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At least 73 records · Page 4

A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for understanding these methods generated. Existing Python programming packages for implementing each algorithm are acknowledged, and the model equations necessary for prediction are presented. A case study on a coal-fired power plant’s NO x emission rates is performed, directly comparing each modeling method’s performance on a mutual system. Each model is evaluated by its root mean squared error (RMSE) on out-of-sample future horizon predictions. Optimal hyperparameters are identified using either an exhaustive search or genetic algorithm. The top five model structures of each method are used to recursively predict future NO x emission rates over a 60-step time horizon. The RMSE at each future timestep is determined, and the recursive output prediction trends compared against measurements in time. The GRU neural network is identified as the best candidate for representing the system, demonstrating accurate and stable predictions across the future horizon by all considered models, while satisfactory performance was observed in several of the ARX/NARX formulations. Finally, these efforts have contributed 1) a concise resource of multiple proven dynamic machine learning methods, 2) a practical guide explaining the use of these methods, effectively lowering the “barrier-to-entry” of deploying such models in control systems, 3) a comparison study evaluating each method’s performance on a mutual system, 4) demonstration of accurate multi-timestep emissions modeling suitable for systems-level control, and 5) generalizable results demonstrating the suitability of each method for prediction over a multi-step future horizon to other complex dynamic systems.

42 ENGINEERING↗

Nucleation-mediated reshaping of facetted metallic nanocrystals: Breakdown of the classical free energy picture

Shape stability is key to avoiding degradation of performance for metallic nanocrystals synthesized with facetted non-equilibrium shapes to optimize properties for catalysis, plasmonics, and so on. Reshaping of facetted nanocrystals is controlled by the surface diffusion-mediated nucleation and growth of new outer layers of atoms. Here, Kinetic Monte Carlo (KMC) simulation of a realistic stochastic atomistic-level model is applied to precisely track the reshaping of Pd octahedra and nanocubes. Unexpectedly, separate constrained equilibrium Monte Carlo analysis of the free energy profile during reshaping reveals a fundamental failure of the classical nucleation theory (CNT) prediction for the reshaping barrier and rate. Why? Nucleation barriers can be relatively low for these processes, so the system is not locally equilibrated before crossing the barrier, as assumed in CNT. This claim is supported by an analysis of a first-passage problem for reshaping within a master equation framework for the model that reasonably captures the behavior in KMC simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Controlled Dielectric Breakdown to Form Pinhole Passivating Contacts

This contribution explores an alternate route to forming pinhole-based poly-Si/dielectric/c-Si passivating contacts. The method utilizes controlled dielectric breakdown or electroforming to produce nanoscale pinholes in a thick (non-tunnelling) dielectric which, when annealed, allows dopant atoms to pass from doped poly-Si through the pinholes and into the c-Si wafer, forming conductive pathways. We show that the pinholes lose passivation after electroforming but can be repassivated with a forming gas anneal. N-type contacts show contact resistivities of ~20 mOhm-cm2, but p-type contacts are ~100 mOhm-cm2. Devices show a distinct kink in the J-V curve indicative of a barrier to transport. The method can be expanded to optimized dielectric passivation stacks (not just thin, single layers) and can be formed in parallel over the faces of the wafer in selected areas (pinholes only under the grid lines).

CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SU↗

Essential barrier height and a probabilistic approach in characterizing potential landscape

In this work we propose a probabilistic approach to investigate the shape of landscapes of multi-dimensional potential functions. Under a suitable coupling scheme, two copies of the overdamped Langevin dynamics associated with the potential function are coupled, and the coupling times are collected. Assuming a set of intuitive yet technically challenging conditions on the coupling scheme, it is shown that the tail distributions of the coupling times exhibit qualitatively different dependencies on the noise magnitude for single-well versus multi-well potential functions. More specifically, for convex single-well potentials, the negative tail exponent of the coupling time distribution is uniformly bounded away from zero by the convexity parameter and is independent of the noise magnitude. In contrast, for multi-well potentials, the negative tail exponent decreases exponentially as the noise vanishes, with the decay rate governed by the essential barrier height, a quantity introduced in this paper to characterize the non-convex nature of the potential function. Numerical investigations are conducted for a variety of examples, including the Rosenbrock function, interacting particle systems, and loss functions arising in artificial neural networks. These examples not only illustrate the theoretical results in various contexts but also provide crucial numerical validation of the conjectured assumptions, which are essential to the theoretical analysis yet lie beyond the reach of standard technical tools.

