Detection of [Ne II] Emission from Young Circumstellar Disks
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第40卷第3期2021年6月红外与毫米波学报J.Infrared Millim.Waves Vol.40,No.3 June,2021文章编号:1001-9014(2021)03-0363-06DOI:10.11972/j.issn.1001-9014.2021.03.013 Improving measurement accuracy of composite non-point sources emissionsbased on laser detectionTANG Qi-Xing1,2*,ZHANG Yu-Jun1*,HE Ying1,WANG Li-Ming1,LI Meng-Qi1,YOU Kun1,LI Xiao-Yi1,CHEN Dong3,LIU Wen-Qing1(1.Key Laboratory of Environmental Optics&Technology,Anhui Institute of Optics and Fine Mechanics,the ChineseAcademy of Sciences,Hefei,230031,China;2.Anhui Agricultural University,Hefei,230061,China;3.Hefei University of Technology,Hefei230009,China)Abstract:In the measurement of source emissions,it is inevitably interfered by the gas emissions from the adja⁃cent fields and turbulence,which affects the accuracy of gas detection.In order to improve the measurement accu⁃racy,the measurement method of composite non-point sources non-uniformity methane emissions based on laserspectrum detection has been studied.Moreover,the interference in external environment is reduced with multipleself-calibration measurements.A detection system for composite non-point source emissions has been estab⁃lished,and the detection method of eliminating gas fluctuation has been proposed.First,the accuracy verificationtest has been carried out.The standard deviation of source a is0.17,and that of source b is0.18.Subsequently,a comparative test has been carried out with the extraction method of the photo acoustic spectrum,and the correla⁃tion coefficient reached0.91.Finally,the actual field measurement has been carried out to monitor the two non-uniform emission sources caused by different fertilization methods to achieve accurate measurement.It has practi⁃cal engineering value such as agricultural gas emission and environmental gas detection.Key words:laser absorption spectroscopy,accurate measurement,non-uniformity,composite non-point sources基于激光检测提高复合面源排放测量精度研究唐七星1,2*,张玉钧1*,何莹1,王立明1,李梦琪1,尤坤1,李潇毅1,陈东3,刘文清1(1.中国科学院环境光学与技术重点实验室,安徽光学精密机械研究所,安徽合肥230031;2.安徽农业大学,安徽合肥230061;3.合肥工业大学,安徽合肥230009)摘要:在面源气体排放的测量过程中,不可避免地受到相邻田地气体排放干扰,又受到环境扰动的影响,影响气体检测的准确性。
Determination of Organic Emission of Non-metallic materials from vehicles Interior VDA 277Contents1. General2. Test preparations3. Testing sets and conditions4. Attempt realization5. Calibration6. Evaluation1. General1.1 PurposesAccording to this test method, the organic emission from non-metallic materials is determined with direct or indirect influence for the passenger's cell of automobiles stand. It measure the emission potential of a material, the sum of all release values of the emitted substances with gaschromatograph and detection with a Flame ionization detector. The test operated by means of steam space analysis (Head Space technology) at temperature of 120ºC.1.2 RequirementsThe accompanying sample, the respective requirements as well as special method is of the suitable specification to take drawing or the like.If materials are composed of different components, a separate check is required for every single material.2. Test preparationsTransport and storage of the tests has to occur in an aluminum coated Polyethylenbeutel. The sampling has immediately after incoming goods or in a condition, which corresponds to this, to take place. The times of the incoming goods and the sampling are to be labelled. There is no conditioning of the test as a rule. Except of it are physical materials (cotton, wood, leather, wool). These materials are dried before the weighted sample in the chopped up state for 24 hours with calcium chloride (CaCl2).The test is to be inferred at the agreed place about the whole test cross section from the component. The samples are chopped up in pieces with a weight more than 10 mg and less than 25 mg, without the test warms itself up. If necessary, another test preparations can be also undertaken and such deviation from standard should be mentioned in the final result.The test amount to be rocked to sleep is directed after the size of the Head Space of little glass whose least contents 5 ml must amount. Per 10 ml little glass volumes are to be rocked to sleep 1.000 g +0.001 g (i.e. maximum content error 0.1%) test material. Metal are to be removed before weighting. When metal parts are liable to organic substances, for example, varnish, pastes, should be separated mechanically at first and then to rock to sleep.The weighted test particles become in a Head Space little glasses (least 3 little glasses per test), then air-tighted with the use of a septums with the Teflon coating which points to the interior of the little glass.3. Testing sets and conditions3.1 testing setsGaschromatograph for capillary column with Head Space Tester, flame ionization detector (FID) and calculator/ Integrator.WCOT-capillary dividing column with a separating phase from 100% Polyethylene glycol (so-called Wax type, e.g., DBWax, Carbowax...)0.25 mm I.D., 0.25 µm film thickness, 30-m lengthAnalytic balance, in the order of 0.1 mgMicroliter syringe, 5 µl, sample in vitreous body3.2 measuring conditionsStove temperature program GC: 3 minutes isotherm at 50ºCHeating at 200ºC with a rate of 12 K / min4 minutes isotherm at 200ºCInjector temperature: 200ºCDetector temperature: 250ºCSplit ratio: approx. 1: 20Carrier gas: heliumMiddle carrier gas speed: approx. 22-27 cm /s.time smaller than 16 minutes.4. Attempt realizationThe little glasses are tempered to the enrichment of the substances in the air standing about the test directly before the measurement 5 hours + 5 minutes with 120 + 1 ºC in the Head Space Tester and are analyzed directly afterwards. At least 3 tests are to be analyzed in each case.The control value is determined by average signal value of at least 3 measurements with empty test little glasses.The dosage must run off in all analyses of the tests, the control value and the calibration solution identically and reproduceable.The separating column must be brought to the bake once per week for 15 minutes at maximum temperature.5. CalibrationFor the quantitative determination of the total carbon emission as well as the amount of special single substances, calibration curve are compared with the method of the external standard.For the total carbon emission, acetone serves as a calibration substance, for the single substances and the respective materials.After installation of a new column and after changes in the device a basic calibration with 7 calibration concentration is to be carried out. In addition, a control calibration with at least 3 concentrations has to be carried out at least every 4 weeks.For basic calibration, 7 calibration solutions of acetone with concentration of 0.1/0.5/1/5/10/50/100grams of acetone in per liter of n-Butanol is made. For the control calibration solution at least three concentrations 0.5/5/50 grams of acetone per liter are required. It is to be guaranteed that in the used n-Butanol show no Peaks at the