Computational Chemistry Researchchemistry.ncssm.edu/book/chap23/Chap23CompChemResearch.pdfChapter 23 Computational Chemistry Research 23.1 Key Notes 23.1.1 Choosing a Research Problem:

Chapter 23

Computational ChemistryResearch

23.1 Key Notes

23.1.1 Choosing a Research Problem:

Students wishing to engage in computational chemistry research should have reasonablepractical experience in building molecules, submitting calculations (jobs), and analyzingresults. The student researcher should also have a good idea of the types of problems thatcan, and that cannot, be solved using available computational resources. While there isno magic number, most students wishing to do an independent project in computationalchemistry will have done several dozen or more smaller projects, often under the directionof the classroom teacher.

In choosing a research problem, there are four guiding questions that the student canuse to help narrow down the choices:

1. What area of chemistry are you most interested in? Answers to thisquestion include organic chemistry, inorganic chemistry, medicinal chemistry, andenvironmental chemistry, among others.

2. What resources do you have at your disposal? Answers to this questioninclude the amount of computing time, access to mentors, etc.

3. How much time to you have? Specifically, this means what is the duration of theresearch? Is this a one-week project, or something being done over the course of asemester or summer research program? Guidelines for how many jobs might be rungiven the length of the project in days is presented in the reading below.

4. Is there a particular category of computations that is of most interest?

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2 CHAPTER 23. COMPUTATIONAL CHEMISTRY RESEARCH

Beginning student researchers might be intrigued by determination of transition stategeometries, or calculation of various spectra for a molecule or series of molecules.

23.1.2 Applying for a Research Account:

Computational chemistry researchers in the scientific community often need to requestcomputing time on large supercomputers, located at a variety of supercomputing centers.To do so, they submit a research proposal, describing the research to be conducted, theexpected results, the amount of computing time need (in terms of CPU minutes or hours),and other issues related to the research. Likewise, student researchers wishing to use thecomputational chemistry resources described in this document must submit an online re-search proposal. The proposal is evaluated by the computational chemistry server supportstaff, and computing time is appropriately awarded. The proposal includes componentsthat include a working time, an abstract describing the work, software requirements, perjob time limit, a total CPU time limit, and the name(s) of a teacher or mentor who issupporting or sponsoring the student research.

23.1.3 Choosing a Model Chemistry:

One of the most critical components of student research is the choice of a computationalapproach for the research problem. In other words, a description of the calculations to beperformed, and, for quantum methods, a description of the model chemistry that mightbe used to do the calculations. The critical guideline is that the student researcher shouldchoose the simplest model chemistry that produces the data needed to answerthe research question. For the beginning researcher, this is a challenging issue. Thegoal of any good computational chemistry research is to get the best data possible with theleast amount of computing time. This is an important consideration in professional com-putational chemistry research, and important in student-based computational chemistryresearch.

23.1.4 The Computational Chemistry Notebook:

Good researchers keep good lab notebooks, and that requirement does not change forcomputationally-based research. The basics of keeping a computational chemistry note-book are similar to that of a notebook kept in a traditional wet-chemistry lab, but withsome differences. Computational chemistry lab notebooks will include discussions of thecomputational approach, the programs or software used to perform the calculations, thetypes of calculations performed, specific file names for submitted jobs, and drawings of thechemistry being evaluated.

23.2. CHOOSING A RESEARCH PROBLEM: 3

23.1.5 Presenting Results:

Upon completion of a research project, students can present their results using one of threeformats typically found in the professional scientific community. The first is the creationof a poster, for display at a poster session at a scientific conference. Student researcherstypically stand next to the poster, and answer questions as other scientists or studentscientists visit the poster. Students can also prepare a lab abstract of the research. Lababstracts are short narratives, approximately 250-300 words in length, and contain thepurpose, computational approach, example data and sample results, and a conclusion. Forlarger computational chemistry projects, students can also create a journal-type article.Articles are typically 3-10 pages in length, and follow a specific set of guidelines. Atthe North Carolina School of Science and Mathematics (NCSSM), student computationalchemistry researchers follow the Journal of Computational Chemistry author guidelines.