97 MATHEMATICS AND COMPUTING↗

Lowering the barrier to access information-rich transient kinetic data for machine learning methods

Transient kinetic data contain a wealth of information about intrinsic features of a catalyst as well as the reaction mechanism. Currently, high volume transient data is underutilized, and data science methods could both increase the value of information that can be extracted from this data, integrate experimental with theoretical data sources, and accelerate the pace of catalyst technology advancement. Transient kinetic characterizations with simple probe molecules exhibiting reversible adsorption, irreversible adsorption and bulk-surface diffusion are presented as training components for similar experiments with more complex surface reactions. In conclusion, by increasing the availability and accessibility of transient kinetic data through details of its structure and acquisition, we aim to decrease the barrier for data scientists to apply machine learning methods to this valuable data source.

Catalysis↗

Uncovering the predictive pathways of lithium and sodium interchange in layered oxides

Ion exchange is a powerful method to access metastable materials with advanced functionalities for energy storage applications. However, high concentrations and unfavourably large excesses of lithium are always used for synthesizing lithium cathodes from parent sodium material, and the reaction pathways remain elusive. Here, using layered oxides as model materials, we demonstrate that vacancy level and its corresponding lithium preference are critical in determining the accessible and inaccessible ion exchange pathways. Taking advantage of the strong lithium preference at the right vacancy level, we establish predictive compositional and structural evolution at extremely dilute and low excess lithium based on the phase equilibrium between Li 0.94 CoO 2 and Na 0.48 CoO 2 . Such phase separation behaviour is general in both surface reaction-limited and diffusion-limited exchange conditions and is accomplished with the charge redistribution on transition metals. Guided by this understanding, we demonstrate the synthesis of Na y CoO 2 from the parent Li x CoO 2 and the synthesis of Li 0.94 CoO 2 from Na y CoO 2 at 1-1,000 Li/Na (molar ratio) with an electrochemical assisted ion exchange method by mitigating the kinetic barriers. Our study opens new opportunities for ion exchange in predictive synthesis and separation applications. Ion exchange is a powerful method to access metastable materials for energy storage, but identifying lithium and sodium interchange in layered oxides remains challenging. Using such model materials, vacancy level and corresponding lithium preference are shown to be crucial for ion exchange pathway accessibility.

25 ENERGY STORAGE↗

Portable fiber optic sensor for rare earth elements and other critical metals using photoluminescence methods

Rare earth elements and other metals are vital to a range of technologies that are used in the energy and defense sectors. However, monopolistic market conditions have caused significant concern over the stability of the critical metal supply chain, and this has spurred extensive efforts in many nations to produce these metals domestically, both from conventional sources such as mining and well as from unconventional sources such as coal and its utilization byproducts. Slow and expensive characterization methods pose a significant barrier for both metals prospecting and process monitoring. A promising solution to this challenge is the development of highly sensitive luminescent sensors for metals, which can offer low costs, portability, and sensitivity. Anionic zinc adeninate metal-organic frameworks (BioMOFs) are known to distinguishing and detect part-per-billion levels of terbium, europium, samarium, and dysprosium in water by sensitizing the narrow, element-specific emission bands from these lanthanides. Here, a BioMOF material is immobilized onto a large diameter, solarization-resistant fiber optic tip integrated with a portable, low-cost spectrometer for rare earth element sensing. Immobilizing the sensing material on fiber instead of dispersing the sensing material in solution offers several advantages: it facilitates solvent removal, which enhances luminescent signal from the sensitized lanthanides, and it also allows the BioMOF to be recycled for multiple uses. The sensing system was deployed on a simulated process stream and exhibited qualitative agreement with inductively-coupled plasma mass spectrometry for terbium and europium detection, highlighting the potential for the sensing system to be deployed for real-world applications. By using different sensing materials, the same portable sensor may be deployed to detect other energy relevant metals such as cobalt, providing a cost-effective and sensitive platform for critical metal characterization.

Crawford, Scott↗

Method for forming a temperature sensing layer within a thermal barrier coating

A thermal barrier coated component, such as a turbine blade formed from a superalloy substrate, includes a thermal barrier coating applied onto the substrate. A metallic bond coat layer is on the substrate and includes rare-earth luminescent dopants. A ceramic top coat layer is on the bond coat layer. A temperature sensing thermally grown oxide (TGO) layer is formed at the interface of the bond coat layer and ceramic top coat layer. The temperature sensing TGO layer includes grown rare-earth luminescent ions migrated from the metallic bond coat layer in an amount sufficient to enable luminescence sensing of the TGO layer for real-time phosphor thermometry temperature measurements at the TGO layer.