same time as acetone.For the single substances, calibration solution are to be produced in the same concentration like for the acetone-control calibration and in each case, a solvent is to be used which shows no peaks with the retention time of the relevant single substance and boiling point lies under 120ºC.All substances used for the calibration procedure should be checked at least each year to show quality.With the calibration measurement with one 5 μl - syringe in each case 2 μl + 0.02 μl (i.e. maximum injection error 1%) per 10 ml little glass volume in an empty, unlocked Head Space little glasses squirted. Specific attention should be paid to the fact that no air bubbles are in the cylinder when drawing the syringe. The little glass is closed directly after as under 2 described.The calibrated sample is kept at a moderate temperature for 1 hour with 120ºC in the Head space Tester and then analyzed in accordance with the general test specification, whereby the temperature program of the gaschromatograph can be broken off after elution of the solvent. At least 3 measurements are to be carried out for each calibration solution. With the concentrations of the calibration solutions (in g/l), determined for the respective calibration substance, a straight line can be drawn, whose upward gradient represents the calibration factor k (k(G) for the least squares to take place. The coefficient of correlation K must be thereby larger than 0,995.)6. EvaluationFrom the data of the gaschromatogram the total peak area as well as the surfaces of the peaks belonging to the single substance indicated in the design and/or TL must have to be extracted. For the computation of the total peak area only peaks are consulted,-their height greater than 10% of the triple value of the baseline isAnd-their area greater than 10% of the area of the Acetone peaks in the calibration solution with the concentration 0.5 g/l isThe detection limit of the analysis procedure must deliver a peak area and a peak height which is in each case smaller than 10% of the respective value which will receive for acetone in analysis of a calibration solution concentration of 0.5 g/l acetone.The desired emission values result from the results of measurement as follow:Total carbon emission E G:Ascertained from the total peak area which has arisen in the analysis of the tests, and the calibration factor k (G) from the acetone calibrationE G= Total peak area – Peak area of control x 2 x 0.6204K (G)The unit " µg carbon per g of sample ".The factor two is originated from the relation of " µg of sample " and arises by the fact that 1 g of sample, 2 µl calibration solution are given in 10 ml little glass.The factor 0.6204 shows the weight proportion of carbon in acetone.Single material – Emission Ei:Ascertained from the Peak area which has arisen in the analysis of the tests for the single material in request i, and the calibration factor k (i) from the single material calibrationEi = Peak area of the single material i x 2K (i)The unit " µg substance i per g of sample ".The factor two is originated from the relation of " g of sample " and arises by the fact that for 1 g of sample, 2 µl calibration solution are given in 10 ml little glass.For the results of 3 measurements of a part, not the average value, but all 3 measured values must fulfill the requirement. This is necessary to guarantee that at all places of the construction meet the requirements.。
detection limit探测极限"Detection Limit: Unmasking the Boundaries of Scientific Exploration"Introduction:In the vast realm of scientific investigation, one often encounters the term "detection limit." This intriguing concept refers to the lowest level of concentration, measurement, or phenomenon that can be reliably identified by an instrument or method. Detection limits play a crucial role in a variety of scientific disciplines, including chemistry, biology, environmental sciences, and physics. In this article, we will delve into the underlying principles of detection limits and explore the step-by-step process of their determination.1. Defining the Detection Limit:The detection limit, also known as the limit of detection (LOD), is the smallest quantity of the analyte or phenomenon that can be distinguished from the background noise or non-specific signal. It marks the threshold below which reliable measurements become challenging. Detection limits are often reported with a specified confidence level, ensuring scientifically rigorous outcomes.2. Significance of Detection Limits:Accurate determination of detection limits is paramount in various scientific applications. From environmental monitoring to pharmaceutical research, detection limits allow scientists to differentiate between trace amounts of substances, quantitatively analyze analytes, and set boundaries for safety regulations. These limits aid in tracking pollution levels, identifying disease markers, ensuring product quality, and much more.3. Factors Affecting Detection Limits:Several key factors directly impact the determination and improvement of detection limits. These factors include instrument specifications, background noise levels, analyte concentration, sample matrix, detection technique, and data analysis methods. Understanding these factors and their interactions is vital for optimizing detection limits.4. Methodology for Determining Detection Limits:The process of determining detection limits involves a systematic approach to quantify the lowest detectable concentration or value. Here is a step-by-step exploration of this methodology:a. Selecting the Analyte and Background Matrix:The first step is to identify the analyte of interest and the medium in which it is present. Different analytes and matrices impose varying challenges and may require specific approaches for successful detection.b. Instrument Calibration:Calibrating the instrument or method to be used is essential before determining the detection limit. This includes obtaining a range of known standards with concentrations both above and below the expected detection limit. By analyzing these calibration standards, a calibration curve can be constructed.c. Determining the Signal-to-Noise Ratio:The signal-to-noise ratio (S/N) is calculated by comparing the measured signal from the analyte to the background noise level. A higher S/N ratio indicates a more favorable signal strength relative to noise, hence lowering the detection limit.d. Performing Replicate Measurements:To ensure robustness and reliability, multiple replicatemeasurements at different analyte concentrations or values should be performed. This allows for statistical analysis, enhancing the accuracy of the detection limit determination.e. Statistical Analysis:Using statistical tools, such as regression analysis or hypothesis testing, the obtained measurements and their uncertainties are analyzed. These statistical calculations aid in establishing rigorous detection limits with appropriate confidence levels.5. Improving Detection Limits:Once the detection limit is determined, researchers strive to lower it to enhance the efficiency and sensitivity of their methods. Strategies for improving detection limits include optimizing sample preparation techniques, reducing background noise, enhancing signal amplification, employing advanced instruments, and utilizing cutting-edge data analysis techniques.Conclusion:Detection limits are essential boundaries that enable scientists to explore the minute details of their subjects of interest. Byunderstanding the underlying principles and employing astep-by-step methodology for their determination, researchers continue to unravel the mysteries of the natural world and contribute to scientific progress. The pursuit of lower detection limits challenges scientists to refine their techniques, pushing the boundaries of scientific exploration further with each breakthrough.。
