PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions
Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pres...
Ausführliche Beschreibung
Autor*in: |
Awolayo, Adedapo N. [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2022transfer abstract |
---|
Schlagwörter: |
---|
Übergeordnetes Werk: |
Enthalten in: An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan - Miyata, Hugo Hissashi ELSEVIER, 2022, (including Isotope geoscience) : official journal of the European Association for Geochemistry, New York, NY [u.a.] |
---|---|
Übergeordnetes Werk: |
volume:606 ; year:2022 ; day:20 ; month:09 ; pages:0 |
Links: |
---|
DOI / URN: |
10.1016/j.chemgeo.2022.120984 |
---|
Katalog-ID: |
ELV05842461X |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | ELV05842461X | ||
003 | DE-627 | ||
005 | 20230626050842.0 | ||
007 | cr uuu---uuuuu | ||
008 | 220808s2022 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1016/j.chemgeo.2022.120984 |2 doi | |
028 | 5 | 2 | |a /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001842.pica |
035 | |a (DE-627)ELV05842461X | ||
035 | |a (ELSEVIER)S0009-2541(22)00278-9 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | 4 | |a 004 |q VZ |
084 | |a 85.35 |2 bkl | ||
084 | |a 54.80 |2 bkl | ||
100 | 1 | |a Awolayo, Adedapo N. |e verfasserin |4 aut | |
245 | 1 | 0 | |a PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions |
264 | 1 | |c 2022transfer abstract | |
336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
337 | |a nicht spezifiziert |b z |2 rdamedia | ||
338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
520 | |a Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. | ||
520 | |a Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. | ||
650 | 7 | |a Thermodynamic properties |2 Elsevier | |
650 | 7 | |a Variable-chemistry clays |2 Elsevier | |
650 | 7 | |a Thermodynamic database |2 Elsevier | |
700 | 1 | |a Tutolo, Benjamin M. |4 oth | |
773 | 0 | 8 | |i Enthalten in |n Elsevier |a Miyata, Hugo Hissashi ELSEVIER |t An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan |d 2022 |d (including Isotope geoscience) : official journal of the European Association for Geochemistry |g New York, NY [u.a.] |w (DE-627)ELV008354693 |
773 | 1 | 8 | |g volume:606 |g year:2022 |g day:20 |g month:09 |g pages:0 |
856 | 4 | 0 | |u https://doi.org/10.1016/j.chemgeo.2022.120984 |3 Volltext |
912 | |a GBV_USEFLAG_U | ||
912 | |a GBV_ELV | ||
912 | |a SYSFLAG_U | ||
936 | b | k | |a 85.35 |j Fertigung |q VZ |
936 | b | k | |a 54.80 |j Angewandte Informatik |q VZ |
951 | |a AR | ||
952 | |d 606 |j 2022 |b 20 |c 0920 |h 0 |
author_variant |
a n a an ana |
---|---|
matchkey_str |
awolayoadedapontutolobenjaminm:2022----:yececlayhnakgfreceiatemdnmcacltosrmm |
hierarchy_sort_str |
2022transfer abstract |
bklnumber |
85.35 54.80 |
publishDate |
2022 |
allfields |
10.1016/j.chemgeo.2022.120984 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001842.pica (DE-627)ELV05842461X (ELSEVIER)S0009-2541(22)00278-9 DE-627 ger DE-627 rakwb eng 004 VZ 85.35 bkl 54.80 bkl Awolayo, Adedapo N. verfasserin aut PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. Thermodynamic properties Elsevier Variable-chemistry clays Elsevier Thermodynamic database Elsevier Tutolo, Benjamin M. oth Enthalten in Elsevier Miyata, Hugo Hissashi ELSEVIER An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan 2022 (including Isotope geoscience) : official journal of the European Association for Geochemistry New York, NY [u.a.] (DE-627)ELV008354693 volume:606 year:2022 day:20 month:09 pages:0 https://doi.org/10.1016/j.chemgeo.2022.120984 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 606 2022 20 0920 0 |
spelling |
10.1016/j.chemgeo.2022.120984 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001842.pica (DE-627)ELV05842461X (ELSEVIER)S0009-2541(22)00278-9 DE-627 ger DE-627 rakwb eng 004 VZ 85.35 bkl 54.80 bkl Awolayo, Adedapo N. verfasserin aut PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. Thermodynamic properties Elsevier Variable-chemistry clays Elsevier Thermodynamic database Elsevier Tutolo, Benjamin M. oth Enthalten in Elsevier Miyata, Hugo Hissashi ELSEVIER An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan 2022 (including Isotope geoscience) : official journal of the European Association for Geochemistry New York, NY [u.a.] (DE-627)ELV008354693 volume:606 year:2022 day:20 month:09 pages:0 https://doi.org/10.1016/j.chemgeo.2022.120984 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 606 2022 20 0920 0 |
allfields_unstemmed |
