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Articles 331 - 360 of 3436

Full-Text Articles in Physical Sciences and Mathematics

A Survey Of Graph Neural Networks On Synthetic Data, Brigham Stone Carson Apr 2023

A Survey Of Graph Neural Networks On Synthetic Data, Brigham Stone Carson

Theses and Dissertations

We relate properties of attributed random graph models to the performance of GNN architectures. We identify regimes where GNNs outperform feedforward neural networks and non-attributed graph clustering methods. We compare GNN performance on our synthetic benchmark to performance on popular real-world datasets. We analyze the theoretical foundations for weak recovery in GNNs for popular one- and two-layer architectures. We obtain an explicit formula for the performance of a 1-layer GNN, and we obtain useful insights on how to proceed in the 2-layer case. Finally, we improve the bound for a notable result on the GNN size generalization problem by 1.

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Skew Relative Hadamard Difference Set Groups, Andrew Haviland Apr 2023

Skew Relative Hadamard Difference Set Groups, Andrew Haviland

Theses and Dissertations

We study finite groups $G$ having a nontrivial subgroup $H$ and $D \subset G \setminus H$ such that (i) the multiset $\{ xy^{-1}:x,y \in D\}$ has every element that is not in $H$ occur the same number of times (such a $D$ is called a {\it relative difference set}); (ii) $G=D\cup D^{(-1)} \cup H$; (iii) $D \cap D^{(-1)} =\emptyset$. We show that $|H|=2$, that $H$ has to be normal, and that $G$ is a group with a single involution. We also show that $G$ cannot be abelian. We give examples of such groups, including certain dicyclic groups, by using results …

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Designing Resilient Agents Using Grammatical Evolution, Behavior Trees, And Finite Linear Temporal Logic, Aadesh Neupane Apr 2023

Designing Resilient Agents Using Grammatical Evolution, Behavior Trees, And Finite Linear Temporal Logic, Aadesh Neupane

Theses and Dissertations

Resilience is essential for long-term autonomous agents. Swarm behaviors seen in bees, ants, birds, fish, and others are interesting because they resiliently perform complex coordinated tasks like foraging, nest-selection, flocking and escaping predators without centralized control or coordination. Conventionally, mimicking swarm behaviors with robots requires researchers to study actual behaviors, derive mathematical models, and implement these models as state machines. Since the conventional approach is time-consuming and cumbersome, this dissertation uses a grammatical evolution algorithm with Behavior Trees (BTs) to evolve behaviors that are resilient to different perturbations for foraging and nest maintenance tasks. The modular, reactive, and readable properties …

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A Language-Model-Based Chatbot That Considers The User's Personality Profile And Emotions To Support Caregivers Of People With Dementia, Yeganeh Nasiri Apr 2023

A Language-Model-Based Chatbot That Considers The User's Personality Profile And Emotions To Support Caregivers Of People With Dementia, Yeganeh Nasiri

Theses and Dissertations

Chatbots are programs that mimic human conversation using Artificial Intelligence (AI). Recent advances in natural language pro- cessing pave the way for chatbots to generate more human-like responses. Therefore, chatbots are finding more complex tasks to perform, such as emotional support which requires both understanding emotions and the ability to properly respond to them. This work presents a chatbot capable of identifying the user's personality and creating responses based on that. During this process, emotion detection is being used to detect and react to users' emotions. The chatbot uses a dynamic knowledge graph to save information as the conversation goes …

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Unsupervised Categorical Clustering On Labor Markets, Matthew James Steffen Apr 2023

Unsupervised Categorical Clustering On Labor Markets, Matthew James Steffen

Theses and Dissertations

During this "white collar recession,'' there is a flooded labor market of workers. For employers seeking to hire, there is a need to identify potential qualified candidates for each job. The current state of the art is LinkedIn Recruiting or elastic search on Resumes. The current state of the art lacks efficiency and scalability along with an intuitive ranking of candidates. We believe this can be fixed with multi-layer categorical clustering via modularity maximization. To test this, we gathered a dataset that is extensive and representative of the job market. Our data comes from PeopleDataLabs and LinkedIn and is sampled …

