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At least 1,099 records · Page 61

Catalyst design for small molecule activation of energy consequence

This project targets the conversion of ubiquitous small molecules (e.g. NO, CO, H 2 O) into viable precursors to synthetic fuels. Current state of the art catalyst design has not directly targeted transition metal complexes capable of mediating the multi-electron redox processes necessary to reduce the overpotential (energy loss) required achieve efficient activation of small molecule substrates. In this vein, a new strategy has been developed for the assembly of polynuclear architectures; allowing for the construction of tunable polymetallic centers that assemble easily within a pre-organized template (conferring stability, selectivity and tunability) that can effect multi-electron redox processes for reactions. Catalyst development has commenced with the following target design elements: (1) catalysts featuring multiple transition metal ions in the same reaction space to greatly expand accessible molecular redox capabilities; (2) catalysts are assembled in a polynucleating ligand framework that permits control over the cluster morphology as well as the local steric and electronic environment of the transition metal ions within the cluster. The high-tunability of the catalyst composition (metal content) and geometric flexibility has permitted a rigorous assessment of electronic-structure-to-function relationship to be developed, further guiding synthetic efforts to realize more potent catalysts. The numerous permutations possible showcase the high degree of generality to this approach with many synthetic handles to tune redox and reaction chemistry. Trinuclear complexes have been synthesized featuring homo- and hetero-trinuclear cores featuring a variety of first row transition metal ions (Cr→Ni). The molecular clusters have been shown to successfully mediate multi-electron redox processes in a cooperative fashion without requiring strong chemical reductants or oxidants. The reactive molecular complexes are being utilized to activate and breakdown the robust bonds within typical waste stream small molecules (e.g., greenhouse gases) and convert them into value-added commodity chemicals. Ultimately, the catalysts developed by this approach will be required to convert energy acquired via renewable resources (e.g., solar or wind) into synthetic fuels as an energy storage mechanism.

10 SYNTHETIC FUELS↗

Accelerators for the Future: R&D at the Fermilab FAST Facility

High energy physics in the U.S. has ambitious plans requiring new and improved accelerator technologies, including an upgraded complex at Fermilab for DUNE, next-generation light sources, and the potential of a future collider to be built on U.S. soil. To address these requirements, Fermilab operates the Fermilab Accelerator Science and Technology (FAST) facility, dedicated to accelerator R&D. FAST includes an electron gun and superconducting RF linac (up to 300 MeV), a storage ring, and an upcoming proton source and injector line (up to 2.5 MeV). In addition to the future of Fermilab accelerators, the broad physics program includes general R&D with potential impact across the DOE science program. This colloquium will provide a basic introduction to accelerator technologies and describe the principles of proton and electron accelerators, including the challenges associated with next-generation operations. We will discuss the exciting R&D ongoing at FAST to address the required technological advancements, focusing on Non-Linear Integrable Optics (NIO) for improved beam intensity and Optical Stochastic Cooling (OSC) for improved beam quality, and touching on a wide range of additional ongoing research. I intend to make the content interesting and accessible to those who have never taken any formal courses in accelerator physics.

43 PARTICLE ACCELERATORS↗

Energy performance of an operational government building retrofitted with ceiling phase change material tiles in a mixed-humid climate

The aging U.S. building stock requires various retrofit measures to enhance their energy efficiency. Here, this study explores the integration of thermal energy storage and advanced building controls as viable retrofit solutions for load flexibility and peak demand response while maintaining the occupants' comfort. A detailed assessment is conducted on the energy use of an administrative building in Sumner County, Kansas, focusing on the implementation of phase change materials (PCMs) in the ceiling of occupied zones. First, a time-resolved, whole-building energy model is developed in EnergyPlus, incorporating complex thermal behaviors such as air exchange between the plenum space and occupied zones, envelope leakage, and operational schedules. The model is then validated using experimental field test data, and subsequently a parametric assessment of key PCM properties and application strategies is performed to evaluate cooling electricity demand benefits. The parametric study shows that the optimal retrofit strategy, comprising a PCM with 23°C peak melting temperature, 0.125 in. (3.17 mm) thickness, and 150 kJ/kg latent heat, combined with active controls that include 8 h of precooling, forced convection under the ceiling, and a 2°C thermostat setback during peak hours, can result in a maximum load shift during the peak period of 99.6 % and the total electricity savings during the peak period of 98.9 % for the optimum case and thus provide significant cost savings under time-of-use pricing scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Corrosion evaluation of metal foams in eutectic molten salts for high temperature latent heat energy storage application