detection词根词缀1. 单词概述单词:detection含义:它主要表示“察觉”“发觉”“侦查”的意思。
这个词在很多场景中都能用到呢,比如说在安全领域,检测是否有危险物品或者非法入侵就会用到detection;在医疗方面,检测疾病也会用到这个词,像癌症的早期检测(early detection of cancer)。
2. 词根词缀解析词根:tect,来源于拉丁语,表示“覆盖”“掩盖”的意思。
前缀de - 有“向下”“除去”等含义。
合起来,detection就有把掩盖的东西去除从而发现、察觉的感觉。
3. 应用短文与场景应用短文1:英文:I was at the airport last week with my friend, Tom. Man, airports are such busy places! There were people rushing around everywhere. We were waiting in line for our flight when all of a sudden, there was amotion. A security guard was shouting, "We've got a detection issue here!" Tom looked at me with wide eyes and said, "What do you think it could be? Maybe someone's trying to smuggle something?" I shrugged and replied, "I don't know, but with all this high - tech detection equipment they have nowadays, I'm sure they'll figure it out soon." We watched as they brought out these really cool - looking detection devices. It was like something out of a spy movie. They were waving them over people's bags and bodies. I thought to myself, "Detection really is an important part of keeping everyone safe here." After a while, they found out that it was just a false alarm. Some guy had accidentally left his phone charger in a really strange place in his bag, and it had set off the metal detector. Tom laughed and said, "Well, better safe than sorry, right? I'm glad they have such strict detection procedures."中文翻译:上周我和我的朋友汤姆在机场。
[Ontology]Physical sciences / Astronomy and planetary science / Astronomy and astrophysics / Stars [URI /639/33/34/867]Physical sciences / Astronomy and planetary science / Astronomy and astrophysics / High-energy astrophysics [URI /639/33/34/864][Subject strapline]Supernovae[Title]The supernova in a bubble[Standfirst: 230 characters including spaces]The story behind the supernova remnant RCW 86 might be one of the most wondrous ever told.[Author]Peter NugentAstronomers have long sought the progenitor systems of supernovae, since such discoveries provide the only direct checks of our understanding of the death throes of stellar evolution. Much of the work in this field over the past decade and a half has focused its attention on serendipitous pre-explosion imaging garnered by ground and space-based observations of nearby galaxies. With these data, astronomers have been able to place stringent constraints on the progenitor masses of a variety of hydrogen-rich Type II core-collapse supernovae (cc-SNe), upper limits on the mass of several more stripped-mass Type Ib/c supernovae as well as excellent upper limits on the companion stars for a couple of nearby Type Ia supernovae (1,2). Furthermore, in just the past few years, high-cadence optical surveys have provided several supernova discoveries within hours of their explosion. This has allowed astronomers a brief window (often less than 24 hours) to see the effects of the supernova explosion’s shock-breakout on the surrounding environment before the rapidly-expanding ejecta completely overrun it. From such observations links have now been made between Wolf-Rayet-like winds and cc-SNe whose progenitors have suffered significant mass loss (3). These early observations have also been used to detect the potential signature of the ejecta of a thermonuclear (Type Ia) supernova slamming into, and shocking, its binary companion star (4).Writing in Nature Astronomy, Vasilii Gvaramadze and collaborators tackle this problem from the other direction, not by looking at what happened before or during the supernova explosion, but rather at what was left behind hundreds of years later in the supernova’s remnant. They have turned their attention to the supernova remnant RCW 86, located over 8,000 light years away and found between the constellations of Circinus and Centaurus. RCW 86 has had a long and rather convoluted history, with claims of it being the result of both a thermonuclear andcore-collapse supernova. Associations with 10 nearby massive B-type stars, alongwith the fact that the supernova exploded into a “cavity”, perhaps through a massive star’s wind prior to explosion, favour the core-collapse progenitor (5). Recentstudies focused on the X-ray and IR observations of the remnant, showing high iron abundances and strong hydrogen emission from non-radiative shocks, favour the thermonuclear origin (6). There is also a tentative association with the supernova seen by Chinese astronomers in 185 AD (SN 185).What Gvaramadze et al. have added to the story is the detection of a solar-type star strongly polluted with calcium and iron among other elements. It is coincident with a candidate neutron star (NS) within the remnant RCW 86 (see Figure). Moreover, from radial velocity measurements, the G star is in a binary system. This is suggestive of a massive star going supernova, leaving behind a NS and the supernova ejecta polluting a companion. The G star/NS binary is offset from the centre of the RCW 86 remnant, in its own, smaller bubble. They believe that the supernova progenitor was a massive, moving star, which exploded near the edge of its wind bubble and lost most of its initial mass due to common-envelope evolution with this G star. It is a two-step process to manufacture this remnant: the first requiring mass loss during the main-sequence phase creating a large-scale bubble in the interstellar medium, and a second mass loss episode during the red supergiant phase producing a slow, dense wind creating a bow-shock-like structure at the edge of the bubble. They further posit that due to the factor of 6 enhancement of calcium in the G star’s spectrum, that perhaps this supernova is related to the rare calcium-rich subclass. Ca-rich supernovae are a recently identified class of explosions, which are relatively faint at peak and whose brightness drops rapidly. After a few months their spectra are dominated by calcium in emission – hence the moniker. The origins of these supernovae are up for debate. By and large they are associated with early-type galaxies, many of which show signs of recent merger activity, and are often separated by scores of kiloparsecs from the putative host (7). Proposed progenitor scenarios