Digital Commons Network^™

Characterizing Electrospray Performance Of Hydroxylammonium Nitrate (Han) And 2-Hydroxyethylhydrazinium Nitrate (Hehn) Ionic Liquids By Mass Spectrometry And Dynamics Simulations, Wenjing Zhou

Dissertations, Theses, and Capstone Projects

Dual-mode propulsion combines chemical and electric propulsion methods into a single compact system by sharing hardware and propellant for both modes, offering complementary advantages tailored to specific mission needs. A promising propellant candidate for dual-mode propulsion is a binary mixture of hydroxylammonium nitrate (HAN) and 2-hydroxyethylhydrazinium nitrate (HEHN) ionic liquids (ILs). Each of the two ILs was developed as a greener alternative to the traditional, yet toxic, hydrazine monopropellant used in chemical propulsion. Recently, their potentials in electrospray propulsion have garnered attention. This thesis focused on the investigation of reaction dynamics and kinetics of HAN, HEHN and their binary mixture …

Excitons And Polaritons In Two-Dimensional Materials Heterostructures - Applications As Qubits, Time Crystals, And Superfluids, Gabriel Pimenta Martins

Dissertations, Theses, and Capstone Projects

This dissertation is concerned with exploring the properties and applications of excitons and polaritons in two-dimensional (2D) materials and heterostructures. It focuses on their potential to form qubits, time crystals, and superfluids. The work is motivated by the unique electronic and optical properties of 2D materials—specifically, their ability to host strongly bound excitons and hybrid light-matter quasiparticles known as polaritons. By exploiting a combination of theoretical modeling and numerical simulations, this work examines the behavior of these quasiparticles under various physical conditions, including strain-induced pseudomagnetic fields, optical microcavities, and periodic external potentials.

The first part of this dissertation is devoted …

Unpacking The Orders, Leonard J. Santos

Dissertations, Theses, and Capstone Projects

At the end of the first week of his presidency this year in 2025, Donald Trump signed a total of thirty-six executive orders. After only one month, that number had gone up to seventy-six. He is currently on track to sign the highest number of executive orders in his first year in office of any president in the last 50 years, and potentially even the last 100 years if he keeps moving at this rate. In the first 90 days of his term, Donald Trump has signed 159 executive orders, more than any other president in the history of the …

Transmedial Econarratology: Environment And The Subject Of Science Fiction, Joseph R. Boisvere

Dissertations, Theses, and Capstone Projects

This dissertation argues that narrators are constructed by their interactions with diegetic space and time in an ecological relationship. This argument draws upon Erin James’s work on econarratology, particularly her book The Storyworld Accord: Econarratology and Postcolonial Narratives, putting her theories of narrating time and place in dialogue with contemporary “unnatural” narratology as theorized by scholars such as Jan Alber and Brian Richardson. Science fiction (SF) offers a rich complement to these theoretical stances. I also focus much of my dissertation on how narratology works across and is influenced by specific media, featuring literary, audiovisual, and digital media, including novels, …

Sla Evaluation And Composition In Reconfigurable Cloud-Based Services, Michael Iannelli

Dissertations, Theses, and Capstone Projects

Given the business model of offering data and computing services in a cloud setting, a major question arises: How do the services of one cloud provider compare to those of others? With the ubiquitous use of smartphones and tablets, the ability of a cloud provider to support QoS and client mobility becomes paramount. This research proposes a methodology for evaluating service-level agreements (SLAs) between cloud providers and their consumers, with a particular focus on dynamic SLA composition to adapt to changes in the application requirements and the external environment—such as traffic surges, security threats, or evolving business models.

In one …

Tracing My Roots: An Exploratory Data Visualization And Analysis Of Jewish Immigration And Assimilation To New York City, Jamie E. Gelberg

Dissertations, Theses, and Capstone Projects

As my Capstone, I explored the complex process of immigrant assimilation to New York City from the late 19th century and beyond through a personal lens, using my Ashkenazi Jewish family as a case study.