23.1.6 Sample Project Titles:

In the reading below, sample project titles are listed to help the educator and studentresearcher get a sense of the types of projects and project titles might be suitable forstudent research.

23.2 Choosing a Research Problem:

What do you want to know? Any research effort starts with this question. While itsounds like a simple question, the answer is anything but simple. Generating a researchquestion that is appropriate to the research situation is both an art and a science. What,however, does appropriate to the research situation mean? For the educational audience(for whom this book is written), this typically means a research project being done tosatisfy the requirements for a course in computational chemistry, or for a project thatmight be submitted to one or more science competitions. In this chapter, the focus will beon student projects of both short- and long-duration.

All good research starts with an understanding of the technologies, techniques, andtools of computational chemistry. By the time a student researcher is consideringa research project, s/he should have a good practical understanding of what types ofproblems computational chemistry can solve (technologies), an understanding of how touse the available software, submit jobs, and analyze results (techniques), and be able tochoose the most appropriate software for the problem (tools). By the time the studentis ready for research, s/he should have run a dozen or more jobs using several differentsoftware packages, and have successfully completed both structured labs (teacher directed)and smaller, open-ended (teacher guided) lab activities.

In developing a research question for a student project, there are several guiding ques-tions that can help direct the student:


• What area of chemistry are you most interested in? Answers to this questionmight be topics such as these (with examples):

1. organic chemistry (structures and/or mechanisms)

2. medicinal chemistry (comparison of energies of substituted lead drugs)

3. environmental chemistry (rates of hydroxyl radical degradation in the atmo-sphere)

4. inorganic chemistry (excitation states of coordination complexes)

5. reaction chemistry (prediction of kinetics, thermodynamics, transition states,etc.)

• What resources do you have at your disposal? Resources specifically meanscomputing resources, both time and software availability. If the researcher is using ashared (distributed) resource such as the North Carolina High School ComputationalChemistry server, then there has to be a recognition that the student is sharing com-puting time and cannot submit numerous jobs, especially simultaneously-submittedjobs. The student researcher (with support from the teacher-mentor or externalmentor) needs to coordinate the submission of jobs with the server administrativeteam. In terms of software, the student needs enough familiarity with the varioussoftware packages to know what types of problems can be solved, and perhaps moreimportantly, what types of problems cannot be solved with the available computingresources.

• How much time do you have? For an end-of-course project, time constraintsput significant limitations on the scope of the project. The number of jobs thatneed to be completed for the project to be successful probably needs to be 20 orless, with each job requiring 10 minutes or less of compute time per job. For longerterm projects (such as a research course or science competition project), the numberand length of jobs scales appropriately. The table below shows guidelines for how todetermine the number of jobs and the size of the jobs. For example, if the projectmust be completed in a week (as in a small classroom assignment), the student shouldprobably consider running no more than 8 jobs, each requiring on average no morethan 66 seconds (2.1 minutes) per job. Larger research projects, such as one lasting10 weeks (perhaps as a summer research project or independent school year project)might result in 80 or more submitted jobs, with single jobs requiring 21 minutes ormore. Assuming the multiplier of number of jobs times time per job, 84 jobstimes 21 minutes suggests a total CPU computing time of about 30 hours. For largerresearch projects, one run might require that much time. As a rule-of-thumb, anyresearch project that anticipates needing more than 100 total CPU hoursof time must coordinate the scheduling of jobs with the server systemadministrative team!

23.2. CHOOSING A RESEARCH PROBLEM: 5

Available Time (Calendar days) Number of Jobs Time per Job (minutes)

2 2 0.64 5 1.27 8 2.110 12 3.014 17 4.221 25 6.328 34 8.435 42 10.542 50 12.649 59 14.770 84 21.0

Table 23.1: Guidelines for determining number and size of jobs, based on research timeavailable

Graphically, this scaling can be represented as in Figure 24.1. The graphic showsthe number of days available for the project on the x-axis and the total CPU timesuggested on the y-axis. It is important to remember that the table and related chartare simply suggestive, not prescriptive!

