Honors Chemistry Lab and Discussion by mifei


									                                 Chemistry Lab and Discussion
                                   Chem-111A-05 Fall 2007

Professor: Dr. Ka Yee C. Lee
TA: Chris Morong
E-mail: cmorong@uchicago.edu (e-mail before 10:00 PM to ensure a response that day)
Webpage:       http://fermi.uchicago.edu/~morong
Office : Jones 023
Office Phone: 2-7262
Office Hours: TBA and by appointment (Usually available 9 AM to 5 PM weekdays)
               10:00-11:00 AM Fishbowl

Discussion: Thursdays 3:30 – 4:20 PM – Kent 103
Laboratory: Tuesdays 1:30 – 5:20 PM – Kent 201

There will be seven labs for this quarter each having a maximum of 100 points.
        25% – Hand in signed data sheet at end of lab, includes doing pre-lab assignment,
                and table setup
        75% – Actual lab write up, results, and conclusions
Also 100 points will be given at the end of the quarter by me at my discretion based on your
attendance, promptness, participation, safety compliance, lab cleanliness, completion of
assignments, and how you advanced over the quarter.
        The lab will be due one week after the completion of the experiment. Each working day
(weekends don’t count) the lab is late, 5 points will be taken off. That’s 25 points per week, up
to a maximum of 50 points. After three weeks late, I don’t take it anymore. (This is UC’s rule,
not mine!)
        Think about this. Will you be able to improve the quality of the lab report enough to
offset the point deduction? If you haven’t started, then the answer would be yes. If you’re near
completion, maybe not. It’s your responsibility to hand in the labs and pre labs on time. Don’t
lose easy points. Start writing the report early.
        To help allay fears that I’m too hard (or too easy) of a grader compared to the other
sections, the grades of all the sections will be collected together at the end of the quarter and
normalized, thereby eliminating grader differences.
        If you have a complaint on the grade, put your reasons in writing and give them to me
with the lab report. I will evaluate your reasoning and make the decision on whether or not to
increase or decrease the grade.

         Safety is an essential part of the laboratory experience. Even if you are the safest person
in the lab and follow the directions, you must still wear the goggles, apron and gloves. Although
these experiments are not dangerous when performed correctly, you must be prepared for
anything. Also you must not assume that your lab mates are as safe as you. An accident that you
did not cause could still affect you. More of UC’s safety rules are present in the lab manual and
will be discussed at the safety orientation.
       You must have a graphing calculator capable or performing linear regression and you
must know how to use it in lab. If you don’t know how, look in your calculator manual.

Lab Notebook:
        The lab notebook is your record of what you did during your experiment. The notebook
should not be just a collection of data tables. It should have the experiment title, what
phenomena you hope to observe, where the data is coming from, your observations (color
observation, heat evolution, etc.). The self copying notebooks are available in the bookstore. It
should be written so that it is legible and someone or you five years later still could repeat your
experiment. Sign and date each experiment and page. It does not have to be neat and perfect. If
you make an error, simply put a line through it, don’t scribble it out or erase it. Put a table of
contents in the front.
        Before the lab, do the prelab and write any necessary tables as explained in the
experiment. The prelabs are due when you enter the lab. Summarize the experiment, materials,
and weights you will need. This will save time so you don’t have to read through the lab manual
during the experiment and run the risk of missing something. The yellow/blue copy pages of
your lab notebook (the signed data sheet) are due when you leave.

Sample lab report summary:
       You may collaborate with each other for the interpretation of results and drawing of
conclusions but Each lab report must be written individually!!!!!!!!
You need these parts. Additional subsections can be added if they are needed. See the end of the
each lab for hints on what should be included.

