Gas transfer velocities (k600), CH4 and CO2 concentrations were measured with multiple methods. Our data supported modelling approaches accounting for various stream slopes, water velocities and discharge. The results revealed large but partially predictable spatio-temporal variabilities in k600, dissolved gas concentrations, and emissions. The variability in CO2 emission was best explained by the variability in k, while dissolved CH4 concentrations explained most of the variability in CH4 emission, having implications for future measurements. There were disproportionately large emissions from high slope stream reaches including waterfalls, and from high discharge events. In the catchment, stream reaches with low slope and time periods of moderate discharge dominated (90% of area and 69% of time). Measurements in these stream areas and time periods only accounted for <36% of the total estimated emissions. Hence, not accounting for local or episodic high emissions can lead to substantially underestimated emissions.Global stream and river greenhouse gas emissions seem to be as large as the oceanic C uptake. However, stream and river emissions are uncertain until both spatial and temporal variability have been quantified. Here we investigated in detail the stream CH Consequently, some of the highest reported k values have been observed in small streams2 budgets with high per m2 emissions4 emissions are poorly understood although there is a growing awareness of their importance114 yr−1 by Stanley et al.4 emissions from streams could be even more variable in space and time than CO2 emissions6Inland waters emit significant amounts of greenhouse gases such as methane  with direct determination of CH4 and CO2 concentrations during a two-year study period in the stream network of a hemiboreal catchment in Southwest Sweden (4 and CO2 emissions. To do this we (1) measured the spatio-temporal variability in k in key reaches of the stream network (2) used the measurements to develop a locally validated model for k for the whole stream network (3) derived stream network CH4 and CO2 emissions from directly measured concentrations and the modelled k, accounting for the identified spatio-temporal variability and (4) quantified the importance of turbulent sections and high discharge periods.Another dilemma is that most large scale aquatic COt Sweden . The ovek) depend on the diffusivity of the gas and the temperature influencing the viscosity of the water. Hence, k values are related to Schmidt numbers representing the ratio of the kinematic viscosity of water to the diffusion coefficient of the gas in focus. For comparison across temperatures and gases, k600, representing k normalised to a Schmidt number of 600 , p < 0.001; k600 from location L7  was more than 3 times higher than the overall mean modelled k600 from the two years (k600 (k600 with 1.4 times higher k600 in 2014 than in 2013 (The modelled wo years . In partrs (k600 . Moreove in 2013 .4 concentrations were highly variable and with a mean concentration of 1.7 ± 3.5 [0.01–46.1] μM (mean ± 1 SD [min − max]). For comparison, the theoretical CH4 concentration in equilibrium with the atmosphere (2.0 ± 0.09 ppm measured during the study) was 0.004 μM. Hence, CH4 was detected in all of our samples with concentrations that were more than 2 to over 11000 times supersaturated relative to atmospheric levels. The mean CH4 concentrations in the sampling points of L1, L4 and L5 were similar and higher than the mean stream concentration .The CHriations . However2 concentration was 131.6 ± 79.8 [range 27.5–1124.1] μM . These concentrations correspond to excess concentrations of 1.3 to 54 times when compared to atmospheric levels (mean atmospheric CO2 concentration of 405 ± 28 ppm measured during the study). All our measurements showed that the streams were supersaturated relative to the atmosphere at all times. The CO2 concentrations occasionally reached higher than 15000 μatm (approx. >670 μM) especially close to the inlets and outlets of the lake Följesjön. In general, the spatial variability in CO2 was lower than for CH4 . Diel variability in CO2 concentration was frequently observed from the high resolution CO2 sensor data .Biweekly COsor data . CO2 con4 emission was 8.8 ± 23.5 [0.009–930] mmol m−2 d−1 . The mean CO2 emission was 1600 ± 4800 [3.3–90300] mmol m−2 d−1  from all sections . This was very different compared to the CH4 emissions, for which k for CH4 explained only 50% of the temporal variation (p < 0.001). The CH4 concentrations were a better predictor for CH4 emissions, as they explained 72% of the variability together with slope categories (p < 0.001). The cumulative CH4 and CO2 emissions from each of the sections showed higher increments in emissions during high discharge periods  was 6.5 m d−1. The mean modelled k600 for the entire network, accounting for the relative area distribution as 90.5% of the stream area in the catchment has a slope less than 1% . This could be explained if the previously published models were not based on data for high slope stream sections and therefore not calibrated or validated for high k situations.Several models to predict 4 concentrations measured in our study  was within the ranges reported for streams in the literature. Our CH4 concentrations were higher than the range (0.2–5.8 μM) measured in the Stordalen catchment, Northern Sweden4 concentrations were also reported in studies in boreal region of Northern Québec, Canada (0.04–49.2 μM)2 concentrations measured in our study (27.5–1124.1 μM) was similar to the range (23.8–714.7 μM) previously reported in many studies in Northern Québec, Canada, U.K. and Sweden13The range in CHda 0.04–4.2 μM2 cody 27.5–14.1 μM wa4 and CO2 concentrations13The gas concentrations in stream water represents a net balance between (1) the emission rates from the stream and (2) the input from terrestrial and aquatic sources along the stream network5205192037384 emissions in the range of 0.03 to 0.8 mmol m−2 d−1 were measured in first order streams in Tennessee, USA4 emissions ranging from 2.2 to 37.4 mmol m−2 d−1 in headwaters in Scotland, 0 to 60.1 mmol m−2 d−1 in small streams in USA, and emissions of 0.8 to 5.0 mmol m−2 d−1 in headwaters of Alaska have been measured1834et al.4 emissions of 15.8 mmol m−2 d−1 in streams of Northern Sweden. CO2 emissions from headwater streams of UK and streams of central Germany ranged between 316.1 and 3461.0 mmol m−2 d−1 −2 d−1, respectivelyet al.et al.−2 d−1 and −50.0 to 2030.0 mmol m−2 d−1, respectively. Mean CO2 emissions of 1300.0 mmol m−2 d−1 were reported in streams of Northern Sweden by Lundin et al.4 emission of 8.8 ± 23.5 and mean CO2 emission of 1600 ± 4800 mmol m−2 d−1) were within previously measured ranges, but on the high side which is explained by the organic rich soils in the catchment and that we tried to account for the full spatio-temporal variability in emissions including high turbulent sections of the stream network, which was important for the total emissions (discussed further below).Previous measurements show a wide range of emissions from streams. CH4 emissions reported includes the transport of dissolved CH4 across the water-air boundary layer . Enhanced emissions of CH4 via microbubbles have recently been suggested4 microbubbles would not form spontaneously, i.e. although there was a supersaturation relative to 2 ppm CH4 in the air, there was not a supersaturation relative to 100% CH4. Rapid degassing of both CH4 and CO2 into small air bubbles formed in the highly turbulent  were integrated in the k values measured, and thereby included in our model. Release of CH4 bubbles from sediments could only have been captured by the drifting chambers used for model validation but the limited extent in time of these measurements implies that ebullition was not representatively measured. Hence, overall CH4 emissions may have been underestimated because ebullition was not accounted for.The CHi) modelling from k determined with propane tracer injections combined with water concentrations measurements, (ii) mass balance calculations along selected stream sections, and (iii) drifting chambers –in spite of highly variable conditions along the stream network, indicates that our measurements and model results are relatively robust (see i) and (ii) should be comparable because both are based on mass balance calculations of gas loss over short stream sections for either the injected propane tracer or in this case CO2 (which dominates the dissolved inorganic carbon pool in the studied streams). Lower correspondence is expected between approach (i) and (iii) because drifting chambers measure gas exchange along a specific path of the stream. Additional questions regarding if drifting chambers disturb the water surface have been raised44The general agreement between the three independent methods to estimate emissions–(bust see . Approack (i.e. stream slope and water velocity) and gas concentrations regarding both studied gases. k was relatively more important for CO2 emissions, while CH4 emissions seem to be more dependent on the water CH4 concentrations. This was likely due to the higher variability in CH4 concentrations making emissions more dependent on concentrations than on k. These differences are important for designing future efforts to better estimate stream emissions, and optimising the resource allocation to k versus concentration monitoring. However, at the local level, both k and concentrations were influenced by discharge with gas import and export. Hence, the difference among years related to discharge is expected and was also noted: discharge in 2014 was 1.7 times higher than in 2013 being consistent with the different emission estimates among the years  kg yr−1 and 32.9 (24.6–41.2) Mg yr−1, respectively, from an area of 6319 m2  Mg yr−1 , we still could have covered majority of the space and time (90% of area and 69% of time) but arrived at substantially underestimated emissions i.e. the emissions from flat areas and moderate flows were just 55 and 36% of CH4 emissions and 41 and 26% of CO2 emissions, respectively. This illustrates the importance of representative sampling and modelling when scaling to the landscape level. Hotspots of degassing along the stream network and high discharge events should be taken into account when possible. Moreover, k values from small areas with high water turbulence should not be extrapolated to large areas because this lead to overestimated emissions.Regarding temporal variability, 69% of the days had a stream discharge that was lower or equal to the mean discharge of the two-year study period, but the emissions from this period were lower than the overall mean CHmissions . The meamissions . The higk and concentrations. Although steep sections can have low gas concentrations, their high k can make these sections important for emissions. On a temporal scale, high discharge events are important and a large of part of the annual emissions may happen during these very short periods. Projected shifts in the hydrological regimes for many regions, as a result of a changing climate, may contribute further to the temporal patterns. The potential importance of the short high discharge periods has been discussed previously, but quantifications of their relative importance are still rare. We conclude that further development of sensor network based measurements and the types of modelling approaches presented