The 2021 Employment and Salary Survey

Analysis of a Mixture Solution Using Silver Nanoparticles Based on SERS

An Inside Look at Data Mining and Data Fusion

Enhanced Raman and Mid-Infrared Spectroscopic Discrimination of Geographical Origin of Rice 

Combined Raman and Photoluminescence Imaging 

Jerome Workman Jr. serves on the Editorial Advisory Board of Spectroscopy and is currently with Unity Scientific LLC. He is also an adjunct professor at Liberty University and U.S. National University. He can be reached at jworkman04@gsb.columbia.edu.

Dmitry Kurouski of the Department of Biochemistry and Biophysics at Texas A&M University in College Station, Texas, is applying Raman spectroscopy to important applications in agriculture for identification and classification of various plant species, for quantification of essential plant constituents, for disease diagnosis in plants, and for Raman-based digital and precision farming. He and his colleagues are at the forefront of using the advantages of Raman based measurements for non-invasive and non-destructive analyses for important field and remote measurement applications.

You have said that “Raman spectroscopy (RS) is an emerging analytical technique that can be used to develop and deploy precision agriculture” (1). Why is precision agriculture an important concept?

Continuing population growth makes global food security a critical issue for maintaining a healthy civilization. Currently, over a billion people suffer from malnutrition due to a lack of food. This problem can be solved by expansion of agricultural territories or by development of what is being called 

. While the first approach is destructive and inefficient, the second strategy is focused on the enhancement of farming efficiency. By other means, digital farming, or precision agriculture, aims to maximize crop yield with minimal environmental impact. This can be achieved by timely detection and identification of biotic (plant diseases) and abiotic (drought, nutrient deficiency) stresses. This is very important because plant diseases caused by fungi and viruses can reduce crop yields on an average of 40%, whereas losses associated with lack of nutrients, water or hyper salinity may reach 70%. Thus, solving the problem of timely diagnostics of biotic and abiotic stresses, we aim to solve the problem of food security that our civilization is going to face in the near future.

The question is, What can Raman do to solve those problems? Our group discovered that Raman spectroscopy could be used for highly accurate, nondestructive and label-free diagnostics of fungal, viral, and bacterial diseases on a large variety of plants. Moreover, we showed that Raman spectroscopy can assist in plant breeding enabling digital selection of plants. Our experimental evidence shows that nutrient content of fruits and seeds can be probed using this non-invasive and non-destructive approach. These pieces of evidence demonstrate that this technique can be used to solve the problem of timely disease diagnostics, which currently cannot be solved by any molecular (polymerase chain reaction [PCR], enzyme-linked immunosorbent assay [ELISA]) or imaging (satellite and drone) techniques. Thus, Raman spectroscopy can transform digital farming in the United States and overseas.

You have reported that Raman spectroscopy can be used for Huanglongbing (HLB) diagnostics on both orange and grapefruit trees, as well as detection and identification of various fungal and viral diseases in plants. What has led you to pursue this research, and when did you discover that there was merit in the idea of applying Raman spectroscopy

to perform analyses where previously quantitative PCR (qPCR) had been used as the “gold standard” for pathogen diagnostics in plants?

HLB is a devastating disease that obliterates citrus trees in the United States. The disease is caused by bacteria that are vectored by psyllids. Once they appear in the plant, bacteria migrate into the phloem, thus clotting this very important transportation system of the tree. Such trees exhibit premature fruit drop, yellowness of leaves, and ultimately the death of the entire plant. Currently, all citrus plants in Florida are infected, just like the trees in three counties in the South of Texas. The disease spreads so quickly that it is highly likely that all citrus trees in Texas and California will be infected soon. Proliferation of HLB can be stopped by timely diagnostics of bacteria. However, pathogen detection is extremely challenging to do by qPCR or ELISA due to the high cost of such tests. Also, PCR and ELISA are often not sensitive enough to detect the pathogen on the early stages of disease proliferation.

Our group was privileged to collaborate with Prof. Kranthi Mandadi from Texas A&M Research and Extension Center located in Weslaco, Texas, to investigate the potential of Raman spectroscopy for timely diagnostics of HLB. Our findings exceeded our expectations. We demonstrated that this technique could be used to detect HLB on early and late stages, as well as to identify plants that exhibit nutrient deficiencies. These findings show that Raman spectroscopy is not only an excellent tool for detection and identification of bacterial diseases, but it also has a far reaching implications in diagnostics of abiotic stresses caused by nutrient deficiencies.

We also questioned whether Raman spectroscopy is more accurate that qPCR, the “gold standard” of plant disease diagnostics. To answer this question, we selected a group of plants that was monitored by both qPCR and Raman spectroscopy every 3 months. Our results showed that Raman spectroscopy was more sensitive than qPCR, as it could predict the infectious status of orange trees three months before this conclusion could be made by qPCR. It should be noted that in hot summer months, bacteria migrate from leaves into roots of trees. Thus, if leaves of such a tree are sampled for PCR in June–August, the results will be false negative. Our data conclusively show that Raman cannot be misled by the lack of bacteria in the leaves and will diagnose the tree as infected if the pathogen is located in the roots.

Using Raman spectroscopy, you have reported the development of a label-free, non-invasive and non-destructive approach for remote and field detection and identification of poison ivy (

) and for other plant constituents (2,3). You have applied a miniature Raman spectrometer for identification of this species in one second using roaming robotic mounted Raman spectroscopy

or unmanned aerial vehicle (UAV) mounted Raman spectroscopy. How successful is this application for surveying a large area for poison ivy? Is this method applicable for identifying many other plant species in a designated area?

This work showed that different plant species have unique Raman spectra that can be used for their confirmatory identification. In fact, our recent findings show that such sensitivity can be reached for different plant varieties or cultivars within a species. Thus, Raman spectroscopy can be used to scan an agricultural or forest area to identify plant species that grow there. This finding will likely transform botanical approaches in identification of species and potentially revolutionize plant taxonomy. Currently, we have designed a robot that will be able to survey a large agricultural area identifying plant species that grow in such ecosystems.

This study also broughtgreat public recognition of our work in general and of Raman-based plant identification in particular. I received numerous calls from excited people appreciating the development of a fully non-invasive and non-destructive approach that can be used for identification of poison ivy, a very dangerous plant species that is present in all U.S. states except Alaska and Hawaii. Considering current technological development that enabled miniaturization of Raman spectrometers to the size of a cell phone, our discovery can be used for inspection of nearly any territory ranging from a personal backyard to a state park.