                                   The Copper Cycle  Title

                                         Your name
                                   Your lab partner’s name
                      Department of Chemistry, The University of Chicago
                                     Date of Experiment

        Short! summary of the experiment. No more than 100 words. Make it interesting so I
want to read the rest of the report. If this were a paper for submission, many times only the
abstract is used for searching, or is available to read. Hence the Chemical Abstracts Service
(CAS). Include what you did, how you did it, and any results that you obtained. For example:
        “We discuss the physical nature of a remarkably faint pair of Lyman alpha-emitting
images discovered close to the giant cD galaxy in the lensing cluster Abell 2218 (z=0.18) during
a systematic survey for highly-magnified star-forming galaxies beyond z=5. [What you did] A
well-constrained mass model suggests the pair arises via a gravitationally-lensed source viewed
at high magnification. [Why you did it] Keck spectroscopy confirms the lensing hypothesis and
implies the unlensed source is a very faint (I~30) compact (<150 pc) and isolated object at
z=5.576 whose optical emission is substantially contained within the Lyman alpha emission line;
no stellar continuum is detectable. [Results] The available data suggest the source is a promising
candidate for an isolated ~10^6 solar mass system seen producing its first generation of stars
close to the epoch of reionization.” [Conclusions] [astro-ph/0109249] Reference!
       Give an overview of the theory behind the experiment, what you hope to observe. Place
for chemical equations, mathematical manipulations, and the technique used (if applicable).
Number the equations, both mathematical and chemical. Expand upon the abstract, but not the
Results and Conclusions.

        I won’t make you rewrite the experimental procedure that’s in the lab manual. You can
simply reference the lab manual, and page numbers. However, if there is some change in the
procedure, this must be included. Changes in procedure include, but are not limited to,
something I tell you and some “error” you made during the experiment. I know that you are not
professional chemists and will make errors. Honestly report your errors, be it spills, weight
differences, or whatever.

                                            Data Analysis:
        You do not need to list all the data you took down. I have that from your lab book copy.
Only the relevant data is needed, i.e. list the weight recovered, not the crucible weight and the
crucible weight + product.
        You can manipulate (not fudge) the numbers and graph them. If there is a table in the
experimental procedure, this is the place to put it with a caption [Table 1 - …]. If you make a
graph, put a caption [Figure 1 - …]. Tables and Figures need to be referenced in the text. For
“Through the use of Eq. (1), the data in Table 1 can be plotted in Figure 2 yielding a linear fit.”
        Many of the labs will require statistics of some kind. You need to know how to do linear
regression and propagation of errors on the computer (MS Excel, or some other program you’re
familiar with) and your graphing calculator. If you are unsure, open your manual, or ask a friend
who knows. If you are still unsure, ask me.
        Give me the linear fit equation with proper units, or if that is too long, give the equation
with the coefficients listed afterwards. The propagation of errors will usually give you an idea of
how many significant figures you will need. The calculator may give you 10 digits, but how
many of them can you trust? I have included how to calculate least squares errors.

        Do the results make sense? Do the values agree with the accepted numbers? If not, why
not? This is the thinking section. Anyone can mix chemicals together and take data points, but
can you interpret your observations correctly? Do you see a connected area? If the results are
off, make a better explanation than “human error”. Even though that may be the largest source
of error in these experiments, give ways on how the experiment could be improved to remove
“human error.”

        The labs have a few questions for you to answer at the end of the lab based on what you
just did. Answer these to the best or your ability.

        Although not required, I certainly encourage you to look at outside references (besides
the text book and lab manual!) when you do a lab report, such as journals, internet (but beware of
the website sources like Wikipedia), other books, chemical handbooks, etc. This is where you
list them so you don’t have to worry about plagiarism.

General points:
    When writing a lab report, don’t use I or we. Example
      Don’t – “I added 9 g of naphthalene to the cyclohexane.”
      Do – “Add 9 g of naphthalene to the cyclohexane.” Or
              “9 g of naphthalene was added to the cyclohexane.” Or
              “The naphthalene was added to the cyclohexane.” (If a table is present)
    Keep your tenses straight. Don’t jump from past, present, and future tenses.
    Have continuity between sentences. Do the ideas and formulas make a general logical
    Use a computerized word processor (MS Word, Abiword, or Latex for the adventurous).
      Put the equations, super/sub scripts, pictures, graphs, and tables in the document. You
      are going to have to do this eventually, so learn now.
    If for some reason you cannot print, e-mail it to me.
    Make the section headings in bold and centered
    Use standard paper with a 12 pt Times New Roman Font and double sided if possible

