Academic literature on the topic '030699 Physical Chemistry not elsewhere classified'

Abstract A topographical study of the electron momentum density (EMD) of some linear molecules is presented with special emphasis on the bond-directionality principle. A new approach to the bond-directionality (BD) principle has been proposed. This is based on the analysis of curvatures of critical points at p = 0 and elsewhere on the bonding axis. The linear molecules are classified into three broad categories: those which fully obey or disobey the BD principle as well as those which satisfy it only partly. The Laplacian of the EMD at p = 0 has been associated with the quality of the wavefunction via the electron density in the tail region. Also, the similarity in the critical structure of both the EMD and the spherically averaged EMD at the origin is brought out.

Forest plays a vital role in carbon sequestration and climate regulation. A crucial tool for managing forest, particularly in protected regions, is keeping track of how the land cover changes in natural places. Using geospatial approaches, such as remote sensing and geographic information system (GIS), the present study has revealed spatio-temporal changes in land use categories and forest cover in the Chandaka National Park of Odisha, India, throughout the period of 1980-2020. The Landsat, LISS III and Sentinel satellite images of the year 1980, 2000 and 2020 were utilized respectively to map five land use land cover categories i.e. deciduous broadleaf forest, crop land, mixed forest, scrub land and water bodies in this preserved area. The satellite images were classified using a Supervised Classification method using Maximum Likelihood algorithm and ground control points (GCPs) were used for the spatial statistical analyses. The overall accuracies of the classification method in land cover categories in year 1980, 2000 and 2020 were 90.45%, 92.76% and 94.68%, respectively. Elsewhere, in order to study land use land cover (LULC) change and loss in forest of the Chandaka National Park, LULC classification, per-pixel scales post classification and self-knowledge on the LULC change process were used. The LULC change detection results showed that deciduous broadleaf forest decreased from 179.01 sq. km (76.66%) in 1980 to 132.75 sq. km (56.85%) in 2020, while mixed forest cover increased by 8.17 sq. km (3.50%) in 1980 to 38.84 sq. km (16.63%) in 2020. Crop land, Scrub land and Water bodies were also increased by 3.34%, 3.27% and 0.07%, respectively. Two significant change processes in the area are the logging activities in several places for timber and the conversion of natural forests with plantation. Agriculture expansion in the forest’s periphery is linked to the dramatic decline in forest cover change. The decline in forest cover is also a result of the production of charcoal and lumber exploitation. Overall, our findings indicated that more public awareness and participatory forest management are necessary to preserve Chandaka National Park. This study highlights the use of geospatial technologies in understanding the changes in LULC in the Chandaka National Park.

Neuroendocrine tumors (NETs) throughout the body are the focus of much current interest. Most occur in the gastrointestinal tract and have shown a major increase in incidence over the past 30 years, roughly paralleling the world-wide increase in the use of proton pump inhibitor (PPI) drugs. The greatest rise has occurred in gastric carcinoids (g-NETs) arising from enterochromaffin-like (ECL) cells. These tumors are long known to occur in auto-immune chronic atrophic gastritis (CAG) and Zollinger-Ellison syndrome (ZES), with or without multiple endocrine neoplasia type-1 (MEN-1), but the incidences of these conditions do not appear to have increased over the same time period. Common to these disease states is persistent hypergastrinemia, generally accepted as causing g-NETs in CAG and ZES, and postulated as having similar tumorigenic effects in PPI users. In efforts to study the increase in their occurrence, g-NETs have been classified in a number of discussed ways into different grades that differ in their incidence and apparent pathogenesis. Based on a large amount of experimental data, tumorigenesis is mediated by gastrin’s effects on the CCK2R-receptor on ECL-cells that in turn leads to hyperplasia, dysplasia, and finally neoplasia. However, in all three conditions, the extent of response of ECL-cells to gastrin is modified by a number of genetic influences and other underlying risk factors, and by the duration of exposure to the hormonal influence. Data relating to trophic effects of hypergastrinemia due to PPI use in humans are reviewed and, in an attached Appendix A, all 11 reports of g-NETs that occurred in long-term PPI users in the absence of CAG or ZES are summarized. Mention of additional suspected cases reported elsewhere are also listed. Furthermore, the risk in humans may be affected by the presence of underlying conditions or genetic factors, including their PPI-metabolizer phenotype, with slow metabolizers likely at increased risk. Other problems in estimating the true incidence of g-NETs are discussed, relating to non-reporting of small tumors and failure of the Surveillance, Epidemiology, and End Results Program (SEER) and other databases, to capture small tumors or those not accorded a T1 rating. Overall, it appears likely that the true incidence of g-NETs may be seriously underestimated: the possibility that hypergastrinemia also affects tumorigenesis in additional gastrointestinal sites or in tumors in other organ systems is briefly examined. Overall, the risk of developing a g-NET appears greatest in patients who are more than 10 years on drug and on higher doses: those affected by chronic H. pylori gastritis and/or consequent gastric atrophy may also be at increased risk. While the overall risk of g-NETs induced by PPI therapy is undoubtedly low, it is real: this necessitates caution in using PPI therapy for long periods of time, particularly when initiated in young subjects.