here would be beneficial to better account for the hot spots and hot moments in future gas emission assessments.Given these results, accurate assessments of gas emissions from stream networks depend on consideration of the large spatial variability in both 2 catchment is mostly covered by forest , dominated by Picea abies (L.) H. Karst. and Pinus sylvestris L., and to a minor part by agricultural land (9%). About 14% is covered by cleared forest, 4% by mire and 1% by lakes and streams. The annual mean temperature and precipitation were 7.0 °C and 910 mm, respectively, for the years 1983–2013 . The altitudes in the catchment ranged from 51 to 78 m above the average sea level. The main stem of the stream network originates in a mire just upstream of Lake Erssjön , situated in Southwest Sweden . The 7 k Erssjön . Via a c Erssjön . The netg) were determined using injections of a volatile gas tracer, propane (C3H8), as described in similar studies111437Gas transfer coefficients , τ is the reach travel time (min), [C3H8]U and [C3H8]Dare the relative concentrations of propane in the upstream and downstream samples, respectively, and QU and QD are the discharge (L s−1) at the upstream and downstream stations, respectively. The difference in the upstream and downstream discharge calculated from the estimated discharge (see below) ranged from 0.06 to 0.5%, and this was used to calculate QU and QDfrom the measured mean discharge. The k; m d−1) by multiplication with the average stream depth of the reach at each sampling occasion. An alternative approach to derive k from the general diffusive flux calculation49where Caq is the water concentrations as measured and Ceq is the theoretical water concentration in equilibrium with the atmospheric partial pressure according to Henry’s Law, yielded almost identical k values.where F is the flux to the atmosphere–here determined as the loss of propane from a water section during the reach travel time, k values for propane were converted to k600  to enable comparison across temperatures and different gases according to WanninkhofThe k denotes the gas transfer velocity (m d−1) and Sc is the Schmidt number of the gas in focus according to WanninkhofSc for propane was calculated as described in Raymond et al.51where k600 values were converted to gas and temperature specific k-values for CO2 and CH4 according toThe kg and Scg denote k and Sc for a specific gas (here CO2 or CH4) at a specific temperature (the water temperature during the time period in focus). Stream velocity (m s−1) for each tracer injection was calculated by dividing the length of the reach by the reach travel time  described in detail in Bastviken et al.2 measurements were made in the two years.The CO4 concentrations were determined by a headspace equilibration method4 in the stream water were measured approximately every two weeks in 2013 (May-Nov) and 2014 (Apr-Nov) at four monitoring stations whose locations are given in 4 concentrations were also measured close to the CO2 chamber measurements to better cover the spatial variability. CH4 concentrations measured during the propane injections were included in the data analysis. A total of 292 stream water CH4 concentration measurements were conducted during the study period. Additional details on gas analysis using a gas chromatograph are given in the The CHhttps://maps.slu.se/get/). The stream network of the catchment and the overall and partial drainage areas were extracted from the DEM using the Spatial Analyst toolbox in ArcGIS 10.3. The daily discharge for each 2 m stream section, out of the, in total, 6.4 km long stream network was estimated as follows: (1) Stream discharge was measured at four monitoring stations in the catchment according to the methodology described by Wallin et al.D = bA, where D is discharge, A is upstream drainage area, and b is a constant , based on the discharge data for the specific day from the four stations. The study encompassed 623 days , meaning that 623 separate such equations valid for their respective day were made. R2 exceeded 0.92 for all days (average 0.98). The range of b was 0.2 to 315. (4) The upstream drainage area for each 2 m stream section was determined from ArcGIS and was multiplied with b of the 623 equations to estimate average daily discharge for each such 2 m section.A digital elevation model (DEM) of the catchment with a 2 m horizontal resolution was obtained from Lantmäteriet (The stream network was divided into 84 reaches where the length of each reach was defined by an elevation difference of 0.5 m. The slopes (%) of the stream reaches were calculated by dividing the elevation difference of each reach by the reach length.k600 values in the whole stream network were then modelled from stream slope and water velocity as predictor variables (see We established a regression model with velocity as a function of discharge and slope measured in the stream reaches where tracer injections were conducted . This mok estimates. No good relationship between CH4 and CO2 concentrations and any independent variables were found (see Results), thus modelling spatially distributed CH4 and CO2 concentrations at a daily time step was not possible. Instead, CO2 and CH4 concentrations in the un-sampled reaches were estimated, based on manual concentration measurements from 20 points of the stream network (measurements done on 5 occasions for CH4 and 7 for CO2 in 2014). Concentrations were interpolated between these 20 points (e.g. assuming linear change in concentration between upstream and downstream measurements when available). The ratios of the interpolated concentrations in relation to the concentrations at the most frequently samples measurement points of CH4 and CO2 were then calculated, yielding relative concentrations in each stream reach. Assuming that these relative concentrations were valid for the time periods between the spatially resolved samplings, the concentration levels in each reach over time were estimated from the concentrations at the temporally resolved sampling points (biweekly for CH4 and daily mean for CO2). For the days between sampling occasions, concentrations were linearly interpolated to gap-fill. Daily emissions for each of the 84 reaches were then calculated based on the stream surface area of each reach (expressed in kg d−1 for CH4 and Mg d−1 for CO2). The emissions from all 84 reaches were then summed and total emissions of CH4 and CO2 from the streams were expressed in kg yr−1 or Mg yr−1. By far the largest uncertainty in the emission estimates come from the relative concentration ratios used to represent spatial differences along the streams during the different periods to interpolate concentrations within the stream network. Therefore, the coefficient of variations (CV) of the interpolation ratios of each reach were calculated and the maximum CV was used to estimate uncertainty range for the mean for all reaches, which were 60 and 25% for CH4 and CO2 emissions, respectively.Emissions were calculated by using 10 transformed when this criterion was not met. The predicted values from the log10 transformed linear regression equations were back transformed to original units using the correction proposed by Newmank600 and emissions for CO2 and CH4 were divided into seven groups based on location  with Tukey’s post hoc test was used, with location and slope categories as factors, to analyse spatial variability. All statistical analyses were done in IBM SPSS Statistics 23  with a significance level of 0.05. GIS related analyses were performed in ArcGIS 10.3 .Residuals in the linear regressions were checked for normal distribution and randomness of errors and the original variables were logHow to cite this article: Natchimuthu, S. et al. Spatio-temporal patterns of stream methane and carbon dioxide emissions in a hemiboreal catchment in Southwest Sweden. Sci. Rep.7, 39729; doi: 10.1038/srep39729 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Here, we present experimental data at 1–3 GPa, 800 °C, and ∆FMQ ≈ −0.5 for the volatiles and solute contents of graphite-saturated fluids in the systems COH, SiO2–COH ( + quartz/coesite) and MgO–SiO2–COH ( + forsterite and enstatite). The CO2 content of fluids interacting with silicates exceeds the amounts measured in the pure COH system by up to 30 mol%, as a consequence of a decrease in water activity probably associated with the formation of organic complexes containing Si–O–C and Si–O–Mg bonds. The interaction of deep aqueous fluids with silicates is a novel mechanism for controlling the composition of subduction COH fluids, promoting the deep CO2 transfer from the slab–mantle interface to the overlying mantle wedge, in particular where fluids are stable over melts.Estimates of dissolved CO 2 in subduction-zone fluids based on thermodynamic models rely on a very sparse experimental data base. Here, the authors show that experimental graphite-saturated COH fluids interacting with silicates at 1–3 GPa and 800 °C display unpredictably high CO2 contents.Current estimates of dissolved CO CO2 removal through dissolution of carbonates occurring in altered oceanic lithosphere and its sedimentary cover, along with diapirism of slab rocks3 and/or melts4, provides an efficient way to recycle carbon back to the mantle wedge and, ultimately, to the Earth’s surface6. However, other forms of carbon, often closely associated with silicates, have been reported in slab rocks and in particular in subduction mélanges. For instance, graphite has been described in blueschist-facies mafic rocks, metasediments and hybridized peridotites at Santa Catalina7, and in ophiolitic serpentinites from the Western Alps8, where also diamond has been found in UHP metasediments9. In Alpine Corsica10 and in the Western Italian Alps11, reduction of carbonates during subduction results in graphite-rich metasediments and serpentinites, suggesting that graphite may become a major phase in hybridized silicate-rich subduction mélanges. Graphite has been considered to represent a refractory sink of carbon in the subducting slab, owing to its lower solubility in aqueous fluids12 and melts13 compared to carbonates. On the other hand, graphite dissolution mechanisms and solute transport in complex COH fluids at high pressures have remained experimentally unconstrained. Moreover, recent thermodynamic models highlight the role of graphite in subduction-zone fluids14 and suggest that the presence of graphite is capable of modifying fluid properties and promoting the formation of C-bearing anions, possibly enhancing the complexation of major and trace elements at elevated P and T conditions12.Subduction of the oceanic lithosphere and its sedimentary cover is accompanied by devolatilization processes2, SiO2, and MgO in increasingly complex petrological systems at controlled redox conditions, buffered by using the double-capsule technique and both the nickel-nickel oxide (NNO) and the fayalite-magnetite-quartz (FMQ) buffers, in order to develop a model for the interaction between deep aqueous fluids and silicates in subduction mélanges. A carbonate-free compositional range has been explored at P = 1 GPa, T = 800 °C and P = 3 GPa, T = 800 °C in order to focus on the role of graphite and silicates in the investigated processes. We synthesized COH fluids in equilibrium with graphite and other minerals representative of subduction mélanges, i.e., Mg-silicates (forsterite and enstatite), representative