Digital Commons Network^™

Real-Time Likelihood Map Generation To Localize Short-Duration Gamma-Ray Transients, Jeremy Buhler, Marion Sudvarg

Computer Science Faculty Research & Creative Works

High-energy transient astrophysical phenomena, such as supernovae and binary neutron star mergers, benefit from a multi-wavelength investigation in which a space- or balloon-based omnidirectional telescope detects and localizes early high-energy emissions (such as a gamma-ray burst), then alerts a narrow-field follow-up instrument to observe the source. The high-energy telescope must provide a map that assigns to each sky location a likelihood that the source appears there. To issue prompt alerts despite limits on communication bandwidth and latency, it is desirable to compute this map aboard the high-energy telescope, but doing so requires rapid response while computing under stringent size, weight, …

Performance Modeling And Improvements On The Grb Source Localization Streaming Pipeline Aboard The Antarctic Demonstrator For The Advanced Particle-Astrophysics Telescope (Adapt), Ye Htet, Ye Htet, Marion Sudvarg, Marion Sudvarg, Honghao Yang, Jeremy Buhler, Roger Chamberlain, Wenlei Chen, Wenlei Chen, James Buckley, Matthew Andrew, Blake Bal, Elisabetta E. Bissaldi, Richard G. Bose, Dana Braun, James H. Buckley, Jeremy Buhler, Eric Burns

Computer Science Faculty Research & Creative Works

The Advanced Particle-astrophysics Telescope (APT) is a mission concept for a space-based gamma-ray telescope whose capabilities include prompt localization of gamma-ray bursts (GRBs) to support multi-wavelength and multi-messenger astrophysics. ADAPT — APT's balloon-borne prototype — can localize GRBs in well under a second using on-board computing hardware. ADAPT will partner with ground-based, fast-slewing optical telescopes, rapidly providing alerts that enable the partner to observe a short-duration burst within a few seconds of detection. In this work, we investigate the utility of having ADAPT issue progressively more accurate location estimates for a GRB as detected Compton events from the burst accumulate …

Polyminhash: Efficient Area-Based Minhashing Of Polygons For Approximate Nearest Neighbor Search, Alima Subedi, Sankalpa Pokharel, Satish Puri

Computer Science Faculty Research & Creative Works

Similarity searches are a critical task in data mining. As datasets grow larger, exact nearest neighbor searches quickly become unfeasible, leading to the adoption of approximate nearest neighbor (ANN) searches. ANN has been studied for text data, images, and trajectories. However, there has been little effort to develop ANN systems for polygons in spatial database systems and geographic information systems. We present PolyMinHash, a system for approximate polygon similarity search that adapts MinHashing into a novel 2D polygon-hashing scheme to generate short, similarity-preserving signatures of input polygons. Minhash is generated by counting the number of randomly sampled points needed before …

Accessing Cation And Anion Redox In Mixed-Valent One-Dimensional Iron-Chalcogenides, Na1.5fe1s2–Xsex(X = 0, 1, And 2), For Na-Ion Batteries, Santhoshkumar Sundaramoorthy, Milad Aghayi-Anaraki, Sutapa Bhattacharya, Amitava Choudhury

Chemistry Faculty Research & Creative Works

Sodium-ion batteries (NIBs) have attracted considerable attention as a cost-effective and sustainable alternative to lithium-ion batteries (LIBs), owing to the abundance and low cost of sodium resources. Here, we investigate previously reported mixed-valent (Fe^3+/2+) one-dimensional (1D) iron chalcogenides: Na1.5FeS2, its selenide analogue Na1.5FeSe2, and newly developed solid solution Na1.5FeSSe, focusing on their synthesis, structural characterization, and electrochemical performance in NIBs. While the full Fe²⁺sulfide version (NaFeS2) of the compound is explored in solid-state cells for its dual cation–anion redox mechanism, we reveal the effect of anion substitution on the electrochemical behavior of Na1.5FeS2–xSex(x = 0, 1, …

Engineered Multifunctional Drug-Loaded Dendrimer Nanoparticles For Glaucoma: Triple Mechanism Via Antioxidant Activity, Iron Chelation, And Enhanced Ocular Transport, Burhan Ates, Ashish Trital, Vimalin Jeyalatha Mani, Lei Xu, Jonathan Kenlee, Nuran Ercal, Hu Yang