• Is there a particular category of computations that is of most interest? Bythis, we mean the following three items:

1. Structure: projects based on structure typically focus on trying to determinethe optimum, or optimized, geometry of one or more molecules. A researchproject might, for example, try to determine which model chemistry might workbest for a specific type of molecule or molecular family, such as cycloalkanes. Or,a project might try to evaluate how well computation predicts the known exper-imental structure, perhaps using data from the Computational Chemistry Com-parison and Benchmark Database (http://srdata.nist.gov/cccbdb/ ). Structure-based projects might also consider trying to determine a suitable transition statestructure for a specific reaction mechanism.

2. Property: projects based on property typically are looking to determine thosecharacteristics of a molecule or group of molecules that exist in that moleculeregardless of the presence of other molecules. For example, a property-based re-search project might look at determining the vibrational frequencies and IR spec-tra of an organometallic compound. Another project might look at determiningthe gas-phase basicities of a compound or family of compounds. Property-basedprojects might also include investigations to find fundamental quantum descrip-tors such as dipole moments, polarizabilities, molecular orbital energies, and


Figure 23.1: Scaling of available time in days vs. total CPU compute times

spectroscopic information. One category of property-based projects involves theuse of the techniques of QSPR (quantitative structure-property relationships),in which regression mathematics is used to try to capture the mathematicalrelationships between some property of the molecule and one or more structure-based quantum descriptors.

3. Activity: projects based on activity are probably better described as reactivity.Activity-based projects typically look at applying computational techniques toreaction mechanisms. A project that looks to investigate the SN1 and SN2reaction mechanisms in organic chemistry is a good example of an activity-based problem. Other projects might look at determining heats of formationand other thermodynamic parameters of some reaction.

23.3 Applying for a Research Account:

As more computational chemistry tools become available (or affordable, as the case maybe) for individual computers, the need to apply for a research account will no longer be

23.3. APPLYING FOR A RESEARCH ACCOUNT: 7

necessary. In many cases, however, a researcher applies for time on a large computer.Student researchers requiring the resources of a distributed computing system such asthe North Carolina High School Computational Chemistry server must submit a researchproposal to the scientific team that maintains the server. This is excellent practice forstudents who will continue into the area of high performance computing, also known assupercomputing. It is still common practice for professional scientific researchers to submitproposals to institutions such as the National Center for Supercomputing Applications(NCSA) and the San Diego Supercomputing Center (SDSC) for supercomputing time.

Student researchers requiring an account on the NC HS Computational Chemistryserver must also submit a research proposal in order to get an account. Project proposalsshould contain the following pieces of information:

1. Paper Title: at the proposal stage, this can be a working title (i.e., not necessarilythe final title). The title should be descriptive enough to provide the server admin-istrators with a sense of what problem is the focus of the study. An example titlemight be: Determination of the Transition State of the Decomposition ofFormaldehyde.

2. Paper Abstract: the student researcher should prepare a short abstract describingthe main goal(s) of the research, along with a description of how the researcher mightapproach the solution of the problem (in other words, the computational approach).Of critical importance at this stage is an indication of what model chemistry thestudent researcher might be using. Model chemistry selection is described in greaterdetail below.

3. Software requirements: in submitting a proposal, the researcher should also in-dicate which software package or packages s/he might require for the research. Thesupport team can often advise the researcher whether or not the choice of a softwaretool is the most appropriate.

4. Per job time limit: in any distributed computing system (i.e., a computer thatsupports multiple users), one of the primary responsibilities of the server supportteam is to ensure that there are enough computing resources for all of the users. Inattempting to predict the per job time limit, the student shows whether or not s/hehas an realistic understanding of how long the computations will take.

5. Total CPU time limit: as with per job time limit, the student researcher shouldattempt to predict the total computing time necessary. A simple algorithm such asthe number of total jobs that will be needed multiplied by the average amount oftime for each job should work for predicting total time. Student researchers (andeven experienced researchers) tend to underestimate both the per job and total timelimits, so it is not uncommon to scale, or increase, the predicted time limits by 10%or more.


6. Name of teacher(s)/mentor(s): until a researcher acquires principle investigatorstatus, s/he typically conducts research under the watchful eye of one or more men-tors. High school student researchers, just like undergraduate or graduate students,are hopefully being guided by a research mentor, such as the school chemistry edu-cator and/or a mentor at a local university. The amount of support that the studentresearcher will receive, along with the name(s) of the mentor(s), should be describedin the proposal.

