Chemistry Commons^™

Software For The Frontiers Of Quantum Chemistry: An Overview Of Developments In The Q-Chem 5 Package, Evgeny Epifanovsky, Andrew T.B. Gilbert, Xintian Feng, Joonho Lee, Yuezhi Mao, Narbe Mardirossian, Pavel Pokhilko, Alec F. White, Marc P. Coons, Adiran L. Dempwolff, Zhengting Gan, Diptarka Hait, Paul R. Horn, Leif D. Jacobson, Ilya Kaliman, Jorg Kussmann, Adrian W. Lange, Ka Un Lao, Daniel S. Levine, Jie Liu, Simon C. Mckenzie, Adrian F. Morrison, Kaushik D. Nanda, Felix Plasser, Dirk R. Rehn, Marta L. Vidal, Zhi-Qiang You, Ying Zhu, Bushra Alam, Benjamin J. Albrecht, Abdulrahman Aldossary

Chemistry and Biochemistry Faculty Research

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange–correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear–electronic orbital method, and …

Automated Parsing Of Flexible Molecular Systems Using Principal Component Analysis And K-Means Clustering Techniques, Matthew J. Nwerem

Computational and Data Sciences (MS) Theses

Computational investigation of molecular structures and reactions of biological and pharmaceutical interests remains a grand scientific challenge due to the size and conformational flexibility of these systems. The work requires parsing and analyzing thousands of conformations in each molecular state for meaningful chemical information and subjecting the ensemble to costly quantum chemical calculations. The current status quo typically involves a manual process where the investigator must look at each conformation, separating each into structural families. This process is time-intensive and tedious, making this process infeasible in some cases, and limiting the ability of theoreticians to study these systems. However, the …

Identification Of Chemical Structures And Substructures Via Deep Q-Learning And Supervised Learning Of Ftir Spectra, Joshua D. Ellis

Graduate Theses/Dissertations

Fourier-transform infrared (FTIR) spectra of organic compounds can be used to compare and identify compounds. A mid-FTIR spectrum gives absorbance values of a compound over the 400-4000 cm^-1 range. Spectral matching is the process of comparing the spectral signature of two or more compounds and returning a value for the similarity of the compounds based on how closely their spectra match. This process is commonly used to identify an unknown compound by searching for its spectrum’s closes match in a database of known spectra. A major limitation of this process is that it can only be used to identify …

Awegnn: Auto-Parametrized Weighted Element-Specific Graph Neural Networks For Molecules., Timothy Szocinski, Duc Duy Nguyen, Guo-Wei Wei

Mathematics Faculty Publications

While automated feature extraction has had tremendous success in many deep learning algorithms for image analysis and natural language processing, it does not work well for data involving complex internal structures, such as molecules. Data representations via advanced mathematics, including algebraic topology, differential geometry, and graph theory, have demonstrated superiority in a variety of biomolecular applications, however, their performance is often dependent on manual parametrization. This work introduces the auto-parametrized weighted element-specific graph neural network, dubbed AweGNN, to overcome the obstacle of this tedious parametrization process while also being a suitable technique for automated feature extraction on these internally complex …

Characterizing The Vibrational Spectra Of Hydrogen Bonded Systems With Molecular Dynamics Simulations And Quantum Chemical Methods, Dalton Boutwell

Master of Science in Chemical Sciences Theses

We apply and assess the utility of DMD for the purpose of investigating complex spectral features in N₂H⁺···OC, N₂D⁺···OC, C₂O₄H^-, C₂O₄D^- and (HCOOH)₂. The proton transfer as a vibrational motion consists of diffuse qualities that can be accounted for with classical and quantum chemical analyses. Classical approaches yield a wealth of information about vibrational spectra at a reduced cost, as in the case of previously investigated N₄H⁺. The isoelectronic N₂H⁺···OC has …

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

Game-Based Learning In Science: Can Video Games Simplify Organic Chemistry?, Rachel Israel

