The Spectral Game with ChemDoodle

In the summer of 2009, we published an article on the Spectral Game. This game is based on spectra uploaded as Open Data (in JCAMP-DX format) on ChemSpider (currently about 2000 H NMRs and a few C NMRs, IRs and NIRs). Students get points by clicking on the molecule associated with the spectrum on display.

Although this has proved to be a useful tool to teach spectroscopy (especially H NMR), there have been some limitations, which are related to the use of Java (JSpecView) to provide an interactive display of the spectra.

1) Spectra do not display properly on Macs - there are problems with the "right-click" options in JSpecView. It took me a really long time to understand why some of my friends were really unimpressed by JSpecView. When I recognized that they were all Mac users I took a look and it became clear.

2) Spectra do not display at all on smartphones because of the Java components

I am very happy to report that these issues have been overcome (for the most part) using ChemDoodle. Through a collaborative effort between Kevin Theisen, Andrew Lang, Antony Williams and myself, we now have a non-Java based version of the Spectral Game at SpectralGame.com.



The game plays well on Mac, iPhone and iPad. However I have seen it fail on 2 Androids so there are still a few kinks to work out. Luckily I happen to be teaching NMR right now in my organic chemistry course so my students will be testing out the ChemDoodle version extensively.

There are some really nice additional features as well. My favorite is the auto-scaling of the integration line when zooming in. In the JSpecView version, integration is problematic because, when zooming into high field peaks, the start of the integration line does not reset to zero and this requires several iterations of changing the integration offset to get a usable measurement.

Another advantage in the ChemDoodle design is the simplicity of the interface. There are no right-click options: everything available is clearly labeled at all times (toggle integration, reset spectrum and view header information). This makes the game easier to learn and play.

I would especially like to thank Kevin Theisen for being so responsive on the ChemDoodle end. I was skeptical that we would have a playable game for this term but he addressed all of our major issues very quickly.

NMR integration web service expanded

The ONS Challenge has extensively used a web service created by Andrew Lang to automatically calculate solubility from NMR spectra. One of the constraints of the service was that the JCAMP-DX file had to be deposited in a special folder on a server at Drexel.

Andy has now modified the script so that the JCAMP-DX file can be located anywhere on the internet. I have prepared a modified Google Spreadsheet to serve as a template for SAMS calculations (Semi-Automated Measurement of Solubility). Simply enter the url to the JCAMP-DX file in the appropriate column and fill in the ppm ranges and corresponding hydrogen numbers for the solvent and solute, and molecular weight and density data. (The predicted density of solids can be found on Chemspider). The concentration of the solute will then be automatically calculated based on an assumption of volume additivity.

The web service (which handles baseline correction) could be used for any other purpose involving the integration of spectra. Just make a copy of the Google Spreadsheet and modify.

Note that the JCAMP-DX files must be in XY format. If your instrument saves spectra in a compressed format they must be converted to XY. The desktop version of Robert Lancashire's JSpecView can be used to carry out the conversion.

This template spreadsheet also features a service in a cell to display the NMR spectrum by simply clicking on the link inside the cell. This is very handy because it obviates the need to create an HTML file which must normally accompany the JCAMP-DX file for viewing. Being able to quickly view a spectrum from a particular row within the Google Spreadsheet makes tracking data provenance very intuitive and errors easy to spot.

Spectral Game talk at ACS Fall 09

Yesterday (August 17, 2009) I gave my talk on the Spectral Game at the Using Technology to Enhance Learning in Organic Chemistry symposium at the American Chemical Society meeting. I was not able to attend the entire symposium but luckily I did catch David Soulby's talk on using Google groups to distribute NMRs for labs that require many students to submit samples. I am a fan of using free and hosted services to simplify workflows of all types.

Also in attendance at the symposium were Liz Dorland and Bob Hanson. It was good to catch up with them. Bob shared a story of how he has been assigning his students tasks in his organic chemistry class which lead to updating Wikipedia. There is so much potential for using the educational infrastructure to create better scientific content for everyone.