I outlined and analyzed relevant demographic data from the US Census Bureau, Berman Jewish DataBank, and other sources to understand New York City during this period and how Jewish immigrants fit into the story. I focused on my family history, immigration and settlement, social assimilation, and economic status. I also incorporated personal narratives from my family history from 3 generations. These narratives help provide context …

Integrating Universal Generative Ai Platforms In Educational Labs To Foster Critical Thinking And Digital Literacy, Vasiliy S. Znamenskiy, Joel Hernandez, Rafael Niyazov

Publications and Research

This study investigates the educational potential of generative artificial intelligence (GenAI) platforms based on large language models (LLMs), such as ChatGPT, Claude, and Gemini, as tools for studentcentred learning. Recognizing the current limitations of GenAI, particularly its propensity for generating inaccurate or misleading information—the paper proposes a novel instructional strategy: an interdisciplinary laboratory designed to foster critical evaluation of GenAI-generated outputs. In this pedagogical model, students engage with GenAI systems by posing questions or solving problems drawn from topics they have already studied and understand. Equipped with correct answers, students are positioned to assess the accuracy and relevance of AI-generated …

Fast Transients From Magnetic Disks Around Non-Spinning Collapsar Black Holes, Justin A. Bopp

Dissertations, Theses, and Capstone Projects

Most black holes (BHs) formed in collapsing stars have low spin, though some are expected to acquire a magnetic accretion disk during the collapse. While such BH disks can launch magnetically driven winds, their physics and observational signatures have remained unexplored. We present global 3D general relativistic magnetohydrodynamic simulations of collapsing stars that form slowly spinning BHs with accretion disks. As the disk transitions to a magnetically arrested state, it drives mildly relativistic, wobbling, collimated magnetic outflows through two mechanisms: steady outflows along vertical magnetic field lines (“Blandford-Payne jets”) and magnetic flux eruptions. With isotropic-equivalent energy of E_iso ≈10 …

Nurturing The Student Voice And Its Creative Power In Mathematics Teaching And Learning: Research With Students On Emotion, Imagination, And Understanding., Luis Adolfo Zambrano

Dissertations, Theses, and Capstone Projects

This research in mathematics education explores the teaching and learning of mathematics at the high school and community college levels, integrating diverse research methods to examine how educators can cultivate a dynamic, collaborative, and responsive classroom climate. Framed by K. Tobin and K. Alexakos’s authentic inquiry education research framework (2020), the methodology actively engages students as co-researchers, valuing their insights and experiences as integral to the learning process. This approach fosters a meaningful dialogue on managing emotional and cognitive challenges faced by students of mathematics while identifying strategies to support and enhance students’ innate imaginative and creative capacities.

Grounded in …

Exploring The Enstatite Chondrites: Modal Abundances, Metamorphic History, And Volatile Challenges, Mabel Gray

Dissertations, Theses, and Capstone Projects

This thesis investigates the formation conditions, thermal histories, and volatile inventories of enstatite chondrites (ECs). A diverse set of ECs is analyzed to capture the broad variability within this meteorite class. Chapter 1 presents a comparative analysis of mineral abundances using automated point counting, X-ray diffraction analysis, and XMapTools-based phase mapping. The results reveal significant variations in silicate and sulfide abundances across EC groups, challenging the conventional binary classification and suggesting distinct formation conditions. Chapter 2 explores the thermal histories of two highly equilibrated EH chondrites, proposing a novel formation mechanism on the parent asteroid: contact metamorphism driven by an …

Computability Theoretic Aspects Of Profinite Groups And Models Of Presburger Arithmetic, Jason Block

Dissertations, Theses, and Capstone Projects

Profinite groups, which are exactly the Galois groups, are all either finite or uncountable. However, all second countable profinite groups can be presented as the set of paths through a countable tree. We use these tree presentations to find upper bounds on the complexity of the existential theories of profinite groups, as well as to prove sharpness for these bounds. These complexity results enable us to distinguish the class of profinite groups that are isomorphic to a direct product of finite groups, for which we find an upper bound on the complexity of the entire first order theory. Additionally, given …

