Anomalous Self-Optimizing Microporous Graphene-Based Lithium-ion Battery Anode from Laser Activation
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Zhang, Binghao↗
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Results for “Optimal process control”
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Solvent-Dependent Dynamics of Cellulose Nanocrystals in Process-Relevant Flow Fields
Flow-assisted alignment of anisotropic nanoparticles is a promising route for the bottom-up assembly of advanced materials with tunable properties. While aligning processes could be optimized by controlling factors such as solvent viscosity, flow deformation, and the structure of the particles themselves, it is necessary to understand the relationship between these factors and their effect on the final orientation. In this study, we investigated the flow of surface-charged cellulose nanocrystals (CNCs) with the shape of a rigid rod dispersed in water and propylene glycol (PG) in an isotropic tactoid state. In situ scanning small-angle X-ray scattering (SAXS) and rheo-optical flow-stop experiments were used to quantify the dynamics, orientation, and structure of the assigned system at the nanometer scale. The effects of both shear and extensional flow fields were revealed in a single experiment by using a flow-focusing channel geometry, which was used as a model flow for nanomaterial assembly. Due to the higher solvent viscosity, CNCs in PG showed much slower Brownian dynamics than CNCs in water and thus could be aligned at lower deformation rates. Moreover, CNCs in PG also formed a characteristic tactoid structure but with less ordering than CNCs in water owing to weaker electrostatic interactions. The results indicate that CNCs in water stay assembled in the mesoscale structure at moderate deformation rates but are broken up at higher flow rates, enhancing rotary diffusion and leading to lower overall alignment. Albeit being a study of cellulose nanoparticles, the fundamental interplay between imposed flow fields, Brownian motion, and electrostatic interactions likely apply to many other anisotropic colloidal systems.
36 MATERIALS SCIENCE↗
Effects of Heat Treatment on Microstructure, Thermal Transport and Stability in SRF Niobium
Efficient heat transfer and thermal stability are critical for preventing thermal quench and ensuring the high performance and reliability of superconducting radiofrequency (SRF) cavities, especially under high RF fields. In this article, we investigate thermal conductivity and heat capacity of high-purity cold-worked niobium used in SRF applications, with a particular focus on the effects of high-temperature heat treatments. Our measurements reveal a pronounced sensitivity of thermal transport and thermodynamic properties to the underlying microstructure such as grain size and dislocation density. The results show the critical role of controlled heat treatment processes in optimizing the thermal performance of SRF niobium, providing valuable insights for improving cavity fabrication and processing.
36 MATERIALS SCIENCE↗
Preliminary Look at the LBEG & MPEG Beam Transmissions between HPSim and Operation Data
This report summarizes recent work on estimating the transmission of LANSCE H- beams from the end of the present DTL to both the PSR stripper foil (LBEG) and WNR target 4 (MPEG). The LBEG beam might be considered a more typical LINAC beam and lends itself to continuous monitoring of transmission through the various stages of the accelerator. For the MPEG, however, the widely-spaced micropulses and lack of the requisite sensitivity current monitors throughout the accelerator make these measurements extremely difficult and more uncertain. Therefore, to assist in estimating the MPEG beam transmission, beam-dynamics simulations using HPSim were employed. These beam transmission estimates from the end of the Drift Tube Linac (DTL) to Target 4 (MPEG) and the PSR stripper foil (LBEG) are vital to determine the charge requirements for LAMP’s front end. In this technote, we demonstrate three major efforts in determining the transmission: (1) Convert the WNR beamline lattice from TRANSPORT to HPSim for use in the simulation; (2) Simulate the optimization process in the Central Control Room (CCR) that brings down the losses by up to a factor of 4000 between the end of the initial physics-based tuneup phase and production beam operation; (3) Analyze operational data to deduce measured transmissions. Table 1 shows the estimated losses with HPSim and operational analysis. Finally, a better measurement and other improvements to refine the results are also proposed.
