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At least 937 records · Page 52

Comparison of wind farm control strategies under realistic offshore wind conditions: turbine quantities of interest

Abstract. Wind farm flow control is a strategy to increase the efficiency and therefore lower the levelized cost of energy of a wind farm. This is done using turbine settings such as the yaw angle, blade pitch angles, or generator torque to manipulate the flow behind the turbine, affecting downstream turbines in the farm. Two inherently different wind farm flow control methods have been identified in the literature: wake steering and wake mixing. This paper focuses on comparing the turbine quantities of interest between these methods for a simple two-turbine wind farm setup, while a companion article (Brown et al., 2025) focuses on the wake quantities of interest for a single wind turbine setup. Both papers use the same set of wind farm simulations based on high-fidelity large-eddy simulations (LESs) coupled with OpenFAST turbine models. First, precursor simulations are executed in order to match wind conditions measured with lidars in an offshore wind farm off the east coast of the USA. These measurements show general wind conditions that exhibit substantially higher vertical wind shear and veer than any of the LES studies performed with wind farm flow control strategies currently available in the literature. The precursors are used to evaluate the effectiveness of the control methods. In the LES, the wind veer leads to highly skewed wakes, which have considerable influence on the power uplift of wind farm flow control strategies. In addition to a baseline controller, four different control strategies, each of which uses either pitch or yaw control, are performed on the upstream turbine of a simple two-turbine wind farm. Assuming that the wind direction is known and constant over time, the simulations show that wake steering is generally the superior wind farm flow control strategy, considering both wind farm power production and turbine damage equivalent loads when substantial wind veer is present. This result is consistent over different wind speeds and wind directions. On the other hand, for similar wind conditions with lower veer, wake mixing was found to yield the highest power production, although at the expense of generally higher loads. This leads us to conclude that the effect of wind veer, which has so far not usually been considered, can not be neglected when determining the optimal wind farm flow control strategy.

17 WIND ENERGY↗

MODELING OF HIGH SPEED FRICTION STIR SPOT WELDING USING A LAGRANGIAN FINITE ELEMENT APPROACH

Friction stir spot welding (FSSW) has been shown to be capable of joining steels of very high strength, while also being very flexible in terms of controlling the heat of welding and the resulting microstructure of the joint. This makes FSSW a potential alternative to resistance spot welding (RSW) if tool life is sufficiently high, and if machine spindle loads are sufficiently low so that the process can be implemented on an industrial robot. Robots for spot welding can typically sustain vertical loads of about 8kN, but FSSW at tool speeds of less than 3000 rpm cause loads that are too high, in the range of 11-14 kN. Therefore, in the current work tool speeds of 3000 rpm and higher were employed, in order to generate heat more quickly and to reduce welding loads to acceptable levels. The FSSW process was modeled using a finite element approach with the Forge® software package. An updated Lagrangian scheme with explicit time integration was employed to model the flow of the sheet material, subjected to boundary conditions of a rotating tool and a fixed backing plate [3]. The modeling approach can be described as two-dimensional, axisymmetric, but with an aspect of three dimensions in terms of thermal boundary conditions. Material flow was calculated from a velocity field which was two dimensional, but heat generated by friction was computed using a virtual rotational velocity component from the tool surface. An isotropic, viscoplastic Norton-Hoff law was used to model the evolution of material flow stress as a function of strain, strain rate, and temperature. The model predicted welding temperatures and the movement of the joint interface with reasonable accuracy for the welding of a dual phase 980 steel.

Advanced High strength steel↗

Domain switching of fatigued ferroelectric thin films

We investigate the domain wall speed of a ferroelectric PbZr{sub 0.48}Ti{sub 0.52}O{sub 3} (PZT) thin film using an atomic force microscope incorporated with a mercury-probe system to control the degree of electrical fatigue. The depolarization field in the PZT thin film decreases with increasing the degree of electrical fatigue. We find that the wide-range activation field previously reported in ferroelectric domains result from the change of the depolarization field caused by the electrical fatigue. Domain wall speed exhibits universal behavior to the effective electric field (defined by an applied electric field minus the depolarization field), regardless of the degree of the electrical fatigue.

