scholarly journals Solubility equilibria and geochemical modeling in the field of radioactive waste disposal

2005 ◽  
Vol 77 (3) ◽  
pp. 631-641 ◽  
Author(s):  
W. Hummel
Keyword(s):  
Experimental Data ◽  
Review Process ◽  
Geochemical Modeling ◽  
Radioactive Waste Disposal ◽  
Strict Sense ◽  
Chemical Thermodynamic ◽  
Hydroxo Complexes ◽  
Thermodynamic Constants ◽  
Experimental Solubility Data ◽  
Chemical Knowledge

If a true thermodynamic equilibrium with a well-known solid is expected to establish, chemical equilibrium thermodynamics allows estimation of the maximum concentration of a given radionuclide in a specified pore fluid of an underground repository. However, in the course of the review process for the Nagra/PSI Chemical Thermodynamic Data Base 01/01, important cases of insufficient chemical knowledge were identified, leading to gaps in the database. First, experimental data for the ThO2–H2O and UO2–H2O systems cannot be interpreted by a unique set of thermodynamic constants. There, a pragmatic approach was chosen by including parameters in the database that are not thermodynamic constants in a strict sense, but that reproduced relevant experimental observations. Second, potentially important thermodynamic constants are missing because of insufficient experimental data. Estimations of these missing constants led to problem-specific database extensions. Especially constants for ternary mixed carbonato-hydroxo complexes of tetravalent actinides have been estimated by the “backdoor approach”, i.e., by adjusting thermodynamic constants to maximum feasible values that are still consistent with all available experimental solubility data.

The application and development of geochemical modeling in high-level radioactive waste disposal

2014 ◽  
Vol 44 (10) ◽  
pp. 1508-1520
Author(s):  
MeiLing JIANG ◽  
XiangYun WANG ◽  
Tao CHEN ◽  
MingLiang KANG ◽  
ChunLi LIU
Keyword(s):  
Radioactive Waste ◽  
Waste Disposal ◽  
Geochemical Modeling ◽  
Radioactive Waste Disposal ◽  
High Level Radioactive Waste ◽  
High Level

Testing Analytical Models Using Archival or Experimental Methods

2012 ◽  
Vol 27 (1) ◽  
pp. 129-139 ◽  
Author(s):  
Shane S. Dikolli ◽  
John H. Evans ◽  
Jeffrey Hales ◽  
Michal Matejka ◽  
Donald V. Moser ◽  
...  
Keyword(s):  
Experimental Data ◽  
Empirical Research ◽  
Analytical Model ◽  
Empirical Data ◽  
Review Process ◽  
Experimental Methods ◽  
Analytical Models ◽  
Journal Review ◽  
Advantages And Disadvantages ◽  
Jel Classifications

SYNOPSIS Analytical models can quite naturally complement empirical data, whether archival or experimental. This article begins by discussing the advantages and disadvantages of combining an analytical model with archival or experimental data in a single study. We next describe how models are typically used in empirical research and discuss when including an analytical model is more versus less useful. Finally, we offer examples of more and less successful combinations of analytical models and empirical data, along with a brief discussion of how such studies are likely to fare in the journal review process. JEL Classifications: C02; C51; C99.

Geochemically derived non-gaseous radionuclide source term for the Asse salt mine – assessment for the use of a Mg(OH)2-based backfill material

2004 ◽  
Vol 92 (9-11) ◽  
Author(s):  
Volker Metz ◽  
W. Schüßler ◽  
B. Kienzler ◽  
Thomas Fanghänel
Keyword(s):  
Radioactive Waste ◽  
Waste Disposal ◽  
Source Term ◽  
Geochemical Modeling ◽  
Test Site ◽  
Radioactive Waste Disposal ◽  
Salt Mine ◽  
Waste Forms ◽  
Radionuclide Inventory ◽  
Radionuclide Source

SummaryThe Asse salt mine was used as a test site for radioactive waste disposal from 1967 to 1978. Low- and intermediate-level waste forms (LLW/ILW) were emplaced, containing a total radionuclide inventory of 3×10Geochemical modeling leads to the conclusion that Portland cement, a Mg(OH)

scholarly journals Fungal Bioweathering of Mimetite and a General Geomycological Model for Lead Apatite Mineral Biotransformations

2015 ◽  
Vol 81 (15) ◽  
pp. 4955-4964 ◽  
Author(s):  
Andrea Ceci ◽  
Martin Kierans ◽  
Stephen Hillier ◽  
Anna Maria Persiani ◽  
Geoffrey Michael Gadd
Keyword(s):  
Experimental Data ◽  
Geochemical Modeling ◽  
General Pattern ◽  
Soil Fungus ◽  
Industrial Applications ◽  
Ex Situ ◽  
Biogeochemical Model ◽  
Content Type ◽  
Lead Arsenate ◽  
Metal Stabilization