include the merger of a NS and a white dwarf (WD), WD-WD mergers and sub-Chandrasekhar thermonuclear explosions (8,9). Yet this link to Ca-rich supernovae is a bit murky as there are likely viable cc-SNe that could produce the observed abundances given their uncertainties. Overall the argument of Gvaramadze and collaborators is not completely convincing since much of it rests on the unlikely finding of such an odd G star next to a potential neutron star – but it is possible, and it is quite tantalizing.While some may see this work as just adding to the pantheon of potential progenitors for this system, a smoking gun can, and likely will, be found in the next few years that could settle this debate once and for all. It will come to us through an indirect path in the form of a light echo. Just as sound can reflect off the face of a cliff, the light from a nearby supernova can reflect off a sheet of cosmic dust. And if the dust is situated several hundred light years away from the explosion, the light echo itself will be delayed by hundreds of years before it reaches us – giving us the opportunity to see the explosion as it happened – a cosmic DVR. With the advent ofwide-field optical surveys, several of these light echoes have been discovered in thepast few decades. Coupled with 8–10m-class telescopes, spectra of the echoes have been taken that reveal the underlying supernova subclass and, if there are echoescoming from a number of different directions, the three-dimensional nature of the supernova explosion itself (10). Such a discovery for RCW 86 would go a long way to clearing up this mystery and determining if this thermonuclear supernova bubble will burst.Peter Nugent is in the Computational Research Division of the Lawrence Berkeley National Laboratory, M.S. 50B-4206, 1 Cyclotron Road, Berkeley, Calfornia 94720-8139, USA.email:****************References:1. Smartt, S. J. Pub. Astron. Soc. Austrailia. 32, 16-38 (2015).2. Li, W. et al. Nature 480, 348-350 (2011).3. Gal-Yam, A. et al. Nature 509, 471-474 (2014).4. Cao, Y. et al. Nature 521, 328-331 (2015).5. Vink, J. et al. Astron. Astrophys. 328, 628-633 (1997).6. Williams, B. J. et al. Astrophys J. 741, 96-111 (2011).7. Foley, R. J. Mon. Not. R. Astron. Soc. 452, 2463-2478 (2015).8. Lyman, J. D. et al. Mon. Not. R. Astron. Soc. 444, 2157-2166 (2014).9. Sullivan, M. et al. Astrophys J. 732, 118-131 (2011).10. Rest, A. & Welch, D. L. Pub. Astron. Soc. Austrailia. 29, 466-481 (2012).Figure 1 | Title. Text.。
时间分辨荧光寿命英文缩写Time-resolved fluorescence lifetime (TRFL) is a technique used in spectroscopy to measure the decay time of fluorescence after excitation. It provides valuable information about the molecular environment and interactions of fluorophores. TRFL measurements are commonly used in various scientific fields, such as biology, chemistry, material science, and medical diagnostics.The most commonly used method for TRFL measurements is time-correlated single photon counting (TCSPC). In TCSPC, a pulsed laser is used to excite the sample, and the resulting fluorescence emission is collected and detected using a photon-counting detector. The detector records the arrival time of each emitted photon relative to the excitation pulse, and this information is used to build a decay curve. The decay curve represents the fluorescence intensity as a function of time, and the fluorescence lifetime can be derived from the decay curve.The fluorescence lifetime is the average time that a fluorophore spends in the excited state before returning to the ground state. It is determined by various factors, including the molecular structure, solvent environment, and the presence of other molecules that can quench or enhance the fluorescence. By measuring the fluorescence lifetime, researchers can obtain valuable information about the structure and dynamics of molecules, as well as their interactions with other molecules.TRFL measurements have been widely used in the study of biological systems. For example, in fluorescence microscopy, TRFL can be used to differentiate between different fluorophoresin a sample based on their fluorescence lifetimes. This allows for the simultaneous detection of multiple fluorophores with overlapping emission spectra. TRFL can also be used to study protein-protein interactions, DNA-protein interactions, and membrane dynamics in living cells.In the field of chemistry, TRFL can be used to study the kinetics and mechanisms of chemical reactions. By monitoring changes in fluorescence lifetime during a reaction, researchers can gain insights into reaction intermediates and transition states. TRFL can also be used to study the properties of nanomaterials, such as quantum dots and nanoparticles, as well as the behavior of dyes and sensors.In medical diagnostics, TRFL has been used in various applications, such as drug discovery, clinical diagnostics, and imaging. For example, TRFL-based assays can be used to detect and quantify specific biomarkers in clinical samples, such as blood or urine, for disease diagnosis and monitoring. TRFL imaging techniques, such as fluorescence lifetime imaging microscopy (FLIM), can provide high-resolution images of biological samples, allowing for the visualization of molecular interactions and spatial localization of fluorophores.In summary, TRFL is a powerful technique for studying the fluorescence properties of molecules. It provides valuable information about the molecular environment, interactions, and dynamics. TRFL has applications in various scientific fields, including biology, chemistry, material science, and medicaldiagnostics, and it continues to contribute to advancements in these areas.。
a r X i v :a s t r o -p h /0703616v 1 23 M a r 2007Detection of [Ne ii ]Emission from Young Circumstellar DisksI.Pascucci 1,D.Hollenbach 2,J.Najita 3,J.Muzerolle 1,U.Gorti 4,G.J.Herczeg 5,L.A.Hillenbrand 5,J.S.Kim 1,J.M.Carpenter 5M.R.Meyer 1,E.E.Mamajek 6,J.Bouwman 7ABSTRACTWe report the detection of [Ne ii ]emission at 12.81µm in four out of the six optically thick dust disks observed as part of the FEPS Spitzer Legacy program.In addition,we detect a H i (7-6)emission line at 12.37µm from the source RX J1852.3-3700.Detections of [Ne ii ]lines are favored by low mid–infrared excess emission.Both stellar X–rays and extreme UV (EUV)photons can sufficiently ionize the disk surface to reproduce the observed line fluxes,suggesting that emission from Ne +originates in the hot disk atmosphere.On the other hand,the H i (7-6)line is not associated with the gas in the disk surface and magnetospheric accretion flows can account for at most ∼30%of the observed flux.We conclude that accretion shock regions and/or the stellar corona could contribute to most of the H i (7-6)emission.Finally,we discuss the observations necessary to identify whether stellar X–rays or EUV photons are the dominant ionization mechanism for Ne atoms.Because the observed [Ne ii ]emission probes very small amounts of gas in the disk surface (∼10−6M J )we