High-temperature Thermal Energy Storage (TES) has drawn great attention as a technology that can increase the role and profitability of micro nuclear reactors in the decentralized clean energy market. Various research needs have been proposed by Idaho National Laboratory (INL) in "the Integrated Energy Systems: 2020 Roadmap" with the goal of utilizing the high temperature of 550 degrees or more generated in the 4th generation reactor to industrial purposes from the standpoint of integrated energy systems [1]. With the recent development of the 4th generation nuclear power plant, including micro nuclear reactor, there is a great deal of interest in researching how to efficiently couple a heat source to an industrial process through thermal processing. Texas A&M University (TAMU) and INL are currently collaborating to develop a novel latent heat storage design called HITB (Heat pipe-Integrated Thermal Battery). As part of the small-scale experimental demonstration research for HITB, a study for storage medium selection was conducted at TAMU. Eutectic salts have attracted interest as high-temperature heat storage medium for HITB. Especially, chloride molten salts and fluoride molten salts are considered promising candidates due to their high melting temperature, thermal stability, and high latent heat of fusion. Since eutectic salts have poor thermal conductivity in general, it is critical to distribute materials with high thermal conductivity evenly to facilitate the charging and discharging of heat. In this study, metal foam was considered in the HITB system to overcome the poor heat transfer characteristics of eutectic salts. In order to improve heat transfer, it is necessary to study materials with high thermal conductivity, corrosion resistant to molten salts, such as fins, extended surfaces, particles, microcapsulation, or foam structure. Porous structure of copper or aluminum can increase heat transfer area, form a thermal transfer network, and increase the effective thermal conductivity of thermal storage medium [2]. Since the melting temperature is required to be at least 450? in the current HITB design, various eutectic salts are being considered. FLiNaK and FLiBe, which are famous for fluoride salts, are good candidates, but due to the sharp rise in the price of LiF recently, they are excluded for economic reasons to be applied to large-capacity thermal energy storage. On the other hand, chloride salts are very cheap and easy to obtain, have a high melting temperature, and have a high latent heat of fusion, so they are recently in the spotlight as a phase change material. However, because of the hygroscopic nature of chloride salts, HCl gas due to impurity is easy to be released and is particularly vulnerable to corrosion. Chloride eutectic salts have been tested and suggested for metal alloys that are particularly resistant to corrosion, such as SS304, SS316, Hastelloy, Inconel 625, Incoloy 800H, which has low thermal conductivity, and is very expensive [3-6]. Porous materials with high thermal conductivity such as copper and aluminum have been tested for stability in fluids such as paraffin or water as metal foam or metal fin structures, but high temperature corrosion tests were not performed on various eutectic salts yet. Therefore, this study investigated the high temperature corrosion characteristics of metal alloys, such as C10100 foam, C10100 plate, 6101 alloy foam, and SS316 plate, while immersed in the candidate eutectic salts. A total of 20 tests for SS316 coupons and 10 tests for C10100 coupons were performed to ensure the repeatability of the present measurements. Since it is difficult to completely remove the salt inside metal foam due to the complex inner structure of the metal foam, only the surface condition was observed with a microscopy and scanning electron microscopy (SEM) image, except for measuring the corrosion rate and average mass loss.