of the mantle component, and quartz, representative of the sedimentary component. Experimental products were analyzed for their volatile COH composition by quadrupole mass spectrometry (QMS) and for their Mg and Si solute load by cryogenic laser-ablation inductively coupled plasma mass spectrometry (ICP-MS). Measured data were compared to thermodynamic modeling results. Further details are provided in Methods section and as Supplementary Information. Our results suggest that the interaction of deep aqueous fluids with silicates in the presence of graphite in a subduction mélange promotes the dissolution of graphite and enhances the CO2 contents of the fluids; this provides a new mechanism for controlling the volatile composition of COH fluids already at depths of ~30 km.Here, we provide comprehensive experimental constraints on the composition of high-pressure graphite-saturated COH fluids in terms of dissolved CO15. Measured data were subsequently compared with the compositions predicted by traditional thermodynamic modeling using different equations of state and mixing properties of H2O and non-polar species (details in Methods section). Carbon-saturated fluids were synthesized first in the pure COH system, where fluids interacted only with graphite molar]  and + 28% (SiO2–COH) in experiments buffered by FMQ at 1 GPa, 800 °C, + 9% (SiO2–COH) in experiments buffered by FMQ at 3 GPa, 800 °C, and + 14% (SiO2–COH) and + 15% (MgO–SiO2–COH) in experiments buffered by NNO at 1 GPa, 800 °C.The volatile compositions of COH fluids were measured by piercing the capsules after quench in a gas-tight vessel and then conveying the emanating gases to a quadrupole mass spectrometer (QMS)XCO2 of the fluid, provided that graphite is present in excess. We therefore measured additionally the dissolved Si and Mg in the synthetic COH fluids at 1 GPa and 800 °C by using a modified version of the cryogenic LA-ICP-MS technique16. This technique was originally developed for the analysis of solutes in pure water, which is frozen in the experimental capsules and analyzed via laser-ablation ICP-MS. In the case of COH fluids, an immiscible mixture of water and non-polar gases is expected at the investigated P, T conditions17  are lost when the capsule is opened for analysis. Consequently, the solute contents retrieved by ICP-MS pertain to the aqueous part of the bulk COH fluid only (Supplementary Table 2–COH system) and forsterite + enstatite (MgO–SiO2–COH system) at 1 GPa and 800 °C, where SiO2 molalities have been obtained by correcting the concentration of the internal standard (Cs) on the basis of the measured fluid XCO2 , but much higher than previously reported quartz solubilities in H2O–CO2 fluids characterized by similar XCO2 but without graphite . The dissolved silica in COH fluids in equilibrium with forsterite, enstatite and graphite , resembling the solubility of quartz in pure water. The solubility of forsterite and enstatite has not previously been measured in mixed H2O–CO2 fluids, but it has been investigated in pure water24, amounting to 0.21–0.30 mol SiO2 kgH2O-1 ref. 24. We additionally performed a dissolution experiment of forsterite and enstatite in pure water , clearly testifying that the solubility of forsterite and enstatite in pure water is much lower than in COH-bearing fluids.The interpretation of the observed differences in volatile content of COH fluids that do and do not interact with silicates is not straightforward. Because, we did not find any evidence of hydration and/or carbonation reactions in the run products, our preferred interpretation is that dissolution reactions of silicates are influencing the 2–COH and MgO–SiO2–COH systems, the carbon dissolved in fluids does not behave merely as an inert diluent, but promotes the dissolution of silicates at the conditions of our experiments. The simplest explanation of these results is that new unexpected organic complexes containing Si–O–C and Si–O–Mg bonds are formed in addition to the solutes known experimentally, such as the Mg2+ ion and the silica monomer and dimer25. This hypothesis is supported by the measured dissolved Mg concentrations in the MgO–SiO2–H2O and MgO–SiO2–COH systems. Although published experimental data are not available to date for the P–T conditions investigated, the extrapolated solubility of Mg derived from the dissolution of forsterite and enstatite in pure water should be less than 0.17 mol kgH2O−1 at P = 1–2 GPa and T = 900–1200 °C23. In our experiments in pure water at 1 GPa and 800 °C, dissolved Mg is slightly higher . For the system MgO–SiO2–H2O, the predicted silica concentrations agreed with the experimentally measured values. However, the predicted Mg concentrations in the MgO–SiO2–H2O system were too low, even when a predicted equilibrium constant for the species Mg(OH)+ was included. Consequently, an Mg(OH)2(aq) complex was fit to the experimental solubility data for the MgO–SiO2–H2O system 2(aq) complex and the predicted complexes MgHCO3+, MgCO3(aq), MgHSiO3+, and MgSiO3(aq) were used together with the silica monomer and dimer in trial calculations to predict Mg and Si solubilities. However, numerous calculations resulted in solubilities that were too low, indicating the likely need for an additional complex involving the components MgO, CO2, and SiO2 in the MgO–SiO2–COH system compared to the carbon-free MgO–SiO2–H2O system. An analysis of the available solubility data at 800 °C and 1 GPa for the MgO–SiO2–H2O and the MgO–SiO2–COH systems indicates that a variety of MgO–SiO2–CO2 complexes might be feasible. For example, complexes involving oxidized C-species such as bicarbonate or carbonate complexes, or complexes involving reduced C-species could account for the observed solubilities. In Supplementary Table 3)][CH3CH2COO]. This complex provides an explanation for the distinctive enhanced solubilities of Mg and Si measured in the present study. In particular, the MgSiC complex is predicted to be important in the relatively reduced systems investigated, i.e., bearing H2O–CO2 fluids in equilibrium with graphite close to the C–CO2 (CCO) buffer29. This complex, however, would be insignificant in the COH fluids in all previous studies of silicate solubilities that focused on unbuffered H2O–CO2 fluids without graphite , which are potentially stable up to extremely oxidizing conditions. Analogous calculations for the SiO2–COH system suggest the possibility of other organic complexes involving SiO2 and reduced C-species. It is worth noting here that the stability of organic COH species in subduction-zone fluids has been recently suggested14. A more complete analysis of the potential importance of MgO–SiO2–CO2 complexes over a wide range of temperatures and pressures is hampered by the lack of other experimental Mg- and Si-solubility data in the MgO–SiO2–COH and SiO2–COH systems. Consequently, a full equation of state characterization of the standard partial molal properties of MgO–SiO2–CO2 complexes must await the development of estimation schemes for refining the properties of such complexes.In the system MgO–SiO2–COH and MgO–SiO2–COH systems externally buffered by FMQ and NNO, dissolution reactions of either quartz/coesite and forsterite + enstatite are able to boost the CO2 content of graphite-saturated COH fluids at elevated pressures and temperatures. No significant differences have been observed concerning the XCO2 increase between quartz-bearing and forsterite + enstatite-bearing experiments, suggesting that dissolved Si, rather than Mg, is the major player in this boosting process. This could be attributed to the polymerized nature of silica at high pressures and temperatures20, which may be different from other species, for example aluminum species30. Our model predicts that neutral silica monomers [SiO2(aq)] and dimers [Si2O4(aq)] are important species at the investigated conditions  against HCO3− and CO32−. Moreover, reaction  and log fO2 = −14.31 (inner capsule buffered by FMQ), respectively.Our experimental data  and MgO–SiO2–COH (ochre dots), either log fH2O  should decrease at constant log fO2  can account for the measured increase in fCO2 in both SiO2–COH and MgO–SiO2–COH systems , we are able to calculate the decrease in water activity (aH2O), assuming that aH2O = fH2O/fH2O0, where fH2O0 is the fugacity of pure water at 1 GPa and 800 °C . The required decrease in aH2O with respect to the pure COH system is −4.17 log units in the experiments buffered with NNO and −4.14 log units in the experiments buffered with FMQ. Because only small differences in measured XCO2 have been observed between the SiO2–COH and MgO–SiO2–COH systems, we argue that dissolved silica monomers [Si(OH)4] and dimers [Si2O(OH)6] are much more effective than MgO–SiO2–CO2 complexes in decreasing water activity. The activity of total silica can be calculated on the basis of the measured SiO2 molality in the experiments buffered with NNO and the measured XCO2 of the corresponding COH fluid20, log (aSiO2) being equal to −2.59 in MgO–SiO2–COH and −2.90 in the SiO2–COH systems. The activity of dissolved silica in the SiO2–COH and MgO–SiO2–COH systems is therefore much higher  compared to the difference in aH2O estimated in the SiO2–COH and MgO–SiO2–COH systems versus the pure COH system. In order to match the observed increase in fCO2, we estimated that only 0.31 mol%  and 1.89 mol%  of the measured dissolved silica are required, assuming that the decrease in water activity is solely related to the formation of hydrated silica monomers [Si(OH)4] and dimers [Si2O(OH)6]. These low solubility data  probably needs to be adjusted up by 10–30% (0.6–1.8 Mt C/y). Additional experiments investigating more complex, carbonate-bearing systems as well as an improved quantification of the content of graphite and organic matter in subducted sediments are required to better quantify the impact of this novel mechanism on the global carbon flux.Our results suggest that the silica component derived from the dissolution of either magnesium silicates or quartz/coesite alone, even in absence of carbonates, controls the composition of deep COH fluids in equilibrium with graphite, in particular enhancing their COre33Fig. . Indepen2O38 and CO242 on subsolidus and melting relations in peridotitic systems at upper-mantle conditions. Only few studies considered the effect of the simultaneous occurrence of H2O and CO2 or more generally, the influence of COH fluids on the peridotitic systems44. The H2O/CO2 ratio in COH fluids is crucial because it affects the location of carbonation/decarbonation reactions and the position of the solidus. However, the H2O/CO2 ratio of the fluid in equilibrium with mantle minerals has mainly been estimated through thermodynamic modeling3, using equations of state of simple H2O–non-polar gas systems46 , equations that do not consider the complexity related to dissolution processes47.Several experimental studies investigated separately the effect of the volatiles H2O-bearing fluids at high-pressure conditions is the capacity to transport dissolved species18. The amount of solutes from rock-forming minerals in aqueous fluids increase with increasing pressure50 until the fluid becomes no longer distinguishable from a silicate melt and a supercritical liquid is formed52 The solubility of forsterite and enstatite has been measured in pure water up to 1.5 GPa and at T = 700–1300 °C24. Experimental data on mineral dissolution in mixed