Chemistry Faculty Research & Creative Works

In this study, we developed multifunctional nanoparticles based on polyamidoamine (PAMAM) dendrimers functionalized with caffeic acid (CA) and poly (ethylene glycol) maleimide (PEGM) for the topical delivery of hydrophobic antiglaucoma drugs brimonidine (BM) and betaxolol (BX). The PAMAM-CA and PAMAM-CA-PEGM conjugates exhibited antioxidant and iron-chelating activities in a dose-dependent manner. BM- and BX-loaded dendrimer nanoparticles produced using a multi-inlet vortex mixer showed uniform spherical morphology (∼80 nm by TEM) and hydrated sizes of ∼135-144 nm by DLS. Both nano formulations demonstrated high cytocompatibility with human corneal epithelial cells and were nonirritant in the HET-CAM assay, with PEGM further improving cytocompatibility. …

Wacsaw: An Adaptive, Statistical Method To Classify Movement Into Sleep And Wakefulness States, Austin Vandegriffe, V. A. Samaranayake, Matthew S. Thimgan

Mathematics and Statistics Faculty Research & Creative Works

Wearable actimeters can improve our understanding of sleep in the natural environments. Current algorithms may produce inaccuracies in specific individuals and circumstances, such as quiet wakefulness. New hardware allows data collection at higher frequencies enabling sophisticated analytical methods. We have developed a novel statistical algorithm, the Wasserstein Algorithm for Classifying Sleep and Wakefulness (WACSAW), to identify behavioral states from recordings of everyday movement. WACSAW employs optimal transport techniques to identify segments with differing activity variability. Functions characterizing the segments' movement distributions were clustered into two groups using a k-nearest neighbors and labeled as sleep or wake based on their proximity …

Early Career Setback And Future Achievement In Professional Sports, Suman Kalyan Maity, Yang Wang, Nima Dehmamy, Victoria Medvec, Brian Uzzi, Dashun Wang

Computer Science Faculty Research & Creative Works

A central tenet of human performance posits that past success is a key predictor of future outcomes. This principle underpins selection processes in various human endeavors, shaping opportunity, wage, and winner-take-all inequalities. Here we systematically examine the future performance of previous winners and non-winners across two sports contexts using two different empirical strategies. First, we track young athletes participating in world-class track and field competitions and compare the future performance of bronze medalists to those finishing just shy of the podium. Next, we study a novel natural experiment in tennis, where we compare future performances of 'lucky losers'—players who advanced …

Catalytic Synthesis Of Iron-Doped Graphitic Aerogels From Poly(Phloroglucinol-Terephthalaldehyde – Urethane) Precursors, Stephen Yaw Owusu, Rushi U. Soni, Chariklia Sotiriou-Leventis

Chemistry Faculty Research & Creative Works

We report a new class of graphitic carbon aerogel precursors based on iron oxide-doped poly(phloroglucinol-terephthalaldehyde–urethane) (T-POL/PU-FeOx) networks. The hybrid polymeric network incorporates a rigid aromatic triisocyanate, tris(4-isocyanatophenyl)methane, which reacts in situ with the hydroxyl groups of phloroglucinol to form a polyurethane-containing framework. Monolithic aerogels derived from this system undergo catalytic graphitization at significantly reduced temperatures (800–1500 °C) compared to conventional graphitization (2500–3300 °C). An oxidative ring fusion aromatization step (240 °C, air) prior to pyrolysis enhanced the degree of graphitization. The resulting graphitic aerogels were characterized by XRD, Raman spectroscopy, TGA, TEM, SEM, XPS, and N₂ sorption porosimetry. Compared to …

Enhancing Management Of Transportation Projects: Integration Factors For Using Smart Contracts, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The US Department of Transportation (USDOT) delivers a wide range of infrastructure projects, backed by a fiscal year 2023 budget exceeding $100 billion. These projects face mounting pressures to meet performance, accountability, and delivery standards, driven by their dependence on public funding and their operational complexity. Transportation infrastructure presents sector-specific challenges - such as time-sensitive user disruptions, multiparty coordination, and asset intersection risks - that demand more robust, automated, and transparent project delivery mechanisms. Blockchain-enabled smart contracts have emerged as a promising solution to address these operational pain points through real-time automation, immutable data records, and decentralized transaction processing. However, …

Learning-Assisted Schedulability Analysis: Opportunities And Limitations, Sanjoy Baruah, Pontus Ekberg, Marion Sudvarg

Computer Science Faculty Research & Creative Works

We present the first (to our knowledge) Deep-Learning based framework for real-time schedulability-analysis that guarantees to never incorrectly mis-classify an unschedulable system as being schedulable, and is hence suitable for use in safety-critical scenarios. We relate applicability of this framework to well-understood concepts in computational complexity theory: membership in the complexity class NP. We apply the framework upon the widely-studied schedulability analysis problems of determining whether a given constrained-deadline sporadic task system is schedulable on a preemptive uniprocessor under both Deadline-Monotonic and EDF scheduling. As a proof-of-concept, we implement our framework for Deadline-Monotonic scheduling, and demonstrate that it has a …

Effect Of Powder Recycling On Powder Characteristics And Mechanical Properties Of Materials Produced By Laser Powder Bed Fusion (Lpbf): A Review, Mihiretu Ganta, Marta Kurek, Arezoo Emdadi, Tadeusz Łagoda, Marek Pagáč

Materials Science and Engineering Faculty Research & Creative Works

As the Laser powder bed fusion (LPBF) process advances toward industrial-scale production, the sustainability of metal powder feedstocks has become a focal point of research. The powder recycling approach, while environmentally and economically favorable, results in a series of physicochemical variations that could compromise the part quality. The resulting variation in powder characteristics with powder recycling could affect the powder layer density and melt pool dynamics, resulting in defect formation and hindering the structural integrity of LPBFed parts. These alterations pose significant constraints to mechanical performance, particularly in fatigue-sensitive applications where even minor imperfections can substantially reduce service life. The …

Tuning A Magnetic Energy Scale With Pressure And Field In Ute2, Hyunsoo Kim, I. Lin Liu, Wen Chen Lin, Yun Suk Eo, Sheng Ran, Nicholas P. Butch, Johnpierre Paglione

Physics Faculty Research & Creative Works

When a fragile ordered state is suppressed to zero temperature, a quantum phase transition occurs, which is often marked by the appearance of unconventional superconductivity. While the quantum critical point can be hidden, the influence of the quantum criticality extends to fairly high temperatures, manifesting non-Fermi liquid behavior in a wide range of the field-temperature-pressure phase space. Here, we report the tuning of a magnetic energy scale in the heavy-fermion superconductor UTe₂, previously identified with a peak in the c-axis electrical transport temperature dependence, using applied hydrostatic pressures and a-axis-oriented magnetic fields as complementary (and opposing) tuning parameters: …

Applications Of Machine Learning In Gravitational-Wave Research With Current Interferometric Detectors, Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger

Physics Faculty Research & Creative Works

This article provides an overview of the current state of machine learning in gravitational-wave research with interferometric detectors. Such applications are often still in their early days but have reached sufficient popularity to warrant an assessment of their impact across various domains, including detector studies, noise and signal simulations, and the detection and interpretation of astrophysical signals. In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. Algorithms could predict and help in mitigating environmental disturbances in real time, ensuring detectors operate at peak performance. Furthermore, machine-learning tools for characterizing and cleaning …

Time-Resolved 3d Momentum Spectroscopy In Continuous Wave Atomic Photoionization Experiments, K. L. Romans, B. P. Acharya, A. H.N.C.De Silva, K. Foster, O. Russ, Daniel Fischer

Physics Faculty Research & Creative Works

An experimental continuous-wave (cw) pump-probe scheme is demonstrated by investigating the population and photoionization dynamics of an atomic system. In particular, 6Li atoms are initially prepared in optically pumped 22S1/2 and 22P3/2 states before being excited via multi-photon absorption from a tunable femtosecond laser. The subsequent cascade back to the ground state is analyzed by ionizing the atoms in the field of a cw optical dipole trap laser. Conventional spectroscopic methods, such as standard cold-target recoil ion momentum spectroscopy or velocity map imaging, cannot provide simultaneous momentum and time-resolved information on an event-by-event basis for the system investigated here. The …

Investigating The Correlation And Synergy Of Artificial Intelligence Techniques, Construction Technologies, And Their Key Benefits, Fareed Salih, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Despite its reputation as one of the least digitized sectors, the construction industry increasingly adopts artificial intelligence (AI) and construction technologies. However, previous research has not adequately explored the benefits of AI techniques and construction technologies nor the correlations between them. This study aims to fill this knowledge gap. To this end, the authors used a multistep research methodology. First, a systematic literature review of studies published between 1985 and 2022 was conducted to identify AI techniques and construction technologies. Second, content and frequency analysis were performed to determine the benefits associated with AI and technology adoption. Finally, a survey …

Friction And Texture Evaluation Of Asphalt-Based Binders As Alternatives To Epoxy-Based High-Friction Surface Treatments, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High-friction surface treatment (HFST) is a safety-focused pavement treatment that restores and maintains pavement friction to reduce road accidents. Traditional epoxy-based HFSTs, while widely used, face challenges such as high costs, potential compatibility issues with the substrate pavement, and long-term durability under specific conditions. This study investigates asphalt-based alternative HFST, which is compatible with various pavement types and cost-effective and versatile solutions for a wider range of pavement applications. Performance and friction testing, including the British pendulum test, British wheel test, and dynamic friction test, were performed to examine the coefficient of friction (COF) before and after polishing with a …

Nonlinear Flow Structures From The Interaction Of Internal Waves With Topography, Matthew R. Klema, S. Karan Venayagamoorthy

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This paper presents numerical simulations of the interaction of first-mode internal waves with a topographic edge at the intermediate scale, O (100) m, with a focus on the evolution of flow structures. Flow structure variation and evolution is explored through direct modifications to the amplitude of the internal wave interacting with topographic features of varying wave-topographic slope (g/s), height of the topography to the total domain depth (ht/d), and the wave Froude number (Fr = U0/cph), where g is the internal wave slope, s is the topographic slope, ht is the height of the topography, d is the simulation depth, …

The Equity Implications Of Pecuniary Externalities On An Electric Grid, Charles Sims, Gasser G. Ali, J. Scott Holladay, Tim Roberson, Chien Fei Chen, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The adoption of rooftop photovoltaic (PV) systems can create upward pressure on retail electricity rates as utilities are forced to spread their fixed costs of generation and transmission across a smaller customer base. Since high-income households are more likely to purchase PV systems, low-income households may be disproportionately impacted by these rate increases. Using a novel combination of agent-based computational economic modeling and a choice experiment of rooftop solar adoption, we show how this pecuniary externality between low- and high-income customers increases low-income electricity bills by 10% in an area with some of the highest poverty rates in the United …

Evaluating Crumb Rubber Modified (Crm) Asphalt As A Sustainable Binder Alternative For High-Friction Surface Treatments, Abdallah Aboelela, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High-friction surface treatments (HFSTs) are widely applied to improve pavement safety by enhancing long-term skid resistance. Although epoxy resins are commonly used due to their strength and durability, their high cost, susceptibility to delamination, incompatibility with substrates of flexible pavements, and adverse environmental concerns limit their long-term performance. This study presents crumb rubber modified (CRM) asphalt as a sustainable alternative binder for HFST applications. CRM binders offer high performance and compatibility with existing pavement surfaces, cost effectiveness and reduced environmental impacts as compared to epoxy binders. In addition, the binder development utilizes enhanced recycling technologies for interacting with used tire …

Data Center Composite Load Model Parameters’ Tuning, Mohammed Sleiman, Amirreza Sahami, Oluwatimilehin Adeosun, Nathaniel Rice, Katelyn Vance

Electrical and Computer Engineering Faculty Research & Creative Works

The vast expansion of data center campuses has created concentrated and highly dynamic electrical loads that challenge traditional transmission system planning and protection studies. This paper presents a novel approach to model the load of data centers and validate their dynamic performance in a composite-load-model (CMLD) framework.