25 ENERGY STORAGE↗

Neural Network-Enhanced Reproducing Kernel Particle Method for Image-Based Multiphysics Damage Modeling of Energy Storage Materials

Energy storage materials undergo significant stresses during charge/discharge cycling, which makes understanding their reliability and durability fundamental in predicting performance and service life. Strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking, largely along material interfaces and grain boundaries. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), image-based modeling techniques are used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electrochemical-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in capturing crack propagation due to mesh dependency. Additionally, commonly used damage models, such as the continuous damage model and the cohesive zone model, often have steep tradeoffs between discontinuous field accuracy and computational expense. In this work, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1] is leveraged to accurately capture damage and crack propagation throughout the material by learning the location, orientation, and sharpness of discontinuity while allowing for a coarser nodal distribution than that necessary for capturing sharp solution transitions using traditional mesh-based methods. NN-RKPM is used to inform how crack opening and closure in turn affect the coupled chemical equations and material microstructure. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022.

damage modeling↗

Multiphysics Meshfree Degradation Modeling of Energy Storage Materials with Kernel Enrichment

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. Reference: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

25 ENERGY STORAGE↗

Molecular Insights into Geochemical Reactions of Iron-Bearing Minerals: Implications for Hydrogen Geo-Storage

Here, this study investigates the reaction of hydrogen (H 2 ) with pyrite (FeS 2 ), focusing on how temperature and the presence of water influence the reaction pathways and kinetics. Utilizing computational molecular simulations and kinetic analyses, we explore the impact of these factors on the formation of hydrogen sulfide (H 2 S) and related species. First, grand canonical Monte Carlo/molecular dynamics (GCMC/MD) simulations reveal that physical H 2 adsorption occurs in distinct layers on the pyrite surface. In addition, increased temperatures reduce the absolute adsorption capacities. Reactive MD simulations demonstrate that H 2 interacts differently with pyrite under varying conditions. At 298 K, H 2 reacts with pyrite to form HS – , leading to the formation of HS – through covalent bonding with sulfur of pyrite. However, no H 2 S is produced at this temperature, suggesting that a kinetic barrier (i.e., activation energy) may prevent this reaction. At higher temperatures, H 2 S production significantly increases. The presence of water introduces additional complexity to the reaction mechanism. Unlike dry conditions, water enhances H 2 S generation, even at low temperatures. Water also facilitates the formation of additional products, such as SOH, indicating a more intricate chemical environment on the pyrite surface. Our findings identify the association of HS – ions to form H 2 S as the rate-limiting step, with temperature influencing this process. This finding suggests that while the presence of water can create a more dynamic reaction environment, the overall mechanisms leading to H 2 S formation remain consistent. These outcomes suggest the need for developing targeted strategies to manage and control H 2 S emissions within the context of underground hydrogen storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Entangled Electrons Drive a Non-superexchange Mechanism in a Cobalt Quinoid Dimer Complex

A central theme in chemistry is the understanding of the mechanisms that drive chemical transformations. A well-known, highly cited mechanism in organometallic chemistry is the superexchange mechanism in which unpaired electrons on two or more metal centers interact through an electron pair of the bridging ligand. We use a combination of novel synthesis and computation to show that such interactions may in fact occur by a more direct mechanism than superexchange that is based on direct quantum entanglement of the two metal centers. Specifically, we synthesize and experimentally characterize a novel cobalt dimer complex with benzoquinoid bridging ligands and investigate its electronic structure with the variational two-electron reduced density matrix method using large active spaces. The result draws novel connections between inorganic mechanisms and quantum entanglement, thereby opening new possibilities for the design of strongly correlated organometallic compounds whose magnetic and spin properties have applications in superconductors, energy storage, thermoelectrics, and spintronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A technique for generating correlated X-band weather degradation statistics

It is, known that the X-band noise temperature of DSN receivers can go up from 20 K to over 100 K or more, if the air is heavily laden with water vapor, although that is an uncommon occurrence. It is proposed that the DSN furnish flight projects relying on X-band degradation models, one for each DSN Complex. Such models would be in the form of a random process generator, say in an MBASIC program, that would permit the project to generate X-band degradation data with the right autocorrelations for periods of interest to the Projects. The autocorrelation modeling is especially important because bursts of degradation lasting several days can affect data storage and mission sequence design strategy. One approach which works if the degradation statistics obey a half-gaussian law. That is, the random variables are formed by taking the absolute values of another set of random variables, themselves having a Gaussian distribution. The technique then permits the half-gaussian random variables to have given one and two-step correlation coefficients.