H2O–CO2 fluid are available only for quartz53, albite54, and diopside55 and suggests that solubility decreases with increasing content of CO2 in the fluid.Another fundamental property of HfO2 conditions. Fluids have been investigated in equilibrium with graphite only in the system COH, with graphite + quartz/coesite in the system SiO2–COH and with graphite + forsterite + enstatite in the system MgO–SiO2–COH. Two different experimental setups and analytical techniques were employed to determine the volatile composition and the solubility of minerals in COH fluids at P = 1.0 and 3.0 GPa, and T = 800 °C. These conditions were selected for sake of simplicity to avoid the presence of carbonates (magnesite) in the system MgO–SiO2–COH and the consequent complexities related to carbonate dissolution. In particular, the link between H2O/CO2 ratio  and silicate dissolution (investigated by cryogenic laser-ablation inductively coupled plasma mass spectrometry [LA-ICP-MS]56) is highlighted here and compared with thermodynamic calculations.The aim of the paper is to provide for the first time experimental constraints on the composition of high-pressure COH fluids in equilibrium with graphite in terms of both volatile content and dissolved solutes in increasingly complex petrological systems at controlled 2C2O4·2H2O) or an equivalent mixture of 1:1 oxalic acid anhydrous  + water  = 0.5 and an excess of H2.generating a starting fluid characterized by −1) water was employed as fluid source in experiments on mineral solubility in COH fluids  and silicon dioxide , mixed in stoichiometric proportions, pelletized and loaded in a vertical furnace at 1500 °C for 24 h. Synthesis products were ground in ethanol for 1 h, dried and characterized by X-ray powder diffraction analysis . The resulting composition of the mixture, derived by Rietveld analysis, is forsterite 83.2 wt%, enstatite 16.7 wt%, and cristobalite 0.1 wt%. Run products were characterized using scanning electron microscopy and electron microprobe WDS analyses (Jeol JXA 8200). Silica polymorphs (quartz/coesite) were identified by X-ray diffraction analysis.Graphite  was added in all experiments to ensure carbon saturation of the COH fluid. In SiOIn LA-ICP-MS experiments, a layer of diamond powder (grain size 20 µm) serves as a trap for collecting the COH fluids in equilibrium with solids . Temperature was measured with a K-type thermocouple located within 0.6 mm from the top of the capsule and is considered accurate to ± 5 °C.Capsules were welded shut in a frozen steel holder to avoid overheating. Capsules were reweighed to ensure no fluid loss during welding occurred. Sintered MgO rods were employed to embed the capsule, surrounded by a graphite heater, Pyrex glass and NaCl. A rocking piston-cylinder apparatus was used to reach high-pressure and high-temperature conditions. The rocking piston-cylinder is a regular end-loaded piston-cylinder, which allows forward and backward rotation of 180° during the experimental run, thus inverting its position in the gravity field. Chemical inhomogeneity within the capsule is in fact common in fluid saturated experiments. The rocking piston-cylinder overcomes this problemBecause the volatile composition of graphite-saturated COH fluids is dependent on the redox state of the system, all experiments were performed using a conventional double-capsule design to constrain the chemical potentials  or fayalite + magnetite + quartz + H2O . As long as all phases are present in the buffering mixtures, they fix the fugacity of H2  through the reactions:The outer Au capsule , which contains the COH fluids in equilibrium with graphite ± quartz/coesite ± forsterite + enstatite, is permeable to hydrogen. Therefore, the fugacity  of H2 is expected to be homogeneous and identical in the inner and in the outer capsules. Indirectly, also all the other species composing the COH fluid will be externally buffered, including oxygen. However, since the inner capsule contains a mixed COH fluid instead of pure water, the oxygen fugacity in the inner capsule will be lower compared to that fixed in the outer capsule. The fugacities of oxygen and hydrogen fixed in the outer capsule by both NNO and FMQ were calculated employing Perple_X59 (http://www.perplex.ethz.ch) using the thermodynamic data set of Holland and Powell60 revised by the authors in 2004 and the Perple_X EoS n. 16 (H–O HSMRK/MRK hybrid EoS) (Supplementary Table fH2 fixed by both NNO and FMQ through thermodynamic modeling using (i) the software package Perple_X59 (based on Gibbs free energy minimization) and the EoS of Connolly and Cesare45 (Perple_X EoS n. 11) (CC93 in Supplementary Table 31 (based on gaseous equilibrium constants Kp) with the EoS of Zhang and Duan46 and the static H2 fugacity coefficient provided in the spreadsheet (ZD09 in Supplementary Table 31 (based on gaseous equilibrium constants Kp) with the EoS of Zhang and Duan46, with a modified H2 fugacity coefficient (γH2) changing dynamically as a function of X(O), fitted from the EoS of Connolly and Cesare (1993) (γH2 = a •X(O)3 + b•X(O)2 + c•X(O) + d, where: at 1 GPa and 800 °C, a = −43.919, b = 114.55, c = −105.75 and d = 41.215; at 3 GPa and 800 °C, a = −11,208, b = 26723, c = −21,949 and d = 6979.2) , the X(O), the fO2 and the ∆FMQ (= log fO2=−log fO2FMQ) of the COH fluid in the inner capsule at the investigated P and T conditions , −0.64 (ZD09) and −0.58 (ZD09mod) at 1 GPa, 800 °C, fH2FMQ;−0.73 (CC93), −0.70 (ZD09) and −0.61 (ZD09mod) at 1 GPa, 800 °C, fH2FMQ.−0.42 (CC93), −1.17 (ZD09) and −0.47 (ZD09mod) at 3 GPa, 800 °C, 2O and CO2, with XCO2 [ = CO2/(CO2 + H2O)] generally higher compared to the starting equimolar H2O–CO2 composition 2(aq) and Mg[OSi(OH3)][CH3CH2COO]0  and Mg[OSi(OH3)][CH3CH2COO]0 species are predicted to contribute significantly to the total solubilities of both Mg and Si in the MgO–SiO2–COH system. However, because of the low activity of water in the system the amounts of Mg(OH)2(aq), Si(OH)4(aq), and (OH)3SiOSi(OH)3(aq) are much lower than in the carbon-free system. Under more oxidizing conditions, the Mg[OSi(OH3)][CH3CH2COO]0 species would become unimportant, and the solubilities of Mg and Si in the MgO–SiO2–COH system could become extremely low.The aqueous speciation and solubility calculations in the investigated silicate-bearing systems were carried out using mass balance, charge balance, and mass action expressions in the code EQ315 Quenched COH fluids are extracted from the inner capsule and conveyed to a quadrupole mass spectrometer (QMS). The capsule-piercing device consists of an extraction vessel (reactor) that is heated by an electric furnace to T = 80 °C to transform liquid water into water vapor. The reactor, made of Teflon, is composed of a basal part, where the capsule is placed, and a top part, where a steel pointer is mounted. The piercing is executed by screwing the basal part on to the top part until the pointer penetrates the capsule. The capsule, partially embedded in epoxy, is mounted on a steel support, designed to oppose the rotation exerted by the steel pointer during the piercing operation. The furnace design includes a pilot hole in the base part that permits screwing the reactor with a hex key while placed in the furnace. Openings on the top of the reactor allow the carrier gas (ultrapure Ar) to flow inside it and to generate vent or vacuum conditions. The presence of O-rings ensures a tight seal. The reactor is connected to a QMS by a heated line (80 °C) to avoid condensation of water on the metal tubes. The pressure conditions in the line and in the reactor are monitored through high-resolution sensor gauges ( ± 1 mbar precision). The temperatures of the line, reactor and furnace are monitored with K-type thermocouples. Line and reactor pressures and temperatures are recorded by a Eurotherm Nanodac data recorder with PID control. The internal volume of the reactor was calibrated against the distance h between the basal and the top part. P–T–V conditions in the reactor at the time of piercing are used to retrieve the total moles, n, of gases released from the capsule, following the ideal gas law n = RT/PV.Here, we provide a brief summary of the technique used to measure the volatile composition of the COH fluids in the inner capsule. The full description and the validation of the technique is provided in Tiraboschi et al.2, 10 vol% O2; (ii) 80 vol% Ar, 10 vol% CH4, 10 vol% CO; and (iii) 90 vol% Ar, 10 vol% H2. Water calibration is performed by loading a known amount of water  with a micro-syringe inserted through a silicon septum present at the top into the reactor. The calibration allows performing quantitative analyses of H2O, CO2, CH4, CO, H2, and O2. Uncertainties for major species were typically ~1% for H2O and CO2, and ~10% for CO. After piercing has occurred, gases are conveyed to the QMS by opening a valve. For every m/z channel, the QMS counts are measured every 5 s for 310 steps, for a total of 1550 s of measurement time. The moles of gases were obtained by comparing the areas of the m/z peaks with those of the standards, using a least-squares regression method. Monte Carlo simulations provided the propagation of uncertainties for each species, which corresponds to measurement uncertainty of the sample and can be represented as a probability distribution plot in ternary COH diagrams.For the calibration of the QMS, standard gas mixtures of known compositions were utilized: (i) 80 vol% Ar, 10 vol% CO56, which is applied for the first time on double capsules bearing COH fluids. The recovered experimental capsule is mounted on a freezing stage, which consists of a stack of two Peltier elements, surrounded by plastic to thermally insulate the elements from the atmosphere61. The sample holder is placed on a copper block, in direct contact with the Peltier elements and cooled to T ~ −35 °C. The conventional freezing technique has been updated using a cutter blade mounted on a steel support. This device allows cutting longitudinally double capsules by fastening a screw that pushes the cutter blade via a steel block through the capsule. During this operation, the capsule is enclosed in a copper holder. Once the capsule is cut open, the cutting device is removed from the freezing stage together with the upper part of the capsule holder including the top part of the capsule. The upper half of the capsule is investigated using a binocular microscope, while the lower part remains frozen on the stage during the entire laser-ablation analytical session that follows immediately.The solute content in the fluid was measured employing the cryogenic LA-ICP-MS technique also known as the “freezing technique”24Mg, 25Mg, 26Mg, 29Si, 62Ni, 133Cs, 195Pt, and 197Au, using a 60 µm beam diameter, ~13 J/cm laser fluency, and 5 Hz repetition rate. Data were acquired in blocks of up to  ~ 10 individual sample analyses bracketed by three analyses of the standard NIST SRM610, placed in the ablation chamber with the sample. Background was taken for ~50 s and the sample signal, on the diamond trap or on the solid residue, was collected for ~20 s. LA-ICP-MS data reduction employed the SILLS software62 and in-house spreadsheets to calculate solute concentrations, employing rigorous limit of detection filtering63 for each element and each measurement individually.Analyses were performed using a 193 nm ArF GeoLas Pro excimer laser system coupled to an ELAN DRCD-e quadrupole mass spectrometer