topic/ in chemic~linftrument~tion
edited by
FRANKA. SETTLE,JR. V t Lexington, r g i n i 8 M VA i l i ~24450 lnslil~~
Information Management Systems in the Undergraduate Instrumental ~nalysisLaboratory Part II. Applications of LIMS Robert J. Merrer Western Connecticut State University, Danbury. CT 06610
In Part I the basics of laboratory information management systems were examined (I 1. In order to illustrate the utility of a LIMS system, two experiments have heen chosen from the list for the instrumental analysis course (see table in ref. (I)): thecoulometric titration of thiosulfate with electrogenerated triiodide ion and the atomic absorption determination of calcium using both analytical calibration curve and standard addition methods. Both experiments involve fairly large data sets, which offer good examples for retrieval in a systematic fashion. In the coulometric case, the precision and accuracy of four different pipet delivery systems are compared using paired visual (starch) and instrumental (biamperometric) endpoints. Each pipet system is run in quadruplicate. Each replicate involves two endpoint times (in seconds) and one current (in milliamperes) or a total of 48 pieces of data for each pair of students. The results for paired endpoints in each pipet system are then correlated using the t-test for comparison of averages. This comparison, of course, is preceded by the F-test for homogeneity of random error variances. In the atomic ahsorption experiment, two different matrices are examined (with and without lanthanum(II1)) by calihration curve (five data points) and standard addition (four data points) or a total of 18pieces of data for each pair of students. An extensive statistical treatment ( 2 4 ) is involved: (1)examination of significance of y-intercept in calihration curve, (2) check for homogeneity of random error variances in calihration curve and standard addition methods, and (3) comparison of slopes for matrix effects and their negation withaut and with lanthanum(III), respectively,(test of null hypothesis: slope for analytical calihration cuwe--slope for standard addition curve = 0) (5).These statistical treatments include access to a full sequential file o f t and F values. The coulometric titration experiment is emphasized in this paper.
Before performing the actual analysis in the laboratory thedata hase must be configured by creating and defining the relationship of the various data sets within the data hase. The utilities (see Fig. 3 in ref. (I)) used for this purpose are DSM (Data Set Maintenance), DEFINITion, and PM (Protected Maintenance). Using DEFINIT each test is defined. For the coulometric titration and comparison of the four pipet delivery systems, the predefined test is CULPI. The four specific tests are: CULPA (Class A pipet), CULPM (measuring pipet), and CULPY and CULPZ (two commercial pipets). Any one or all tests may be assigned to each sample of titrand (thiosulfate). A test involves four times (in seconds) for the visual endpoint (for example, CULPAOOl to CULPA004), four times (in seconds) for biamperometric endpoint (CULPAOOS to CULPA008), and four currents (in milliamperes) (CULPAOOS to CULPA012). In order to make the entry of data more user friendly, each piece of data for each test is labeled using DSM. A prompt data set with input fields is constructed for this purpose and is shown later in this discussion. The student implementation of LIMSI ZOO0 system involves the following: Case I, accessing predefined, prestored sets of data (archived from previous semesters), and Case 11, simulation of the operation in a commerciallindustrial analytical laboratory. The latter involves following a sample's fate throughout the laboratory including: 1) logging-in the sample and hiographically tagging with pertinent information (e.g., analytical: sample description, storage conditions; management: submitter, course name, due date), 2) assigning tests, 3) gathering data, 4) tiling of data and setting search criteria to retrieve these data, 5) performing the search and archiving both the data and this search,
6 ) generating the report.
The following three application modules (Fig. 3 in ref. (1) are highlighted in this experiment. 1) SAmple: used to enter, modify, and list samples or groups of samples. The sample number is automatically generated and must he noted since it is one of the key tags for the thiosulfate sample. In this module, any or all of the previously created tests are assigned, CULPA through CULPZ. 2) ANalysis: used to complete tests (procedures). LIMS12000 asks for the sample number. Once entered, the procedures that have been assigned are displayed with their expected range (field). Next, results are entered. 3) SELect: allows a selective search of the data base using the sample's hiographical tags (e.g., sample number, date received, submitter, etc.). I t is a prompting language through which the user can easily access the data hase without having to program. The specific information so delivered can then he displayed or integrated into a high-level language program. In addition, should such a selective search he performed routinely, it may he predefined, given a name (STATSUM in this case), and executed by simply entering that name. This module is one of the key elements of the present experiment. In this coulometric experiment, STATSUM culls data from the predefined tests CULPI, which are associated with a certain sample or group of samples. These report data are placed in a ("manila-like file envelope") user data file ( C O U G .UDF). For each selective search carried out aunique user data file may be generated, for example, student pair Q
Volume 62
(Continued on page AI76)
Number 6
June 1985
A173
places the report data in C0ULQ.UDF and student pair K opens COULK.. UDF for their report data. Now the reoort data derived from SELect can he acted i o o n bv the user-written orogram. This program (COUL.BAS) manypulates the report dataand performs post-run calculationswith statistics. Student pair Q or K, or any subsequent students, may now run C0UL.BA.S and pmcess the unique data that resides in the chosen user data file. This feature enables immediate comparison of any student data. The BASIC oramam reads the report data in the followvlng manner. the first column of the user data fde IS the test (procedure), and the second column contains the experimental data (seconds or milliamperes). As mentioned previously in Case I the uninitiated student aeeesses data from earlier semesters. A sample of student output from COUL.BAS Ls ahuwn in Figrve 1. Note in the four pipet delivery syrtemr the biamperometric (instrumental) endpoint leads the visual endpoint. This approach allows the student to compare his or her data with previous students' data as well as to investigate the orecision and accuracv of various ninet .. delivery system. This latter point is panicularly interesting for the *tudenr, as precision and accuracy are dependent on the order in which the pipet systems are investigated. In Case 11,not only must the data be accessed (as in Case I), but it must first be assembled by the student. This aspect simulates the actual steps taken in routing a sample within the commercial/induatrial analytical laboratory. ~~
~~
~~~~~~~
~
.~~~.~
~
~
~~~~
F w r n 1. A n m u t screen frompragramCOU-tor co~lometrictitrations of various pipet dsiwery s y b terns. (From ref. (g).)
The sample is logged-in with the SAmple module. Figure 2 shows a typical sample menu screen. Tests to he carried out on the sample are now assigned (CULPA thrgh CULPZ or any combmation). Apartialscreen for completing an analysis in the ANalyais module is shown in Figure 3. As mentioned previously, each piece of data for each test or procedure is labeled to facilitate entry. Now as in Case I, the SELect module searches the test file CULPI using STATSUM and stores the data in COUL-.UDF whose data are processed by the program COUL.BAS. The student compares all results far this "electronic" notebook exercise with those carried out previously by manual cakulation.
A176
Journal of Chemical Education
Fbue 2. SAmpb m&le for twinsin a sample for a set of couiomelrictibations.
ThB electronic notebook comparison is both useful and straightforward since each set of student data now resides in a unique user data file that can be called on in the future. This approach is particularly effective not only in the coulometric experiment but also in the atomic absorption experiment which allows for comparison of numerous matrix
modified systems for calcium determination. Student evaluation of this use of LIMS in the instzumental analysis course has heen uniformly enthusiastic. A graduating senior commented: In this experiment I learned about the importance of data base formatting and
formation (for me) than in any other experiment. The inclusion of digital electronia and mieropmeeasors, in addition to LIMS, contributes to the power of this course and is well worth the considerable effort to do well.
Literature Cited
In addition to the aforementioned use of LIMS, other academic appl~cat~ons include (but arc not limited WI:
1) entry of procedural text for experiments, 2) transference of data within a network, 3) grading of laboratories, 4) inventory uses (supply and equipment), 5) cataloging, assigning for maintenance, and scheduling instruments within the department, and 6) cataloging safety/toxicologicaldata for reagents used in Laboratory experiments F'@w 3. A paNal saeen in t k ANaWs module fa CompMng a test in the mlomebic tibation of a Class A pipet (test: CULPA).
the power of an efficient, user-friendly DBMS. I also learned about various methoda of creating, storing, and a& files, as well aa data base c o n f i a t i o n , data entrv. ...nromots..information screens. menus, hardware and software system interactions, and the Westconn computing capacity. I think 1learned more useful in-
.
Acknowledgment The author wishes to thank the PerkinElmer Corporation and the LIMS120M) Support Group for makiig possible this corporate-university cooperative effort. In addition, special thanks go to Rick Brown and Kevin CLaffey.
Volume 62
Number 6
June 1985
A177
