Laboratory automation-A case history

Hunter College of the City University of New York. 695 Park Avenue, New York, New York 10021. In the past decade there has been great interest in the ...
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Chemical Instrumentation Edited by GALEN W. W I N G , Seton Hall University, So. Orange, N. J. 07079 These articles are intended to serve the readers o f m r s JOURNAL by calling attention to new developments in the theory, de&gn, or availability of chemical laboratory instrumentation, or by presenting useful insights and ezplanations of topics that are o j practical imporlance to Uose who use, o+ leach the use of, modern instrumentation and instrumental techniques. The editor invites correspondence from prospective contributors.

LXXVI. Laboratory Automation-A History

Case

Bernard J. Bulkin, Edward H. Cole and Arthur Noguerola Hunter College of the City University of New York 695 Park Avenue, New York, New York 10021 In the past decade there has been great interest in the use of small computers in chemical instrumentation. What has been done to date undoubtedly represents only a small fraction of the automation of data collection and data reduction which we will see in coming years. It can be safely said that every decrease in the price of minicomputers and peripheral devices results in a large increase in the number of instruments which incorporate them as integral components. In addition, these price decreases are, in large part, responsible for the appearance of certain instruments which are completely dependent on the minicomputer for data reduction, specifically Fourier Transform infrared and nmr spectrometers. It is important in this era for chemists to be able to make decisions about the retrofitting of computers to their existing instrumentation. Such decisions will bring chemists into contact with a wide array of electronic and computer terminology with whieh they are generally unfamiliar. Often decisions will have to be made on questions such as "Should a particular piece of hardware (interface, ete.) be constructed or purchased?" To answer such questions s variety of factors related to the electronics personnel support staff available to the chemist will have to be weighed against commercial availability, quality, and cost. Similar decisians will arise on the programming or software front. Which programs should be purchased from instrument companies, as opposed to in-house generation? If the latter choice is made, who should do the work, undergraduate, technician, graduate student, or faculty member? These questions can be as mystifying as hardware questions if one is not an experienced programmer who can estimate the difficulty of the task accurately. Beyond these points, one often must question whether a particular automation retrofit should be attempted a t all if saftware must be generated locally. In this article we depart from the usual format of this column to discuss a case

history of laboratory automation. While many texts and articles are now available providing details of interfacing and programming for chemists, we feel that the episodic approach used herein is useful in conveying the specific decisions to be faced by a chemist, particularly one in the academic environment, who is interested in an automation problem. At the same time, the overall system should prove useful to others interested in retrofitting of computers to spectroscopic instrumentation. Further, the specific circuitry described is of general applicability to a wide variety of problems. The instrument which is going to be described is an automated Raman spectrometer. The discussion will first present a rationale for selection of the equipment to be used. Following that the interfaces and related hardware will be explained in detail. Then the programs or software will he discussed.

I Bernard J. Bulkin is Professor and Chairman, Department of Chemistry, Hunter College of the City University of New York. He received his B.S. in Chemistry from Polytechnic Institute of Brooklyn in 1962, Ph.D. in Physical Chemistry from Purdue University in 1966, and was a postdoctoral fellow a t the Eidg. Techn. Hochschule in Zurich in 1966-67. He joined the Hunter College faculty as assistant professor in 1967, became a n associate professor in 1970 and professor in 1974. Professor Bulkin's interests are in the area of vibrational spectroscopy of liquid crystals and cell membranes. He contrjbuted an article on Raman Spectroscopy which appeared in this column for November and December, 1969. Edward H. Cole is a n electrical engineer in the molecular cellular developmental biology department of the University of Colorado, Boulder. He was educated a t the University of Virginia, Adelphi University, and State University of N.Y.Stony Brook. He has been employed a t Brookhaven National Labs and operated his own consulting company before serving a t Hunter College as a Research Associate from 197074. Mr. Cole's interests are in the area of application of computers to pmblems in the physical and hiological sciences, as well as in the development of instrumentation. Arthur Noguerala is presently completing his B.A. degree in the City University of New York B.A. program. The data reduction programs discussed in this paper are from a part of his B.A. thesis.

THE PROBLEM Raman spectroscopy is an example of a spectroscopic technique which is ideally suited for automation. Foremost among the suitability criteria is the need for automatic data collection and reduction techniques. In this area four aspects of Raman spectroscopy stand out: 1. The weak signals make signal averaging desirable. 2. Most instruments already use photon counting amplification of intensities so a digital output is available. 3. The use of several laser exciting lines makes intensity correction far instrumental factors important. 4. The need to calculate depolarization ratios for comolex molecules. havine a large number of Raman hands, height& the need for computer based data reduetion. Some preliminary signal averaging methods for Raman instruments have been described briefly in the literature ( I ) , and Scherer (2) has described a Raman automation system using a remote IBM 1800 computer.

RATIONALE In selecting a computer system for automation of an instrument, the first question to be answered is whether the automation of data calleetion is to be done "off-line" or "on-line." By the former choice, we mean that the collection of data in digital form can be done without a computer. The computer is used only for the data reduction, plotting, integration, ete. In such a system, a hard-wired set of switches and integrated circuits might be used to set up such parameters as digitization interval, counting time, scan direction and counter limit. The system could also control a paper tape punch or magnetic tape unit to output the data in a format suitable for input t o a computer. The limitations an such an off-line automation system are mainly in terms of flexibility. The system cannot make decisions (Continued on page A274! Volume 51, Number 5. May 1974

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arise from a large region (30W e m 1 ) digitized a t relatively coarse intervals (1 e m ' ) or a small region digitized as finely as 0.1 cm-' intervals. Considering that in the course of a spectrum, because all calculation of depolarization ratios, subthe parameters are varied by operator contraction of solvent bands, and intensity trol of switches. In addition, the system corrections due to instrumental factors will, in general, not be able to carry out will often require the computer to hold two more than one function a t a time. If a spectra simultaneously, the minimum computer is used, the computer can carry memory requirements of a Raman data reout data reduction operations while it is duction system are fixed. simultaneously doing data acquisition. Suppose that the programs are assumed When it is time for more data to be transto require approximately 4000 (4K) words ferred into computer memory, the data in memory (reasonable for most data acprocessing can be interrupted automatiquisition and reduction), and that a eomcally while the data transfer is accomputer is used with a 16-bit word size, then plished. one can assume that 12 K of core memory In our case, we began by using a n offwill suffice for almost all operations. If line automation system. This system was very large signals are to be digitized, then readily availahle because of the similarity the size of the signal might exceed the of Raman spectroscopic instrumentation largest number that can be stored in a to x-ray spectroscopy. A commercial unit word of 16 binary hits (i.e. 32,168). In this was available using thumbwheel switch case, two words will he needed per data programming. Data were punched onto point (double precision) and the size of paper tape using a teletype. This system memory must he increased. Surprisingly will not be described in any detail here. enough, these considerations are sufficient Suffice to say that one finds such devices to fix the size of the basic computer and are commercially available rather often, as the price a t ahout $8000. Most of the many simple automation jobs have been speeds for actually carrying out operations approached in this way. Sometimes comare comparable for the minicomputers ponents purchased for an off-line automawhich are availahle, and in any ease tion system can be utilized'in a n on-line Raman spectroscopy is not a technique avstem , inter. - ~ ~ ~ - ~ ~ ~ ~ a~ - ~ high speed which~ requires particularly In designing and building a n on-line sysmachine in any phase of the automation tem such as the one described below, more operation. Such high speeds are required detailed considerations as to equipment when data is coming into care memory a t are necessary. Foremast are the size of the very highrates, e.g. greater than 1MHz. computer which will be needed, and its An important question which arises a t speed. Raman spectra usually consist of no this point is additional storage. If three or more than 3000 data points. These may four spectra are ta he recalled frequently,

Chemical Instrumentation

should more core memory he added to accomodate these? In general, this will not he the chosen solution, because bulk storage with somewhat slower access time is availahle a t lower price than core memory, often an order of magnitude lower in dollars per word. Such storage is either in the form of a disc or in the form of magnetic tape. The former is considerably faster than the latter. In considering automation of the spectrometer, an importent decision often involves the balance between laboratory computer and large central facility. In this case we have favored the laboratory computer or minicomputer. This is true even if data collection is being done off-line, with data reduction on-line. The disadvantage of the minicomputer which is usually cited is the need to do mast programming in the assembly language of the machine, rather than in a higher level language such as BASIC or FORTRAN. This is not campletely true any more, as many of the compilers for BASIC can call routines from assembly language, allowing the bulk of the program to flow through the higher level language. Nonetheless, it will still he necessary to do'the data acquisition programs in assembly language. Same examples of such programs will be given later in this paper, so as to indicate the level of difficulty of the task described. Use of BASIC or a high level language will usually he less efficient in terms of core memory requirements. The advantage of the laboratory computer is substantial-all of the operation remains within the laboratory. Changes in the operating system are made only when desired, not when changes occur a t the central facility. In addition, even the best central facilities have some forced shut down time. It has been our experience that the reliability of the minicomputers is extremely high. Thus round the clock operation of the spectrometer is possible on a regular basis. The system which we use involves two minicomputers. Soon we expect that it will also involve the central computer facility of the university. This is what is known as a hierarchical system far automation. The system is shown schematiially in Fig. 1. The three computers in the system are a Digital Equipment Corp. PDP-8L, with 4 K of care memory, a Data General Nova Computer (12 K of core) and an IBM 370/168. The 370/168 is not used in our current system, although it will he in the near future. b.M

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