My talk on the Spectral Game highlighted the role of openness in teaching and research to create new educational tools, especially for learning NMR. Tony Williams said a few words at the end about ChemSpider, RSC and some upcoming opportunities to publish synthesis articles on ChemSpider.

Spectral Game ACS Fall 09

View more presentations from Jean-Claude Bradley.

Spectral Game paper live on the Journal of Cheminformatics

Our paper on the Spectral Game is now published:

Jean-Claude Bradley, Robert J Lancashire, Andrew SID Lang and Antony J Williams The Spectral Game: leveraging Open Data and crowdsourcing for education Journal of Cheminformatics 2009, 1:9 doi:10.1186/1758-2946-1-9

This has been an especially gratifying collaboration because of the enthusiasm and vision of my co-authors. The philosophy behind the game is deeply rooted in openness and as a result it is an open ended evolving project. Any new NMR spectra uploaded to ChemSpider and marked as Open Data will continue to be automatically incorporated into the pool of problems. Teachers and students from around the world can play the game and flag problems or errors as they arise. This blurs the line between content creators and consumers and I think reflects a powerful trend that is occurring in education.

Another aspect of openness relating to this endeavor is the communication of our progress. Our paper was written on a public wiki. Not only were we able to discuss our progress on recorded talks and blog posts, but we were also able to cite these as regular references in the paper. And of course the Journal of Cheminformatics is itself an Open Access peer-reviewed publication so there is no limitation to sharing the final product.

Controversy still rages in the blogosphere about the wisdom of blogging research results prior to publication in peer-reviewed journals. It is true that this practice limits where articles can be submitted. Since many of our references are from the Journal of Chemical Education, we contacted the editors to see if they would accept our paper. Unfortunately their current pre-print policy did not allow them to do so.

If more authors begin to see the value of early disclosure it may just start to tip the balance towards journals such as the Journal of Cheminformatics.

Andrew Lang and I have just completed another paper on Chemistry in Second Life - written in the same way - that one just got submitted to Chemistry Central Journal.

NMR integration progress for solubility measurements

In a previous post I reported about issues with using H NMR integrations for quantitative assessment of solute concentration to determine solubility. Using default parameters, a study by David Bulger revealed that integration of the methyl group on 2-phenylbutanoic acid lead to only 8.4% average error while the methine H gave an average of 26% under-integration.(ONSC-EXP102)

We have tried to select methyl or methylene groups whenever possible but obviously this won't work for many compounds, especially our series of aromatic aldehydes and carboxylic acids.

Khalid Mirza has just done a study using longer relaxation times and the results appear very promising (ONSC-EXP103). For 4-pyrenebutanoic acid using default parameters the integration of the aromatic vs. methylene hydrogens was off by 9-18% while extending the relaxation time (d1=50s) reduced the error to less than 1.2%.

Furthermore, Marshall Moritz used the new settings in a measurement of a known concentration of 4-nitrobenzaldehyde in acetonitrile and came within 3.2% using an aromatic hydrogen (ONSC-EXP111). Use of the aldehyde hydrogen was not as good, although much better than what we normally see with the default settings.

So I am cautiously optimistic that we are likely to get better data going forward.

Complications with solubility measurements of aldehydes in alcohols

Last week I mentioned that we had started measuring temperature solubility curves. Since 4-nitrobenzaldehyde in methanol also got flagged by our Outlier Bot we picked it as the next one to process. This one has bothered me for some time because our values have systematically come out to about half of those published by Maccarone, E.; Perrini G. Gazetta Chimica Italiana. 1982, 112, p. 447. (private access) In this paper temperature curves for the solubilities were also provided and so I thought this would be a great opportunity to validate our sequential precipitation method.

This experiment (ONSC-EXP110) turned out to be very puzzling. On the day that we tried to make solutions we could not get as much material to go in as expected from the paper, even by sonicating at 40C. The next day some of these samples went into solution and then we could not get precipitation to occur for some samples even at 0C.

