computer mrie~,79 Using "Electronic Laboratory Notebook Software in the Instrumental Analysis Course Michael F. Delaney Boston University Boston. MA 02215
As computerized instrumentation continues to permeate the analytical laboratory, it is incumbent upon instructors of chemical analysis courses a t all levels to incorporate these developments into the curriculum. Perhaps even more critical than the availability of up-to-date instructional equipment is the need for the students to gain an understanding of the orocess of eoine" from raw exoerimental data to final chemical results and conclusions. While practicing chemists mav not he called unon to desien and build com~uterized eq;ipment, they would be expected to be able to design exneriments. as well as correctlv Drocess and interpret the .. corresponding data and results. In a response to this need, we have incorporated "electric laboratory notebook" (ELN) software into our instrumental analysis course, as well as several other courses (physical chemistry, quantum chemis. . try, and chemometrics). This paper wili simmarize our experience and present some of the student-generated results. The partic& software by amhich our inctrumental ansly&wurst- ia assited is the RS/1 package, available from Bolt Reranek snrl Yrwman Software Products CWI. t 10 Fawcett St., Cambridge, MA 02138). While we have'been using a VAX-750 computer (Digital Equipment Corp.) in an extensive Ethernet network, RSI1 is also available for the DEC PRO-350 and PRO-380 personal computers and more reccntlv for the l H l l l'C'.'l'his hardware c~on~patihilitv and the extensi5.e Dower uf ltS11 make it a leader in K1.N. This i~aper will not address the full range of RSIl's features, hut rather will focus on how we have used ELN software in our course. We should also mention that while RSI1 is not the only ELN-type pakage on the market, it is one of the few systems designed specifically for the scientist. For this reason, we have found it to be especially useful in chemistry courses. The uses of ELN software for our instrumental course can he organized into three sections: analytical concepts, statistical techniaues. We will . . and lahoratorv. experiments. . present examples from each of these areas. These are certainly not all-encompassing, and are probably not nearly even optimal, hut they do serve to illustrate the possibilities. This paper is primarily based on graphical examples, largely generated by students in the instrumental course, as these are the most expediently conveyed. Other examples of RSI1 usage from th& laboratory can be seen in a recent hook chapter ( I ) , a discussion of chromatographic calibration (Z), and also huried in some of our research r e ~ o r t (3). s includine statistical data analysis performed for studies conducted a t the U S . Food and Drug Administration's Winchester Engineering and Analytical Center (4). We have also used RSI1 for compiling and using a database of Chemometrics litera~~~~
.~~~~~~~ ~
edited by JOHN W. MOORE Eastern Michigan university, ypsilanti, 4 m 7
ture, an exciting application we plan to describe in a later publication. The R S l l Phllosophy A few comments on the style and organization of RS11 will, it is hoped, convey the flavor of the interactions between the scientist and RS11. RSI1 stores all information in tables: data are in tables, graphs are generated from tables, device communication is controlled by tables, etc. Tables are comprisedof rows and columns; the intersection of a row and a column is called a table cell. A cell can contain anything from a number to an entire procedure or pages of text. RSI1 understands a restricted, stylized English vocabulary. Once one gains a minimum of experience, the correct command structure is fairly obvious. For example, FIT LINE TO CURVE 2 OF mygraph
will begin the curve-fitting process, which is complete with a statistical analysis, while SET COL 3 = COL 1&OS (COL 2)
transforms an entire column of a table. The goal is to have the commands make sense, to take advantage of context, and to avoid the need for the user to write computer programs. RSI1 also has an extensive on-line HELP facility that removes most of the need to consult a 'User's Manual'. Analytical Concepts Manv. aspects of instrumental analysis are presented using . msthemnticnl rrlationahips a? models of phvsical rci~li~y. Hlx k - l ~ d \radiatmn . is an example oithis. The test we have been usin; (5) gives a rather imposing equation for blackbody radiation: arch
energy density at wavelength A = -(eeklikT- I)-'
X"
(1)
where c is the speed of light, h is Planck's constant, k is Boltzmann's constant, and T is the Kelvin temperature. A graphical presentation is given in the text with some related questions, yet i t is not immediately obvious how the above equation yields the curve shape seen in the graph. RSll has an exeedingly powerful resource in its graphics arsenal-the ability to plot user-specified functions. Rather than writing a program to calculate functionally related data-point pairs, the student enters a mathematical description of the function as well as the range for the x and f(x) axes. RS11 then evaluates the function and produces the plot. The user can then interactively alter the graph in order to explore the function in detail or to optimize the graphical presentation.
