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At least 1,693 records · Page 94

Plasma etching: Yesterday, today, and tomorrow

The field of plasma etching is reviewed. Plasma etching, a revolutionary extension of the technique of physical sputtering, was introduced to integrated circuit manufacturing as early as the mid 1960s and more widely in the early 1970s, in an effort to reduce liquid waste disposal in manufacturing and achieve selectivities that were difficult to obtain with wet chemistry. Quickly, the ability to anisotropically etch silicon, aluminum, and silicon dioxide in plasmas became the breakthrough that allowed the features in integrated circuits to continue to shrink over the next 40 years. Some of this early history is reviewed, and a discussion of the evolution in plasma reactor design is included. Some basic principles related to plasma etching such as evaporation rates and Langmuir–Hinshelwood adsorption are introduced. Etching mechanisms of selected materials, silicon, silicon dioxide, and low dielectric-constant materials are discussed in detail. A detailed treatment is presented of applications in current silicon integrated circuit fabrication. Finally, some predictions are offered for future needs and advances in plasma etching for silicon and nonsilicon-based devices.

36 MATERIALS SCIENCE↗

Model Predictive Control Strategies for Turbine Electrified Energy Management

The increasing electrification of aircraft propulsion systems is leading to new control architectures being developed to address integration between electric machines and gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures often couple electric machines with the shafts of gas turbine engines and introduce energy storage. Leveraging the electrical power system of hybridized engines, Turbine Electrified Energy Management (TEEM) is a recent control approach that improves transient operability in an effort to enable more efficient and lighter weight turbomachinery. This study seeks to expand TEEM’s application beyond traditional proportional integral (PI) control by presenting linear model predictive control (MPC) schemes to execute the TEEM concept. Through constraint selection and cost function design, transient operability goals for TEEM are considered with no external logic or saturation. Unique to the designs are the use of a washout filter, which simplifies transient detection and motor activation logic. The proposed architectures are implemented with both centralized MPC and distributed MPC approaches, and comparisons are drawn to a benchmark PI controller simulated on a nonlinear turbofan engine model at one ground condition and one cruise condition. Performance is evaluated using compressor maps, stall margin performance, and two novel metrics: transient stack usage and transient excursion integral. Results reveal the linear MPC scheme performs comparably to the baseline controller and can be implemented in at least two distinct configurations with potential for further modifications, thus establishing the groundwork for future investigations.

Model Predictive Control↗

High Efficiency Heat Exchanger for High Temperature and High Pressure Applications

CompRex, LLC (CompRex) specializes in the design and manufacture of compact heat exchangers and heat exchange reactors for high temperature and high pressure applications. CompRex’s proprietary compact technology not only increases heat exchange efficiency by at least 25 % but also reduces footprint by at least a factor of ten compared to traditional shell-and-tube solutions of the same capacity and by 15 to 20 % compared to other currently available Printed Circuit Heat Exchanger (PCHE) solutions. As a result, CompRex’s solution is especially suitable for Brayton cycle supercritical carbon dioxide (sCO2) systems given its high efficiency and significantly lower capital and operating expenses. CompRex has already successfully demonstrated its technology and ability to deliver with a pilot-scale compact heat exchanger that was under contract by the Naval Nuclear Laboratory for sCO2 power cycle development. The performance tested unit met or exceeded the thermal and hydraulic specifications with measured heat transfer between 95 to 98 % of maximum heat transfer and temperature and pressure drop values all consistent with the modeled values. CompRex’s vision is to commercialize its compact technology and become the leading provider for compact heat exchangers and heat exchange reactors for various applications including Brayton cycle sCO2 systems. One of the limitations of the sCO2 Brayton power cycle is the design and manufacturing of efficient heat exchangers at extreme operating conditions. Current diffusion-bonded heat exchangers have limitations on the channel size through which the fluid travels, resulting in excessive solid material per heat exchanger volume. CompRex’s design allows for more open area and shorter fluid proximity for increased heat transfer efficiency while sustaining the structural integrity needed for the application. CompRex is developing a novel improvement to its current heat exchanger design where fluids are directed to alternating channels so that each fluid is fully surrounded by the opposing fluid. As compared to similar existing compact heat exchangers, the new design converts most secondary surface area to primary surface area, eliminating fin inefficiencies. CompRex requests that all technical information about the heat exchanger designs be protected as proprietary information. To honor that request, only non-proprietay summaries are included in this report.

