Lewis structure of PO3-1 – Simple Method for Lewis Electron Dot Structures

Lewis Structures of the Phosphite Ion (PO₃)^-1

A simple method for writing Lewis electron dot structures is given in a previous article entitled “Lewis Structures and the Octet Rule”. Several worked examples relevant to this procedure were given in previous posts please see the Sitemap - Table of Contents (Lewis Electron Dot Structures).

Another example for writing Lewis structures following the above procedure is given inthis post.

Let us consider the case of the Lewis structures of phosphite ion PO₃^-.

Step 1: The central atom will be the P atom since it is the less electronegative. Connect the atoms with single bonds:

Step 2: Calculate the # of electrons in π bonds (multiple bonds) using formula (1) in the article entitled “Lewis Structures and the Octet Rule”.:

Where n in this case is 4. Where V = (6 + 6 + 6 + 5) – (-1) = 24 , V is the number of valence electrons of PO₃^-1. Therefore, P = 6n + 2 – V = 6 * 4 + 2 – 24 = 2

So, there is one double bond in the molecule.

Step 3 & 4: The resonance structures of PO₃^-1 are as follows:

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Relevant Posts

Simple Method for writing Lewis Electron Dot Structures of the phosphite ion (PO₃)^-1

Lewis structure of hydrogen phosphate HO₄P^-2 – Simple Procedure for Dot structures

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References

1. G.N. Lewis, J.A.C.S, 38, 762-785, (1916)
2. E. C. McGoran, J. Chem. Educ., 68, 19-23 (1991)
3. A.B.P. Lever, J. Chem. Educ., 49, 819-821, (1972)
4. Steven S. Zumdahl, “Chemical Principles” 6th Edition, Houghton Mifflin Company, 2009

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Key Terms

Lewis structures of, simple method for writing Lewis electron dot structures, Lewis electron dot structures, electron dot structures

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Dot| Lewis structure of Chromic Acid H2CrO4

Lewis Electron Dot Structure of

Chromic Acid H₂CrO₄

A simple procedure for writing Lewis electron dot structures is given in a previous article entitled “Lewis Structures and the Octet Rule”. Several worked examples relevant to this procedure were given in previous posts please see the Sitemap - Table of Contents (Lewis Electron Dot Structures).

Another example  for writing Lewis structures following the above procedure is given below.

Let us consider the case of the Lewis electron dot structures of chromic acid H₂CrO₄. Chromic acid is a strong acid and an oxidizing agent. In oxidation reactions, the chromium atom is reduced from the hexavalent to the trivalent state. It is used as an intermediate in chromium plating, as a strong oxidizing agent in organic synthesis, as wood preservative, for the preparation of other chrome chemicals of analytical grade and for the cleaning of laboratory glassware.

How can we draw the Lewis electron dot structures of chromic acid H₂CrO₄?

 

Step 1: Connect the atoms with single bonds.

 

Step 2: Calculate the # of electrons in π bonds (multiple bonds) using  formula (1) in the article entitled “Lewis Structures and the Octet Rule”. 

Where n in this case is 5, excluding the H atoms. Where V = (1 + 6 + 6 + 6+ 6 + 6 + 1) = 32 , V is the number of valence electrons of the molecule.

Therefore, P = 6n + 2 – V = 6 * 5 + 2 – 32  = 0     So, there is no multiple bond in the molecule.

Step 3 & 4: The Lewis resonance structures of chromic acid H₂CrO₄ are as follows:

Statistics| Analysis of Data – Confidence intervals

Most of the time the population mean differs from the mean of each individual sample taken from the population.

Consider the following example where absorbance of a solution containing a known concentration of substance A was determined by U.V./Visible spectrometer. The absorbance of the solution was measured three times during each experiment and the average value, standard deviation s and 2s was calculated (see Table I.1).

Table I.1: Absorbance values measured for a solution A using a U.V./Visible spectrometer. Three consecutive measurements were recorded during each experiment.

The mean values from Table I.1 were plotted in the graph shown in Fig. 1 below and 2s (2 * standard deviation s) is shown for each mean. As can you see, the mean value calculated for the absorbance of A in each experiment (sample of the population) differs from the mean of the population (red line). Please also note that the interval - solid line above and below the mean in each experiment (Fig. 1) -  of  each mean (the range of values the mean can take with a certain probability) does not always contain the population mean (experiments 5, 9, 10, 13).

Fig 1: Absorbance values obtained by measuring a solution of substance A with known concentration C using a U.V/Visible spectrometer. Each point shown on the graph is the mean of three consecutive measurements of the solution of substance A with concentration C.

From the above discussion the following question arises:

How can we assess the accuracy of the population mean? Within wich boundaries the true value of the population mean is contained? 

Such boundaries are called confidence intervals or confidence levels. Confidence intervals in a sense give us the range of values that the population mean can take with a certain degree of confidence – usually 90%, 95% or 99%.

Most of the time we look at 95% confidence intervals but all of them have similar interpretation:

they are limits constructed such that a certain percentage of the time 95% in this case the value of the population mean will fall within these limits.

How can we calculate confidence intervals? 

In order to calculate the confidence interval, we need to know the limits within which 95% of means will fall. If we will assume a normal distribution with a mean = 0 and  s = 1 we can use the z-scores with values between -1.96 and  +1.96 (remember that 95% of z-scores fall between these two values). Remember also that we can convert values to z-scores using the formula:

z = (x - x̅ )/ s                      (1)

If we know that the upper limit will be z = +1.96 then from (1) we get:

(x - x̅ )/ s  = 1.96  and  x =   x̅ + 1.96 * s  (this is the upper boundary – limit)

and

(x - x̅ )/ s  = -1.96  and  x =   x̅ - 1.96 * s  (this is the lower boundary – limit)

Therefore, the confidence interval can easily be calculated once the standard deviation s of the mean and the mean are known. The general form of the confidence interval is given below:

                                                           x =   x̅ ± z_critical * s               (2)

where x is the upper or lower value the mean of the population can take with a certain degree of confidence,  x̅ is the mean value of the population of measurements, z_critical is the z critical value from statistical tables (see Table I.2) at a certain confidence level (usually 95%) and s is the standard deviation of the measurements.

Confidence Level (%)	z-critical value
99	2.58
95	1.96
90	1.645
50	0.675

Table I.2: Critical values of z at different confidence levels