43 PARTICLE ACCELERATORS↗
In-Situ Powder-Directed Energy Process Control for Additively Manufactured Multi-Layer, Functionally Graded Components
Coatings and cladding can experience damage in harsh environments: Erosion Oxidation Delamination External mechanical damage Radiation induced damage Functionally Graded Materials (FGMs) were primarily designed to reduce thermal stress in thermal barrier coatings (TBCs), but can produce coatings which resist a variety of material damage (corrosion, surface damage, diffusion) Powder-fed DED with multiple independent feeders allows for AM FGMs, and provides robust control over process parameters to optimize microstructure and performance. FGMs have a great opportunity for applications in energy applications as a strategy to increase plant efficiency and lifetime.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Feedforward control of thermal history in laser powder bed fusion: Toward physics-based optimization of processing parameters
Not Available
36 MATERIALS SCIENCE↗
Control co-design of commercial building chiller plant using Bayesian optimization
Not Available
Bhattacharya, Arnab↗
Correlating processing variables to material properties in recycled polypropylene: A data‐driven approach
Abstract Polypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% of solid waste PP being reprocessed. Mechanical recycling through extrusion is the most practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence the thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how these factors shape the properties of recycled PP, using conditions designed to mimic post‐industrial recycled (PIR) scrap. Residence time was measured using colorimetric tracking and correlated with molecular weight, viscosity, and mechanical properties over multiple extrusion cycles. Data‐driven modeling, including response surface methodology, support vector machines, and artificial neural networks, identified processing temperature as the dominant factor in material degradation, followed by residence time. Mechanical properties remained stable, while viscosity decreased predictably with increasing residence time. By linking reprocessing conditions to property evolution, this study provides a method to optimize processing parameters and reduce variability in recycled PP. These findings help manufacturers improve process control, making recycled PP more predictable for reuse in manufacturing. Highlights Study of PIR‐quality PP without additives or compatibilizers. Residence time analysis shows processing temperature drives PP property changes. Mark‐Houwink enables quick molecular weight checks for quality control. Models predict mechanical and rheological shifts in reprocessing. Optimized processing parameters minimize property degradation in recycling.
Estela‐García, John E. [Polymer Engineering Center↗
Room-temperature fabrication of garnet-type solid-electrolyte: Optimizing particle size for high ionic conductivity
Dense and uniform Li 6.25 Al 0.25 La 3 Zr 2 O 12 (Al-doped LLZO) solid-electrolyte film of ~24 µm thickness is successfully fabricated by room temperature aerosol deposition (AD) method. The process optimization study revealed that careful control of particle size and morphology is one of critical determinants in the development of a compact AD membrane. Notably, our method facilitated an impressive ionic conductivity of approximately 10 –5 S cm –1 , bypassing the necessity for post-annealing processes, a milestone in itself. However, it is hypothesized that the attained conductivity is somewhat restrained by factors such as smaller grain size and potential surface degradation due to moisture exposure during fabrication, indicating avenues for further research. Looking forward, detailed investigations into the film's microstructure and its impact on transport properties will be a focal point, alongside potential enhancements through post-annealing and particle coating strategies. Finally, this research hints at a promising trajectory for the development of high-efficiency solid-state battery technology.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Accelerated CO2 Storage Optimization Using Multi-Resolution Fourier Neural Operator at the Illinois Basin Decatur Project (IBDP)
This paper presents a deep learning-based approach for optimizing CO2 injection in carbon capture and storage (CCS) operations. We developed a multi-resolution machine learning model to significantly reduce data generation costs. Utilizing this proxy model, we implemented a multi-objective genetic algorithm to optimize well control during the CO2 injection process. The proposed approach was applied to the Illinois Basin Decatur Project (IBDP), successfully optimizing the CO2 injection schedule based on three key objectives: maximizing the amount of CO2 stored, maximizing sweep efficiency, and minimizing pressure increase. The use of the proxy model accelerated the optimization workflow by two orders of magnitude, while the cost of data generation for the proxy model was reduced by 90% by utilizing a coarse-scale model.
