Digital Commons Network^™

Evaluating Fine-Scale Air-Quality Heterogeneity Using A Low-Cost Multipollutant Sensor Network In Twin Cities, Minnesota, Varuni Abhayaratne, Weixing Hao, Chen Ye, Anjana Yatawara, Philip K. Hopke, Jiayu Li, Yang Wang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

There is growing interest and effort in deploying low-cost sensors (LCSs) to understand fine-scale spatiotemporal heterogeneity of ambient air pollutants in urban areas. The Assessing Urban Air Quality project conducted by the Minnesota Pollution Control Agency deployed 45 low-cost air-quality monitors (AQMesh, Environmental Instruments Ltd.) in the Minneapolis/St. Paul metropolitan area network. Hourly averaged pollutant concentrations or mixing ratios for carbon monoxide (CO), ozone (O₃), nitrogen dioxide (NO₂), nitric oxide (NO), and sulfur dioxide (SO2), as well as particulate matter (PM), including PM1, PM2.5, and PM10, were obtained. The network data from June 2019 to June …

Quantitative Phase-Field Modeling Of Nonequilibrium Microstructural Evolution In Rapid Solidification For Additive Manufacturing, Leiji Li, Fei Xiao, Ying Zhou, Xiaorong Cai, Chongfeng Zhang, Jinzhong Gao, Xiaopeng Shen, Tianchi Zhu, Sihan Wang, Yijia Gu, Xuejun Jin

Materials Science and Engineering Faculty Research & Creative Works

Fusion-based metal additive manufacturing (AM) relies on layer-by-layer deposition and rapid solidification, where the material transitions swiftly from liquid to solid. A key phenomenon during this process is solute trapping, a nonequilibrium effect governed by a velocity-dependent partition coefficient, which critically influences microstructure kinetics, morphology, and phase formation. In this study, we employ a recently proposed quantitative phase field (PF) model to systematically explore solute trapping, solute drag, and their impacts on pattern formation during rapid solidification at AM-relevant velocities, in both one and two dimensions. Our simulations reveal a growth mode transition from planar to cellular to dendritic, and …

Sex-Based Effects Of Shock Energy Exposure In Warfighters, Melissa Sutter, Catherine Johnson

Mining Engineering Faculty Research & Creative Works

Personal armors were initially designed to fit against the male torso, as men previously filled roles requiring them, thus not made to accommodate the female anatomy. As a result, armor worn by female warfighters tends to have non-form fit in the waist, armpit, bust, and collarbone areas, causing reduced coverage. Shifting, riding up, air gaps, breathing difficulty, and physical discomfort have also been observed. Although this has been documented, the impact on the armor's protective capabilities has not been well studied. To address this, this study compared the protective capabilities of unisex armor for male and female warfighters from shock …

Indirect Carbonation Of Fbc Ash For Sustainable Production Of Caco3 And Reactive Pozzolanic Residues, Suhawn Ju, Heejung Jun, Seongho Han, Minseok Kim, Soohyun Song, Mingi Cho, Sukhoon Pyo, Jinyoung Yoon

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study investigates the potential of indirect carbonation for CO₂ sequestration and high-purity CaCO₃ production using fluidized bed combustion (FBC) fly ash (FFA) and bottom ash (FBA). XRF and XRD analyses revealed high reactive CaO contents derived from lime, portlandite, and anhydrite. Calcium extraction using 1- mol NH₄Cl achieved markedly higher efficiency than deionized (DI) water, yielding up to 17,586 mg/L of Ca²⁺ and producing 10.2 wt.% and 8.4 wt.% CaCO₃ from FFA and FBA, respectively, with CO₂ capture capacities of 45.0 and 36.8 kg per ton of ash. The precipitated CaCO₃ exhibited …

Exploring Scms And Fibers For Structural Build-Up In 3d Printing Using Penetration Test, Shiva Kumar Goud Kasani

