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Non-random two-liquid model

Non-random two-liquid model is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Non-random two-liquid model rather than just read about it. In short: The non-random two-liquid model (abbreviated NRTL model) is an activity coefficient model introduced by Renon and Prausnitz in 1968 that correlates the activity coefficients γ i {\displaystyle \gamma _{i}} of a compound with its mole fractions x i {\displaystyle x_{i}} in the liquid phase concerned. It is frequently applied in the field of chemical engineering to calculate phase equilibria.

Non-random two-liquid model — main illustration
Non-random two-liquid model — illustration

Key takeaways

  • Non-random two-liquid model belongs to physics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Non-random two-liquid model to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Non-random two-liquid model from memory before moving on to harder problems.

Reference excerpt

The non-random two-liquid model (abbreviated NRTL model) is an activity coefficient model introduced by Renon and Prausnitz in 1968 that correlates the activity coefficients γ i {\displaystyle \gamma _{i}} of a compound with its mole fractions x i {\displaystyle x_{i}} in the liquid phase concerned. It is frequently applied in the field of chemical engineering to calculate phase equilibria. The concept of NRTL is based on the hypothesis of Wilson, who stated that the local concentration around a molecule in most mixtures is different from the bulk concentration. This difference is due to a difference between the interaction energy of the central molecule with the molecules of its own kind U i i {\displaystyle U_{ii}} and that with the molecules of the other kind U i j {\displaystyle U_{ij}} . The energy difference also introduces a non-randomness at the local molecular level. The NRTL model belongs to the so-called local-composition models. Other models of this type are the Wilson model, the UNIQUAC model, and the group contribution model UNIFAC. These local-composition models are not thermodynamically consistent for a one-fluid model for a real mixture due to the assumption that the local composition around molecule i is independent of the local composition around molecule j. This assumption is not true, as was shown by Flemr in 1976. However, they are consistent if a hypothetical two-liquid model is used. Models, which have consistency between bulk and the local molecular concentrations around different types of molecules are COSMO-RS, and COSMOSPACE.

Derivation Like Wilson (1964), Renon & Prausnitz (1968) began with local composition theory, but instead of using the Flory–Huggins volumetric expression as Wilson did, they assumed local compositions followed

x 21 x 11 = x 2 x 1 exp ⁡ ( − α 21 g 21 / R T ) exp ⁡ ( − α 11 g 11 / R T ) {\displaystyle {\frac {x_{21}}{x_{11}}}={\frac {x_{2}}{x_{1}}}{\frac {\exp(-\alpha _{21}g_{21}/RT)}{\exp(-\alpha _{11}g_{11}/RT)}}}

with a new "non-randomness" parameter α. The excess Gibbs free energy was then determined to be

G e x R T = ∑ i N x i ∑ j N τ j i G j i x j ∑ k N G k i x k {\displaystyle {\frac {G^{ex}}{RT}}=\sum _{i}^{N}x_{i}{\frac {\sum _{j}^{N}\tau _{ji}G_{ji}x_{j}}{\sum _{k}^{N}G_{ki}x_{k}}}} . Unlike Wilson's equation, this can predict partially miscible mixtures. However, the cross term, like Wohl's expansion, is more suitable for H ex {\displaystyle H^{\text{ex}}} than G ex {\displaystyle G^{\text{ex}}} , and experimental data is not always sufficiently plentiful to yield three meaningful values, so later attempts to extend Wilson's equation to partial miscibility (or to extend Guggenheim's quasichemical theory for nonrandom mixtures to Wilson's different-sized molecules) eventually yielded variants like UNIQUAC.

Equations for a binary mixture For a binary mixture the following functions are used:

… excerpt ends here. Continue reading the full article.

Illustrations

Non-random two-liquid model: VLE of the mixture of chloroform and methanol plus NRTL fit and extrapolation to different pressures
VLE of the mixture of chloroform and methanol plus NRTL fit and extrapolation to different pressures

Worked examples

Example 1 — a first encounter with Non-random two-liquid model

Start with the simplest possible case. Write down what Non-random two-liquid model claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Non-random two-liquid model before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Non-random two-liquid model ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Non-random two-liquid model

In research
Non-random two-liquid model appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Non-random two-liquid model in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Non-random two-liquid model is common in secondary-school and first-year university syllabi. It links to neighbouring topics Engineering thermodynamics, Equations of state, Physical chemistry, so understanding it makes those chapters shorter.
In everyday life
Look for Non-random two-liquid model outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Non-random two-liquid model in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Non-random two-liquid model means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Non-random two-liquid model out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Non-random two-liquid model in simple terms?

The non-random two-liquid model (abbreviated NRTL model) is an activity coefficient model introduced by Renon and Prausnitz in 1968 that correlates the activity coefficients γ i {\displaystyle \gamma _{i}} of a compound with its mole fractions x i {\displaystyle x_{i}} in the liquid phase concerned…

Why does Non-random two-liquid model matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Non-random two-liquid model?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Non-random two-liquid model.

Tags

  • Engineering thermodynamics
  • Equations of state
  • Physical chemistry
  • Thermodynamic models

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