An Overview of Computational Methods for Chemical Equilibrium and Kinetic Calculations for Geochemical and Reactive Transport Modeling
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The Practice of Chemistry Education (Paper)
CHEMISTRY EDUCATION: THE PRACTICE OF CHEMISTRY EDUCATION RESEARCH AND PRACTICE (PAPER) 2004, Vol. 5, No. 1, pp. 69-87 Concept teaching and learning/ History and philosophy of science (HPS) Juan QUÍLEZ IES José Ballester, Departamento de Física y Química, Valencia (Spain) A HISTORICAL APPROACH TO THE DEVELOPMENT OF CHEMICAL EQUILIBRIUM THROUGH THE EVOLUTION OF THE AFFINITY CONCEPT: SOME EDUCATIONAL SUGGESTIONS Received 20 September 2003; revised 11 February 2004; in final form/accepted 20 February 2004 ABSTRACT: Three basic ideas should be considered when teaching and learning chemical equilibrium: incomplete reaction, reversibility and dynamics. In this study, we concentrate on how these three ideas have eventually defined the chemical equilibrium concept. To this end, we analyse the contexts of scientific inquiry that have allowed the growth of chemical equilibrium from the first ideas of chemical affinity. At the beginning of the 18th century, chemists began the construction of different affinity tables, based on the concept of elective affinities. Berthollet reworked this idea, considering that the amount of the substances involved in a reaction was a key factor accounting for the chemical forces. Guldberg and Waage attempted to measure those forces, formulating the first affinity mathematical equations. Finally, the first ideas providing a molecular interpretation of the macroscopic properties of equilibrium reactions were presented. The historical approach of the first key ideas may serve as a basis for an appropriate sequencing of -
Geochemical and Biogeochemical Reaction Modeling, Second Edition Craig M
Cambridge University Press 978-0-521-87554-7 - Geochemical and Biogeochemical Reaction Modeling, Second Edition Craig M. Bethke Frontmatter More information GEOCHEMICAL AND BIOGEOCHEMICAL REACTION MODELING Geochemical reaction modeling plays an increasingly vital role in a number of areas of geoscience, ranging from groundwater and surface water hydrology to environmental preservation and remediation to economic and petroleum geology to geomicrobiology. This book provides a comprehensive overview of reaction processes in the Earth’s crust and on its surface, both in the laboratory and in the field. A clear exposition of the underlying equations and calculation techniques is balanced by a large number of fully worked examples. The book uses The Geochemist’s Workbench® modeling software, developed by the author and installed at over 1000 universities and research facilities worldwide. The reader can, however, also use the software of his or her choice. The book contains all the information needed for the reader to reproduce calculations in full. Since publication of the first edition, the field of reaction modeling has continued to grow and find increasingly broad application. In particular, the description of microbial activity, surface chemistry, and redox chemistry within reaction models has become broader and more rigorous. Reaction models are commonly coupled to numerical models of mass and heat transport, producing a classification now known as reactive transport modeling. These areas are covered in detail in this new edition. This book will be of great interest to graduate students and academic researchers in the fields of geochemistry, environmental engineering, contaminant hydrology, geomicrobiology, and numerical modeling. CRAIG BETHKE is a Professor at the Department of Geology, University of Illinois, specializing in mathematical modeling of subsurface and surficial processes. -
An Overview of Occurrence and Evolution of Acid Mine Drainage in the Los Vak Republic Andrea Slesarova Slovak Academy of Sciences