Miners Solving for Tomorrow Research Conference

Additive manufacturing with cementitious materials advances rapidly, but predicting structural build-up is critical for 3D printed structure buildability. Various supplementary cementitious materials (SCMs) and fibers are commonly used to enhance structural build-up in 3D printing. Evaluating their effects is necessary for successful printing. In this research, this effect is studied for common SCMs, including fly ash and silica fume, and fibers including polypropylene (0.375% and 0.75% by volume), steel (0.75% and 1.5% by volume), and hemp fibers (0.375% and 0.75% by volume). The Structural build-up was quantified through continuous static yield stress measurements (via vane rheometer, penetration, and slump) during …

Synthesis And Hydrothermal Evaluation Of Poly(Styrene Phosphonate) For Conformance Control In Geothermal Reservoirs, Sara Mccauley

Miners Solving for Tomorrow Research Conference

As atmospheric carbon dioxide levels continue to rise, geothermal energy has emerged as a promising energy alternative to fossil fuels. A barrier to widespread implementation and energy production efficiency is macro-heterogeneity of the rock matrix. Cracks, void spaces, and flow conduits divert fluid flow away from unswept portions of the geothermal reservoir and can cause cooling of the reservoir. Flow heterogeneity has been treated in oil reservoirs by injecting hydrogel particles that travel preferentially to ultra-high permeability zones and selectively block fluid flow in these regions. We are applying polymer hydrogels that withstand hydrothermal conditions of 225 up to 275°C …

Adaptive Parallel Downloader For Large Genomic Datasets, Rasman Mubtasim Swargo

Miners Solving for Tomorrow Research Conference

Modern next-generation sequencing (NGS) projects routinely generate terabytes of data that researchers download from public repositories such as SRA and ENA. Existing download tools typically employ static concurrency settings, leading to inefficient bandwidth utilization and prolonged download times under dynamic network conditions. We introduce FastBioDL, a parallel downloader for large biological datasets with an adaptive concurrency controller. FastBioDL frames downloading as an online optimization problem, using a utility function and gradient descent to adjust the number of concurrent socket streams during runtime. This approach maximizes throughput while minimizing resource overhead. Evaluations on public genomic datasets show that FastBioDL achieves up …

Dispersive Shock And Rogue Waves In Two-Dimensional Quantum Droplets, Farhana Bristy

Miners Solving for Tomorrow Research Conference

Quantum droplets, are liquid type configurations stabilized by the balance between attractive mean-field interactions and repulsive quantum fluctuations. They provide highly flexible platforms for the quantum simulation of hydrodynamic phenomena using ultracold gases. Here, we explore the nonlinear quantum dynamics of two-dimensional quantum droplets under Riemann initial conditions. The steepness of the latter facilitates the emergence of radially symmetric dispersive shock waves (DSWs) when quantum fluctuations dominate. In particular, the ensuing DSWs travel from the potential edges toward the center where they collide and through their interference high amplitude spatially localized rogue wave structures emerge. In contrast, tuning the interactions …

Challenges And Best Practices Of Regional Innovation Ecosystems, Mahnaz Asgari Sooran

Miners Solving for Tomorrow Research Conference

Many places around the world are developing regional innovation ecosystems to spur regional economic. Many innovation ecosystems fail or barely maintain their initial momentum after a few years. In this paper, we identified challenges and best practices facing innovation ecosystems interviews with the innovation ecosystem stakeholders. We employed the MIT REAP (Regional Entrepreneurship Acceleration Program) model to categorize the five main stakeholders of the innovation ecosystem: entrepreneurs, universities, industry, risk capital, and government. Our initial results indicated the following: (a) Access to capital and talented workforce; (b) Stakeholder discovery process is one of the critical areas to understand the basic …

Simulating Thermal Diffusion Through Image-Derived Microstructures Of Ceramic Matrix Composites, Matik Heskin