Senior Honors Theses

Organic chemistry has been taught in the same way for decades, and students still have difficulty understanding and comprehending the subject material. Perhaps it is time to change the methods by which this subject is taught. Video games have been successfully used in education to create learning environments that increase student motivation and engagement as well as challenge students and promote collaboration. It is difficult for students to maintain a growth mindset in organic chemistry within the classroom. However across different genres, video games create a unique environment where an individual is encouraged to try again when they fail. This …

Data-Driven Approaches To Complex Materials: Applications To Amorphous Solids, Dil Kumar Limbu

Dissertations

While conventional approaches to materials modeling made significant contributions and advanced our understanding of materials properties in the past decades, these approaches often cannot be applied to disordered materials (e.g., glasses) for which accurate total-energy functionals or forces are either not available or it is infeasible to employ due to computational complexities associated with modeling disordered solids in the absence of translational symmetry. In this dissertation, a number of information-driven probabilistic methods were developed for the structural determination of a range of materials including disordered solids to transition metal clusters. The ground-state structures of transition-metal clusters of iron, nickel, and …

Bibliometric Analysis Of Named Entity Recognition For Chemoinformatics And Biomedical Information Extraction Of Ovarian Cancer, Vijayshri Khedkar, Charlotte Fernandes, Devshi Desai, Mansi R, Gurunath Chavan Dr, Sonali Tidke Dr., M. Karthikeyan Dr.

Library Philosophy and Practice (e-journal)

With the massive amount of data that has been generated in the form of unstructured text documents, Biomedical Named Entity Recognition (BioNER) is becoming increasingly important in the field of biomedical research. Since currently there does not exist any automatic archiving of the obtained results, a lot of this information remains hidden in the textual details and is not easily accessible for further analysis. Hence, text mining methods and natural language processing techniques are used for the extraction of information from such publications.Named entity recognition, is a subtask that comes under information extraction that focuses on finding and categorizing specific …

Mach-Zehnder Quantum Interference Rules In Hydrocarbons With Substituents, Alaa Al-Jobory, Zainelabideen Y. Mijbil

Karbala International Journal of Modern Science

We have investigated the conditions of quantum interferences in hydrocarbons with substituents using density functional theory and tight binding approximation combined with non-equilibrium Green’s function technique. The chosen model systems, namely benzene and tripyridyl–triazine molecules, have elucidated three prominent rules. The ‘first rule’ is the occurrence of inevitable, destructive quantum interference when 1,3-benzene ring incorporates single substituent at the fifth site. The ‘second rule’ is the chaotic occurrence of quantum interferences due the position and/or type of the substituents. The ‘third rule’: the substituents decrease (increase) the probability of destructive (constructive) interferences

Physical-Chemical Characterization And Heavy Metals Assessment Of Waters And Sediments Of Sebou Watershed (Top Sebou, Morocco), Mohamed Kabriti, Eda Mahougnon Léonce, Chaimaa Merbouh, Bensaber Abdelfattah, Abdelmajid Achkir, Abdlhakim Aouragh, Iounes Nadia

Karbala International Journal of Modern Science

The main purpose of this study was to investigate the impact of human activities, geochemical background and seasons on pollutant pathway. Surface water, groundwater and sediments were assessed to highlight and confirm those impacts. Sixteen physico-chemical parameters were measured (T°, pH, O2, salinity, conductivity, BOD5, COD, SM, Cl-, NO2-, NO3-, NH4+, TAC, TH, SO₄²- and PO43-) and twelve metallic trace elements were analyzed (Ar, Cr, Zn, Mn, Ni, Fe, Al, Cd, Cu, Pb, K and Na). Five sampling campaigns were carried out in 18 sampling points for over one year, between July 2018 and July 2019 in the upstream part …

Molecular Structure Vibrational & Electronic Properties Of Some Isatin Derivatives, Fatma K. Fkandermili Prof, Fatma M. Aldibashi S, Hakan S. Sayiner Prof