Volume 64
Number 1
January 1987
29
Figure 1. Black-body radiation curve calculated atthree temperatures using eq 1.
Figure 3. Simple integrationand differentiation models am used to transform a spectral waveform.
5-
,
..
,-
A typical example is shown in Figure 1. (It should he noted that all the figures in this paper were produced using RSI1.) Another intimidating equation is the one that summarizes much of chromatography (6),
:=-. 1
,','
,,
500
1500
,000
number ilt
3000
2500
2000
plat^^
5-
. .
. . . . . . . . . . .
.
where R is the resolution, N is the number of theoretical plates, n is the selectivity factor, and k'is the capacity factor. How the values of N, a,and k' each affect R is not immediately obvious. The students were asked to examine these relationships and produced graphs such as those shown in Figure 2. Other concept-conveying examples included Beer's Law deviation caused by polychromatic light, Fourier analysis of waveforms, polarograms, signal processing (Fig. 3), and an examination of the potential for impure chromatographic peaks to go unnoticed. Statlstlcal Techniques
1
2
3
4
5
6
7
8
9
2
0
selectivity
.-.---.-_ _ - _- _ - -
At a SIGNIFICANCE LEVEL of 0.05, there is INSUFFICIENT EVIDENCE to REJECT the NULL HYPOTHESIS that the SAMPLES came from POPULATIONS with EQUAL MEANS.
1
0
1
2
3
4
5
6
7
8
9
,
O
c a p a c i t y factor
FigureZ.(a)Theeffectof the number ofthearetical plates(Monthe resolution
(fO. (b) The effect of selectivity (a)on resolution. ( c ) The effect at capacity factor ( k ' ) on resolution. These were each calculated using eq 3.
30
Let us face i t s t a t i s t i c s is a boring hut necessary aspect of experimental science. Inmost cases statistics is used to allow the user to conclude with quantifiable certainty what he or she already surmises. RS11 has solid statistical capabilities, beginning with descriptive statistics, progressing through linear regression and correlation analysis, and including the more sophisticated approaches of analysis of variance (ANOVA), nonlinear and polynomial regression, test for normality, and a number of other goodies. Just as in dealing with a human statistician, using RSII does not relieve the scientist of the ultimate responsibility for decision making. However, RS11 will go so far as to express the results of its analysis in true statistical parlance, for example,
Journal of Chemical Education
The student must achieve a reasonable level of statistical prowess in order to understand these statements. Apart from the interpretation of calibration curve data, which we have discussed a t some length elsewhere (3, other statistical techniques used in the instrumental course ineluded analysis of variance for interlaboratory collaborative studies, weighted linear regression, and significance testing (e'g'2 paired-t tests)' A cautionary note regarding statistics is in order. It is often said that anything can he proved with statistics, and
Figure 4. Kinetic data collected by monitoring the reaction between triethyl gallium and 1-butylchloridegives the appearance of being rerom order. This happened because data at shan andlong times were ignored. this is certainly true, especially when an experiementalist is only out to verify a preconceived notion or when one too quickly concludes that correlated events are the result of a cause-and-effect relationship. RS11 can make such miscarriages ofjustice frightfully easy. F~~example, we were asked hv look a t some kinetic data in-,nnother research erotln to ~-~~~ volving the reaction of triethyl gallium with t-butylchloride, monitored by NMR peak heights. The data seemed to i d cate that a zeroth-order reaction was occurring-which is exceedingly unusual. We produced the graph shown in Fignre 4, which agrees with this premise in that the rate of reaction appears to be constant. At a later date when we asked about the final outcome, we were told that actually the reaction was found to ~ r o c e e dbv an autocatalvtic mecha-
~"-.~~.~ ~~
~~
Laboratory Experiments In qu:tntitat~\.eanalysis mud1 of the expt.rimtmtittiun is h s e d on implicit or rxplkit calihratic~ncurves, relaring measured resoo&es to analvte concentrations. Correctlv utilizing calibration data can be demanding and tedious. The data might need to he transformed or altered, different models might need to be considered, residuals should be visually inspected, the presence of outliers should he checked, and the final results must be evaluated. The RS/1 regression and graphics capabilities makes this type of data analysis routine. This frees students of worry about the specific calculational formulae; instead they can focus on the meaning of their results. While the concerns of a few years ago regarding the impact of hand-held calculators apply now to personal computers, both are inevitable tools of the scientists, and students must learn to include these resources in their repertoire One example of calibration that we have used in the laboratory is a flow-injection analysis (FIA) experiment for the determination of chloride a t the parts-per-million level. Routinely the calibration curve obtained has a large positive intercept on the response axis. The students are asked to ~ r o v i d ereasons for this nonideality and also how they would try to confirm the cause of the intercept. Another example of calibration data analysis is the determination of fluoride in toothpaste using an ion-selective electrode (ISE). A logarithmic transformation is needed to achieve a linear relationshin (Fie. 5). A transformation is using ~ ~ 1 1. .
