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Entropy quantifying

The most important concept in Information Theory is Shannon s Entropy, which measures the amount of information held in data. Entropy quantifies to what extent... [Pg.86]

This is the result for monatomic fluids and is well approximated by a sum of tliree Lorentzians, as given by the first tliree temis on the right-hand side. The physics of these tliree Lorentzians can be understood by thinking about a local density fluctuation as made up of tliemiodynamically independent entropy and pressure fluctuations p = p s,p). The first temi is a consequence of the themial processes quantified by the entropy... [Pg.724]

It can be seen that a high mp implies either a high enthalpy of melting, or a low entropy of melting, or both. Similar arguments apply to vaporization and the bp, and indicate the difficulties in quantifying the discussion. [Pg.54]

Many of the conventional measures used in studying dynamical systems - power spectra, entropy, Lyapunov exponents, etc. - can in fact be used to quantify the difference among Regimes I-IV ([kaneko89a], [kaneko89c]). [Pg.394]

Continuing with the mini-theme of computational materials chemistry is Chapter 3 by Professor Thomas M. Truskett and coworkers. As in the previous chapters, the authors quickly frame the problem in terms of mapping atomic (chemical) to macroscopic (physical) properties. The authors then focus our attention on condensed media phenomena, specifically those in glasses and liquids. In this chapter, three properties receive attention—structural order, free volume, and entropy. Order, whether it is in a man-made material or found in nature, may be considered by many as something that is easy to spot, but difficult to quantify yet quantifying order is indeed what Professor Truskett and his coauthors describe. Different types of order are presented, as are various metrics used for their quantification, all the while maintaining theoretical rigor but not at the expense of readability. The authors follow this section of their... [Pg.427]

The commercially available software (Maximum Entropy Data Consultant Ltd, Cambridge, UK) allows reconstruction of the distribution a.(z) (or f(z)) which has the maximal entropy S subject to the constraint of the chi-squared value. The quantified version of this software has a full Bayesian approach and includes a precise statement of the accuracy of quantities of interest, i.e. position, surface and broadness of peaks in the distribution. The distributions are recovered by using an automatic stopping criterion for successive iterates, which is based on a Gaussian approximation of the likelihood. [Pg.189]

The second law of thermodynamics introduces a new function of state, the entropy, S, in order to quantify the spontaneity and direction of change for natural systems... [Pg.78]

We have seen that by considering the states of the reactants and products in a chemical reaction we can obtain a qualitative idea of the change in entropy but this can be quantified using the expression AS° = Z S°(products) - Z S (reactants)... [Pg.40]

The Second Law of Thermodynamics is a way of quantifying concepts around entropy, a measure of disorder. [Pg.29]

The mole fractions of labeled water at t = 0 and at equilibrium are noted as Xq and Xoo, respectively (Pig. 4). In the end, the signal of bound water becomes small and difficult to quantify. But, this does not influence the quality of the measured rate constant because the mole fraction at equilibrium, x, is known from the concentration of the metal ion and the coordination number. These experiments can be performed at variable temperature and at variable pressure to obtain activation enthalpies and entropies as well as activation volumes. [Pg.334]

The information content of such bit strings can be usefully quantified in terms of entropy H as defined by... [Pg.177]

Figure 11.5 compares the fluid entropy vectors, whose lengths range from about 0.25 (ideal gas) to about 0.75 (ether). As expected, the entropy vectors exhibit an approximate inverted or complementary (conjugate) relationship to the corresponding T vectors of Fig. 11.3. The length of each S vector reflects resistance to attempted temperature change (under isobaric conditions), i.e., the capacity to absorb heat with little temperature response. The lack of strict inversion order with respect to the T lengths of Table 11.3 reflects subtle heat-capacity variations between isochoric and isobaric conditions, as quantified in the heat-capacity or compressibility ratio... Figure 11.5 compares the fluid entropy vectors, whose lengths range from about 0.25 (ideal gas) to about 0.75 (ether). As expected, the entropy vectors exhibit an approximate inverted or complementary (conjugate) relationship to the corresponding T vectors of Fig. 11.3. The length of each S vector reflects resistance to attempted temperature change (under isobaric conditions), i.e., the capacity to absorb heat with little temperature response. The lack of strict inversion order with respect to the T lengths of Table 11.3 reflects subtle heat-capacity variations between isochoric and isobaric conditions, as quantified in the heat-capacity or compressibility ratio...
The thermodynamic ceiling temperature (26) T for a polymerization is computed by dividing the Afi°polym by the standard entropy of polymerization, A+°polym. The T is the temperature at which monomer and polymer are in equilibrium in their standard states at 25°C (298.15 K) and 101.3 kPa (1 atm). (In the case of p-xylylene, such a state is, of course, purely hypothetical.) The T quantifies the binding forces between monomer units in a polymer and measures the tendency of the polymer to revert back to monomer. In other systems, the T indicates a temperature above which the polymer is unstable with respect to its monomer, but in the case of parylene it serves rather as a means of comparing the relative stability of the polymer with... [Pg.431]

Entropy is also a macroscopic and statistical concept, but is extremely important in understanding chemical reactions. It is written in stone (literally it is the inscription on Boltzmann s tombstone) as the equation connecting thermodynamics and statistics. It quantifies the second law of thermodynamics, which really just asserts that systems try to maximize S. Equation 4.29 implies this is equivalent to saying that they maximize 2, hence systems at equilibrium satisfy the Boltzmann distribution. [Pg.77]

To finalize the development of the aqueous CO2 force field parameters, the C02 model was used in free energy perturbation Monte Carlo (FEP/MC) simulations to determine the solubility of C02 in water. The solubility of C02 in water is calculated as a function of temperature in the development process to maintain transferability of the C02 model to different simulation techniques and to quantify the robustness of the technique used in the solubility calculations. It is also noted that the calculated solubility is based upon the change in the Gibbs energy of the system and that parameter development must account for the entropy/enthalpy balance that contributes to the overall structure of the solute and solvent over the temperature range being modeled [17]. [Pg.348]


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Quantifying Entropy Changes in the Surroundings

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