Karbala International Journal of Modern Science

Abstract

In this study, Natural Bonding Orbitals (NBOs) were applied to isatin, 5‑fluoroisatin, 5‑chloroisatin, 5‑methylisatin and 5‑methoxyisatin using the Lee-Yang-Parr correlation functional B3LYP with 6‑311++G(2d,2p) basis set. Natural bonding analysis was performed to consider the transfer interactions of intra-molecular charge, pre-hybridization and electron density within the isatin, 5‑fluoroisatin, 5‑chloroisatin, 5‑methylisatin and 5‑methoxyisatin. In natural bonding orbital analysis, the wave functions of the electrons were explicated in sets of occupied Lewis type terms, (bonds or lone pairs) and sets of unoccupied non‑Lewis (anti‑bond and Rydberg) localized natural bonding orbitals. The electron density between these orbitals was correlated to stabilize the interaction …

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

Computational Catalyst Discovery: Active Classification Through Myopic Multiscale Sampling, Kevin Tran, Willie Neiswanger, Kirby Broderick, Eric Xing, Jeff Schneider, Zachary W. Ulissi

Machine Learning Faculty Publications

The recent boom in computational chemistry has enabled several projects aimed at discovering useful materials or catalysts. We acknowledge and address two recurring issues in the field of computational catalyst discovery. First, calculating macro-scale catalyst properties is not straightforward when using ensembles of atomic-scale calculations [e.g., density functional theory (DFT)]. We attempt to address this issue by creating a multi-scale model that estimates bulk catalyst activity using adsorption energy predictions from both DFT and machine learning models. The second issue is that many catalyst discovery efforts seek to optimize catalyst properties, but optimization is an inherently exploitative objective that is …

Information Architecture For A Chemical Modeling Knowledge Graph, Adam R. Luxon

Theses and Dissertations

Machine learning models for chemical property predictions are high dimension design challenges spanning multiple disciplines. Free and open-source software libraries have streamlined the model implementation process, but the design complexity remains. In order better navigate and understand the machine learning design space, model information needs to be organized and contextualized. In this work, instances of chemical property models and their associated parameters were stored in a Neo4j property graph database. Machine learning model instances were created with permutations of dataset, learning algorithm, molecular featurization, data scaling, data splitting, hyperparameters, and hyperparameter optimization techniques. The resulting graph contains over 83,000 nodes …

The Role Of Ammonia In Atmospheric New Particle Formation And Implications For Cloud Condensation Nuclei, Arshad Arjunan Nair

Legacy Theses & Dissertations (2009 - 2024)

Atmospheric ammonia has received recent attention due to (a) its increasing trend across various regions of the globe; (b) the associated direct and indirect (through PM2.5) effects on human health, the ecosystem, and climate; and (c) recent evidence of its role in significantly enhancing atmospheric new particle formation (NPF or nucleation) rates. The mechanisms behind nucleation in the atmosphere are not fully understood, although over the last decade there have been significant developments in our understanding. This dissertation aims at improving our understanding of atmospheric ammonia in the atmosphere, its spatiotemporal variability, its role in atmospheric new particle formation, and …

Modified Firearm Discharge Residue Analysis Utilizing Advanced Analytical Techniques, Complexing Agents, And Quantum Chemical Calculations, William J. Feeney

Graduate Theses, Dissertations, and Problem Reports (ETD)

The use of gunshot residue (GSR) or firearm discharge residue (FDR) evidence faces some challenges because of instrumental and analytical limitations and the difficulties in evaluating and communicating evidentiary value. For instance, the categorization of GSR based only on elemental analysis of single, spherical particles is becoming insufficient because newer ammunition formulations produce residues with varying particle morphology and composition. Also, one common criticism about GSR practitioners is that their reports focus on the presence or absence of GSR in an item without providing an assessment of the weight of the evidence. Such reports leave the end-used with unanswered questions, …

The Application Of Machine Learning In Analyzing Organic Compounds From Nmr Spectral Data, Nicole Maia Powell