36 MATERIALS SCIENCE↗

A Real-Time ANPC Inverter Digital Twin with Integrated Design-For-Trust

The demand for renewable energy has increased over the last few years, and so has the demand for greater expectations within the energy market. This increasing trend has been accompanied by more significant usage of internet-connected devices (IoT), leading to critical electrical infrastructure being connected to the internet. Implementing internet connectivity with such devices and systems provides benefits such as improving the system's performance, facilitating irregularity and anomaly mitigation, and providing additional situational awareness for enhanced decision-making. However, enhancing the connected system with IoT introduces a drawback – a greater vulnerability to cyber-attacks. Cyber-attacks targeting critical infrastructure in the electrical sector have occurred in the United States and Ukraine. These cyber-attacks highlight and expose vulnerabilities that a system inherits when connecting to the internet. These attacks left thousands of customers without electricity for hours until operators could regain control of the electric utility grid. Therefore, to address the vulnerabilities of an internet-connected power electronic device, this work focused on the hardware layer of the system. Implementing a cyber-control system inside the hardware layer can significantly reduce the possibility of an attacker patching malicious controller firmware into a photovoltaic grid-connected inverter, thus mitigating the likelihood that the inverter becomes inactive a cyber-attack scenario. With this mitigation technique, if a cyberattack is successful and an attacker gains control of the network, a cyber-defense technique is in place to mitigate the impact of the cyber-attack. This additional protection layer was developed based on an innovative concept known as Digital Twin (DT). A DT, in this case, replicates an Active-Neutral Point Clamped (ANPC) inverter and was designed using a hardware language known as VHDL (Very High-Speed Integrated Circuit Hardware Description Language) and applied to Field-Programmable-GateArray (FPGA). The DT is embedded within the FPGA and contained in a controller board, the UCB (Unified Controller Board), developed by the University of Arkansas electrical engineering team. This UCB also contains two Digital Signal Processors (DSPs) responsible for generating associated signals to control an authentic physical inverter. These DSP signals are received and processed by the FPGA that implements the DT of an ANPC; in other words, it simulates in realtime the expected output of an actual ANPC inverter using the signals from the DSP. When a new firmware is ready to be patched, the DT provides output signals simulating behavior that a real ANPC inverter would generate with the new firmware. The new firmware is tested to check if it meets all the operational requirements established using a Design-For-Trust technique (DFTr). If the new firmware fails in at least one of the DFT tests, it is considered malicious and must be rejected. This work is divided into sections, such as Background, which explains the pieces that were used and the strategy behind this work; Process and Procedure, which explains the methodology that was adopted to prove the reliability and effectiveness of this work; Results and Discussion, where the simulations and results are described and explained; followed by Conclusion and Future work section, which concludes this work and adds possible future projects to continue this work further.

do Amaral Custodio, Paulo Vitor↗

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗

Provision for Guaranteed Inertial Response in Diesel-Wind Systems via Model Reference Control

Frequency performance has been a crucial issue for islanded microgrids. On one hand, most distributed energy resources (DER) are converter-interfaced and do not inherently respond to frequency variations. On the other hand, current inertia emulation approach cannot provide guaranteed response. In this paper, a model reference control based inertia emulation strategy is proposed for the diesel-wind systems. Desired inertia can be precisely emulated through the proposed strategy. A typical frequency response model with parametric inertia is set to be the reference model. A measurement at a specific location delivers the information about the disturbance acting on the diesel-wind system to the reference model. The objective is for the speed of the diesel generator to track the reference so that the desired inertial response is realized. In addition, polytopic parameter uncertainty will be considered. The control strategy is configured in different ways according to different operating points. The parameters of the reference model are scheduled to ensure adequate frequency response under a pre-defined worst case. The controller is implemented in a nonlinear three-phase diesel-wind system fed microgrid using the Simulink software platform. Lastly, the results show exact synthetic inertia is emulated and adequate frequency response is achieved.

