Chemical recycling of plastics is an important strategy to improve both the effectiveness and financial sustainability of plastics recycling. Pyrolysis of plastic to decompose polymers, followed by the refining of the pyrolysate into valuable chemicals, is advantageous but there is an incomplete understanding of the chemical mechanisms governing plastics pyrolysis. Pyrolysis of the plastic polyvinyl chloride produces a variety of chlorinated hydrocarbons, such as 2-(chloroethyl)benzene. The purpose of these experiments is to probe the pyrolysis pathways of 2-(chloroethyl)benzene via matrix-isolation FTIR. A dilute mixture of the sample in argon was subject to pyrolysis in a resistively heated SiC tubular reactor at temperatures up to 1400 K. Matrix-isolation FTIR spectroscopy was used to identify pyrolysis products. The products observed include HCl, acetylene, ethylene, propyne, isobutene, vinylacetylene, propargyl radical, styrene, and phenylacetylene. Matrix-isolation FTIR spectra were recorded for commercial samples of styrene and phenylacetylene in order to verify the assignment of these species in the spectra collected following pyrolysis of 2-(chloroethyl)benzene.

Epithelial ovarian cancer (EOC) is one of deadliest cancers among women, ranking as the 5th leading cause for cancer related deaths in women in the United States. The higher mortality can be linked to the poor ability to diagnose this type of cancer at an early, treatable stage due to the lack of sensitivity and specificity in the methods that have been clinically used. Therefore, developing new techniques that can identify individuals who are at the treatable or early stage is important to increase the survival rate. Spectroscopic aided bio-conjugation technique is one such technique that could potentially alleviate some of the problems associated with the current clinical methods. In this immunoassay method, we conducted two separate investigations into the individual affinities of an antibody and an aptamer towards the ovarian cancer biomarker CA125 aided by gold nanoparticles (AuNPs) pre-modified with a Raman marker and evaluate the sensitivity of each aptamer or antibody based assay. For this goal, we used Ni-NTA (Nickel-nitrilotriacetic acid) micro particles (magnetic beads) to sandwich and purify the CA125-antibody or aptamer complex labelled with Raman markers. Firstly, Ni-NTA magnetic beads were conjugated to CA125 through histidine (CA125 His-tag). It was then incubated with a biotinylated antibody or aptamer. Finally, the conjugate was labelled by streptavidin coated AuNPs, which are pre-modified with a Raman marker. Following the magnetic separation, the final conjugates were investigated with surface enhanced Raman spectroscopy. The Raman signatures from the label verified the purification of the CA125-antibody or CA125-aptamer complex sandwiched by magnetic beads and AuNPs.

Histopathology serves as the bedrock of cancer diagnoses and grading with a resource-intensive workflow involving biopsy, tissue processing, and manual examination. Stimulated Raman Scattering microscopy (SRSM) is an emergent method that enables direct measurement of inherent molecular composition in tissue and consequently dispensing with the need for tissue processing and staining. The optical sectioning capability of SRSM enables thick tissue imaging at various depths thereby obviating the need for thin sectioning. In this work we leverage these capabilities to develop an alternate workflow, combining SRSM and deep learning to rapidly generate archival-quality virtual hematoxylin and eosin stains from excised tissue. We demonstrate our workflow with Prostate Cancer which is the leading form of carcinoma in males. The virtual stains we generate are in excellent visual agreement with stained images and on blinded evaluation by five expert urological pathologists were found to be non-inferior from real stains for diagnosis and grading. Since SRSM imaging involves no sample processing, the native lipid composition of the tissues is retained and reveals significant differences between cancer and benign patients. Collectively, we demonstrate a noise-tolerant, clinically translatable method of SRSM-based histopathology.