Further investigations have led you to apply Raman spectroscopy

for nondestructive discrimination between hemp and cannabis (4). You determined whether this technique

can be used to detect cannabidiol (CBD) and cannabigerol (CBG) in hemp, and to differentiation between hemp, cannabis, and CBD-rich hemp. What have you learned from this work?

This was by far the most fascinating and crazy project that we had in our lab. At that time, neither cannabis nor hemp could be grown in Texas legally. So, we jumped on the plane and went to Denver, Colorado, where we were collecting spectra from industrial hemp, CBD-rich hemp, and cannabis.

The biggest difference between industrial hemp, CBD-rich hemp, and cannabis is the presence of cannabinoids. In hemp, tetrahydrocannabinolic acid (THCA), the psychologically active compound, is present in a very low quantity, below 0.3%. In cannabis, the percentage of THCA varies from 4 to 12% or even 15% sometimes. CBD-rich hemp has below 0.3% of THCA, but contains cannabidiol (CBD) in high quantities. CBD has unique pharmacological applications. Therefore, there is a growing interest in farming of CBD-rich hemp nation-wide. However, it is important for farmers to prove that their plants have below 0.3% of THCA or total THC.

Raman spectroscopy can detect the presence of THCA, CBD, and other cannabinoids by non-invasive spectroscopic analysis of plants. Moreover, we can measure intensities of bands that originate from those cannabinoids to predict quantities of those cannabinoids in the plant material. Altogether, this discovery opened up a possibility to use Raman to probe the cannabinoid content of plants, as well as identify different varieties of CBD-rich hemp and cannabis.

You have also investigated the application of Raman spectroscopyfor the fast and accurate identification of peanut genotypes, and for the prediction of nematode resistance and oleic-linoleic oil (O/L) ratio in peanuts (5). How accurate is this analysis and are you able to determine other constituents with high confidence using Raman spectroscopy?

This analysis is highly accurate. In addition to the O/L ratio, we were able to probe the concentration of proteins, carbohydrates, oils, fiber, esters, and unsaturated fatty acids.

Have you had to develop any specialized chemometric techniques for your various applications of Raman spectroscopy? What has been your greatest data analysis challenge in performing your research?

We typically use supervised chemometric algorithms such as partial least squares–discriminant analysis (PLS-DA). Data analysis for plants is a challenging task. Primarily because we work on live field- and greenhouse-grown plants that exhibit substantial variability associated with small differences in biology of these subjects. Therefore, we have to collect hundreds and often thousands of spectra to make a reasonable conclusion about the feasibility of Raman-based diagnostics for a certain disease. The burden of data analysis is handled by Charlie Farber, the fourth-year graduate student in my lab. So, the success of our group is to a large extend dependent upon his professionalism and persistence in data analysis.

In a more general sense, what were some of the major challenges you have encountered during your career of laboratory research? How important is sound experimental design in your work?

Launching a lab is a challenge. Launching a physics–chemistry lab with a ton of instrumentation is a challenge to the fourth power. In addition to this, a large portion of our work is in the field. Several times, together with my team, we have continued working until 2:00 AM doing measurements in a corn field, which is somewhat spooky. Nevertheless, a great team of young researchers is what has allowed us to make such dramatic progress (we now have more than 40 papers published) in only three years.

Experimental design and planning is the key for everyone who works with living (life) systems. We do very careful planning of our experiments often months ahead. After that, strong commitment and professionalism of all group members is what determines our success.

What would you consider to be the most meaningful contributions of your research work? What is most exciting to you about your work?

We see Raman spectroscopy transforming agriculture in the United States. Our work shows that Raman has high sensitivity and specificity in diagnostics of both plant diseases and nutrient deficiencies. Raman spectroscopy also provides a chemical-free diagnostics approach, which essentially reduces the cost of analysis to zero. Lastly, measurements can be done directly in the field. We expect that once our approach is fully automated, the customer will receive a text message with the type of problem and the location of this problem or danger area within their field. This precise diagnostic can be used to apply pesticides of fertilizers only to the area where they are needed, saving a large amount of money to farmers, while simultaneously minimizing pollution risks to the environment.

Since the world’s population is continuously increasing, the problem of food security will only get more important in the future. We understand that poor digitalization of current agriculture causes approximately 50% crop loss each year worldwide. This makes more than a million people suffer from all types of malnutrition. Therefore, one can envision that Raman spectroscopy will help to feed the planet in the future.

Would you share with our readers to describe your work ethic philosophy, and how you plan your daily or weekly work schedule?

On my opinion, the key component of any company is people. I am privileged to lead a great team of young enthusiasts who work very hard to make all of us succeed. I also try to gather a team of top experts to solve problems that we work on. We are professionals in spectroscopy, but we understand that this is not enough to succeed in the world of plants or agriculture. The success comes from our working together with professionals in plant pathology, plant breeding, and plant biology. We also interact closely with industrial partners. Such collaborations make our work sound and interesting not only to the spectroscopic community, but also to a large audience of farmers and biologists.

What words of wisdom do you have for any young people interested in a scientific research career?

Don’t be afraid to explore uncharted territories. Three years ago, no one would believe that there is any practicality of Raman in agriculture. We were the first who stuck the flagpole in the ground. Today, our experimental findings show that Raman can be used to enable digital farming. Its use in the field will reduce the cost of farming and help feed the world.

One of the best markers of usefulness of any academic research is the interest from companies. Currently, our group works with several companies expanding applicability of our fundamental discoveries. We are positive that industrial interest in our work will only increase in the future.

(1) Sanchez, L., Pant, S., Mandadi, K., Kurouski, D. (2020) Raman Spectroscopy vs Quantitative Polymerase Chain Reaction In Early Stage Huanglongbing Diagnostics. 

(2) Farber, C., Sanchez, L., Kurouski, D. (2020) Confirmatory Non-Invasive and Non-Destructive Identification of Poison Ivy Using A Hand-Held Raman Spectrometer. 

(3) Sanchez, L., Ermolenkov, A., Tang, X.-T., Tamborindeguy, C., Kurouski, D. (2020) Non-Invasive Diagnostics of Liberibacter Disease on Tomatoes Using a Hand-held Raman Spectrometer. 

(4) Sanchez, L., Baltensperger, D. and Kurouski, D. (2020) Raman-Based Differentiation of Hemp, Canabdiol-Rich Hemp and Cannabis. 