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Characterizing The Informativity Of Level Ii Book Data For High Frequency Trading, Logan B. Nielsen Apr 2023

Characterizing The Informativity Of Level Ii Book Data For High Frequency Trading, Logan B. Nielsen

Theses and Dissertations

High Frequency Trading (HFT) algorithms are automated feedback systems interacting with markets to maximize returns on investments. These systems have the potential to read different resolutions of market information at any given time, where Level I information is the minimal information about an equity--essentially its price--and Level II information is the full order book at that time for that equity. This paper presents a study of using Recurrent Neural Network (RNN) models to predict the spread of the DOW Industrial 30 index traded on NASDAQ, using Level I and Level II data as inputs. The results show that Level II …

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Network Representation Theory In Materials Science And Global Value Chain Analysis, Mats C. Haneberg Apr 2023

Network Representation Theory In Materials Science And Global Value Chain Analysis, Mats C. Haneberg

Theses and Dissertations

This thesis is divided into two distinct chapters. In the first chapter, we apply network representation learning to the field of materials science in order to predict aluminum grain boundaries' properties and locate the most influential atoms and subgraphs within each grain boundary. We create fixed-length representations of the aluminum grain boundaries that successfully capture grain boundary structure and allow us to accurately predict grain boundary energy. We do this through two distinct methods. The first method we use is a graph convolutional neural network, a semi-supervised deep learning algorithm, and the second method is graph2vec, an unsupervised representation learning …

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The Topology And Dynamics Of Surface Diffeomorphisms And Solenoid Embeddings, Xueming Hui Apr 2023

The Topology And Dynamics Of Surface Diffeomorphisms And Solenoid Embeddings, Xueming Hui

Theses and Dissertations

We study two topics on surface diffeomorphisms, their mapping classes and dynamics. For the mapping classes of a punctured disc, we study the $\ZxZ$ subgroups of the fundamental groups of the corresponding mapping tori. An application is the proof of the fact that a satellite knot with braid pattern is prime. For the mapping classes of the disc minus a Cantor set, we study a special type of reducible mapping class. This has direct application on the embeddings of solenoids in $\mathbb{S}^3$. We also give some examples of other types of mapping classes of the disc minus a Cantor set. …

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Language Modeling Using Image Representations Of Natural Language, Seong Eun Cho Apr 2023

Language Modeling Using Image Representations Of Natural Language, Seong Eun Cho

Theses and Dissertations

This thesis presents training of an end-to-end autoencoder model using the transformer, with an encoder that can encode sentences into fixed-length latent vectors and a decoder that can reconstruct the sentences using image representations. Encoding and decoding sentences to and from these image representations are central to the model design. This method allows new sentences to be generated by traversing the Euclidean space, which makes vector arithmetic possible using sentences. Machines excel in dealing with concrete numbers and calculations, but do not possess an innate infrastructure designed to help them understand abstract concepts like natural language. In order for a …

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Impact Of Applying Visual Design Principles To Boardwork In A Mathematics Classroom, Jennifer Rose Canizales Mar 2023

Impact Of Applying Visual Design Principles To Boardwork In A Mathematics Classroom, Jennifer Rose Canizales

Theses and Dissertations

Though black boards and white boards have been a fundamental tool in the classroom for over a century, little research has been done on how to best design and present information using these boards. My study takes visual design principles and applies them to boardwork in a mathematics classroom to better organize and clarify the content. This research shows that students notice boardwork, have strong opinions on what makes boardwork good, and that the application of design principles on boards has a significant impact on students and the teacher. Students felt their cognitive load was lightened and that they were …

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Investigations Into U'-Band Photometry Of The Haumea System, Seneca Heilesen Mar 2023