ABSTRACTFungi play important roles in biogeochemical processes such as organic matter decomposition, bioweathering of minerals and rocks, and metal transformations and therefore influence elemental cycles for essential and potentially toxic elements, e.g., P, S, Pb, and As. Arsenic is a potentially toxic metalloid for most organisms and naturally occurs in trace quantities in soil, rocks, water, air, and living organisms. Among more than 300 arsenic minerals occurring in nature, mimetite [Pb5(AsO4)3Cl] is the most stable lead arsenate and holds considerable promise in metal stabilization forin situandex situsequestration and remediation through precipitation, as do other insoluble lead apatites, such as pyromorphite [Pb5(PO4)3Cl] and vanadinite [Pb5(VO4)3Cl]. Despite the insolubility of mimetite, the organic acid-producing soil fungusAspergillus nigerwas able to solubilize mimetite with simultaneous precipitation of lead oxalate as a new mycogenic biomineral. Since fungal biotransformation of both pyromorphite and vanadinite has been previously documented, a new biogeochemical model for the biogenic transformation of lead apatites (mimetite, pyromorphite, and vanadinite) by fungi is hypothesized in this study by application of geochemical modeling together with experimental data. The models closely agreed with experimental data and provided accurate simulation of As and Pb complexation and biomineral formation dependent on, e.g., pH, cation-anion composition, and concentration. A general pattern for fungal biotransformation of lead apatite minerals is proposed, proving new understanding of ecological implications of the biogeochemical cycling of component elements as well as industrial applications in metal stabilization, bioremediation, and biorecovery.

scholarly journals Solubility of Acetophenone in Supercritical Carbon Dioxide

2016 ◽  
Vol 10 (1) ◽  
pp. 18-28 ◽  
Author(s):  
Maria Y. Dwi ◽  
Jessica Julian ◽  
Jindrayani N. Putro ◽  
Adi T. Nugraha ◽  
Yi-Hsu Ju ◽  
...  
Keyword(s):  
Experimental Data ◽  
Carbon Dioxide ◽  
Equation Of State ◽  
Supercritical Carbon Dioxide ◽  
Static Method ◽  
Solubility Data ◽  
Experimental Solubility Data ◽  
Experimental Solubility ◽  
Robinson Equation ◽  
Supercritical Carbon

The solubility data of acetophenone in supercritical carbon dioxide (scCO2) were measured using a static method at several temperatures (313.15, 323.15, 333.15, and 343.15K) and pressures ranging from10 MPa to 28 MPa. The density based models (Chrastil and Del valle– Aguilera models) and the Peng-Robinson equation of state (PR-EOS) with quadratic and Stryjek-Vera combining rules were employed to correlate the experimental data. Good correlations between the calculated and experimental solubility data were obtained. The sum of squared errors (SSE) are 0.38 % and 0.37 % for Chrastil and Del Valle – Aguilera models, respectively; and 9.07 % for Peng-Robinson equation of state with quadratic combining rule and 4.00 % for Peng-Robinson equation of state with Stryjek-Vera combining rule.

scholarly journals The importance of the accuracy of the experimental data for the prediction of solubility

2010 ◽  
Vol 75 (4) ◽  
pp. 483-495 ◽  
Author(s):  
Slavica Eric ◽  
Marko Kalinic ◽  
Aleksandar Popovic ◽  
Halid Makic ◽  
Elvisa Civic ◽  
...  
Keyword(s):  
Experimental Data ◽  
Computational Models ◽  
Linear Regression Analysis ◽  
Heuristic Method ◽  
Parameter Analysis ◽  
Solubility Data ◽  
Data Sets ◽  
Data Set ◽  
Experimental Solubility Data ◽  
Experimental Solubility

Aqueous solubility is an important factor influencing several aspects of the pharmacokinetic profile of a drug. Numerous publications present different methodologies for the development of reliable computational models for the prediction of solubility from structure. The quality of such models can be significantly affected by the accuracy of the employed experimental solubility data. In this work, the importance of the accuracy of the experimental solubility data used for model training was investigated. Three data sets were used as training sets - Data Set 1 containing solubility data collected from various literature sources using a few criteria (n = 319), Data Set 2 created by substituting 28 values from Data set 1 with uniformly determined experimental data from one laboratory (n = 319) and Data Set 3 created by including 56 additional components, for which the solubility was also determined under uniform conditions in the same laboratory, in the Data Set 2 (n = 375). The selection of the most significant descriptors was performed by the heuristic method, using one-parameter and multi-parameter analysis. The correlations between the most significant descriptors and solubility were established using multi-linear regression analysis (MLR) for all three investigated data sets. Notable differences were observed between the equations corresponding to different data sets, suggesting that models updated with new experimental data need to be additionally optimized. It was successfully shown that the inclusion of uniform experimental data consistently leads to an improvement in the correlation coefficients. These findings contribute to an emerging consensus that improving the reliability of solubility prediction requires the inclusion of many diverse compounds for which solubility was measured under standardized conditions in the data set.