How Argentina Won The 2022 Fifa Men's World Cup: A Data Story, Aniruddha Parthasarathy

Dissertations, Theses, and Capstone Projects

This project analyzes Argentina’s 2022 FIFA Men’s World Cup win using open-source football (soccer) data. The project evaluates the team’s performance at a micro-level across three domains: without possessing the ball, possessing the ball and the team’s in-game management tactics. A statistical framework, i.e., multiple linear regression modeling, was used to identify the five key defensive actions influencing the Argentinian team’s intensity of pressure applied, and visualized by heatmaps and time-segmented plots. More specifically, an Expected Threat (xT) analysis quantified the threat or danger from passes and progressive carries (moving the ball at least 10 meters), revealing that Lionel Messi’s …

Streaming Instabilities In Class 0/I Disks, Shirin Gul Zaidi

Dissertations, Theses, and Capstone Projects

While it is clear that planets form in protoplanetary disks, fragmentation and the radial drift of pebbles inhibit the growth of grains to planetesimals. To overcome these barriers, effective localized dust clumping on a short enough time scale is required. One promising solution to this problem is the streaming instability. Streaming instability is only triggered with a large enough dust-to-gas ratio and grain size. Though it is unknown when and where those conditions are met in protoplanetary disks, recent studies have indicated that planetary cores likely require early formation to match detected exoplanet system masses, so that we need to …

Parametrization Of Formal Norm Compatible Sequences, Joseph Dicapua

Dissertations, Theses, and Capstone Projects

We give a classification of power series parametrizing Lubin-Tate trace compatible sequences. This proof answers a question posed in the literature by Berger and Fourquaux. Lubin-Tate trace compatible sequences are a generalization of norm compatible sequences, which arise in Iwasawa theory and local class field theory. The result we prove generalizes the interpolation theorem proved by Coleman in the classical norm compatible sequence case. We also, jointly with Victor Kolyvagin, give a method for finding such series explicitly in certain special cases.

Artificial Intelligence And Astronomy: Lab Manual For Generative Ai-Based Learning Activities, Vasiliy Znamenskiy

Open Educational Resources

This laboratory manual introduces an innovative approach to teaching astronomy by integrating generative artificial intelligence (AI) tools into hands-on educational activities. Aimed at undergraduate and general education students, the manual guides learners through interactive exercises that involve evaluating AI-generated text responses, creating scientifically inspired images, and producing short educational videos about astronomical phenomena. By engaging with platforms such as ChatGPT, Gemini, DALL·E, and InVideo, students develop critical thinking skills, enhance their digital literacy, and deepen their understanding of space science. The method emphasizes inquiry-based learning, creativity, and scientific communication, preparing students to become thoughtful users of AI in academic and …

Quantum-Enhanced Training Of Large Language Models: A Hybrid Approach, Nan Wu, Fangmin Song, Xiangdong Li

Publications and Research

The training of large language models (LLMs) presents significant computational challenges, particularly regarding efficient convergence. This paper presents a hybrid quantum-classical framework designed to address the significant computational challenges associated with training large language models (LLMs). By integrating quantum computing principles superposition, entanglement, and tunneling with classical deep learning methods, we propose an approach to accelerate convergence, enhance optimization efficiency, and improve model generalization. Specifically, quantum feature mapping is employed to project classical data into high-dimensional Hilbert spaces, facilitating more expressive data representations. Quantum-assisted optimization algorithms, such as Quantum Approximate Optimization Algorithm (QAOA) and Variational Quantum Eigensolver (VQE), efficiently navigate …

Math 115: College Algebra Instructor Guide, Seth Lehman

Open Educational Resources

OER instructor guide for Math 115, College Algebra, Queens College

Mat 301 - Applied Statistics And Data Analysis, Eric Aragundi

Open Educational Resources

Data analysis using standard statistical methods and relevant computer software. Emphasis on real-world data, interpretation, and misinterpretation of computer output.