Investigations Into U'-Band Photometry Of The Haumea System, Seneca Heilesen

Undergraduate Honors Theses

The dwarf planet Haumea orbits near the edge of the Solar System in the Kuiper Belt. As it rotates, different parts of the object can be seen from Earth, so observing Haumea as it rotates allows us to see whether the surface is uniform or varied. Previous work has shown that one part of Haumea has a reddish dark spot, as opposed to the bright gray surface, and that Haumea has two nearby moons, the larger of which is called Hi’iaka. To better understand Haumea’s surface and Hi’iaka, we gathered new observations using BYU time at the Astronomical Research Consortium …

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Role Of The Cytosolic Chaperonin Cct In The Folding Of Novel Substrates, Theresa M. Smith Mar 2023

Role Of The Cytosolic Chaperonin Cct In The Folding Of Novel Substrates, Theresa M. Smith

Theses and Dissertations

All cells depend on properly folded proteins for survival and function. Misfolding of proteins results in loss of critical functions and may trigger the misfolding of other nearby proteins leading to toxic aggregation. While many proteins can fold on their own, others with complicated domain structures require assistance from protein folding machines called chaperones. The most complex and highly specialized of all chaperones is the eukaryotic chaperonin complex CCT which is necessary for the folding of a wide variety of essential proteins. These include the cytoskeletal proteins actin and tubulin as well as the Gβ subunit of the G protein …

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Hierarchical Joint Entity Recognition And Relation Extraction Of Contextual Entities In Family History Records, Daniel Segrera Mar 2023

Hierarchical Joint Entity Recognition And Relation Extraction Of Contextual Entities In Family History Records, Daniel Segrera

Theses and Dissertations

Entity extraction is an important step in document understanding. Higher accuracy entity extraction on fine-grained entities can be achieved by combining the utility of Named Entity Recognition (NER) and Relation Extraction (RE) models. In this paper, a cascading model is proposed that implements NER and Relation extraction. This model utilizes relations between entities to infer context-dependent fine-grain named entities in text corpora. The RE module runs independent of the NER module, which reduces error accumulation from sequential steps. This process improves on the fine-grained NER F1-score of existing state-of-the-art from .4753 to .8563 on our data, albeit on a strictly …

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Alegaatr The Bandit, Ethan Pedersen Mar 2023

Alegaatr The Bandit, Ethan Pedersen

Theses and Dissertations

One design strategy for developing intelligent agents is to create N distinct behaviors. At each time step during task execution, the agent, or bandit, chooses which of the N behaviors to use. Traditional bandit algorithms often (1) assume the environment is stationary, (2) focus on asymptotic performance, and (3) do not incorporate external information available to them. Each of these simplifications limits these algorithms such that they often cannot be used successfully in practice. In this paper, we propose a new algorithm, called AlegAATr, as a step toward overcoming these deficiencies. AlegAATr utilizes a technique called Assumption-Alignment Tracking (AAT), proposed …

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Developing Methods For Measuring In Vivo Lipid Metabolism, Russell L. Denton Feb 2023

Developing Methods For Measuring In Vivo Lipid Metabolism, Russell L. Denton

Theses and Dissertations

Lipid metabolism is critically important to the normal function of individual cells and for signaling between tissues of the human body. There is a great need to quantify changes in lipid metabolism because of its implications in both normal healthy conditions and during disease development. In our first study, we developed a liquid chromatography mass spectrometry based workflow to assess in vivo metabolism of murine brain lipids. This involved sample preparation, data acquisition, and analysis software development and improvements. Regarding sample preparation, we maintained the mice at 5% body water for the duration of the experiment. As mouse metabolism proceeds, …

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Characterization Of Telsam Chaperone Linker To Improve Crystallization Resolution And Structural Elucidation Of The Hydrogenase Maturase Complex, Parag Laljibhai Gajjar Feb 2023