Preparing a research proposal not only prepares the student researcher for the realworld, but also provides the computational chemistry support team with the informationneeded to ensure adequate computational resources for all users.

23.4 Choosing a Model Chemistry:

For all but the most basic research projects, one of the critical determinations is the choiceof a model chemistry. The student researcher needs to make decisions about which level oftheory s/he might need to obtain the appropriate data for a specific research question. Thegoal is always to choose the simplest level of theory that will yield adequate results. If, forexample, the student can use a semi-empirical approach rather than an ab initio approach,then that is the most appropriate approach. The student must work to choose a levelof theory that results in the most accurate data requiring the least amount ofcomputational time.

If the student researcher is using an ab initio or DFT quantum method, s/he also needsto choose a basis set that provides good data at a minimal computational expense. For largeresearch projects that are intended for submission to one or more scientific competitions,it is suggested that the student use at least a 6-31G or higher basis set (unless, of course,the research project is looking at evaluating the proper choice of a basis set!). Studentsare encouraged to use smaller, less accurate basis sets for their preliminary calculations inorder to get a sense of what the results might look like. When, however, they are ready forproduction runs, meaning the final calculations that will be analyzed and reported, largerbasis sets are encouraged.

Most published research articles report a model chemistry that is used to ensure that themolecule is geometry optimized and then the model chemistry used for the calculation(s).For example, the student might indicate that s/he will use an HF/6-31G model chemistryfor the geometry optimization, and a B3LYP/6-31G(p,d) model chemistry for the finalcalculations. If the student does not have a basic understanding of model chemistries, s/heis probably not ready to engage in a large-scale computational chemistry research project.

23.5. THE COMPUTATIONAL CHEMISTRY NOTEBOOK: 9

23.5 The Computational Chemistry Notebook:

Keeping a notebook in computational chemistry research is just as important as keepinga notebook in any other research program. There are, however, some differences in howone might keep a notebook in computational research versus that in a wet lab. Dr. JohnHanson of the University of Puget Sound has developed an excellent model for keeping acomputational science notebook. Figure 24.2 shows an example computational chemistrynotebook page with numeric labels:

Figure 23.2: Notebook example courtesy of Dr. John Hanson, University of Puget Sound,http://www2.ups.edu/faculty/hanson/c455.07/intro.htm


1. Page number (mandatory)

2. Date (mandatory)

3. Title of the lab or project (mandatory)

4. Drawing of the project (optional): for most computational labs, a drawing of themolecule(s) and/or the reaction mechanism is useful and appropriate. In this case,the drawing shows the mechanism of the nucleophilic attack on the the carbonyl.

5. References to the literature (optional, but normally a part of the note-book)

6. Program(s) used to perform the calculation(s) (mandatory)

7. Computational approach (mandatory): The computational approach is listedhere as the strategy. The strategy is not a procedure; rather, it describes the overallplan for the project

8. Procedure (mandatory): as typical, the procedure describes in some detail howthe calculations will be performed

9. Calculation (mandatory): a description of the model chemistry used in the lab. Agood notational system is HF/6-31G(d)//B3LYP/6-31G(p,d), where the first modelchemistry describes how the molecule was optimized, and the second model chemistrydescribes how the calculations were performed

10. File (mandatory): this section lists the file name(s) for the calculation(s)

11. Basic data (mandatory): this section lists the primary data for the calculations,including how long the runs required (shown here as both CPU time and wall, orclock, time), and the final energy of the molecule

12. Data (mandatory): this section might include a table of data and/or a drawingof the visualizations. For example, in this lab notebook, the researcher has sketchedthe molecular orbitals of the molecules, describing the interaction of the MOs

13. Summary (mandatory): not included in this example, the lab should concludewith a summary statement

23.6 Presenting Results

There are primarily three ways to present the results of a computational chemistry researchproject:

23.6. PRESENTING RESULTS 11

1. Poster

2. Lab abstract

3. Journal-type article

Each is described in more detail as follows.

23.6.1 Poster

Most educators and students are familiar with this option. Posters and poster sessions arecommon occurrences for most students who have participated in a science fair-type activity.Experienced researchers also regularly create posters to present information. Posters aretypically set up at a wide variety of scientific meetings. The researcher will often standnext to the poster, explaining the research as other scientists browse through the posterarea. Figure 24.3 shows a photograph of a scientific poster session. It is the rare scientificconference that does not sponsor at least one poster session!