Miners Solving for Tomorrow Research Conference

Thermal energy transport in materials can be effectively modeled using finite element software such as COMSOL. Experimentally measured or NIST–JANAF thermal conductivity data can be used to represent material behavior within these simulations. For heterogeneous or composite materials, effective properties are often approximated using rule-of-mixtures calculations. However, this overlooks the nuanced effects caused by complex microstructural geometry. To address this limitation, imaging and coding tools such as MATLAB can be used to process scanning electron microscopy (SEM) images. By thresholding the images to distinguish constituent materials, a representative mesh can be generated and imported into an FEM program. This approach …

Distributed Control Plane For Cross-Silo Federated Learning, Rabin Pandey

Miners Solving for Tomorrow Research Conference

Cross-silo federated learning (FL) trains shared models across geographically distributed institutions without centralizing raw data, but its reliance on wide-area networks makes round completion time highly sensitive to heterogeneous link conditions, congestion, and straggler clients. Existing SDN-based FL frameworks address this through centralized traffic engineering, an approach that breaks down when silos span independent administrative domains where no single entity can maintain complete, timely network knowledge. We replace the centralized control plane with a fully distributed overlay in which each silo gateway operates as an equal peer, continuously probing local links, exchanging EWMA-smoothed metrics via bounded gossip, and computing least-cost …

Transition Metal Chalcogenide As Multifunctional Biosenser To Detect Neurochemicals, Amitav Sen

Miners Solving for Tomorrow Research Conference

The development of highly sensitive real-time sensing platforms for selectively detecting dopamine (DA) and norepinephrine (NE) is of significant clinical importance since these are closely associated with several neurodegenerative disorders. Herein, we report copper telluride (Cu₂Te) nanostructure as a bifunctional electrocatalyst for the simultaneous detection of dopamine and norepinephrine. Cu₂Te exhibits excellent electrocatalytic activity toward both DA and NE oxidation, as demonstrated by detailed electrochemical measurements. High sensitivities of 24 and 40 µA cm⁻² µM⁻¹ for DA and NE, respectively, were obtained with a wide linear detection range of 10–200 nM and low limit of detection (LOD), 31 nM for …

Human Intention Prediction Using Cnn And Lstm Networks In Physical Human–Robot Interactions, Khosro Ghorbani Zadeh

Miners Solving for Tomorrow Research Conference

Advances in robotics and artificial intelligence have increased expectations for interactive robots in eldercare and assistive applications. A key challenge in creating safe and effective systems is accurately recognizing human intent and translating it into meaningful commands for robots to follow. Traditional physics-based models often fail to fully represent human force interactions due to their dynamic nature, while neural networks provide a promising alternative for predicting force-movement intentions. Multi-layer perceptrons (MLPs) show potential, however, they struggle with temporal dependencies and generalization. Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs) help address these limitations. This study compares these architectures …

Toward Sustainable 3d Printable Cementitious Materials: Low-Carbon Design With Fiber Reinforcement, Nima Mahmoudzadeh Vaziri

Miners Solving for Tomorrow Research Conference

3D printing of cementitious materials, as an emerging construction technology, faces challenges in both mechanical performance and sustainability. Conventional mixture designs rely on high cement contents, leading to increased CO2 emissions, while printed elements often exhibit brittle behavior with limited crack resistance and reduced post-cracking performance. This study investigates the development of low-carbon 3D printed cementitious composites using environmentally friendly supplementary cementitious materials (SCMs) and fillers, combined with fiber reinforcement to enhance mechanical performance. Locally available SCMs and fillers were incorporated to significantly reduce cement content (>40%) and improve sustainability. Fiber reinforcement was introduced to mitigate brittleness and enhance …

Ai-Driven Frameworks For Mitigating Rockfall Hazards, Unstable Ground Condition And Improving Safety In Underground Mine Through Thermal Imaging, Akhrorbek Narmatov

Miners Solving for Tomorrow Research Conference

Scaling, the removal of loose rocks from excavation walls to prevent rockfalls is a critical safety procedure in underground mining operations. Approximately a quarter of fatal mining accidents are due to rockfalls. Detecting unstable rocks during scaling and assessing ground stability remain challenging due to limited visibility, dust, and environmental conditions.