(5) Farber, C., Sanchez, L., Rizevsky, S., Ermolenkov, A., McCutchen, B., Cason, J., Simpson, C., Burow, M., Kurouski, D. (2020) Raman Spectroscopy Enables Non-Invasive Identification of Peanut Genotypes and Value-Added Traits. 

 earned his M. S. in Biochemistry from Belarusian State University, Belarus and Ph.D. (Distinguished Dissertation) in Analytical Chemistry from SUNY Albany, NY, USA. After a Postdoc in the laboratory of Professor Richard P. Van Duyne at Northwestern University, Dr. Kurouski joined Boehringer-Ingelheim Pharmaceuticals, where he worked as Senior Research Scientist. In 2017, Dr. Kurouski joined the Biochemistry and Biophysics Department of Texas A&M University as an Assistant Professor. His research interests are focused on nanoscale characterization of biological and photocatalytic systems using tip enhanced Raman spectroscopy (TERS), and atomic force microscope infrared-spectroscopy (AFM-IR).

Articles

Dmitry Kurouski of the Department of Biochemistry and Biophysics at Texas A&M University in College Station, Texas, is applying Raman spectroscopy to important applications in agriculture for identification and classification of various plant species, for quantification of essential plant constituents, for disease diagnosis in plants, and for Raman-based digital and precision farming. He and his colleagues are at the forefront of using the advantages of Raman based measurements for non-invasive and non-destructive analyses for important field and remote measurement applications.  

Spectroscopy for Analysis of Botanicals: Raman-Based Agriculture and Detection of Important Chemical Constituents in Plant Materials

R.C. McDowall is the principle of McDowall Consulting and director of R.D. McDowall Limited, and "Questions of Quality" column editor for LCGC Europe, Spectroscopy's sister magazine.

“SneakerNet,” or the manual transfer of data using a disk or USB stick from one computer system to another, should be long dead, but this noncompliant transfer process still survives. In this edition of “Focus on Quality,” we discuss why SneakerNet should be consigned to the graveyard of technology.

Walk through any laboratory and you’ll see a variety of spectrometers with their own data systems to control the instrument, to acquire and process data, and then report the results. Look a little harder and you’ll see that most (if not all) of these systems are stand-alone, unconnected to a IT network, and their output is paper. A few may be interfaced to a laboratory information management system (LIMS) for data transfer, but these are in the minority. Instead of manually typing results into a LIMS or another computerized system from the paper printouts, the more enlightened are using “SneakerNet” to transfer data from one system to another.

was coined to describe the practice of a person (presumably wearing a mandatory pair of sneakers) transferring data on a floppy disk from one computer system to another instead of transferring data electronically by interfacing the two systems together, or manually entering data into the other computer system. Originally, the process involved 5.25-inch disks (if you are old and can remember that far back), and then matured to use higher capacity 3.25-inch disks (your memory may still be a bit hazy). You would think that, in the third decade of the 21st century, this method of data transfer would be consigned to the graveyard of technology. But no, alas, it has matured further to encompass even higher capacity universal serial bus (USB) devices. Unfortunately, SneakerNet is alive and kicking. The purpose of this column can be summarized by quoting that eminent spectroscopist William Shakespeare:

I come to bury SneakerNet, not to praise it, The evil that men do lives after them.

As we shall see, the evil of using USB devices for transferring regulated good clinical, laboratory, and manufacturing practices (GxP) data are not held in the best regard by either regulatory authorities, company IT departments, cybersecurity guidance, or me. Also, we will consider what is the impact of using a USB stick to transfer regulated GxP data; do you need to archive the USB stick used to transfer the data? (Note to self: Consider buying shares in companies making USB sticks)

USB devices can be split into two main areas: external hard drives and USB sticks or thumb drives. We will only consider the use of USB sticks or thumb drives for transferring data by SneakerNet, and exclude the use of USB external drives for automatic data backup from this discussion.

Look at the top workflow of Figure 1; a SneakerNet data transfer by USB seems very innocuous and simple. Just think about it—plug a USB device into the instrument data system, drag and drop the required data file to the stick via Windows Explorer, remove the device, then wander over to a LIMS workstation, plug in the USB stick, and drag and drop the data to a LIMS directory for upload into the database. Easy peasy! Cheap, quick, none of that painful validation stuff, and you can even use your own stick with your latest holiday photos and malware to show colleagues.

FIGURE 1: SneakerNet and interfaced transfer mechanisms between an instrument data system and a LIMS.

What’s the problem with this approach? First, let’s see what the regulators say about this.

We’ll start our discussion with two companies that have earned the highest form of praise from the US Food and Drug Administration (FDA) by way of a warning letter. The first is Zhejiang Hisun Pharmaceutical Co., Ltd that had a warning letter in 2015:

We note that some records we requested during the inspection were not provided in a timely manner.

As we shall see, this is an understatement.

During the inspection, an analyst removed a USB thumb drive from a computer controlling an HPLC (high-performance liquid chromatography instrument). When asked to provide the drive, the analyst instead exited the room with the thumb drive. After approximately 15 minutes, management provided our investigator with what they asserted was the USB thumb drive in question. It is impossible to know whether management provided the same USB thumb drive that the analyst had removed (1).

This was followed by a warning that the company was delaying and limiting the inspection (2). Using the USB thumb drive was bad, but the analyst doing a runner with it was unconscionable.

Our second example, BBT Biotech, did not use a USB drive but a CD, however, it is not the medium but the means of data transfer that is important. Citation 4 is a “failure to exercise sufficient controls over computerized systems.....to provide adequate controls to prevent omission of data.”

..... Our investigator also noted that your firm copied raw data to a CD <redacted>, and then deleted the data from the <redacted> system to free space on the hard drive. Files copied to the CD were selected manually; the selection process was not supervised. Without audit trail capabilities or supervised file selection, there was no assurance that all raw data files were copied to the CD before they were permanently deleted from the system (3).

It seems that the FDA are not happy with USB sticks and manual transfer of data without checks. Let’s consider what advice is offered by data integrity regulatory guidance.

The draft Pharmaceutical Inspection Cooperation Scheme (PIC/S) data integrity guidance (4) has in Section 9.3 a specific section on restricting the use of USB devices:

For reasons of system security, USB ports should be default disabled on computer clients and servers hosting GxP critical data. If necessary, ports should only be opened for approved purposes and all USB devices should be properly scanned before use. The use of private USB devices (flash drives, cameras, smartphones, keyboards, etc.) on company computer clients and servers hosting GxP data, or the use of company USB devices on private computers, should not be allowed.

Rationale: This is especially important for Windows environments where system vulnerabilities are known that allow USB devices to trick the computer, by pretending to be another external device, e.g. keyboard, and can contain and start executable code.

Summarizing and interpreting this section:

Disable USB ports on computers and servers by default

USB devices must be only used for approved purposes

Only use company supplied and approved USB devices

Don’t use company USB devices on private computers

Private USB devices are not permitted under any circumstances

Before use the device must be scanned, typically on a separate isolated computer to prevent infection

What Are the Problems with USB Data Transfer?