24 POWER TRANSMISSION AND DISTRIBUTION↗

MODELING AND PARAMETRIC STUDY OF END-GAS AUTOIGNITION TO ALLOW THE REALIZATION OF ULTRA-LOW EMISSIONS, HIGH-EFFICIENCY HEAVY-DUTY SPARK-IGNITED NATURAL GAS ENGINES

Engine knock and misfire are barriers to pathways leading to high-efficiency Spark-Ignited (SI) Natural Gas (NG) engines. The general tendency to knock is highly dependent on engine operating conditions and the fuel reactivity. The problem is further complicated by the low emission limits and the wide range of chemical reactivity in pipeline-quality natural gas. Depending on the region and the source of the natural gas, its reactivity, described by its Methane Number (MN), which is analogous to the Octane Number for liquid SI fuels, can span from 65 to 95. In order to realize diesel-like efficiencies, SI NG engines must be designed to operate at high Brake Mean Effective Pressures (BMEP), near or beyond knock limits, over a wide range of fuel reactivity. This requires a deep understanding of the combustion-engine interactions pertaining to flame propagation and End-Gas Autoignition (EGAI), i.e., the autoignition of the unburned gas (end gas) ahead of the flame front. However, EGAI, if controlled, provides an opportunity to increase SI NG engine efficiency by increasing the combustion rate and the total fraction of burned fuel, mitigating the effects of the slow flame speeds characteristic of natural gas fuels, which generally reduce BMEP and increase unburned hydrocarbon emissions. For this reason, to realize diesel-like efficiencies and ultra-low emissions on SI NG engines, this work proposes the study of the main parameters influencing the modeling and prediction of NG EGAI to allow for its control. In this work, a novel EGAI detection and onset determination method was developed to reliably quantify EGAI for data analysis and engine control. The new method allowed the prediction of EGAI on SI NG engines without the need to use engine- and operating-condition-dependent thresholds and reduced the error in quantifying the fraction of the total energy released by the EGAI event by up to 40%pts. One- and three-dimensional engine models were then developed to study the engine/fuel interactions that lead to NG EGAI and its performance benefits. These models, although having decent agreement with experimental data, showed the need to account for NOx chemistry when predicting NG EGAI due to a consistently later prediction of the EGAI onset (~1.65 crank-angle degrees) and thus, a new reduced chemical mechanism for real NG fuels was developed containing NOx chemistry. The new reduced mechanism improved the EGAI onset prediction agreement to within ±0.5 crank-angle degrees and decreased simulation time during combustion by nearly 50% when using the further reduced AREIS50NOx chemical mechanism. These models were then used to study the role of NG composition on EGAI, evaluate the engine/fuel interactions leading to NG EGAI, and perform engine optimization while leveraging EGAI to increase thermal efficiency. Piston design optimization combined with a Controlled EGAI (C-EGAI) combustion mode allowed a Heavy-Duty (HD) SI NG engine to operate at diesel-like efficiencies, i.e., Brake Thermal Efficiency (BTE) ≥44%. Experimental and modeling data analysis revealed that earlier and faster heat release increases combustion efficiency by an average of 1%pts, increases work transferred to the piston resulting in a decrease in exhaust losses by 50% depending on the engine operating condition while slightly increasing heat losses. Finally, the simulation results revealed an opportunity to further enhance the BTE (up to 50%) by enabling C-EGAI combustion at leaner conditions, λ=1.4-1.6.

Bestel, Diego Bernardi↗

Manipulating nanoscale structure to control functionality in printed organic photovoltaic, transistor and bioelectronic devices

Printed electronics is simultaneously one of the most intensely studied emerging research areas in science and technology and one of the fastest growing commercial markets in the world today. For the past decade the potential for organic electronic (OE) materials to revolutionize this printed electronics space has been widely promoted. Such conviction in the potential of these carbon-based semiconducting materials arises from their ability to be dissolved in solution, and thus the exciting possibility of simply printing a range of multifunctional devices onto flexible substrates at high speeds for very low cost using standard roll-to-roll printing techniques. However, the transition from promising laboratory innovations to large scale prototypes requires precise control of nanoscale material and device structure across large areas during printing fabrication. Maintaining this nanoscale material control during printing presents a significant new challenge that demands the coupling of OE materials and devices with clever nanoscience fabrication approaches that are adapted to the limited thermodynamic levers available. In this review we present an update on the strategies and capabilities that are required in order to manipulate the nanoscale structure of large area printed organic photovoltaic (OPV), transistor and bioelectronics devices in order to control their device functionality. This discussion covers a range of efforts to manipulate the electroactive ink materials and their nanostructured assembly into devices, and also device processing strategies to tune the nanoscale material properties and assembly routes through printing fabrication. The review finishes by highlighting progress in printed OE devices that provide a feedback loop between laboratory nanoscience innovations and their feasibility in adapting to large scale printing fabrication. The ability to control material properties on the nanoscale whilst simultaneously printing functional devices on the square metre scale is prompting innovative developments in the targeted nanoscience required for OPV, transistor and biofunctional devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Operando visualization of porous metal additive manufacturing with foaming agents through high-speed x-ray imaging