Posner, E. C.↗

Command and control of unmanned scientific spacecraft

Recent developments in command and control technology for use with the Voyager and the planned Galileo are discussed. These spacecraft each carry more than 10 scientific instruments, many of which are very complex, and these instruments must be able to function with a considerable degree of autonomy because the round-trip light time to the spacecraft in the vicinity of Jupiter and Saturn is too great to permit prompt ground-based management of onboard anomalies or control of some observation programs. Command and control procedures, including data storage procedures, for systems of the two spacecraft are examined.

Gates, C. R.↗

Operating systems

A counter operating system creates a hierarchy of levels of abstraction, so that at a given level all details concerning lower levels can be ignored. This hierarchical structure separates functions according to their complexity, characteristic time scale, and level of abstraction. The lowest levels include the system's hardware; concepts associated explicitly with the coordination of multiple tasks appear at intermediate levels, which conduct 'primitive processes'. Software semaphore is the mechanism controlling primitive processes that must be synchronized. At higher levels lie, in rising order, the access to the secondary storage devices of a particular machine, a 'virtual memory' scheme for managing the main and secondary memories, communication between processes by way of a mechanism called a 'pipe', access to external input and output devices, and a hierarchy of directories cataloguing the hardware and software objects to which access must be controlled.

Denning, P. J.↗

Integrated System for Health Management and Autonomous Control (ISHM-AC): Development and Application

Autonomous control systems represent a technological barrier from manual and automated operated control systems in an industry wide application. An increase in energy-efficient storage, transfer and use of cryogens and cryogenic propellants on Earth and in space has been observed in space related industries between NASA, government and commercial programs. An increase in efficiency of cryogenic systems demands an increase in the capabilities of the control and monitoring system that manages them. As new technologies are developed for cryogenic systems, complexity and capability increases. The increase in complexities are a natural drive to develop better and more capable health monitoring and control system management. Current research and development efforts lead the Cryogenics Test Laboratory at the Kennedy Space Center to improve its automated control and health monitoring system from a Programmable Logic Control (PLC) based-only system to a fully Integrated System for Health Management (ISHM) - Autonomous Control (AC) capable of performing autonomous operations on a cryogenic propellant transfer system. This ISHM-AC system has been developed and tested by controlling a complete simulated propellant transfer operation. The capabilities and test results of this fully integrated autonomous system for cryogenics propellant transfer operation will be presented in this paper.

Toro, Jaime A.↗

Integrated System for Health Management and Autonomous Control (ISHM-AC) for Cryogenic Operations on the Simulated Propellant Loading System

Autonomous control systems represent a technological barrier from manual and automated operated control systems in an industry wide application. An increase in energy-efficient storage, transfer and use of cryogens and cryogenic propellants on Earth and in space has been observed in space related industries between NASA, government and commercial programs. An increase in efficiency of cryogenic systems demands an increase in the capabilities of the control and monitoring system that manages them. As new technologies are developed for cryogenic systems, complexity and capability increases. The increase in complexities are a natural drive to develop better and more capable health monitoring and control system management. Current research and development efforts lead the Cryogenics Test Laboratory at the Kennedy Space Center to improve its automated control and health monitoring system from a Programmable Logic Control (PLC) based-only system to a fully Integrated System for Health Management (ISHM) - Autonomous Control (AC) capable of performing autonomous operations on a cryogenic propellant transfer system. This ISHM-AC system has been developed and tested by controlling a complete simulated propellant transfer operation. The capabilities and test results of this fully integrated autonomous system for cryogenics propellant transfer operation will be presented in this paper.