However, an examination of the NMRs of the samples with lowest concentration revealed the problem. It turns out that they were about 50% converted to the methanol hemiacetal. The NMR clearly shows the coupling between the benzylic and hydroxyl protons at 5.6 and 6.8 ppm, each integrating for 1H each compared with 2H for each of the new peaks in the aromatic region.



It turns out that the hemiacetal was present in all our previous measurements for 4-nitrobenzaldehyde in methanol but we didn't spot it. Furthermore we found significant hemiacetal formation for 2-chloro-5-nitrobenzaldehyde, 2,6-dichlorobenzadehyde and 4-chlorobenzaldehyde but only trace on none for others like veratraldehyde (ONSC-EXP033 has several of these NMRs). So it appears that if the aromatic ring bears sufficiently electron withdrawing groups hemiacetal formation is facilitated without the presence of a catalyst. This makes sense from a mechanistic standpoint.

Since the hemiacetal forms so easily in these cases I wonder why there was no mention made of it in the Maccarone paper. They assayed concentration using GLC - perhaps the hemiacetal decomposed quickly under those conditions? (PNBA is para-nitrobenzadlehyde):

From a practical standpoint is it even possible to measure the solubility of 4-nitrobenzaldehyde in alcohols? If you try to make up a solution for a reaction the concentration will be much less than calculated. With an excess of alcoholic solvent it seems unlikely that a reaction consuming the aldehyde will shift the equilibrium enough to make the formation of the hemiacetal inconsequential.

I think that for the Ugi reaction the implication of this is that alcoholic solvents should not be used for aldehydes bearing electron withdrawing groups.

Recent insights about solubility measurements

Over the past several months we have learned a lot more about measuring non-aqueous solubilities. (see experiment list) Here is a summary:

1) Sonication: It can be really difficult to reach saturation for some compounds. Since we started the ONS Challenge project in the fall of last year students have used all kinds of methods to mix the solvent and solute. For a while we required that solid remain during 10 minutes of vortexing. However, this proved problematic for doing lots of samples in parallel and required the researcher to stand there holding the vials on the vortexer.

So to be able to leave samples mixing unattended we started using a sonicator. This certainly seems to be a major improvement over vortexing. But, as an unintended benefit, sonication also caused the temperature to rise. Upon cooling to room temperature, additional solid is often observed to come out of solution - the only sure guarantee that saturation has been reached. Our current protocol is to continue to add solute until 30 minutes of sonication leaves solid in the vials. Temperature of the bath is also taken before and after to ensure reproducibility.

2) Screw Cap Vials: One of the problems with sonication and increasing temperature is that standard one dram vials with caps that snap in often pop out. Using half-dram vials with screw caps completely solved that problem.

3) Filtration, centrifugation and decantation: Coming up with a common protocol to separate the supernatant after saturation is reached is not as straightforward as it might seem. The problem is that saturated solutions can behave quite differently. The easiest behavior to deal with is when the solute just settles on the bottom and simple decantation can be used. This typically happens for low solubility cases where the solute is much more dense than the solvent. In other situations a suspension forms that does not settle quickly. Centrifugation for a few minutes often resolves that issue and then the supernatant can be decanted. However, there are more difficult suspensions that do not settled after centrifugation. The worst of these actually form a gel. We have found that filtering through as Pasteur pipette packed with a small piece of cotton usually does the trick. The gel or suspension is transferred into the pipette and a bulb is carefully squeezed to try to get at least a drop of supernatant out. Even getting a single drop can be challenging sometimes so it is fortunate that our NMR method does not require accurate volume measurements.