Porous metals find extensive applications in soundproofing, filtration, catalysis, and energy-absorbing structures, thanks to their unique internal pore structure and high specific strength. In recent years, there has been an increasing interest in fabricating porous metals using additive manufacturing (AM), leveraging its unique advantages, including improved design freedom, spatial material control, and cost-effective small-batch production. In this study, we conducted pioneering operando visualization of AM porous metal using a laser powder bed fusion (L-PBF) setup combined with a high-speed synchrotron x-ray imaging system. Single track printing experiments using Ti6Al4V (Ti64) combined with titanium hydride (TiH 2 ) and sodium carbonate (Na 2 CO 3 ) as foaming agents, with varying mixing ratios were performed under different processing conditions. Here. the results elucidate the dynamic development of porosity formation. The average pore size is significantly influenced by the particle size of foaming agents when pore coalescence is absent. For all foaming agent content tested in the current study, the number of pores is found to be more sensitive to changes in laser power than in laser scanning speed. Increasing linear energy density (increasing laser power or reducing laser scanning speed) promotes the foaming agent activation thereby porosity formation. However, high linear energy density skews pore distribution towards the surface despite forming deeper melt pools. In addition, the impact of additional factors including foaming agent's laser absorptivity and decomposition kinetics with respect to AM time scales should be carefully considered to avoid ineffective activation of foaming agents during the AM of porous metals.

36 MATERIALS SCIENCE↗

Exploring electron-beam induced modifications of materials with machine-learning assisted high temporal resolution electron microscopy

Directed atomic fabrication using an aberration-corrected scanning transmission electron microscope (STEM) opens new pathways for atomic engineering of functional materials. In this approach, the electron beam is used to actively alter the atomic structure through electron beam induced irradiation processes. One of the impediments that has limited widespread use thus far has been the ability to understand the fundamental mechanisms of atomic transformation pathways at high spatiotemporal resolution. Here, we develop a workflow for obtaining and analyzing high-speed spiral scan STEM data, up to 100 fps, to track the atomic fabrication process during nanopore milling in monolayer MoS 2 . An automated feedback-controlled electron beam positioning system combined with deep convolution neural network (DCNN) was used to decipher fast but low signal-to-noise datasets and classify time-resolved atom positions and nature of their evolving atomic defect configurations. Through this automated decoding, the initial atomic disordering and reordering processes leading to nanopore formation was able to be studied across various timescales. Using these experimental workflows a greater degree of speed and information can be extracted from small datasets without compromising spatial resolution. This approach can be adapted to other 2D materials systems to gain further insights into the defect formation necessary to inform future automated fabrication techniques utilizing the STEM electron beam.

36 MATERIALS SCIENCE↗

Electronic Transport and Ferroelectric Switching in Ion-Bombarded, Defect-Engineered BiFeO 3 Thin Films

Despite continued interest in the multiferroic BiFeO 3 for a diverse range of applications, use of this material is limited by its poor electrical leakage. This work demonstrates some of the most resistive BiFeO 3 thin films reported to date via defect engineering achieved via high-energy ion bombardment. High leakage in as-grown BiFeO 3 thin films is shown to be due to the presence of moderately shallow isolated trap states, which form during growth. Ion bombardment is shown to be an effective way to reduce this free carrier transport (by up to ≈4 orders of magnitude) by trapping the charge carriers in bombardment-induced, deep-lying defect complexes and clusters. The ion bombardment is also found to give rise to an increased resistance to switching as a result of an increase in defect concentration. This study demonstrates a systematic ion-dose-dependent increase in the coercivity, extension of the defect-related creep regime, increase in the pinning activation energy, decrease in the switching speed, and broadening of the field distribution of switching. Ultimately, the use of such defect-engineering routes to control materials will require identification of an optimum range of ion dosage to achieve maximum enhancement in resistivity with minimum impact on ferroelectric switching.

