SOLUTIONS of EXERCISES 301 Central Role of Gibbs Energy 301:1
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Chapter 3. Second and Third Law of Thermodynamics
Chapter 3. Second and third law of thermodynamics Important Concepts Review Entropy; Gibbs Free Energy • Entropy (S) – definitions Law of Corresponding States (ch 1 notes) • Entropy changes in reversible and Reduced pressure, temperatures, volumes irreversible processes • Entropy of mixing of ideal gases • 2nd law of thermodynamics • 3rd law of thermodynamics Math • Free energy Numerical integration by computer • Maxwell relations (Trapezoidal integration • Dependence of free energy on P, V, T https://en.wikipedia.org/wiki/Trapezoidal_rule) • Thermodynamic functions of mixtures Properties of partial differential equations • Partial molar quantities and chemical Rules for inequalities potential Major Concept Review • Adiabats vs. isotherms p1V1 p2V2 • Sign convention for work and heat w done on c=C /R vm system, q supplied to system : + p1V1 p2V2 =Cp/CV w done by system, q removed from system : c c V1T1 V2T2 - • Joule-Thomson expansion (DH=0); • State variables depend on final & initial state; not Joule-Thomson coefficient, inversion path. temperature • Reversible change occurs in series of equilibrium V states T TT V P p • Adiabatic q = 0; Isothermal DT = 0 H CP • Equations of state for enthalpy, H and internal • Formation reaction; enthalpies of energy, U reaction, Hess’s Law; other changes D rxn H iD f Hi i T D rxn H Drxn Href DrxnCpdT Tref • Calorimetry Spontaneous and Nonspontaneous Changes First Law: when one form of energy is converted to another, the total energy in universe is conserved. • Does not give any other restriction on a process • But many processes have a natural direction Examples • gas expands into a vacuum; not the reverse • can burn paper; can't unburn paper • heat never flows spontaneously from cold to hot These changes are called nonspontaneous changes. -
Phase Diagrams and Phase Separation
Phase Diagrams and Phase Separation Books MF Ashby and DA Jones, Engineering Materials Vol 2, Pergamon P Haasen, Physical Metallurgy, G Strobl, The Physics of Polymers, Springer Introduction Mixing two (or more) components together can lead to new properties: Metal alloys e.g. steel, bronze, brass…. Polymers e.g. rubber toughened systems. Can either get complete mixing on the atomic/molecular level, or phase separation. Phase Diagrams allow us to map out what happens under different conditions (specifically of concentration and temperature). Free Energy of Mixing Entropy of Mixing nA atoms of A nB atoms of B AM Donald 1 Phase Diagrams Total atoms N = nA + nB Then Smix = k ln W N! = k ln nA!nb! This can be rewritten in terms of concentrations of the two types of atoms: nA/N = cA nB/N = cB and using Stirling's approximation Smix = -Nk (cAln cA + cBln cB) / kN mix S AB0.5 This is a parabolic curve. There is always a positive entropy gain on mixing (note the logarithms are negative) – so that entropic considerations alone will lead to a homogeneous mixture. The infinite slope at cA=0 and 1 means that it is very hard to remove final few impurities from a mixture. AM Donald 2 Phase Diagrams This is the situation if no molecular interactions to lead to enthalpic contribution to the free energy (this corresponds to the athermal or ideal mixing case). Enthalpic Contribution Assume a coordination number Z. Within a mean field approximation there are 2 nAA bonds of A-A type = 1/2 NcAZcA = 1/2 NZcA nBB bonds of B-B type = 1/2 NcBZcB = 1/2 NZ(1- 2 cA) and nAB bonds of A-B type = NZcA(1-cA) where the factor 1/2 comes in to avoid double counting and cB = (1-cA). -
Calculating the Configurational Entropy of a Landscape Mosaic
Landscape Ecol (2016) 31:481–489 DOI 10.1007/s10980-015-0305-2 PERSPECTIVE Calculating the configurational entropy of a landscape mosaic Samuel A. Cushman Received: 15 August 2014 / Accepted: 29 October 2015 / Published online: 7 November 2015 Ó Springer Science+Business Media Dordrecht (outside the USA) 2015 Abstract of classes and proportionality can be arranged (mi- Background Applications of entropy and the second crostates) that produce the observed amount of total law of thermodynamics in landscape ecology are rare edge (macrostate). and poorly developed. This is a fundamental limitation given the centrally important role the second law plays Keywords Entropy Á Landscape Á Configuration Á in all physical and biological processes. A critical first Composition Á Thermodynamics step to exploring the utility of thermodynamics in landscape ecology is to define the configurational entropy of a landscape mosaic. In this paper I attempt to link landscape ecology to the second law of Introduction thermodynamics and the entropy concept by showing how the configurational entropy of a landscape mosaic Entropy and the second law of thermodynamics are may be calculated. central organizing principles of nature, but are poorly Result I begin by drawing parallels between the developed and integrated in the landscape ecology configuration of a categorical landscape mosaic and literature (but see Li 2000, 2002; Vranken et al. 2014). the mixing of ideal gases. I propose that the idea of the Descriptions of landscape patterns, processes of thermodynamic microstate can be expressed as unique landscape change, and propagation of pattern-process configurations of a landscape mosaic, and posit that relationships across scale and through time are all the landscape metric Total Edge length is an effective governed and constrained by the second law of measure of configuration for purposes of calculating thermodynamics (Cushman 2015). -
Chapter 11: Solutions: Properties and Behavior
Chapter 11: Solutions: Properties and Behavior Learning Objectives 11.1: Interactions between Ions • Be able to estimate changes in lattice energy from the potential energy form of Coulomb’s Law, Q Q Cation Anion , in which is lattice energy, is a proportionality constant, is the charge on E = k E k QCation r the cation, Q is the charge on the anion, and r is the distance between the centers of the ions. Anion 11.2: Energy Changes during Formation and Dissolution of Ionic Compounds • Understand the concept of lattice energy and how it is a quantitative measure of stability for any ionic solid. As lattice energy increases, the stability of the ionic solid increases. • Be able to estimate changes in lattice energy from the potential energy form of Coulomb’s Law, Q Q Cation Anion , in which is lattice energy, is a proportionality constant, is the charge on E = k E k QCation r the cation, Q is the charge on the anion, and r is the distance between the centers of the ions. Anion • Be able to determine lattice energies using a Born-Haber cycle, which is a Hess’s Law process using ionization energies, electron affinities, and enthalpies for other atomic and molecular properties. • Be able to describe a molecular view of the solution process using Hess’s Law: 1. Solvent → Solvent Particles where ∆Hsolvent separation is endothermic. 2. Solute → Solute Particles where ∆Hsolute separation is endothermic. 3. Solvent Particles + Solute Particles → Solution where ∆Hsolvation can be endo- or exothermic. 4. ∆Hsolution = ∆Hsolvent separation + ∆Hsolute separation + ∆Hsolvation This is a Hess’s Law thinking process, and ∆Hsolvation is called the ∆Hhydration when the solvent is water. -
Assembly of Multi-Flavored Two-Dimensional Colloidal Crystals† Cite This: Soft Matter, 2017, 13,5397 Nathan A
Soft Matter View Article Online PAPER View Journal | View Issue Assembly of multi-flavored two-dimensional colloidal crystals† Cite this: Soft Matter, 2017, 13,5397 Nathan A. Mahynski, *a Hasan Zerze,b Harold W. Hatch, a Vincent K. Shena and Jeetain Mittal *b We systematically investigate the assembly of binary multi-flavored colloidal mixtures in two dimensions. In these mixtures all pairwise interactions between species may be tuned independently. This introduces an additional degree of freedom over more traditional binary mixtures with fixed mixing rules, which is anticipated to open new avenues for directed self-assembly. At present, colloidal self-assembly into non-trivial lattices tends to require either high pressures for isotropically interacting particles, or the introduction of directionally anisotropic interactions. Here we demonstrate tunable assembly into a plethora of structures which requires neither of these conditions. We develop a minimal model that defines a three-dimensional phase space containing one dimension for each pairwise interaction, then employ various computational techniques to map out regions of this phase space in which the system self-assembles into these different morphologies. We then present a mean-field model that is capable of reproducing these results for size-symmetric mixtures, which reveals how to target different structures by tuning pairwise interactions, solution stoichiometry, or both. Concerning particle size asymmetry, we find Received 19th May 2017, that domains in this model’s phase space, corresponding to different morphologies, tend to undergo a Accepted 30th June 2017 continuous ‘‘rotation’’ whose magnitude is proportional to the size asymmetry. Such continuity enables DOI: 10.1039/c7sm01005b one to estimate the relative stability of different lattices for arbitrary size asymmetries. -
CHAPTER 20: Lattice Energy
CHAPTER 20: Lattice Energy 20.1 Introduction to Lattice Energy 20.2 Born-Haber Cycles 20.3 Ion Polarisation 20.4 Enthalpy Changes in Solutions Learning outcomes: (a) explain and use the term lattice energy (∆H negative, i.e. gaseous ions to solid lattice). (b) explain, in qualitative terms, the effect of ionic charge and of ionic radius on the numerical magnitude of a lattice energy. (c) apply Hess’ Law to construct simple energy cycles, and carry out calculations involving such cycles and relevant energy terms, with particular reference to: (i) the formation of a simple ionic solid and of its aqueous solution. (ii) Born-Haber cycles (including ionisation energy and electron affinity). (d) interpret and explain qualitatively the trend in the thermal stability of the nitrates and carbonates in terms of the charge density of the cation and the polarisability of the large anion. (e) interpret and explain qualitatively the variation in solubility of Group II sulfates in terms of relative magnitudes of the enthalpy change of hydration and the corresponding lattice energy. 20.1 Introduction to Lattice Energy What is lattice energy? 1) In a solid ionic crystal lattice, the ions are bonded by strong ionic bonds between them. These forces are only completely broken when the ions are in gaseous state. 2) Lattice energy(or lattice enthalpy) is the enthalpy change when one mole of solid ionic lattice is formed from its scattered gaseous ions. 3) Lattice energy is always negative. This is because energy is always released when bonds are formed. 4) Use sodium chloride, NaCl as an example. -
Interval Mathematics Applied to Critical Point Transitions
Revista de Matematica:´ Teor´ıa y Aplicaciones 2005 12(1 & 2) : 29–44 cimpa – ucr – ccss issn: 1409-2433 interval mathematics applied to critical point transitions Benito A. Stradi∗ Received/Recibido: 16 Feb 2004 Abstract The determination of critical points of mixtures is important for both practical and theoretical reasons in the modeling of phase behavior, especially at high pressure. The equations that describe the behavior of complex mixtures near critical points are highly nonlinear and with multiplicity of solutions to the critical point equations. Interval arithmetic can be used to reliably locate all the critical points of a given mixture. The method also verifies the nonexistence of a critical point if a mixture of a given composition does not have one. This study uses an interval Newton/Generalized Bisection algorithm that provides a mathematical and computational guarantee that all mixture critical points are located. The technique is illustrated using several ex- ample problems. These problems involve cubic equation of state models; however, the technique is general purpose and can be applied in connection with other nonlinear problems. Keywords: Critical Points, Interval Analysis, Computational Methods. Resumen La determinaci´onde puntos cr´ıticosde mezclas es importante tanto por razones pr´acticascomo te´oricasen el modelamiento del comportamiento de fases, especial- mente a presiones altas. Las ecuaciones que describen el comportamiento de mezclas complejas cerca del punto cr´ıticoson significativamente no lineales y con multipli- cidad de soluciones para las ecuaciones del punto cr´ıtico. Aritm´eticade intervalos puede ser usada para localizar con confianza todos los puntos cr´ıticosde una mezcla dada. -
Chemistry C3102-2006: Polymers Section Dr. Edie Sevick, Research School of Chemistry, ANU 5.0 Thermodynamics of Polymer Solution
Chemistry C3102-2006: Polymers Section Dr. Edie Sevick, Research School of Chemistry, ANU 5.0 Thermodynamics of Polymer Solutions In this section, we investigate the solubility of polymers in small molecule solvents. Solubility, whether a chain goes “into solution”, i.e. is dissolved in solvent, is an important property. Full solubility is advantageous in processing of polymers; but it is also important for polymers to be fully insoluble - think of plastic shoe soles on a rainy day! So far, we have briefly touched upon thermodynamic solubility of a single chain- a “good” solvent swells a chain, or mixes with the monomers, while a“poor” solvent “de-mixes” the chain, causing it to collapse upon itself. Whether two components mix to form a homogeneous solution or not is determined by minimisation of a free energy. Here we will express free energy in terms of canonical variables T,P,N , i.e., temperature, pressure, and number (of moles) of molecules. The free energy { } expressed in these variables is the Gibbs free energy G G(T,P,N). (1) ≡ In previous sections, we referred to the Helmholtz free energy, F , the free energy in terms of the variables T,V,N . Let ∆Gm denote the free eneregy change upon homogeneous mix- { } ing. For a 2-component system, i.e. a solute-solvent system, this is simply the difference in the free energies of the solute-solvent mixture and pure quantities of solute and solvent: ∆Gm G(T,P,N , N ) (G0(T,P,N )+ G0(T,P,N )), where the superscript 0 denotes the ≡ 1 2 − 1 2 pure component. -
Study of the LLE, VLE and VLLE of the Ternary System Water + 1-Butanol + Isoamyl Alcohol at 101.3 Kpa
View metadata, citation and similar papers at core.ac.uk brought to you by CORE Submitted to Journal of Chemical & Engineering Data provided by Repositorio Institucional de la Universidad de Alicante This document is confidential and is proprietary to the American Chemical Society and its authors. Do not copy or disclose without written permission. If you have received this item in error, notify the sender and delete all copies. Study of the LLE, VLE and VLLE of the ternary system water + 1-butanol + isoamyl alcohol at 101.3 kPa Journal: Journal of Chemical & Engineering Data Manuscript ID je-2018-00308r.R3 Manuscript Type: Article Date Submitted by the Author: 27-Aug-2018 Complete List of Authors: Saquete, María Dolores; Universitat d'Alacant, Chemical Engineering Font, Alicia; Universitat d'Alacant, Chemical Engineering Garcia-Cano, Jorge; Universitat d'Alacant, Chemical Engineering Blasco, Inmaculada; Universitat d'Alacant, Chemical Engineering ACS Paragon Plus Environment Page 1 of 21 Submitted to Journal of Chemical & Engineering Data 1 2 3 Study of the LLE, VLE and VLLE of the ternary system water + 4 1-butanol + isoamyl alcohol at 101.3 kPa 5 6 María Dolores Saquete, Alicia Font, Jorge García-Cano* and Inmaculada Blasco. 7 8 University of Alicante, P.O. Box 99, E-03080 Alicante, Spain 9 10 Abstract 11 12 In this work it has been determined experimentally the liquidliquid equilibrium of the 13 water + 1butanol + isoamyl alcohol system at 303.15K and 313.15K. The UNIQUAC, 14 NRTL and UNIFAC models have been employed to correlate and predict LLE and 15 16 compare them with the experimental data. -
Chapter 9: Other Topics in Phase Equilibria
Chapter 9: Other Topics in Phase Equilibria This chapter deals with relations that derive in cases of equilibrium between combinations of two co-existing phases other than vapour and liquid, i.e., liquid-liquid, solid-liquid, and solid- vapour. Each of these phase equilibria may be employed to overcome difficulties encountered in purification processes that exploit the difference in the volatilities of the components of a mixture, i.e., by vapour-liquid equilibria. As with the case of vapour-liquid equilibria, the objective is to derive relations that connect the compositions of the two co-existing phases as functions of temperature and pressure. 