This syllabus contains open source notebook about data analysis content.

Nuclear Magnetic Resonance Dynamics Of Pyrazole-Litfsi Eutectic Solvents As Promising Electrolytes, Emilia Pelegano-Titmuss, Giselle De Araujo Lima E Souza, Muhammad Zulqarnain, Ramez Elgammal, Thomas Zawodzinski, Steven Greenbaum

Undergraduate Research

Deep Eutectic Solvents (DESs) have emerged as promising candidates to replace conventional organic solvents in various technological applications due to their low vapor pressure, non-flammability, and ease of preparation at low costs. In particular, Type IV DESs, which are composed of metal salts and hydrogen bond donors, are possible replacements for lithium-ion battery electrolytes due to their potential of having high lithium transference numbers. In this study, we investigated solvents of Pyrazole and LiTFSI at varying molar ratios using Fast Field Cycling (FFC) NMR Relaxometry. Notably, the 1:2 LiTFSI: Pyrazole sample shows distinct behavior, exhibiting enhanced relaxation rates for ^{1 …}

Characterization Of Sars-Cov-2 Replication And Transcription Complexes Via Structural And Evolutionary Approaches, Amelie Ghirardo, Ben Shabatian, Avishai Aghelian, Kyle Tau, Eleonora Gianti

Undergraduate Research

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused around 700M cases and over 7M COVID-19-related deaths recorded worldwide (World Health Organization, March 2025). Aiming to effectively combat this and other disease-causing Coronaviruses (CoV), unprecedented research efforts led to the development of new vaccines and antiviral therapies. Due to emergence of variants of concern (VOCs) with increased transmissibility, immune evasion from vaccination, and potential to resist the available treatments, SARS-CoV-2 continues to represent a major threat to global health. Hence, there is a pressing need to discover new antivirals with broad-spectrum efficacy against multiple SARS-CoV-2 variants and related CoVs. This project …

Protein Stability Retention Under Harsh Conditions, Kaylen Su

Student Theses and Dissertations

Plastic waste is a growing environmental concern due to its resistance to natural degradation, leading to long-term accumulation in landfills and oceans. One potential solution is enzymatic degradation, where specific enzymes break down plastic into smaller, biodegradable components. However, enzymes often lose their effectiveness under the extreme conditions plastics experience during manufacturing, such as high temperatures, mechanical stress, and dehydration. This study explores whether small molecules, known as ligands, can help stabilize enzymes and improve their ability to break down plastics.

Using molecular dynamics simulations, we tested four ligands—poly(ethylene glycol) (PEG), 6-hydroxyhexanoic acid (HHA), benzalkonium chloride (BC), and 6-aminohexanoic acid …

Investigating Potential Sugar-Related Uncertainties In A Proxy For Ancient Co2, Liam Cooper

Student Theses and Dissertations

The ε_p proxy for ancient pCO₂ can potentially estimate ancient pCO₂ as from the evolution of rubisco-based photosynthesis, using the difference in stable carbon isotope ratios (δ¹³C) between fixed and inorganic carbon, assuming this difference is proportional to pCO₂. This study aims to address uncertainty with the use of photosynthetic microbes in proxies for ancient pCO₂. While previous studies address uncertainties related to the δ¹³C of initial fixed photosynthate (e.g., growth rate), we aim to address the effects of downstream carbon allocation. Specifically, if a significant fraction of fixed …

Macroeconomics Textbook For Kingsborough Students, Dorina Tila

Open Educational Resources

Textbook customized for Kingsborough students. It was published in May 2025. You can access it through pressbook as well.

https://pressbooks.cuny.edu/macroeconomicsbronxkcc/

In The Quest For New Horizons: Evaluating Novel Therapeutic Approaches For Tuberculosis Treatment, Selassie Mawuko, Aminata Traore, Bibi-Sakeena Khemraj, Anna Steto, Richa Gupta