accelerated CO2 storage optimization↗
Optimization of nutrient utilization efficiency and productivity for algal cultures under light and dark cycles using genome-scale model process control
Abstract Algal cultivations are strongly influenced by light and dark cycles. In this study, genome-scale metabolic models were applied to optimize nutrient supply during alternating light and dark cycles of Chlorella vulgaris . This approach lowered the glucose requirement by 75% and nitrate requirement by 23%, respectively, while maintaining high final biomass densities that were more than 80% of glucose-fed heterotrophic culture. Furthermore, by strictly controlling glucose feeding during the alternating cycles based on model-input, yields of biomass, lutein, and fatty acids per gram of glucose were more than threefold higher with cycling compared to heterotrophic cultivation. Next, the model was incorporated into open-loop and closed-loop control systems and compared with traditional fed-batch systems. Closed-loop systems which incorporated a feed-optimizing algorithm increased biomass yield on glucose more than twofold compared to standard fed-batch cultures for cycling cultures. Finally, the performance was compared to conventional proportional-integral-derivative (PID) controllers. Both simulation and experimental results exhibited superior performance for genome-scale model process control (GMPC) compared to traditional PID systems, reducing the overall measured value and setpoint error by 80% over 8 h. Overall, this approach provides researchers with the capability to enhance nutrient utilization and productivity of cell factories systematically by combining genome-scale models and controllers into an integrated platform with superior performance to conventional fed-batch and PID methodologies.
59 BASIC BIOLOGICAL SCIENCES↗
Autonomous online optimization of a closed-circuit reverse osmosis system
As freshwater becomes increasingly scarce, many industrial and municipal water utilities look at premise-scale water treatment and reuse to meet water demand. Closed-circuit reverse osmosis (CCRO) has been proposed as a promising process design to do so. This sequencing batch process enables operation at higher brine salinity levels by means of a recycle flow. Optimal operation requires that the maximum salinity level at the membrane surface represents an optimal trade-off between brine disposal costs and energy efficiency. This maximum salinity level may change over time as the feed water composition changes and electricity markets fluctuate. In this article, we present the results of the experimental evaluation of an automatic technique for continuous online optimization, known as extremum seeking control. This technique has a long history in the process control community but has received little traction so far in the water industry. We modify this technique to enable its use for online optimization of CCRO, specifically to account for its sequential batch operation. We challenge the optimization schemes through several experimental tests and illustrate the advantages and drawbacks of extremum-seeking control.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Manufacturing Science
The Manufacturing Science area of leadership spans the application of fundamental science research and development activities to understand the critical steps in manufacturing processes for the purposes of control and optimization. Although manufacturing is an applied area of research, fundamental science underpins our knowledge of both traditional and transformational manufacturing processes. For example, casting, welding, and many modern additive manufacturing processes that see wide use are broadly classified as solidification processes, with material transitioning from liquid to solid phases upon cooling from higher temperature. However, our understanding of the detailed physics involved in such processes is incomplete, and solidification remains a grand challenge for materials science. To enable adoption of transformative fabrication processes or to accelerate development of traditional ones, it is necessary to develop a detailed mechanistic understanding spanning multiple scales, starting with atomic building blocks (defects, interfaces, composition) and extending all the way up to macroscale performance in moderate and/or extreme environments.
36 MATERIALS SCIENCE↗
Understanding fundamental effects of Cu impurity in different forms for recovered LiNi 0.6 Co 0.2 Mn 0.2 O 2 cathode materials
When identifying and developing lithium ion battery recycling technologies, understanding the role of impurities is always a concern as they may have an impact on electrochemical performance, material stability, or lifetime for recovered active materials. In this work we show that Cu impurity in different forms could play very different roles on the recovered LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622). Cu metal impurity could easily short the cell, while Cu ion impurity could play a positive role due to partially substitution of the Ni 2+ sites to lower the cation mixing degree. In specific, NCM622 material with certain amount (0.34 at%) of Cu ion impurity delivers high initial specific charge/discharge capacity of 211.8 and 186.0 mAh g -1 at 0.05 C, which are 12.2 and 14.1 mAh g -1 higher than those of virgin NCM622 cathode. Moreover, a superior retention capacity of 171.3 mAh g -1 after 90 cycles at 0.33 C, and striking rate capability are achieved in this NCM622 cathode sample. These results clearly indicate that Cu metal impurity should be avoided and the ionic Cu impurity should be controlled with optimal concentration during recycling process for spent LIBs.
