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Title: NEWTS Argonne Geothermal Geochemical Database with CoDART

Abstract

A database of geochemical compositions of aqueous species in potential geothermal resources. The NETL NEWTS team has formatted the original Argonne V2 database for Charge Balance, Input into OLI Studio, and Input into GWB. (Geochemist WorkBench) In addition, some missing species in the original database were predicted using machine learning techniques within CoDart software, a public ML software developed by the Nation Energy Technology Laboratory. We have made the Input into CoDart and one example output from CoDart available in this dataset.

Authors:
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  1. National Energy Technology Laboratory
Publication Date:
Other Number(s):
9eeb3879-0688-4e34-a124-88864fdd0bd9
Research Org.:
National Energy Technology Laboratory - Energy Data eXchange; NETL
Sponsoring Org.:
USDOE Office of Fossil Energy (FE)
Subject:
Aqueous Chemistry; Geochemists Workbench; Geothermal Waters; INORGANIC GEOCHEMISTRY; National Energy Water Treatment and Speciation Database; Water Management; Water Treatment
OSTI Identifier:
2448231
DOI:
https://doi.org/10.18141/2448231

Citation Formats

Siefert, Nicholas, Able, Chad, and Fritz, Alison. NEWTS Argonne Geothermal Geochemical Database with CoDART. United States: N. p., 2024. Web. doi:10.18141/2448231.
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Siefert, Nicholas, Able, Chad, & Fritz, Alison. NEWTS Argonne Geothermal Geochemical Database with CoDART. United States. doi:https://doi.org/10.18141/2448231
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Siefert, Nicholas, Able, Chad, and Fritz, Alison. 2024. "NEWTS Argonne Geothermal Geochemical Database with CoDART". United States. doi:https://doi.org/10.18141/2448231. https://www.osti.gov/servlets/purl/2448231. Pub date:Mon Sep 30 00:00:00 EDT 2024
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@article{osti_2448231,
title = {NEWTS Argonne Geothermal Geochemical Database with CoDART},
author = {Siefert, Nicholas and Able, Chad and Fritz, Alison},
abstractNote = {A database of geochemical compositions of aqueous species in potential geothermal resources. The NETL NEWTS team has formatted the original Argonne V2 database for Charge Balance, Input into OLI Studio, and Input into GWB. (Geochemist WorkBench) In addition, some missing species in the original database were predicted using machine learning techniques within CoDart software, a public ML software developed by the Nation Energy Technology Laboratory. We have made the Input into CoDart and one example output from CoDart available in this dataset.},
doi = {10.18141/2448231},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Sep 30 00:00:00 EDT 2024},
month = {Mon Sep 30 00:00:00 EDT 2024}
}
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Dataset:
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DOI: https://doi.org/10.18141/2448231
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