at University of Bern. We analyzed the diamond trap for −1 Cs [as Cs(OH)2]. As the initial Cs/H2O ratio is fixed, once the Cs concentration in the fluid phase coexisting with minerals at run P and T is known, solute concentrations of the fluid can be calculated56. However, compared to experiments bearing aqueous fluids, our double-capsule, COH-bearing experiments are more complex, because the initial Cs/H2O is not fixed, as the water content in the inner capsule is variable, depending on P, T and fH2–fO2 conditions  and CfCs is the final concentration of Cs after fluid equilibration at fH2 conditions. ViH2O and VfH2O are the initial and final volumes of water.The cryogenic technique has been originally developed for analyzing the solute content of aqueous fluids. Cesium, introduced in the starting materials, is employed as an internal standard for data quantification, because it is a highly incompatible element that fractionates completely into the aqueous fluid phase at the given residual mineralogy. In our experiments, we introduced a known amount of water solution doped with 590 µg gons Eqs.  and 12. The volume of water is proportional to the moles according to:VH2O, volume of water; nH2O, number of molesof water; VmolH2O, molar volume of water)., this equation can be solved as long as XH2Of is the final H2O/(CO2 + H2O) ratio measured by QMS analysis, and XH2Oi is the initial H2O/(CO2 + H2O) ratio retrieved on the basis of the amounts of water and OAA charged into the capsule. Solute concentrations in the aqueous fraction of the COH fluid at run P and T can thus be calculated (Fig. As ted Fig. .The authors declare that the data supporting the findings of this study are available within the article.Supplementary InformationPeer Review File


Photocatalysis has not found widespread industrial adoption, in spite of decades of active research, because the challenges associated with catalyst illumination and turnover outweigh the touted advantages of replacing heat with light. A demonstration that light can control product selectivity in complex chemical reactions could prove to be transformative. Here, we show how the recently demonstrated plasmonic behaviour of rhodium nanoparticles profoundly improves their already excellent catalytic properties by simultaneously reducing the activation energy and selectively producing a desired but kinetically unfavourable product for the important carbon dioxide hydrogenation reaction. Methane is almost exclusively produced when rhodium nanoparticles are mildly illuminated as hot electrons are injected into the anti-bonding orbital of a critical intermediate, while carbon monoxide and methane are equally produced without illumination. The reduced activation energy and super-linear dependence on light intensity cause the unheated photocatalytic methane production rate to exceed the thermocatalytic rate at 350 °C. 2 can be transformed into valuable hydrocarbons by reaction with H2, but CO is the favoured kinetic product. Here, Liu and co-workers show that plasmonic rhodium nanoparticles not only reduce the activation energy for CO2 hydrogenation, but also photo-selectively produce methane.Atmospheric CO For heterogeneous catalytic reactions with large activation energies to achieve practical rates, heated catalysts are used, but these demand high energy inputs, shorten catalyst lifetimes through sintering deterioration1Rphoto∝In, n>1)18283132332636Recently, it has been discovered that plasmonic metal nanoparticles are photocatalytically active,141516171819202122232425262728−2) on nanoparticle clusters to generate high concentrations of hot carriers1416172021262738394041424445These early demonstrations of plasmonic photocatalysis either featured intense laser pulses  and reverse water gas shift 2 hydrogenation ∼35% below thermal activation energies, it also produces a strong selectivity towards CH4 over CO. Specifically, under illumination from low-intensity (∼W cm−2), continuous wave blue or ultraviolet light-emitting diodes (LEDs), the photocatalytic reactions on unheated Rh nanoparticles produce CH4 with selectivity of >86% or >98%, respectively, with a reaction rate twice that of the thermocatalytic reaction rate at 623 K (350 °C). This high selectivity towards CH4 disappears when the Rh nanoparticles are not illuminated, in stark contrast to plasmonic gold (Au) nanoparticles that only catalyse CO production whether illuminated or not. Density functional theory (DFT) calculations indicate the photo-selectivity of the Rh photocatalyst can be attributed to the alignment of the hot electron distribution with the anti-bonding orbital of the critical reaction intermediate, CHO, which activates the CO2 methanation pathway. Our discovery that plasmonic Rh nanoparticles exhibit a photocatalytic activity with strong product photo-selectivity opens an exciting new pathway in the long history of heterogeneous catalysis by offering a compelling advantage of light over heat.Here, we report the discovery that plasmonic Rh nanoparticles are photocatalytic, simultaneously lowering activation energies and exhibiting strong product photo-selectivity, as illustrated through the CO2O3) nanoparticles with a mass loading of 1.02%  ultraviolet light source (352O3 support with a mass loading of 1.70% (Au/Al2O3)15The Rh photocatalyst was prepared by dispersing 37 nm Rh nanocubes on aluminium oxide  from the overall reaction rates (light on) at the same temperature. All reactions were performed at atmospheric pressure with either an H2-rich 1:5.5 or H2-deficient 1:3.1 mixture of CO2:H2 (as compared with the 1:4 stoichiometry of CO2 methanation) and argon (Ar) as an internal standard.A fixed-bed reaction chamber equipped with a quartz window was used to carry out the photocatalytic reactions with controlled light illumination . The pho4 and CO were produced at comparable rates at 623 K under dark, H2-rich conditions . Upon illumination of ultraviolet light , a seven-fold increase in the CH4 production rate was observed, while only a slight increase in CO production was detected. No other carbon-containing product was observed above the detection limit of the mass spectrometer in our experiments, and the reaction rates responded to light instantly and reversibly. Control experiments using pure Al2O3 nanoparticles . The adsorbed CO can either desorb from the surface or be hydrogenated to form CHO. The dissociation of CH–O generates CH, followed by further hydrogenation to form CH4  and Au (3.25 eV)4 production under dark conditions, whereas the Au catalyst exclusively produced CO.These results demonstrate that the different selectivity of thermo- and photocatalytic reactions on the Rh and Au nanoparticles is primarily determined by the properties of metals, specifically the differing metal-adsorbate interactions. On the Rh catalysts, previous experimental and theoretical investigations47515253545556574:CO ratio of ∼60:40 in the tested range of temperatures and reaction rates. In contrast, under ultraviolet illumination the CH4 production rate was significantly and selectively enhanced. The photoreactions exhibit >95% selectivity towards CH4, and the resulting selectivity towards CH4 from the overall reaction is >90% under 3 W cm−2 ultraviolet illumination and H2-rich conditions over the tested temperature range. Experiments under H2-deficient conditions maintained this high selectivity under illumination but exhibited even lower selectivity under dark conditions, confirming that illumination, not heat or excess H2 feedstock, is responsible for the highly selective production of CH4 . This analysis is based on the assumption that thermo- and photo-reactions have the same elementary steps and surface intermediates, a claim supported by a recent kinetic study of RWGS on Au photocatalystsThe selectivity of these reactions is changed when hot carriers are photoexcited in plasmonic nanoparticles. The different selectivity of thermo- and photo-reactions on Rh nanoparticles is depicted in n of CH4 . The Rh  other , , 63 beca4 production with high selectivity was demonstrated on Rh under ultraviolet illumination at 3 W cm−2 and H2-rich conditions with a reaction rate (circled red square in T=29 K), was caused by photothermal heating of the catalyst bed (separately measured to be 25 K by a non-reactive control experiment with flowing Ar and H2) and the exothermic nature of the CO2 methanation reaction . Likewise, the ambient reaction rate for the highest intensity of our blue LED  was 7.41±0.37 at 623 K and increased to 24.4±1.2 at 523 K. The quantum yield for CH4 production was measured to be 3.70% at 623 K.The effects of LED intensity and photon energy on the reaction rates using the Rh photocatalyst were carefully studied by varying the output power and wavelength of the light source. Under ultraviolet illumination near ∼1 W cm−2) as the ultraviolet LED at 3 W cm−2, the reaction rate and quantum yield were smaller (blue triangles in n≈3.7 at 523 K)−2), the EF and quantum yield at 623 K reached 27.8±1.4 and 7.50%, respectively  of the thermo- and photo-reactions was obtained , respectively, consistent with previous reports on supported Rh catalysts514 production showed a reduced Ea=50.4±1.8 kJ mol−1 (0.52 eV) for all light intensities. This reduction of Ea was also observed for CO production on the Au photocatalyst with visible light, decreasing from 55.8±0.5 kJ mol−1 (0.58 eV) for the thermocatalytic reaction to 39.5±2 kJ mol−1 (0.41 eV) for photoreactions. The photoreaction rates of CO production on the Rh photocatalyst were too small for the activation energy to be deduced reliably.To understand the mechanism, the reaction kinetics of COobtained . In virt2 hydrogenation on the Rh and Au photocatalysts shed light on the reaction mechanism of plasmonic photocatalysis. In thermocatalytic reactions, interactions between surface intermediates and catalysts dictate the propensity of competing pathways. For example, the higher selectivity towards CH4 in the thermocatalytic reactions on Rh has already been ascribed to its higher Eads,O  for adsorbed CHO and CO, key intermediates for CH4 and CO production4751525354555657π* anti-bonding bands, which can accept hot electrons to weaken the C–O bond and facilitate CH4 production, can be easily identified on the C(pz) and O(pz) orbitals at ∼2 eV (px) orbital at ∼1 eV for CO : the lower energy hot electrons had a lower probability of transferring to the higher energy anti-bonding orbital of the CHO intermediate (∼2 eV) and a higher probability of transferring to the lower energy orbital of the CO intermediate (∼1 eV). We note that due to the rapid decay via electron-electron and electron-phonon scatterings, the actual energies of the hot electrons are distributed below the associated photon energies of ultraviolet and blue light. Nevertheless, our computed relative magnitude of the LDOS peaks and the energy ordering for the relevant anti-bonding bands still offer a valid qualitative interpretation both for overall preference for CH4 (under either ultraviolet or blue light) and for the slightly reduced CH4 selectivity under blue light. A recent study using alloys similarly demonstrated the selective activation of certain reactants with different photon energiesDFT calculations were carried out to understand how hot electrons affect the intermediates in the RDSs of CHat ∼2 eV . On the V for CO  suggests2 hydrogenation on plasmonic Rh photocatalysts is summarized