As long as it’s negative, the system - such as a chemical reaction - can start spontaneously. It’s enthalpy (heat) minus the product of temperature and entropy. The free energy of a system can be used to perform physical work (to move things). In short, Gibbs’ free energy formula tells us if a process will happen spontaneously, or not. And in nature, quite like in finances, nothing happens unless you pay for it (with free energy).īringing us neatly to: Gibbs’ Free Energy Some probabilities are more likely than others - which is our statistical entropy - because they lead to simpler, more homogenous systems by transforming energy - our physical entropy. A glass filled half with ice and half with boiling water has a higher imbalance and a lower entropy than a glass where they’re mixed - so they do. The ice takes more data to make it what it is, it’s more complicated, so it’s less probable.Įntropy also moves things along towards low states of energy (including potential energy) because spontaneous processes tend to work towards fixing imbalances and thus expending energy. For the glass of water, all you need to do is define the shape of the glass and how high you’re filling it because its molecules move in an undefinable manner. If you were to simulate a glass of it, you’d have to program their molecular composition, shape, size, and position relative to one another. Molecules in ice are kept in a very specific arrangement, forming a lattice that we perceive as ice cubes. Nature loves that.Ī glass of ice is more orderly than a glass of water. The meat of it is that randomness is simple and low on energy. We all instinctively understand that disorder is more likely than order, but why? However, overall, entropy in a system increases over time, because changes towards disorder are overwhelmingly more likely than those towards order. Josiah Willard Gibbs, an American engineer from the early 1900’s even found a way to calculate why (more on that later). Spontaneous reductions in entropy are possible, such as the formation of life or crystals. Ordered systems break down over time because there’s a single microstate in which they stay the same, and countless in which they change. This statistical understanding of the term is rooted in the physical definition of entropy, and I’m simplifying things a lot, but I feel it’s the best rough idea of how it works.Ĭastles grow moss and crumble, heels snap off of shoes. Because of that, the heads-and-tails sequence is the one with the highest entropy. All are possible, but one outcome (a sequence of heads and tails) has a 1 in 2 chance of happening, while the others have a 1 in 4. Flip it two times, however, and you get four possible microstates - alternating heads and tails, two heads, or two tails. Its macrostate is its shape, size, color, temperature. Entropy is a way of quantifying how likely the system’s current microstate is.Ī coin is a very good analogy. Each arrangement (each microstate) has a chance of ‘happening’. Microstates define the arrangement of all molecules within that system and how they interact. ProbabilityĮach system has a macrostate (its shape, size, temperature, etc) and several microstates. ![]() To get more specific about this concep, we’ll have to look at physics and probability. Both this example and the equation with disorder have some flaws, as we’ll see later on, but they’re descriptive enough that they’re a good starting point.
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