The data center has three major modules: a static element representing the static devices and busway impedance; an electronic-based element constituting power converters such as rectifiers and inverters, associated power supplies, and a motor-based element encompassing the induction nature of chillers, fans and pumps. Each module represented equivalent algebraic and differential equations depicting …

Data Driven Design Of Ultra High Performance Concrete Prospects And Application, Bryan K. Aylas-Paredes, Taihao Han, Advaith Neithalath, Jie Huang, Ashutosh Goel, Aditya Kumar, Narayanan Neithalath

Electrical and Computer Engineering Faculty Research & Creative Works

Ultra-high-performance concrete (UHPC) is a specialized class of cementitious composites that is increasingly used in various applications, including bridge decks, connections between precast components, piers, columns, overlays, and the repair and strengthening of bridge elements. The mechanical and durability properties of UHPC are significantly influenced by factors such as low water-to-binder ratios, the inclusion of supplementary cementitious materials (SCMs), and fiber reinforcement. Machine learning (ML) has been employed to predict the performance of UHPC and optimize its mixture designs by using various raw materials. This study first provides a comprehensive review of ML applications in UHPC, focusing on predicting workability, …

Fluorosilane-Induced Softening And Collapse Of Micropillar Arrays, Gabriela Moreira Lana, Maja Fehlberg, Petra Herbeck-Engel, Gisela Heppe, Raimund Schlüßler, Torsten Jähnke, Eduard Arzt, Roland Bennewitz

Chemical and Biochemical Engineering Faculty Research & Creative Works

Replica molding is a widely used technique for the fabrication of polymer microstructures. As structural dimensions decrease, anti-stick surface treatment of the mold becomes increasingly critical to ensure clean demolding and preserve structural integrity. We fabricated arrays of micropillars with 20 µm diameter and 60 µm height using medical-grade polydimethylsiloxane (PDMS), MDX4-4210, and observed a high fraction of collapsed pillars for the first molding after fluorosilanization of the mold to reduce sticking. To address this issue, we systematically investigated the surface treatment protocol for the molds, made from the PDMS Sylgard 184. We provide results from complementary measurement methods, to …

Simulating Realistic Lyman-𝛼 Emitters Including The Effect Of Radiative Transfer, Hasti Khoraminezhad, Shun Saito, Max Gronke, Chris Byrohl

Research Data

We present an empirical yet physically motivated simulation of realistic Lyman-𝛼 emitters (LAEs) at 𝑧 ∼ 2 − 3, crucial for ongoing and forthcoming cosmological LAE surveys. We combine an empirical UniverseMachine galaxy-halo model with a simple spherical expanding shell model for the Lyman-𝛼 radiative transfer, calibrating only three free parameters to simultaneously reproduce the observed Lyman-𝛼 luminosity function and the angular clustering. Our LAE model is further supported by its consistency with other observables such as the Lyman-𝛼 equivalent width distribution, the Lyman-𝛼 escape fraction as a function of stellar mass and dust reddening, and the systemic velocity offsets. …

Synergistic Doping And Coating Strategy For Boosting Na0.7mno2 Cathode Performance In Sodium-Ion Batteries, Ahmad Helaley, Han Yu, Manashi Nath, Xinhua Liang

Chemistry Faculty Research & Creative Works

Advancing sodium-ion battery (SIB) technology requires novel approaches to optimize cathode materials for improved electrochemical performance. In this study, we employ atomic layer deposition (ALD) to precisely modify the surface of P2-type Na_0.7MnO₂ cathodes with different coating materials including ZnO, NiO, and Al₂O₃, followed by post-annealing at 750°C for 10 hours. The strategic combination of ALD and thermal treatment can achieve thin film coating on particle surface and promote element doping into the near-surface lattice, as confirmed by electron energy loss spectroscopy (EELS) analysis. The incorporation of Zn, Al, and Ni results in …

Unraveling Hydration- And Temperature-Induced Structural Transformations Of Linear Poly(Ethylenimine) Using Raman Microscopy And Numerical Unmixing, Miharu Koh, Jay P. Kitt, Andrew D. Pendergast, Joel M. Harris, Shelley D. Minteer, Carol Korzeniewski

Chemistry Faculty Research & Creative Works

Linear poly(ethylenimine) (LPEI) is a hydration-sensitive polymer of interest for its breadth of application in areas that include medicine, energy, and materials science. To facilitate advances, this work demonstrates in situ Raman microscopy and self-modeling curve resolution (SMCR) analysis as an approach for investigating changes in LPEI structure during melting and crystallization under controlled heating and cooling conditions. With focus on neutral (freebase) LPEI, SMCR analysis of Raman data sets showed that the melting transition of anhydrous LPEI was well described by a pair of spectral vectors representing anhydrous crystalline and amorphous states. However, the transition from the melted to …

