Skip to main content

O. Chem I Lecture #1: Origin of Matter

Hello Internet, and Welcome to the Organic Chemistry Lecture Series by The Science of Life.  This is the first lecture, so let’s start off at the beginning.  That means let’s start off with the synthesis of the units of chemistry in mother nature, well before either the Earth or Humans were even ever a thing.
The Big Bang happened 14.7 billion years ago.  This was the first instance of space, energy, and time in our universe.  It’s where the universe itself banged into existence.  What caused it is a mystery; nobody knows how it happened.
Notice what was missing from the list: matter.  In the very first seconds of the universe, there was no matter in the universe.  Everything in the universe was on the energy side of the  equation.  After a few minutes of cooling, the energy finally became cool enough (and therefor cool enough) to condense to form matter in the form of quarks and bosons.  The quarks are the building blocks of protons and neutrons required for the nucleus of atoms, and the most well-known of the bosons is the electron which orbits the nucleus of an atom.
As things cooled further, the quarks combined to form mainly protons, and combined with electrons to form Hydrogen atoms in clouds.  Gravity takes over, and eventually, these clouds of hydrogen in otherwise empty space condenses enough to form big balls of gas which eventually starts the process of nuclear fusion.  The second that happens, we call that ball of gas a star.
The nuclear fusion in a star works to convert hydrogen into helium, and helium into the heavier elements.  This includes the carbon which is central to the study of Organic Chemistry.  Eventually the stars begin developing Iron 56, at which point the star begins the march towards fizzling out like the end of a camp fire without any fresh wood.  When this happens, it’s only a matter of time before it goes super-nova, or explodes all of its material into space.  This explosion helps accelerate the condensation of nearby space-clouds into star systems, some of which also include planets.  Because nature is messy like that and not the neat and sterile environment of a lab.
After a few generations of stars, about 4.7 billion years ago, one of these supernova helps condense one of these clouds of gas that we now call “our solar system”.  So that’s an oversimplified version of how all the elements were synthesized by nature.
So that comes to the end of this lecture.  Next time, I will be covering some basic definitions which need to be known before carrying on further into the course.  Subscribe to stay up to date and click on the bell to get notified when I upload new episodes.

Labels

Labels:

Comments

Post a Comment

Popular posts from this blog

Multiple Regression: Basic Statistics Lecture Series Lecture #14

As promised from last time , I am going to cover multiple regression analysis this time.  As mentioned last time, correlation may not imply causation, causation does imply correlation, so correlation is a necessary but insufficient (but still necessary) first step in determining causation.  Since this is a basic statistic lecture series, there is an assumption that matrix algebra is not known to students who take this course, so this section will only be working with the solutions obtained through a program such as Excel , R , SPSS , or MatLab . This is the regression case where there is more than one independent variable, or multiple independent variables, for a single dependent variable.  For example, I mentioned last time that there is a causal correlation between the number of wins a team in the MLB has and the ratio of the runs that team score to the runs that team allowed.  The more runs they scored per run they allowed, the more wins they are likely to hav...
Post a Comment
Read more

Confidence Interval: Basic Statistics Lecture Series Lecture #11

You'll remember last time , I covered hypothesis testing of proportions and the time before that , hypothesis testing of a sample with a mean and standard deviation.  This time, I'll cover the concept of confidence intervals. Confidence intervals are of the form μ 1-α ∈ (a, b) 1-α , where a and b are two numbers such that a<b, α is the significance level as covered in hypothesis testing, and μ is the actual population mean (not the sample mean). This is a the statement of there being a [(1-α)*100]% probability that the true population mean will be somewhere between a and b.  The obvious question is "How do we find a and b?".  Here, I will describe the process. Step 1. Find the Fundamental Statistics The first thing we need to find the fundamental statistics , the mean, standard deviation, and the sample size.  The sample mean is typically referred to as the point estimate by most statistics text books.  This is because the point estimate of the po...
1 comment
Read more

Basics of Statistics Lecture #10: Hypothesis Testing of Proportions

As promised last time , I am going to cover hypothesis testing of proportions.  This is conceptually similar to hypothesis testing from the mean and standard deviation , but the calculations are going to be different. A proportion is the percentage of success in a sample or population, reported in decimal form.  This means that if heads comes up 50% of the time, then it is reported as p=0.50.  Because of this, the calculations are different than that of the mean and standard deviation case from last time.  For instance, when we have proportion data, we don't know the standard deviation of either the sample or the population.  This means that the standard error calculation cannot be performed as typical.  We must instead use a proportion-specific version, which is given by $\sigma_{E}=\sqrt{\frac{p*(1-p)}{n}}$, where p is the proportion and n is the sample size.  If we have the sample size and the number of successes, we can calculate the proporti...
Post a Comment
Read more