Characterization Of Telsam Chaperone Linker To Improve Crystallization Resolution And Structural Elucidation Of The Hydrogenase Maturase Complex, Parag Laljibhai Gajjar

Theses and Dissertations

TELSAM crystallization can be a revolutionary tool for the facile crystallization of proteins. TELSAM can increase the rate of crystallization and form crystals at low protein concentrations without direct contact between TELSAM polymers and, in some cases, with very minimal crystal contacts overall. To further understand and characterize TELSAM crystallization, we sought to understand the requirements for the composition of the linker confirmation between TELSAM and the fused target protein. We evaluated four linkers, AlaAla, AlaVal, ThrVal, and ThrThr, between 1TEL and the human CMG2 vWa domain. We compared the number of successful crystallization conditions, the number of crystals, the …

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Community Detection Via Persistent Homology Surfaces, Abigail Jenkins Jan 2023

Community Detection Via Persistent Homology Surfaces, Abigail Jenkins

Theses and Dissertations

Network science continues to be an area of growing interest. In this thesis we introduce new methods of analyzing the structure of networks through the use of persistent homology. We propose the notion of a network's persistent surface, which allows us to visualize a vertex's relation to the whole network from a purely homological point of view. We further introduce a method of persistent surface community detection that finds vertices that play the same structural role in the network. We describe how these concepts provide the basis for an equivalence class among the vertices of a network, and provide many …

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Gamelan Gong Directivity Dataset, Samuel D. Bellows, Dallin T. Harwood, Kent L. Gee, Micah R. Shepherd Jan 2023

Gamelan Gong Directivity Dataset, Samuel D. Bellows, Dallin T. Harwood, Kent L. Gee, Micah R. Shepherd

Directivity

No abstract provided.

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The Unexpected Effectiveness Of Strategically Sparse Cooperation, Neal D. Munson Dec 2022

The Unexpected Effectiveness Of Strategically Sparse Cooperation, Neal D. Munson

Theses and Dissertations

In this work, we will show a result derived from a class of economically inspired multi-agent differential games. The result shows that in the class of games we present, only a sparse cooperation structure is needed by the agents to achieve an outcome that is in a particular sense "optimal". One may expect that to achieve such an outcome, a centralized control or full cooperation would be necessary; it is not. Not only is it not necessary - it is never necessary. We precisely characterize what kind of cooperation IS necessary to attain that kind of optimality. Only the sparsest …

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Short-Range Magnetic Correlations, Spontaneous Magnetovolume Effect, And Local Distortion In Magnetic Semiconductor Mnte, Raju Baral Dec 2022

Short-Range Magnetic Correlations, Spontaneous Magnetovolume Effect, And Local Distortion In Magnetic Semiconductor Mnte, Raju Baral

Theses and Dissertations

The antiferromagnetic semiconductor MnTe has recently attracted significant interest as a potential high-performance thermoelectric material. Its promising thermoelectric properties are due in large part to short-range magnetic correlations in the paramagnetic state, which enhance the thermopower through the paramagnon drag effect. Using magnetic pair distribution function (mPDF) analysis of neutron total scattering data, we present a detailed, real-space picture of the short-range magnetic correlation in MnTe, offering a deeper view into the paramagnon drag effect and the nature of the correlated paramagnetic state. We confirm the presence of nanometer-scale antiferromagnetic correlations far into the paramagnetic state, show the evolution of …

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Quantifying Volatile Fatty Acid Concentrations During The Pretreatment And Anaerobic Digestion Process, Sascha Boutelle Dec 2022

Quantifying Volatile Fatty Acid Concentrations During The Pretreatment And Anaerobic Digestion Process, Sascha Boutelle

Theses and Dissertations

Producing renewable energy from biomass or from the wastewater treatment process has gained momentum in the past 20 years. Anaerobic digestion has historically been used as one step in the waste treatment process, to both reduce the mass of waste that needs to be disposed of and to generate biogas. This process is typically only able to reduce 30-40% of the waste mass because of the recalcitrant nature of the waste streams being treated. Anaerobic pretreatment with the thermophilic bacteria Caldicellulosiruptor bescii (C. bescii) has been proven to increase the percentage of mass digested and consequently increase methane production to …