Connected-Component Labeling Using Hls For High-Energy Particle Physics Instruments, Nick Song, Marion Sudvarg, Roger Chamberlain

Computer Science Faculty Research & Creative Works

Many instruments used in high-energy particle physics observations, e.g., gamma-ray telescopes, use FPGAs for front-end signal processing of raw sensor data. The use of high-level synthesis (HLS) to express the signal processing algorithms has the potential to significantly reduce development time for new instruments of this type. We describe our experience with one of the computational stages in the signal processing pipeline, island detection, exploring its implementation across multiple configurations: 1D versus 2D islands, and 4-way versus 8-way connected-component labeling (CCL) in the 2D configuration. We report resource usage and performance for both configurations of 2D island detection, including the …

Modular Architecture For High-Performance And Low Overhead Data Transfers, Rasman Mubtasim Swargo, Engin Arslan, Md Arifuzzaman

Computer Science Faculty Research & Creative Works

High-performance applications necessitate rapid and dependable transfer of massive datasets across geographically dispersed locations. Traditional file transfer tools often suffer from resource underutilization and instability due to fixed configurations or monolithic optimization methods. We propose AutoMDT, a novel Modular Data Transfer Architecture, to address these issues by employing a deep reinforcement learning agent to simultaneously optimize concurrency levels for read, network, and write operations. This solution incorporates a lightweight network-system simulator, enabling offline training of a Proximal Policy Optimization (PPO) agent in approximately 45 minutes on average, thereby overcoming the impracticality of lengthy online training in production networks. AutoMDT's modular …

Modeling And Optimizing Real-Time Telescope Interaction For Multi-Wavelength Observation Of Gamma-Ray Bursts, Ye Htet, Marion Sudvarg, Honghao Yang, Jeremy Buhler, Roger Chamberlain, James Buckley

Computer Science Faculty Research & Creative Works

Multi-wavelength observation of gamma-ray bursts (GRBs) requires real-time interaction among multiple telescopes. A gamma-ray telescope detects and localizes a GRB in the sky and must then communicate with an optical telescope to direct the latter toward the GRB as quickly as possible. We previously developed software for ADAPT, a suborbital gamma-ray telescope, to localize GRBs in real time, on a timescale shorter than that of the GRB itself. This work therefore studies progressive localization, in which ADAPT computes a series of increasingly accurate location estimates during a GRB to enable a partner instrument to more rapidly find it. We describe …

Proactllm: Proactive Conversational Information Seeking With Large Language Models, Shubham Chatterjee, Xi Wang, Shuo Zhang, Sajad Ebrahimi, Zhaochun Ren, Debasis Ganguly, Gareth Jones, Emine Arrousse, Hamed Zamani

Computer Science Faculty Research & Creative Works

Large Language Models (LLMs) have transformed information access by enabling human-like text understanding and generation. This workshop explores the next step for conversational AI: building proactive information-seeking assistants that go beyond reactive question answering. We aim to investigate how LLMs can anticipate user needs, model complex context, support mixed-initiative interactions, integrate retrieval and external tools, personalize responses, adapt through feedback, and ensure fairness, transparency, and cognitive grounding. Bringing together experts from NLP, IR, HCI, and cognitive science, the workshop will serve as a timely forum for advancing intelligent, proactive dialogue systems. It will also foster interdisciplinary collaboration.

Elucidating The Effects Of Water Activity On The Hydration Kinetics And Thermodynamics Of Ye’Elimite–Calcium Sulfate Hydrate Systems, Godwin I. Ogbuehi, Rupack R. Halder, Aditya Kumar, Gaurav Sant, Monday U. Okoronkwo

Materials Science and Engineering Faculty Research & Creative Works

Relative humidity and water activity (aH) reductions have been known to suppress the hydration of anhydrous cement clinker phases. However, the relationship between ye'elimite (C4A3$) hydration kinetics and water activity remain unclear. This study employs experimental and thermodynamic modeling approaches to investigate the influence of water activity on ye'elimite hydration in the "C4A3$ + water", and "C4A3$ + gypsum + water" systems. Experimental findings indicate that as water activity decreases, C4A3$ hydration diminishes until the reaction is brought to a halt at a threshold aH. The critical aHand corresponding solubility constant of C4A3$ (KC4A3S¯) estimated from thermodynamic analysis are 0.46 …