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At least 1,063 records · Page 59

Spray process of multi-component gasoline surrogate fuel under ECN Spray G conditions

As modern gasoline direct injection (GDI) engines utilize sophisticated injection strategies, a detailed understanding of the air-fuel mixing process is crucial to further improvements in engine emission and fuel economy. In this study, a comprehensive evaluation of the spray process of single-component iso-octane (IC8) and multi-component gasoline surrogate E00 (36 % n-pentane, 46 % iso-octane, and 18 % n-undecane, by volume) fuels was conducted using an Engine Combustion Network (ECN) Spray G injector. High-speed extinction, schlieren, and microscopy imaging campaigns were carried out under engine-like ambient conditions in a spray vessel. Experimental results including liquid/vapor penetration, local liquid volume fraction, droplet size, and projected liquid film on the nozzle tip were compared under ECN G1 (573 K, 3.5 kg/m 3 ), G2 (333 K, 0.5 kg/m 3 ), and G3 (333 K, 1.01 kg/m 3 ) conditions. In addition to the experiments, preferential evaporation process of the E00 fuel was elucidated by Large–Eddy Simulations (LES). The three-dimensional liquid volume fraction measurement enabled by the computed tomographic reconstruction showed substantial plume collapse for E00 under the G2 and G3 conditions having wider plume growth and plume-to-plume interaction due to the fuel high vapor pressure. Here, the CFD simulation of E00 showed an inhomogeneity in the way fuel components vaporized, with more volatile components carried downstream in the spray after the end of injection. The high vapor pressure of E00 also results in ~4 μm smaller average droplet diameter than IC8, reflecting a higher rate of initial vaporization even though the final boiling point temperature is higher. Consistent with high vapor pressure, E00 had a wider plume cone angle and enhanced interaction with the wall to cover the entire surface of the nozzle tip in a film. However, the liquid fuel underwent faster evaporation, so the final projected tip wetting area was smaller than the IC8 under the flash-boiling condition.

33 ADVANCED PROPULSION SYSTEMS↗

Enhanced high-harmonic generation from an all-dielectric metasurface

The recent observation of high-harmonic generation from solids creates a new possibility for engineering fundamental strong-field processes by patterning the solid target with subwavelength nanostructures. All-dielectric metasurfaces exhibit high damage thresholds and strong enhancement of the driving field, making them attractive platforms to control high harmonics and other high-field processes at the nanoscale. Here we report enhanced non-perturbative high-harmonic emission from a Fano-resonant Si metasurface that possesses a classical analogue of electromagnetically induced transparency. The harmonic emission is enhanced by more than two orders of magnitude compared to unpatterned samples. The enhanced high harmonics are highly anisotropic with respect to the excitation polarization and are selective by the excitation wavelength due to its resonant features. Furthermore, by combining nanofabrication technology and ultrafast strong-field physics, our work paves the way for the design of new compact ultrafast photonic devices that operate under high intensities and at short wavelengths.

42 ENGINEERING↗

Unveiling the influence of selective-area-regrowth interfaces on local electronic properties of GaN p-n junctions for efficient power devices

Here, we report correlated nanoscale mapping of the structure, composition, and properties of regrown GaN p-n junctions to identify how etching and non-planar regrowth processes limit diode performance via the introduction of unintentional dopants and defect states. p-GaN was selectively regrown in n-GaN trenches with SiO 2 masks of variable mask-to-trench-width ratio. Dilute Al layers were periodically introduced during regrowth as markers of the growth interface. Correlated nanoscale mapping of doping, conductivity, and dopant complexes was achieved with atom probe tomography (APT), scanning spreading resistance microscopy (SSRM), and cathodoluminescence (CL) spectroscopy, respectively. The Al marker layers, detected by APT, enabled reconstruction of the faceted growth interface and correlation of the dopant concentration with position and time. The p-GaN growth rate is proportional to the mask-to-trench width ratio while the dopant incorporation rate is invariant. At trench edges, magnesium incorporation is suppressed, and oxygen incorporation enhanced, due to preferential incorporation on the semi-polar growth surface, leading to compensation and less abrupt p-n junctions; the SiO 2 mask is a source of oxygen. Residual etch damage below the regrowth interface induces n-type and p-type conductivity, creating leakage pathways. The non-uniform Mg incorporation is driven by crystal anisotropy and is thus inherent to non-planar regrowth, but can be mitigated by engineering the regrowth interface and process parameters. The unprecedented integration of spatially resolved mapping of dopants, impurities, conductivity, and carrier type is a powerful approach to discriminating distinct factors that limit the performance of regrown diodes, enabling the rational optimization of process and device design.

36 MATERIALS SCIENCE↗

Intelligent Weld Manufacturing: Role of Integrated Computational Welding Engineering

A master welder uses his sensory perceptions to evaluate the process and connect them with his/her knowledge base to take the necessary corrective measures with his/her acquired skills to make a good weld. All these actions must take place in real time. Success depends on intuition and skills, and the procedure is labor-intensive and frequently unreliable. The solution is intelligent weld manufacturing. The ultimate goal of intelligent weld manufacturing would involve sensing and control of heat source position, weld temperature, weld penetration, defect formation and ultimately control of microstructure and properties. This involves a solution to a problem (welding) with many highly coupled and nonlinear variables. The trend is to use an emerging tool known as intelligent control. This approach enables the user to choose a desirable end factor such as properties, defect control, or productivity to derive the selection of process parameters such as current, voltage, or speed to provide for appropriate control of the process. Important elements of intelligent manufacturing are sensing and control theory and design, process modeling, and artificial intelligence. Significant progress has been made in all these areas. Integrated computational welding engineering (ICWE) is an emerging field that will aid in the realization of intelligent weld manufacturing. The paper will discuss the progress in process modeling, microstructure, properties, and process control and automation and the importance of ICWE. Also, control and automation strategies for friction stir welding will be discussed.

42 ENGINEERING↗

CFD modeling of near-wall combustion and unburned methane prediction in natural gas spark ignition engines

Natural gas-powered engines play a critical role in gas drilling, compression, and transmission sectors, but methane (CH 4 ) from engine combustion slip can be significant over their lifespan, contributing to atmospheric pollution and signaling reduced engine efficiency. Here, to address this challenge, computational fluid dynamics (CFD) simulations offer valuable insights into the in-cylinder combustion process, enabling the optimization of combustion strategies and engine designs to minimize unburned CH 4 slip. This study aims to evaluate and improve combustion models for simulating the combustion process and predicting unburned CH 4 concentrations in natural gas spark-ignition (SI) engines, including engines that are part of combined reformer-engine systems. Specifically, the performance of two flamelet-based combustion models—the Extended Coherent Flame Model (ECFM) and the G-equation model—was assessed using experimental engine data collected under varying excess-air ratio (λ) conditions and fuel compositions, including natural gas and syngas blends. In addition, to enhance the predictive capabilities of the G-equation model, a flame-wall interaction (FWI) sub-model was integrated into its framework. The effects of its model parameters, such as quenching and influence distance, on combustion behavior and unburned methane predictions were analyzed in detail. The ECFM tended to predict delayed combustion phasing under diluted mixture conditions, resulting in overprediction of unburned CH 4 concentrations. In contrast, the G-equation model provided reasonable predictions of combustion pressure, while representing higher the CH 4 reduction rate across the operating condition compared to experimental data. Incorporating the FWI sub-model—with the quenching distance calculated based on a pressure-dependent relation (P -0.48 ) and a fixed influence distance of 1.5 mm—further improved the G-equation model’s accuracy in predicting CH 4 reduction rates without compromising its ability to simulate the combustion process.

Combustion model↗

Electrochemical Reaction Engineering: A Lost (and Found) Art

The heart (or, perhaps more appropriately, the stomach) of any chemical manufacturing process is the reactor, where chemical and physical transformations occur under precisely controlled conditions. For non-electrochemical industrial processes, the design, optimization and operation of chemical reactors are extremely well developed, drawing upon the principles of chemistry, physics, calculus and economics. However, electrolytic processes face a dearth of well documented reaction engineering principles and design practices. This tutorial-style poster presentation introduces electrochemistry students and industrial practitioners to the "lost art" of reaction engineering and its organic extensions to electrochemical devices. Electrochemical reactor fundamentals and illustrative design equations are presented alongside a proposed five-step generalizable methodology for electrochemical reactor scale-up. Overall, this contribution seeks to educate electrochemistry researchers on practical means of reducing laboratory technologies to commercial practice.

electrochemistry↗

A mixed integer linear programming approach for the design of chemical process families

Tackling climate change goals requires widespread deployment of process technology variants across many decentralized sites with different geographical, environmental, and operational requirements. Conventional engineering approaches focus on unique designs for each installation (process variant), while missing opportunities for manufacturing standardization. Here, instead we seek to optimize a process platform of common unit designs while simultaneously designing an entire family of process variants that make use of that platform. This reduces engineering effort, deployment timelines, and manufacturing costs. We propose a nonlinear generalized disjunctive programming formulation and convert this to an efficient mixed-integer linear programming (MILP) formulation through discretization of the design space. We formulate our optimization in Pyomo with costing from IDAES, and we demonstrate the computational performance and solution quality on a water treatment desalination system from the PARETO framework and a carbon capture system built in Aspen Plus as part of CCSI2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Utilization of Common Automotive Three-Way NO{sub x} Reduction Catalyst for Managing Off- Gas from Thermal Treatment of High-Nitrate Waste - 13094

Studsvik's Thermal Organic Reduction (THOR) steam reforming process has been tested and proven to effectively treat radioactive and hazardous wastes streams with high nitrate contents to produce dry, stable mineral products, while providing high conversion (>98%) of nitrates and nitrites directly to nitrogen gas. However, increased NO{sub x} reduction may be desired for some waste streams under certain regulatory frameworks. In order to enhance the NO{sub x} reduction performance of the THOR process, a common Three-Way catalytic NO{sub x} reduction unit was installed in the process gas piping of a recently completed Engineering Scale Technology Demonstration (ESTD). The catalytic DeNO{sub x} unit was located downstream of the main THOR process vessel, and it was designed to catalyze the reduction of residual NO{sub x} to nitrogen gas via the oxidation of the hydrogen, carbon monoxide, and volatile organic compounds that are inherent to the THOR process gas. There was no need for auxiliary injection of a reducing gas, such as ammonia. The unit consisted of four monolith type catalyst sections positioned in series with a gas mixing section located between each catalyst section. The process gas was monitored for NO{sub x} concentration upstream and downstream of the catalytic DeNO{sub x} unit. Conversion efficiencies ranged from 91% to 97% across the catalytic unit, depending on the composition of the inlet gas. Higher concentrations of hydrogen and carbon monoxide in the THOR process gas increased the NO{sub x} reduction capability of the catalytic DeNO{sub x} unit. The NO{sub x} destruction performance of THOR process in combination with the Three-Way catalytic unit resulted in overall system NO{sub x} reduction efficiencies of greater than 99.9% with an average NO{sub x} reduction efficiency of 99.94% for the entire demonstration program. This allowed the NO{sub x} concentration in the ESTD exhaust gas to be maintained at less than 40 parts per million (ppm), dry basis with an average concentration of approximately 17 ppm, dry basis. There were no signs of catalyst deactivation throughout the 6 day demonstration program, even under the high steam (>50%) content and chemically reducing conditions inherent to the THOR process. Utilization of the common Three-Way automotive catalyst may prove to be a cost effective method for improving NO{sub x} emissions from thermal treatment processes that utilize similar processing conditions. This paper will discuss the details of the implementation and performance of the Three-Way catalytic DeNO{sub x} unit at the THOR ESTD, as well as a discussion of future work to determine the long-term durability of the catalyst in the THOR process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Retrofitting Holcim Ste. Genevieve Cement Plant with CO2 Capture Plant Using Air Liquide Cryocap™ FG Technology

The global cement manufacturing industry is a major contributor to carbon dioxide emissions. The International Energy Agency's "Net Zero Emissions by 2050 Scenario" identifies CCS as a major strategy for meeting that goal. This project is among the first attempts to transfer capture technology developed at coal-fired power plants to the cement industry. The main objective of the project is to execute and complete a front-end engineering and design (FEED) studies for commercial-scale, carbon capture projects that separates 95% of the total CO2 emissions at the Holcim (US) Ste. Genevieve cement manufacturing facility using Air Liquide’s Pressure Swing Adsorption system (PSA) assisted Cryocap™ technology. The Holcim Ste. Genevieve cement plant in Missouri, US, boasts one of the largest single cement production lines in the world, with a capacity of approximately 12,000 t/day. The plant currently uses traditional fuels, namely coal and petcoke. The captured CO2 will be pipeline and geological storage grade. The industrial host site emits approximately 3.0 million tonne CO2/yr. Air Liquide’s Cryocap™ technology has been developed over the last 18+ years for CO2 capture applications. It has been shown to be applicable to a variety of industrial applications (e.g., steel, cement, SMR, Fluidized Catalytic Crackers (FCCs)). Cryocap™ FG consists of a Pressure Swing Adsorption (PSA) unit coupled with a Cryogenic System. The PSA pre-concentrates the CO2 from the flue gas, while the cryogenic unit enables the CO2 purity to be increased to the desired level. The project team is led by the Prairie Research Institute at the University of Illinois at Urbana-Champaign. The tasks include: complete FEED study for retrofitting the industrial facility with a carbon capture system to support developing a detailed cost estimate; business case analysis outlining the anticipated revenue and credits if projects was built and operated; technoeconomic analysis (TEA) outlining how capture system achieves DOE capture goals; and life cycle (LCA) analysis demonstrating zero net carbon emissions. The FEED study was successfully completed. This includes completing the process basis of design; preliminary engineering; outside battery limits (OSBL) detailed engineering including a Zero Liquid Discharge (ZLD) wastewater treatment system; inside battery limits (ISBL) detailed engineering [1]. An overall project capital cost estimate within a -20%/+30% accuracy was developed. The major contributors to the Total Plant Cost (TPC), by system, are the costs associated with the Outside Battery Limit (OSBL) section of the plant which includes a new river water intake structure and a Zero Liquid Discharge (ZLD) system. By cost category, the major contributors to the TPC are equipment and subcontractor costs, followed closely by engineering, construction management, home office and contractor fees. The TEA has been created to reflect the findings of the project. It analyzes the economic performance of the Cryocap™ technology by reviewing the estimated capital costs, operating cost, and revenue. The Cost of Capture (COC) associated with the Cryocap™ technology for 95% CO2 capture, when considering NETL 2018 economic assumptions (42/58 debt/equity ratio, 5.15% interest on debt and 1.42% return on equity in real dollars) and 2022 economic assumptions (42/58 debt/equity ratio, 8.82% interest on debt and 4.90% return on equity in real dollars) was found to be much lower than that for the DOE-NETL’s base-line cases. The highest contributors to the COC are annualized capital expenditures (CAPEX) and electricity consumption which can be offset by using lower cost renewable sources. The LCA was conducted using OpenLCA which is an open-source software that is recommended by NETL. The database utilized for this study was a modified version of TRACI 2.1 (developed by the US. Environmental Protection Agency’s National Risk Management Research Laboratory and modified by NETL). The Cryocap™ FG technology does not consume fuels in significant quantities and does not utilize specialized chemical solvents subject to decomposition, such as those utilized in amine-based carbon capture systems. The Cryocap™ FG technology mainly utilizes electricity as its energy input; hence, its calculated emissions are mainly associated with the generation of electricity offsite and are dependent on the energy matrix of the grid at the time of project implementation. The water consumption impact of the Cryocap™ FG is mostly for makeup of the water lost by evaporation in the cooling tower; however, the carbon capture plant will be equipped with a ZLD system to avoid effluent streams and minimize water consumption. The successful construction and operation of this plant based on this study results will provide a means to demonstrate an economically attractive and transformational capture technology that can be used to retrofit existing plants and be deployed at new plants.

01 COAL, LIGNITE, AND PEAT↗

Energy Consumption and CO 2 Emissions in Ironmaking and Development of a Novel Flash Technology

The issues of energy consumption and CO 2 emissions of major ironmaking processes, including several new technologies, are assessed. These two issues are interconnected in that the production and use of fuels to generate energy add to the total amount of CO 2 emissions and the efforts to sequester or convert CO 2 require energy. The amounts of emissions and energy consumption in alternate ironmaking processes are compared with those for the blast furnace, currently the dominant ironmaking process. Although more than 90% of iron production is currently through the blast furnace, intense efforts are devoted to developing alternative technologies. Recent developments in alternate ironmaking processes, which are largely driven by the needs to decrease CO 2 emissions and energy consumption, are discussed in this article. This discussion will include the description of the recently developed novel flash ironmaking technology. This technology bypasses the cokemaking and pelletization/sintering steps, which are pollution prone and energy intensive, by using iron ore concentrate. This transformational technology renders large energy saving and decreased CO 2 emissions compared with the blast furnace process. Economic analysis indicated that this new technology, when operated using natural gas, would be economically feasible. As a related topic, we will also discuss different methods for computing process energy and total energy requirements in ironmaking.

36 MATERIALS SCIENCE↗

A Causal Approach to Integrate Component Health Data into System Reliability Models

Two of the challenges of current plant reliability approaches are the ability to integrate plant health data, and to support decision making. Condition based data and diagnostic/prognostic information are in fact not considered into plant reliability models to inform system engineers on the most critical components. Currently, the propagation of quantitative health data from the component to the system level is a challenge given the diverse nature/structure of the data. On the other hand, plant reliability methods (which are typically based on fault-trees or reliability block diagrams) can effectively propagate data from the component to the system level, but values of failure rates or failure probabilities are an approximated integral representation of the past industry-wide operational experience, and it neglects the present component health status (e.g., diagnostic and condition-based data) and health projection (when available from prognostic data). Our first claim is that system reliability models should propagate health information from the component to the system/plant level in order to provide a quantitative snapshot of system/plant health and identify the most critical components. Our second claim is that component health should be informed solely by that specific component current and historical performance data and should not be an approximated integral representation of the past industry-wide operational experience. This paper is directly supporting these two claims by proposing a different approach to perform reliability modeling which relies on available component diagnostic, prognostic and condition-based data to measure component health, and it propagates this information through fault tree models. The propagation of health data from the component to the system level is performed not in terms of probability, but in terms of margins where margin is defined as the “distance” between the present actual status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated to a component performance, a margin-based approach focuses on the cause of an undesired component performance (i.e., component health). Hence, thinking of reliability in terms of margins implies decision making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical components.

97 MATHEMATICS AND COMPUTING↗

Digital Twin Model for Advanced Manufacture of a Rotating Detonation Engine Injector

A digital twin material model (DTMM) of an additive manufacturing (AM) process was created to advance the state of the art in rotating detonation engine (RDE) injector design. Current RDE injectors are designed with large pressure drops, enabling a stable and repeatable combustion process. However, this comes at the cost of system efficiency. For the technology to transition to commercial fossil-based power generation, it is important to develop injectors with reduced flow losses. Low-loss injectors are difficult to design and manufacture with conventional manufacturing techniques. AM enables new design options, but the AM manufacturing process must be thoroughly understood to result in a robust design. A DTMM provides the necessary insight by defining the cause-effect relationships between process parameters, microstructure features, and properties. Therefore, a DTMM to support the design and manufacturing process was developed and applied to the design of a new additively manufactured low-loss injector. The injector combustion behavior was characterized through hot-fire tests, and mechanical performance was compared to the DTMM predictions. The two project goals were the successful development of the DTMM and the demonstration of an improved RDE injector design. The RDE injector design and DTMM developments occurred on parallel but dependent paths. The injector was designed to reduce pressure drop by increasing the cross-sectional flow area ratio between the injector air passages and the combustor annulus. This resulted in less structural material, raising the concern that thin members would be susceptible to high-cycle fatigue (HCF) under the periodic loading inherent to an RDE. It was most important for the DTMM to predict behavior in these features; therefore, the injector design concept guided the material thicknesses used in fatigue tests. The DTMM development started by manufacturing a series of coupons over the range of possible AM process variations. A design-of-experiment approach was used to select which process variable combinations gave the most efficient coverage relevant to the injector design space. The microstructure in each of these coupons was characterized, and then computational methods were used to create a numerical model of the correlation between process variables and microstructure. Next, a set of HCF samples were tested to calibrate existing models that map microstructure to HCF performance. Together, these two links formed the DTMM that calculates HCF behavior from AM process variables. Two injector prototypes were additively manufactured. The first injector design strategy aggressively pursued low-loss performance by substantially increasing the oxidizer flow area. The combination of manufacturing lead times and the fatigue testing schedule meant that the DTMM was not available when building this first prototype. Therefore, its process parameters were chosen based on a manual review of the available coupon data. This prototype was built successfully and evaluated in 58 combustion tests. Sustained detonation was achieved with remarkably reduced pressure loss, and some tests even displayed pressure loss characteristics similar to conventional gas turbine combustors. This achieved the project goal of improving RDE injector design. The second injector was manufactured according to the optimized parameters predicted by the DTMM. The flow area modifications of this injector were less aggressive than the first injector since demonstrating low pressure loss was not an objective of the second hot-fire test series. Rather, the test objective was to cause high cycle fatigue failure in the part due to periodic loading from the rotating detonation wave. The observed number of cycles to failure was to be compared to the number predicted by the DTMM and thereby assess the utility of the DTMM in component design. However, the required level of vibration was not obtained during combustion. Therefore, high cycle fatigue was not experienced in the hot-fire tests of the second injector. Fatigue data was obtained by further testing the second injector in a conventional HCF test apparatus. The injector demonstrated HCF strength above the DTMM prediction. In fact, it did not fail and testing was only discontinued due to reaching the end of the period of performance. This points to some success in the project’s primary goal of successfully developing and applying the DTMM to a component design. Implementing the DTMM recommendations for optimal processing parameters led to a part with acceptable properties. The DTMM was also shown to be an efficient correlator of data and to provide insight into the relationship between process settings, microstructure, and property performance. However, the failure of the DTMM prediction to match the experimental result of the injector fatigue test also points to the need to include significantly more data in the model development. In this project, coupons made with identical processing parameters exhibited drastically different properties from each other and from the injector part, which clearly influences the accuracy of a model that predicts performance based on parameters. Uncertainties in the build process must be quantified to develop more robust models. A denser and broader matrix of coupon process and geometry variations, several repeated builds of every point, more in-situ build process measurements, and direct observation of tensile and HCF sample microstructure (as opposed to separate microstructure specimens) are recommendations to improve future AM modeling efforts.

20 FOSSIL-FUELED POWER PLANTS↗

Coupling of Nuclear Waste Form Corrosion and Radionuclide Transports in Presence of Relevant Repository Sediments

Assessments of waste form and disposal options start with the degradation of the waste forms and consequent mobilization of radionuclides. Long-term static tests, single-pass flow-through tests, and the pressurized unsaturated flow test are often employed to study the durability of potential waste forms and to help create models that predict their durability throughout the lifespan of the disposal site. These tests involve the corrosion of the material in the presence of various leachants, with different experimental designs yielding desired information about the behavior of the material. Though these tests have proved instrumental in elucidating various mechanisms responsible for material corrosion, the chemical environment to which the material is subject is often not representative of a potential radioactive waste repository where factors such as pH and leachant composition will be controlled by the near-field environment. Near-field materials include, but are not limited to, the original engineered barriers, their resulting corrosion products, backfill materials, and the natural host rock. For an accurate performance assessment of a nuclear waste repository, realistic waste corrosion experimental data ought to be modeled to allow for a better understanding of waste form corrosion mechanisms and the effect of immediate geochemical environment on these mechanisms. Additionally, the migration of radionuclides in the resulting chemical environment during and after waste form corrosion must be quantified and mechanisms responsible for migrations understood. The goal of this research was to understand the mechanisms responsible for waste form corrosion in the presence of relevant repository sediments to allow for accurate radionuclide migration quantifications. The rationale for this work is that a better understanding of waste form corrosion in relevant systems will enable increased reliance on waste form performance in repository environments and potentially decrease the need for expensive engineered barriers.Our current work aims are 1) quantifying and understanding the processes associated with glass alteration in contact with Fe-bearing materials; 2) quantifying and understanding the processes associated with glass alteration in presence of MgO (example of engineered barrier used in WIPP); 3) identifying glass alteration suppressants and the processes involved to reach glass alteration suppression; 4) quantifying and understanding the processes associated with Saltstone and Cast Stone (SRS and Hanford cementitious waste forms) in various representative groundwaters; 5) investigating positron annihilation as a new tool for the study of glass alteration; and 6) quantifying and understanding the processes associated with glass alteration under gamma irradiation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Progress in demonstrating the performance of Engineered Barriers for the disposal of HLW and SNF: lab studies and demonstration experiments - 20293

Disposal of high-level radioactive waste (HLW) and spent nuclear fuels (SNF) in a geological disposal facility requires a fundamental understanding of the degradation processes of materials used in its engineered barrier system (EBS) over very long timescales. Beyond the wasteform itself (i.e. the borosilicate glass for HLW or the fuel matrix and cladding for SNF), materials often employed in a disposal concept include metallic containers (typically copper and/or carbon steel) and clay-based buffer materials (typically bentonite). In this paper we explore key developments on the long-term evolution of materials employed for the immobilisation, isolation and containment of HLW and SNF in a geological disposal facility, including nuclear glasses, candidate container materials and clay buffers. Our discussion is based on the latest findings from both experimental studies and in-situ demonstration experiments. We present relevant findings from the long-term evolution of HLW glasses (UK composition), metallic materials for the containment system (envisaged in Switzerland, Sweden, Canada and other countries), and bentonite clays (envisaged in many national disposal programmes). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

W-4 W88 Systems Engineering Summer 2023 Project [Slides]

The purpose is to create a simple, streamlined process to produce reports on out of tolerance conditions with CMM data. The methods are to develop the code or process within MATLAB to import the data (import tool can be used) and to develop the code to be able to plot the data of interest. The end states are to use MATLAB to analyze CMM data from the PA and document the process for a user with some knowledge of MATLAB and an engineering background.

42 ENGINEERING↗

Revealing the Defect‐Driven Ferroelectric Mechanisms of Aluminum Nitride

Wurtzite III-nitride compounds are CMOS-compatible with widespread industrial interest to exercise ferroelectricity, despite their polar structure being highly resistant to polarization reversal. Here, we induce and tune ferroelectric properties in w-AlN via direct-write ion-beam processing, using nanoscale patterned defect engineering as a post-growth alternative to conventional cation substitution. Nanometric piezoresponse spectroscopy of the focused He + beam patterned defect concentrations in ferroelectric Al 0.92 B 0.08 N measures a localized 10x enhancement in effective piezoresponse and 40% reduction in switching barrier. The irradiation-induced point defects convert piezoelectric AlN into a ferroelectric system with site-saturated nucleation and raise the dielectric susceptibility, switched polarization, and effective piezoelectric coefficient. Enhanced defect-lattice interactions in AlN increase carrier conduction and phonon scattering loss but preserve long-range crystallinity. Here, based on atomistic analysis of nudged elastic band density functional theory calculations and reactive force field simulations, both nitrogen vacancies and defect complexes disrupt bond ordering, facilitating a line-by-line low-barrier switching of pristine AlN.

36 MATERIALS SCIENCE↗

Evaluating and predicting molecular mechanisms of adhesive degradation during field and accelerated aging of photovoltaic modules

Extending photovoltaic (PV) module lifetimes beyond 30 years is a goal of significant priority. A challenge that must first be addressed, however, is the development of a predictive reliability model that captures the synergy of terrestrial stressors on module degradation, particularly at encapsulant interfaces. Using a metrology designed specifically for PV modules, a comprehensive study of the widely used ethylene vinyl acetate encapsulant was performed in which encapsulant adhesion was evaluated as a function of environmental stressors (UV exposure, temperature, and humidity) for modules aged both under accelerated lab and internationally located field conditions for months to nearly 3 decades. Mechanical and chemical characterization methods are combined with fundamental polymer reaction engineering to unravel the degradation processes active at the molecular scale that lead to encapsulant delamination. An analytical and modular model framework is put forward enabling the prediction of long-term PV module durability, starting from fundamental principles at the molecular level and explicitly accounting for bond rupture events in the bulk encapsulant and at the encapsulant interfaces. Successful parameter tuning to adhesion data indicates a dominant occurrence of deacetylation, β-scission, and hydrolytic depolymerization, respectively. The model contributes to the longstanding challenge of predicting module lifetimes in any geographic location while minimizing time-consuming and costly aging studies.

14 SOLAR ENERGY↗