9.1 Liquid-liquid Equilibria (LLE) 9.1.1 LLE Phase Diagrams Unlike gases which are miscible in all proportions at low pressures, liquid solutions (binary or higher order) often display partial immiscibility at least over certain range of temperature, and composition. If one attempts to form a solution within that certain composition range the system splits spontaneously into two liquid phases each comprising a solution of different composition. Thus, in such situations the equilibrium state of the system is two phases of a fixed composition corresponding to a temperature. The compositions of two such phases, however, change with temperature. This typical phase behavior of such binary liquid-liquid systems is depicted in fig. 9.1a. The closed curve represents the region where the system exists Fig. 9.1 Phase diagrams for a binary liquid system showing partial immiscibility in two phases, while outside it the state is a homogenous single liquid phase. Take for example, the point P (or Q). -
Calculating Lattice Energies Using the Born-Haber Cycle an Extension Activity for AP Chemistry Students
Calculating Lattice Energies Using the Born-Haber Cycle An Extension Activity for AP Chemistry Students A particular set of equations known as a Born-Haber cycle demonstrates how chemists are able to use the first law of thermodynamics—that the energy of the universe is conserved in any chemical or physical change—to find an unknown energy value that is difficult or impossible to measure experimentally. Some energy quantities, such as the lattice energy of a mineral or the electron affinity of an atom, can be difficult to measure in the lab. Examining a Born-Haber cycle we see that there is more than one path to the formation of a substance in a particular state, and that if we use consistent definitions, an energy value that we seek can be calculated from energy values that we already know. The following exercise will help us see the way these energy values relate to one another, give us practice with their definitions and symbols, and deepen our insight to their meaning when we see them in other types of problems. Each physical or chemical change represented has: • an equation that represents a clearly defined physical or chemical change; • a definition of the particular type of energy change; • a symbol or abbreviation for the energy change equal to a value for the change in enthalpy (ΔH), the energy that is released or absorbed during the change, expressed in kJ/mol; and • a name by which that change in enthalpy is commonly known. To set up the equations in a Born-Haber cycle, cut out the cards for names, equations, defini- tions, and symbols with energy values. -
Lecture 6: Entropy
Matthew Schwartz Statistical Mechanics, Spring 2019 Lecture 6: Entropy 1 Introduction In this lecture, we discuss many ways to think about entropy. The most important and most famous property of entropy is that it never decreases Stot > 0 (1) Here, Stot means the change in entropy of a system plus the change in entropy of the surroundings. This is the second law of thermodynamics that we met in the previous lecture. There's a great quote from Sir Arthur Eddington from 1927 summarizing the importance of the second law: If someone points out to you that your pet theory of the universe is in disagreement with Maxwell's equationsthen so much the worse for Maxwell's equations. If it is found to be contradicted by observationwell these experimentalists do bungle things sometimes. But if your theory is found to be against the second law of ther- modynamics I can give you no hope; there is nothing for it but to collapse in deepest humiliation. Another possibly relevant quote, from the introduction to the statistical mechanics book by David Goodstein: Ludwig Boltzmann who spent much of his life studying statistical mechanics, died in 1906, by his own hand. Paul Ehrenfest, carrying on the work, died similarly in 1933. Now it is our turn to study statistical mechanics. There are many ways to dene entropy. All of them are equivalent, although it can be hard to see. In this lecture we will compare and contrast dierent denitions, building up intuition for how to think about entropy in dierent contexts. The original denition of entropy, due to Clausius, was thermodynamic.