Fouliard, Quentin↗

Developing an intrinsically secure information barrier for arms control verification through machine learning

Near-term solutions are needed to allow for flexible engagement in future nuclear arms control discussions. This project developed a method for implementing an information barrier (IB) on commercial systems, shortening the research and development lifecycle for warhead verification technologies while offering improved and inherently flexible capabilities. The crux of the verification challenge remains the difficulty in developing an authenticatable IB which prevents sensitive host country information from inadvertent transmission to an inspector. Many concepts for IB’s rely on dedicated “trusted” processor modules developed with dedicated custom radiation detection systems and associated algorithms. Without a priori knowledge of the treaty item, the parameter space for measurements can be nearly infinite and robustness against spoofing without the ability to view sensitive data is key. This project has produced an unclassified framework capable of ingesting data from common gamma detectors and identifying the presence of weapons grade nuclear material at over 90% accuracy.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Application of Self-Interaction Corrected Density Functional Theory to Early, Middle, and Late Transition States

Density functional theory (DFT)-based methods often significantly underpredict chemical reaction barriers compared with experiments because of the tendency of DFT to over-stabilize transition states with stretched bonds due to the impact of unphysical electron self-interaction. But many reactions have early or late transition states where the transition state geometry closely resembles the reactants or products, respectively. The role of self-interaction in those cases is not known. Here we compare the performance of DFT with and without self-interaction correction (SIC) for describing the hydrogenation of CO and CO 2 catalyzed by a Lewis acid-base pair incorporated onto an aromatic cluster, using CCSD(T) results for reference. The three elementary steps in these reactions consist of an early, a middle, and a late transition. Our results show that the Perdew-Zunger SIC (PZ-SIC), implemented in the Fermi-L Lowdin orbital SIC (FLO-SIC) approach, qualitatively improves the description of the forward and reverse reaction barriers relative to uncorrected DFT for the middle transition, but not the early or late transitions. By contrast, the local scaling SIC (LSIC) method, also implemented in the FLO-SIC framework, significantly improves the calculated barriers over DFT and PZ-SIC in all but one case. Lastly, the results also show how the FLO-SIC approach can provide insight into the bonding in aromatic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ultra-High Temperature Thermal Barrier Coating Development and Validation

The most effective method to improve industrial gas turbine power is to increase firing temperature. To maintain component durability at these higher temperatures, thermal barrier coatings (TBC’s) are playing an increasing role in protecting turbine hardware. TBC’s have been successfully used on Solar Turbines’ combustor liners and turbine airfoils, but there is a need for TBC’s that can operate at higher temperatures. Based on recent, favorable rig testing experience, Solar recognized that yttrium aluminum garnet (YAG) TBC’s made by the Solution Precursor Plasma Spray Process (SPPS) has great potential for higher turbine temperatures. This testing verified the thermal cycle durability of the SPPS YAG TBC’s, as well as demonstrated that the temperature drop through the SPPS YAG TBC was twice that measured across a companion APS YSZ TBC. The SPPS YAG TBC with the potential for a 200°C improvement in temperature capability represents a materials breakthrough. The SPPS process also produces a number of unique microstructural features that confer superior properties. SPPC TBC’s have ultra-fine splats that increase toughness and erosion resistance, and the process can be tailored to produce through-thickness cracks for strain-tolerance and control porosity for lower thermal conductivity and increase coating abradability. This proposal would include further development of SPPS YAG density-graded coatings, optimization of the application process, and validation of higher temperature capability and durability through rig and engine testing of coated combustion liners and turbine outer air seals. The technology would be advanced from a TRL 3 to a proposed TRL 6 by overcoming processing concerns on efficiency, application distance and optimization of a graded coating without impacting coating durability by demonstrating the coating performance on components in rig and development gas turbine engine testing.

36 MATERIALS SCIENCE↗

Growth and characterization of homoepitaxial β-Ga 2 O 3 layers

ß-Ga 2 O 3 is a next-generation ultra-wide bandgap semiconductor (E g = 4.8 eV to 4.9 eV) that can be homoepitaxially grown on commercial substrates, enabling next-generation power electronic devices among other important applications. Analyzing the quality of deposited homoepitaxial layers used in such devices is challenging, in part due to the large probing depth in traditional x-ray diffraction (XRD) and also due to the surface-sensitive nature of atomic force microscopy (AFM). Here, a combination of evanescent grazing-incidence skew asymmetric XRD and AFM are investigated as an approach to effectively characterize the quality of homoepitaxial ß-Ga 2 O 3 layers grown by molecular beam epitaxy at a variety of Ga/O flux ratios. Accounting for both structure and morphology, optimal films are achieved at a Ga/O ratio of ~1.15, a conclusion that would not be possible to achieve by either XRD or AFM methods alone. Finally, fabricated Schottky barrier diodes with thicker homoepitaxial layers are characterized by J-V and C-V measurements, revealing an unintentional doping density of 4.3×10 16 cm -3 - 2×10 17 cm -3 in the epilayer. These results demonstrate the importance of complementary measurement methods for improving the quality of the ß-Ga 2 O 3 homoepitaxial layers used in power electronic and other devices.