What the warning letter citations and regulatory guidance cover is relatively high-level but we need to go into more detail to see the real problems. We’ll start with the transfer process that was mentioned in the BBT BioTech warning letter using manual transfer (3), then slide further down the SneakerNet slippery slope.

 This is a manual process that can be selective either intentionally or by mistake. If a transfer to a USB drive is to be used, as a minimum any transfer to and from the stick should be automatic and validated.

 This is where there could be serious issues as in many cases the file transferred is a comma separated value (CSV) or spreadsheet file format. The file is usually unprotected, with no audit trail to monitor if there have been any changes. The issues with spreadsheets have been discussed recently (5,6), but an unprotected text or CSV file is a critical data integrity vulnerability. Although files can be protected by a checksum or encryption, it adds complexity to a process that should not even be considered.

 Where does the file reside after transfer to the receiving computer? Is it in a directory that has restricted access or open to anybody? How long is the file left before it is imported into the LIMS or the second system.

 What looked to be a simple transfer now is a can of worms when the lucky individual who is the second person reviewer comes on the scene. As the process is not validated, they need to check the data in the instrument data system, the file transferred and the data in the LIMS as a minimum. This will slow the overall business process.

What started as a simple and ideal solution for data transfer at the start of this column, SneakerNet now is turning into a regulatory nightmare, but the nightmare is not over yet.

Users and analytical instrument suppliers who like USB devices won’t like this section at all. Here we discuss the IT and cybersecurity perspectives on using USB sticks, regardless if you are a regulated laboratory or not. Rather than quote verbatim all different requirements, this section summarizes the cybersecurity from the US Cybersecurity and Infrastructure Security Agency (7), and an unnamed major pharmaceutical company’s requirements for (not) using USB sticks. The rationale for this list is that hackers can use USB drives to infect other computers with malware that can detect when the USB drive is plugged into a computer. The malware then downloads malicious code onto the drive. When the USB drive is plugged into another computer, the malware infects that computer (7). The advice is: 

Use of USB devices should be the last resort

Limit USB devices to approved and documented business needs (justification or as part of the user requirements).

Do not allow any writing to USB devices if this is not justified and authorized by management (the process/ data owner).

Configure active devices (workstations and servers) not to auto-run content from USB drives.

Monitor the network to detect external device use.

If allowed, ensure that there is an automatic anti-virus scan of the USB drive when connected.

If USB sticks are permitted, any data written to them must be encrypted.

Never, never, ever use an unknown USB device. Indeed, some guidance suggests only allowing the use of specific USB device identified to an individual serial number (providing this can be enforced by network software).

Many of these points are like those abstracted from the PIC/S guidance earlier. The requirements for USB devices is in addition to keeping all software current and patching as soon as practicable to avoid security breaches that malware can take advantage of.

User’s and Supplier’s Responsibilities

What is the root cause of the problem? In my view, it is in part the design of analytical instruments and the data systems that are designed to work in standalone mode with little or no consideration for networking. To protect the electronic records generated, there must be an option for the software to store data on a secure and resilient drive on a network. However, the other part of the problem are the users failing to specify better connectivity. Suppliers are market driven, and if the market does not require this, then suppliers come up with USB options for data transfer.

Therefore, it is the responsibility of both regulated users to demand better design of laboratory applications to avoid the need to use poor methods of data transfer and avoid buying solutions not offering this.

Now, we come to a question posed in the beginning of this column: Do we need to archive the USB sticks used to transfer regulated data files between systems? Here we need to consider the FDA data integrity guidance and question 12 (8): When does electronic data become a current good manufacturing practice (CGMP) record? I have copied the applicable text which is shown in italic and added my comments underneath each.

When generated to satisfy a CGMP requirement, all data become a CGMP record.

If you are working on a regulated analysis this is self-evident within the instrument. What about the file you are transferring on the USB stick for further analysis? Is this a GMP record? Of course, it is as shown in Figure 1.

You must document, or save, the data at the time of performance to create a record in compliance with CGMP requirements, including, but not limited to, §§ 211.100(b) and 211.160(a) (8).

The transfer file is a key component in the data chain from acquisition and interpretation by the instrument to further analysis and reporting. The question is can you delete the transfer file from the USB stick or must you retain it? The problem is that the transfer has not been validated and who authorizes the deletion of each GMP record?

FDA expects processes to be designed so that data required to be created and maintained cannot be modified without a record of the modification. ...... Similarly, it is not acceptable to store electronic records in a manner that allows for manipulation without creating a permanent record (8).

If the file is unprotected, how do you ensure that the data have not been modified after transfer and up to the point of import? This is the role of the second person review, and they will need to check the source and files in the originating and receiving systems to demonstrate there is no change. The extent of the checks required are shown in Figure 2, and at its simplest is a comparison of the source and transferred files but there are other potential data vulnerabilities where the file could be modified and the ideal review would be all stages from the instrument data system to the LIMS. If the file were protected, say by a checksum, has the process been defined and validated to reduce the amount of checking? Probably not. I would strongly suggest that SneakerNet is not a viable approach to data transfer under data integrity guidance and current interpretation of regulations. What should we do?

FIGURE 2: Problem with SneakerNet transfer and the extent of a second person review.

One alternative approach is to interface a standalone instrument data system to the network and have a script that automatically transfers a file to a secure directory on the LIMS server for the LIMS to scan and automatically import. In terms of data flow the direct network connection to a LIMS is better than USB SneakerNet. The script would be started by a user who would enter the file name to be transferred and the rest would be performed by the script. Naturally, this process must be defined and validated but would drastically reduce the amount of second person review required.

An ideal solution is to use a computerized system that is designed for regulatory compliance with controls to protect e-records and capture all appropriate data and metadata, including audit trail entries of data export to LIMS. The data system should be interfaced to the LIMS using an Application Programming Interface. This is programmed by a supplier and is validated by the laboratory, but is a far more secure interfacing approach that ensures data integrity as no file is created during data transfer between the applications.

We have discussed the regulatory, business and cybersecurity problems of SneakerNet data transfer typically using USB sticks in lieu of instrument interfacing. USB transfer should not be used. Alternatively, are you going to take the Clint Eastwood approach to risk management with SneakerNet: Am I feeling lucky?

I would like to thank John Waldron for helpful comments in writing this article.

(1) FDA Warning Letter: Zhejiang Hisun Pharmaceutical Co., Ltd (Warning Letter: 320-16-06) (Food and Drug Administration, Silver Spring, Maryland, 2015)

Industry Circumstances that Constitute Delaying, Denying, Limiting, or Refusing a Drug Inspection

 (Food and Drug Administration: Rockville, Maryland, 2014).