25 ENERGY STORAGE↗
Distributed fiber sensing systems for 3D combustion temperature field monitoring in coal-fired boilers using optically generated acoustic waves (Final Report)
In this project, we have developed and tested three kinds of fiber optic sensing systems for real time monitoring of temperature variations within an industrial scale boiler furnace. The fiber optic sensing systems target spatial and temporal distributions of high temperature profiles in a boiler furnace in fossil power plants. The reconstructed temperature profile will provide critical input for the control mechanisms to optimize the combustion process. This temperature profile will address the essential problem for fossil power plants in achieving higher efficiency and fewer pollutant emissions. Acoustic pyrometer systems have been used to reconstruct temperature field of power plant boilers based on measuring TOF (times-of-flight) of sound waves along some straight paths in a 2D cross-section of the boiler. In this project, optically generated acoustic signals from a fiber optic sensing system have replaced the acoustic signals generated from an electrical transducer. A 3D reconstruction algorithm replaced the previous 2D model. In this project, three kinds of fiber optic sensing systems have been developed and tested. They are fiber optic sensing system I, fiber optic sensing system II (Distributed Sensing System I) and fiber optic sensing system III (Distributed Sensing System II). For fiber optic sensing system I, the fiber optic ultrasound generator acts as a signal generator. A microphone, hydrophone or other electronic devices serve as a signal receiver. In this system, there are one generator and one receiver. Distance test, water temperature test, air temperature test, air temperature reconstruction, and GE ISBF pilot test were performed by Fiber optic sensing system I. The fiber optic sensing system I successfully detected temperature in all these tests. We got 2D temperature reconstruction results by using the fiber optic sensing system I and it matched the reference data. The fiber optic sensing system I successfully survived in GE ISBF boiler environment (480 °F). For fiber optic sensing system II (Distributed Sensing System I), it is an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Fiber Bragg Grating (FBG) and Fabry-Perot (FP) sensor act as a signal receiver. In this system, there is one generator and one receiver. Aluminum plate temperature test, furnace high temperature test, and GE ISBF pilot test were performed by the fiber optic sensing system II. Fiber optic sensing system II successfully detected the temperature in all these tests. The fiber optic sensing system II successfully survived at up to 700 °C furnace environment and 320 °C GE ISBF boiler environment. For fiber optic sensing system III (Distributed Sensing System II), it is also an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Multiple FP fiber sensors act as signal receivers. In this system, there is one generator and three receivers. Three GE ISBF pilot tests were performed by fiber optic sensing system III. The fiber optic sensing system III survived in the cold flow tests in GE’s ISBF pilot test facility. However, we didn’t get high temperature data by using this system since the nanosecond laser issues. During the period of the project, test trials, data simulation and algorithm optimization was performed successfully. For real time temperature field construction, the sampling rate must be fast enough to capture the field variations. The technology of Code-division multiple access (CDMA) is well studied which could allow parallel multiplexing, even if signals overlap in time or frequencies. Moreover, it has been known that extending the length of signal significantly improves SNR. For acoustic signals, these multiplexing techniques have also been widely used, mainly for sonar and acoustic communications. The CDMA modulation technique has been proposed and studied to guarantee high network throughput, low channel access delay and low energy consumption. We have studied the temperature field reconstruction using Gaussian Radial Basis Functions (GRBF)-based approximation approach. Reconstruction of 3D temperature field using Neural Networks with measured TOF and known propagation paths is feasible. 2D and 3D temperature field reconstruction simulation results are achieved. The milestone status is shown in Table 1. We finished milestone 1-8 and milestone 10. For milestone 9, we did three pilot tests by using the fiber optic sensing system III (Distributed Sensing System II) at GE Power. However, due to the failure of the ns laser, we did not get the temperature results. We conducted some additional tasks that were not originally proposed: 1) We fabricated a fiber optic sensing system I and did a pilot test based on this system. 2) In the proposal, we proposed two pilot tests at GE Power. In reality, we finished at least seven pilot tests at GE Power. GE Power has made a lot of efforts for supporting the pilot tests. 3) We got a simulation results based on CDMA. In summary, most of the tasks have been accomplished. The outcome of this project removed a few barriers that hinder the achievement of the final product of the distributed sensing systems. With the successful accomplishment of this project, a prototype of the fiber optic sensing system can be fabricated to attract more interests from companies and other funding agencies.