                            Function                   Uncertainty
                            y  x1  x2               e y  e x1  e x2
                                                              2      2

                            y  x1  x2               e y  e x1  e x2
                                                              2      2

                             y  x1x2               %e y  %ex1  %ex2
                                                             2      2

                              y                    %e y  %ex1  %ex2
                                                             2      2
                              y  xa                   %ey  a%ex
                                                        1 ex            e
                             y  log x         ey              0.43429 x
                                                      ln 10 x            x
                              y  ln x                     ey  x
                              y  10 x               (ln 10)ex  2.6026ex
                              y  ex                        ex
   Summary of rules for propagation of uncertainty [Daniel Harris, Quantitative Chemical
   Analysis, 5th Ed. (1999) p.63]

   Consider difference between weights (use absolute uncertainty)
                   Crucible                        12.3654  0.0002 g
                   Crucible + dried sample         15.1256  0.0002 g
                   Dried sample                     2.7602  ey     g
                              e y  0.0002 2  0.0002 2  0.0003

Consider ratio of pressures (use relative or percent uncertainty)
                Atmospheric                        760.0  0.5 mm Hg
                Vacuum                             200.0  0.5 mm Hg
                Atmospheric/Vacuum                  3.80  ey
                                                      2                 2
                                ey      0.5          0.5 
                   %e y  100 *  100 *       100 *       0.259
                                 y      760          200 
                        %e y * y
                   ey            0.01

Consider pH and [H+]

                 pH                                  5.21  0.03
                 [H+]=10-pH                          6.2 10-6  ey M
                                      2.3026 * (0.03)  0.0691
                                e y  (10 5.21 )0.0691  0.4  10 6
Express [H+] as (6.20.4)10-6 M or 6.2(0.4)10-6 M.

Least Squares Slope and Intercept Errors
    You have N data points, xi and yi. In this version of least squares xi is assumed to have no
error, and yi is assumed to have an error. More sophisticated treatments where both xi and yi
have error exist, but won’t be considered here.
Start with an equation of a straight line
                                            y  mx  b                                   (1)
The difference between the data point and the best fit line is
                                      yi  y  yi  (mxi  b)
To eliminate the sign of the difference (+/-) the sum of the squares is used
                                      S   ( y i  mxi  b) 2                          (3)
                                          i 1
The errors are minimized by taking the first derivative and setting it to zero.
                                        S S                                           (4)
                                                  0
                                        m b
Also to guarantee we are at a minimum, the second derivative needs to be positive
                                   2S            2S
                                          0 and        0                              (5)
                                   m 2            b 2
After applying the boundary conditions, Eqs. (4-5), to Eq. (3), we arrive at a set of
simultaneous equations which are best visualized as the determinant of a matrix.
   The m and b coefficients are solved to yield
                                        (x y )  x
                                         1          i           i                   i       (6)
                                         D       N          i

                                     1  (x )  (x y )

                                  b                i                           i       i   (7)
                                     D x       y  i                               i


                                              (x )  x 2
                                                        i                       i           (8)
                                             x      N  i

The above notation is taking the determinant of a 22 matrix
                                       e f
                                               eh  fg                                     (9)
                                       g h
Now the error in the slope and intercept can be found using

                                                            N                               (10)
                                       em  s y

                                       eb  s y
                                                             (x        2
                                                                        i   )               (11)

                                             (y    i        mxi  b) 2                    (12)
                                  sy        i 1

                                                        N 2

Finally the answer can be expressed as
                                      y  (m  em ) x  (b  eb )                       (13)
For several experiments, the slope and intercept contain information about thermodynamical
quantities. This is very important for the determination of the accuracy of your experimental
     For least squares fitting to higher order polynomials, the same procedure in Eqs. (2-5)
with appropriately expanded boundary conditions, can be used which results in a larger
matrix and is more conveniently done using a computer program. For nonlinear least squares
fitting using an exponential, logarithmic, trigonometric, or other non-polynomial function,
the same procedure in Eqs. (2-5) can also be used, but the resulting equations will most likely
be coupled and impossible to solve analytically, so an iterative routine is needed.

An Excel Spreadsheet doing the errors for a linear regression can be found on my webpage.

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