(3) FDA Warning Letter BBT Biotech Gmbh (Warning Letter 320-16-12). (Food and Drug Administration, Silver Spring, Maryland, 2016)

PIC/S PI-041-3 Good Practices for Data Management and Integrity in Regulated GMP / GDP Environments

 Draft (Pharmaceutical Inspection Convention/Pharmaceutical Inspection Cooperation Scheme, Geneva, Switzerland, 2018).

(7) Security Tip (ST08-001): Using Caution with USB Drives (2019) Available from: https://us-cert.cisa.gov/ncas/tips/ST08-001

(8) FDA Guidance for Industry Data Integrity and Compliance With Drug CGMP Questions and Answers (Food and Drug Administration, Silver Spring, Maryland, 2018)

 is the director of R.D. McDowall Limited and the editor of the “Questions of Quality” column for 

’s sister magazine. Direct correspondence to: 

“SneakerNet,” or the manual transfer of data using a disk or USB stick from one computer system to another, should be long dead, but this noncompliant transfer process still survives.

Consigning SneakerNet to the Graveyard of Technology

In the late 1990s and early 2000s, frequency combs upended metrology, providing linkages that allowed accurate measurement of differences in microwave and optical frequencies. As the technology around frequency comb generation has matured, numerous other uses have been discovered. Here, we will discuss the some of the methods of application of frequency combs to spectroscopy, and some of the recent implementations that may make practical, fieldable spectroscopic devices with frequency combs ready in the near future.

A frequency comb is a laser source with a series of evenly spaced narrow lines exhibiting phase coherence. The most common way to produce a frequency comb is with a mode-locked ultrafast laser. It was for their contributions to frequency comb development that John Hall and Theodor Hänsch earned their share of the Nobel Prize in Physics in 2005. Frequency combs can also be produced by modulation of a continuous wave laser, or four-wave mixing in a crystal.

Considering the mode-locked ultrafast laser, in the time domain, the electric field of the pulse waveform looks like a sinusoid in a Gaussian envelope, as shown in Figure 1a. The period of the sinusoid is equivalent to twice the length of the laser cavity (a round trip), divided by the group velocity. In frequency space, this looks like a series of narrow lines separated by the laser pulse repetition frequency, as in Figure 1b. Thus, the laser repetition frequency drives the resolution in many applications. The typical spectrum of a frequency comb can have hundreds (or even thousands) of lines, and can extend up to an octave in frequency space.

FIGURE 1: (a) The output of a mode-locked ultrafast laser contains components from a group of longitudinal cavity modes, collectively emitted with a time spacing of 

. These modes each add to the laser pulse. Dispersion-induced phase- and group-velocity distributions relate to the coherence of the pulse, resulting in a frequency offset 

. (b) In frequency space, this periodic wavetrain can be described as a Fourier series, with each component frequency ν

There are several excellent references that provide details about frequency comb operation in the context of spectroscopy (1,2). In practice, the comb from a mode- locked ultrafast laser is very simply parameterized by a group of comb frequencies 

 is the repetition frequency of the laser, 

 is a frequency offset related to the dispersion in the cavity or gain medium that can be tuned. In practice, the absolute spacing between comb lines is set by the laser repetition rate 

 and the fine tuning of the comb to hit specific wavelengths is accomplished by feedback and control of the laser cavity (length and dispersion) to influence the interaction between laser modes and adjust the carrier mode frequency offset 

, provides knowledge of the exact wavelength of every mode of the optical comb. Details of measurement of 

, which is non-trivial, are given in reference (1).

Generation of frequency combs is easiest in the near-infrared (NIR), where ultrafast lasers such as Ti:sapphire and fiber lasers have been instrumental to development. Up-conversion and down-conversion of these sources is the most prevalent method of accessing the visible, mid-infrared (MIR), or longwave regions of the spectrum, although other methods exist. Frequency translation of NIR sources can be done using nonlinear conversion in optical crystals or in photoconductive antennas, where frequency mixing with secondary continuous wave (CW) or pulsed sources can facilitate translation of the wavelength. Combs can be filtered using Fabry–Pérot interferometers or other methods to access particular lines or regions of the spectrum. Further details about comb technology availability in particular spectral regions is given in references (1,2), and elsewhere.

Applications of Frequency Combs to Spectroscopy

The simplest way of using a frequency comb is as a direct light source with a single detector. Line widths of gas-phase molecular transitions at atmospheric pressure are suitably narrow, for example, that a particular comb line can be matched to a particular molecular transition for absorption or excitation. In this case, ideally all other comb lines would be detuned from transitions, and a single detector can be used to monitor the result without interferences. For 2-photon excitation, the even spacing of the comb lines is a boon; all of the lines around a central frequency 1⁄2v will combine in pairs to add to the transition frequency v, and hence substantial power can be applied to pump the transition. Possibly the earliest example of this was given in some early work by Hänsch’s group at Stanford in 1978 (3).

A relatively recent example of using a frequency comb as a direct source is given by Coluccelli and associates (4). Their 2016 contribution demonstrated an all-fiber direct comb measurement. They demonstrated their frequency comb method on acetylene, C

. Instead of collecting the light on a single-element detector, they imaged the transmission measurement on a 320 x 256 indium gallium arsenide (InGaAs) camera, following collection through a multimode fiber. Each wavelength has a predetermined multimode (MM) speckle pattern; this pattern was stored for each wavelength of interest and subsequently used to calibrate the wavelength during measurement. Figure 2 illustrates measurement of multiple bands of C

FIGURE 2: A sequence of transmission spectra by a 142-mm cell filled with pure 

 at pressure of 10 mbar acquired with the MM fiber spectrometer. The sequence has been measured by setting a tunable filter (−10 dB band of 0.6 nm) at the desired central wavelength and imaging the speckle patterns at the MM fiber output onto an InGaAs camera (40-μs exposure time, 10 frames averaged). Each spectrum spans 1 nm and is sampled by ~500 comb lines.

The Frequency Comb in Combination with a Spectrometer 

For studies of condensed phases, typically less resolution is needed and multiple lines are used to interact with a broader feature in the sample. In most cases, standard dispersive spectrometers do not have the resolution to resolve individual comb lines, but this is not required. Rather, the frequency comb is used as a broadband source.