Gas phase studies of the secondary structure of peptides and proteins have become increasingly popular as they offer distinct advantages of small sample usage and experiment time. The mass spectrometer is key to performing these experiments as ions can be manipulated based on their mass to charge ratio. Combining mass spectroscopy with laser spectroscopy birthed a new method for determining gas phase structures, ion spectroscopy. This document begins with an overview of secondary structure analysis using several techniques in solid, liquid, and gas phases. It then describes how ion spectroscopy can also be utilized to obtain detailed fingerprint infrared spectra of ions which are then matched with density functional theory calculations to determine the 3D structure of an ion. After describing the instrumental apparatus, four examples of the use of ion spectroscopy to determine structure are presented. The first study looked to understand the effect of increased flexibility around a proline residue in the diastereomeric pair YAD/LPGA and how a simple switch to glycine can greatly affect beta turn formation in peptides. The next three studies describe an attempt to form a single turn alpha helix in the gas phase using a highly stable tethered peptide motif. Failure to form the single turn helix in the first study led to an interesting examination of the use of computational chemistry to lead the synthesis of peptides where a specific structure is required. After observing the single turn helix attention is then diverted to expanding and controlling its handedness via stereochemistry. In all, this document will guide the reader through the methods and experiments possible with ion spectroscopy.

For decades there has been interest in understanding early prebiotic Earth, including its atmospheric chemistry. Saturn’s moon Titan is the only other body in our Solar System with an atmosphere thought to resemble that of early Earth’s, and for this reason it has garnered a lot of attention over the years. Much is now known about the smaller molecules present in that atmosphere, starting with the most abundant, N₂ and CH₄, and going up to slightly larger molecules such as cyanoacetylene and benzene. As the molecules get larger, however, so does the gap in knowledge, especially as it pertains to nitriles. This dissertation aims to add to the story of Titan’s nitriles by first characterizing a molecule thought to be the photochemical product of the reaction between cyanoacetylene and benzene, 3-phenyl-2-propyne-nitrile (PPN). The UV spectra of PPN proved immensely interesting due to the strong presence of in-plane and out-of-plane vibrations of b₂ and b₁ symmetry, respectively. This is possibly a result of strong vibronic coupling between several excited electronic states or Coriolis coupling between complementary b₁ and b₂ vibrational levels. The multi-layer extension of the multi-configuration time dependent Hartree (ML-MCTDH) algorithm was used to understand how the excited states and the vibrational levels might interact, and emission and absorption spectra were modeled and compared to the experimental spectra. The second group of molecules studied included the ortho-, meta-, and para-methyl PPN. Strong methyl rotor activity is seen in the m-methyl PPN, with some activity in the p-methyl PPN. The methyl rotor activity in the m-methyl PPN is similar to other meta-substituted toluenes, and allows us to describe the methyl rotor barrier height in both ground and excited electronic state. Additionally, in all three methylated PPNs we see evidence for strong vibronic coupling in the abundance of out-of-plane vibrations, as had been seen in PPN.

The function of many biological processes depends on the structure and composition of the biomolecules involved. Both spectroscopy and mass spectrometry provide complimentary information regarding the three-dimensional conformation and the composition, respectively, as well as many other things. Here, double resonance conformer specific spectroscopy coupled with the latest ab inito computational methods is used to make structural assignments at the atomic resolution as well obtain information regarding propensities of intramolecular interactions. Additionally, rapid cooling in conjunction with IR excitation to modulate and measure the relative populations of conformers present in the expansion. Two different designer peptide systems are studied, including an achiral acylated 𝛼-aminoisobutryic acid dipeptide (Ac-AIB2-R) with various C-terminal protecting groups (R=NHBn, NHBnF, 𝛼-methylbenzylamine) and an acylated 𝛾4-phenylalanine (Ac-𝛾4Phe-NHMe) with the a methyl amine C-terminal protecting group. Mass spectrometry is used to determine the kinetics of gas-phase covalent tagging reactions used to enhance the sequence coverage. The covalent modification reactions utilize click chemistry between NHS or HOBt substituted sulfobenzoic acid tags with nucleophiles present on the residues of the amino acids composing the backbone. Effective temperatures are approximated using the Tolmachev model, which relates the statistical average internal energy of the molecule to a temperature.