Excavation disturbs the in-situ stress state, causing stress redistribution, fracture propagation, and the formation of discontinuities that lead to loose rock blocks. Ventilation airflow affects heat transfer at exposed surfaces, amplifying temperature contrasts between intact rock and fractured blocks associated with instability.

Current practices rely on manual inspection, requiring …

Robust Federated Learning With Strategic Adversaries, Manoj Twarakavi

Miners Solving for Tomorrow Research Conference

Federated Learning (FL) leverages the intelligence of untrusted distributed devices through collaborative training. This makes the training process susceptible to malicious behavior. Existing defense mechanisms largely consider an adversary who attacks a proactive FL server without any adaptability. However, they overlook the presence of a strategic adversary. To address this challenge, our work proposes a Robust Game-theoretic framework where the adversary is both strategic and is equipped with the capability of performing large-scale poisoning attacks.

Scenario-Based Pareto Analysis For Multi-Objective Optimization Of Process Parameters To Improve Life Cycle Impacts: Case Study Of Ge Production, Dennis Dadzie

Miners Solving for Tomorrow Research Conference

Growing demand for critical minerals increases the need for clear evidence on the environmental burdens of their production. Life‑cycle assessment (LCA) quantifies impacts, but it does not by itself show how to navigate competing environmental performance improvement goals. We examine 63 process configurations for single‑crystal germanium made via chlorinated distillation using five indicators: global warming potential (GWP), water consumption (WC), fine particulate matter (FPM), terrestrial acidification (TA), and cumulative energy demand (CED). Across scenarios, WC is negatively correlated with GWP, weakly related to FPM, TA, and CED, while the other four indicators are strongly positively correlated. Pareto analysis highlights a …

Assessing Radon And Radon Progeny Deposition On Simulated Lung Filter System: Effects Of Cigarette And E-Cigarette Use Based On The Icrp Model, Manuela Isabel Arenas Alvarez

Miners Solving for Tomorrow Research Conference

This project investigates the potential interaction between radon exposure and e-cigarette aerosols, focusing on how radon progeny deposit in the lungs under combined conditions. An experimental system was developed to simulate regional lung deposition based on the International Commission on Radiological Protection (ICRP) model. The setup uses a filter-based design and a custom modular atomizer to generate stable aerosols, with four commercial plastic filters evaluated. Initial results demonstrate reproducible filtration behavior and a total deposition pattern matching ICRP predictions within 21% error. Ongoing work aims to improve agreement with regional deposition curves and enable combined radon–aerosol exposure experiments. This platform …

Assessing The Effects Of Scale-Dependent Representation Of River Networks On Hydrologic Prediction, Hari Dhital

Miners Solving for Tomorrow Research Conference

Accurate hydrologic prediction at relevant spatial scales is essential for flood risk management. This study explores how spatial scale affects model parameters and simulation outcomes in the Hillslope Link Model (HLM). This was motivated by HLM implementation within the Next Generation Water Resources Modeling (NextGen) framework for the U.S. National Water Model. Since NextGen alters HLM's spatial scale from hillslopes to catchments, we assess how this change affects runoff generation and routing. We implement HLM at both scales using identical, predetermined parameters without calibration to isolate spatial discretization effects. Using approximately ten years of precipitation and streamflow data from watersheds …

Evaluation Of National Water Model Long-Range Streamflow Forecasts In Missouri, Sujan Maharjan

Miners Solving for Tomorrow Research Conference

Long-range river stage forecasts are increasingly used to support barge scheduling along the Missouri and Mississippi River navigation corridor. The reliability of these forecasts over extended lead times remains uncertain, particularly in regulated systems influenced by upstream dam operations. This study evaluates the lead-time-dependent performance of National Water Model long-range forecasts at eleven U.S. Geological Survey stations from Rulo to Thebes during 2019–2024. Results show that forecast skill does not decline smoothly with time but exhibits station-specific dips at lead times corresponding to hydraulic travel from major control structures. These periods coincide withstage bias and dispersion, indicating elevated operational uncertainty. …