When more resolution is required, creative approaches have been used. Fabry–Pérot resonators can be used to filter for specific comb lines, such that specific transitions are targeted. One of the most innovative approaches has been using ringdown spectroscopy in conjunction with a dispersive spectrometer. Thorpe and colleagues modeled the transfer function of the many laser lines through a 1⁄4-meter spectrometer with a 25 GHz resolution (corresponding to about 60 comb lines), following absorption in a cavity ringdown cell. The time-based ringdown signal of the multiple lines at each detection frequency was deconvoluted, yielding pristine absorption spectra of Ar, C

Michelson Interferometer-Based Comb Spectroscopy

The high brightness and discrete lines in a frequency comb enhance the results in applications using a Michelson interferometer. Compared with standard setups using a broadband source, using frequency combs in the interferometer keep all of the good features of the method, but eliminate some of the drawbacks. For example:

High brightness of the laser at specific comb wavelengths decreases measurement time.

Ability to resolve individual comb lines substantially improves the overall resolution, previously dependent on the travel of the moving mirror in the interferometer. The instrumental function is no longer a significant factor in measured line shapes.

Exact wavelength referencing in the comb (possible but not always implemented) eliminates the need for reference features in the sample.

For these reasons, Fourier transform spectroscopy (FTS) with a Michelson interferometer using frequency combs has substantial potential, particularly in gas-phase infrared analysis. It benefits from a large base of knowledge and peripherals such as long-path cells.

An example of FTS with a frequency comb in the mid-infrared is given in the recent paper by Sadiek and colleagues (6). They used a mid-IR frequency comb produced by a high-power 125 MHz Yb-doped fiber laser down-converted through difference frequency generation in a Mg-doped periodically-polled lithium niobate crystal, after mixing with a Raman-shifted soliton generated from the same Yb-doped fiber laser in a highly nonlinear fiber. This is a good example of the complexity of comb generation outside of the relatively easy near-infrared region.

The authors used this source to measure a high-resolution spectrum in the C-H stretch region from 2800 to 3160 cm-1 (~ 3.3 μm) of iodomethane (

I). A series of measurements at 125 MHz were interleaved to obtain a final sample point spacing of 11 MHz, which translates to approximately 0.4 picometer resolution at a wavelength of 3.3 μm. The resulting high-resolution spectrum is shown in Figure 3.

FIGURE 3: (a) Overview of the broadband high-resolution spectrum of pure CH

I measured at 0.03 mbar in the range from 2800 to 3160 cm

. (b)-(d) The zoomed in spectra showing the dense ro-vibrational structures of the different bands. Spectra in panels (b) and (d) were measured at a pressure of 0.11 mbar to increase the absorption signal due to the lower intensity compared to the ν1 band in panel (c).

Dual-comb spectroscopy removes the requirement for a moving mirror for Fourier transform spectroscopy. Instead of generating a frequency difference by projecting a single source along both of the paths in the Michelson interferometer, with one path having a moving mirror, dual-comb spectroscopy uses two frequency combs. The reference comb is held at a particular frequency 

 + δf. The second comb is sent through the sample to be analyzed, and (as in a Michelson interferometer), both combs are directed to a single detector. Over time, the second comb sweeps through the first.

This has the same effect as a moving mirror in a traditional Michelson interferometer, but with some notable advantages. Obviously, a mechanical component is removed, potentially increasing reliability and simplicity. Second, the resolution is strictly limited only by the repetition frequency 

, which determines the spacing between the comb teeth. Difficulties include phase and frequency-locking between the lasers. In the frequency domain, imperfections in locking leads to broadening of features. However, substantial work is underway to minimize these issues for fieldable systems; even more than a decade ago laboratory researchers had achieved sub-picometer resolution for gas phase spectra in the near-infrared with high signal-to-noise (7). Dual-comb spectroscopy is probably the most promising mode for applications, as it requires no moving parts and can be accomplished with a single detector. An excellent, relatively recent, overview is given by Coddington and colleagues (8).

An approach that seems to be one of the most straightforward for eventual application relies on digital processing on a high-speed FPGA to continuously correct and average interferograms from dual-comb spectrometers. This somewhat relaxes the mode-locking requirements and improves spectral quality. Roy and associates achieved real-time processing on signals acquired at 100 MHz during one of the first demonstrations of digital correction of dual-comb spectra in 2012 (9). Their results with a combination of hydrogen cyanide and acetylene are shown in Figure 4. Digital processing capabilities have improved substantially in the intervening nine years, and multiple groups and manufacturers are working on making dual-comb spectrometers practical for laboratory and even field use.

FIGURE 4: Spectrum from a 24-hour measurement with real-time digital correction of interferograms. (a) Full spectrum on a logarithmic scale. (b) Transmittance from gas cells containing C

 and HCN. The baseline was normalized by fitting. (c) Zoom between 1527 nm and 1530.5 nm of the cell’s transmittance. Difference in the width between HCN and C

 lines is attributable to the pressure in the two cells.

Another recent set of efforts has been to use dual-comb spectroscopy to measure high-speed or transient events, such as combustion, rapid chemical reactions, or laser plasmas. The Jones group at the University of Arizona, in conjunction with researchers at the Pacific Northwest National Laboratory and privately held Opticslah, LLC, have pioneered single-shot time-resolved measurements in evolving laser-induced plasmas, and have recently shown a “burst mode” dual-comb spectroscopy method involving delay lines to create a series of time-resolved measurements in laser plasmas (10).

This article has attempted to outline for the non-specialist some of the salient features of the burgeoning work in frequency comb spectroscopy. There is a rich literature and a highly active community in physics, chemistry, and engineering working to develop methods and new applications for frequency combs in metrology.

This rapid evolution is making practical frequency comb spectroscopy closer to reality, as continued development clears technical hurdles and simplifies systems. Laboratory instruments based on fiber lasers and mid-infrared quantum cascade lasers are beginning to appear. A surge in activity around single-cavity dual-comb lasers, microresonators, quantum cascade lasers, and interband cascade lasers holds hope to deliver field-deployable and compact spectrometers in the foreseeable future. Size, weight, and power (SWAP) of demonstration systems is decreasing and in many cases is compatible with battery power. With an eye to fieldable applications, I am keenly looking forward to the next decade of development in frequency comb spectroscopy!

, 153 (2019). https://doi. org/10.1038/s42005-019-0249-y

, 146–157 (2019). https://doi.org/10.1038/s41566- 018-0347-5

(3) J.N. Eckstein, A.I. Ferguson, and T.W. Hänsch, 

, 12995 (2016) https://doi.org/10.1038/ncomms12995

, is the General Manager of the Applied Systems business at Ocean Insight, an affiliate associate professor at the University of Washington, and has started and advised numerous companies in spectroscopy and in applications of machine learning. He has approximately 40 peer-reviewed publications and 6 patents. His work in practical optical spectroscopy, such as LIBS, Raman, and TDL spectroscopy, dovetails with the coverage in this column, which reviews methods (new and old) in laser-based spectroscopy and optical sensing. Direct correspondence to: 

A frequency comb is a laser source, with evenly spaced narrow lines, potentially useful for spectroscopy applications, particularly as a source or for alignment of the wavelength axis.

