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This edition of "Molecular Spectroscopy Workbench" discusses the use of two-dimensional Raman correlation spectroscopy (2D-COS) in the characterization of polymer fibers. We will show how the heterocorrelation of polarized spectra of a polyethylene terephthalate (PET) provides another means to characterize the changes in the local bonding of the atoms in the polymer that are extracted from the orientation dependence of the spectra. We will use again the spectra of PET fibers, because the spectral bands of this polymer have been extensively interpreted so that the 2D correlations can be used to analyze the structural changes without the need to employ band-fitting, which is known to sometimes produce non-unique results. In particular, the 2D-COS algorithms will enable us to identify which changes occur simultaneously (either in the same direction or in the opposite direction), and which changes occur non-simultaneously or sequentially, and which changes are necessary in order for the polymer to crystallize. At the end, we will note how this information can be useful to polymer engineering.

	We have previously described the use of two-dimensional Raman correlation spectroscopy (2D-COS) in the analysis of PET fibers (1), and a melt-quenched pellet (2). In the case of the fibers, we examined only the behavior of the ZZ spectra (both laser and Raman light polarized along the fiber axis), and for the melt-quenched pellet, which will not exhibit any orientation, there was no polarization analysis. For this column, we will look at the ZZ vs. RR components (polarizations parallel to vs. normal to the fiber axis) in heterospectral analysis. It is important to keep in mind that the intensities in the 2D-COS plots are related to changes in the spectra with temperature, and not to the intensities themselves.

	When Raman spectra are used for any kind of quantitative work, it is necessary to introduce a protocol for "normalizing" the spectra. Unlike infrared (IR) or ultraviolet–visible spectroscopy (UV–Vis) absorption spectroscopy, Raman spectroscopy is a single beam technique, so the spectral intensities can only be compared under well-defined conditions. Initially, I chose to normalize to the strongest feature in the spectrum, the aromatic band near 1614 cm

. But, because we would be using both the ZZ and RR spectra, and it is known that the ratio of this band increases when the fiber becomes oriented (3,4), we considered the possibility that this might not be the best method. Instead, we decided to normalize all spectra (in both the ZZ and RR sets) to the band at 632 cm

, which is known to be depolarized (4,5). In fact, if you examine the spectra of the fibers that we measured in the early 1980s, you can see that the intensities of both the 800 and 632 cm

 bands were higher in the off-diagonal configuration (ZR) than either of the diagonal configurations (ZZ or RR) confirming their B

Normal Modes Analysis in PET-Identifying the Atomic Motion in the Raman Bands

	Numerous authors have performed normal modes analysis of PET on which we will rely. The earliest ones were published starting in the early 1970s (3,5,6,7,8 and 10).

	The crystalline phase of a polymer will have all of its chains in the same conformation and orientation, and all the chains will exhibit translational symmetry. Spectroscopically, this state can be measured definitively by measuring the "phonon" mode in the very low frequency region that is attributed to the chains beating against each other in the unit cell. But this condition requires that there is more than one chain in the unit cell, which is not the case with PET (9). On the other hand, the chemical unit in PET contains two carbonyl units at the para positions across the aromatic ring, so their motion has the potential to interact providing two component bands; in the centrosymmetric crystalline form, the symmetric combination will be Raman active and the anti-symmetric component will be IR active. The best measure of crystallinity of which we are aware is the behavior of the carbonyl peak, which is known to sharpen in the crystalline phase (10) as determined by X-ray diffraction (XRD). This sharpening is attributed to resonance stabilization of the π electrons between the carbonyl and the aromatic ring. In fact, when we band-fit this spectral line in the amorphous phase, we find that we can fit to two fairly broad lines; in the amorphous phase, both the symmetric and the asymmetric combination will be Raman active. The band-fitted spectrum of an amorphous fiber is shown in the bottom spectrum in Figure 1, assigning the lower frequency band to the asymmetric combination, and the higher frequency band to the symmetric combination. After the fiber was drawn at RT, the intensity of the lower frequency band grows relative to the higher band, and its frequency shifts up towards the frequency seen in the crystalline phase. This change suggests that the drawing of the fiber has oriented the chains, which requires that the gauche configurations around the single bonds (C-C and C-O) are effectively eliminated; the lower frequency band is now close in frequency to that of the crystalline phase (as we shall see later), but much broader because of the rotational freedom around the single bonds. In the partially crystalline material (Figure 1, 3rd spectrum from the bottom) there are three bands in the fitted spectrum; we assign the lowest and highest frequency bands to the asymmetric and symmetric carbonyl stretches to the cis configuration in the amorphous phase, and the middle band to the symmetric combination when the carbonyls are trans to the ring. This positioning would be the configuration in the crystal form, but because of the heterogeneity of the angle between the carbonyls and the plane of the ring, the band is broad. When this fiber is drawn at RT, the lowest frequency band disappears and then two overlapping bands around 1727 cm

 appear. Because the lowest frequency band is presumably the asymmetric combination of carbonyl stretches (that is the IR type band in the amorphous phase), and the drawing operation eliminates the cis configuration, this combination becomes less Raman active, and is replaced by a more intense broad band at 1727 cm

, well resolved from the small sharper contribution from the "crystalline" trans component. In addition, the intensity of the highest frequency band drops significantly after drawing as the number of carbonyls oriented randomly to the aromatic plane decreases.


	Figure 1: Band-fitted ZZ spectra (from bottom to top) of amorphous fiber spun at 3500m/min, same fiber drawn at room temperature, fiber spun at 4500m/min (partially crystalline), and then the same fiber drawn at RT. 

	While it is possible to put together a story based on this band-fitting, the possibility to derive similar information from 2D-COS is very attractive. In particular, these features that can only be separated spectroscopically by band-fitting are expected to be apparent in the 2D-COS plots without special spectral treatment. In addition, by determining which other features correlate with which of these carbonyl bands, one can infer which changes in the molecular conformation of the entire chain determine the appearance of the different contributions to the carbonyl envelope. Remember that in examining the 2D-COS results, higher intensity means larger changes in intensity, and not higher spectral intensity.

	We have chosen to explore the 2D-COS of the two components of the polarized spectra, because it is clear from previous work that information is encoded in the polarization/orientation dependence.

	We have a series of polarized Raman spectra of a PET fiber immobilized in a chuck in the Linkam tensile stage, and then measured as the temperature was raised. As described earlier, we normalized all spectra to the asymmetric band at 632 cm

. We performed 2D-COS separately on the ZZ spectra, then the RR spectra, and then on the ZZ spectra against the RR spectra. It will be immediately clear that the different plots are indicating that different information is provided.

	Figure 2 shows the ZZ and RR spectra of the fiber held in the chuck and measured at 40 °C (bottom) and 100 °C (top). It is known that the response of the instrument will be better when the light is polarized normal to the grating grooves, which means normal to the slit, so a scrambler is mounted between the microscope and the entrance slit for all measurements to correct for the grating dichroism. A half wave plate was mounted in the laser entry path in order to control the orientation of the laser polarization. Because there can be some drift during the time that the temperature is raised, the alignment was checked routinely, but, just as importantly, all spectra were normalized so that the intensity in the 632 cm


	Figure 2: Polarized Raman spectra of a fiber of PET held in a chuck in a Linkam tensile stage at 40 °C (bottom) and 100 °C (top). In each case, the ZZ spectrum (colored green) has higher intensity in almost all bands (the RR spectrum is colored brown in order to differentiate the two). 

	We will focus on the following features in these spectra when we examine the 2D-COS plots:

		The carbonyl band sharpens in the crystalline phase, as discussed earlier. We will look to see if we can detect the 3 components discussed in the band-fitted spectra earlier.

 seems to broaden in the crystalline phase, but, in fact, is shifting to a higher frequency; the crystalline component is seen spectrally only in the RR spectrum but in the 2D-COS there is evidence for it in ZZ as well.

		In all spectra, there is a band at about 1124 cm

, with close to the same intensity in the ZZ and RR plots, but there is a shoulder at 1096 cm

 in the spectra of the amorphous material that grows in intensity in the high temperature spectrum, with the ZZ intensity surpassing that of the RR.

 of approximately equal intensity in the bottom ZZ and RR spectra of Figure 2, but, in the higher temperature spectra, there is a band of medium intensity at about 1000 cm

 in the ZZ spectrum, but no intensity is present in the RR spectrum.

	These features are indicated on Figure 2.

	In order to make the reading of this work easier, I will tabulate assignments of some bands that have been associated with morphological changes in PET (5,6,7,8,11,12,13,14) (Table I). In fact, critical to this work is the understanding that the local conformations determine the ability to orient, and then crystallize, and this point has been considered in some detail by many of the cited authors (and is implicit in the earlier discussion). In the crystalline form, the two >C=O groups must be trans to the ring and coplanar with it, but in the amorphous form can be at any orientation to the ring. Because the C-C and C-O single bonds have the freedom to rotate, gauche and trans conformers of the glycol unit can be defined around O or C atoms, and are best described in Figure 1 of Rodriguez-Cabello and associates (13), who followed the behavior of several spectral features as a function of annealing temperature, and found that only above the glass transition temperature, T

 (ca. 90 °C), were isomeric transformations (gauche to trans) observed. The hope is that the 2D-COS will elucidate this behavior with much reduced effort.

	Because there is so much information in these results, I am going to show 2D-COS plots only for two regions of the spectra in which some bands discussed above will be shown. The region between 1500 and 1800 cm

 includes information on the aromatic ring and the carbonyl band. The region between 950 and 1250 cm

 has information on the single bond stretches and 3-atom bends in the glycol region of the molecule. Keep in mind that it is this region that will change during alignment (during melt-spinning or drawing or annealing under stress). I will show both the synchronous and asynchronous plots for these regions.

	In order to extract more insight into the behavior of this material, Figure 3 will show the 2D-COS plots (both synchronous and asynchronous) for the ZZ vs. ZZ spectra (left), the RR vs. RR spectra (middle), and then the ZZ vs. ZR (right) in the aromatic/carbonyl region (top), and in the region of the carbon-carbon and carbon-oxygen single bond stretches and bends (bottom). For each set, the plots on the left are the synchronous plots, and those on the right are the asynchronous plots. Note that red means an increase in signal, and blue a decrease. The three sets of plots are showing very different behavior, and these differences have specific information in them. We will comment on some of what the ZZ vs. ZZ and RR vs. RR plots say, and then focus on the ZZ vs RR.


	Figure 3: 2D-COS plots of ZZ vs. ZZ (left), RR vs. RR (middle) and ZZ vs. RR (right). For each, the Synchronous is plotted to the left of the Asynchronous. The top set of plots show the aromatic/carbonyl region, and the bottom set of plots show the region of single bonds (C-C and C-O). The ZZ vs. RR plots will be reproduced in Figure 4 with the matching spectra for the discussion.

	We know that the largest changes in the spectra are occurring in the 1575-1750 cm

 region, which is what the synchronous plot shows. In fact, any attempt to change the intensity scale did not yield more detail. The asynchronous plot does provide some information. Both the 1735 cm

 (asymmetric combination) parts of the carbonyl band in the amorphous phase decrease before the 1725 cm

	In the region of the single bonds, the synchronous plot shows bands at ~1095 cm

 that grow simultaneously; both of these bands are associated with oriented or crystalline material. Curiously, we do not see a decrease in the 1030 cm

 band, something that I have observed in the spectra themselves, and was surprised by, because I was assuming that the 998 cm

 band; apparently this is not so, but is consistent with the band assignments–one band being a stretch, and one a bend. In the asynchronous plot in the region around 1100 cm

, we see something useful. Features at 1098 cm

 are out of phase; we have noted previously that a small feature at 1080 cm

 is observed as the fibers are orienting. Here, we see that this band disappears as the more prevalent 1098 cm

	In the synchronous plot, here, too, the 1614 cm

 band is increasing the fastest (but not as fast as in the ZZ plot, which this display does not show because the color intensities are not equivalent). In addition, we see a loss of a small feature at the lower frequency, which can be seen in the original data (Figure 2). The carbonyl region shows a complicated behavior, due to different behaviors of the three components. Some of this can be sorted in the asynchronous plot. The central part of the band at 1725 cm

 is growing (red in the synchronous plot), while 1720 and 1735 cm

 are much greater (our earlier discussions indicated that this band, the asymmetric stretch of the two carbonyl bands, largely disappears as the polymer chain orients).

	In the region of the single bonds, the synchronous plot shows an increase at 1095 cm

 blob even shows some filling in near 1080 cm

, which would be the feature that was discussed earlier in the ZZ discussion. The band at 1178 cm

 appears here in the RR plot, but not in the ZZ plot. There is no intensity in the region of the 1030 or 1124 cm

 bands in either the RR or ZZ synchronous plots; this observation implies that these bands represent molecular motion that is not sensitive to conformation changes in the oriented or crystalline forms. In the 1175 cm

 region, the lower energy band changes before the higher energy band (that is, there is a shift from low frequency shift to high frequency shift). In the region below 1100 cm

 blob in the synchronous plot. Examination of the 1175/1180 cm

 pair indicates that these two features behave oppositely when compared to the 1098 cm

 band, confirming the coupling of these bands in the crystalline conformation.

 in the synchronous plot is blue (negative). That is because as the ZZ intensity is increasing, the RR intensity is going down. The intensity of the crystalline phase at (1725, 1725) cm

 is increasing (red), while that at (1725, 1720) cm

 is blue, which means that the amorphous RR contribution is decreasing relative to the ZZ.

	Again, in the synchronous plot in the region around 1030 cm

, there is no intensity, because this band is apparently not changing. But the increase at 998 cm

, which is consistent with what we have seen so far, even though we are comparing the two polarization conditions. The point at (1185, 1185) cm

 is surprisingly also positive, which means that even though we did not see ZZ intensity in the ZZ vs. ZZ plot, there is apparently some activity here. The positive intensity at (1185, 1090) cm

 crystal band, correlating with the 1090 cm

 band that is present in both the crystalline and the oriented form. It would be interesting to acquire and analyze spectra of an amorphous material with increasing orientation. The point at (995, 1185) cm

 also shows a strong correlation between the two polarizations.


	Figure 4: 2D-COS plots of ZZ vs. RR in the same spectral regions shown in Figure 3. This figure also superimposes the spectra that are being used in the calculation.

	Here's where I am getting to the edge of my 2D-COS skills, which I am only learning "on the fly". But I am convinced that the conformations of different functional groups have to be coupled in order to first get full orientation of the chain and then crystallization, so let me give this a try. The (1725, 1095) cm

 point on the top left of Figure 5 indicates a positive coupling between these two bands in which we examine the coupling between the two different regions in the ZZ vs. RR plots. But the (1095, 1725) cm

 point on the bottom left is much sharper, indicating that the change is much more confined spectrally. In addition, there is a negative band at (1075-1120, 1715) cm

, indicating the decrease of the asymmetric carbonyl combination at 1715 cm

 in the RR spectrum relative to the increasing carbonyl at about 1725 cm

. There is a surprising correlation at (1095, 1600) cm

; I say it's surprising because we don't really see a spectral feature at 1600 cm

 (the small band that can be seen in Figure 2 is closer to 1580 cm

). And then there is a negative band at (1067-1125, 1615) cm

, which means that, relative to the ZZ growth between 1067 and 1125 cm


	Figure 5: Synchronous and Asynchronous plots of ZZ vs. RR comparing the two regions of interest: the aromatic/carbonyl region (1500-1800 cm

). Note that two comparisons are necessary because the exchange of spectral regions yields different spectra for ZZ and RR.

	Clearly, there is much more that can be said about the morphology of this PET fiber from these 2D-COS results than I have explored here. My goal has been to demonstrate that 2D-COS of vibrational spectra can provide more information on this (and other) polymers than simple spectral interpretation. By following dynamic changes (in this case caused by thermal changes), one can piece together a fuller picture of structural changes in a polymer. The point is to provide a tool for the engineer to use spectral changes revealed by 2D-COS to interpret structural changes determined by processing conditions, so that polymer materials can be rationally engineered for particular applications with known mechanical requirements. After I have had a chance to more fully interpret these results, I hope/expect to publish a full article.

	As always, I am recognizing Herman Noether posthumously for introducing me to polymer material science. I also want to thank Isao Noda for developing 2D-COS and introducing me to it; it is a multivariate tool that provides structural information from spectral features that cannot be easily "seen" in single spectra. I also want to thank my colleague Sergey Mamedov, who spent some time helping me to plough through matrix algebra that I learned 50 years ago.

	(6) S.K. Bahl, D.D. Cornell, F.J. Boerio, and G.E. McGraw, 

	(7) F.J. Boerio, S.K. Bahl, and G.E. McGraw, 

	(8) J. Stokr, B. Schneider, D. Doskocilova, J. Lovy, and P. Sedlacek, 

	(9) R.D.P. Daubeny, C.W. Bunn and C.J. Brown, 

	(11) M. Richard-Lacroix and C. Pellerin, 

	(12) C.C.C. Lesko, J.F. Rabolt, R.M. Ikeda, B. Chase and A. Kennedy, 

	(13) J.C. Rodrigues-Cabello, L. Quintanilla and J.M. Pastor, 

 is the Principal Raman Applications Scientist for Horiba Scientific in Edison, New Jersey. Direct correspondence to: 

Spectral changes revealed by two-dimensional correlation spectroscopy can be used to interpret structural changes in polymers determined by processing conditions, so that materials can be rationally engineered for particular applications with known mechanical requirements.

Heterocorrelation Using Polarized Raman Spectra in the Characterization of Polymers

	You know the situation. You go on holiday, have a great time, and the first day back in the laboratory you tell everyone about it, and then reality dawns. You must do some analysis. You go to your spectrometer system or the LIMS, try to log on and your mind goes blank..... What's my password? You have forgotten it! At this point it depends if your system is networked or not, but you either have to contact the IT help desk or an administrator, get your grovel pads out and beg for a password reset.

	What will happen now is that you will get a one-time default password, that when you log on to the system, you will be forced to change it. Now comes your big test: navigating the minefield that is your organization's rules for password complexity. Your super holiday memories are now receding into the mists of time at warp factor nine.

	Now we come face to face with the password paradox: easy to remember but easy to hack, and so on. To meet the rules, your new password must:

	• be at least 8 characters long
	• have at least three or all of the following:

	     - one upper case character
	     - one lower case character
	     - one number character
	     - one special character.

	Here goes: take the word "consultant" and convert it to meet your password rules into c0n5Ultan! There you go; it just rolls off your fingers as you type on the keyboard. The problem is remembering it. Here is where your pen hovers over an easily available piece of paper, ready to write it down and break at least three of your organization's additional rules on passwords.

	Then, just to make your descent into password purgatory even more interesting, every 30, 60, or 90 days you must replace it, and you can't reuse an old one.

	Passwords are a fact of life. Dumb and stupid passwords are also a fact of life. I was going to show you the most popular passwords from the hacked Ashely Madison web site as an example of poor password selection. However, this is a scientific magazine, and, as the editors would have redacted most of them, a more boring section of the top 20 stupid passwords of 2017 is displayed in Table I. You can imagine the cerebral effort that the owners of these passwords used in devising them.

	The biggest issue with complex passwords is remembering them, so this is why they are written down by some users. As an auditor, I take great delight in turning over keyboards in the laboratory to see if there are any notes underneath with passwords written on them. Although, in some laboratories, my job is made immeasurably easier, as shown in Figure 1. Even better was a typed note on the keyboard of one instrument: Operator Password = 1111. The philosophical question that arises is, What idiots are employed here that need a written reminder for such a password?


	Figure 1: How not to set up user accounts (2) (published with permission from the RSC).

	Let us question the need for complex passwords and changing them regularly. Are both requirements absolutely essential? It appears that there is a whole IT security industry built on the premise that we need strong passwords that are changed at regular intervals. Operating systems, and many general as well as laboratory applications, have functions to ensure that these requirements are enforced rigorously.

	We have password complexity rules, which are a pain to comply with. However, intrepid users have simple ways of meeting the password policies. We'll take an example from Table I: password.

		We need an upper-case character = Password

		We need a special character = Password1!

		We need to age the password = Password2!, Password3!, and so on.

	Simple compliance, but easily broken. Hence the need for a directory of unacceptable passwords.

	Consider the problem with passwords from an analyst's perspective. You want to do some spectroscopy, and you must log on to an instrument to do this, but verifying who you are is an activity that stands between you and the spectrometer. Logging on is a pain with complex passwords; essential for ensuring data integrity and data security, but still a pain. Implementation of a policy for complex passwords may lead to compromised security, as users are more likely to write down their complex passwords, or there is an increased number of calls to the IT Help Desk to reset locked accounts. The issue is compounded if a user needs to access multiple systems each with a different password; oh, joy. Hence the rise for networked applications of single sign-on, and only a single password to remember. Unfortunately, even with a single complex password, it is not easy to remember, and hence the unofficial workaround of writing it down.

	However, approaches to passwords and their construction have changed. Enter stage left the NIST Information Technology Laboratory.

	NIST is the National Institute of Standards and Technology, a U.S. government science facility that produces standards, reference materials and lots more besides (see 

 for more details). One of the divisions of NIST is the Information Technology Laboratory that is responsible for developing IT and cybersecurity standards for the U.S. government and its agencies. One of their outputs is via a series of NIST special publications 800 series (

	In this column, I want to focus on a suite of standards under the esoteric title of n SP-800 63 Digital Identity Guidelines. This consists of the following documents:

		SP 800-63-3, Digital Identity Guidelines, provides an overview of general identity frameworks, guidance regarding use of authenticators, credentials, and assertions together in a digital system, and a risk-based process of selecting assurance levels (3).

		SP 800-63A, Enrollment and Identity Proofing; the process to verify users are who they claim to be (4).

		SP 800-63B, Authentication and Lifecycle Management; an authenticator is something a user has and controls (such as a password) that is used to authenticate the subject's identity (5).