suggest using this gas line to determine the presence or absence of gas in more evolved circumstellar disks.Subject headings:line:identification –circumstellar matter –planetary systems:protoplanetary disks –infrared:stars –stars:RX J1111.7-7620,PDS 66,HD 143006,[PZ99]J161411.0-230536,RX J1842.9-3532,RX J1852.3-37001.IntroductionYoung stars are often surrounded by gas and dust disks that may succeed in forming planets.The properties and evolution of their dust and gas components are key to understanding planet for-mation and the diversity of extrasolar planetary systems.Circumstellar dust has been extensively stud-ied in young and old disks since the IRAS mis-sion.Grain growth has been identified in disksHere,we present high-resolution Spitzer spec-tra for the six FEPS targets with excess emis-sion beginning at or shortward of the8µm IRAC band.Their IRAC colors are consistent with those of accreting classical T Tauri stars (Silverstone et al.2006)suggesting that these stars are surrounded by optically thick dust disks. We report the detection of the H i(7–6)line at 12.37µm in one system and of the[Ne ii]line at12.81µm in four systems(Sect. 3.1).Be-cause Ne atoms have a large ionization potential (21.6eV),the detection of[Ne ii]lines is of par-ticular interest to assess the role of stellar X–ray and EUV(hν>13.6eV)photons on the disk chemistry and to explore the conditions for disk photoevaporation(Glassgold,Najita&Igea2007; Gorti&Hollenbach2007).We discuss in detail predictions from the proposed X–ray and EUV models and future observations that will be able to identify the dominant ionization mechanism (Sect.4and Sect.5).Since both modelsfind that the[Ne ii]line probes small amounts of gas on the surface of circumstellar disks,we also suggest using this tracer to place stringent constraints on the presence or absence of gas in more evolved disks.2.Observations and Data ReductionThe general properties of the328stars in the FEPS sample are described in Meyer et al.(2006). We summarize in Table1the main properties of the six FEPS sources surrounded by optically thick dust disks.In Cols.4,5,and6we give the star spectral types(SpTy),distances(d),and ages (Age).References for these quantities are pro-vided in Col.7.The stellar effective temperatures (T eff),visual extinctions(A V),and bolometric lu-minosities(L⋆)are listed in Cols.8,9,and10. The last column summarizes the source X-ray lu-minosities(L X).To compute the X–ray luminosities we used the ROSAT PSPC All–Sky Survey count–rates and HR1hardness ratios(Alcal´a et al.1997; Voges et al.1999,2000)following Fleming et al. (1995),and adopting the distances in Table1. These X-ray luminosities are representative for the energy band0.1–2.4keV(or120–5˚A).The er-rors in L X include the uncertainties in the count–rates,HR1,and distances.Note however that the intrinsic variability of log(L x)due to stellar ac-tivity is larger than the quoted uncertainty and amounts to at least a few tenths of a dex(e.g. Marino et al.2003).Our X–ray luminosities agree with values from the literature(Alcal´a et al.1997 for source1;Mamajek et al.2002for source2; Sciortino et al.1998for source3;Neuh¨a user et al. 2000for sources5and6).Because source4ap-pears extended in the ROSAT PSPC image,we also searched for an independent measurement of its X–rayflux.Its count–rates from the XMM–Newton1MOS1and MOS2cameras in the0.2–2keV bandpass convert to log(L x)=30.8erg/s. Since an increase of0.26dex in luminosity could be simply due to stellar activity,we prefer to adopt the luminosity from ROSAT for consistency with the other sources.Among the sources listed in Table1,HD143006 is the only one that was included in the FEPS pro-gram as part of the gas detection experiment be-ing a known dust disk from IRAS(Sylvester et al. 1996).The otherfive dust disks have been re-cently identified by our group from IRAC/Spitzer photometry(Silverstone et al.2006).The spec-tral energy distributions of thesefive systems,in-cluding photometry from IRAC and MIPS as well as IRS low–resolution spectra,are presented in Silverstone et al.(2006).Hillenbrand et al.in prep.show that single temperature blackbodyfits to the33and70µm data cannot account for the excess emission at shorter wavelengths in any of the six sources in Table1,indicating the pres-ence of warm inner disk material.These optically thick dust disks are also the only six FEPS sources exhibiting dust features in the Spitzer/IRS low–resolution spectra.Bouwman et al.(2007)present a detailed analysis of their mineralogy andfind that RX J1842.9-3532is surrounded by an almost primordial disk(flared geometry and1µm–sized grains)while[PZ99]J161411.0-230536has the most processed disk(close toflat geometry and large5µm grains).In Sect.2.1we describe the observations and data reduction of the high–resolution infrared spectra.We complemented the Spitzer data with optical spectra(Sect.2.2)that are used to esti-mate mass accretion rates(Sect.3.2).2.1.High–resolution IRS SpectraSpitzer/IRS high–resolution spectra for the6FEPS optically thick dust disks were obtained be-tween August2004and September2005.Observa-tions were done in the Fixed Cluster–Offsets modewith two nod positions on–source(located at1/3and2/3of the slit length)and two additional skymeasurements(1′east of the nod1and nod2posi-tions)acquired just after the on–source exposures.We used these sky exposures to remove the in-frared background and reduce the number of roguepixels as described in Pascucci et al.(2006).ThePCRS or the IRS Peak–up options were used toplace and hold the targets in the spectrograph slitwith positional uncertainties always better than1′′(1sigma radial).Exposure times were cho-sen to detect a5%line–to–continuum ratio witha signal–to–noise of5(see Table2).In the fol-lowing we focus on the reduction and analysis ofthe SH module(9.9–19.6µm)where we detectedgas lines in four out of six targets.No gas linesare detected in the wavelength range18.7–37.2µmthat is covered by the LH module.The SH mod-ule is a cross–dispersed echelle spectrograph witha resolving power of∼650in the spectral rangefrom9.9–19.6µm,corresponding to a spectral res-olution of0.015µm around10µm.The detectorhas a plate scale of2.3′′/pixel and the slit aperturehas a size of2×5pixels,thus covering a region of∼1600×700AU around a star at140pc.Data reduction was carried out as in Pascucci et al.(2006)starting from the Spitzer Science Center(SSC)S13.2.0droop products.Wefixed pixelsmarked bad in the bmaskfiles withflag valueequal to29or larger,thus including anomalouspixels due to cosmic–ray saturation early in theintegration,or preflagged as unresponsive.Wealso inspected visually all the SH exposures tocatch additional rogue pixels and found less than5per frame.These bad and rogue pixels were cor-rected using the SSC irsclean package as explainedin Pascucci et al.