A Brush with Frequency Comb Spectroscopy: A Developing Story

Plasma spray–deposited metal films are of interest for many industrial applications. Four samples of spray-deposited nickel layers on an alumina layer were examined by high resolution terahertz time-domain spectroscopy (THz-TDS). The absorbance spectra of these samples reveal that all samples exhibited absorption peaks at approximately 6 and 8 THz. These absorbance peaks are consistent with those reported for nickel-based dilute alloys (Ni > 98%). Analysis of the absorbance spectra for all samples from 1 cm-1 to 300 cm-1 reveal a systematic shift in absorbance peak frequency of the samples. Because these samples were fabricated by a spray-deposition technique, some lattice dilation occurred because of hydrogen embrittlement. The shift in absorbance peaks occurred because of the lattice dilation of the same samples. Observed absorbance peaks at 403 cm

, for samples HHT-111, HHT-129, HHT-81, respectively, are a close match for nickel oxide (NiO) phonon excitation modes. The peaks support the hypothesis of excess energy generation via nonradiative phonon excitation because of lattice vibration at elevated temperatures under a radio frequency (RF) field.

Plasma spray–deposition of metal films are of interest for many industrial applications. Here, the combined operations of particle melting, quenching, and consolidation are carried out in a single process. Brillouin Energy Corporation has developed a uniquely fabricated, hydrogen gas–based reactor, referred to as a “hydrogen hot tube” (HHT). These reactors can generate controlled heat energy on demand for potential industrially useful applications. Details of the experimental arrangement are given in the literature (1). In this case, a plasma-sprayed nickel film on a ceramic layer plays a crucial role for the reported excess energy generation.

The concept of excess energy generation continues to evolve. A report from Brillouin (1) summarizes the origin from a comparison of the time-integrated electrical power input to the time-integrated calorimetric thermal power output. When the thermal output exceeds the electrical input, the presumption is that the excess energy is generated from something other than chemical, electrical, mechanical, or morphological mechanisms. This assumption stems from many reports in the field where the integrated excess power is one or more orders of magnitude greater than what can be sourced from those mechanisms cited above. The controlled electron capture hypothesis proposes a mechanism that can explain the excess energy. The scope of this paper does not include the detail analysis of any of those possibilities and may be addressed in a future study.

The plasma spray process involves the injection of powder particles (such as metallic, ceramic, or cermet powders) into the plasma jet created by heating an inert gas in an electric arc confined within a water-cooled nozzle, as seen in Figure 1. The final properties of the resulting film may be uniquely studied by spectral analysis. Terahertz spectroscopy provides the highest sensitivity analyses of the absorbance characteristics of the material, because terahertz radiation (T-ray) is sensitive to a wide range of resonances present in a material (2,3).

FIGURE 1: (a) Main components of a plasma spray–deposition system, and (b) process flow for deposition.

Recently, we reported on the lattice dilation of plasma sprayed nickel films via terahertz imaging (4) that overcomes the Abbe diffraction limit for the generation of high-resolution images via the terahertz nanoscanning route. A camera-less terahertz imaging technique was used (4). It was found that the lattice of plasma spray–deposited nickel films was dilated because of hydrogenation during the spraying process. Furthermore, it was found that a systematic dilation also occurred under various experimental stresses. A sample of metallic nickel was also measured in an identical way and served as a calibration of the imaging process.

The lattice dilation is the root cause for hydrogen embrittlement and a nano- to micro-crack formation in metals. This is well-known for steel. The nickel lattice is dilated by virtue of the plasma-spray deposition (5). Plasma-spray deposition is a very well-controlled process and reproducible. Thus, we assume that the lattice dilation should also be controllable, as mentioned in the literature (5). Because the HHT experiments are done under an applied radio frequency (RF) field, the nickel lattice is subjected to simultaneous lattice dilation and time variation. This fits the definition of time-crystal-like nonequilibrium (5).

In this paper, we report terahertz spectroscopic analyses of HHT samples (5). Unlike the lattice imaging reported earlier (5), we describe here the terahertz spectral analysis of specific nickel layers for four HHT samples. The principle of terahertz time-domain spectroscopy is outlined below. Figure 1 depicts the main components of a plasma spray–deposition system as well as the process flow from the beginning to the final deposition. Here, a sequential spray-deposition of the layers was used, as indicated in Figure 2. Although deposition and operation take place under reducing conditions, subsequent exposure to air can lead to nickel oxide formation for the surface layer. The possibility of nickel oxide (NiO) formation was deduced from the terahertz absorbance spectra.

FIGURE 2: A planarized sketch of the HHT tube sample.

Specific details concerning electro-optic dendrimer based terahertz time-domain spectroscopy principles and applications have been described extensively (2,3). This new mechanism of terahertz generation is referred to as 

 (6). The interaction of terahertz radiation (T-ray) with molecules excite a wide range of resonances present in a given sample. These resonances may occur from molecular vibrations, rotations, translations, torsions, or conformations. As such, the T-ray photons are affected by the interaction with the molecular matrix, which is determined by a specific resonance. Therefore, quantification of such an interaction may be used for identifying the physical properties of the sample because the observed change in energy or frequency reveals important information concerning the nature of the interaction. Infrared and Raman spectroscopy may yield similar information but are unable to detect many resonance states, which may be possible using terahertz spectroscopy. Terahertz photons are uniquely sensitive to the vibrational states of the entire molecule as opposed to a specific bond or charge state. All materials may be considered as a matrix consisting of atoms and molecules. Molecular simulation, especially molecular dynamics (7), reveals that there are numerous vibrational and conformational states possible when a molecule is not at its lowest energy state. Because most materials remain at their lowest energy state under normal and steady state conditions, T-ray perturbation is expected to access and stimulate possible available states in the low frequency regions. Therefore, the transmitted or reflected T-ray beam will report and communicate unique information about a material being probed. Quantitative predictions of such information is material-specific and best determined by experimental measurements. For example, a T-ray absorbance spectrum of a specific sample will exhibit unique absorption peaks corresponding to a range of resonances present only in that material. As such, the sensitivity of T-ray spectroscopy to the detection of these subtle resonances provides an ultra-sensitive probing technique for characterizing materials, which may be expanded to other materials, such as pharmaceuticals and semiconductors.