Chemical science spans multiple scales, from a single proton to the collection of proteins that make up a proteome. Throughout my graduate research career, I have developed statistical and machine learning models to better understand chemistry at these different scales, including predicting molecular properties of molecules in analytical and synthetic chemistry to integrating experiments with chemo-proteomic based machine models for drug design. Starting with the proteome, I will discuss repurposing compounds for mental health indications and visualizing the relationships between these disorders. Moving to the cellular level, I will introduce the use of the negative binomial distribution to find biomarkers collected using MS/MS and machine learning models (ML) used to select potent, non-toxic, small molecules for the treatment of castration--resistant prostate cancer (CRPC). For the protein scale, I will introduce CANDOCK, a docking method to rapidly and accurately dock small molecules, an algorithm which was used to create the ML model for CRPC. Next, I will showcase a deep learning model to determine small-molecule functional groups using FTIR and MS spectra. This will be followed by a similar approach used to identify if a small molecule will undergo a diagnostic reaction using mass spectrometry using a chemically interpretable graph-based machine learning method. Finally, I will examine chemistry at the proton level and how quantum mechanics combined with machine learning can be used to understand chemical reactions. I believe that chemical machine learning models have the potential to accelerate several aspects of drug discovery including discovery, process, and analytical chemistry.

The work presented here employs cryogenic ion spectroscopy for the study of protein structure, kinetics, and dynamics. The main technique used is IR-UV double resonance spectroscopy. Here peptide ions are generated through nano electrospray ionization, guided into a mass spectrometer, mass selected, and then guided into a cryogenically held octupole ion trap. Ions are subsequently cooled to their vibrational ground state through collisions with 5 K helium allowing for high resolution IR and UV spectra to be recorded. The IR spectra are highly sensitive to an ion’s conformation, and the well resolved UV spectra provides a means generate conformer specific IR spectra. With the use quantum mechanical calculations, it is possible to calculate the vibrational spectra of candidate structures for comparison with experimental spectra. Strong correlations between theory and experiment allow for unambiguous structural assignments to be made.

Structural studies are performed on β-turn motifs and well as salt-bridge geometries. Beta-turns are a commonly occurring secondary structure in peptides and proteins. It is possible to artificially encourage the formation of this secondary structural element through the incorporation of the D-proline (^DP) stereoisomer followed by a gly or ala residue. Interestingly, the L-proline (^LP) stereoisomer is seen to discourage the formation of beta turn structure. Here were probe the inherent conformational preferences of the diastereomeric peptide sequences YA^LPAA and YA^DPAA. The findings agree with solution phase studies, the ^DP sequence is observed to adopt a beta turn however, the ^LP sequence is found to undergo a sterically driven trans à cis isomerization about the proline amide bond. We find the energetics associated with this unfavorable interaction and show the ability to reverse it by proper substitution of Ala₂ for a Gly.

The studies directed towards gas phase salt bridges have been limited to single amino acids or dipeptides. Generally, these species are ionized using a metal ion or adducted with water or excess electrons in order to stabilize a zwitterionic motif. Here we take the first look at a salt bridge motif incorporated into polypeptide in order to understand how the solvation from the secondary structure can aid in stabilizing these motifs in non-polar environments. We find a unique salt bridge motif in the YGRAR sequence in which the tyrosine OH acts as a neutral bridge to form a network between the C-terminal arginine and the ion pair formed between the central arginine and C-terminal carboxylate group. This binding motif has not been discussed in literature and appears as an important structural element in non-polar environments as all salt bridge character is lost upon substituting Tyr for Phe. We are the process of mining the PDB for these types of interactions.

To better understand how cryo-cooling impacts the resulting population distribution at 10 K we measured the distribution among the two major conformation of the YGPAA ion. This was carried out using population transfer spectroscopy. In this method conformational isomerization is induced vis single conformer infrared excitation. The change in population can be related to the final population distribution at 10 K. With this number, we were able to develop a cooling model to simulate the change in the distribution as a function of cooling. The cooling rates, were experimental established, and the isomerization rates and starting population were theoretically derived through RRKM and thermodynamic calculations. With these parameters and cooling model, we found that the room temperature population distribution is largely preserved. When isomerization events involve breaking a hydrogen bond, they become too slow to complete with the cooling time scale of the experiment, effectively freezing in the room temperature structures. These are important physical parameters to characterize when performing structural studies at 10 K.

Finally, we demonstrate a 2-Color IRMPD technique that is able to generate linear spectra at varied temperatures. This is in sharp contrast to traditional IRMPD which results in non-linear and skewed spectra. The importance of generating linear spectra when making structural assignments is highlight by comparing the performance between both techniques. Furthermore, with this technique we show the ability to record the spectra of ion prepared with high internal energies. This provides spectroscopic snapshots of the unfolding events leading to dissociation. Overall, the versatility of this technique to record ground state spectra comparable to IR-UV DR, to record linear spectra at room temperature, and to probe dynamics proves this technique to be useful in the field of ion spectroscopy.

Raman multivariate curve resolution (Raman-MCR) spectroscopy is used to study water-mediated interactions by decomposing Raman spectra of aqueous solutions into bulk water and solute-correlated (SC) spectral components. The SC spectra are minimum-area difference spectra that reveal solute-induced perturbations of water structure, including changes in water hydrogen-bonding strength, tetrahedral structure, and formation of dangling (non-hydrogen-bonded) OH defects in a solute's hydration shell. Additionally, Raman-active intramolecular vibrational modes of the solute may be used to uncover complementary information regarding solute--solute interactions. Herein, Raman-MCR is applied to address fundamental questions related to: (1) confined cavity water and its connection to host-guest binding, (2) hydrophobic hydration of fluorinated solutes, (3) specific ion effects on nonionic micelle formation, and (4) ion pairing in aqueous solutions.

The chemical complexity of the interstellar medium and combustion environments pose a challenge to the scientific community seeking to provide a molecular understanding of their combustion. More refined spectroscopic tools and methodologies must be developed to selectively detect and characterize the widening array of fuel and interstellar species. The direct relationship between molecular structure and rotational frequencies makes rotational spectroscopy highly structural specific; therefore, it offers a powerful means of characterizing polar molecules. However, rotational spectra usually contain transitions from multiple components with multiple conformations as well as other dynamical properties interleaved with one another, making the assignment of the spectra very challenging. This thesis describes experimental work using broadband microwave spectroscopy and vacuum ultraviolet time-of-flight mass spectrometry to address a number of challenging problems in the spectroscopy of gas complex mixtures.

This dissertation reports a study of the dissolution mechanism which governs the leaching of Cu from chalcopyrite (CuFeS2) in acidic media at atmospheric pressure and examines the differences between chemical (abiotic), leaching and bioleaching. An array of solution, solid surface and bulk speciation studies were used to make a comprehensive study of the CuFeS2 leaching process(es).
Thesis (PhD)--University of South Australia, 2008.

Open questions remain on the influence of various conditions and ion behavior on the hydration-shell of oily molecules. My research uses Raman spectroscopy and Raman multivariate curve resolution to study the hydration-shell of oily molecules as tools to help answer some of these open questions.

More specifically, I present results on the effect of molecular crowding on the structure of water around various oily molecules, and report the effect of molecular crowding on hydrophobic crossover. These results are important, as crowding has the potential to influence several fields, such as biology and environmental sciences. This work shows that increasing molecular concentration results in oil-oil crowding, decreases the tetrahedrality of the water structure around the oily molecules, and subsequently, the crossover temperature.

In addition to studying the hydration-shell under crowded conditions, I also present work on ion affiliation for the hydration-shell of an oily molecule. Ion affiliation for oil/water interfaces has been an ongoing topic of research since the Hoffmeister experiments because of their effect on biological processes. This study focuses on hydroxide and its affiliation for tert-butyl alcohol in comparison to other electrolytes. These results show iodide is less repelled by the oil/water interface in comparison to hydroxide.

Finally, I present findings on the influence of hydrogen peroxide in comparison to other small molecules on the water structure of an oily molecule. Hydrogen peroxide has been shown to reach supercooled temperatures, which may be useful in future studies of liquid phase transitions or studies on solute behavior at supercooled conditions. It is found that hydrogen peroxide does not significantly influence the water structure around tert-butyl alcohol, while other small molecules display significant water structure changes.

All these projects aim to contribute results to heated debates, as well as share information for future experiments.