4) Evaporation of supernatant: Sometimes we observe higher solubilities than the known saturation values. This was puzzling because looking at the NMRs it was clear that the ratios of the solute to solvent were real. We traced back this problem to the way the supernatant is handled. When the drop is introduced at the top of the NMR tube it rolls down and a significant amount of solvent can evaporate. When the deuterated solvent is then added the ratio of solute to solvent will appear to be much higher than it was in the saturated solution. This is especially problematic for volatile solvents like THF. A similar effect can be caused by waiting too long to take the NMR as solvent does evaporate slowly even with a cap on. The solution to this problem is to transfer the drop of saturated solution directily into a vial containing the deuterated solvent and taking the NMR immediately.

5) Deuterated solvent considerations: We have also had problems with solutes precipitating out when diluted into the deuterated solvent. Polyphenols in DMSO or THF tend to do this when diluted in CDCl3. In this case diluting in DMSO-d6 resolves the issue. If a solvent other than DMSO is used non-deuterated DMSO can be added to DMSO-d6 to conserve deuterated solvent. Its only purpose is to enable locking during NMR acquisition.

6) Additivities of volumes and density predictions: There are two assumptions made in the way we measure solubility - that volumes are additive and that the predicted densities (via ChemSpider) of solid solutes are accurate. If one or both of these assumptions is a dominant contributor of error, we would expect the maximum deviation to occur at higher concentration. To investigate this issue (EXP102) David Bulger made up known concentrations of 2-phenylbutanoic acid and measured the SAMS solubility using the integration of the terminal methyl and the methine proton. Then the error was plotted against concentration.

It turns out that the error does not increase with increasing concentration suggesting that - at least in this system - those two assumptions hold up to 3M.



However there was a marked difference in the error of the methyl (8.4% average) and the methine H (26% average). Clearly the methine proton is systematically under-integrating, a feature of a longer relaxation time. The solution to this in general would be allow sufficiently long relaxation times during NMR acquisitions and we are looking into this.

Still, lets put these results into context. Is a 26% error that bad? Well it depends on the application. The purpose of this project is to give chemists guidelines in choosing solvents for carrying out their reactions. Whether the solubility is 1M or 1.26M is not going to be of much concern to plan a reaction at 0.5 M and rules out reactions at 1.5M.

Also note that very small temperature changes can have very large effects on solubility. For example if we look at the solubility of 4-nitrobenzaldehyde in various solvents between 26C and 19C we find differences of 45% in acetonitrile, 34% in benzene, 59% in carbon tetrachloride, 42% in methylene chloride and 36% in toluene. This temperature range is within the variation of what could be considered "room temperature" in a lab (at least the ones I have worked in).

Sometimes temperatures are reported in solubility studies but often they are not. For example, the solubility of aspirin is reported as 1:5 in ethanol in this book. No exact temperature is given and this is not a very precise measurement. But there is enough information there to plan a reaction or to gain an appreciation for roughly how much solvent to use for a recrystallization.

We will never control for all parameters. For example, even if we have an exact measure of temperature (and recently we have been leaving vials equilibrate in 23C water baths), we don't degass solvents or work under rigorously anhydrous conditions.

The key question to consider: Is it more useful to make our results available immediately and improve them over time as we learn - or is it more helpful to keep them closed until an arbitrary standard has been reached?

Baseline correction for automated integration of NMR JCAMP-DX files

We were initially getting a surprisingly large solubility measurement for one of our solutes (spectrum from ONSC-EXP077). After investigating, it was clear that the discrepancy was originating from a peak with a sloping baseline:


The web service was integrating all of the area beneath the peak and the raised baseline. After discussing the situation with Andrew Lang, he modified his code to exclude the area beneath a linearly sloping baseline. Andy's code is Open Source and made available here, including detailed instructions for anyone wishing to implement it themselves. This modified web service is included in the most recent Google Spreadsheet template for semi-automated measurement of solubility using NMR.

The progress of science is a clumsy walk toward a non-attainable ideal of full understanding and control. With every experiment we have to re-question what think we know as variables change. This is why I am so passionate about Open Notebook Science and having all stakeholders interact at the level of the individual experiment. We caught this issue early and we were able to deal with it because our computational collaborator was engaged in details with the chemists and responsive.

Spectral Game Winners

Following up on my last post about the SpectralGame, I have given out 2 molecular model kits to the highest scoring students in my CHEM242 class.

The first winner was Scott Beaudoin with 24 points followed by HaeJi Choi with 17 points.

The current high scores for the Drexel students can be accessed here. High scores from everyone in the world can be found here. The top score is currently 40 by VK.

Andy and Tony continue to fine tune the operation of the game. The recent introduction of a "Reload Spectrum" button below the molecules prevents the game from stopping prematurely if the spectrum won't load for any reason.

We still welcome contributions of spectra (NMR, IR, UV, MS, etc.) and players!

Semi-automated measurement of solubility using NMR

Over the past few days Andrew Lang and I have been discussing ways of streamlining the measurement of non-aqueous solubilities using NMR. Inspired by David Strumfels' VBA code on Excel to automatically measure kinetics, Andy found a way to directly extract the integration values from the H NMR spectra hosted on our server in JCAMP-DX format.

We have set up a Google Spreadsheet (see ONSC-EXP062B for an example) that automatically calculates solubility based on information that the researcher provides. What is required:

• A link to the NMR spectrum (the HTML file linking to the JCAMP-DX file)
• Density and molecular weight of the solute
• Density and molecular weight of the solvent
• A range in the solute to integrate with the number of corresponding Hs
• A range in the solvent to integrate with the number of corresponding Hs

The spreadsheet calculates the molar ratio of the solute to solvent then the molarity by making use of the assumption that the volumes of the two components are additive. The volume of solids is typically not available experimentally but ChemSpider gives a reasonable prediction. We have been using this assumption to convert published solubility values from g solute/ 100 g solvent to molar. In order to prevent taxing the server, once the measurements are computed they are stored in a database so that the spectrum and calculations don't have to be performed again.

The beauty of this approach is that there are no volume measurements. A saturated solution is made then, generally diluted in a deuterated solvent. When using an internal standard the volume of the saturated solution and the volume (or weight) of the standard must be known exactly. It is often difficult to micropipette some solvents and there is always the possibility of making an error in the handling of the micropipette. In general the fewer variables there are the more likely the results will be reproducible.

This is method can save a lot of time but it is not as automated as it could be. The densities must be looked up manually, although the molecular weight is automatically calculated from the common name using a web service by Rajarshi Guha run directly from within Google Spreadsheets. It also requires students to define solvent and solute ranges manually. All of the input cells are colored green, the output red and the intermediate calculations are in yellow.

However, once a range for a solute or solvent (and corresponding number of hydrogens) has been determined it can be used as a handy default and we will be collecting these and storing them in this sheet.

Does this mean that students don't need to think anymore?

Used properly, this system should actually elevate the level of thinking, in much the same way that the calculator did not remove the need for thought in data analysis. It just removed a lot of the tedium of manually calculating square roots and all of the associated sources of error in manual calculations of that type.

Students should use this tool to handle more measurements - faster - and think about their results in aggregate form. The ability to detect systematic errors becomes an essential skill to be developed. Also students need to spot problematic results quickly, for example where solvent and solute peaks overlap - or where there are baseline anomalies.

Of course even these last issues of quality can control can probably be automated to a large extent and we will report on this as we go. For example, it is conceivable that the NMR of a solute and solvent can be predicted or looked up automatically (on ChemSpider for example) and probable peak overlaps could be flagged. Software could also probably detect a mislabeling error.

At this point, we are getting closer to scientific progress by machine-to-machine communication on the free open read/write web. All we would need are a few groups around the world who see the value in endeavors such as this and donate a part of their NMR autosampling time. I am sure we could come up with simple ways of automatically converting files on their local computers to JCAMP-DX format and automatically upload them. We also need people to make up saturated solutions - but with the decoupling of tasks in this new workflow - these don't necessarily have to be the same people who process the NMR spectra.

Spectral Game update

The end of February 09 has come and gone and nobody hit the 100 points to win the molecular model kit I announced earlier for the Spectral Game. The highest score in that time period was 75.