10.1016/j.chemgeo.2022.120984 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001842.pica (DE-627)ELV05842461X (ELSEVIER)S0009-2541(22)00278-9 DE-627 ger DE-627 rakwb eng 004 VZ 85.35 bkl 54.80 bkl Awolayo, Adedapo N. verfasserin aut PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. Thermodynamic properties Elsevier Variable-chemistry clays Elsevier Thermodynamic database Elsevier Tutolo, Benjamin M. oth Enthalten in Elsevier Miyata, Hugo Hissashi ELSEVIER An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan 2022 (including Isotope geoscience) : official journal of the European Association for Geochemistry New York, NY [u.a.] (DE-627)ELV008354693 volume:606 year:2022 day:20 month:09 pages:0 https://doi.org/10.1016/j.chemgeo.2022.120984 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 606 2022 20 0920 0 |
allfieldsGer |
10.1016/j.chemgeo.2022.120984 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001842.pica (DE-627)ELV05842461X (ELSEVIER)S0009-2541(22)00278-9 DE-627 ger DE-627 rakwb eng 004 VZ 85.35 bkl 54.80 bkl Awolayo, Adedapo N. verfasserin aut PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. Thermodynamic properties Elsevier Variable-chemistry clays Elsevier Thermodynamic database Elsevier Tutolo, Benjamin M. oth Enthalten in Elsevier Miyata, Hugo Hissashi ELSEVIER An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan 2022 (including Isotope geoscience) : official journal of the European Association for Geochemistry New York, NY [u.a.] (DE-627)ELV008354693 volume:606 year:2022 day:20 month:09 pages:0 https://doi.org/10.1016/j.chemgeo.2022.120984 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 606 2022 20 0920 0 |
allfieldsSound |
10.1016/j.chemgeo.2022.120984 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001842.pica (DE-627)ELV05842461X (ELSEVIER)S0009-2541(22)00278-9 DE-627 ger DE-627 rakwb eng 004 VZ 85.35 bkl 54.80 bkl Awolayo, Adedapo N. verfasserin aut PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. Thermodynamic properties Elsevier Variable-chemistry clays Elsevier Thermodynamic database Elsevier Tutolo, Benjamin M. oth Enthalten in Elsevier Miyata, Hugo Hissashi ELSEVIER An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan 2022 (including Isotope geoscience) : official journal of the European Association for Geochemistry New York, NY [u.a.] (DE-627)ELV008354693 volume:606 year:2022 day:20 month:09 pages:0 https://doi.org/10.1016/j.chemgeo.2022.120984 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 606 2022 20 0920 0 |
language |
English |
source |
Enthalten in An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan New York, NY [u.a.] volume:606 year:2022 day:20 month:09 pages:0 |
sourceStr |
Enthalten in An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan New York, NY [u.a.] volume:606 year:2022 day:20 month:09 pages:0 |
format_phy_str_mv |
Article |
bklname |
Fertigung Angewandte Informatik |
institution |
findex.gbv.de |
topic_facet |
Thermodynamic properties Variable-chemistry clays Thermodynamic database |
dewey-raw |
004 |
isfreeaccess_bool |
false |
container_title |
An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan |
authorswithroles_txt_mv |
Awolayo, Adedapo N. @@aut@@ Tutolo, Benjamin M. @@oth@@ |
publishDateDaySort_date |
2022-01-20T00:00:00Z |
hierarchy_top_id |
ELV008354693 |
dewey-sort |
14 |
id |
ELV05842461X |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV05842461X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626050842.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">220808s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.chemgeo.2022.120984</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001842.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV05842461X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0009-2541(22)00278-9</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">85.35</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.80</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Awolayo, Adedapo N.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022transfer abstract</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Thermodynamic properties</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Variable-chemistry clays</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Thermodynamic database</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tutolo, Benjamin M.