Publications and Research

Tuberculosis (TB) in humans, caused by Mycobacterium tuberculosis, is a significant global health concern, resulting in high disease burden and mortality each year which together make it the world’s topmost infectious killer. The emergence of multidrug-resistant tuberculosis (MDR-TB) in recent decades has further exacerbated the present situation and warrants an urgent need to develop and investigate innovative treatment regimes. This study aims to assess the therapeutic potential of newly identified drug candidates, namely Bedaquiline, Delamanid, and Linezolid, in treating MDR-TB. We adopted a consolidated and integrated approach encompassing a thorough literature review, empirical experimental studies, multiple sequence alignments, and …

Machine Learning Course: A 15-Week Interactive Curriculum With Code And Case Studies, Pegah Khosravi

Open Educational Resources

This open-access machine learning course is a comprehensive 15-week curriculum developed and published on GitHub with full Google Colab compatibility. It combines theoretical concepts with hands-on Python coding, real-world datasets, and structured projects covering regression, classification, clustering, deep learning, transformers, and multimodal AI. The course is designed for students, educators, and researchers interested in applied machine learning, including biomedical applications. It includes explainable AI components and ethical discussions to align with modern AI standards. The course is maintained by BioMind AI Lab at CUNY.

Bayesian Statistics: Origins And Applications, Evelyn Pulla

Publications and Research

Bayesian Statistics applies Bayes' Theorem to update beliefs through new evidence. In this project, I explored how Bayesian Statistics applies into real supporting decision-making under uncertainty. By solving problems using data, I was able to realize how prior knowledge and evidence collaborate to make better conclusions. The project also demonstrates how Bayesian reasoning corrects our intuition to make decisions based on logical reasoning. Through this project, I was able to learn why using probability to make informed decisions matters both in science and real life.

Automation Of Javanese Shadow Puppets Using Machine Control, Kristian Rice, Yinson Tso, Mukhammadali Yuldoshev

Publications and Research

The virtualization of Javanese shadow puppetry (Wayang Kulit) offers a unique opportunity to preserve and revitalize traditional performance art through immersive digital platforms. This project explores the development of a virtual Wayang Kulit experience using real-time 3D engines like Unity/Unreal Engine while focusing on simulating the mechanics and aesthetics of shadow puppet performance. The puppets are designed using detailed 2D planes and rigged with skeletal systems to reflect the stylized motion of traditional puppetry. An aspect of this project is integrating an AI-driven control system that autonomously animates the puppets, learning from recorded puppeteer performances to replicate gesture, rhythm, and …

Symmetry Induced Pairing In Dark Excitonic Condensate At Finite Temperature, Adham Alkady, Anatoly Kuklov

Publications and Research

Bose Einstein condensate of dark intervalley excitons must be inherently multi-component because of crystalline symmetries. Since valleys hosting such excitons are separated by large quasi-momenta, a minimal inter-component Josephson-type coupling can only be established between pairs of excitons from the time-reversed valleys. As a result, a paired condensate can emerge at finite temperature, that is, the off-diagonal order exists for the pairs from the time-reversed valleys, while the individual valleys are disordered. This prediction follows from the elementary mean field analysis regardless of the dimensionality. However, as Monte Carlo simulations show, no such a phase exists in 3D crystals. Instead, …

Hybridize Functions: A Tool For Automatically Refactoring Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian, Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code—supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the “best of both worlds,” using them effectively requires subtle considerations to make code amenable to safe, accurate, and efficient graph execution—avoiding performance bottlenecks and semantically inequivalent results. We discuss the engineering aspects of a …

Hybridize Functions: A Tool For Automatically Refactoring Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian, Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code—supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the “best of both worlds,” using them effectively requires subtle considerations to make code amenable to safe, accurate, and efficient graph execution—avoiding performance bottlenecks and semantically inequivalent results. We discuss the engineering aspects of a …