Figure 23.3: A scientific poster session. Image courtesy of Swarthmore College,http://www.swarthmore.edu/NatSci/cpurrin1/posteradvice.htm

In designing a poster for a computational chemistry project, one may or may not followthe typical hypothesis-based approach described in most readings on the scientific method.A computational chemistry poster should at a minimum contain the following sections:


1. Abstract

2. Purpose of the Project

3. Scientific Background

4. Computational Approach

5. Data/Example Data

6. Results and Discussion

7. References

23.6.2 Lab Abstract

Most if not all journal articles begin with a short (250-300 word) abstract describing theresearch work. For smaller research projects, such as a small class project or shorterindependent research project, the presentation of results in a journal abstract form is avery effective tool. Students often comment that it is easier to write a complete reportrather than the shorter lab abstract!

As an example, students in a computational chemistry class were given a small, one-week research project to evaluate which theoretical method, or model chemistry mightprovide the best value for the heat of formation for the protonation reaction of pyridine1.A sample lab abstract for this project is shown below:

Abstract: The choice of a theoretical method in computational chemistryis a critical consideration for the computational chemistry practitioner. Thechoice of a theoretical method is evaluated as applied to the protonation of thepyridine molecule, a benzene-like cyclic organic compound containing a singlenitrogen atom in the ring. Geometry optimizations are performed on both aneutral pyridine molecule and a positively charged pyridinium cation, wherea proton is attached to the nitrogen atom. The optimizations are performedusing two semi-empirical methods, AM1 and PM3, using the MOPAC soft-ware. Geometry optimizations are also performed using a density functionaltheory (DFT) hybrid functional (B3LYP/6-31G(p,d) on both of the organics.Single point energy calculations are performed on the proton using AM1 andPM3. A comparison of the heats of formation for the reaction, calculated us-ing Hess’ Law, shows that the DFT theoretical method is significantly better(-231.9557007 kcal/mol, or 1.6% error as compared to the experimental value

1Introduction to Computational Chemistry, The North Carolina School of Science and Mathematics,Spring 2007. Project design courtesy of Dr. Clyde Metz, Department of Chemistry, College of Charleston,SC

23.6. PRESENTING RESULTS 13

of -219.2 kcal/mol) than that of the PM3 method (-196.69071 kcal/mol, or 5%error) or the AM1 method (-162.79073 kcal/mol, or 10% error).

The basic format for the lab abstract is as follows:

1. Purpose: typically, a one- or two-sentence description of the goal of the project. Inthe sample abstract, the writer describes why the work is important and provides abroad description of what the research evaluates

2. Computational approach: the writer describes the type of calculations performed,in this case through geometry optimization and single point energy calculations usingsemi-empirical and hybrid density functional theory (DFT) techniques

3. Example data: given the size of this research, the abstract does not report exampledata. For a larger work, the abstract would try to give the reader a flavor of thetypes of data that was collected from the computations

4. Sample results: again, given the size of this project, the results section of theabstract reports all of the final results. In this project, the writer reports the finalheats of formation for reaction for the three theoretical methods and the percenterror calculations from the experimental value

5. Conclusion(s): the last line of this abstract, which also contains the sample results,states the conclusions, reporting that DFT is better than the AM1 or PM3 semi-empirical methods for this particular chemical reaction

In classes conducted at the North Carolina School of Science and Mathematics, stu-dents are required to submit a copy of their lab notebook and a final abstract for all labsperformed. Typically, students conduct their computations in teams of two or three stu-dents, can collaborate and consult with each other on the data analysis, but are requiredto write their own lab abstract. This practice helps to ensure that each student learns howto write clearly and concisely.

23.6.3 Journal-type article

For larger classroom projects, and certainly for independent research projects, studentsare required to prepare a complete journal-type article. At the North Carolina School ofScience and Mathematics, students use the Journal of Computational Chemistry as themodel for the journal article.

1. Title: students need to be creative in finding a title that appropriately captures theresearch work without being too long. We counsel students to avoid titles such as AComputational Study of .....