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Miyata, Hugo Hissashi ELSEVIER</subfield><subfield code="t">An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan</subfield><subfield code="d">2022</subfield><subfield code="d">(including Isotope geoscience) : official journal of the European Association for Geochemistry</subfield><subfield code="g">New York, NY [u.a.]</subfield><subfield code="w">(DE-627)ELV008354693</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:606</subfield><subfield code="g">year:2022</subfield><subfield code="g">day:20</subfield><subfield code="g">month:09</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.chemgeo.2022.120984</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">85.35</subfield><subfield code="j">Fertigung</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">54.80</subfield><subfield code="j">Angewandte Informatik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">606</subfield><subfield code="j">2022</subfield><subfield code="b">20</subfield><subfield code="c">0920</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
author |
Awolayo, Adedapo N. |
spellingShingle |
Awolayo, Adedapo N. ddc 004 bkl 85.35 bkl 54.80 Elsevier Thermodynamic properties Elsevier Variable-chemistry clays Elsevier Thermodynamic database PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions |
authorStr |
Awolayo, Adedapo N. |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV008354693 |
format |
electronic Article |
dewey-ones |
004 - Data processing & computer science |
delete_txt_mv |
keep |
author_role |
aut |
collection |
elsevier |
remote_str |
true |
illustrated |
Not Illustrated |
topic_title |
004 VZ 85.35 bkl 54.80 bkl PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions Thermodynamic properties Elsevier Variable-chemistry clays Elsevier Thermodynamic database Elsevier |
topic |
ddc 004 bkl 85.35 bkl 54.80 Elsevier Thermodynamic properties Elsevier Variable-chemistry clays Elsevier Thermodynamic database |
topic_unstemmed |
ddc 004 bkl 85.35 bkl 54.80 Elsevier Thermodynamic properties Elsevier Variable-chemistry clays Elsevier Thermodynamic database |
topic_browse |
ddc 004 bkl 85.35 bkl 54.80 Elsevier Thermodynamic properties Elsevier Variable-chemistry clays Elsevier Thermodynamic database |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
zu |
author2_variant |
b m t bm bmt |
hierarchy_parent_title |
An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan |
hierarchy_parent_id |
ELV008354693 |
dewey-tens |
000 - Computer science, knowledge & systems |
hierarchy_top_title |
An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)ELV008354693 |
title |
PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions |
ctrlnum |
(DE-627)ELV05842461X (ELSEVIER)S0009-2541(22)00278-9 |
title_full |
PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions |
author_sort |
Awolayo, Adedapo N. |
journal |
An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan |
journalStr |
An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan |
lang_code |
eng |
isOA_bool |
false |
dewey-hundreds |
000 - Computer science, information & general works |
recordtype |
marc |
publishDateSort |
2022 |
contenttype_str_mv |
zzz |
container_start_page |
0 |
author_browse |
Awolayo, Adedapo N. |
container_volume |
606 |
class |
004 VZ 85.35 bkl 54.80 bkl |
format_se |
Elektronische Aufsätze |
author-letter |
Awolayo, Adedapo N. |
doi_str_mv |
10.1016/j.chemgeo.2022.120984 |
dewey-full |
004 |
title_sort |
pygeochemcalc: a python package for geochemical thermodynamic calculations from ambient to deep earth conditions |
title_auth |
PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions |
abstract |
Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. |
abstractGer |
Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. |
abstract_unstemmed |
Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool. |
collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U |
title_short |
PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions |
url |
https://doi.org/10.1016/j.chemgeo.2022.120984 |
remote_bool |
true |
author2 |
Tutolo, Benjamin M. |
author2Str |
Tutolo, Benjamin M. |
ppnlink |
ELV008354693 |
mediatype_str_mv |
z |
isOA_txt |
false |
hochschulschrift_bool |
false |
author2_role |
oth |
doi_str |
10.1016/j.chemgeo.2022.120984 |
up_date |
2024-07-06T18:58:46.900Z |
_version_ |
