Factors that determine the coefficient of linear expansion

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SUMMARY

The coefficient of linear expansion (α) is influenced by factors such as atomic separation, density, molecular bond strength, and material rigidity. Soft metals like aluminum exhibit higher α values compared to denser metals like steel, which have lower expansion rates. The discussion highlights that the relationship between thermal expansion and density, stiffness, and melting temperature is generally inversely correlated, with stronger molecular bonds leading to reduced thermal expansion. Additionally, the relationship between thermal conductivity and α remains complex and requires further investigation.

PREREQUISITES
  • Understanding of thermal expansion principles
  • Familiarity with atomic structure and molecular bonds
  • Knowledge of material properties such as density and stiffness
  • Basic grasp of thermal conductivity concepts
NEXT STEPS
  • Research the relationship between molecular bond strength and thermal expansion coefficients
  • Explore the effects of density and stiffness on thermal expansion in various materials
  • Investigate the correlation between thermal conductivity and the coefficient of linear expansion
  • Examine experimental methods for measuring thermal expansion in solids
USEFUL FOR

Material scientists, mechanical engineers, and students studying thermodynamics or materials science will benefit from this discussion, particularly those interested in the properties of metals and ceramics.

philip012
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ΔL=LαΔT

The concept is interesting and applying its formula isn't even tedious, but what are the real factors that determine α here? I understand that thermal expansion is a direct consequence of the average separation between atoms. And that the coefficient can be found through different experiments. But I want to understand why different solids have different coefficients.

I think my strongest insight is that α value must be somehow inversely proportional to a solid's density. So we have soft metals like aluminum with high values of α and epoxy with twice that of alumn. And then we have dense metals like steel that don't really expand that much. Titanium is one of the hardest metals I've worked with and its coefficient α is very low. Is there a strong relationship between these two? Or is there a factor more relevant?
 
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I would probably guess that the strength of the molecular bonds is a better predictor of thermal expansion. Of course, stronger molecular bonds go somewhat hand in hand the more rigid the object is, and thus solids would have less expansion.
 
rumborak said:
I would probably guess that the strength of the molecular bonds is a better predictor of thermal expansion.

Agreed. Since thermal expansion in ceramics and metals is primarily dependent on the shape of the atomic pair potential and its depth, the coefficient of thermal expansion in these materials is generally inversely correlated with the density, the stiffness, and the melting temperature, all of which tend to increase with bond strength.
 
I don't think it's simple. Here's the coefficient of thermal expansion for Fe/Ni alloys as the Ni composition varies. Note the sharp minimum at 36%.

350px-Invar-Graph-CTE-composition.svg.png
 
Oh, definitely. My link shows only the trend for elements, and even then the correlation isn't absolute. With ferritic alloys, you're going to get some coupling with magnetism that could complicate things tremendously. (Or let you design a cool low-thermal-expansion material, depending on how you look at it!)
 
Really good stuff, thanks a bunch. Just a very subtle follow-up question on this...
how does thermal conductivity relate to this coefficient? Does it have to do with its density, stiffness, melting temp like Mapes noted or molecular bonds like Rumborak suggested?
When i a build a chart, there doesn't seem to be any, proportional or not, relationship..
metal / a / k
iron / 12 / 0.163
copper/ 16.6 / 0.99
Alum / 22.2 / 0.50

It's a very small sample, but it already prevents any kind of linear relationship.. When I manipulate the formulas "ΔL=LαΔT" and "k = (Q*L) / (A*ΔT*Δt)", there definitely is some kind of inverse proportionality inherent, but the could the other variables be weighted more resulting in my skewed chart?
 
Is there a specific reason why you would think the two are related? I mean, two values not being related is probably more the norm than the exception.
 
Only because I have a lab question that asks what the relationship between the two is.. But yeah, to digress more, when I had manipulated the two formulas "ΔL=LαΔT" and "k = (Q*L) / (A*ΔT*Δt)", I ended up with a single equation that was obnoxiously hairy where, while "k" was on one side and "1/α", there was just too many other variables that affected the relationship..
 
philip012 said:
Only because I have a lab question that asks what the relationship between the two is.
Then such a question needs to be asked in the homework forum, with an attempt at a solution.

Thread closed.
 

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