		SP 800-63C, Federation and Assertions; this is verification of a person's identity by a trusted third party, who can then provide this information to other parties. As such, it is outside the scope of our password discussion (6).

	You may be wondering what all this has to do with passwords. As you delve into the detail, you find some gems that help the password debate are contained in SP 800-63B (5).

	SP 800-63B (5) presents three levels of Authenticator Assurance Level (AAL 1, 2 or 3). The higher the AAL, the better the capabilities and the greater the resources required to hack a computer. Therefore, risk of unauthorized access is reduced compared with a lower AAL or lesser effective protection.

		Authenticator Assurance Level 1 (AAL1) provides confidence that user are who they claim to be by single-factor authentication (password) in combination with a valid user identity to access a computerized system. Key to success is that users do not disclose their passwords, and that the passwords are of sufficient strength to deter a hack.

		Authenticator Assurance Level 2 (AAL2) provides high confidence that users are who they claim to be via two factor authentication. This is typically a known password followed by entering a number that is sent via text or voice to a user's registered phone number.

		Authenticator Assurance Level 3 (AAL3) provides very high confidence that users are who they claim to be, as they are in possession of a cryptographic key and hardware registered to a user. Authentication at this level is based on proof of possession of a key through a cryptographic protocol.

	As you can see, with passwords alone, we are down with the bottom feeders on AAL1. Don't despair, there are other factors to consider, such as physical security of your buildings and laboratories to mitigate the data security risk but not data integrity.

	What does this NIST publication call a password? A

. Why make something simple, when you can make it complex? Don't worry, I'll refer to MSAs as 

	A password is something that is known only to you, and is impractical for a colleague or hacker to guess (with the exceptions presented in Table I). Although the NIST SP 800-63B mentions that service providers can allocate you a secret password, I will only consider passwords that you can make up yourself.

		Passwords should be at least 8 characters long.

		There will be a list of disallowed passwords (such as those in Table I), so if you select one on the list you will be required to select another password.

	Whoa! What happened to the complexity criteria that we listed earlier?

	In Section 10.2.1, there are some usability criteria for passwords that are summarized in Table II. Some of these comments will cause apoplexy in many IT/IS departments, due to their being no complexity and no enforced password aging. You can almost hear the sacrifice of sacred cows in the background.

	Appendix A of NIST SP 800-63B (5) is devoted to a discourse on passwords, and it notes that users are frustrated with having to remember complex passwords; this is compounded by our brain's limited ability to remember them. Hence the selection of simple, easy-to-guess passwords as shown in Table I. Of note, there are the following sentences:

		Analyses of hacked password databases has shown that the benefit of policies for complex passwords is not as significant as initially thought, but there is severe impact on usability (5).

		Users should be encouraged to make their passwords as lengthy as they want, within reason (5).

	The old criterion that password complexity is essential for computer security is not proven, and the sole requirement for computer security is password length so that passwords can be easily memorized. Allied to this is the need to avoid the use of commonly used passwords. As NIST SP800-63B notes apart from length "no additional complexity requirements are imposed" (5).

	Each time a character is added to a password, the difficulty to crack it increases exponentially. For example, an 8-character password has 95

 combinations (95 being the number of keys) and a 10-character password has 95

 combinations. However, this only applies on brute force attacks. Most of our laboratory systems in the laboratory should have a limit on the number of attempts before an account is locked.

	The good news is that password complexity and aging are not essential elements for computer security as shown in NIST SP800-63B. Will corporate password policies change? The bad news is, probably not.

	(1) K. Korosec, "The 25 Most Common Passwords of 2017 Include 'Star Wars'" (2017). 

http://fortune.com/2017/12/19/the-25-most-used-hackable-passwords-2017-star-wars-freedom/

Validation of Chromatography Data Systems: Ensuring Data Integrity, Meeting Business and Regulatory Requirements

 (Cambridge: Royal Society of Chemistry, Cambridge, UK, 2nd Ed., 2017).

	(3) P.A. Grassi, M.E. Garcia, and J.L. Fenton, 

NIST Special Publication 800-63-3 Digital Identity Guidelines 

(National Institute of Science and Technology, Gaithersburg, Maryland, 2017).

NIST Special Publication 800-63A: Digital Identity Guidelines Enrollment and Identity Proofing Requirements 

	(5) P.A.Grassi, J.L. Fenton, E.M. Newton, R.A. Perlner, A.R. Regenscheid, W.E. Burr, and J.P. Richer, 

NIST Special Publication 800-63B: Digital Identity Guidelines Authentication and Lifecycle Management 

	(6) P.A.Grassi, J.P. Richer, S.K. Squire, J.L. Fenton, and E.M. Nadeau, 

NIST Special Publication 800-63C: Digital Identity Guidelines Federation and Assertions 

 is the Director of RD McDowall Limited and the editor of the "Questions of Quality" column for 

s sister magazine. Direct correspondence to: 

The password paradox states that simple passwords are simple to remember but easy to break, but complex passwords that are difficult to hack are also difficult to remember. Is there a better way?

Pesky Passwords?

We have spent over a year exploring the infrared spectroscopy of carbonyl containing functional groups. Before we move on, we will review the group wavenumbers of the many C=O containing functional groups we have looked at, and discuss how to distinguish different carbonyl containing functional groups from each other. 

	For over a year now, we have been studying the infrared spectroscopy of the carbon-oxygen double bond, C=O, otherwise known as a the carbonyl group (1–8). Given the breadth of material covered, it makes sense to devote this column to a review.

	Recall (1) the electronic structure of the carbonyl group, as seen in Figure 1. Carbonyl bonds are highly polar because of the large electronegativity difference between carbon and oxygen. As a result, the carbonyl carbon has a large partial positive charge, and the oxygen has a large partial negative charge. Recall that when in a chemical bond there are two charges separated by a distance it forms what is called a dipole moment (9). Additionally, remember that one of the things that determines the intensity of infrared peaks is the change in dipole moment with respect to bond length, dµ/dx, during a molecular vibration (9). And we have certainly seen that in pure substances containing a carbonyl group, the C=O stretch is almost always the strongest peak, and is one of the strongest peaks you will ever see in infrared spectra (9). For the functional groups we have examined, the C=O stretch typically falls between 1900 cm

 (going forward, assume all peak positions are in cm


	Figure 1: The chemical structure and charge distribution in a carbonyl bond.

	Carbonyl bonds can be divided into two classes, depending upon what type of carbon(s) are attached to the carbonyl carbon. A 

 has only saturated carbons attached to the carbonyl carbon. An 

 has one or more aromatic carbons attached to the carbonyl carbon. An example of an aromatic carbonyl group is seen in Figure 2.


	Figure 2: The p-type orbitals and conjugation within an aromatic carbonyl group.

	Saturated and aromatic carbonyl groups can be distinguished from each other using infrared spectroscopy. In general, aromatic C=O stretching peaks fall ~30 cm

 lower than saturated C=O stretching peaks. Aromatic rings, such as benzene, contain p-type orbitals with electron density that sticks up out of the plane of the molecule (10), as illustrated to the left in Figure 2. The carbonyl group also contains a p-type orbital that points through space towards the orbitals on the aromatic ring, as is also illustrated. The orbitals are close enough that they somewhat overlap, allowing a portion of the electron density from the carbonyl bond to be pulled off into the benzene ring, resulting in a phenomenon known as conjugation, which is illustrated at right in Figure 2. Conjugation weakens the C=O bond, lowers its force constant, and hence its peak position is lowered, on average about 30 cm

 (1). Thus, for almost every carbonyl containing functional group, which we have discussed, two carbonyl stretching regions exist, one for the saturated and one for the aromatic versions of the functional group.

	The ketone functional group has the chemical structure seen in Figure 3.


	Figure 3: The structural framework of the ketone functional group.

	Recall (1) that the two diagnostic group wavenumbers for ketones are the C=O stretch and the C-C-C stretch. For saturated ketones, these two peaks fall at 1750±10 and from 1230 to 1100.

	Aldehydes feature a carbonyl carbon and a unique aldehydic hydrogen bonded to the carbonyl carbon, as seen in Figure 4.


	Figure 4: The structural framework of the aldehyde functional group.

	Recall (2) that the electronegative oxygen atom pulls off electron density from the aldehyde's C-H bond, giving an unusually low wavenumber C-H stretch between 2850 and 2700. For saturated aldehydes, the C=O stretch falls at 1730±10, while for aromatic aldehydes, it is found from 1710–1685. The diagnostic pattern to remember for aldehydes then is an unusually low C-H stretch, combined with a carbonyl stretch.

	Carboxylic acids are weak acids whose chemical structure is seen in Figure 5.


	Figure 5: The structural framework of the carboxylic acid functional group. Note the locations of the alpha carbon and the hydroxyl group.

	Because of the strong hydrogen bonding that takes place in carboxylic acids, the peaks from the acid group are unusually broad and easy to spot. The O-H stretch is a broad envelope of absorbance from 3500 to 2500. This is one of the broadest peaks you will ever observe in an infrared spectrum (3).

	The carbonyl stretch for saturated acids falls from 1730 to 1700, while for aromatic acids it falls from 1710 to1680. Carboxylic acids also have a C-O stretch from 1320 to 1210, and a broad O-H wag at 960 to 900. This functional group is unusual in that it has four useful group wavenumbers. However, for diagnostic purposes, the pattern easiest to remember is that the combination of a broad O-H stretch and a carbonyl group indicates a carboxylic acid.


	Figure 6: The reaction of two carboxylic acid molecules to give an acid anhydride and water.

	Acid anhydrides (4) are made by reacting two carboxylic acid molecules to obtain the structure seen in Figure 6.

	The unusual double carbonyl structure of anhydrides means there are not one but two carbonyl stretching peaks. Anhydride structures can be categorized as saturated non-cyclic, unsaturated non-cyclic, saturated cyclic, and unsaturated cyclic. The position and relative intensity of the two carbonyl stretching peaks can be used to distinguish the four types of anhydrides from each other. This information is summarized in Tables 1 and 2.

	Carboxylates (5) are made by reacting carboxylic acids with strong bases to produce the structure seen in Figure 7.


	Figure 7: The reaction of a carboxylic acid with sodium hydroxide to give a carboxylate and water.

	Note that carboxylates do not have a carbonyl group, hence no carbonyl stretching peak. Instead, they have two intense carbon-oxygen bond-and-a-half stretches that fall from 1650 to 1540 and 1450 to 1360, respectively.

	Esters have the molecular structure seen in Figure 8.


	Figure 8: The molecular structure of the ester functional group.

	Recall (7, 8) that esters follow the Rule of Three, with three intense peaks at about 1700, 1200, and 1100. These are from the C=O, C-C-O, and O-C-C stretches, respectively. Saturated and aromatic esters both follow the Rule of Three, but have different sets of peaks, any of which can be used to distinguish the two types of ester. Group wavenumbers for saturated and aromatic esters are summarized in Table 3.

	Organic carbonates can be thought of as two esters put together, as seen from the structure in Figure 9.


	Figure 9: The molecular framework of an organic carbonate.

	Carbonates are found in three classes: saturated carbonates where both alpha carbons are saturated, mixed carbonates where one alpha carbon is saturated and the other is aromatic, and aromatic carbonates where both alpha carbons are aromatic. Like esters, organic carbonates follow their own Rule of Three (8), with peaks from C=O, O-C-O, and O-C-C stretches. Their diagnostic group wavenumbers are found in Table 4.

	Note that, for many carbonyl containing functional groups, their C=O stretches fall in overlapping ranges. This is why, as I have emphasized (1), that the C=O stretch by itself should never be used to determine the presence of a functional group in a sample. Other peaks, as we have learned (1-8), need to be used to obtain a proper identification.

	1. Ketones have a carbonyl stretch around 1700 cm

. They have no other strong infrared bands and their spectra are relatively simple.

	2. The distinguishing structural feature of an aldehyde is the aldehydic hydrogen, which is isolated from the rest of the molecule by the carbonyl group. The aldehydic hydrogen gives rise to a unique, low wavenumber C-H stretch between 2850 and 2700. Aldehydes also have a C=O stretch just above 1700 cm

. The combination of a low wavenumber C-H stretch and a carbonyl stretch are strong indicators of an aldehyde.

	3. Carboxylic acids have an O-H bonded to the carbonyl carbon and, due to strong hydrogen bonding, have unusually wide bands. An O-H stretch combined with a C=O stretch are diagnostic for carboxylic acids.


	Quiz Section: Answer to the September Quiz

	4. Carboxylates are derivatives of carboxylic acids. Carboxylates have two "bond and a half" C-O linkages that give rise to two strong bands from the asymmetric and symmetric stretches at 1650 to 1540 and 1450 to 1360.

	5. Anhydrides contain two carbonyl groups, so they have two C=O stretches. The position and relative intensity of these bands can tell whether an anhydride is straight chain or cyclic, and whether it is saturated or aromatic. Their group wavenumbers are summarized in Tables I and II.

We review the group wavenumbers of the many carbonyl-containing functional groups we have examined this year and discuss how to distinguish these functional groups from each other.

November 2018

Spectroscopy November Issue PDF

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