scholarly journals Crystallographic raw data, education and refereeing

2016 ◽  
Vol 62 (3) ◽  
pp. 257-261
Author(s):  
John R. Helliwell
Keyword(s):  
Experimental Data ◽  
Protein Data Bank ◽  
Structural Biology ◽  
Diffraction Data ◽  
Review Process ◽  
Data Bank ◽  
The Impact ◽  
And Training ◽  
Scientific Achievements ◽  
Future Plans

This article provides an overview of the preservation of raw diffraction data, then addresses the impact on future plans in the education and training of our community with respect to raw diffraction data and its potential reuse, and, thirdly presents the issue of referee access to the underpinning diffraction data and coordinates, as well as the Protein Data Bank Validation Report, in the review process of structural biology articles submitted for publication. Overall I pay tribute to the scientific achievements of Alex Wlodawer, who is also an ardent advocate of the importance of experimental data

scholarly journals Validation and Recalibration of the Solubility Models in Support of the Heater Test in Salt Formations

MRS Advances ◽  
2020 ◽  
Vol 5 (5-6) ◽  
pp. 233-243
Author(s):  
Yongliang Xiong ◽  
Kris Kuhlman ◽  
Melissa Mills ◽  
Yifeng Wang
Keyword(s):  
Experimental Data ◽  
Single Phase ◽  
Elevated Temperatures ◽  
Geochemical Modeling ◽  
Department Of Energy ◽  
Chemical Compositions ◽  
Solubility Model ◽  
Predicted Values ◽  
Simple Systems ◽  
Validation Tests

AbstractThe US Department of Energy Office of Nuclear Energy is conducting a brine availability heater test to characterize the thermal, mechanical, hydrological and chemical response of salt at elevated temperatures. In the heater test, brines will be collected and analyzed for chemical compositions. In order to support the geochemical modeling of chemical evolutions of the brines during the heater test, we are recalibrating and validating the solubility models for the mineral constituents in salt formations up to 100°C, based on the solubility data in multiple component systems as well as simple systems from literature.In this work, we systematically compare the model-predicted values based on the various solubility models related to the constituents of salt formations, with the experimental data. As halite is the dominant constituent in salt formations, we first test the halite solubility model in the Na-Mg-Cl dominated brines. We find the existing halite solubility model systematically over-predict the solubility of halite. We recalibrate the halite model, which can reproduce halite solubilities in Na-Mg-Cl dominated brines well.As gypsum/anhydrite in salt formations controls the sulfate concentrations in associated brines, we test the gypsum solubility model in NaCl solutions up to 5.87 mol•kg–1 from 25°C to 50°C. The testing shows that the current gypsum solubility model reproduces the experimental data well when NaCl concentrations are less than 1 mol•kg–1. However, at NaCl concentrations higher than 1, the model systematically overpredicts the solubility of gypsum.In the Na+—Cl–—SO42–—CO32– system, the validation tests up to 100°C demonstrate that the model excellently reproduces the experimental data for the solution compositions equilibrated with one single phase such as halite (NaCl) or thenardite (Na2SO4), with deviations equal to, or less than, 1.5 %. The model is much less ideal in reproducing the compositions in equilibrium with the assemblages of halite + thenardite, and of halite + thermonatrite (Na2CO3•H2O), with deviations up to 31 %. The high deviations from the experimental data for the multiple assemblages in this system at elevated temperatures may be attributed to the facts that the database has the Pitzer interaction parameters for Cl–—CO32– and SO42–—CO32– only at 25°C.In the Na+—Ca2+—SO42–—HCO3– system, the validation tests also demonstrate that the model reproduces the equilibrium compositions for one single phase such as gypsum better than the assemblages of more than one phase.

On the Problem of Consistency of Chemical Thermodynamic Data Bases

1990 ◽  
Vol 212 ◽  
Author(s):  
Hans Wanner
Keyword(s):  
Thermodynamic Data ◽  
Radioactive Waste Disposal ◽  
Geochemical Modelling ◽  
Chemical Model ◽  
List Type ◽  
Chemical Thermodynamic ◽  
Data Bases ◽  
Auxiliary Data ◽  
Additional Information

ABSTRACTThe geochemical modelling in support of the performance assessment of radioactive waste disposal systems calls for a large number of chemical thermodynamic data. For realistic modelling it is essential that the data used are fully consistent. The verification of consistency of existing data bases is complicated by the fact that it requires the knowledge of a considerable amount of primary information to ensure:1.Consistency with the fundamental laws of thermodynamics2.Consistency within a chemical model3.Consistency with auxiliary data4.Consistency in the data correction proceduresThis paper includes selected examples for each of the four items to visualize the problems. It should be noted that there are numerous other systems that could serve as examples as well, and the range of cases reported here is far from being exhaustive.Realistic geochemical modelling depends not only on the quality of the data base, but also on the quality of the chemical model used. For the establishment of a chemical model, additional information is needed that is not contained in thermodynamic data bases.

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