(2006).Weflux calibrated the extracted spectra usingnine independent observations(over four differ-ent Spitzer campaigns,from C21to C24)of thebright standard starξDra and the MARCS stel-lar atmosphere model degraded to the spectro-graph’s resolution and sampling2.The dispersion3/legacy/fepshistory.htmlTable2Log of the IRS short-wavelength high-resolution observations.Source AOR Key SH Peak-uptime×ncycles modelight using custom routines in IDL,following themain steps described in White et al.(2006).The spectrum of RX J1111.7-7620was ac-quired in March2003with the MIKE echellespectrograph on the Magellan Clay6.5–m tele-scope(Bernstein et al.2002).The star was ob-served in a360–second exposure with the MIKERed CCD in the standard setup with the0.35′′slit,and2–pixel resolution of R≃36,000coveringthe wavelength range4800–8940˚A.The data werereduced using the MIKE Redux IDL package4.Finally,the spectrum of PDS66was acquiredin April2002with the echelle spectrograph on theCTIO4meter Blanco telescope.We used the31.6red long echelle grating covering the wavelengthrange between3,000–10,000˚A and a0.′′8×3.′′3slitwith a2–pixel resolution of R≃45,000.The ex-posure time on–source was120seconds.Forthe data reduction we used the IRAF pack-ages quadred/echelle that can treat multiamplifierechelle data.3.ResultsIn Sect.3.1we present the gas line detectionsfrom the Spitzer spectra of the six FEPS opticallythick dust disks.We also compute mass accretionrates from the Balmer emission profiles(Sect.3.2)and use them in Sect.4to search for correlationswith theflux of the detected infrared lines.3.1.Fluxes of Infrared Gas LinesWe report the detection of[Ne ii]emission at12.81µm in four out of the six targets and theadditional detection of H i(7–6)at12.37µm inRX J1852.3-3700(see Fig.1).For these detec-5The resolving power of the SH module is R∼650corre-sponding to∼460km/s.RXJ185212.212.412.612.813.0λ [µm]2030405060F ν [m J y ]RXJ184212.212.412.612.813.0λ [µm]80100120140160RXJ111112.212.412.612.813.0λ [µm]120140160180200F ν [m J y ]PZ99_J16141112.212.412.612.813.0λ [µm]300320340360380400HD14300612.212.412.612.813.0λ [µm]600700800900F ν [m J y ]PDS6612.212.412.612.813.0λ [µm]600700800900H I (7-6)H I (7-6)[N e I I ][N e I I ]Fig.1.—Expanded view of the wavelength regions around the H i (7–6)and [Ne ii ]emission lines.On top of the stellar and dust continuum we overplot the best Gaussian fits to the data (red dashed–lines)and the hypothetical 3σupper limits (light blue dot–dashed lines)reported in Table 3.In the case of PDS 66,we might have detected [Ne ii ]emission at a level of ∼2σ(Flux ∼1.4×10−14erg s −1cm −2).However,due to the faintness of the emission we cannot confirm its presence in both nod positions and therefore prefer to report a 3σupper limit in Table 3.RXJ185215.015.215.415.615.816.0λ [µm]606570758085F ν [m J y ]RXJ184215.015.215.415.615.816.0λ [µm]100120140160180RXJ111115.015.215.415.615.816.0λ [µm]150160170180190200F ν [m J y ]PZ99_J16141115.015.215.415.615.816.0λ [µm]300320340360380400HD14300615.015.215.415.615.816.0λ [µm]100011001200130014001500F ν [m J y ]PDS6615.015.215.415.615.816.0λ [µm]800900100011001200[N e I I I ][N e I I I ]Fig.2.—Expanded view of the wavelength regions around the [Ne iii ]line at 15.55µm.On top of the stellar and dust continuum we overplot the hypothetical 3σupper limits (light blue dot–dashed lines)reported in Table 3.Table 3Line fluxes and upper limits (3σ)from the IRS/Spitzer spectra.SourceFlux(H i )Flux([Ne ii ])Flux([Ne iii ])[10−15erg s −1cm −2][10−15erg s −1cm −2][10−15erg s −1cm −2]Note.—The wavelengths for the H i (7-6),[Ne ii ],and [Ne iii ]lines are 12.37,12.81,and 15.55µm respectively.The 1σerrors on the detections are calculated from the RMS of the observations minus model fit.2001;Kurosawa et al.2006).The UV/optical con-tinuum excess emission is the most common and direct measure of mass accretion rates(˙M⋆).How-ever,in many instances,this excess is too weak to be measured,and other methods such as model-ing Balmer emission profiles are necessary.This is particularly true for objects with predominately low accretion rates,such as older5–10Myr TTSs (e.g.Muzerolle et al.2000;Lawson et al.2004)in the same age range as our sample.Many diagnostics in our spectra suggest low ac-cretion rates in comparison to values typical of younger TTSs such as in Taurus:the lack of opti-cal continuum veiling(continuum excess over pho-tosphericflux<0.1),weak or absent mass loss signatures such as[O i]λ6300˚A emission,and the lack of broad emission components in the Na D doublet and Ca ii triplet lines.The Hαand Hβemission profiles,shown in Figures3and 4,are in most cases qualitatively suggestive of weak accretion.One object,RX J1842.9-3532,ex-hibits blueshifted absorption indicative of signifi-cant mass loss,and two objects exhibit redshifted absorption components in Hα([PZ99]J161411.0-230536and HD143006).Given the spectral types of these stars,the lack of optical veiling im-plies an upper limit of˙M⋆ 10−8M⊙yr−1(see Calvet et al.2004).We followed the procedures outlined in detail in Muzerolle et al.(2001)to model the Balmer line profiles and thus estimate mass accretion rates for our targets.Although the paper by Muzerolle et al.(2001)focused on low–mass stars with late K and M spectral types,accretion diag-nostics such as UV excess and Paβ(Calvet et al. 2004,Natta et al.2006)indicate that magneto-spheric model assumptions can be extended to stars with early K and G spectral types like our targets.We adopted stellar parameters based on the empirically–derived quantities in Table1.Gas temperatures were set roughly to10,000K fol-lowing the constraints derived in Muzerolle et al. (2001).Note that for the density regime appropri-ate for these particular objects,the gas is already nearly fully ionized and larger gas temperatures will not result in significantly different line emis-sion.The magnetosphere size/width was set to afiducial value(between2.2–3R⋆),lacking any observable constraints.This is the largest source of uncertainty in constraining the accretion rate;however,a plausible range of values results in no more than a factor of3–5range in accretion rates that can reproduce the observed line profiles.We further included rotation,using the treatment of Muzerolle et al.