1803857246973591552 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV05842461X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626050842.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">220808s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.chemgeo.2022.120984</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001842.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV05842461X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0009-2541(22)00278-9</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">85.35</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">54.80</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Awolayo, Adedapo N.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">PyGeochemCalc: A Python package for geochemical thermodynamic calculations from ambient to deep Earth conditions</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022transfer abstract</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Over the past half century, techniques for evaluating the thermodynamics of water-rock interactions from ambient to deep Earth conditions have advanced incredibly and in myriad directions. As these tools for analyzing the thermodynamic states of geochemical species as a function of temperature, pressure, and composition have multiplied, so too have the possibilities for tracing water-rock interaction from ambient to deep conditions on Earth and beyond. Yet, the aqueous geochemical community still lacks a centralized platform for incorporating this constantly updating thermodynamic data into aqueous geochemical models. Here, we introduce PyGeochemCalc (PyGCC), a community-driven, open-source Python package that meets this need by providing a consolidated set of functions for calculating the thermodynamic properties of gas, aqueous, and mineral (including solid solutions and variable-formula clays) species, as well as reactions amongst these species, over a broad range of temperature and pressure conditions. The PyGCC package utilizes the revised Helgeson-Kirkham-Flowers (HKF) equation of state, and newly proposed density-based extrapolations based upon it, to calculate the thermodynamic properties of aqueous species; a choice of equations of state and electrostatic models (including the Deep Earth Water (DEW) model) to calculate thermodynamic and dielectric properties of water; and heat capacity functions to calculate thermodynamic properties of minerals and gases. Additionally, PyGCC integrates these functions to generate thermodynamic databases for various geochemical programs, including the Geochemist's Workbench (GWB), EQ3/6, TOUGHREACT, and PFLOTRAN, with straightforward possibilities for extension to other simulators. The various functions in the package can also be modularly utilized, and introduced into other modeling tools, as desired. In this paper, we detail the capabilities of PyGCC and the equations it relies on for calculating thermodynamic properties of water, aqueous species, and gases. Although the fundamental thermodynamic data necessary for state-of-the-science PyGCC calculations will necessarily evolve as our collective geochemical knowledge base expands, PyGCC's open source, community-driven design will allow for users to keep pace via rapid implementation of these advancements in this modern geochemical tool.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Thermodynamic properties</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Variable-chemistry clays</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Thermodynamic database</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tutolo, Benjamin M.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Miyata, Hugo Hissashi ELSEVIER</subfield><subfield code="t">An iterated greedy algorithm for distributed blocking flow shop with setup times and maintenance operations to minimize makespan</subfield><subfield code="d">2022</subfield><subfield code="d">(including Isotope geoscience) : official journal of the European Association for Geochemistry</subfield><subfield code="g">New York, NY [u.a.]</subfield><subfield code="w">(DE-627)ELV008354693</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:606</subfield><subfield code="g">year:2022</subfield><subfield code="g">day:20</subfield><subfield code="g">month:09</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.chemgeo.2022.120984</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">85.35</subfield><subfield code="j">Fertigung</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">54.80</subfield><subfield code="j">Angewandte Informatik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">606</subfield><subfield code="j">2022</subfield><subfield code="b">20</subfield><subfield code="c">0920</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
score |
7.4003687 |