Since my CHEM242 class is having 2 tests and one exam in the next 3 weeks I thought I would make the next prize available to them exclusively. The student from that class who scores highest by 9:50 Wednesday March 4, 2009 will win a molecular model kit. That happens to be the end of class on that day. The scores have been reset.

The game has been improved considerably during the past few weeks. A few security flaws were fixed, including modifying what metadata can be viewed via JSpecView and preventing the refresh button from selecting a new set of molecules. The game play was also changed to get increasingly more difficult over time, including adding more molecules and a timeout after the first set of ten spectra. This work was a collaboration between Andrew Lang, Antony Williams, Robert Lancashire and myself.

We are very excited by what we have put together so far. There are currently 457 H NMR, 389 C NMR, 11 IR and 29 NIR spectra. This is only possible because of people who submitted their spectra to ChemSpider as Open Data - please keep uploading!

The game has been played 1,824 times, viewing the spectra a total of 8,652 times - with a lot of curation by users. (If you see something wrong with a spectrum you can write a note and that helps us clean up the database). We have had 612 unique visitors from 37 different countries - a total of 13,919 page views in just over two weeks!

We now have a wiki with key links relating to the game. I also added the NMR notes from my CHEM242 class and we'll keep collecting resources. This could become a helpful resource to learn about NMR and practice it by playing the game.

Web based Spectra Game

Yesterday I used the NMR game in Second Life during our 2-hour Friday workshop in CHEM242. (We used a new location on Drexel island SLURL) The students who attended had looked at little or no material prior to the workshop. By the end I ended up explaining chemical shifts, complex coupling patterns and diastereotopic hydrogens differentiated by the presence of a chiral center. The only concept we didn't cover is integration, although we used peak size to take a guess about groups with lots of hydrogens (like trimethyl).

I think it was a very efficient way to teach NMR and the students can now go off and continue to practice till our next workshop Monday. Second Life has some advantages - such as the ability to mediate group study sessions where students from remote location can come together to play and discuss spectral assignments using either voice or chat. It is also nice to see the molecules in 3D, especially for bridged cyclic systems.

However, there is a bit of a learning curve to get into Second Life and not all computers have a suitable video card. So it is nice to now have the ability to play the game on a web browser. Andy set up the game play so that the score reflects the number of correct answers obtained in a row. There are also only 3 molecules to choose from instead of 5 in Second Life.

We're using JSpecView to render the spectra so expanding peaks simply requires dragging the mouse across the area of interest. It is also possible to integrate and view the metadata by right clicking.

Currently we mainly have H NMR spectra but we'll be adding lots more C NMR, IR, UV, MS, etc. It all depends on how many Open Data contributions we can find. If anyone has spectra to donate please upload them to ChemSpider and don't forget to check the box for Open Data.

This has been a wonderful example of rapid collaboration by Andrew Lang, Rajarshi Guha, Antony Williams, Robert Lancashire and myself.

Give the web Spectra Game a spin and see if you can beat the high score....

Tony Williams Drexel Visit

Tony Williams stopped by Drexel on August 21, 2008. After a nice chat with Martin Walker over lunch, Tony presented a demo of ChemSpider. The timing was not great because this was concurrent with the ACS meeting in Philadelphia. However, Tony recorded the session and it is available here as a Flash screencast.

Tony also took the opportunity to make an announcement of some new text mark-up features about to be made available on ChemSpider. For a brief video and description see his blog post.

I met Tony when I was a graduate student at the University of Ottawa and he was running the NMR facilities there. Even though he had not touched an NMR in 12 years he clearly has not lost his touch and got us out of a serious jam with the acquisition of carbon spectra on our Varian instrument. Just like old times.

Once you get to know Tony you'll appreciate why so many of us are willing to support and put our trust in ChemSpider.

