The scientific term "ideal gas" describes a scientific notion in which a specific gas is made up of molecules that adhere to one major principal: that no attraction or repellence exists between its molecules. The only possible way molecules of an ideal gas would be able to interact with one another would be through elastic collisions; when they collide with one another or the container’s walls. Other conditions a gas must fulfill in order to be considered “ideal” are that the gas particles must have negligible volume, the particles must be of equal size and they must follow Newton’s 3 laws of motion (Tenny & Cooper, 2021). A law was thus derived in order to coherently predict these gases’ behaviour. Émile Clapeyron introduced the rule in 1834. The ideal gas law can thus be seen as a combination of Charles' law, Avogadro's law, Boyle's law and Gay-Lussac's law. In spite of the fact that no gas has these exact characteristics, the ideal gas law can rather accurately predict how real gases behave at enough low pressures and high temperatures , when very huge distances between molecules and their fast speeds preclude any contact. But when the gas in question is close to its condensation point, or the temperature at which it liquefies, it deviates from obedience to the equation.
This topic peaked my interest since I had already studied it in the Chemistry SL IB course and thus I wondered if its applications might be different in the physics course as both sciences revolve around two different domains. Another reason I was enticed to commence this exploration is the fact that I am a car enthusiast. Not long ago I was surfing the internet when I found a very interesting article that explains how a car’s airbags are deployed during an accident. Airbags were one of the few components in a car which I had no idea on how they operated. Turns out that the ideal gas law governs how these airbags function. The numerous sorts of gases swiftly fill the airbags upon installation, inflating them. An interaction between potassium nitrate and sodium azide results in the nitrogen gas filling the airbags. (Vedantu Content Team, 2022)
The aim of this exploration it thus to investigate how temperature affects pressure in light ideal gases and at a constant volume. To do so, I will be using a computer simulation that models the relationship between the variables in the ideal gas law.
The general gas equation also known as the ideal gas law is essentially a rule that links pressure, volume, temperature, number of moles and the gas constant. Although the law describes an ideal (hypothetical ) gas's behaviour, in many circumstances it closely resembles the behaviour of real gases. ("Ideal gas | Definition, equation, properties, & facts," n.d.)
The equation for ideal gas law is: pv = nrt Equation 1 Where -
p - pressure in pascals ( Pa )
v - volume in ( m3 )
n - quantity of particles in ( mol )
R - ideal gas constant
\( ( 8.31446261815324 ≈ 8.31\frac{ J} {K.mol} )\)
t - temperature in Kelvin ( K )
This equation suggests that grapphing temperature on the X-axis as an independent variable and pressure on the Y-axis as a dependent variable should result in a linear correlation. It can thus be deduced that pressure and temperature share a relationship of proportionality and that the graph would have a gradient of \(\frac{ Nr}{ v} .\)
In order to properly study the connection between temperature and pressure, all other variables present in the equation must be kept constant. Since most real life applications involve “light gases”, this is the option that will be chosen during this simulation.
Because the procedure followed was performed using a computerized simulation, the environmental ramifications of this exploration are practically non-existent. This also applies to the ethical consequences as the usage of this computerized simulation rendered them unsubstantial; no real materials were used and therefore there was no waste and no material loss. Following a simulated procedure also helped in the reduction of random errors as most of the calculations were done by an artifical intelligence system and not by a human.
Apparatus
Temperature ( K ) | Pressure 1 st trial ( kPa ) | Pressure 2 nd trial ( kPa ) | Pressure 3 rd trial ( kPa ) |
---|---|---|---|
275 | 6565 | 6520 | 6565 |
285 | 6776 | 6795 | 6750 |
295 | 7010 | 6985 | 7010 |
305 | 7239 | 7247 | 7236 |
315 | 7514 | 7487 | 7490 |
Temperature ( K ) | Pressure 1 st trial ( kPa | Pressure 2 nd trial ( kPa ) | Pressure 3 rd trial ( kPa ) | Pressure Average | Pressure Uncertainty |
---|---|---|---|---|---|
275 | 6565 | 6520 | 6565 | 6550 | 20 |
285 | 6776 | 6795 | 6750 | 6770 | 20 |
295 | 7010 | 6985 | 7010 | 7.00 x 103 | 10 |
305 | 7239 | 7247 | 7236 | 7240 | 6 |
315 | 7514 | 7487 | 7490 | 7490 | 20 |