Toro Medina, Jaime A.↗

Filament Wound Composite Analysis Using the NASA Multiscale Analysis Tool (NASMAT) and Finite Element Analysis

Fiber reinforced composite materials, owing to their tailorable thermomechanical and functional properties, allow one to produce a structure that is stronger, stiffer, and lighter than its metal counterpart while performing the same function, yielding a more efficient structure. This not only allows for the improvement of current technologies like aircraft structures, but also enables new technologies like gaseous hydrogen storage for mobility applications, which are otherwise impractical when manufactured using traditional metals due to weight and space restrictions or material embrittlement. However, the use of composites imposes greater design and manufacturing challenges on an engineer, since they are heterogenous, having a distinct structure across multiple length scale, behave generally anisotropically at the structural level and require complex manufacturing and processing methods. Capturing this complex behavior requires detailed numerical simulations, including the modeling of microstructural features like undulations, voids, and fiber alignment. In this paper, multiple repeating unit cells (RUCs), representing filament wound composites, are developed (via a script provided in the Appendix) and analyzed. The refinement of these RUCs is varied, and the analyses are performed using both the Abaqus finite element software and the NASA Multiscale Analysis Tool (NASMAT). A study is undertaken to compare the predicted effective elastic properties of the wound RUC to a laminate representation of the wound RUC, which neglects the undulations. Additionally, two different sets of periodic boundary conditions (PBCs) have been examined. One approximates the real boundary conditions using a standard approach and the other represents the PBCs exactly through the use of an offset. Lastly, a comparison of the local elastic stress fields is made among the models and approaches. Since wound structures are often approximated as laminated structures, it is important to understand the degree to which this assumption is valid, namely by first comparing the elastic constants and local elastic fields. This will provide, on the one hand, information concerning the bulk mechanical behavior and, on the other hand, insights concerning local load distributions and likely damage initiation sites.

Composites↗

Responses of Boreal Forest Ecosystems and Permafrost to Climate Change and Disturbances: A Modeling Perspective

The north circumpolar region contains a large amount of carbon. This carbon storage is vulnerable due to permafrost degradation and wildfire disturbances under ongoing and projected climate change. Climate warming and wildfires change soil organic horizons gradually or abruptly, and modify permafrost thermal-hydrology and biogeochemistry, ecosystem structures, functions, and capability of sequestrating rising atmospheric CO2. Land models do not fully take accounts of these interactions and its complexity in the high latitude. This chapter describes a terrestrial ecosystem model with dynamic organic soil module (DOS-TEM) and its unique freezing-thawing algorithm, and presents key results of its applications mainly in boreal forests of Alaska. The DOS-TEM explicitly considers interactions of soil thermal and hydrological processes, permafrost degradation and the direct and indirect effects of wildfire disturbances, in addition to soil–plant C and N cycles. We first introduce four modules of DOS-TEM, focusing on its disturbance module and coupling with a dynamic organic soil module. Then we describe and validate DOS-TEM’s freezing-thawing algorithm and development based on two-directional Stefan algorithm (TDSA). Finally, we apply the DOS-TEM at site and region scales, with a focus on model ability to dynamically simulate soil organic thickness under warming and wildfires, and consequent impacts on permafrost in the Yukon River Basin. We conclude that land surface model development is urgently needed to include other critical landscape processes, such as thermalkarst and other disturbances, to synchronize thermal-hydrological-biogeochemical processes, and to incorporate an advanced understanding of biospheric feedbacks to atmosphere and ecosystems. Such a complexity of modeling scope is plausible with advancement of high performance computing.