36 MATERIALS SCIENCE↗

TORBEAM 2.0, a paraxial beam tracing code for electron-cyclotron beams in fusion plasmas for extended physics applications

The paraxial WKB code TORBEAM (Poli, 2001) is widely used for the description of electron-cyclotron waves in fusion plasmas, retaining diffraction effects through the solution of a set of ordinary differential equations. With respect to its original form, the code has undergone significant transformations and extensions, in terms of both the physical model and the spectrum of applications. The code has been rewritten in Fortran 90 and transformed into a library, which can be called from within different (not necessarily Fortran-based) workflows. The models for both absorption and current drive have been extended, including e.g. fully-relativistic calculation of the absorption coefficient, momentum conservation in electron–electron collisions and the contribution of more than one harmonic to current drive. The code can be run also for reflectometry applications, with relativistic corrections for the electron mass. Formulas that provide the coupling between the reflected beam and the receiver have been developed. Accelerated versions of the code are available, with the reduced physics goal of inferring the location of maximum absorption (including or not the total driven current) for a given setting of the launcher mirrors. Optionally, plasma volumes within given flux surfaces and corresponding values of minimum and maximum magnetic field can be provided externally to speed up the calculation of full driven-current profiles. These can then be employed in real-time control algorithms or for fast data analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Trends in best-in-class energy-efficient technologies for room air conditioners

Improving the efficiency of room air conditioners (RACs) could provide significant energy and associated emissions savings, particularly in emerging economies with hot climates where the cooling demand is expected to increase dramatically. To help accelerate efficiency improvements, this study identifies “best-in-class” high-efficiency RAC components and products. The findings show that manufacturers tend to minimize manufacturing costs by using RAC designs that are readily available or standardized to their production, and they share components across various models. High-efficiency RAC models use advanced compressor technologies optimized at a low frequency, large heat exchangers with thermodynamically effective materials and designs, highly efficient direct current fan motors, advanced metering devices, and smart sensors for temperature and humidity control. Recently RAC manufacturers have been improving seasonal efficiency – better reflecting part-load operation – especially via variable-speed (inverter) drives for compressor motors. Recent highest-efficiency RAC models use low global warming potential (GWP) refrigerants, having transitioned from conventional high-GWP refrigerants, in regions where RACs that use these low-GWP refrigerants are commercially available. Recently demonstrated innovative technologies show trends toward smart hybrid designs, evaporative cooling, and solid-state materials beyond the conventional vapor-compression technology. This information could help policymakers improve their RAC market-transformation programs to align with the most-efficient global technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fluid‐Driven Cohesive Strengthening: Critical Role of Reaction Kinetics as the Determinant for Frictional Stability

After an earthquake, faults in the Earth's crust lock up and slowly regain strength. This process, called fault healing, plays a key role in determining how often earthquakes happen and how large they can be. While scientists know that healing involves both mechanical friction and chemical changes in rocks, it has been unclear how these processes work together, especially over shorter timescales in laboratory settings. In our study, we ran controlled experiments on the mineral anhydrite under different fluid conditions. We found that the presence and pressure of water speeds up fault healing by triggering a chemical reaction that strengthens the fault over time. This strengthening makes the fault more resistant to sliding, which could delay future earthquakes—but also sets the stage for larger ones when they do occur. We propose a model that combines frictional and chemical processes to explain this water‐activated, time‐dependent healing. Importantly, our results show that even faults typically considered stable could still produce earthquakes if they undergo sufficient chemical healing. This has broad implications for understanding where and when earthquakes might strike, especially in fluid‐rich environments such as subduction zones and geoenergy settings.