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Effect Of X-Ray Illumination On Magnetic Domain Memory In [Co/Pd]/Irmn Multilayers, Colby Singint Walker Dec 2022

Effect Of X-Ray Illumination On Magnetic Domain Memory In [Co/Pd]/Irmn Multilayers, Colby Singint Walker

Theses and Dissertations

This thesis focuses on investigating the possible x-ray illumination effects on the magnetic domain memory (MDM) in magnetic [Co/Pd]IrMn multilayers. In this material, MDM is induced via exchange couplings between the ferromagnetic Co/Pd layer and the antiferromagnetic IrMn layer. To carry out this investigation, we have used magneto-transport and x-ray resonant magnetic scattering. The use of magneto-transport in-situ at synchrotron x-ray scattering facility has allowed us to follow the gradual effect of x-ray illumination on the amount of exchange bias, initially present after field cooling the material. With our in-situ measurements we have been able to see that x-ray illumination …

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A Usability Study Of Fido2 Hardware Tokens On Mobile Devices, Stephen Lambert Dec 2022

A Usability Study Of Fido2 Hardware Tokens On Mobile Devices, Stephen Lambert

Theses and Dissertations

Passwords as the primary form of authentication on the web have many issues, such as password re-use across sites and difficulty in remembering secure passwords. The FIDO Alliance has created a passwordless system that has with support from companies like Google, Apple, and Microsoft: FIDO2. Studies have shown so far that users find FIDO2 usable on personal computers, but no work has been published on its usability on mobile devices. I conducted a lab study in which participants used FIDO2 passwordless authentication with hardware tokens on a mobile phone. Participants found FIDO2 usable on mobile devices, but had similar fears …

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Computational Studies Of Dinuclear Catalytic Reaction Mechanisms, James Curtis Coombs Iii Dec 2022

Computational Studies Of Dinuclear Catalytic Reaction Mechanisms, James Curtis Coombs Iii

Theses and Dissertations

Heterodinuclear and homodinuclear metal complexes with a direct metal-metal interaction offer the potential for unique catalysis due to cooperativity effects that impact reaction mechanisms, reactivity, and selectivity. Quantum-chemical density functional theory (DFT) calculations can directly examine the origin of dinuclear reactivity and selectivity effects. Chapter 1 provides a short overview of heterodinuclear and homodinuclear catalysts that have been experimentally and computationally examined. Chapter 2 reports our study using DFT methods to understand the mechanism and reactivity of a heterodinuclear Co-Zr catalyst with phosphinoamide ligands that catalyzes a Kumada coupling between alkyl halides and alkyl Grignards. Chapter 3 reports DFT calculations …

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Wildfire Modeling With Data Assimilation, Andrew Johnston Dec 2022

Wildfire Modeling With Data Assimilation, Andrew Johnston

Theses and Dissertations

Wildfire modeling is a complex, computationally costly endeavor, but with droughts worsening and fires burning across the western United States, obtaining accurate wildfire predictions is more important than ever. In this paper, we present a novel approach to wildfire modeling using data assimiliation. We model wildfire spread with a modification of the partial differential equation model described by Mandel et al. in their 2008 paper. Specifically, we replace some constant parameter values with geospatial functions of fuel type. We combine deep learning and remote sensing to obtain real-time data for the model and employ the Nelder-Mead method to recover optimal …

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Determining Figure Skating Jump Under-Rotation In Real-Time Using Imu Sensors During Practice, Duncan O. Furgeson Dec 2022

Determining Figure Skating Jump Under-Rotation In Real-Time Using Imu Sensors During Practice, Duncan O. Furgeson