47 OTHER INSTRUMENTATION↗
Learning reference governor for cycle-to-cycle combustion control with misfire avoidance in spark-ignition engines at high exhaust gas recirculation–diluted conditions
Cycle-to-cycle feedback control is employed to achieve optimal combustion phasing while maintaining high levels of exhaust gas recirculation by adjusting the spark advance and the exhaust gas recirculation valve position. The control development is based on a control-oriented model that captures the effects of throttle position, exhaust gas recirculation valve position, and spark timing on the combustion phasing. Under the assumption that in-cylinder pressure information is available, an adaptive extended Kalman filter approach is used to estimate the exhaust gas recirculation rate into the intake manifold based on combustion phasing measurements. The estimation algorithm is adaptive since the cycle-to-cycle combustion variability (output covariance) is not known a priori and changes with operating conditions. A linear quadratic regulator controller is designed to maintain optimal combustion phasing while maximizing exhaust gas recirculation levels during load transients coming from throttle tip-in and tip-out commands from the driver. During throttle tip-outs, however, a combination of a high exhaust gas recirculation rate and an overly advanced spark, product of the dynamic response of the system, generates a sequence of misfire events. In this work, an explicit reference governor is used as an add-on scheme to the closed-loop system in order to avoid the violation of the misfire limit. The reference governor is enhanced with model-free learning which enables it to avoid misfires after a learning phase. Experimental results are reported which illustrate the potential of the proposed control strategy for achieving an optimal combustion process during highly diluted conditions for improving fuel efficiency.
42 ENGINEERING↗
Lamination of >21% Efficient Perovskite Solar Cells with Independent Process Control of Transport Layers and Interfaces
Transport layer and interface optimization is critical for improving the performance and stability of perovskite solar cells (PSCs) but is restricted by the conventional fabrication approach of sequential layer deposition. While the bottom transport layer is processed with minimum constraints, the narrow thermal and chemical stability window of the halide perovskite (HP) layer severely restricts the choice of top transport layer and its processing conditions. To overcome these limitations, we demonstrate lamination of HPs—where two transport layer-perovskite half-stacks are independently processed and diffusion-bonded at the HP-HP interface—as an alternative fabrication strategy that enables self-encapsulated solar cells. Power conversion efficiencies (PCE) of >21% are realized using cells that incorporate a novel transport layer combination along with dual-interface passivation via self-assembled monolayers, both of which are uniquely enabled by the lamination approach. This is the highest reported PCE for any laminated PSC encapsulated between glass substrates. We further show that this approach expands the processing window beyond traditional fabrication processes and is adaptable for different transport layer compositions. The laminated PSCs retained >75% of their initial PCE after 1000 h of 1-sun illumination at 40 °C in air using an all-inorganic transport layer configuration without additional encapsulation. Furthermore, a laminated 1 cm 2 device maintained a V oc of 1.16 V. Finally, the scalable lamination strategy in this study enables the implementation of new transport layers and interfacial engineering approaches for improving performance and stability.
14 SOLAR ENERGY↗
Designing Monte Carlo Simulation and an Optimal Machine Learning to Optimize and Model Space Missions
This paper investigates applying artificial intelligence (AI) algorithms to attitude control system of satellites to optimally tune the controller using high performance computing. This methodology is applied to the Virtual Telescope for X-ray Observation mission, which is a precise formation of two separate spacecraft observing multiple objects in the space in the X-ray domain. The mission is divided into phases based on the instrumentation and the mission goal. To reach an stable precise formation robust to stochastic slew and slew rate (i.e., Euler angles and angular velocities) in a minimal constrained time T , consumed energy of the attitude control system, denoted as E, and root-mean-square state error of attitude control system, denoted as e, are minimized. Monte-Carlo simulation is used for the sensitivity analysis of optimization and designing a controller. Deep neural networks (DNN), Gaussian processes (GP), and support vector regression (SVR) learn this optimization as a surrogate model, while their hyperparameters are optimized in a novel approach. THETA supercomputer at Argonne Leadership Computing Facility (ALCF) is used for optimizing the hyperparameters of DNN. The surrogate model meets the requirements of the mission, and it shows a better performance over the optimization and Monte-Carlo. The optimal DNN can satisfy the mission requirements e and T while reducing E for 90% compared to the other given methods.
42 ENGINEERING↗