Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Hybrid Work”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27

Single Entity Electrochemistry in Nanopore Electrode Arrays: Ion Transport Meets Electron Transfer in Confined Geometries

Electrochemical measurements conducted in confined volumes provide a powerful and direct means to address scientific questions at the nexus of nanoscience, biotechnology, and chemical analysis. How are electron transfer and ion transport coupled in confined volumes and how does understanding them require moving beyond macroscopic theories? Also, how do these coupled processes impact electrochemical detection and processing? We address these questions by studying a special type of confined-volume architecture, the nanopore electrode array, or NEA, which is designed to be commensurate in size with physical scaling lengths, such as the Debye length, a concordance that offers performance characteristics not available in larger scale structures. The experiments described here depend critically on carefully constructed nanoscale architectures that can usefully control molecular transport and electrochemical reactivity. We begin by considering the experimental constraints that guide the design and fabrication of zero-dimensional nanopore arrays with multiple embedded electrodes. These zero-dimensional structures are nearly ideal for exploring how permselectivity and unscreened ion migration can be combined to amplify signals and improve selectivity by enabling highly efficient redox cycling. Our studies also highlight the benefits of arrays, in that molecules escaping from a single nanopore are efficiently captured by neighboring pores and returned to the population of active redox species being measured, benefits that arise from coupling ion accumulation and migration. These tools for manipulating redox species are well-positioned to explore single molecule and single particle electron transfer events through spectroelectrochemistry, studies which are enabled by the electrochemical zero-mode waveguide (ZMW), a special hybrid nanophotonic/nanoelectronic architecture in which the lower ring electrode of an NEA nanopore functions both as a working electrode to initiate electron transfer reactions and as the optical cladding layer of a ZMW. Furthermore, while the work described here is largely exploratory and fundamental, we believe that the development of NEAs will enable important applications that emerge directly from the unique coupled transport and electron-transfer capabilities of NEAs, including in situ molecular separation and detection with external stimuli, redox-based electrochemical rectification in individually encapsulated nanopores, and coupled sorters and analyzers for nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tensor decompositions for count data that leverage stochastic and deterministic optimization

There is growing interest to extend low-rank matrix decompositions to multi-way arrays, or tensors. One fundamental low-rank tensor decomposition is the canonical polyadic decomposition (CPD). The challenge of fitting a low-rank, nonnegative CPD model to Poisson-distributed count data is of particular interest. Several popular algorithms use local search methods to approximate the maximum likelihood estimator (MLE) of the Poisson CPD model. Here, this work presents two new algorithms that extend state-of-the-art local methods for Poisson CPD. Hybrid GCP-CPAPR combines Generalized Canonical Decomposition (GCP) with stochastic optimization and CP Alternating Poisson Regression (CPAPR), a deterministic algorithm, to increase the probability of converging to the MLE over either method used alone. Restarted CPAPR with SVDrop uses a heuristic based on the singular values of the CPD model unfoldings to identify convergence toward optimizers that are not the MLE and restarts within the feasible domain of the optimization problem, thus reducing overall computational cost when using a multi-start strategy. We provide empirical evidence that indicates our approaches outperform existing methods with respect to converging to the Poisson CPD MLE.

CPAPR↗

Prediction of topological phases in metastable ferromagnetic $MPX_3$ monolayers

Density functional theory calculations are carried out to study the electronic and topological properties of MPX 3 (M = Mn, Fe, Co,Ni; X = S, Se) monolayers in the ferromagnetic (FM) metastable magnetic state. Here we find that FM MnPSe 3 monolayers host topological semimetal signatures that are gapped out when spin-orbit coupling is included. These findings are supported by explicit calculations of the Berry curvature and the Chern number. The choice of the Hubbard-U parameter to describe the d-electrons is thoroughly discussed, as well as the influence of using a hybrid-functional approach. The presence of band inversions and the associated topological features are found to be formalism-dependent. Nevertheless, routes to achieve the topological phase via the application of external biaxial strain are demonstrated. Within the hybrid-functional picture, topological band structures are recovered under a pressure of 15% (17 GPa). The present work provides a potential avenue for uncovering new topological phases in metastable ferromagnetic phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Intrinsic and complex defect engineering of quasi-one-dimensional ribbons Sb 2 S 3 for photovoltaics performance