Proceedings of the Annual International Conference on Soils, Sediments, Water and Energy Volume 12 Article 3 January 2010 An Overview Of Occurrence And Evolution Of Acid Mine Drainage In The loS vak Republic Andrea Slesarova Slovak Academy of Sciences Maria Kusnierova Slovak Academy of Sciences Alena Luptakova Slovak Academy of Sciences Josef Zeman Masaryk University in Brno Follow this and additional works at: https://scholarworks.umass.edu/soilsproceedings Recommended Citation Slesarova, Andrea; Kusnierova, Maria; Luptakova, Alena; and Zeman, Josef (2010) "An Overview Of Occurrence And Evolution Of Acid Mine Drainage In The loS vak Republic," Proceedings of the Annual International Conference on Soils, Sediments, Water and Energy: Vol. 12 , Article 3. Available at: https://scholarworks.umass.edu/soilsproceedings/vol12/iss1/3 This Conference Proceeding is brought to you for free and open access by ScholarWorks@UMass Amherst. It has been accepted for inclusion in Proceedings of the Annual International Conference on Soils, Sediments, Water and Energy by an authorized editor of ScholarWorks@UMass Amherst. For more information, please contact [email protected]. Slesarova et al.: Overview of Acid Mine Drainage In The Slovak Republic Chapter 2 AN OVERVIEW OF OCCURRENCE AND EVOLUTION OF ACID MINE DRAINAGE IN THE SLOVAK REPUBLIC Andrea Slesarova1, Maria Kusnierova1, Alena Luptakova1 and Josef Zeman2 1Institute of Geotechnics, Slovak Academy of Sciences, Watsonova 45, 04353 Kosice, Slovak Republic; 2Institute of Geological Sciences, Faculty of Science, Masaryk University in Brno, Kotlarska 2, 61137 Brno, Czech Republic Abstract: Acid mine drainage (AMD) is one of the worst environmental problems associated with mining activity. Both at the beginning and in the middle of the 20th C., the attenuation of mining activity in the Slovak Republic gave rise to the extensive closing of deposits using wet conservation i.e. -
GEOCHEMICAL MODELING to PREDICT the CHEMISTRY of LEACHATES from Aixal;INE SOLID WASTES: OIL SHAIE DEPOSITS, WESTERN U.S.A
GEOCHEMICAL MODELING TO PREDICT THE CHEMISTRY OF LEACHATES FROM AIxAL;INE SOLID WASTES: OIL SHAIE DEPOSITS, WESTERN U.S.A. KJ. Reddy James I. Drever V.R. Hasfurther 1993 Journal Article WWRC-93-03 In Applied Geochemistry KJ. Reddy Wyoming Water Resources Center James I. Drever Geology and Geophysics Department Victor R. Hasfurther Civil Engineering Department and Wyoming Water Resources Center University of Wyoming Laramie, Wyoming Applied Geochemistry. Suppl. Issue No. 2. pp. 155-158. 1993 0883-2927i93 $6.00 + .OO Printed in Great Britain @ 1992 Pergamon Press Ltd Geochemical modeling to predict the chemistry of leachates from alkaline solid wastes: oil shale deposits, western U.S.A. K. J. REDDY Water Resources Center, P.O. Box 3067, University of Wyoming, Laramie, WY 82071, U.S.A. J. I. DREVER Department of Geology & Geophysics, P.O. Box 3006, University of Wyoming, Laramie, WY 82071, U.S.A. and V. R.HASFURTHER Civil Engineering and Water Resources Center, P.O. Box 3067, University of Wyoming, Laramie, WY 82071, U.S.A. Abstract-Oil shale processing at elevated temperatures to extract oil results in large amounts of alkaline oil shale solid wastes (OSSW). The objective of this study was to use a geochemical model to help predict the chemistry of leachates, including toxic chemicals, from OSSW. Several geochemical models were evaluated (e.g. EQ3EQ6, GEOCHEM, MINTEQAZ, PHREEQE, SOLMINEQ, WATEQFC); the model GEOCHEM was selected based on its more comprehensive capabilities. The OSSW samples were subjected to solubility and XRD studies. Element concentrationsand pH of OSSW leachates were used as input to GEOCHEM to predict their chemistry. -
Analyzing Binding Data UNIT 7.5 Harvey J
Analyzing Binding Data UNIT 7.5 Harvey J. Motulsky1 and Richard R. Neubig2 1GraphPad Software, La Jolla, California 2University of Michigan, Ann Arbor, Michigan ABSTRACT Measuring the rate and extent of radioligand binding provides information on the number of binding sites, and their afÞnity and accessibility of these binding sites for various drugs. This unit explains how to design and analyze such experiments. Curr. Protoc. Neurosci. 52:7.5.1-7.5.65. C 2010 by John Wiley & Sons, Inc. Keywords: binding r radioligand r radioligand binding r Scatchard plot r r r r r r receptor binding competitive binding curve IC50 Kd Bmax nonlinear regression r curve Þtting r ßuorescence INTRODUCTION A radioligand is a radioactively labeled drug that can associate with a receptor, trans- porter, enzyme, or any protein of interest. The term ligand derives from the Latin word ligo, which means to bind or tie. Measuring the rate and extent of binding provides information on the number, afÞnity, and accessibility of these binding sites for various drugs. While physiological or biochemical measurements of tissue responses to drugs can prove the existence of receptors, only ligand binding studies (or possibly quantitative immunochemical studies) can determine the actual receptor concentration. Radioligand binding experiments are easy to perform, and provide useful data in many Þelds. For example, radioligand binding studies are used to: 1. Study receptor regulation, for example during development, in diseases, or in response to a drug treatment. 2. Discover new drugs by screening for compounds that compete with high afÞnity for radioligand binding to a particular receptor. -
Fugacity Nov 2 2011.Pdf
Fugacity - Wikipedia, the free encyclopedia 頁 1 / 5 Fugacity From Wikipedia, the free encyclopedia In chemical thermodynamics, the fugacity (f) of a real gas is an effective pressure which replaces the true mechanical pressure in accurate chemical equilibrium calculations. It is equal to the pressure of an ideal gas which has the same chemical potential as the real gas. For example, [1] nitrogen gas (N2) at 0°C and a pressure of 100 atm has a fugacity of 97.03 atm. This means that the chemical potential of real nitrogen at a pressure of 100 atm has the value which ideal nitrogen would have at a pressure of 97.03 atm. Fugacities are determined experimentally or estimated for various models such as a Van der Waals gas that are closer to reality than an ideal gas. The ideal gas pressure and fugacity are related through the dimensionless fugacity coefficient .[2] For nitrogen at 100 atm, the fugacity coefficient is 97.03 atm / 100 atm = 0.9703. For an ideal gas, fugacity and pressure are equal so is 1. The fugacity is closely related to the thermodynamic activity. For a gas, the activity is simply the fugacity divided by a reference pressure to give a dimensionless quantity. This reference pressure is called the standard state and normally chosen as 1 atmosphere or 1 bar, Again using nitrogen at 100 atm as an example, since the fugacity is 97.03 atm, the activity is just 97.03 with no units. Accurate calculations of chemical equilibrium for real gases should use the fugacity rather than the pressure. -
Chemical Kinetics I: Basics
2 CHEMICAL KINETICS I: BASICS c1 In the previous chapter, we c2discussed some the fundamental biological pro- cesses c3undertaken by cells such as transcription and translation. The purpose of this chapter is to introduce the basic concepts needed to model the dynamics of such processes. c4These next two chapters explain how to describe chemical re- actions mathematically, both at a deterministic level where stochastic effects are ignored, as well as probabilistically where stochasticity is explicitly incorporated. 2.1 Law of mass action Consider a reaction where two kinds of molecules, c5 A and B, irreversibly re- act to produce a third kind c6of molecule, C. Schematically, such a reaction is represented as k A+B C. (2.1) ! The parameter k is the rate of the reaction. c7In general, kinetic parameters such as k depend on the environment through thermodynamic quantities such as the pressure and temperature. However, since cells often operate in environments where these quantities do not vary much, for simplicity, we will neglect these dependencies in what follows. According to the law of mass action,the rate of increase of the concentration of the product is given by d[C] = k[A][B] (2.2) dt where we follow the standard convention in chemistry texts: the concentration of the chemical X is represented by [X]. Note that the accompanied decrease of the concentrations of A and B is given by the same expression: k[A][B]. Namely, d[A] d[B] = = k[A][B] (2.3) dt dt − c1Pankaj: This is a test c2Pankaj: have introduced some of the basic c3Pankaj: Text added. -
Geochemical Modeling to Evaluate Remediation Options for Iron-Laden Mine Discharges
Geochemical Modeling to Evaluate Remediation Options for Iron-Laden Mine Discharges Charles “Chuck” Cravotta III U.S. Geological Survey Pennsylvania Water Science Center [email protected] Summary Aqueous geochemical tools using PHREEQC have been developed by USGS for OSMRE’s “AMDTreat” cost- analysis software: Iron-oxidation kinetics model considers pH-dependent abiotic and biological rate laws plus effects of aeration rate on the pH and concentrations of CO2 and O2. Limestone kinetics model considers solution chemistry plus the effects of surface area of limestone fragments. Potential water quality from various treatments can be considered for feasibility and benefits/costs analysis. TREATMENT OF COAL MINE DRAINAGE Al3+ Fe2+ / Fe3+ Passive Mn2+ Active Increase pH/oxidation Increase pH/oxidation with natural substrates & with aeration &/or microbial activity industrial chemicals Reactions slow Reactions fast, efficient Large area footprint Moderate area footprint Low maintenance High maintenance ACTIVE TREATMENT 28 % – aeration; no chemicals (Ponds) 21 % – caustic soda (NaOH) used 40 % – lime (CaO; Ca(OH)2) used 6 % – flocculent or oxidant used 4 % – limestone (CaCO3) used PASSIVE TREATMENT Vertical Flow Limestone Beds PASSIVE Bell Colliery TREATMENT Limestone Dissolution, O2 Ingassing, CO2 Outgassing, Fe(II) Oxidation, & Fe(III) Accumulation Pine Forest ALD & Wetlands Silver Creek Wetlands BIMODAL pH FREQUENCY DISTRIBUTION 40 A. Anthracite Mine Discharges pH, field 35 Anthracite AMD pH, lab (aged) 30 pH increases after 25 “oxidation” of net alkaline 20 water (CO2 outgassing): - - 15 HCO3 = CO2 (gas) + OH 10 Frequency in percent, N=41 in percent, Frequency 5 0 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 40 B. -
1301 Dynamic Equilibrium, Keq, and the Mass Action Expression
1301 Dynamic Equilibrium, Keq, and the Mass Action Expression The Equilibrium Process Dr. Fred Omega Garces Chemistry 111 Miramar College 1 Equilibrium 05.2015 Concept of Equilibrium & Mass Action Expression Extent of a Chemical Reaction Many reactions do not convert 100% of reactants to products. There is often a point in a reaction when the products will back react to form reactants. The extent of the reaction i.e., 20% or 80%, can be determined by measuring the concentration of each component in solution. In general the extent of the reaction is a function of: Temperature, Concentration and degree of organization which is monitored by some constant value called the - The equilibrium constant (Keq). 2 Equilibrium 05.2015 (Dynamic) Equilibrium Chemical Equilibrium is a dynamic state in which the rates of the forward and the reverse reaction are equal. A teeter-totter is an analogy of a system in balance. The left is balanced with the right. In a chemical reaction this means that the Left (reactant) is changing at the same rate as the right (products). Reactant Product 3 Equilibrium 05.2015 How Equilibrium is achieved Consider the reaction A → B Forward A → B rate = kf[A] Reverse B → A rate = kr[B] Overall A D B rate forward (kf[A]) = rate reverse (kr[B]) Example: N2O4 + E D 2 NO2 Effect of temperature on the N2O4/NO2 equilibrium. The tubes contain a mixture of NO2 and N2O4 . As predicted by Le Chatelier’s principle, the equilibrium favors colorless N2O4 at lower temperatures, but shifts to the darker brown NO2 at higher temperature. -
Geochemical Modeling, Reactive Transport
CO2 SEQUESTRATION IN SALINE AQUIFER: GEOCHEMICAL MODELING, REACTIVE TRANSPORT SIMULATION AND SINGLE-PHASE FLOW EXPERIMENT by BINIAM ZERAI Submitted in partial fulfillment of the requirements For the degree of Doctor of Philosophy Dissertation Advisors: Dr. B. Saylor and Dr. J. Kadambi Department of Geological Sciences CASE WESTERN RESERVE UNIVERSITY January, 2006 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the dissertation of ______________________________________________________ candidate for the Ph.D. degree *. (signed)_______________________________________________ (chair of the committee) ________________________________________________ ________________________________________________ ________________________________________________ ________________________________________________ ________________________________________________ (date) _______________________ *We also certify that written approval has been obtained for any proprietary material contained therein. Dedicated to My family TABLE OF CONTENTS TABLE OF CONTENTS………………………………………………............................. i LIST OF TABLES……………………………………………………….......................... v LIST OF FIGURES...……………………………………………………………………vii ACKNOWLEDGEMENTS…………………………………………….......................... xii NOMENCLATURE……………………………………………………. .......................xiii ABSTRACT…………………………………………………………….......................xviii INTRODUCTION……………………………………………………… .......................... 1 PART I GEOCHEMICAL MODELING AND REACTIVE TRANSPORT SIMULATION CHAPTER 1: INTRODUCTION -
Math for Biology - an Introduction
Math for Biology - An Introduction Terri A. Grosso Outline Math for Biology - An Introduction Differential Equations - An Overview The Law of Terri A. Grosso Mass Action Enzyme Kinetics CMACS Workshop 2012 January 6, 2011 Terri A. Grosso Math for Biology - An Introduction Math for Biology - An Introduction Terri A. Grosso Outline 1 Differential Equations - An Overview Differential Equations - An Overview The Law of 2 The Law of Mass Action Mass Action Enzyme Kinetics 3 Enzyme Kinetics Terri A. Grosso Math for Biology - An Introduction Differential Equations - Our Goal Math for Biology - An Introduction Terri A. Grosso Outline We will NOT be solving differential equations Differential Equations - An Overview The tools - Rule Bender and BioNetGen - will do that for The Law of us Mass Action This lecture is designed to give some background about Enzyme Kinetics what the programs are doing Terri A. Grosso Math for Biology - An Introduction Differential Equations - An Overview Math for Biology - An Introduction Terri A. Grosso Differential Equations contain the derivatives of (possibly) unknown functions. Outline Differential Represent how a function is changing. Equations - An Overview We work with first-order differential equations - only The Law of Mass Action include first derivatives Enzyme Generally real-world differential equations are not directly Kinetics solvable. Often we use numerical approximations to get an idea of the unknown function's shape. Terri A. Grosso Math for Biology - An Introduction A few solutions. Figure: Some solutions to f 0(x) = 2 Differential Equations - Starting from the solution Math for 0 Biology - An A differential equation: f (x) = C Introduction Terri A. -
Compilation of Kinetic Data for Geochemical Calculations
JNC TN8400 2000-005 JP0055265 Compilation of Kinetic Data for Geochemical Calculations January 2000 3300306 ^ Tokai Works Japan Nuclear Cycle Development Institute T319-1194 Inquiries about copyright and reproduction should be addressed to: Technical Information Section, Administration Division, Tokai Works, Japan Nuclear Cycle Development Institute 4-33 Muramatsu, Tokai-mura, Naka-gun, Ibaraki-ken, 319-1194 Japan PLEASE BE AWARE THAT ALL OF THE MISSING PAGES IN THIS DOCUMENT WERE ORIGINALLY BLANK JNC TN8400 2000-005 January, 2000 Compilation of Kinetic Data for Geochemical Calculations Randolph C Arthur", David Savage2', Hiroshi Sasamoto3' Masahiro ShibataJ\ Mikazu Yui3> Abstract Kinetic data, including rate constants, reaction orders and activation energies, are compiled for 34 hydrolysis reactions involving feldspars, sheet silicates, zeolites, oxides, pyroxenes and amphiboles, and for similar reactions involving calcite and pyrite. The data are compatible with a rate law consistent with surface reaction control and transition-state theory, which is incorporated in the geochemical software package EQ3/6 and GWB. Kinetic data for the reactions noted above are strictly compatible with the transition-state rate law only under far-from-equilibrium conditions. It is possible th'at the data are conceptually consistent with this rate law under both far- from-equilibrium and near-to-equilibrium conditions, but this should be confirmed whenever possible through analysis of original experimental results. Due to limitations in the availability of kinetic data for mineral-water reactions, and in order to simplify evaluations of geochemical models of groundwater evolution, it is convenient to assume local-equilibrium in such models whenever possible. To assess whether this assumption is reasonable, a modeling approach accounting for coupled fluid flow and water-rock interaction is described that can be used to estimate spatial and temporal scale of local equilibrium.