(2001),since rotation rates typi-cal of our objects can have an observable effect on the line profiles near the line center.The adopted stellar equatorial velocities,based on the observed v sin(i)values,are given in Table4.Finally,the model inclination angle and mass accretion rate are varied to reproduce the wings,width,and peak of the observed lines.The best matches are shown in Figs.3and4and the inferred inclination angles (i)and mass accretion rates(˙M⋆)are summarized in Table4.Note that˙M⋆ 5×10−11M⊙yr−1 produce negligible Hαemission for our sources and thus represent lower limits for their accretion rates.Given the magnetospheric model param-eters in Table4,we also compute the predicted flux in the H i(7–6)transition(last column of the table).The models reasonably account for the observed profiles,with a few exceptions.The Hαemission line of RX J1852.3-3700exhibits a narrow,sym-metric core that the models cannot reproduce.It is possible that there is a chromospheric emission component superposed on top of the broader ac-cretion component.For this to occur,a significant amount of the stellar surface must not be covered by the accretionflow(which would be consistent with the more pole-on orientation of the model). The models also cannot reproduce the blueshifted absorption components seen in both Hαand Hβprofiles of RX J1842.9-3532.A treatment of the wind is necessary to account for such features, which is beyond the scope of this work.How-ever,we note that the models still account for the overall emission profile,suggesting that the wind produces negligible emission.The derived mass accretion rates are all lower than the average value for1Myr–old T Tauri stars (Gullbring et al.1998;Calvet et al.2004)by fac-tors larger than10.Given the older ages of the stars in our sample,this may be consistent with a general decline in accretion rate with time as predicted by models of viscous disk evolution(e.g. Hartmann et al.1998;Muzerolle et al.2000).The predicted H i(7–6)emission for RX J1852.3-3700 contributes to at most∼30%of the observedvalue6,while predictedfluxes from the other sources are negligible or fall well below the3σupper limits we report in Table3.Thus,mag-netospheric accretion models argue against the H i(7–6)transition originating in accretionflows. Accretion shock regions,the stellar chromosphere, and the hot disk surface are other possible sources of emission.We discuss the contribution from the disk in the next Section and note that the possi-ble chromospheric emission component in the Hαprofile of RX J1852.3-3700could also contribute to the H i(7–6)line.4.Disk Atmosphere and[Ne ii]EmissionTwo-thirds of our optically thick dust disks present a[Ne ii]emission line at12.81µm.Where does the[Ne ii]emission originate?Recently Glassgold,Najita&Igea(2007)showed that stel-lar X-rays can partially ionize the gas in the disk atmosphere and produce detectable[Ne ii]lines. Alternatively,Hollenbach&Gorti in prep.sug-gest that extreme ultraviolet(EUV,hν>13.6eV) photons from the central star ionize the upper layer of circumstellar disks and create a kind of coronal H ii region producing detectable[Ne ii] emission.Although the two models rely on dif-ferent ionization mechanisms,they both predict that[Ne ii]emission originates from gas in a hot surface layer of circumstellar disks7.We can thus expect tofind some correlations between the ob-served[Ne ii]fluxes and the star/disk properties such as infrared excess emission,stellar UV or X–rayflux,and mass accretion rates.First we explore any correlation between the continuum emission in the vicinity of the[Ne ii] line and the[Ne ii]line luminosities(see Fig.5). Although there is no obvious trend between the plotted quantities,it is interesting that the four detections cluster in a narrow range of[Ne ii]line luminosities(differences less than a factor of2) and below400mJy of excess emission at13µm. The weaker mid–infrared continuum level(caused by an inner hole and/or grain growth)improves the line to continuum ratio in these relatively lowTable4Magnetospheric accretion model parameters and resulting mass accretion rates(˙M⋆).Source R∗V eq T max i log(˙M⋆)Predicted Flux(H i)[R⊙][km s−1][K][◦][M⊙yr−1][10−15erg s−1cm−2]Note.—T max is the maximum value of the adopted temperature distribution of the accretion column.All models are calculated for a solar mass star and for outer magnetospheric radii between2.2and3R∗.The last column gives the predictedflux in the H i(7–6)transition at12.37µm.Uncertainties in the massaccretion rates are no more than a factor of3–5.By varying˙M⋆by a factor of5the models give a rangeof H ifluxes within a factor of∼2.Fig. 3.—Observed and model Balmer line profiles(solid and dashed lines,respectively)for the sources RX J1852.3-3700,[PZ99]J161411.0-230536,and RX J1842.9-3532.Model parameters are listed in Table4.Fig. 4.—Observed and model Balmer line profiles(solid and dashed lines,respectively)for the sources HD143006,RX J1111.7-7620,and PDS66.Model parameters are listed in Table4.spectral resolution Spitzer observations and thus makes it more favorable to detect[Ne ii]emission lines.We also search for correlations with the disk structure,in particular with the diskflaring.The continuumflux emitted from the surface layer of the disk is proportional to the angle at which stel-lar radiation impinges onto the disk.This so–called grazing angle becomes proportional to the diskflaring at radial distances from solar–type stars 0.4AU(Chiang&Goldreich1997).Such distances are probed by dust emission at mid–infrared wavelengths.Thus,we can use the ratio offluxes at two different mid–infrared wavelengths to trace changes in the diskflaring.We chose as referenceflux that at5.5µm,which is the short-est wavelength covered by the IRS low–resolution modules,and computed theflux ratios at13,24 and33µm(see Fig.6).Largerflaring is indicated by higher ratios of long wavelength continuum to short wavelength continuumflux from the dust disk.Source RX J1852.3-3700is peculiar in having small excess at13µm and large excesses at24and 33µm.The SED of this object(Silverstone et al. 2006)is reminiscent of transition systems such as GM Aur and DM Tau(Calvet et al.2005).We do not see any obvious correlation between disk flaring and[Ne ii]line luminosities.Interestingly,wefind trends with the stellar X–ray luminosities(Fig.7)and with the mass ac-cretion rates from the Balmer profiles(Fig.8). Stellar X–ray luminosities are computed from the ROSAT All–Sky Survey count rates and hardness ratios(see Table1).We did not attempt to correct for the interstellar extinction because the X–ray spectrum of our targets is not well–known from the ROSAT observations alone.Nevertheless,the largest difference in visual extinction(0.7mag be-tween HD143006and RX J1852.3-3700)trans-lates into less than0.1dex difference in log(L X), well within the estimated errors and variations due to stellar activity.This indicates that any ob-served trend in our sample can be only marginally influenced by the correction in interstellar extinc-tion.The best(minimum chi–square)fit to the [Ne ii]detections in Fig.7gives the following cor-relation between the[Ne ii]and the X–ray lumi-nosity:L[Ne II]∝L+1.2(±0.7)XThe slope of the relation is not constrained butF 13/F 5.5F 24/F 5.527.828.028.228.428.628.8Log(L NeII ) [erg/s]F 33/F 5.5Fig. 6.—Possible correlations of [Ne ii ]line lu-minosities with the disk flaring.[Ne ii ]detectionsare filled symbols and right–most [Ne ii ]limits areopen symbols with left pointing arrows.The diskflaring is represented by the flux ratio at 13(upperpanel),24(middle panel),and 33µm (lower panel)over the reference flux at 5.5µm,that is the short-est wavelength covered by the IRS low–resolutionspectra.More flaring is indicated by higher ra-tios in the figure.There is no obvious correlationbetween disk flaring and [Ne ii ]emission.it is positive within 1.5σ.To further evaluate the likelihood of a positive correlation,we gen-erate 100normally–distributed points around the four [Ne ii ]detections and fit the data using six different linear regression methods described in Isobe et al.(1990).The analytical slopes as well the average slopes of 100random resampling of the data using bootstrap and jackknife techniques (Babu &Feigelson 1992;Feigelson &Babu 1992)are all positive.The Pearson correlation coeffi-cient is 0.24meaning that we can be confident of a positive correlation between L [Ne II]and L X at a 95%confidence level.We perform a similar anal-ysis to test the apparent anti–correlation between the [Ne ii ]luminosity and the mass accretion rate in Fig.8.The ordinary least–squares fit to the four [Ne ii ]detections results in:L [Ne II]∝˙M ⋆−0.45(±0.36)The slope of the relation is negative only within 1σ.The Monte Carlo approach in combination with the six regression methods also indicates a negative correlation at a 95%confidence level.In summary,we have evidence for a positive correlation between L [Ne II]and L X and a nega-tive correlation between L [Ne II]and ˙M ⋆.How-ever we cannot quantify the slopes of these rela-tions because of the small number of detections and of the large errorbars in the measured and es-timated quantities.It is also important to point out that source 5(RX J1842.9-3532)has a large weight in determining these trends being the tar-get with the most different X–ray luminosity and mass accretion rate.Note that if the 2σdetection from PDS 66is real it would confirm the posi-tive trend between [Ne ii ]luminosity and X–ray luminosity.A larger sample of sources spanning a wider range in X–ray luminosities and mass ac-cretion rates is necessary to constrain the slopes of the L [Ne II]–L X and L [Ne II]–˙M⋆relations.In the subsections below we discuss predictions fromthe X–ray and EUV models and compare them tothe measured [Ne ii ]fluxes and to the correlationspresented in this Section.4.1.Plausible Disk Origin for the Ne +emission According to the model proposed by Glassgold,Najita &Igea(2007),detectable [Ne ii ]emission can be pro-30.030.230.430.630.831.0Log(L X ) [erg/s]27.828.028.228.428.6L o g (L N e I I ) [e r g /s ]Fig.7.—Line luminosities (filled symbols)and upper limits (open symbols with downward arrows)for the[Ne ii ]transition versus the star X-ray luminosity as given in Table 1.The two open stars represent the two extreme thermal models from Glassgold,Najita &Igea (2007):the upper model is when mechanical heating (accretion)dominates (Xray-M),the lower model is when X–ray heating dominates (Xray).The ordinary least–squares fit to the four detections suggests a positive correlation between L [Ne II]and L X .duced by the atmosphere of a disk both ionized and heated by stellar X–rays(Glassgold,Najita&Igea 2004).Ne ions,primarily Ne+and Ne2+,are gen-erated through X–ray ionization and destroyed by charge exchange with atomic hydrogen and radia-tive recombination.Because the X–rays emittedby young stars have a characteristic energy similarto the K–edges of Ne and Ne+at∼0.9keV,theyare efficient in producing Ne ions.The warm disk surface region(T∼4000K)generated by X–ray irradiation extends out to large radii(∼20AU).As a result,fine structure transitions of Ne+ and Ne2+,which have excitation temperaturesof∼1000K,can be produced over a vertical col-umn of warm gas of1019−1020cm−2and overa large range of disk radii.These circumstances lead to a significantflux of[Ne ii]at12.81µm and [Ne iii]at15.55µm.For a typical T Tauri disk(D’Alessio et al. 1999)located at140pc,Glassgold,Najita&Igea (2007)predict that a stellar X–ray luminosity oflog(L X)=30.30erg s−1generates a[Ne ii]flux of 6.22×10−15erg s−1cm−2when accretion related processes are unimportant in heating the disk sur-face.The[Ne iii]flux is estimated to be approxi-mately10times lower.The X–ray luminosity as-sumed in the Glassgold et al.model is close to that of RX J1842.9-3532(see Table1and Fig.7) and the predicted[Ne ii]flux is similar(withina factor of1.5)to the value we report in Table3. Unfortunately,the upper limits on the[Ne iii]lines (see Table3)are not stringent enough to test the model predictions.In the model proposed by Hollenbach&Gorti (2007,in preparation),EUV photons from the stellar chromosphere(Alexander et al.2005)and/or from accretion(Matsuyama et al.2003;Herczeg et al. 2007)create an H ii–region like ionized layer onthe surface of young circumstellar disks.The EUV photons incident on the disk are mostly absorbed near the so–called”gravitational radius”(∼10AUfor a1M⊙star)where the local thermal speed ofthe104K ionized hydrogen nuclei is equal to the escape speed from the gravitational potential(e.g. Hollenbach et al.1994).The numerical model forthe EUV–heated disk surfaces includes a calcu-lation of the diffusefield due to hydrogen and helium recombinations,and ionized gas chemistry comprising photoionizations,recombinations,and charge exchange reactions(Hollenbach&Gorti 2007,in prep.).In the case of a soft EUV spec-trum(e.g.a blackbody at4×104K),photon luminosities of∼1041erg s−1produce a[Ne ii] line luminosity of∼10−6L⊙,which corresponds to aflux of2×10−15erg s−1cm−2from a source at140pc.Harder EUV spectra can produce more doubly ionized Ne in the disk atmosphere which may result in stronger[Ne iii]lines in comparison to the case of soft EUV spectra(Hollenbach& Gorti2007,in prep.).With the assumption that Ne atoms are ion-ized only by stellar EUV photons and that the sources have a soft EUV spectrum,one can use [Ne ii]lines as an indirect tool to estimate EUV fluxes8,which are unconstrained for the majority of the stars.The[Ne ii]fluxes we report in Ta-ble3convert to EUVfluxes between2.6×1041(for RX J1842.9-3532)and4.4×1041(for RX J1852.3-3700)photons s−1.Such ionizing rates seem plau-sible for∼5Myr old TTSs like our targets.For comparison Herczeg et al.(2007)calculate∼1041 ionizing photons s−1for the∼10Myr old TW Hya system while Alexander et al.(2005)estimate a wide range of ionizingfluxes∼1041−1044photon s−1for a sample offive classical T Tauri stars.The estimates from Alexander et al.(2005)are based on modeling UV emission lines such as C iv and have only an order of magnitude accuracy due to model uncertainties and more significanly to un-certainties in the reddening.Nevertheless,if X–rays contribute to ionize Ne atoms,as proposed by Glassgold,Najita&Igea(2007),our EUV es-timates from[Ne ii]lines can be only taken as upper limits.In summary,both the X–ray and the EUV mod-els can reproduce the observed[Ne ii]line lumi-nosities with star/disk properties that are plausi-ble for our targets.Can the same models explain the H i(7-6)flux from RX J1852.3-3700?Hollen-bach&Gorti estimate that L H I∼10−3L[Ne II]if all the H i(7–6)emission originates from the ion-ized disk surface.They show that if X–rays dom-inate the[Ne ii]emission,then the H i luminosity should be even lower because the gas is mostly neutral.This demonstrates that neither the EUV nor the X–ray models can account for the observed。