Senior Independent Study Theses

Nuclear magnetic resonance (NMR) is used in organic chemistry to identify unknown organic compounds. The data obtained from an NMR spectrometer are typically shown in the form of a spectrum, which is then analyzed by an analytical chemist. The action of analyzing a spectrum, especially one of a large and complex molecule, is a long and tedious process. In this project, Python is used to implement hierarchical clustering on NMR data obtained from an NMR spectrometer at the College of Wooster to explore its application in NMR analysis. MATLAB is used to build a decision tree from the same data, …

Predicting Material Properties: Applications Of Multi-Scale Multiphysics Numerical Modeling To Transport Problems In Biochemical Systems And Chemical Process Engineering, Tom Pace

Theses and Dissertations--Physics and Astronomy

Material properties are used in a wide variety of theoretical models of material behavior. Descriptive properties quantify the nature, structure, or composition of the material. Behavioral properties quantify the response of the material to an imposed condition. The central question of this work concerns the prediction of behavioral properties from previously determined descriptive properties through hierarchical multi-scale, multiphysics models implemented as numerical simulations. Applications covered focus on mass transport models, including sequential enzyme-catalyzed reactions in systems biology, and an industrial chemical process in a common reaction medium.

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

Eelgrass (Zostera Marina) Population Decline In Morro Bay, Ca: A Meta-Analysis Of Herbicide Application In San Luis Obispo County And Morro Bay Watershed, Tyler King Sinnott

Master's Theses

The endemic eelgrass (Zostera marina) community of Morro Bay Estuary, located on the central coast of California, has experienced an estimated decline of 95% in occupied area (reduction of 344 acres to 20 acres) from 2008 to 2017 for reasons that are not yet definitively clear. One possible driver of degradation that has yet to be investigated is the role of herbicides from agricultural fields in the watershed that feeds into the estuary. Thus, the primary research goal of this project was to better understand temporal and spatial trends of herbicide use within the context of San Luis …

Development Of Computational To Ols To Target Microrna, Luo Song

Dissertations and Theses (Open Access)

MicroRNAs (a.k.a, miRNAs) play an important role in disease development. However, few of their structures have been determined and structure-based computational methods remain challenging in accurately predicting their interactions with small molecules. To address this issue, my thesis is to develop integrated approaches to screening for novel inhibitors by targeting specific structure motifs in miRNAs. The project starts with implementing a tool to find potential miRNA targets with desired motifs. I combined both sequence information of miRNAs and known RNA structure data from Protein Data Bank (PDB) to predict the miRNA structure and identify the motif to target, then I …

Coevolution, Dynamics And Allostery Conspire In Shaping Cooperative Binding And Signal Transmission Of The Sars-Cov-2 Spike Protein With Human Angiotensin-Converting Enzyme 2, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Binding to the host receptor is a critical initial step for the coronavirus SARS-CoV-2 spike protein to enter into target cells and trigger virus transmission. A detailed dynamic and energetic view of the binding mechanisms underlying virus entry is not fully understood and the consensus around the molecular origins behind binding preferences of SARS-CoV-2 for binding with the angiotensin-converting enzyme 2 (ACE2) host receptor is yet to be established. In this work, we performed a comprehensive computational investigation in which sequence analysis and modeling of coevolutionary networks are combined with atomistic molecular simulations and comparative binding free energy analysis of …

A Fuzzy Assessment Model For Hospitals Services Quality Based On Patient Experience, Mohamed Khodyer Alkafaji, Eman Salih Al-Shamery

Karbala International Journal of Modern Science

The patient's experience is a lens for services assessment that provide from healthcare institutions because the patient is the first and the last recipient for the service. The patient's experience carries a lot of uncertainty and an ultimate decision cannot be taken from the patient about the services, but it carries the partial truth. Many artificial intelligence technologies deal with the concept of partial truth, such as genetic algorithms and neural networks, but the fuzzy logic remains pioneering to deal with uncertainty. This paper aims to develop an assessment model by using fuzzy inference that is able to assess the …