Affinito, R [Pennsylvania State Univ., University ↗

Note: Fast imaging of DNA in atomic force microscopy enabled by a local raster scan algorithm

Approaches to high-speed atomic force microscopy typically involve some combination of novel mechanical design to increase the physical bandwidth and advanced controllers to take maximum advantage of the physical capabilities. For certain classes of samples, however, imaging time can be reduced on standard instruments by reducing the amount of measurement that is performed to image the sample. One such technique is the local raster scan algorithm, developed for imaging of string-like samples. Here we provide experimental results on the use of this technique to image DNA samples, demonstrating the efficacy of the scheme and illustrating the order-of-magnitude improvement in imaging time that it provides.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Laboratory strains of Bacillus anthracis lose their ability to rapidly grow and sporulate compared to wildlife outbreak strains

Bacillus anthracis is the causative agent of anthrax in animals and humans. The organism lies in a dormant state in the soil until introduced into an animal via, ingestion, cutaneous inoculation or inhalation. Once in the host, spores germinate into rapidly growing vegetative cells elaborating toxins. When animals die of anthrax, vegetative bacteria sporulate upon nutrient limitation in the carcass or soil while in the presence of air. After release into the soil environment, spores form a localized infectious zone (LIZ) at and around the carcass. Laboratory strains of B. anthracis produce fewer proteins associated with growth and sporulation compared to wild strains isolated from recent zoonotic disease events. We verified wild strains grow more rapidly than lab strains demonstrating a greater responsiveness to nutrient availability. Sporulation was significantly more rapid in these wild strains compared to lab strains, indicating wild strains are able to sporulate faster due to nutrient limitation while laboratory strains have a decrease in the speed at which they utilize nutrients and an increase in time to sporulation. These findings have implications for disease control at the LIZ as well as on the infectious cycle of this dangerous zoonotic pathogen.

59 BASIC BIOLOGICAL SCIENCES↗

Development and application of processing and process control for nano-composite materials for lithium ion batteries (CRADA Final Report)

Oak Ridge National Laboratory and A123 Systems, Inc. collaborated on this project to develop a better understanding, quality control procedures, and safety testing for A123 System’s nanocomposite separator (NCS) technology which is a cell based patented technology and separator. NCS demonstrated excellent performance. x3450 prismatic cells were shown to survive >8000 cycles (1C/2C rate) at room temperature with greater than 80% capacity retention with only NCS present as an alternative to conventional polyolefin. However, for a successful commercialization, the coating conditions required to provide consistent and reliable product had not been optimized and QC techniques for being able to remove defective material before incorporation into a cell had not been developed. The work outlined in this report addresses these latter two points. First, experiments were conducted to understand temperature profiles during the different drying stages of the NCS coating when applied to both anode and cathode. One of the more interesting discoveries of this study was the observation of the large temperature decrease experienced by the wet coating between the end of the infrared (IR) drying stage and the beginning of the exposure to the convection drying oven. This is not a desirable situation as the temperature gradient could have a deleterious effect on coating quality. Based on this and other experimental data a radiative transfer model was developed for IR heating that also included a mass transfer module for drying. This will prove invaluable for battery coating optimization especially where IR drying is being employed. A stress model was also developed that predicts that under certain drying conditions tensile stresses are formed in the coating which could lead to cracking that is sometimes observed after drying is complete. Prediction of under what conditions these stresses form is vital to improving coating quality. In addition to understanding the drying process other parameters such as slurry quality and equipment optimization were examined. Removal of particles and gels by filtering, control of viscosity by %solids and mixing adjustments, removal of trapped gas in the slurry and modification of coater speed and slot die gap were all found to be important for producing uniform and flaw-free coatings. Second, an in-line Hi-Pot testing method has been developed specifically for NCS that will enable detection of coating flaws that could lead to soft or hard electrical shorts within the cell. In this way flawed material can be rejected before incorporation into the cell thus greatly reducing the amount of scrap that is generated. Improved battery safety is an extremely important benefit of NCS. Evaluation of battery safety is usually accomplished by conducting a variety of tests including nail penetration, hot box, over charge, etc. For these tests entire batteries must be built but the resultant temperature and voltage responses reveal little about the breakdown mechanism. In this report is described a pinch test which is used to evaluate NCS quality at various stages including coated anode and cathode as well as assembled cell. Coupled with post-microscopic examination of the damaged ‘pinch point’ test data can assist in the coating optimization from an improved end-use standpoint. As a result of this work two invention disclosures, one for optimizing drying methodology and the other for an in-line system for flaw detection, have been filed. In addition, 2 papers are being written for submission to peer-reviewed journals.

25 ENERGY STORAGE↗