in 4 and CO at comparable rates on the ground-state reaction coordinate  and 25 mg polyvinylpyrrolidone  were dissolved in 2 ml EG separately and injected into the hot reaction mixture by a two-channel syringe pump at a rate of 1 ml h−1. The injection was paused for 15 min after adding 20 μl of the Rh precursor. After complete injection of the precursor, the reaction mixture was stirred for another 30 min and then cooled to room temperature. The suspension was washed with deionized water/acetone until no Cl− and Br− was detected in the supernatant. The solid was dispersed in 20 ml ethanol and impregnated on 90 mg Al2O3 nanoparticles . The obtained solid was ground into powder and calcined in air at 400 °C for 2 h. The Rh nanocubes were well dispersed on the Al2O3 support and behaved as isolated nanoparticles.2O3 photocatalystAu/Al. A deposition-precipitation method was used to prepare highly dispersed small Au nanoparticles on support2O3 nanoparticles were dispersed in 10 ml deionized water in a 20 mL glass vial by sonication. A total of 16 mg gold(III) chloride trihydrate  was added into the suspension and stirred in an oil bath at 80 °C. The pH was adjusted to ∼8 by 1 M sodium hydroxide (NaOH) solution. After 4 h, the suspension was cooled and washed with copious deionized water/acetone until no Cl− was detected in the supernatant. The solid was dried at 100 °C overnight and calcined at 300 °C for 2 h.2, Research grade), carbon dioxide  and argon  were obtained from Airgas. The gas flow rates were controlled individually by mass flow controllers . Overall, ∼15 mg of photocatalyst was loaded into the sample cup  in the reaction chamber  for each experiment. The temperature was measured by a thermocouple under the catalyst bed, and calculations indicate good thermal contact between the Rh nanoparticles and the surrounding media. The temperature of the photocatalyst bed was controlled by a PID temperature controller kit  that managed the resistive heating power of the reaction chamber, and cooling water to mitigate heating caused by LED illumination. The photocatalysts were first reduced under 60.1 ml min−1 H2 and 27.6 ml min−1 Ar at 350 °C for 4 h and then another 10.9 ml min−1 CO2 was introduced to achieve an H2-rich CO2:H2 ratio of 1:5.5 and activate the photocatalysts for ∼12 h to reach stable catalytic activities. The experiments with a H2-deficient CO2:H2 ratio of 1:3.1 were conducted under 19.5 ml min−1 CO2, 60.1 ml min−1 H2 and 16.5 ml min−1 Ar. Three LEDs with emission of 365 nm, 460 nm and 5700 K white light  were used as light sources. The output power was controlled by a remote dial and measured with a thermopile power metre . The emission spectra of the light sources were measured with a CCD-based spectrometer . The gaseous product was analysed by a quadrupole mass spectrometer  equipped with a Faraday cup detector. The detection limit of the mass spectrometer is ∼0.001% conversion of CO2. The reactions were all operated in the low-conversion and light-controlled regime. For each temperature and light intensity condition, at least 15 min elapsed before reaching steady state and seven sequential measurements were made to determine the steady-state concentration of each gas and the associated reaction rates and uncertainties. The 15 atomic mass unit (amu) signal was used to quantify the methane production rate. The 28 amu signal was used to quantify the carbon monoxide production rate, from which the background from carbon dioxide feedstock was subtracted. Deuterium  was used in place of H2 for the isotopic labelling experiments.The photocatalytic reaction was carried out on a custom-built gaseous reaction system. Hydrogen (H−1), and 1 × 8 × 8 for the projected LDOS calculations. Periodic boundary conditions were used in all three directions for the face-centred cubic (fcc) Rh model (x direction to separate the Rh(100) surface slabs containing four layers of Rh atoms. In the y and z directions the lattice size for the supercell was chosen to be three times that of a unit cell. The adsorbed CHO and CO groups were placed on the exposed Rh(100) surface.All calculations in this work were performed with the Vienna Ab initio Simulation Package (VASP)Rh model . A vacuu2 Twin operating at 200 kV. The TEM samples were prepared by dispersing the photocatalysts in ethanol with sonication and depositing on a copper grid coated with a carbon film . Diffuse-reflectance ultraviolet–visible extinction spectra were obtained on an Agilent Cary 5,000 equipped with an external diffuse-reflectance accessory (DRA-2500). The composition of the photocatalysts was measured by a Kratos Analytical Axis Ultra X-Ray Photoelectron Spectrometer.Transmission electron microscopy (TEM) images were collected by a FEI Tecnai GThe data that support this study are available from the corresponding authors on request.How to cite this article: Zhang, X. et al. Product selectivity in plasmonic photocatalysis for carbon dioxide hydrogenation. Nat. Commun.8, 14542 doi: 10.1038/ncomms14542 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary Figures, Supplementary Notes and Supplementary References


Additionally, 22 IMRT fields were measured and evaluated using gamma index analysis. The overall accuracy of RCF with respect to CC04 was found to be 2%–4%. The overall accuracy of RCF was determined using the absolute mean of difference for all flat and wedge field profiles. For clinical IMRT fields, both scanners showed an overall gamma index passing rate greater than 90%. This work demonstrated that EBT films, in conjunction with a commercially available flatbed scanner, can be used as an accurate and precise absolute dosimeter. Both scanners showed that no significant scanner nonuniformity correction is necessary for accurate absolute dosimetry using the EBT films for field sizes smaller than or equal to 15×15 cm2.To report a study of the use of GAFCHROMIC EBT radiochromic film (RCF) digitized with a commercially available flatbed document scanner for accurate and reliable all‐purpose two‐dimensional (2D) absolute dosimetry within a clinical environment. We used a simplified methodology that yields high‐precision dosimetry measurements without significant postirradiation correction. The Epson Expression 1680 Professional scanner and the Epson Expression 10000XL scanner were used to digitize the films. Both scanners were retrofitted with light‐diffusing glass to minimize the effects of Newton rings. Known doses were delivered to calibration films. Flat and wedge fields were irradiated with variable depth of solid water and 5 cm back scatter solid water. No particular scanner nonuniformity effect corrections or significant post‐scan image processing were carried out. The profiles were compared with CC04 ionization chamber profiles. The depth dose distribution was measured at a source‐to‐surface distance (SSD) of 100 cm with a field size of PACS number: 87.53.Bn Film has been used to record ionizing radiation since the original discovery of X‐rays and has remained an important technique through the present time. Since then, film dosimetry has been proven to be a highly reliable and valuable tool for radiation dosimetry. The high spatial resolution of film makes it a useful dosimeter in quality assurance (QA) and research. With the introduction of intensity modulated radiation therapy (IMRT), film dosimetry has found another application for evaluating the high gradient dose distributions generated by IMRT.,,,Currently, 2 types of film are available for radiation therapy applications: radiographic and radiochromic , temperature and humidity dependence of polymerization, and scanning artifacts.,GAFCHROMIC EBT  radiochromic film (RCF) is a commercially available film designed to measure the absorbed dose from photon beams with a recommended dose range of 1 cGy to 800 cGy. RCF is composed of radiation‐sensitive dye that is organized into microcrystals and embedded in a gelatin binder. Upon irradiation, a solid state polymerization(–) have attempted to correct the scanner nonuniformity effect and were able to improve it by 1.1% to 3.6%. A sophisticated correction matrix for each film batch must be generated that will compensate for the light scattering from the scanner lamp, which depends on pixel location and OD, to obtain such close agreement. Briefly, a set of uniformly irradiated films are scanned and normalized profiles for each film are established. From these normalized profiles, correction factors are obtained, taking the geometrical position and the optical density into consideration. In effect, a three‐dimensional (3D) correction factor is generated. Although this scanner nonuniformity correction method has produced good results, it must be performed for each batch of film, which is labor intensive and thus impractical in a clinical setting.Proper usage of a flatbed scanner is important to minimize significant scanning artifacts. Lynch et al.–13 h~8% for the 300 cGy film. This variation in OD can be minimized with consistent positioning of the films during irradiation and scanning. The third effect depends on the temperature of the scanner bed while scanning and it can result in a variation in OD of up to 7% for low OD.The second effect is a film rotation effect, which depends on the orientation of the film on the flatbed scanner bed. Lynch et al.In the clinical setting, the correction methods stated above can be cumbersome and impractical. In this paper, we report the use of GAFCHROMIC EBT RCF, in conjunction with two flatbed scanners, to obtain good agreement with dose measurements made using an ionization chamber (for cross‐plane and in‐plane directions for open and wedge fields) and with a planar dose (for IMRT fields) without using a scanner nonuniformity correction method. The two flatbed scanners were the Epson Expression 1680 Professional scanner  and the Epson Expression 10000XL scanner. For comparison, CC04  ionization chamber profiles were used as a reference.3 treatment planning system .To evaluate the IMRT dose distribution, we used a planar dose distribution from the Pinnacle10×10 cm2 defined at a source‐to‐axis distance (SAD) of 100 cm. Beam profiles were scanned using a 3D water tank system with a CC04 ionization chamber that has a sensitive volume of 0.04cm3. Water tank profile scans were used as the reference for all open and wedge field profiles. For all CC04 scans, a constant SSD of 90 cm was maintained. For flat fields, three field sizes  and four depths  were used. For wedge fields, two field sizes (6×6 cm2 and 10×10 cm2) and three depths  were used. A depth dose distribution was measured using the CC04 ionization chamber at a SSD of 100 cm with a field size of 10×10 cm2. The pixel resolution for all profiles and depth dose distributions was maintained at 1 mm. To evaluate the IMRT 2D dose distribution, planar dose from the Pinnacle3 treatment planning system for comparison was used. For IMRT fields, the gantry and collimator angles were maintained at 0 degrees with a SSD of 90 cm, depth of 10 cm, and 5 cm of backscatter material. The planar doses from the treatment planning system and the MapCHECK 2D diode array detector  were also used for the evaluation. A total of 22 IMRT fields from the treatment plans for four patients with head and neck cancers were delivered and analyzed for this study.For this study, all irradiations were performed with a 6 MV photon beam from an Elekta Synergy linear accelerator . Absolute dose calibration of the linear accelerator was done according to the TG‐5121.6×29.7 cm2 and 31 × 43.7cm2, respectively. The physical dimensions of the Epson 1680 scanner were 33.2 cm width, 56.2 cm depth, 13.3 cm height, and 8.5 kg weight. The physical dimensions of the Epson 10000XL scanner were 65.6 cm width, 45.8 cm depth, 15.8 cm height, and 13 kg weight.Both the Epson Expression 1680 and 10000XL scanners are flatbed color image scanners with xenon gas cold cathode fluorescent lamp and charge‐coupled device (CCD) line sensor. Both systems have transparency units, which were used to scan the RCFs. Both scanners were also retrofitted with light diffusing glass which is effective at minimizing Newton ring artifacts.Radiochromic films (Lot # 47261‐07I) were used for flat and wedge fields and depth dose measurements. For IMRT studies, RCFs with Lot # 36306‐001I were used. For each measurement set, calibration films were also irradiated to convert OD to absolute dose. In this study, the term absolute dose or dosimetry refers to a technique in which a known dose is defined at a corresponding OD so that OD can be converted to be expressed in terms of absolute dose. The doses of the calibration films were cross‐calibrated with the measurements from an ADCL calibrated ion chamber, following TG51 protocol.