Figure 5. A linearized calibration curve for the determination of fluoride in toothpaste by an ion selective electrode.
Dlscusslon The two main considerations that are commonly pondered 5'' the instructor of any course are: How can I fit in everything? What do I cut out? Computerized data analysis certainly cannot completely solve either problem, however, ELN software does assist in using course time efficiently in Severs' ways:
. . .
Instrumental analysis techniques that are infeasible far direct experimentation due to limitations of time or facilities can be studied using stored data. Students do not need to learn computer programming in order to process experimental data. Canned programs that greatly restrict the student's options need not be used.
RSII is a professional software package, so it can be useful in many endeavors before or beyond instrumental analysis. As with any software, it does what you tell it to do, rather than what you want it to do. Acknowledgment The author would like to thank the instrumental analysis students for heine, . the euinea nies .. . .. for the effort that contrihured to rhi4 manuscript. Avkn~wlrdymentis gratefully made tu rhe Narimal Sciencr Ftudnriotl's Iuformdtion Scienre and Chemical Analysis Divisions (Grant No. IST-8120255) for the financial support of this research.
The Use of Commercial Spreadsheet Programs in the Science Laboratory Jerome S. Levkov lona College New Rochelle. NV 10801 Commercial spreadsheet programs such as MagiCalc, VisiCalc, and Multiplan have achieved immense popularity in the business world (7) but much more limited recognition in the scientific community. Discussion of the use of VisiCalc as a gradebook (8, 9),for calculating activity coefficients (lo), and for scientific and mathematical modeling (11) have appeared previously. Second generation spreadsheets such as LOTUS 1-2-3 add graphics features that, together with Volume 64
Number 1 January 1987
31
the previously described facility for creating tables of data and performing intricate calculations using these data, make them powerful tools for the science laboratory. We have used LOTUS 1-2-3 primarily in the physical chemistry laboratory. Students have a two- or three-hour hands-on session where the most imoortant features are introduced and illustrated. They are given a short manual that includes sufficient information for them to get started and work independently. The average student can use LOTUS 1-2-3 productively after three or four hours of instruction. The full LOTUS 1-2-3 manualand tutorial disk are also available a t several key locations on campus. An initial homework assignment involves creating some simple tables and graphs. A numher of instructor-prepared worksheets are made ivailahle earlv in the semester. hut as the semester progresses students are expected to create more of their own worksheets. What follows is a brief description of LOTUS 12-3 and several examples illustrating its usefulness in scientific aoolications. Some advantages .. - and disadvantages of using the program are also presented.
Figure 6. Table of masses, volumes, and corresponding densities
The LOTUS 1-2-3 Program
The LOTUS 1-2-3package consists of several floppy disks that contain the working program, various utility programs, and a user's manual. Included in the 1-2-3 package is an interactive tutorial disk that introduces many of the program's features in a clear, straightforward manner. Using this disk, students can learn the program outside of class time. The basic strategy followed throughout LOTUS 1-2-3 is that one proceeds through the program by selecting options from a series of menus. Each option is provided with a hrief description. Often the selection of an option results in another menu of choices being presented. The user is thus led via a treelike structure to the choice that performs the specific task desired. As a consequence of this organizational strategy, one does not have to memorize the operating manual or learn a programming language since instructions are given on the screen. In addition, a t any point one can request help, which results in a more detailed explanation of the particular menu currentlv on the screen. The oroeram is anite forgiving. . . - . {wrmitting caiy c~~rrecrion of errors including inappropriate menu selecfiuns. Finall\, rhc. LOTCS 1-2-:
