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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Real-time gross actinide monitoring in extreme (10 6 :1) beta-gamma background fluid streams using mini-ATMFDs

Real-time, trace alpha activity monitoring in extreme mixed radiation fields is a well-known challenge in fission product-rich streams containing mixtures of beta-gamma-alpha radiation-emitting isotopes, arising due to the extreme 10 6 :1 ratio of background beta-gamma vs. alpha radiation activity levels. This paper presents results from a novel approach to addressing this challenge, based on Tensioned Metastable Fluid Detector (TMFD) sensing technology. An acoustically driven technique was developed and tested at Purdue University (using dissolved Rn-Po and U-chain alpha emitters), and validated (with dissolved Pu) at Savannah River National Laboratory for real-time monitoring of alpha activity in the 100–10,000 dpm/mL range.

Environmental Monitoring↗

Process Optimization and Real-Time Control of Synergistic Microalgae Cultivation and Wastewater Treatment (Final Technical Report)

The overarching goal of this work was to accelerate the commercialization of high productivity, mixed community microalgal treatment technologies for the synergistic treatment of wastewater and the production of biofuel feedstocks. This project addressed a critical barrier to the financial viability and energy efficiency of algal wastewater treatment: an inability to design and operate high-rate processes that reliably achieve target effluent qualities, areal productivities, and biochemical compositions (lipid, protein, carbohydrate content) despite fluctuations in wastewater composition, weather, and microbial communities. Key outcomes from this work include an optimized and controlled Advanced Biological Nutrient Recovery (ABNR) design as well as a suite of open-source tools that include a calibrated and validated algae process simulator in QSDsan and a novel low-cost, real-time microbial monitoring tool. These tools can be leveraged by other algal cultivation and wastewater treatment technology developers in future work.

09 BIOMASS FUELS↗

Ten questions concerning low-cost indoor air quality sensors: Perspectives from research and practice

Low-cost indoor air quality (IAQ) sensors are increasingly being used in homes and commercial and public buildings, driven by growing concerns about the impact of air on health, cognitive performance, and occupant wellbeing. These sensors offer a potentially transformative opportunity to increase spatial and temporal coverage of IAQ monitoring at a fraction of the cost of conventional reference instruments. However, their widespread use raises questions around accuracy, calibration, placement, data handling and interpretation, and integration into existing standards and workflows. This paper presents ten critical questions concerning the use of low-cost IAQ sensors in buildings, drawing on the latest empirical research, field deployments, and emerging practice. It discusses potential frameworks for deployment and evaluation, examines current sensor capabilities for measuring common pollutants, identifies methodological gaps in validation and uncertainty quantification, and outlines the extent to which existing IAQ standards can accommodate sensor-based evidence. The paper also explores how monitoring needs and deployment models vary by building type, the potential of real-time IAQ data to support building operations, and the ethical and legal implications of widespread sensor use. While significant challenges remain in ensuring data quality and building stakeholder trust, new applications are emerging through open data initiatives and advances in analytics and visualization. As the technology, science, and standards co-evolve, low-cost IAQ sensors are poised to become integral to routine building operation, building science, and environmental health research.

Parkinson, Thomas↗

Experimental Evaluation of a High-Performance Cold-Climate Heat Pump Using Tandem Vapor-Injection Compressors

A high-performance cold-climate heat pump (CCHP) was developed and experimentally validated through comprehensive laboratory and field testing. The system utilized two equal-size tandem vapor-injection (VI) compressors with an inter-stage flash tank to improve efficiency and capacity retention under subfreezing conditions. Laboratory testing was conducted on a 3-ton prototype in a controlled environmental chamber equipped with calibrated thermocouples, refrigerant-side mass flow and pressure transducers, and precision airflow measurement for energy balance verification. The prototype achieved heating coefficients of performance (COPs) of 4.4 at 47 °F, 3.1 at 17 °F, and 2.0 at –13 °F, while maintaining 88% of its rated heating capacity at –13°F. These results confirm strong low-temperature performance and indicate the potential for significant reductions in electric resistance backup use. A field prototype was installed and monitored in a residential building in Fairbanks, Alaska, during a heating season. Instrumentation included real-time power, temperature, and refrigerant state measurements to evaluate performance under dynamic outdoor conditions. The heat pump operated reliably down to –30 °F, delivering 75% of its rated heating capacity with a COP of 1.8, while maintaining stable operation, effective defrost control, and indoor comfort without auxiliary heating. The combined laboratory and field results demonstrate that the tandem VI compressor configuration provides a practical and energy-efficient approach for residential heat pumps designed for cold and very cold climate regions.

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗

AI-powered municipal solid waste management: a comprehensive review from generation to utilization

The accumulation of municipal solid waste (MSW) continues to rise due to burgeoning population, rapid global urbanization and economic growth, intensifying ecological concerns associated with landfills and greenhouse gas (GHG) emissions. Over the past 2 decades, global waste generation has surged by 50%, with one-third remaining uncollected and about 70% sent to landfills. This review examines the critical role of integrating emerging technologies, such as advanced sensors and artificial intelligence (AI), into end-to-end MSW management to alleviate landfill burdens. The suitability of various AI tools for different stages of MSW management is assessed, alongside the deployment of advanced sensors including hyperspectral cameras, computer vision systems, and internet of things (IoT) devices for material identification. Applications of genetic algorithms and reinforcement learning for optimizing collection routes, reducing costs, and lowering emissions are highlighted. Life cycle assessment (LCA) across all stages of MSW management is also reviewed, along with future trends in leveraging generative AI, natural language processing (NLP), and agent-based AI systems to analyze waste generation patterns and public sentiment. Efficient collection and handling can be enhanced through route optimization with geographic information systems and real-time bin-level monitoring. Furthermore, sensor-embedded, real-time object detection systems paired with robotics enable material characterization and automated sorting, thereby lowering costs and diverting waste from landfills into value-added products for diverse industrial sectors including packaging, chemicals, textiles, metals and glass, transportation, and electronics industries. Without intervention, global waste is projected to reach 4.54 billion tons by 2050, contributing direct economic costs of $\$$400 billion and roughly 2.38 billion tons of CO 2 -equivalent emissions annually. This review demonstrates how AI-driven, end-to-end solutions for MSW management can mitigate economic and environmental challenges, while directly supporting the United Nations Sustainable Development (UNDP) goals related to innovation and infrastructure (SDG 9), sustainable cities (SDG 11), responsible consumption and production (SDG 12), and climate action (SDG 13).

09 BIOMASS FUELS↗

Accessing Fungal Contributions to the Birch Effect: Real-Time Respiration from Pore-Scale Microfluidics

Drying and rewetting of soil stimulates soil carbon emission. The Birch effect, driven by these cycles, leads to CO2 efflux, which can be monitored using real-time mass spectrometry (RTMS). Although soil fungi retain water during droughts, their contribution to CO2 release during drying–rewetting cycles remains unclear. In this study, we present the first demonstration of integrating micromodels with RTMS to monitor the Birch effect by simulating drought and rewetting. Micromodels were inoculated with axenic fungal culture and dried to assess moisture retention. After drying, RTMS quantified CO2 release upon rewetting with H218O mixtures. Our results showed that soil fungi released CO2 upon rehydration and immediately utilized the external water source at the pore scale by generating subsequent 46CO2. This work is the first to integrate RTMS with microsystems to investigate pore-scale biogeochemistry and the involvement of fungi in the Birch effect.

54 ENVIRONMENTAL SCIENCES↗

Embedded Sensing in Additive Manufacturing Metal and Polymer Parts: A Comparative Study of Integration Techniques and Structural Health Monitoring Performance

This study presents a comparative evaluation of post-process sensor integration in additively manufactured (AM) metal and the in-situ process for polymer structures for structural health monitoring (SHM), with an emphasis on embedded sensors. Geometrically identical specimens were fabricated using copper via metal fused filament fabrication (FFF) and PLA via polymer FFF, with piezoelectric transducers (PZTs) inserted into internal cavities to assess the influence of material and placement on sensing fidelity. Mechanical testing under compressive and point loads generated signals that were transformed into time–frequency spectrograms using a Short-Time Fourier Transform (STFT) framework. An engineered RGB representation was developed, combining global amplitude scaling with an amplitude-envelope encoding to enhance contrast and highlight subtle wave features. These spectrograms served as inputs to convolutional neural networks (CNNs) for classification of load conditions and detection of damage-related features. Results showed reliable recognition in both copper and PLA specimens, with CNN classification accuracies exceeding 95%. Embedded PZTs were especially effective in PLA, where signal damping and environmental sensitivity often hinder surface-mounted sensors. This work demonstrates the advantages of embedded sensing in AM structures, particularly when paired with spectrogram-based feature engineering and CNN modeling, advancing real-time SHM for aerospace, energy, and defense applications.

additive manufacturing↗

Surface-Enhanced Raman Detection of the CO 2 Moisture Swing

The development of scalable, energy-efficient carbon dioxide (CO 2 ) capture technologies is critical for achieving net-zero emissions. Moisture swing (MS) sorbents offer a promising alternative to traditional thermal regeneration methods by enabling reversible CO 2 binding through humidity-driven ion hydrolysis. In this study, we investigate the anion speciation dynamics in two classes of MS materials─an anion-exchange resin with a bicarbonate anion and activated carbon impregnated with potassium bicarbonate salt─using both sorption measurements and in situ surface-enhanced Raman spectroscopy (SERS). Ni-coated Ag nanowires were employed as SERS substrates to enhance signal intensity and enable the real-time detection of carbonate (CO 3 2– ), bicarbonate (HCO 3 – ), and hydroxide (OH – ) species under controlled humidity conditions in both air and nitrogen atmospheres. The results reveal humidity-dependent interconversion between anionic species with significant spectral shifts confirming the reversible hydrolysis reactions that drive the MS mechanism. Under humid conditions, we observed the depletion of bicarbonate signals and a concurrent increase in carbonate species, consistent with moisture-induced desorption of CO 2 . With the activated carbon samples, we further observed the formation of hydroxide. These findings not only validate the mechanistic models of humidity-driven anion exchange in MS sorbents but also demonstrate the practical potential of SERS as an operando diagnostic tool for monitoring CO 2 capture media. The ability to resolve and semiquantitatively evaluate the reversible transformation of carbonate, bicarbonate, and hydroxide ions under realistic environmental conditions provides valuable insight for the rational design, performance optimization, and quality control of next-generation sorbent materials for direct air capture applications.

CO2 capture↗

Assessing Seismic Risk for CO2 Geologic Storage: Comparative Analysis of the Delaware Basin and Basin and Range Province Projects

ABSTRACT: Effective management of induced seismicity is critical for safe and sustainable CO2 storage. This study evaluates fault slippage risks in the Delaware Basin (Texas) and Basin and Range Province (Utah), integrating geological, operational, and geomechanical parameters to assess fault stability and seismic hazard mitigation. In the Delaware Basin, two sites were analyzed under an injection rate of 20,000 bbl/day over 25 years. One site showed low fault slip risk, while the other exhibited higher reactivation potential due to proximity to critically stressed faults. Sensitivity analysis revealed that increased pore pressure significantly heightened slip potential, highlighting the necessity of precise pressure control and real-time monitoring. In the Basin and Range Province, fault stability was evaluated at Neck of the Desert, Escalante Desert, Parowan, and Beaver sites under injection rates of 8,750 bbl/day per site over 30 years. Minimal fault slip risk was observed at Neck of the Desert and Escalante Desert sites, whereas Parowan and Beaver sites exhibited elevated slip potential due to semi-critically stressed faults sensitive to modest pore pressure increases. The findings demonstrate that fault slippage analysis, combined with sensitivity analysis of pore pressure and friction coefficients, is essential for understanding seismic risks. Continuous monitoring, adaptive injection management, and rigorous geomechanical analysis are key strategies for minimizing induced seismicity in CO2 sequestration projects.

58 GEOSCIENCES↗

A critical review of electrochemical heat pump technologies: Status, challenges, and perspectives

The development of advanced heat pump technologies is critical for reducing global energy consumption in the building sector, where space heating and cooling account for nearly 50% of energy use. Electrochemical heat pumps (EHPs) offer a promising alternative to vapor compression systems by enabling direct electrochemical-to-thermal energy conversion, often with environmentally benign working fluids that exhibit low or zero global warming potential (GWP). Prior literature has predominantly focused on chemically reactive heat pumps, while comprehensive assessments of electrochemical mechanisms remain limited. Here, this review addresses this gap by systematically evaluating the underlying principles, architectures, and performance metrics of EHP systems. Compared to conventional vapor compression systems, EHPs can achieve 10%-30% higher energy efficiency, with reported cooling coefficients of performance (COP c ) ranging from 3.5 to 14.3 under standard operating conditions. Despite these advantages, widespread adoption is hindered by challenges including membrane degradation, electrode fouling, sluggish redox kinetics, and elevated system-level capital costs. To address these limitations, the review outlines three research priorities: (i) the development of advanced membranes, catalysts, and electrode materials with enhanced chemical and mechanical stability; (ii) the application of molecular-level simulations for the rational design of high-performance redox-active working fluids; and (iii) the integration of advanced diagnostic techniques for real-time monitoring and sustained operation of EHPs. By consolidating recent advances and explicitly identifying technological and scientific gaps, this work uniquely contributes a comprehensive framework for guiding future electrochemical heat pump research and facilitating the transition to sustainable thermal management technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hydrological connectivity: a review and emerging strategies for integrating measurement, modeling, and management

This review synthesizes methods for measuring, modeling, and managing hydrologic connectivity, offering pathways to improve practices and address environmental challenges (e.g., climate change) and sustainability. As a key driver of water movement and nutrient cycling, hydrologic connectivity influences flood mitigation, water quality regulation, and biodiversity conservation. However, traditional field-based methods (e.g., dye tracing), indirect measurements (e.g., runoff analysis), and remote sensing techniques (e.g., InSAR) often struggle to capture the complexity of catchment-scale interactions. Similarly, modeling approaches—including process-based and percolation theory-based models, graph theory, and entropy-based metrics—face limitations in fully representing these interconnected processes. Both modeling and measurement techniques are constrained by inadequate spatial and temporal coverage, high data demands, computational complexity, and difficulties in representing subsurface connectivity. Subsequently, we critique current management practices that prioritize isolated variables (e.g., streamflow, sediment transport) over system-wide strategies and emphasize the need for adaptive, connectivity-based approaches in water resource planning and restoration. Moving forward, we highlight the importance of interdisciplinary collaboration, technological innovations (e.g., AI-driven modeling, real-time monitoring), and integrated frameworks to improve connectivity measurement, modeling, and adaptive management to restore fragmented hydrologic networks. This integrated approach sets the stage for transformative water resource management, fostering proactive policy development and stakeholder engagement.

Dwivedi, Dipankar↗

Adaptive spectra-to-exposure conversion using ridge regularized polynomial response models

Real-time gamma spectra-to-exposure conversion in aerial and ground monitoring commonly relies on calibration-derived, detector- or system-specific conversion coefficients that are assumed to generalize across operational environments. In practice, deployment specific differences in spectral composition and transport conditions can introduce systematic bias relative to reference instruments, motivating methods that adapt coefficients using minimal field supervision while explicitly limiting overfitting. In this work, we present a conservative coefficient adaptation framework that updates a baseline polynomial energy-weighting function using ridge-regularized regression, with leave-one-out cross-validation (LOOCV) used to select the regularization strength. The findings support ridge-constrained minimal-supervision adaptation as a practical mechanism to suppress site-specific bias without destabilizing a calibration-derived baseline.

61 RADIATION PROTECTION AND DOSIMETRY↗

Energy Improvements of Fire Station 71

Since 2018, the City of Shawnee, Kansas has completed two phases of the State of Kansas Facility Conservation Improvement Program (FCIP), an initiative that guarantees operational cost and energy savings through targeted construction improvements on City facilities and infrastructure. The City is currently in the third phase of this FCIP, where one of the projects included an investment in energy improvements for Fire Station 71 (FS 71). The City partnered with Navitas, an Energy Service Company (ESCO), to implement a Photovoltaic Solar Array on FS71. The purpose of this project was to invest in sustainable building improvements with Energy Conservation Measures (ECM) to bring cost savings to the City and to provide sustainable benefits to the residents of Shawnee. In the first task of the project, Navitas collaborated with the City of Shawnee and the Community Development Department to determine the optimal layout and schedule for the installation of the solar array on FS 71. In the second task of the project, Navitas installed the 99.8 kW DC Photovoltaic solar array system. This system installation comprised of racking, inverters, optimizers, load center, and disconnect, which were all installed at a total ECM price of $\$$247,948. The third task focused on start-up and commissioning of the array. Navitas installed a real-time data analytics information management system integrated with utility meters, which evaluates the operations of the utility system and verifies operation of equipment and ensures optimum operation for energy efficiency. In the final task of this project, this analytics system was used for monitoring and verification, which will continue to be used to evaluate the success of the project for the coming years. The primary goal of the project was to install the 99.8 kW DC PV solar array at FS 71 to demonstrate the viability of solar energy systems in essential municipal facilities. Fire stations are energy demanding structures, as they require a constant intake of power and have a high baseline energy usage. The success of solar arrays on a fire station exemplifies their energy efficiency and effectiveness and displays their potential for application on other city facilities. By installing a solar array at such a facility, the City sought not only to offset electricity usage but also to serve as a model for ECMs in other municipal facilities and infrastructure projects. From an economic standpoint, this project demonstrates the feasibility of renewable energy at the municipal level. The total project cost of $\$$247,948 was split evenly between city funds and award funding, minimizing financial risk while ensuring guaranteed long-term savings. Any excess savings that are beyond the guaranteed minimums remain with the city, which enables future investment in sustainable energy initiatives. This project provides many benefits to the public. In addition to reducing the environmental footprint of city operations, it lowers taxpayer-funded utility spending and improves the energy security of a critical facility. The knowledge gained from this implementation motivates the City to focus on similar efforts across other public facilities in future FCIP phases and other City projects.

14 SOLAR ENERGY↗

Short-term experimental flooding impacts soil biogeochemistry but not aboveground vegetation in a coastal forest

Rising sea levels and intensifying storms increase flooding pressure on coastal forests, triggering tree mortality, ecosystem transitions, and changes to the coastal carbon cycle. However, the mechanisms that drive coastal forest mortality remain elusive due to the complex interplay between belowground and aboveground processes during flooding disturbances and limitations of observations typically reported in coastal forest mortality studies. We used an ecosystem-scale manipulation to simulate hurricane-level flooding of a coastal forest and explore the individual and interactive impacts of inundation and salinity. Monitoring real-time soil conditions and tree physiological responses, we observed consistent impacts on soil biogeochemistry aligned with belowground drivers of tree mortality, but no consistent responses in aboveground vegetation immediately following flooding. Our findings provide empirically based insight into the earliest stages of a hypothesized forest mortality spiral and offer critical benchmarks for predicting coastal forest resilience in the face of accelerating climate change.

coastal forests↗

Advancing ocean monitoring and knowledge for societal benefit: the urgency to expand Argo to OneArgo by 2030

The ocean plays an essential role in regulating Earth’s climate, influencing weather conditions, providing sustenance for large populations, moderating anthropogenic climate change, encompassing massive biodiversity, and sustaining the global economy. Human activities are changing the oceans, stressing ocean health, threatening the critical services the ocean provides to society, with significant consequences for human well-being and safety, and economic prosperity. Effective and sustainable monitoring of the physical, biogeochemical state and ecosystem structure of the ocean, to enable climate adaptation, carbon management and sustainable marine resource management is urgently needed. The Argo program, a cornerstone of the Global Ocean Observing System (GOOS), has revolutionized ocean observation by providing real-time, freely accessible global temperature and salinity data of the upper 2,000m of the ocean (Core Argo) using cost-effective simple robotics. For the past 25 years, Argo data have underpinned many ocean, climate and weather forecasting services, playing a fundamental role in safeguarding goods and lives. Argo data have enabled clearer assessments of ocean warming, sea level change and underlying driving processes, as well as scientific breakthroughs while supporting public awareness and education. Building on Argo’s success, OneArgo aims to greatly expand Argo’s capabilities by 2030, expanding to full-ocean depth, collecting biogeochemical parameters, and observing the rapidly changing polar regions. Providing a synergistic subsurface and global extension to several key space-based Earth Observation missions and GOOS components, OneArgo will enable biogeochemical and ecosystem forecasting and new long-term climate predictions for which the deep ocean is a key component. Driving forward a revolution in our understanding of marine ecosystems and the poorly-measured polar and deep oceans, OneArgo will be instrumental to assess sea level change, ocean carbon fluxes, acidification and deoxygenation. Emerging OneArgo applications include new views of ocean mixing, ocean bathymetry and sediment transport, and ecosystem resilience assessment. Implementing OneArgo requires about $100 million annually, a significant increase compared to present Argo funding. OneArgo is a strategic and cost-effective investment which will provide decision-makers, in both government and industry, with the critical knowledge needed to navigate the present and future environmental challenges, and safeguard both the ocean and human wellbeing for generations to come.