~5×5cm2 squares. The films  were marked to maintain consistent orientation during scanning. After these pieces were cut and marked, a reference setup was used to irradiate the films to known doses. The reference setup was a 6 MV isocentric perpendicular setup at a SSD of 90 cm, depth of 10 cm, field size of 10×10 cm2, and 5 cm of solid water backscatter conditions. In this reference setup, 1 monitor unit (MU) was equal to 0.78 cGy. Once this setup was established, each EBT calibration film was placed just below the 10 cm depth of solid water in the middle of the light field and irradiated to known doses. One piece of calibration film was not irradiated to represent 0 cGy. The calibration dose ranged from 0 cGy to 312 cGy. After the film images were allowed to develop for 24 hrs, RCFs were scanned using the Epson 1680 and Epson 10000XL scanners to establish a net OD versus dose sensitometric curve  with four depths . For wedge fields, there were two field sizes (6×6 cm2 and 10×10 cm2) with three depths . For all flat fields, 200 MU were used for the irradiations while, for all wedge fields, 400 MU were used. For both flat and wedge fields, an SSD of 90 cm was maintained. Except for the 20×20 cm2 beam, the films were irradiated in an orientation such that the cross‐plane direction was orthogonal to the longer side of the film (portrait mode). Because of the limitation due to film size, the film was positioned so that the cross‐plane of the 20×20 cm2 beam was parallel to the longer side of the film and the in‐plane profiles were not measured. A depth dose distribution was measured using a CC04 ionization chamber at an SSD of 100 cm with a field size of 10×10 cm2. For the depth dose setup, RCF was sandwiched between two 10 cm thick solid water blocks. The length (shorter side) of the RCF was aligned with the length of the solid water and laid flat on the couch horizontally. The gantry was rotated 90° and the source‐to‐surface distance was 100 cm with a field size of 10×10 cm2. For the IMRT plans, the gantry and collimator angles were maintained at 0° with 90 cm, depth of 10 cm, and 5 cm of backscatter material. In all, 22 IMRT fields were studied.A series of flat and wedge fields were irradiated with varying field sizes at different depths to obtain cross‐plane and in‐plane profiles. For flat fields, there were three field sizes ((0.254mm/pixel) and saved as a] 48‐bit RGB uncompressed tagged image file format (TIFF) image file.Both scanners were turned on 30 min before scanning to allow them to warm up sufficiently. After the 30 min warm‐up, several scans were made without any films to further warm up both systems. Each calibration and measurement film was then placed individually in the center of the scanning bed, with their orientation maintained constant to minimize film rotation error. Since no scanner nonuniformity correction was applied, it was critical that the film orientation be maintained for each scanner. RCFs were positioned in both scanners in portrait mode . Before each measurement scan, a preview scan was done to verify the film's position. Once verified, the whole scanning area was scanned with 100 dpi resolution (CC04@CAX–RCF@CAX) at central axis CAX (a single pixel point from the RCF profile) of the profile normalized to the CC04 dose. The mean of the difference is the mean of the dose difference between CC04 and RCF for 50% – 50% (D50) and 80% – 80% (D80) of the profile . The calibration films were used to generate a fourth‐order polynomial sensitometric curve which was applied to the measurement films to convert the net OD to absolute dose. Only the pixel values from the red channel were used in the analysis. MATLAB was also used to analyze the cross‐plane and in‐plane profiles for the flat and wedge fields. The 2D dose distributions from the film measurements, the planar dose from the treatment planning system, and the 2D diode array detector were used to evaluate the IMRT fields. All three datasets were imported into the 2D diode array detector software for gamma index analysis. The RCF profiles (cross‐plane and in‐plane) and depth dose distributions were resampled to have the same resolution as the CC04 ionization chamber measurements (1 mm per pixel). To evaluate film measurements obtained with the CC04 ionization chamber for a given profile, a central axis (CAX) percent dose difference and the mean of the difference was used. The CAX percent dose difference is the dose difference To evaluate the IMRT fields, the gamma test criteria were 3% dose difference and 3 mm distance‐to‐agreement (DTA). Pass rates of greater than or equal to 90% were considered acceptable since these are the criteria used in our clinic.5×5 cm2,10×10 cm2, and 20×20 cm2, respectively. For this dataset, the maximum and minimum CAX percent dose differences were −1.6% and −2.3%, respectively, for the Epson 1680 scanner. For the Epson 10000XL scanner, the maximum and minimum CAX percent doses differences were 2.6% and 1.1%, respectively. The D50 values for the mean of the difference (one standard deviation) for the Epson 1680 scanner were −2.7%(1σ=2.8%),−3.0%(1σ=3.6%), and −0.3%(1σ=3.3%) for field sizes of 5×5 cm2, 10×10 cm2, and 20 xby 20 cm2, respectively. For the same field sizes, D80 values for the mean of the difference were −2.3%(1σ=2.0%),−2.5%(1σ=2.5%), and −0.6%(1σ=1.9%), respectively. Similarly, for the Epson 10000XL scanner, the D50 values for the mean of the difference were 1.1%(1σ=2.6%),2.2%(1σ=2.2%), and 2.2%(1σ=2.2%) for field sizes of 5×5 cm2, 10×10 cm2, and 20 xby 20 cm2, respectively. For the same field sizes, D80 values for the mean of the difference were 1.3%(1σ=1.6%),2.2%(1σ=1.4%), and 1.9%(1σ=0.9%), respectively. All other flat field profiles had similar results. Tables Figure 6×6 cm2  for a field size of 6×6 cm2 and 0.5%(1σ=5.7%) for a field size of 10×10 cm2. For the same field sizes, D80 values for the mean of the difference were −1.2%(1σ=2.0%) and −0.1%(1σ=1.7%), respectively. For the Epson 10000XL scanner, the D50 values for the mean of the difference were −2.9%(1σ=5.2%) for a field size of 6×6 cm2 and −1.3%(1σ=3.1%) for a field size of 10×10 cm2. The D80 values for the mean of the difference were −2.8%(1σ=2.9%) and −1.3%(1σ=2.8%) for a field size of 6×6 cm2 and 10×10 cm2, respectively. All other wedge field profiles had similar results. Tables Figure 0.2%(1σ=1.4%) for the Epson 1680 scanner and 0.9%(1σ=1.2%) for the Epson 10000XL scanner. Table Figure Gamma index analysis with criteria of 3% dose difference and 3 mm DTA were used to evaluate 22 IMRT fields using the 2D diode array detector software. Planar doses from the treatment planning system were used as the reference. For the Epson 1680 scanner, 20 of the 22 IMRT fields had a passing rate greater than 90%. For the Epson 10000XL scanner, all 22 IMRT fields had a passing rate greater than 94%. The performance of RCFs was evaluated using the 2D diode array detector, which is a standard device for IMRT QA in our clinic, using the gamma index  have to be done in conjunction with the measurement film to properly characterize the conversion from OD to absolute dose. In order to do this correctly, the user should perform a quick output check on the linear accelerator to make sure that its daily output is within tolerances. Once this has been done, a known dose is delivered to each calibration film to generate a sensitometric curve. It is also important to keep in mind that the temperature and humidity level will affect the crystal polymerization process. Therefore, both calibration and measurement films should be handled together at all times. The orientation of the film during scanning will also affect pixel OD. For this reason, it is critical for the user to mark the films' orientation so that they can be consistently placed on the scanning bed. For this work, no film nonuniformity corrections were done. All films were placed in the center of the scanner bed to minimize scanner nonuniformity effects. Finally, only the red channel data from the TIFF files were used for analysis.(<10cGy). With such low doses, the percent dose difference analysis would show higher values at low doses. Another reason for such disagreement was the inherent scanner nonuniformity effect, which was not corrected for in this work. Because the profiles beyond the 50% penumbra region were larger than the 10×10 cm2 field size, scanner nonuniformity had a noticeable effect. This was more apparent for the Epson 1680 scanner  for the Epson 1680 scanner and of 0.9%(1σ=1.2%) for the Epson 10000XL scanner. This result is consistent with that of van Battum et al.