Theses and Dissertations

We explore the use of machine learning to detect under-rotation in figure skating jumps. Under- rotation in jumps is difficult for the skater to sense but learning to recognize under-rotation is an impor- tant part of learning proper jump technique. To address this difficulty, we present the Under-rotation Monitor, or UR Monitor, a system for detecting under-rotated figure skating jumps in real-time. UR Monitor uses a single inertial measurement unit (IMU) attached to the skater's waist that sends a stream of accelerometer and gyroscope data to a mobile phone via Bluetooth. The mobile phone creates and sends an input vector …

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Complete Equitable Decompositions, Joseph Paul Drapeau Dec 2022

Complete Equitable Decompositions, Joseph Paul Drapeau

Theses and Dissertations

A well-known result in spectral graph theory states that if a graph has an equitable partition then the eigenvalues of the associated divisor graph are a subset of the graph's eigenvalues. A natural question question is whether it is possible to recover the remaining eigenvalues of the graph. Here we show that if a graph has a Hermitian adjacency matrix then the spectrum of the graph can be decomposed into a collection of smaller graphs whose eigenvalues are collectively the remaining eigenvalues of the graph. This we refer to as a complete equitable decomposition of the graph.

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Developing A Quantitative Understanding Of U-Substitution In First-Semester Calculus, Leilani Camille Heaton Fonbuena Dec 2022

Developing A Quantitative Understanding Of U-Substitution In First-Semester Calculus, Leilani Camille Heaton Fonbuena

Theses and Dissertations

In much of calculus teaching there is an overemphasis on procedures and manipulation of symbols and insufficient emphasis on conceptual understanding of calculus topics. As such students to struggle to understand and use calculus ideas in applied settings. Research shows that learning calculus topics from a quantitative reasoning-perspective results in more powerful and flexible conceptions of calculus topics like integration. However, topics beyond introducing integrals and the Fundamental Theorem of Calculus, like u-substitution, have yet to be explored from a quantity-based perspective. In this study, I conducted a set of two clinical interviews where we discussed quantitative meanings of integrals, …

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Structural Reasoning With Rational Expressions, Dana Steinhorst Dec 2022

Structural Reasoning With Rational Expressions, Dana Steinhorst

Theses and Dissertations

Many students struggle to make sense of algebraic expressions in math. This lack of understanding results in students making symbolic manipulation errors, hindering their procedural fluency. Researchers believe these errors are linked to students' lack of structural reasoning. While research has shown that students rarely engage in expert structural reasoning, little is known about how students actually reason structurally. In this study, I interviewed six high school calculus students to study the way they identified, matched, and evaluated structures as they solved problems involving rational expressions and equations. I analyzed the participant interviews and outlined the matching process they used …

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Determination Of A Catalytic Mechanism By Time Resolved Fourier Transform Infrared Spectroscopy And Time Domain Analysis Of Data From Fourier Transform Ion Cyclotron Resonance Mass Spectrometry, Jacob T. Davis Dec 2022

Determination Of A Catalytic Mechanism By Time Resolved Fourier Transform Infrared Spectroscopy And Time Domain Analysis Of Data From Fourier Transform Ion Cyclotron Resonance Mass Spectrometry, Jacob T. Davis

Theses and Dissertations

Heterobimetallic catalysts offer large potential for efficient and selective catalysis of a wide range of reactions. Better understanding of these catalytic mechanisms could yield further improvement in their catalytic abilities. Cp(CO)2Fe-Cu(IPr) (IPr = N,N-bis(2,6-diisopropylphenyl)imidazol-2-ylidene) is a catalyst that has been reported to catalyze arene borylation. The catalytic mechanism of this catalyst that had been previously proposed had the initial step being a metal-metal cleavage. However, computational modeling suggested an alternate mechanism that could be more energetically favorable. Rather than a metal-metal cleavage as the initial step, we proposed a photoactivated carbonyl dissociation. To support this proposition, we performed time resolved …

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