Older Males Prefer NMR of Ester

I was just looking at the YouTube Insight feature showing demographic and access info on my uploaded videos. Since I use my YouTube account mainly to provide solutions to organic chemistry problems in my undergrad classes it was surprising to see that the most active group of viewers were 45-55 year old men.


And the most popular video is the NMR of an ester, where I explain the effect of a chiral center on the splitting pattern of methylene groups.

NMR prediction on ChemSpider

As Tony recently mentioned, there is a new button on ChemSpider to predict H NMR spectra based on the nmrdb.org web service:


To give it a spin I am posting the experimental spectrum of Ugi product UC-150D underneath the predicted one.


This is going to be extremely helpful and yet another reason for using ChemSpider in active chemistry research. However, this tool does not replace the need for understanding how to interpret NMR spectra.

First, two of the predicted peaks - the phenanthrene H at 8.5 ppm and the benzylic H at 5.7 ppm - are off by almost half a ppm. Second, the algorithm does not take into account the diastereotopic nature of the methylene group centered at 4.8 ppm. This is predicted to be a singlet but appears, as expected, as a pair of doublets.

With this new tool there is a danger that students might think that they don't need to learn the finer details of NMR analysis since the predicted spectrum just pops up so conveniently. I hope people will report on what they find to be most and least reliable as they work on real problems.

The beauty of ChemSpider is that both the theoretical and experimental spectra can be stored in the same record. Yet another reason to continue to routinely upload our spectra.

Tag: InChIKey: PBZQTKRWYXTXIS-WLRTZDKTBU

NMR viewer in Second Life

Andrew Lang just finished coding this nifty little JCAMP-DX viewer in Second Life. The video shows that you can expand any area of the spectrum by typing zoom followed by the desired range in the chat box.

You can also type "back" and "reset" commands. It essentially functions like Robert Lancashire's JSpecView if it were running in Second Life (although integration is not yet implemented).

There are still a few kinks to iron out but it should work with any spectrum that can be represented in JCAMP-DX format: IR, CNMR, HNMR, UV-vis, MS, etc.

This should extend considerably the set of tools available to chemistry teachers who use Second Life to interact with students.

Give it a try on Second Nature island: SLURL. (You'll need the most recent version of Second Life to run this and click the link from within IE, not Firefox)

JSpecView Article on Chemistry Central

Robert Lancashire has just published an article in Chemistry Central Journal:

The JSpecView Project: an Open Source Java viewer and converter for JCAMP-DX, and XML spectral data files

Our lab has found this software to be key for communicating organic chemistry results within an Open Notebook Science environment. All NMR raw data and metadata are automatically recorded and users from anywhere can mine the spectra by expanding and integrating at will from a browser interface. This is an enormous improvement over the traditional method of storing and publishing spectra as images that cannot be expanded.

The article describes other useful applications, such as the integration of JSpecView with Jmol, to show the assignment of specific peaks.

The other reason I really like this article is that Robert has used some UsefulChem blog posts as primary references. This is an important way for the scientific blogosphere to get incorporated and accepted by the mainstream.

Abstract

The JSpecView Open Source project began with the intention of providing both a teaching and research tool for the display of JCAMP-DX spectra. The development of the Java source code commenced under license in 2001 and was released as Open Source in March 2006. The scope was then broadened to take advantage of the XML initiative in Chemistry and routines to read and write AnIML and CMLspect documents were added. JSpecView has the ability to display the full range of JCAMP-DX formats and protocols and to display multiple spectra simultaneously. As an aid for the interpretation of spectra it was found useful to offer routines such that if any part of the spectral display is clicked, that region can be highlighted and the (x,y) coordinates returned. This is conveniently handled using calls from JavaScript and the feedback results can be used to initiate links to other applets like Jmol, to generate a peak table, or even to load audio clips providing helpful hints. Whilst the current user base is still small, there are a number of sites that already feature the applet. A tutorial video showing how to examine NMR spectra using JSpecView has appeared on YouTube and was formatted for replay on iPods and it has been incorporated into a chemistry search engine.