediate level and the electric field gradient or magnetic field generated at the probe site due to surrounding charge distribution. If the probe surrounding charge distribution produces a non cubic symmetry, an electric feld gradient (EFG) is generated at the probe nuclear site.The perturbed angular correlation is an important nuclear technique181Hf metal (~1 mg) was added and re-melted in the arc furnace. This was used for PAC measurements. The Hf concentration in the sample was estimated to be ~0.3 at.%. This small Hf concentration should not influence the sample properties anyway. For activation of 181Hf, a natural Hf metal with ~30% 180Hf was irradiated by thermal neutrons in the Dhruba reactor using a flux of ~1013/cm2/s. In a similar way, another TiNi sample was prepared (without active Hf probe). This sample in coarse grain form was used for XRD measurement which was carried out using Rigaku X-ray diffractometer TTRAX-III and Cu Kα radiation (λ = 1.54056 Å).The equiatomic TiNi alloy was prepared by arc melting in argon atmosphere with the constituent elements taken in stoichiometric ratios. The metals in wire forms had purities of 99.99% and 99.98% for Ti and Ni, respectively. The Ti metal was procured from Aldrich and Ni was procured from Alfa Aesar. Repeated melting was carried out to get a homogeneous mixture of the two metals and a shiny globule was formed. No significant weight loss of sample was found and the total sample was ~78.5 mg. With this sample, a pre-activated tiny piece of 181Ta produced in the β− decay of 181Hf (T1/2 = 42.4 days) emits two successive γ-rays, 133 keV and 482 keV passing through an intermediate level 482 keV having half-life 10.8 ns and a spin angular momentum I = 5/2+ℏ33. The coincidence count rate between these γ-rays can be written asθ is the angle between the detectors, τ is mean lifetime of the intermediate level, P2 and P4 are Legendre polynomials and A22, A44 are angular correlation coefficients of the γ-γ cascade. The perturbation functions G22(t), G44(t) arise due to hyperfine splitting of intermediate level of the probe nucleus. For the 133–482 keV cascade, A22 ≫ A44 30 and, therefore, A44G44(t) can be neglected. For a polycrystalline material, G22(t) is given by30The daughter ωi are frequencies related to the hyperfine splitting of the intermediate nuclear level such that ω1 + ω2 = ω3. The EFG tensor Vij due to electrostatic potential (V) at the nucleus are given byHere, 2V = 0. Thus, EFG is conventionally expressed by largest diagonal component Vzz and the asymmetry parameter defined asωQ is related to Vzz byIn the principal axis system, only the diagonal components are non-zero and ∇I = 5/2+ and η = 0 , there are three observable frequencies ω1, ω2 and ω3 related aswhere, Q is nuclear electric quadrupole moment of the intermediate level. For kn coefficients can be found in ref.34. Due to chemical inhomogeniety in the sample, all probe nuclei do not experience exactly the same EFG but slightly different EFG’s are experienced which produces a distribution of frequency around the principle value and this gives rise to a broadening of frequency. Here, a Lorentzian frequency distribution is considered in the perturbation function where, δ is the frequency distribution width. The experimental setup of PAC is equipped with two LaBr3(Ce) detectors (38 × 25.4 mm2) and two BaF2 detectors (50.8 × 50.8 mm2). Four standard slow-fast coincidence combinations were formed to acquire four coincidence spectra at 180° and 90° The LaBr3(Ce) was used for the selection of 133 keV γ-rays and the 482 keV γ-rays were selected in BaF2 detectors. An instrumental prompt time resolution (FWHM) of ~653 ps has been found for the LaBr3(Ce)-BaF2 set up using a 22Na source and selecting the 133 and 482 keV γ-ray energies. From the measured coincidence counts at 180° and 90°, a ratio R(t) is formed. This is given byThe defination of SW13 is the random subtracted coincidence count for the detector combination of 1 and 3 set at an angle 180° at time channel t. Neglecting A44 (A22 ≫ A44), the A22G22(t) can be found from R(t) as34Here, ωQ = 40.0(5) Mrad/s, η = 0.66(3) and δ = 12(1)% at room temperature (component 2). This component can be assigned as monoclinic martensite phase (M) of TiNi. The corresponding electric field gradient for the monoclinic phase is found to be Vzz = 4.5 × 1021 V/m2.The results of PAC measurements in TiNi are shown in Table ωQ = 14.8(1) Mrad/s, η = 0 has site fraction ~19% at room temperature which increases to 52% with values of ωQ = 13.8(3) Mrad/s, η = 0 at 373 K. Results of ωQ and η for this component indicate a cubic structure and an abrupt increase of this component at 373 K at the expense of the martensite phase further suggests this as a cubic austenite phase (A). In second thermal cycle, this component is found to be ~48% at 423 K with almost same values of ωQ and η as found at 298 K. The probe Ta atoms can experience non-zero value of EFG in the cubic TiNi lattice if these are positioned in a slightly distorted lattice environment. A third component with values ωQ = 56.7(3) Mrad/s, η = 0.39(2), δ = 0 are found at room temperature  with temperature for different components are shown in Fig. The first component with values of et al.10. But, a definite value of η for the intermediate phase found from present PAC measurements indicates that structure of intermediate phase is not hexagonal. Rather, closer agreements of results for the monoclinic TiNi and the intermediate phase suggest these two have structural similarities. A hexagonal structure is expected to produce asymmetry parameter η = 0. Here, the intermediate phase can be assigned to the orthorhombic B19 structure (space group Pmmb). The intermediate R-phase was found in TiNi10 and in Ti-Ni-Fe system13 while the B19 intermediate phase was found in ternary systems with Ti-Ni-Cu and Ti-Ni-Pd25. Our PAC measurements in TiNi, on the other hand, suggest that the intermediate phase has orthorhombic B19 structure. The crystal structure parameters reported for the R-phase10 were found to be quite different from the B19 phase25. So, if the intermediate phase was R, PAC results for components 2 and 3 would be quite different. But, similar values of ωQ and η found for these components indicate that intermediate phase is not R. Otsuka et al.35 reported that monoclinic B19′ structure is derived from B2 in two steps. Namely, the structure B2 transforms into a B19 first, and then a monoclinic martensite is derived by shearing the B19 in [100]B19 direction on (001)B19 plane. However, the B19 structure in TiNi was not reported earlier although this structure was found to be stabilized in TiPd and TiPt. The results from present temperature dependent PAC measurements suggest that TiNi has three crystal structures in the temperature range 298–373 K.The crystal structure of the intermediate R-phase was reported to be hexagonal  a single frequency component corresponding to monoclinic TiNi phase was observed from the previous PAC measurement29 at room temperature while three frequency components have been found from present measurements and ii) only a single quadrupole frequency with a broad frequency distribution was found from previous measurement29 at 400 K which was attributed to the cubic austenite phase. At 400 K and above, no monoclinic martesite phase and also no intermediate phase was observed. From present measurements, all three frequency components have been observed up to 873 K with changes in relative fractions but, no pure austenite phase has been found up to 873 K.The results from present PAC measurements using 8, cubic B2 phase7 and intermediate phase are found. The intermediate phase is found to be B19 instead of R-phase, by comparing the present XRD pattern of annealed sample  only induced the B19 phase25. Apart from these, the peaks corresponding to Ti2Ni and TiNi3 are clearly found in annealed sample. Here, presence of Ti2Ni (space group Fd-3m36) and TiNi3 (space group P63/mmc37) can be explained by considering the eutectoid decomposition of TiNi to Ti2Ni and TiNi3 as reported earlier38. Indication of these two phases are found also in preannealed sample and these are probably produced during sample preparation in arc furnace. From PAC measurements, however, no signal due to Ti2Ni or TiNi3 are found at any temperature. The component 3 with a finite value of η can not be assigned to Ti2Ni (cubic structure) or TiNi3 . The wt% of these two phases were probably small in our PAC sample and could not be detected.The XRD powder diffraction patterns for TiNi in both as prepared and annealed sample are shown in Figs ple Fig.  with theωQ for all three phases indicate that individual crystal structures do not change much with temperature. The results for ωQ and phase fractions depend slightly on the thermal history of the sample. From previous PAC measurements using 111In probe, however, only the monoclinic phase below the transition temperature (~340 K) with a single quadrupole frequency and a cubic austenite phase above this temperature was found. Observed phases of Ti2Ni and TiNi3 from present XRD measurements, probably, give a clear experimental evidence of eutectoid decomposition of TiNi to Ti2Ni and TiNi3.From present investigations, three crystalline phases of TiNi viz. cubic austenite B2, monoclinic martensite B19′ and intermediate orthorhombic B19 have been found in the temperature range 298–873 K. The B19 orthorhombic structure has been found as an intermediate phase in the transformation from cubic B2 to monoclinic B19′ phase. A martensitic phase transformation at ~298 K has been found in this material. The austenite phase is found to increase with temperature at the expense of the martensitic phase. At 77 K, only monoclinic phase of TiNi is found. In present sample, no R–phase is observed. From present studies, observation of a stable B19 phase co-existing with B19′ phase in TiNi, not reported earlier, is interesting and needs further investigations both theoretically and experimentally. Weak temperature dependent variations of


Candida antarctica in packed bed reactors (PBR) using supercritical CO2 as a solvent. Readers will find data related to different Figures or equations of the article as well as supplementary data that will help to make the difference between flowrates of CO2 in a liquid state and corresponding flowrates of supercritical CO2 for various CO2 pressure and temperature combinations.Data in this paper describes the catalytic performances, expressed in terms of conversion %, of geraniol and acetic acid to geranyl acetate, using the immobilized lipase B from  Specifications TableValue of the data•2 on Candida antarctica lipase B (CALB) catalytic properties.These data describe, for the first time, the combined effect of pressure and temperature variations of supercritical CO•2 flow-rate (i.e. reaction mixture residence time) for the achievement of a very high conversion % together with a good process productivity.These data show how important is the appropriate control of CO•These data may be considered with interest by any immobilized enzyme suppliers as well as manufacturers interested in continuous, green and enzymatic synthesis of terpenes esters.12 as a green, cheap, safe solvent for the synthesis of geranyl acetate, a widely used terpene ester. In this data in brief article, we found appropriate to focus on data related to the design of experiments on the influence of pressure and temperature on the conversion % of geraniol to geranyl acetate. We then present data related to the study of the impact of the supercritical CO2 residence time in the packed bed reactor (PBR) on the conversion %. Finally we give supplementary data helping the reader to easily get the densities, flow rates and residence times of various supercritical CO2 produced from a -8°C liquid CO2 pumped at various flow-rates. This last point is also important since when CO2 expand when passing from the liquid state to the supercritical state, its density, flow-rates but also the substrates concentrations in it, change.The collection of the experimental data in this paper aimed to contribute to the promotion of supercritical CO22.1−1 of liquid CO2 at −8 °C was pumped, converted to supercritical CO2 at the target pressure and temperature, and mixed with of an equimolar mixture of acetic acid and geraniol pumped at flow rate of 40 µL min−1 prior to pass through a 1 mL PBR filled with 300 mg of lipozyme®435 equilibrated at a water activity of 0.23 (water activity measurement performed with a Novasina Lab-Master aw meter). The substrates concentration in CO2 was therefore 57 mM, based on the CO2 flow in a liquid form (i.e. prior to density changes when increasing pressure and temperature). Unreacted substrates as well as products geranyl acetate (no visible water traces), were collected in a liquid form by CO2 depressurization through a back-pressure regulator-separator and a CO2 flow-breaker. Collecting vials were 60 mL amber vials. The run time was 30 min.Pressure was in the range 150–300 bars with a central point at 225 bar. Temperature was in the range 45–65 °C with a central point at 55 °C . For each P-T conditions, a flow rate of 3 mL min3 × sa0/a] and [10 × sa0/a] respectively, with sa0 and a, the standard deviation on the intercept and the slope of the calibration curve, respectively.After each run, the collected volume was measured and 200 µL of this volume was added to 800 µL of acetone prior addition of 50 µL of methyl decanoate as an internal standard. After mixing, 1 µL of the sample was injected with a split ratio of 100:1 in a Agilent 7890 A gas chromatograph equipped with a Agilent HP-INNOWax 30 m × 0.32 mm internal diameter x 0.25 µm column and a FID detector for quantification. The GC-FID was also coupled with an Agilent 7000 A MS triple quad detector . Details are given in the article. The detection and quantification limits (LOD and LOQ) were determined for all standards according to a US-EPA method The conversion % was calculated according to equation 1 as the ratio between the amount of geranyl acetate produced (mole) and the amount of geraniol (mole) pumped during the run:The four corner points conditions of the DoE were tested three times whereas the central point condition was tested six times, according to JMP 10 software from SAS institute Inc.  recommendations In order to generate the surface response and isocontour plots corresponding to 2.22 pumped at 60 bar and −8 °C with a density of 0.991. All along the article, for convenience, we used the liquid CO2 flow-rate as a constant basis for substrates concentration, residence times and enzymatic conversion comparisons. But it is obvious that, when passing from liquid to supercritical, CO2 density, and therefore CO2 flow-rate and substrate concentrations in the supercritical CO2, change. We used densities of supercritical CO2 as found with the Span and Wagner Equation of State defined in 1996. A free computational tool from the Energy Institute of the University of Pennsylvania was used to calculate the densities with this equation 2 was 754 kg m−3. At 65 °C and 150 bar, this density was 0.559 kg m−3.In our Design of experiment and stability tests, we used 3 mL/min of liquid CO2 as well as the residence time of supercritical CO2 in the PBR, expressed in seconds, assuming that spaces between beads is about 40% as currently considered with spherical catalyst particles. Conversion % and corresponding standard deviations were calculated with n=3. These data were used to generate the 2 flow-rates (at −8 °C and 60 bar) used in experiments with one single short 1 mL PBR filled with 300 mg of Lipozyme®435 beads or with two short 1 mL PBR in parallel, also filled with 300 mg of Lipozyme®435 beads (300 mg/PBR). The third column shows the corresponding flow-rates once that the CO2 expanded when reaching the supercritical zone at 55 °C and 200 bar. These flow-rates are logically higher due to lower CO2 density. The fourth column gives the residence time of supercritical CO2 in the PBR (expressed in seconds).2 at 65 °C and 150 bar, the best experimental temperature and pressure found based on our Design of Experiment.