36 MATERIALS SCIENCE↗

A Barrier-Certificated Reinforcement Learning Approach for Enhancing Power System Transient Stability

Increasing integration of renewable resources brings more flexibility and poses new challenges to modern power systems, leading to highly nonlinear and complex dynamics. Here, this paper aims to provide a general solution framework to traditional control problems, such as frequency control and voltage control, which attempt to maintain the stability of either synchronous generators-governed or inverter-governed systems when subjected to a disturbance and simultaneously guarantee operational constraints, providing a complete complement to existing works on control design. Building on reinforcement learning (RL) and control barrier functions, the framework includes two subsystems, i.e., a model-free controller and a barrier-certification system, which discover RL-based control actions and sequentially filter them using a barrier certificate to satisfy operational constraints. Calculating a barrier function is generally challenging for a complex power system. This is addressed by representing the barrier function using neural networks (NNs) and data-based approaches. An adaptive method is introduced to certify the neural barrier function that perseveres barrier conditions, which is more compatible with online implementation. The proposed framework synthesizes a stabilizing controller that satisfies predefined safety regions. The effectiveness of the proposed framework is demonstrated via several comparative case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

All-Polyester Multilayer Plastics (‘All-Polyester MLPs’): A Redesign for Inherently Recyclable Plastics

Multilayer plastics (MLPs) are widely used in modern packaging because they combine multiple functions such as oxygen and moisture barriers, mechanical strength, puncture resistance, and heat sealability into lightweight and cost-effective packaging solutions. These attributes are essential for food, beverage, pharmaceutical, and consumer goods packaging. However, conventional commercial MLPs typically consist of five to twelve layers made from chemically incompatible materials, including polyolefins, polyethylene terephthalate, nylon, ethylene-vinyl alcohol (EVOH), adhesives, and tie layers. This complexity makes MLPs extremely difficult to recycle. As a result, the vast majority of multilayer plastics (MLPs) are disposed of through landfilling or incineration. This disposal pathway perpetuates demand for virgin material production, thereby driving high industrial energy consumption, increasing greenhouse gas (GHG) emissions, and contributing to the long-term accumulation of plastic waste. The scope of work included: (1) Design and fabrication of all-polyester multilayer structures using commercially relevant processing methods; (2) Experimental validation of barrier, mechanical, and sealing performance; (3) Demonstration of both mechanical and chemical recycling pathways; and (4) Comprehensive techno-economic analysis (TEA) and life-cycle assessment (LCA) to quantify cost, energy, and environmental impacts.

36 MATERIALS SCIENCE↗

Real-time patch-clamp sensing of transport across a barrier tissue

The present disclosure relates to methods, apparatuses, and systems to measure one or more electrical signals from a cultured cell layer. In some embodiments, such electrical signals can be indicative of transport or lack of transport of an agent through the cell layer.

Source record↗

The role of international collaboration in the United States geologic disposal research program

Abstract. More than a decade ago, the United States disposal program discontinued all research activities focused on the unsaturated fractured tuff formation at Yucca Mountain as the geologic disposal site for spent fuel and high-level radioactive waste. A new research and development (R&D) program was initiated to provide a sound technical basis for alternative disposal options across clay, crystalline, and salt rocks. The goals of this broad program were (and still are) to (1) increase confidence in the robustness of generic disposal concepts, (2) develop the science and engineering tools needed to support disposal concept implementation, and (3) conduct R&D on the direct disposal of existing dual-purpose (storage and transportation) canisters. Recognizing the benefits of international collaboration toward the common goal of safely and efficiently managing the back end of the nuclear fuel cycle, the program emphasized international cooperation as an effective strategy for sharing information and knowledge. In a multi-laboratory effort coordinated by Lawrence Berkeley National Laboratory, the United States Department of Energy (DOE) program established formal and informal cooperation partnerships with several international initiatives and institutions and developed a number of collaborative R&D activities in important research areas, such as engineered barrier integrity, near-field perturbations, radionuclide transport, performance assessment, and methods for characterization and monitoring of engineered and natural barriers. This presentation gives an overview of these R&D activities, with a specific focus on activities that improve our current understanding of the coupled thermal–hydrological–mechanical–chemical (THMC) processes occurring in engineered and natural barriers. We start with a brief review of selected international collaboration initiatives and then describe a few specific collaboration projects. We focus specifically on such studies that use experimental data sets provided by international research cooperation for joint modeling work to increase confidence in performance-relevant predictions of coupled processes. Overall, the focus on international collaboration has allowed deep engagement of US researchers with the international waste management R&D community in terms of best practices, new scientific advances, state-of-the-art simulation tools, new monitoring and performance confirmation approaches, and lessons learned. The joint R&D with international researchers, worldwide sharing of knowledge and experience, and access to relevant data and experiments from a variety of host rocks have helped our researchers to significantly improve their understanding of the current technical basis for disposal in a range of potential host rock environments. International collaboration also provides ample opportunity for training and educating junior staff that are well suited to move the United States disposal research program forward into the next decades, a promising avenue for developing a next-generation workforce of disposal scientists.