ARGO↗

Correlation of Surface Acoustic Wave (SAW) force myography sensor output with elbow joint torque

Accurate assessment of skeletal muscle forces and net joint torque is essential for preventing fatigue-related injuries, optimizing physical training, and monitoring disease progression in neuromuscular conditions. However, existing joint torque evaluation techniques are hindered by limited portability and high operational costs, confining their use to controlled laboratory or clinical settings. Despite substantial advances in wearable joint torque estimation systems, ongoing challenges such as power constraints, bulky wired setups, and susceptibility to environmental or motion artifacts underscore the urgent need for truly batteryless, wireless solutions deployable in real-world settings. This paper proposes a novel surface acoustic wave (SAW)-based force myography (FMG) system for noninvasive measurement of joint torque, validated against a gold-standard electromechanical dynamometer. The approach uses a single SAW sensor embedded in an armband to detect volumetric biceps brachii changes, with a second-order polynomial mapping sensor output and elbow angle to torque. Seven participants were tested in both isometric (15°–90°) and isokinetic (10°/s and 20°/s) supinated elbow flexion tasks. Under isometric conditions, subject-specific calibration achieved a normalized root-mean-square error (NRMSE) of 13.6% ± 6.0% and R 2 = 0.834 ± 0.180, while a group-level model yielded 14.4% ± 6.8% and 0.808 ± 0.208, respectively. For isokinetic trials, the group model produced an NRMSE of 24.1% ± 6.6% at 10°/s and 24.9% ± 08.9% at 20°/s, highlighting the feasibility of using a single-sensor SAW-FMG setup across different speeds. Because SAW devices support wireless, battery-free operation, the proposed system offers a pathway to portable, real-time monitoring for sports medicine, rehabilitation, and clinical diagnostics.

36 MATERIALS SCIENCE↗

A portable and reusable sensor system based on graphene for real-time and sensitive detection of lead ions in water

Long-term exposure to Pb 2+ can cause irreversible damage to the nervous, cardiovascular, and reproductive systems. Therefore, developing a fast and sensitive detection system capable of monitoring minuscule concentrations of Pb 2+ is essential. In this study, we demonstrated a fully portable sensor system enabling rapid, sensitive, and real-time monitoring of Pb 2+ . The sensor system adopted the remote-gate field-effect transistor (RGFET) detection scheme and was easy to operate, even for non-experts. The sensor system comprised two printed circuit boards (PCBs): a sensor PCB with a remote-gate electrode and an analyzer PCB with a metal-oxide-semiconductor field-effect transistor (MOSFET) transducer and peripheral electronics to manage sensor signals. To achieve a high sensitivity for Pb 2+ , we utilized graphene ink drop-casted on the sensor PCB as a sensing membrane. The graphene film was easy to deposit and remove, enabling the sensor PCB to be reused multiple times. The sensor system was further linked to a smartphone application that instantly monitors the sensor response, allowing for rapid point-of-use detection. The sensor exhibited a high sensitivity of 21.7% when the limit of detection (LOD) value of 1 nM (∼0.2 ppb) was detected, and the typical detection time for each sample was approximately 60 seconds. This portable sensor system advances sensing technologies and could potentially supplement expensive, laborious conventional sensing equipment.

54 ENVIRONMENTAL SCIENCES↗

Integration and Demonstration of Monitoring, Modeling, and Prediction of DV-1 Amendment Performance at the Bench Scale: DV-1 Amendment Demonstration

During fiscal years 2024 and 2025, the U.S. Department of Energy’s Hanford Field Office commissioned Pacific Northwest National Laboratory to conduct applied research aimed at reducing the cost, time, and uncertainty associated with in situ treatment of vadose zone contaminants at the Hanford Site. This report outlines the integration of three key research efforts into a meso-scale demonstration designed to advance field-scale solutions that aim to (1) optimize the delivery of chemical amendments to contaminated soils, (2) reduce uncertainty in amendment delivery performance assessment using advanced monitoring techniques, and (3) provide real-time insights into when and where amendment-induced precipitation reactions occur in the subsurface. To achieve these objectives, the tank-scale (~ 1 cubic meter) Geophysical Imaging of Flow and Transport (GIFT) system was developed. GIFT enables experimental testing of amendment delivery while incorporating automated multi-modal monitoring approaches, including pressure measurements, direct fluid sampling, and remote time-lapse geophysical imaging. The data generated from these monitoring techniques will serve as inputs for a generative artificial-intelligence-driven digital twin – a numerical simulation model designed to honor observed data while quantifying uncertainty in simulation accuracy. Using this simulator, researchers will refine an amendment injection strategy to maximize delivery efficiency within a low-permeability soil zone. Monitoring data will be interpreted through simulated outputs to enhance understanding of the injection process. The efficacy of this integrated approach will be evaluated through direct sampling at the conclusion of the experiment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