2. Author(s): in the classroom, this section provides us with an opportunity to intro-duce students to the idea of first and second authors, a phenomenon which they willhopefully experience at the undergraduate, graduate, and profession levels.

3. Institution: writers list their institutions. If more than one institution is involved,the order follows the order of the authorship

4. Keywords: students are required to identify 3-8 keywords that best capture thefocus of the research. We encourage students to do this last.

5. Abstract: the abstract follows the same format as described above. Students are en-couraged to write the abstract last. For the final exam in the NCSSM computationalchemistry class, we often give students an article from the Journal of ComputationalChemistry with the abstract missing and give them 90 minutes to read the articleand prepare a suitable abstract for the article.

6. Introduction: in this section, the writer presents the chemistry of the research. Thechallenge in this section is to provide the reader with enough background informationsuch that s/he can then read the rest of the article, but not have so much backgroundinformation that the article becomes lengthy. Student writers need to be able to makesome assumptions about the readership of the journal for which the article might besubmitted.

7. Computational Approach: in this section, the writer describes in some detailthe types of calculations performed, the model chemistries chosen (if appropriate),and the specific software tools used. This section should contain enough detail suchthat another computational chemist could reasonably duplicate the work. Again, thestudent writer needs to make some assumptions about what the reader already knowshow to do.

8. Results and Discussion: in this section, the writer presents most if not all of thedata. Data can be presented in appropriately labeled and captioned data tables andgraphical formats, with a written discussion referencing the data tables and graphics.For larger projects, students need to make decisions about how much data to reportin the article.

9. Conclusion(s): the conclusion section provides the writer with a chance to presenthis or her analysis of the data results, with the overall goal of providing the readerwith some important and/or useful understanding of the question being evaluated.The writer might also suggest ideas for further evaluation based on the results of thiswork.

10. Acknowledgment: the writer recognizes any individual mentor or other organiza-tion providing support for the work. For students at NCSSM, we require them to

23.7. SAMPLE PROJECT TITLES 15

recognize the funding support provided by the Burroughs Wellcome Fund and theNorth Carolina Science, Mathematics and Technology Center with this notation inthe Acknowledgments section:

Appreciation is also extended to the Burroughs Wellcome Fund andthe North Carolina Science, Mathematics and Technology Center for theirfunding support for the North Carolina High School Computational Server.

Student researchers using the Global Grid Exchange computational chemistry serverwould follow suit, using an acknowledgment as follows:

Appreciation is also extended to the Global Grid Exchange, ParabonComputation, and Cisco for their funding support for the ComputationalChemistry Server for Pre-College Students.

This type of requirement helps students understand the role of funding agencies thatsupport science and scientific research.

11. References: learning how to properly prepare a references section is an importantskill for student writers. The school media specialist can often help with this aspect.For computational chemistry articles, the student must cite the use of specific softwarepackages, servers, etc. A standard citation format is used for these entities. Thereader is encouraged to look at the example journal article written for the pyridineprotonation lab, found on this website, for examples of how to cite WebMO, the NorthCarolina High School Computational Chemistry server, and the various softwaretools.

23.7 Sample Project Titles

Below is a list of project titles for a variety of student-designed research projects conductedover the past several years.

• Transition State of a Creatine Molecule during Dehydration

• The Diels-Alder Reaction

• Comparison of Relative Sweetness to Molecular Properties of Artificial and NaturalSweetners

• Comparative Study: Sarin and VX

• Is there a transition state for the insertion of ethylene into the Ziegler-Natta catalyst?

• Gaussian94 Analysis of C60


• GAMESS Animation Study of LiH

• Transition State Study of a Diels-Alder Reaction

• Transition State Study of a Cocaine Molecule

• Basicities of Amines

• Comparison of the Bonding Properties of Serotonin and Lysergic Acid

• Conformational Anaysis Study of n-Butane

• Transitional State Study of ATP

• Potential Energy Scan of an Ester using Gaussian94

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Computational Chemistry Researchchemistry.ncssm.edu/book/chap23/Chap23CompChemResearch.pdfChapter 23 Computational Chemistry Research 23.1 Key Notes 23.1.1 Choosing a Research Problem: