HokieFlincs_H2O-NaCl

l s u he H2O–NaCl Fluid inclusions the most common salt in ). Consequently, phase equili- VTX) for H2O–NaCl are often ric data from aqueous fluid natural aqueous electrolyte erature–composition (PVTX) advantages and disadvantages in FI research. The comprehensive models can be used as stand-alone internally consistent tools to analyze fluid PVTX properties, but they require iterative calcula- tions to interpret Tm–Th data, which can make data reduction time consuming. The FI-specific models compute FI properties (com- position, density, etc.) directly from Tm and/or Th (without iteration). However, no single model covers the complete range of PVTX conditions of interest in most FI studies. Owing to the piecemeal nature of the FI-specific models, inter- ann, rams le to ls for own, another FI are entered. As a result, entry of large FI datasets is time Contents lists available at SciVerse ScienceDirect .el Computers & Computers & Geosciences 49 (2012) 334–337 during microthermometry—namely, dissolution temperaturespilar@vt.edu (P. Lecumberri-Sanchez), rjb@vt.edu (R.J. Bodnar). consuming, and it is not possible to have all data for an analytical session saved to a single output file. The ideal computer model allows the user to input tempera- tures of phase changes commonly measured in the laboratory 0098-3004/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.cageo.2012.01.022 n Corresponding author: Tel.: þ1 540 231 8575; fax: þ1 540 231 3386. E-mail addresses: mjmaci@vt.edu (M. Steele-MacInnis), (dissolution temperature, Tm, and homogenization temperature, Th) as independent variables (e.g., Bodnar et al., 1989; Bodnar, 1994; Bodnar and Vityk, 1994). Both types of models have 2003). A drawback of some of these programs (e.g., Bakker, 2003; Driesner, 2007; Driesner and Heinrich, 2007) is that after results for one FI are computed, the program must be re-set before data for data from FI. Those models can be categorized as (1) comprehen- sive models (equations of state) that are not specifically designed to interpret FI data (e.g., Anderko and Pitzer, 1993; Driesner, 2007; Driesner and Heinrich, 2007); or (2) correlation equations designed specifically for FI research, with measurable quantities 2003; Bodnar et al., 1989; Brown, 1989; Brown and Hagem 1995; Driesner, 2007; Driesner and Heinrich, 2007). These prog have made the numerical models more accessible and applicab FI research. The programs provide powerful and adaptable too interpreting FI data and for theoretical modeling (Bakker and Br properties of H2O–NaCl have been well characterized by numer- ous experimental and theoretical studies, as summarized in Bodnar et al. (1985) and Bodnar (2003). Several numerical models have been developed to represent the PVTX properties of H2O–NaCl, facilitating interpretation of preting microthermometric data can be tedious, requiring contin- uous switching between the various models to obtain all the desired information. To circumvent this issue, several easy-to-use computer programs have been published that implement various models to interpret H2O–NaCl (and other) microthermometric data (Bakker, Isochores 1. Introduction Sodium chloride (NaCl) is often natural fluids (e.g., Fyfe et al., 1978 brium (PTX) and volumetric data (P used to interpret microthermomet inclusions (FI), and for modeling fluids. The pressure–volume–temp Microthermometry PVTX Short note HOKIEFLINCS_H2O-NACL: A Microsoft Exce microthermometric data from fluid incl of H2O–NaCl Matthew Steele-MacInnis n, Pilar Lecumberri-Sanc Department of Geosciences, Virginia Tech, Blacksburg, VA 24061, USA a r t i c l e i n f o Article history: Received 3 December 2011 Received in revised form 29 January 2012 Accepted 30 January 2012 Available online 6 February 2012 Keywords: journal homepage: www preadsheet for interpreting sions based on the PVTX properties z, Robert J. Bodnar sevier.com/locate/cageo Geosciences (Tm) of various phases and homogenization temperature (Th)—to determine the composition, density, and pressure in the inclusion at homogenization. From this information one can also calculate the slope of the isochore and estimate the PT conditions of FI formation, provided that either trapping T or P are known independently and the inclusions are trapped in the single-phase fluid field. Here, we assemble the numerical formulae necessary to fully characterize H2O–NaCl FI properties, based only on the tempera- ture of dissolution of the last solid phase, Tm, and the liquid-vapor homogenization temperature, Th, obtained during microthermo- metry. Note that an H2O–NaCl FI can exhibit more than two phase changes during heating from temperatures less than the eutectic temperature (�21.2 1C; Hall et al., 1988) to the total homogeni- zation temperature, but only the liquid–vapor homogenization temperature and the temperature of disappearance of the last solid phase are required to uniquely define the fluid composition and density. Using these two input parameters, the program calculates fluid density and salinity, and also estimates the isochore slope, which allows the user to calculate a pressure correction. Importantly, the program is designed such that the user can quickly and easily reduce large datasets. hal M. Steele-MacInnis et al. / Computers & Geosciences 49 (2012) 334–337 335 liquid-va por-hy droh alite /hal ite: Ster ner et al., 1988 liq uid -va po r-i ce: Bo dn ar, 19 93 loc us of cri tica l po int s:K nig ht a nd Bo dna r,1 989 At kin so n, 20 02 ite liquidus: Lecu m berri-Sanchez et al., in review Not shown: + liquid density: Bodnar, 1983; + isochore slope: Bodnar and Vityk, 1994Pr es su re Temperature T = -21.2 to 700 °C P = LVH to 6000 bar X = 0 to 70 wt% NaCl H2O liquid -vapor: Atkinson, 20 02 liq uid -v ap or cu rv es : Fig. 1. Schematic illustration of H2O–NaCl phase boundaries, showing the sources of the various equations used in the present study. The halite liquidus line and liquid–vapor curve both represent projections of constant liquid composition, whereas the other curves represent a range of compositions. For complete description of these features in PTX space, the reader is referred to Bodnar et al. 2. Program HokieFlincs_H2O-NaCl HOKIEFLINCS_H2O-NACL includes a set of FI-specific equations (Fig. 1) that describe the PVTX properties of H2O–NaCl based only on the measured Tm, and Th. Depending on the mode of homo- genization, different models may be required. For H2O–NaCl FI in which the last solid phase to disappear is H2O–ice, salinity is determined using the equation of Bodnar (1993). If the last solid phase to disappear (in equilibrium with liquid and vapor) is either hydrohalite or halite, equations from Sterner et al. (1988) are used to determine the liquid composition. Correlation equations derived in the present study are used to compute the densities of liquid and vapor, the vapor composition, and the mass propor- tions of liquid and vapor. The liquid and vapor compositions and mass fractions are used to precisely determine the bulk composi- tion. For homogenization in the absence of solids, pressure at Th and liquid density are represented by equations of Atkinson (1985) and Driesner and Heinrich (2007). (2002) and Bodnar (1983), respectively. The dP/dT slopes of isochores in the liquid field are modeled using equations of Bodnar and Vityk (1994), allowing direct determination of trap- ping PT conditions if an independent estimate of either P or T is supplied. Note that although the slopes of fluid isochores gen- erally have slight concave-down curvature, at crustal PT condi- tions the isochores of H2O–NaCl fluids are essentially linear (Bodnar and Vityk, 1994) and we assumed linearity in the program. Critical properties are based on the model of Knight and Bodnar (1989). The numerical models described above cannot model the PVTX properties of fluid inclusions for which ThoTm (i.e., inclusions homogenize by halite disappearance). Therefore, in cases where ThoTm, the salinity, pressure at homogenization, density and dP/ dT slope of the isochore in the liquid field are determined using the model of Lecumberri-Sanchez et al. (in review), which is a revision of an earlier model of Becker et al. (2008). The Excel spreadsheet ‘‘HOKIEFLINCS_H2O-NACL’’ (available in the online Supporting Information, Appendix A) does not require iterative procedures to interpret microthermometric data. The user inputs a value of Tm (specifying which solid phase, either H2O–ice, hydrohalite or halite, is the last to dissolve) and Th, in 1C (Fig. 2). The fluid salinity, density and the isochore slope are output (Fig. 2). If a pressure correction is required, the user inputs an estimate of either P or T of trapping, and the other quantity is computed using the isochore slope and the slope-intercept method. We avoided any formulae that require indirect solutions (iteration) in order to avoid using macros in the program. There- fore, HOKIEFLINCS_H2O-NACL uses only Excel formulae and does not employ Visual Basic (VBA) code. The program was designed in this way because VBA macros are not supported in all versions of Excel. Thus, because HOKIEFLINCS_H2O-NACL does not use macros, the program can be implemented using any version of Excel, on both Mac and PC platforms. As an example of the use of HOKIEFLINCS_H2O-NACL, consider a FI that contains liquid and vapor at room T, has final ice melting (in the presence of vapor) at �10 1C, and homogenizes by vapor bubble disappearance at 300 1C. To interpret these data, the value ‘‘�10’’ is entered into the cell for Tm (column C), and ‘‘ice’’ is entered into the adjacent cell in column D (phase) (row 30 in the screenshot; Fig. 2). Using the equation of Bodnar (1993) gives a salinity of 13.9 wt% NaCl (column H; Fig. 2). To determine the density of the FI and P at homogenization, the homogenization temperature (‘‘300’’) is entered into the same row in column E (Th), and the program applies the equations of Bodnar (1983) and Atkinson (2002) to estimate a bulk density of 0.86 g/cm3 (column J; Fig. 2) and P at homogenization of 78 bar (column I; Fig. 2). Using the equation of Bodnar and Vityk (1994), the isochore dP/dT slope for this inclusion is 12.1 bar/1C (column K; Fig. 2). The isochore slope can be used along with an independent estimate of the trapping T to determine the trapping P. For example, if mineral equilibria indicate that the host phase for the FI formed at 600 1C, the P of formation would have been �3700 bar. As another example, consider a FI that contains liquid, vapor and halite at room temperature, and in which halite dissolves and the bubble disappears at the same T of 400 1C (i.e., the FI homogenizes on the LVH curve). To interpret these microthermo- metric data, ‘‘400’’ is entered into columns C and E, and ‘‘halite’’ is entered into column D (row 30; Fig. 2). Based on the mode of homogenization, the models of Sterner et al. (1988) and Bodnar (1983) are used to determine the salinity (47.4 wt% NaCl) and density (1.09 g/cm3) of the FI (Fig. 2). The program uses the models of Atkinson (2002) and Bodnar and Vityk (1994) to estimate the P at homogenization (170 bar) and the slope of the isochore (14.4 bar/1C) (Fig. 2). Note that most natural FI homo- genize either by dissolution of the halite before the vapor bubble, in th ns a M. Steele-MacInnis et al. / Computers & Geosciences 49 (2012) 334–337336 or by disappearance of the vapor bubble before the halite. The significance of each mode of homogenization has been discussed by Roedder and Bodnar (1980) and Bodnar (1994), and Lecumberri-Sanchez et al. (in review) provide a model to interpret data from FI in which ThoTm. All three modes of homogenization can be modeled using (HOKIEFLINCS_H2O-NACL). For some FI it is not possible to measure the melting tem- perature. For example, in some liquidþvapor FI the vapor bubble occupies less than �10% of the inclusion volume and the ice melts metastably during freezing experiments (Roedder, 1967). Also, for very small FI the salinity is sometimes determined from Raman analysis because ice melting cannot be observed during microthermometry. In these cases, it is useful to have the option to model the FI properties without entering a measured Tm and instead entering an estimate of salinity. HOKIEFLINCS_H2O-NACL allows the user to input salinity directly for those FI for which Tm is not known (Column F, Fig. 2). HOKIEFLINCS_H2O-NACL can be used to determine properties of FI that homogenize to the liquid phase. The program is generally valid from �21.2 to 700 1C, the LV curve to 6000 bar and 0 to 70 wt% NaCl for FI that homogenize by vapor bubble disappear- ance; and from Th of 100 to 600 1C, the LVH curve to 3000 bar and 28–75 wt% NaCl for FI that homogenize by halite disappearance. For additional details, see Bodnar and Vityk (1994) and Lecumberri-Sanchez et al. (in review). The program includes a Fig. 2. Screenshot of the Excel spreadsheet. Microthermometric data are placed adjacent columns to the right (under ‘‘Outputs’’). Further to the right, other colum estimate trapping conditions. series of ‘‘if/then’’ statements to identify and alert the user to potentially invalid input data. For example, if the user inputs a value of �25 1C in the column for ice melting temperature, the program recognizes that the input Tm is less than the H2O–NaCl eutectic temperature (�21.2 1C; Hall et al., 1988) and a warning appears in the same row in column ‘‘S’’. Similarly, the program verifies that Tm, Th and all estimated fluid properties (density, pressure at homogenization, etc.) are within the ranges of validity of the various numerical models. A major advantage of HOKIEFLINCS_H2O-NACL over other avail- able programs for interpreting FI microthermometric data is the speed and ease with which the user can interpret large datasets. The spreadsheet is arranged such that Tm and Th each occupy one column (Fig. 2), and the maximum number of input data is only limited by the number of rows available in Excel. An inclusionist who regularly enters and stores microthermometric data in a spreadsheet format needs only copy and paste Tm and Th into the proper columns to reduce the data. Because all computations are direct, the results are immediately displayed when Tm and Th are entered. This is a significant advantage compared to previous computer tools for interpreting FI data, especially in applications Appendix A. Supporting materials Supplementary data associated with this article can be found in the online version at doi:10.1016/j.cageo.2012.01.022. Acknowledgments We thank Carlos Marques de Sa´ for discussions about inter- pretation of microthermometric data, which motivated us to create HOKIEFLINCS_H2O-NACL. John Mavrogenes provided sugges- tions for the program layout and experimented with an early version. Two anonymous reviewers provided critical comments that clarified and improved the manuscript and the program. Financial support for MS-M was provided by the Institute for Critical Technology and Applied Science (ICTAS) at Virginia Tech. This material is based upon work supported by the US National Science Foundation under grants nos. OCE-0928472 and EAR- 1019770 to RJB. where large numbers of FI are analyzed (e.g, thermal history reconstructions, or studies of fluid evolution in hydrothermal ore deposits). HOKIEFLINCS_H2O-NACL is available for download as an electronic annex to this paper (see Appendix A). e leftmost columns (under ‘‘Inputs’’), and calculated PVTX results appear in the llow the user to input an estimate of formation T or P to construct an isochore to References Anderko, A., Pitzer, K.S., 1993. Equation-of-state representation of phase equilibria and volumetric properties of the system NaCl–H2O above 573 K. Geochimica et Cosmochimica Acta 57, 1657–1680. Atkinson Jr., A.B., 2002. A model for the PTX properties of H2O–NaCl. Unpublished M.Sc. Thesis, Virginia Tech, Blacksburg, pp. 133. Bakker, R.J., 2003. Package FLUIDS 1. Computer programs for analysis of fluid inclusion data and for modelling bulk fluid properties. Chemical Geology 194, 3–23. Bakker, R.J., Brown, P.E., 2003. Computer modelling in fluid inclusion research. In: Samson, I., Anderson, A., Marshall, D. (Eds.), Fluid Inclusions: Analysis and Interpretation, Short Course 32, 32. 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