Shilajit, a Rasayana herbo-mineral substance, is a popular Ayurvedic treatment throughout the world to restore the body's energetic balance and fend off diseases like Alzheimer's and cognitive disorders. In Saudi Arabia, patients with bone fractures are treated locally with Shilajit. Due to its multiple usage elemental analysis of Shilajit to determine its nutritional value and heavy metal contamination for the patients' safety is highly significant. Using three cutting-edge analytical methods (LIBS, ICP, and EDX), the elemental composition of Shilajit was determined. The two varieties of Shilajits that are most frequently used are made in Pakistan and India were gathered for comparative studies. To hinge on Shilajit's therapeutic potential, our main focus is to draw attention to nutritional excellence and heavy metal contamination. In this study, Shilajit was analyzed both qualitatively and quantitatively using Laser-Induced Breakdown Spectroscopy (LIBS). Our LIBS analysis revealed that Shilajit samples contains several elements like Ca, S, K, Mg, Al, Na, Sr, Fe, P, Si, Mn, Ba, Zn, Ni, B, Cr, Co, Pb, Cu, As, Hg, Se and Ti. Shilajits from Pakistan and India had levels of Al, Sr, Mn, Ba, Zn, Ni, B, Cr, Pb, As, and Hg toxins that were higher than the standard permissible limit while also being highly enriched in beneficial nutrients like Ca, S, and K for human body. Even though the amounts of the majority of elements were comparable between the two Shilajits, the Indian Shilajit had higher concentrations of nutrients and toxins overall, with the exception of Hg and Ti. The self-developed calibration-free laser-induced breakdown spectroscopy (CF-LIBS) method was applied for the elemental quantification, and the LIBS results are in good agreement with the concentrations revealed using the conventional ICP OES/MS method. The presence of the aforementioned elements was confirmed by EDX spectroscopy, which was also used to validate our results from LIBS and ICP OES/MS techniques. This work is vital for raising awareness among those who are suffering from overdoses of this product and thus saving many lives worldwide.

In this talk, we report room-temperature optical detection of radiocarbon dioxide (¹⁴CO₂) with better than 10 parts-per-quadrillion (10¹⁵, ppq) (¹⁴C/C) measurement accuracy with the two-color cavity ringdown (2C-CRD) technique. The current sub-10-ppq measurement accuracy of ¹⁴CO₂ is 10X better than our previous work [McCartt, A. D., & Jiang, J. (2022). ACS Sensors, 7(11), 3258-3264], which demonstrated the first-ever room temperature detection of ¹⁴CO₂ at concentrations below the natural abundance ( ∼ 1200 ppq ¹⁴C/C). This significantly enhanced measurement capability of our 2C-CRD technique, achieved with under 2 minutes of averaging, is made possible by a combination of 30X improvement in the signal-to-noise ratio in our detection system and nearly 10X reduction in the magnitude of the collisionally-induced background 2C signal. As in our previous work, cavity-enhanced pump and probe laser beams are used to excite a pair of ν₃=1-0 and ν₃=2-1 rovibrational transition of ¹⁴CO₂. With the pump radiation switched off during every other probe ringdown events, the net 2C signals from the difference between the pump-on and pump-off decay rates is immune to drifts of the CRD rates and spectral overlaps from one-photon molecular transitions. The 10-ppq level detection capability of our 2C-CRD technique has been reproducibly demonstrated with several rounds of measurements of combusted ¹⁴C standard samples (with close to contemporary ¹⁴C concentrations) and low ¹⁴C content biofuel samples (10-80 ppq ¹⁴C/C). Room temperature optical detection of ¹⁴CO₂ at our demonstrated sensitivity and accuracy is not possible with other existing one-photon detection methods, because of severe spectral overlap between the very weak ¹⁴CO₂ ν₃-band transitions ( ∼ 4/s RD rate at natural abundance) and the strong hot-band transitions of other CO₂ isotopologues ( ∼ 10000/s). In addition to its use for ultra-trace analysis, our cavity-enhanced 2C technique is well-suited for rovibrational-state-resolved measurements in chemical dynamics and high-resolution spectroscopic studies, which we will discuss at the end of the talk.

A Molecular rotational resonance (MRR) spectrometer, which operates in the 18-26GHz, has been evaluated for monitoring the oxidation process of SO₂ and O₂ in the presence of NH₄VO₃. This work is performed as a part of effort to determine the utility of rotational spectroscopy as a tool for monitoring the conversion of SO₂ to H₂SO₄. The initial MRR measurements revealed the reduction of SO₂and the presence of small polar impurities (i.e., water vapor and ammonia). The current data have been further employed to validate K-Band MRR for SO₂ removal. The MRR maintains its linearity confirming its strength to monitor the removal of SO₂ in presence of other polar impurities. Work to improve this analytical procedure is underway and will be reported in this talk.

An important yet often unappreciated aspect of the spectroscopist’s workflow is the use of key software packages for data analysis. Spectroscopists young and old alike recall their first experiences with a multitude of packages, such as Herb Pickett’s CALPGM for rovibrational spectra, Colin Western’s powerful PGOPHER graphical user interface, David Plusquellic's JB95 and its magical B+C/B-C rotational constant sliders, or Kisiel’s AABS for speedrunning assignment for large broadband microwave or millimeter wave datasets. There are, of course, many other examples of spectroscopic software, whose existences evoke a wide range of emotions, including passion, apathy, and sometimes even mortal fear. However, the 21st century has provided a difficult inflection point in the interplay between experiment and software for microwave spectroscopy. Chirped-pulse microwave spectroscopy has ushered in routine acquisition of species- and transition-dense spectroscopic data sets, and the typical workflow for such data is generally split between a series of software packages that each provide only a partial solution to efficient workflow. With the growing promise of high-throughput, library-free spectroscopic analysis using machine learning techniques, there is an increased need for performant and “black box” solutions to interpreting and evaluating spectra. Even worse, with the recent passings of Herb Pickett and Colin Western, the community is left with an issue of sustainability and transparency for continuing use and training in these legacy packages. In this talk, I propose a new, unified software package for spectroscopic prediction and assignment, the so-called “Pickett 2.0” package, which was introduced as an idea that was informally discussed between a set of concerned microwavers last year at this conference. I will outline the features that modern broadband microwave spectroscopists require from a software package for efficient analysis, as well as those required by an emergent community of chemists who use rotational techniques as merely an analytical tool. I will also present new ideas for features that are more applicable for machine learning and high-throughput applications, as well as a brief discussion about the necessity for long-term software sustainability and methodological transparency.

Chiral tag rotational spectroscopy is a general method for determining the absolute configuration and enantiomeric excess (EE) of a chiral analyte. It is a chiral derivatization method where noncovalent interactions are used to attach a small, chiral molecule to the analyte via cluster formation in a pulsed jet expansion. The addition of a new, known chiral center converts the analyte enantiomers into spectroscopically distinguishable diastereomers. The high spectral resolution in rotational spectroscopy spectrometers makes it possible to fully resolve the diastereomeric chiral tag complex spectra – a favorable situation for quantitative EE measurements. The formula used to determine the analyte EE, when the tag EE is known, is derived under the assumption that transition intensities in the homochiral and heterochiral tag complex spectra are linear in the number densities of the tag and monomer. Using a simple kinetics model, it can be shown that this assumption breaks down in the case where complex formation has reversibility. In this model, chiral recognition, which results from binding energy differences in the homochiral and heterochiral complexes, leads to different dissociation rates of the initial complexes. This kinetics model has been used to explain the enhancement of ²²Ne complexes (relative to ²⁰Ne complexes) where the binding energy difference is caused by zero-point vibrational energy differences. If the dissociation rate of the initial collision complex is on the order of the stabilization rate of the complex, then deviations from the derived EE formula are expected in chiral tag rotational spectroscopy. A study of the accuracy of EE determinations using chiral tag rotational spectroscopy in the autotag analysis of trifluoroisopropanol is presented. Quantum chemistry calculations of the binding energy in the homochiral and heterochiral dimers gives an energy difference of about 2 kJ/mol suggesting that deviations from the EE formula could be observed. However, the formula is quantitative across the full EE range. This observation suggests that collision stabilization is rapid compared to the dissociation rate of the initial collision complex for a cluster formed from strong noncovalent interactions.