Yi, Shuhua↗

SEI formation mechanisms and Li + dissolution in lithium metal anodes: Impact of the electrolyte composition and the electrolyte-to-anode ratio

The lithium metal battery is one of today's most promising high-energy-density storage devices. Its full-scale implementation depends on solving operational and safety issues intrinsic to the Li metal high reactivity leading to uncontrolled electrolyte decomposition and uneven Li deposition. In this work, we study the spontaneous formation of the solid electrolyte interphase (SEI) upon contact of Li metal with the electrolyte and describe the heterogeneous SEI morphological features. Multiple electrolyte formulations based on lithium bis(fluorosulfonyl)imide (LiFSI), dimethoxyethane (DME), dimethyl carbonate (DMC), 1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropyl ether (TTE) and bis(2,2,2-trifluoroethyl) ether (BTFE) are used. Findings include the description of the SEI evolution from dispersed LiO, LiS, LiN, and LiF clusters to a continuous and compact inorganic phase in which the LiO and LiF content depend on the presence of fluorine diluents. Further, the role of the DME ether solvent helping the growth of a “wet-SEI” is compared to that of the highly unstable carbonate DMC, which decomposes into complex radical oligomers that might contribute to further electrolyte decomposition. The impact of the electrolyte-to-anode ratio on LiFSI decomposition is highlighted. Finally, we suggest the existence of a critical LiFSI concentration and electrolyte-to-anode ratio that could potentially balance the rate of electrolyte depletion and lithium consumption.

25 ENERGY STORAGE↗

Foundations of machine learning for low-temperature plasmas: methods and case studies

Abstract Machine learning (ML) and artificial intelligence have proven to be an invaluable tool in tackling a vast array of scientific, engineering, and societal problems. The main drivers behind the recent proliferation of ML in practically all aspects of science and technology can be attributed to: (a) improved data acquisition and inexpensive data storage; (b) exponential growth in computing power; and (c) availability of open-source software and resources that have made the use of state-of-the-art ML algorithms widely accessible. The impact of ML on the field of low-temperature plasmas (LTPs) could be particularly significant in the emerging applications that involve plasma treatment of complex interfaces in areas ranging from the manufacture of microelectronics and processing of quantum materials, to the LTP-driven electrification of the chemical industry, and to medicine and biotechnology. This is primarily due to the complex and poorly-understood nature of the plasma-surface interactions in these applications that pose unique challenges to the modeling, diagnostics, and predictive control of LTPs. As the use of ML is becoming more prevalent, it is increasingly paramount for the LTP community to be able to critically analyze and assess the concepts and techniques behind data-driven approaches. To this end, the goal of this paper is to provide a tutorial overview of some of the widely-used ML methods that can be useful, amongst others, for discovering and correlating patterns in the data that may be otherwise impractical to decipher by human intuition alone, for learning multivariable nonlinear data-driven prediction models that are capable of describing the complex behavior of plasma interacting with interfaces, and for guiding the design of experiments to explore the parameter space of plasma-assisted processes in a systematic and resource-efficient manner. We illustrate the utility of various supervised, unsupervised and active learning methods using LTP datasets consisting of commonly-available, information-rich measurements (e.g. optical emission spectra, current–voltage characteristics, scanning electron microscope images, infrared surface temperature measurements, Fourier transform infrared spectra). All the ML demonstrations presented in this paper are carried out using open-source software; the datasets and codes are made publicly available. The FAIR guiding principles for scientific data management and stewardship can accelerate the adoption and development of ML in the LTP community.

Physics↗

Synthetic Metal Atomic Layer Deposition Tool (Final Report)

As part of the Cyclotron Road program, Laminera Inc. worked towards development of atomic layer deposition process customizations and tool modifications to produce synthetic metal films at commercial scale and improve the film quality. Today's state-of-the-art in atomic layer deposited synthetic metal technology is only possible at a research-scale because current tools have practical limitations for scaling industrially and generating high conductivity films. Ultrathin, conformal synthetic metal films have many possible applications such as high surface area nanoporous electrodes for supercapacitors and water desalination devices; protective electrode coatings for electrochemical devices; seed layers for semiconductor device fabrication; or metallic component stabilizing coatings that enable enhanced storage density in next generation hard disk drives. The best synthetic metal conductive and plasmonic properties have been demonstrated using sputtering, which relies on high temperature sputtering with substrate dependent and directional growth limiting usage. This work explored refining process and tool modifications to create ultrathin, conformal, synthetic metal films that can be deposited with high quality over complex three-dimensional surfaces.

36 MATERIALS SCIENCE↗