±0.6%. They measured depth dose profiles using a water tank with a CC04 ionization chamber and EBT film immersed in water during irradiation. The increase in depth dose difference at depths larger than 18 cm may be due to breakdown of charged particle equilibrium.The depth dose distribution from a depth of 0.15 cm to 20 cm for a field size of 10×10 cm2 will start to produce a noticeable effect from the scanner nonuniformity, which will adversely affect the passing rate. For such large field sizes, the user will observe that most failure points lie on the edges of the fields because of the scanner nonuniformity effect.All 22 IMRT fields were taken from the treatment plans of four head and neck patients, with field dimensions ranging from 10 cm to 20 cm. The two fields that had a passing rate of 85.7% had both x‐ and y‐dimensions greater than 20 cm. Because of the large field size, these fields were susceptible to an over response by the Epson 1680 scanner due to scanner nonuniformity. Better passing rates were achieved by the Epson 10000XL scanner because of its larger lamp size and scanning area. It is worth mentioning that because the Epson 1680 scanner has a smaller scanning area than the Epson 10000XL scanner, scanning IMRT fields larger than ~35cGy to 150 cGy), all MU were increased by a factor of 5  so that the doses delivered to the films were in a range where percent relative error was less than 1%. The percent relative error was obtained by irradiating small strips of RCF similar to the dose calibration films to known doses (0 cGy – 621 cGy). Means and standard deviations (1σ) of doses were obtained for all strips of films. The percent relative error was ascertained by taking the ratio between the standard deviation and the mean for a particular film strip. A small percent relative error (<1%) would indicate small OD variations. A large percent relative error (>1%) would indicate large OD variations. In other words, a small percent relative error would indicate a high level of precision by the RCF. From Fig. (<100cGy), the RCF have a percent relative error greater than 1%, while at higher doses (>100cGy), the EBT films have a percent relative error less than 1%. Overall, using RCF in conjunction with a commercially available flatbed scanner is appropriate for absolute dosimetry for IMRT. As indicated by the gamma index results for the scanners and 2D diode array detector, the detector had a higher passing rate than the film. This is partly due to the fact that the detector has much fewer evaluation points than the RCF, which has thousands of evaluation points. Also, unlike RCFs, the detector is not impacted by the scanner nonuniformity effect. In spite of these minor pitfalls, both scanners performed well relative to the detector in evaluating IMRT plans.When delivering IMRT fields  using RCF without significant scanner nonuniformity corrections.The purpose of this work was to demonstrate accurate absolute dosimetry using GAFCHROMIC EBT film, in conjunction with a commercially available flatbed scanner, is feasible without the need for any scanner nonuniformity correction. In this work, the overall accuracy of flat and wedge profiles when compared with CC04 ionization chamber profiles was 2%–4% for both the Epson 1680 and the Epson 10000XL scanners. In general, IMRT fields do not exceed


The state is excited from the ground 2S1/2 state (which has the same parity) using two single-photon transitions via the intermediate 2P3/2 state. The value of the hyperfine constant we measure is A = 93.095(52) MHz, which resolves two discrepant values reported in the literature measured using other techniques. Our value is also consistent with theoretical calculations.We report a precise measurement of hyperfine structure in the 3S However, experimental measurements are complicated by the fact that Li is highly reactive with most transparent materials. This precludes the use of vapor cells , and the technique of saturated absorption spectroscopy (SAS) to get narrow Doppler-free hyperfine peaks.The three-electron structure of Li lends itself to theoretical calculations with high accuracy, which can be used to test fundamental atomic theories of few-electron systems2.The standard way to solve this problem is to collect fluorescence from an atomic beam excited by a perpendicular laser beam. The perpendicularity ensures that the first-order Doppler effect is minimized; but it is not really zero (Doppler free) because of a small misalignment angle from perpendicularity and any divergence of the beam. In fact, the lineshape of each peak is not Lorentzian but Voigt (combination of Lorentzian for spontaneous decay and Gaussian for Doppler broadening). However, if one still wants an SAS spectrum with Doppler-free Lorentzian peaks, then the solution is to use an actively pumped stainless steel (SS) chamber with high-enough vapor pressure of Li to get significant absorption1/2 state of 7Li. The state is populated using a two-step laser excitation process—the first one is a diode laser at 671 nm to populate intermediate 2P3/2 state, while the second one is a diode laser at 813 nm that takes it to the upper 3S1/2 state. The motivation for the measurement is that there are two conflicting high-precision values reported in the literature—one using Stark spectroscopy of Rydberg state reported in 19953, and the second using two-photon laser spectroscopy reported in 20034. The value from the former is 189.36(43) MHz, while the value from the latter is 186.212(22) MHz. Our technique is different because it uses two electric dipole allowed single-photon transitions, and does not rely on locking to the second laser. Our value of 186.19(10) MHz is consistent with the more recent measurement reported in ref.4. This value is also in good agreement with theoretical calculations6.In this work, we use the atomic-beam technique to measure the hyperfine interval in the 3S1/2 → 2P3/2 transition at 671 nm. The upper transition from the intermediate state is the 2P3/2 → 3S1/2 transition at 813 nm. Both transitions are strong because they are electric dipole (E1) allowed; hence they can be driven using low-intensity laser beams.The relevant low-lying energy levels of Li are shown in Fig. 7. The one at 671 nm uses a grating with 2400 lines/mm, while the one at 813 nm uses a grating with 1800 lines/mm.The experimental setup is shown schematically in Fig. e2 diameter of 1 mm × 4 mm. Its power is controlled using a halfwave (λ/2) retardation plate followed by a polarizing beam splitter cube (PBS). The laser frequency is locked using modulation at 30 kHz of the injection current into the laser diode. As seen from Fig. 2 line (2S1/2 → 2P3/2 transition) are too closely spaced to be resolved completely. Therefore, the laser is locked to the unresolved F = 2 → F′ peak in the D2 line—the exact lock point is not important as long as transitions to the upper state are allowed. Both 1 → F′ and 2 → F′ will work; however, 2 → F′ is chosen because the peak is more prominent. This point is explained further when we discuss the experimental spectrum.The laser beam at 671 nm has an elliptic shape, with 1/e2 diameter of 1.5 mm × 4 mm. The measurement requires the 813 nm beam to be shifted by a known frequency. This is achieved using an acousto-optic modulator (AOM). The frequency of the AOM is in the RF range, which is set by a frequency generator (HP8656B) with a timebase accuracy of 10−6. Both the unshifted and AOM-shifted 813 nm beams are used for the experiment. As seen in the figure, the two beams are separated and combined using PBSs. The polarization of the combined beam is adjusted using a λ/2 plate. The combined beam counter-propagates with the locked 671 nm beam for the two-step excitation to the 3S1/2 state. The polarization of the combined 813 nm beam is adjusted to get significant heights for both unshifted and AOM-shifted beams.The laser beam at 813 nm also has an elliptic shape with 1/−7 torr using a 40 l/s ion pump. The Li source consists of an SS vial containing a small ingot of unenriched Li. The vial is resistively heated to a temperature of about 200 °C. When heated, the source produces an atomic beam containing both stable isotopes of Li, namely 6Li and 7Li. The atomic beam is mechanically collimated with a divergence angle of 0.1 mrad using apertures. The pressure rises by 2 orders-of-magnitude when the source is turned on. The two laser beams intersect the atomic beam at right angles, which as mentioned before minimizes the first-order Doppler shift. The fluorescence signals are collected by photomultiplier tubes (PMTs).All the required spectroscopy experiments are done by having an atomic beam inside an ultra-high vacuum (UHV) system, maintained at a pressure below 107Li used for the experiment is shown in Fig. 1/2 state to the intermediate 2P3/2 state is plotted as a function of 813 nm laser frequency. The AOM shift for the spectrum shown is 168 MHz. The first peak (P1) corresponds to the F = 2 level of the 3S1/2 state; the second peak (P2) corresponds to the F = 1 level of the 3S1/2 state; and the third peak (P3) is the second peak along with the AOM shift. The solid line is a multipeak fit to the 3 peaks with a Lorentzian lineshape for each peak. Even though, as mentioned in the introduction, the lineshape of each peak is a Voigt function, we have used a Lorentzian function because it fits the data quite well, as seen from the featureless residuals on top of each peak . In addition, the error  is well-defined for a Lorentzian function.A typical spectrum in S1/2 → 2P3/2 transition—a combination of the 5.25 MHz natural linewidth of the 3S1/2 state8 convolved with the 6 MHz natural linewidth of the 2P3/2 state. The increase in linewidth arises for the following reasons.(i)Small misalignment angle from perpendicularity of the laser and atomic beams—we know that the angle is small because the increase in linewidth is quite small.(ii)Residual divergence of the atomic beam.(iii)3/2 state.Closely spaced  hyperfine levels of the 2PThe linewidth of each peak is 15–20 MHz, which is larger than the expected linewidth of the 3x axis in Fig. The δ is equal to the sum of the errors in P1 and P3.Since the hyperfine interval to be measured is near 190 MHz, the AOM shift is varied from 160 to 212 MHz, in steps of 2 MHz. At each value of AOM shift, a spectrum of the kind shown in Fig. δ as a function of AOM frequency is shown in Fig. A, the measured value of the constant is A = 93.095 ± 0.050 MHz, where the error is the statistical error in the curve fit.The quantity 9. The main advantage is that the technique avoids servo-loop errors, as demonstrated by us in ref.10. Another advantage is that the measured interval is independent of scaling of the laser scan axis. Any such rescaling will change the y-axis of Fig. Scanning the laser to get the entire spectrum has many advantages compared to the other technique that we have developed where the AOM frequency is locked to a hyperfine peakError in the curve fit – 50 kHz.Doppler shift error due to non-overlap of shifted and unshifted 813 nm beams – 10 kHz.AC Stark shift, which causes the lineshape to deviate from Lorentzian – 5 kHz.Optical pumping into Zeeman (magnetic) sublevels in the presence of stray magnetic fields – 10 kHz.Velocity redistribution due to radiation pressure – 5 kHz.Collisional shift – 1 kHz.AOM frequency timebase error – 0.3 kHz.The different sources error in the measurement are listed below. The values for each one are detailed in the attached supplementary file.Adding the above sources of error in quadrature yields the final error in the measurement as 52.45 kHz. Thus the value of the hyperfine constant measured in this work iset al.4, but quite inconsistent with the value of Stevens et al.3. This shows that the work in ref.3 may have been plagued by unaccounted systematic errors. The figure also shows that our value is consistent with theoretical calculations, done with Hylleraas variational method5 and multiconfiguration Hartee-Fock method6. We also show that our value compares favorably with results of isotope-shift measurements in Li (both stable and short lived) done at GSI in Germany11. The authors extract the value of the relevant hyperfine constant using a combination of theory and experiment.Our present measurement is compared to the two conflicting earlier experimental values in Fig. 1/2 state of 7Li. The state is populated using two single-photon transitions via the intermediate 2P3/2 state. Both transitions are excited using diode lasers. This method is different from previous techniques used in refs4, which report discrepant values for the hyperfine constant. Our value of A = 93.095(52) MHz is consistent with the more recent measurement in ref.4, which uses two-photon spectroscopy for excitation from the ground state. Our value is also consistent with theoretical calculations.In summary, we have measured the hyperfine constant in the 3SSupplementary information