47 OTHER INSTRUMENTATION↗

m-CUBES An efficient and portable implementation of multi-dimensional integration for gpus

The task of multi-dimensional numerical integration is frequently encountered in physics and other scientific fields, e.g., in modeling the effects of systematic uncertainties in physical systems and in Bayesian parameter estimation. Multi-dimensional integration is often time-prohibitive on CPUs. Efficient implementation on many-core architectures is challenging as the workload across the integration space cannot be predicted a priori. We propose m-Cubes, a novel implementation of the well-known Vegas algorithm for execution on GPUs. Vegas transforms integration variables followed by calculation of a Monte Carlo integral estimate using adaptive partitioning of the resulting space. m-Cubes improves performance on GPUs by maintaining relatively uniform workload across the processors. As a result, our optimized Cuda implementation for Nvidia GPUs outperforms parallelization approaches proposed in past literature. We further demonstrate the efficiency of m-Cubes by evaluating a six-dimensional integral from a cosmology application, achieving significant speedup and greater precision than the CUBA library's CPU implementation of VEGAS. We also evaluate m-Cubes on a standard integrand test suite. m-Cubes outperforms the serial implementations of the Cuba and GSL libraries by orders of magnitude speedup while maintaining comparable accuracy. Our approach yields a speedup of at least 10 when compared against publicly available Monte Carlo based GPU implementations. In summary, m-Cubes can solve integrals that are prohibitively expensive using standard libraries and custom implementations. A modern C++ interface header-only implementation makes m-Cubes portable, allowing its utilization in complicated pipelines with easy to define stateful integrals. Compatibility with non-Nvidia GPUs is achieved with our initial implementation of m-Cubes using the Kokkos framework.

Sakiotis, Ioannis↗

Crack propagation in silica from reactive classical molecular dynamics simulations

Mechanistic insight into the process of crack growth can be obtained through molecular dynamics (MD) simulations. In this investigation of fracture propagation, a slit crack was introduced into an atomistic amorphous silica model and mode I stress was applied through far–field loading until the crack propagates. Atomic displacements and forces and an Irving–Kirkwood method with a Lagrangian kernel estimator were used to calculate the J –integral of classical fracture mechanics around the crack tip. The resulting fracture toughness (K IC ), 0.76 ± 0.16 MPa√m, agrees with experimental values. In addition, the stress fields and dissipation energies around the slit crack indicate the development of an inelastic region ~30Å in diameter. This is one of the first reports of KIC values obtained from up–scaled atomic–level energies and stresses through the J –integral. In conclusion, the application of the ReaxFF classical MD force field in this study provides the basis for future research into crack growth in multicomponent oxides in a variety of environmental conditions.

36 MATERIALS SCIENCE↗

Capacity Design Method for Integrated Convective/Radiant Terminals to Guarantee Overall and Local Environment

To achieve energy efficiency in the operation of heating devices and ensure thermal comfort in indoor environments, the integrated convective/radiant terminals have become an important development direction for heating systems. This study selected a 14 m 2 bedroom hot summer and cold winter region in China as a case study. Computational Fluid Dynamics (CFD) methodology was used to investigate the design of integrated convective/radiant terminals to ensure thermal comfort for both the entire room and partial space. The results indicate that focusing on partial space during the steady-state stage can achieve energy savings of 31.1% compared to guaranteeing the entire room. Additionally, during the start-up stage, there is a significant reduction of convective unit capacity by 17.6% when the start-up time is 15 minutes. These findings provide data support for the design and engineering applications of products of integrated convective/radiant terminals. Besides, the excess convection ratios for the entire room and partial space are specified as 0.69 to 0.80 and 0.73 to 0.83, respectively.

Chi, Junjie↗

Investigation of Adaptive-threshold Approaches for Determining Area-Time Integrals from Satellite Infrared Data to Estimate Convective Rain Volumes