Terahertz spectral analysis may be done in more than one way, because there are several different Fourier transform variations available. A common approach is to express the damped signal (material response) in terms of the normalized absorbance in the unit of decibels, dB_norm, where the measured absorption is normalized to 0 for a frequency channel with maximum power. Other parameters may also be computed from the same measured data via the software package included in the TNS3DI instrument used in this study. Available parameters (plots and data) include: the real and imaginary parts of the Fourier spectrum, with its magnitude defined by √Re

; and the dual plot of magnitude and phase; and amplitude, which is defined by 2(√Re

 is the total number of points, and the power spectral density is calculated from the amplitude sum squared. These options allow us a suitable parameter description to be utilized for each different need. For this study, the spectra are analyzed in terms of frequency (Hz) and wavenumber (1/cm) for the interpretation of the absorbance peaks of the present material system.

Four HHT tubular samples were obtained and designated as HHT-77, HHT-81, HHT- 129, and HHT-111. All samples were manufactured by sequentially plasma-spraying the respective layers on an alumina tube, as depicted in Figure 2. Sample HHT-77 is as the manufactured sample, with no HHT experiment being performed on it. Samples HHT-81 and HHT-129 were subjected to the HHT experiment and produced higher energy than input, whereas HHT-129 produced even higher energy than HHT- 81. Sample HHT-111 also produced some excess energy but less than both HHT-129 and HHT-81. The plasma-spray deposition of these samples occurred under reducing conditions. However, it is assumed that some oxidation might have occurred on the exposed surface after deposition, which produced NiO on the surface layer, as seen from the spectral analysis.

All samples were polished at a steep oblique angle for exposing the different constituent layers. As shown in Figure 3, the nickel layer on top of the ceramic layer is exposed by polishing at the nickel-ceramic interface. The T-ray beam was focused on the exposed nickel layer next to the ceramic layer.

FIGURE 3: Image of sample-77 (left), and sample-81 (right), after polishing and mounting both on the nanoscanner. The green circle indicates the area of interest for the low-energy nuclear reaction (LENR) effect.

All samples were mounted individually on the terahertz nanoscanning spectrometer and three-dimensional imager (TNS3DI from Applied Research & Photonics) with the help of a special fixture (Figure 3). Figure 4a shows the schematic diagram of the TNS3DI experimental setup whereas Figure 4b exhibits the mounted sample and the beam control aperture of the TNS3DI (7). The nanoscanner was manipulated by the front-end software on all three orthogonal axes to pinpoint an area that is rich in nickel but located near the nickel-ceramic interface (4). Once the correct spot was chosen, the built-in kinematic screws were adjusted for maximum reflection, thereby ensuring a vertical incidence of the T-ray beam on the sample surface (Figure 4). The time-domain terahertz spectral signal (the pump-probe interferogram) was acquired by the built-in front-end software for each sample. Details of the time-domain measurement and terahertz pump-probe technique have been described elsewhere (2,3) and are not repeated here. As indicated before, the TNS3DI uses a dendrimer dipole excitation-based continuous wave terahertz source producing >200 mW of stable power (5), and the detected (damped) signal reflected by the sample gave a measured power of ~2 mW. The detected intensity was recorded in terms of the number of T-ray photons.

FIGURE 4: (a) Experimental layout (adapted from reference [7]), and (b) T-ray beam incidence arrangement on the sample mounted on the nanoscanner.

Four interferograms were acquired for each sample, and the average interferogram was used for subsequent analysis. A special Fourier transform called the Lomb-Scargle periodogram (8) was used to compute the absorbance spectra of each sample. The Lomb-Scargle periodogram is a well-known algorithm for detecting and characterizing periodicity in unevenly sampled time-series. Some details of this algorithm and its implementation are found in the literature (8,9). Since most experimentally collected data in the time-domain are unevenly spaced in time, the Lomb-Scargle periodogram is the most effective way to compute the absorbance frequency spectrum from experimental data. The algorithm defines a second series of evenly spaced abscissa (time) values using a variable offset term in the definition of the power spectral density. This results in an algorithm that is equivalent to the least-squares fitting of sine curves (at specified frequencies) to the data (8). Further detail of the Lomb-Scargle algorithm is outside the main topic of this paper and the readers are encouraged to review the literature for more details (8).

Terahertz absorbance spectra obtained from the aforementioned Lomb-Scargle periodogram analysis are discussed in this section. Figure 5 exhibits the frequency domain absorbance spectra of all four samples corresponding to the nickel rich area over the range of 0.1 THz to ~32 THz. Many distinct absorbance peaks are visible for all samples (Figure 5). Given that the absorbance peaks are well-defined in the spectrum itself, the frequency and the wavenumber value corresponding to chosen peaks were read off the spectrum without the aid of any curve-fitting algorithm. While there are several absorbance peaks visible in Figure 5, the meanings of many of them are not clearly analyzed at this point. However, it was explained elsewhere (2) that many of these peaks are expected to be meaningful. As such, the observation of these additional peaks offers an opportunity for further theoretical and experimental investigations and justifies the emergence of this new branch of THz-TDS.

FIGURE 5: Frequency domain absorbance spectra of all four samples corresponding to the nickel rich area. This gives a broader view of the spectra over 0.1 to ~32 THz. Many distinct absorbance peaks visible for all samples. These peaks are further analyzed in Figure 6.

Figure 6 exhibits a closeup of the spectra in Figure 5, where the x-axis was truncated to 10 THz to facilitate the examination of absorbance peaks. It is seen from Figure 6 that all four samples exhibit prominent absorption peaks at or around 6 THz and around 8 THz. The observed absorbance peaks at ~6 THz and ~8 THz are consistent with the observation for nickel based dilute alloys (Ni > 98%) (10), similar to those deposited on these samples. In their work (10), the authors have calculated the real and imaginary parts of the resonance and localized modes. They reported strong resonance for nickel at ~6 THz and ~8 THz. Thus, the observation of the absorbance peaks at ~6 THz and ~8 THz of the present study is assigned to the nickel as expected (10).

FIGURE 6: A closeup of the spectra in Figure 5. The 

-axis is truncated to 10 THz to facilitate examination of absorbance peaks. A few peaks are identified for all four samples by the respective characteristic frequencies.

Plasma spray–deposited metal films are used in many industrial applications. This study shows how high resolution terahertz time-domain spectroscopy (THz-TDS) can be used to analyze and characterize such films.

Featured Content

The 2021 Employment and Salary Survey

Analysis of a Mixture Solution Using Silver Nanoparticles Based on SERS

Enhanced Raman and Mid-Infrared Spectroscopic Discrimination of Geographical Origin of Rice

Combined Raman and Photoluminescence Imaging