Evaluation Of Channel Routing Module In The Nextgen National Water Model, Md Saiduzzaman

Miners Solving for Tomorrow Research Conference

The Next Generation Water Resources Modeling (NextGen) framework has a modular structure that enables the integration of multiple hydrologic models with channel routing processes. Within NextGen, the T-Route model performs channel routing using vector-based river networks and supports a hybrid routing approach within a single watershed. This study evaluates the hydraulic diffusive wave routing method implemented in T-Route and compares its performance with the operational Muskingum-Cunge routing used in the National Water Model. The primary objective is to assess the operational capability of streamflow data assimilation across different routing methods using an extensive network of streamflow observations. The routing models …

Controlled Gelation Of Co₂-Resistant Polymer Systems For Improved Conformance In Co₂-Eor, Maryam Sharifi Paroushi

Miners Solving for Tomorrow Research Conference

This presentation introduces a CO₂-resistant hydrogel developed to control fluid movement and improve CO₂ injection performance in subsurface reservoirs for Enhanced Oil Recovery (EOR) and Carbon Capture and Storage (CCS). Conventional polymer gels often lose strength in CO₂-rich environments, resulting in weak plugging, early breakdown, and ineffective flow control. To address this limitation, a sulfonated HPAM-based gel system crosslinked with chromium was developed. The effects of polymer concentration, molecular weight, crosslinker ratio, ionic strength, and pH were investigated to better understand gelation behavior and performance. The formulation exhibited controlled gelation, strong resistance to temperature and CO₂, and minimal shrinkage over …

Empirical Evaluation Of Policy-Based Reinforcement Learning For Dynamic Service Control In An M/M/1 Queue, Joseph Walton

Miners Solving for Tomorrow Research Conference

While reinforcement learning has been increasingly applied to stochastic control, limited work examines policy-based methods in queuing environments modeled as semi-Markov decision processes (SMDP). This study investigates how policy-based reinforcement learning (RL) algorithms perform when applied to service rate control in an M/M/1 queue, a common queuing model for manufacturing and service systems. The problem is formulated as an SMDP in which decisions occur at each new service, allowing an agent to select different service rates from a finite set of speeds, aiming to minimize an objective function that manages system congestion and energy costs. Three policy-based reinforcement learning algorithms, …

Structural Analysis On Iron Phosphate Glasses After Dechlorination Of Mixed Chloride Waste Forms, Lucas Greiner

Miners Solving for Tomorrow Research Conference

Molten salt reactors (MSRs) require durable waste forms for immobilizing halide-rich salts. This study examines iron phosphate glasses derived from a simple salt mixture (SSM), focusing on the effect of Fe₂O₃ additions (2.5–10 wt%) on structure and phase stability. Intermediates were processed at 300–600 °C and vitrified at 1050 °C. Raman spectroscopy and HPLC show that increasing iron content depolymerizes the phosphate network, shifting from Q² toward Q¹ species and reducing chain length. XRD confirms amorphous behavior for ≤7.5 wt% Fe₂O₃, while 10 wt% shows crystallization, with KFeP₂O₇ observed in samples processed at 400 °C. Despite reduced connectivity, iron enhances …

Preventive Maintenance Scheduling Using Artificial Intelligence And Decision Support Agent, Samiksha Aryal

Miners Solving for Tomorrow Research Conference

Preventive Maintenance models have traditionally relied on a time-based maintenance model, which uses fixed statistical distribution to represent the time-to-failure (TTF). The requirement of data-driven models and automated decision-making systems have become essential for modern manufacturing systems. The use of fixed statistical distribution limits the ability of existing models in producing solutions in real-time. Our model overcomes these limitations by implementing an empirical distribution to represent TTF. The empirical distribution is generated using a neural network which eliminates noise from the raw maintenance log. Renewal Reward Theorem (RRT) is implemented to efficiently provide maintenance threshold in real time. The use …