The principal goal of this project is to establish relationships that would allow application of area-time integral (ATI) calculations based upon satellite data to estimate rainfall volumes. The research is being carried out as a collaborative effort between the two participating organizations, with the satellite data analysis to determine values for the ATIs being done primarily by the STC-METSAT scientists and the associated radar data analysis to determine the 'ground-truth' rainfall estimates being done primarily at the South Dakota School of Mines and Technology (SDSM&T). Synthesis of the two separate kinds of data and investigation of the resulting rainfall-versus-ATI relationships is then carried out jointly. The research has been pursued using two different approaches, which for convenience can be designated as the 'fixed-threshold approach' and the 'adaptive-threshold approach'. In the former, an attempt is made to determine a single temperature threshold in the satellite infrared data that would yield ATI values for identifiable cloud clusters which are closely related to the corresponding rainfall amounts as determined by radar. Work on the second, or 'adaptive-threshold', approach for determining the satellite ATI values has explored two avenues: (1) attempt involved choosing IR thresholds to match the satellite ATI values with ones separately calculated from the radar data on a case basis; and (2) an attempt involved a striaghtforward screening analysis to determine the (fixed) offset that would lead to the strongest correlation and lowest standard error of estimate in the relationship between the satellite ATI values and the corresponding rainfall volumes.

Smith, Paul L.↗

A creep model for metallic composites based on matrix testing: Application to Kanthal composites

An anisotropic creep model is formulated for metallic composites with strong fibers and low to moderate fiber volume percent (less than 40 percent). The idealization admits no creep in the local fiber direction and assumes equal creep strength in longitudinal and transverse shear. Identification of the matrix behavior with that of the isotropic limit of the theory permits characterization of the composite through uniaxial creep tests on the matrix material. Constant and step-wise creep tests are required as a data base. The model provides an upper bound on the transverse creep strength of a composite having strong fibers embedded in a particular matrix material. Comparison of the measured transverse strength with the upper bound gives an assessment of the integrity of the composite. Application is made to a Kanthal composite, a model high-temperature composite system. Predictions are made of the creep response of fiber reinforced Kanthal tubes under interior pressure.

Binienda, W. K.↗

Machine learning-enhanced design of lead-free halide perovskite materials using density functional theory

The investigation of emerging non-toxic perovskite materials has been undertaken to advance the fabrication of environmentally sustainable lead-free perovskite solar cells. This study introduces a machine learning methodology aimed at predicting innovative halide perovskite materials that hold promise for use in photovoltaic applications. The seven newly predicted materials are as follows: CsMnCl 4 , Rb 3 Mn 2 Cl 9 , Rb 4 MnCl 6 , Rb 3 MnCl 5 , RbMn 2 Cl 7 , RbMn 4 Cl 9 , and CsIn 2 Cl 7 . The predicted compounds are first screened using a machine learning approach, and their validity is subsequently verified through density functional theory calculations. CsMnCl 4 is notable among them, displaying a bandgap of 1.37 eV, falling within the Shockley-Queisser limit, making it suitable for photovoltaic applications. Here, through the integration of machine learning and density functional theory, this study presents a methodology that is more effective and thorough for the discovery and design of materials.

36 MATERIALS SCIENCE↗

Integrated Vehicle Health Management Project-Modeling and Simulation for Wireless Sensor Applications

This paper describes the efforts in modeling and simulating electromagnetic transmission and reception as in a wireless sensor network through a realistic wing model for the Integrated Vehicle Health Management project at the Glenn Research Center. A computer model in a standard format for an S-3 Viking aircraft was obtained, converted to a Microwave Studio software format, and scaled to proper dimensions in Microwave Studio. The left wing portion of the model was used with two antenna models, one transmitting and one receiving, to simulate radio frequency transmission through the wing. Transmission and reception results were inconclusive.

Wallett, Thomas M.↗

NASA Goddard Giovanni Support for YOTC

The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been twofold: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. In regards to the second challenge, it should be stressed that this problem will not be solved through the production and examination of one or a few high quality long-term records of fundamental quantities (e.g., SST, water vapor, cloud fraction). Rather, an alternative and more comprehensive paradigm is needed, one that integrates the multitude of applicable resources and measures of tropical convection in a manner that that can be better utilized by the diagnostic, modeling and forecasting communities to more completely and coherently focus on the problem.Because the goal of YOTC involves examining a scientifically complex, multi-scale process , rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO). The proposed dissemination framework for the YOTC satellite data archive is based on the Giovanni system. Giovanni is a web-based application developed by the NASA Goddard Earth Science (GES) Data and Information Service Center (DISC) that provides a simple and intuitive way to visualize, analyze, and access/download vast amounts of Earth science remote sensing data. A prototype YOTC Giovanni System (hereafter YOTC-GS) is in the process of being developed. YOTC-GS will provide access to level 2 (i.e. swath level data) and/or level 3 (i.e. gridded/mapped data) forms of satellite data, the choice or both depending on what is appropriate and relevant. The former is needed and better suited for detailed process examination, exploiting the highest temporal-spatial resolutions available and comparison to regional cloud-system resolving model / cloud resolving model (CSRM/CRM) model output. The latter is needed and more well suited for examination of phenomena, conditions and processes on large to global scales, and for comparisons to global model analyses, prediction and simulation output.