A Systematic Mapping Study On The Risk Factors Leading To Type Ii Diabetes Mellitus, Karar N. J Musafer, Fahrul Zaman Huyop, Mufeed J Ewadh, Eko Supriyanto, Mohammad Rava

Karbala International Journal of Modern Science

Diabetes is one of the most common diseases that has had devastating effects on the general population. It is also among the most popular research trends in modern medicine. Thus, due to the complexity and desirability of this particular affliction, there is a lot of demand towards understanding this disease better, so that it can pave the way towards better solutions in combating diabetes. The aim of this review is to provide a categorization of the risk factors leading to Type II Diabetes. In order to provide a justification for the type of diabetes, an explanation is provided which covers …

Chemical Composition And Antibacterial Activity Of The Essential Oil Of Myrtus Communis Leaves, Hajar El Hartiti, Amine El Mostaphi, Mariam Barrahi, Aouatif Ben Ali, Nabila Chahboun, Rajaa Amiyare, Abdelkader Zarrouk, Brahim Bourkhiss, Mohammed Ouhssine

Karbala International Journal of Modern Science

The aim of this work is to determine the yield of the essential oil of the Myrtus communis leaves, to identify its chemical composition and to evaluate its antibacterial properties. The plant is harvested from Sidi Ahmed Chrif, a region in Ouazzane, Morocco. The extraction of the essential oil was carried out by hydrodistillation in a Clevenger apparatus type. The average yield was 0.7%. The analysis of this oil by Gas Chromatography coupled with Mass Spectrum (GC/MS) allows the identification of 32 compounds. Eucalyptol was the main compound with 42.43%, followed by myrtenyl acetate (21.25%) and α-pinene (19.39%). Myrtle essential …

Hormones Of Maize Crop As Affected By Potassium Fertilization , Water Quality And Ascobin Foliar Application ., Qais Hussain Al-Samak Prof., Fatima Karim Khudair Alasadi

Karbala International Journal of Modern Science

A pot assay on the plastic container of the wire sunshade in the University of Kerbala's Agricultural Division was conducted to research the impact of potassium treatment, the salinity of irrigation water and ascobin sprinkling, just as their connections, on the some plant hormones activities (auxin, gibberellin and abscisic acid) in developing Zea mays crops in a soil with sandy texture during the farming fall period of 2017–2018. The trial was planned as a factorial one with three factors, Potassium adding are 0, 100 and 200 Kg K.ha^–1 . the irrigation water salinity are 1, 3 and 6 ds.m …

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

Computational And Pharmacological Evaluation Of Carveol For Antidiabetic Potential, Muhammad Shabir Ahmed, Arif Ullah Khan, Lina Tariq Al Kury, Fawad Ali Shah

All Works

© Copyright © 2020 Ahmed, Khan, Kury and Shah. Background: Carveol is a natural drug product present in the essential oils of orange peel, dill, and caraway seeds. The seed oil of Carum Carvi has been reported to be antioxidant, anti-inflammatory, anti-hyperlipidemic, antidiabetic, and hepatoprotective. Methods: The antidiabetic potential of carveol was investigated by employing in-vitro, in-vivo, and in-silico approaches. Moreover, alpha-amylase inhibitory assay and an alloxan-induced diabetes model were used for in-vitro and in-vivo analysis, respectively. Results: Carveol showed its maximum energy values (≥ -7 Kcal/mol) against sodium-glucose co-transporter, aldose reductase, and sucrose-isomaltase intestinal, whereas it exhibited intermediate energy …

Allosteric Regulation At The Crossroads Of New Technologies: Multiscale Modeling, Networks, And Machine Learning, Gennady M. Verkhivker, Steve Agajanian, Guang Hu, Peng Tao

Mathematics, Physics, and Computer Science Faculty Articles and Research

Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the “second secret of life.” The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of …