Robustness Of Fuzzy Artmap To Adversarial Attacks And Progressive Adversarial Training For Streaming Learning, Shane Cairns

Miners Solving for Tomorrow Research Conference

Incremental learners deployed on streaming data must remain robust to evolving adversarial perturbations, yet most adversarial-robustness studies assume offline multi-epoch training with repeated access to historical data. We investigate adversarial robustness in Fuzzy ARTMAP, a prototype-based Adaptive Resonance Theory model that supports single-pass learning without replay. We propose WB-Softmax, a differentiable relaxation that aggregates category-level activations into class-level scores for gradient-based attacks. WB-Softmax PGD achieves 89–100% attack success on vanilla models, exceeding transfer and query-based baselines. We then study adversarial training under true streaming constraints by comparing offline versus online adversarial example generation and standard versus selective updates. Offline adversarial …

Triple Active Bridge Implementation And Control, Nehemiah Milton

Miners Solving for Tomorrow Research Conference

The Triple Active Bridge (TAB) is a three-port power converter that allows power flow in both directions with galvanic isolation. This has a wide range of applications, like high-frequency DC-DC conversion, electric vehicles, microgrids and renewable energy systems. To control the TAB during operation, two phase shift parameters between the bridges are adjusted. In this presentation, I will showcase the software and simulation optimizations which extend previous work by reproducing hardware results which align with simulations. I will also go over the knowledge I’ve gained and the skills acquired through this project.

Vortex Generation In Dipolar Supersolids, Jacob Harl

Miners Solving for Tomorrow Research Conference

Ultracold atomic gases offer highly tunable platforms for exploring complex quantum many-body phenomena. In addition, dipolar quantum gases of magnetic atoms featuring long-range anisotropic interactions are exquisite systems for realizing exotic phases-of-matter in an experimentally controlled way. A prototypical example is the supersolid state which simultaneously exhibits frictionless flow of superfuids and crystalline density modulation of solids. In this realm, we investigate the dynamical generation of vortex topological defects by imprinting a suitable phase jump in quasi-two-dimensional dipolar supersolids. This protocol enables the nucleation of a dark soliton which consecutively becomes unstable via the eponymous snake instability due to its …

The Effects Of Preventing Dephosphorylation Of Lqg1 On Cytokinesis, Jenna Mueller

Miners Solving for Tomorrow Research Conference

Iqg1 plays crucial roles in cytokinesis, including the assembly, contraction, and disassembly of the actomyosin ring, as well as the coordination of contraction and septation. Given that cytokinesis must occur post-mitosis, Iqg1 is regulated by the cell cycle. This study explores hypotheses regarding Iqg1 regulation: it’s binding to action is negatively influenced by the cyclin-dependent kinase (CDK) Cdc28 and positively influenced by dephosphorylation via Cdc14. Newly developed yeast degron tagged strains allow for rapid depletion of specific proteins. Iqg1 mutations that alter serine to threonine, which allows phosphorylation but not dephosphorylation, in the degron strain allow testing of mutant phenotypes. …

Elucidating Complex H Behavior In Amorphous Oxide Semiconductors By Machine Learning, Lucas Ethington

Miners Solving for Tomorrow Research Conference

In this project, the disordered oxide structures will be mapped by a machine-learning algorithm (e.g., HDBSCAN) to identify characteristic behaviors of the proton across different material densities and defect types. This should help identify the under-coordinated, highly distorted, weakly-bonded, and dynamically unstable atoms to predict the most probable H locations. This fast and accurate prediction of energetically favorable H distribution will enable a reliable and fast screening of a large number of AOSs with variable cation and/or anion compositions. The approach will help find AOSs with suppressed numbers of M-OH defects (that form deep electron traps, limiting the number of …