Ostrenga, Dana↗

Extending GPU-accelerated Gaussian integrals in the TeraChem software package to f type orbitals: Implementation and applications

Here, the increasing availability of graphics processing units (GPUs) for scientific computing has prompted interest in accelerating quantum chemical calculations through their use. However, the complexity of integral kernels for high angular momentum basis functions often limits the utility of GPU implementations with large basis sets or for metal containing systems. In this work, we report the implementation of f function support in the GPU-accelerated TeraChem software package through the development of efficient kernels for the evaluation of Hamiltonian integrals. The high efficiency of the resulting code is demonstrated through density functional theory (DFT) calculations on increasingly large organic molecules and transition metal complexes, as well as coupled cluster singles and doubles calculations on water clusters. Preliminary investigations into Ni(I) catalysis with DFT and the photochemistry of MnH(CH 3 ) with complete active space self-consistent field are also carried out. Overall, our GPU-accelerated software appears to be well-suited for fast simulation of large transition metal containing systems, as well as organic molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Embedding spatial decomposition in parareal in time power system simulation

We propose an approach for combining two decompositions in power system simulation, temporal and spatial, with a goal to achieve faster simulation time than utilizing either one of them alone. The proposed approach builds upon the structure of the Parareal algorithm for temporal decomposition and explores an efficient way of embedding the spatial decomposition into its coarse and fine solutions. This introduces two types of simultaneous parallelism in power system simulations - parallelism between system areas and between coarse integration intervals for time integration. The results from the application of the proposed approach are shown on a two-area system comprised of the IEEE 16-machine, 68-bus, and the IEEE 50-machine, 145-bus system.

Duan, Nan↗

Fully CMOS-compatible titanium nitride nanoantennas

CMOS-compatible fabrication of plasmonic materials and devices will accelerate the development of integrated nanophotonics for information processing applications. Using low-temperature plasma-enhanced atomic layer deposition (PEALD), we develop a recipe for fully CMOS-compatible titanium nitride (TiN) that is plasmonic in the visible and near infrared. Films are grown on silicon, silicon dioxide, and epitaxially on magnesium oxide substrates. By optimizing the plasma exposure per growth cycle during PEALD, carbon and oxygen contamination are reduced, lowering undesirable loss. We use electron beam lithography to pattern TiN nanopillars with varying diameters on silicon in large-area arrays. In the first reported single-particle measurements on plasmonic TiN, we demonstrate size-tunable darkfield scattering spectroscopy in the visible and near infrared regimes. Finally, the optical properties of this CMOS-compatible material, combined with its high melting temperature and mechanical durability, comprise a step towards fully CMOS-integrated nanophotonic information processing.

36 MATERIALS SCIENCE↗

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Novel Electrolyzer Applications: Providing More Than Just Hydrogen

Hydrogen can be used for many different applications and can be integrated into many different system architectures. One of the methods for producing the hydrogen is to use an electrolyzer. This work explores the flexibility of electrolyzers to behave as responsive loads. Experimental tests were performed for a proton exchange membrane (PEM) and an alkaline electrolyzer to assess the operational flexibility of electrolyzers to behave as responsive loads. The results are compared to the operational requirements to participate in end-user facility energy management, transmission and distribution system support, and wholesale electricity market services. Electrolyzers begin changing their electricity demand within milliseconds of a set-point change. The settling time after a set-point change is on the order of seconds. It took 6.5 minutes for the PEM unit to execute a cold start and 1 minute to turn off. In addition, a frequency disturbance correction test was performed and electrolyzers were able to accelerate the speed that the grid frequency can be restored. Electrolyzers acting as demand response devices can respond sufficiently fast and for a long enough duration to participate in all of the applications explored. Furthermore, electrolyzers can be operated to support a variety of applications while also providing hydrogen for industrial processes, transportation fuel, or heating fuel. Additionally, favorable operating properties and a variety of potential system architectures showcase the flexibility of electrolyzer systems.

08 HYDROGEN↗