Birkholzer, Jens T.↗

Achieving clean production with nanostructured coated milling tools dry machining low carbon steel

The advancement of clean production using nanostructured materials in subtractive manufacturing processes has focused on replacing the use of liquid lubrication with solid lubricants coated to conventional cutting tools machining low carbon steel (~ 0.2 wt. % carbon). However, little is known about the wear mechanisms that dominate such tools when coated with functional graded nanostructured coatings. The present study follows an international standard for characterizing such wear (ISO 8688) but uses advanced measurement techniques such as x-ray fluorescence technology to measure the diffusion of chemical species from tool to workpiece and vice versa, that contributes to tool wear with the view to enhance the principles of cleaner production. The results show that when commercially-available tools coated with the appropriate functionally graded industrial coating, diffusion does not take place and creates an effective chemical barrier during machining. The experimental methods used in the study include machining workpieces using a CNC milling machine, tachometer for measuring spindle speed, dynamometer for measuring cutting forces, infra-red camera for measuring cutting temperatures, chemical species diffusion wear using x-ray florescence detector, and an optical microscope for measuring tool wear. Coupled with the physical measurement of wear, it is concluded that mechanical wear dominates the milling of a low carbon steel and that thermal properties of the coatings do not correlate with such wear. It is also concluded that flank wear as a function of volume of workpiece removed and machining duration (machining index) is a sound method for assessing the transition of the stages of wear during clean machining operations. The present study not only has implication for the design of better cutting tools, but also advances dry machining processes that eliminate the use of liquid lubricants making subtractive production processes cleaner. The main conclusions drawn from this study show that coated tools have a longer life under dry conditions compared to uncoated tools and that there is no correlation between coating properties and tool wear. In conclusion, diffusion of chemical species into the cut chips did not occur because of the lack of thermally induced chemical wear of the cutting tool and that wear is caused by the gradual erosion of the flank face due to the chip abrading the cutting tool.

36 MATERIALS SCIENCE↗

UEMtomaton: A Source-Available Platform to Aid in Start-up of Ultrafast Electron Microscopy Labs

The steady rise in the number of ultrafast electron microscopy (UEM) labs, in addition to the opacity and lack of detailed descriptions of current approaches that would enable point-by-point construction, has created an opportunity for sharing common methods and instrumentation for (for example) automating data acquisition to assist in efficient lab start-up and to learn about common and robust protocols. In the spirit of open sharing of methods, we provide here a description of an entry-level method and user interface (UI) for automating UEM experiments, and we provide access to the source code and scripts (source-available) for ease of implementation or as a starting reference point for those entering or seeking to enter the field (https://github.com/CEMSFlannigan/UEMtomaton/releases/tag/v1.0). Core instrumentation and physical connections in the UEM lab at Minnesota are described. Interface communication schemes consisting of duo server-client pairs between critical components – the optical delay stage and the UEM digital camera – are presented, with emphasis placed on describing the logic and communications sequence designed to conduct automated series acquisitions. An application designed and programmed with C++/CLI as Windows Forms in Microsoft Visual Studio – dubbed UEMtomaton – is also presented. Key to the UI layout is centralization of the automation tasks and establishment of communication within the software rather than by interfacing with each individual workstation. It is our hope that this note provides useful insight for current and future UEM researchers, particularly with respect to generalizability and portability of the approach to emerging labs. Here, we note that while this basic, entry-level approach is certainly not the most sophisticated or comprehensive of those currently in use, we feel there is nevertheless value in clearly communicating a proven straightforward method to hopefully lower the barrier to entry into the field.

47 OTHER INSTRUMENTATION↗