Sb 2 S 3 has attracted great attention recently as a prospective solar cell absorber material. In this work, intrinsic defects, dopants, and their complexes in Sb 2 S 3 are systematically investigated by using hybrid functional theory. V Sb and V S are dominant native defects and pin the Fermi level near the midgap, which is consistent with the high resistivity observed experimentally. Both V Sb and V S introduce deep levels inside the band gap, which can trap free carriers. Our calculated deep transition levels of V Sb and Sb S are consistent well with the results of the deep-level transient spectroscopy measurement. We further study dopants (including Cu, Ti, Zn, Br, and Cl) in Sb 2 S 3 and find that Zn and Br/Cl are shallow acceptors and donors, respectively, which may be used to control the carrier and trap densities in Sb 2 S 3 . In addition, the defect complexes, i.e., Cu(Zn) Sb +V S and Cl(Br) S +V Sb are also investigated. The interaction between the donor and acceptor defects makes the defect levels of complexes shallower and less detrimental to carrier transport.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Kauhale 'O Kipapa: Kahikinui Community Cultural, Educational, and Resilience Center Preliminary Design Technical Assistance Summary Report

The Kahikinui Homestead Community in Maui faces energy resilience challenges due to its remote, off-grid location. This report summarizes preliminary technical assistance to design a microgrid for six modular homes using solar PV, wind, and battery storage. Findings show hybrid PV and battery systems, supplemented by small wind turbines, offer cost-effective, resilient solutions. This work supports enhanced energy independence and disaster preparedness for the community.

Quiroz, Jimmy Edward [Sandia National Laboratories↗

Modeling FLEX Human Actions Using the EMRALD Dynamic Risk Assessment Tool

Most current efforts have modified and applied existing human reliability analysis (HRA) methods to treat human actions related to beyond-design-basis external events in which diverse and flexible coping strategies (FLEX) equipment would be deployed. However, many questions remain regarding the suitability of legacy HRA methods to address FLEX human actions, sparking the need for a new method of reasonably evaluating them. In this context, Idaho National Laboratory (INL) researched a relatively new approach to treating FLEX human actions via Event Modeling Risk Assessment Using Linked Diagrams (EMRALD) software. EMRALD was developed to support the increasing need for dynamic probabilistic risk assessment (PRA) models that can respond to evolving plant conditions during simulations. A couple benefits were identified when analyzing FLEX human actions through this software. In general, it is especially useful for evaluating a strategy’s feasibility, including FLEX human actions that require a relatively long time to perform. In this paper, we suggest how FLEX human actions can be modeled using the EMRALD software. Two different HRA modeling approaches using EMRALD are introduced: (1) procedure-based modeling and (2) PRA/HRA-based modeling. The former approach was introduced in the authors’ previous paper, whereas this paper mainly discusses how the latter approach works for an extended loss of AC power (ELAP) scenario with relevant procedures and PRA models. A hybrid method combining the two modeling approaches is introduced at the paper’s conclusion.

99 GENERAL AND MISCELLANEOUS↗

Desalination Multi-Effect Evaporator Models in Support of Integrated Energy Systems

The purpose of this work is to contribute to the Integrated Energy Systems (IES) modeling efforts from the Department of Energy with Idaho National Laboratory. The DOE is working on a plug-and-play set of models in an open-source repository called HYBRID that can be used to improve IES modeling capabilities.

99 GENERAL AND MISCELLANEOUS↗

Efficient computational design of two-dimensional van der Waals heterostructures: Band alignment, lattice mismatch, and machine learning

Here, we develop a computational database, website applications (web-apps), and machine-learning (ML) models to accelerate the design and discovery of two-dimensional (2D) heterostructures. Using density functional theory (DFT) based lattice parameters and electronic band energies for 674 nonmetallic exfoliable 2D materials, we generate 226 779 possible bilayer heterostructures. We classify these heterostructures into type-I, -II, and -III systems according to Anderson’s rule, which is based on the relative band alignments of the noninteracting monolayers. We find that type II is the most common and type III the least common heterostructure type. We subsequently analyze the chemical trends for each heterostructure type in terms of the Periodic Table of constituent elements. The band alignment data can also be used for identifying photocatalysts and high-work-function 2D metals for contacts. We validate our results by comparing them to experimental data as well as hybrid-functional predictions. Additionally, we carry out DFT calculations of a few selected systems (MoS 2 /WSe 2 , MoS 2 /h-BN, and MoSe 2 /CrI 3 ), to compare the band-alignment description with the predictions from Anderson’s rule. We develop web-apps to enable users to virtually create combinations of 2D materials and predict their properties. Additionally, we use ML tools to predict band-alignment information for 2D materials. The web-apps, tools, and associated data will be distributed through the JARVIS-HETEROSTRUCTURE website. Our analysis, results, and the developed web-apps can be applied to the screening and design applications, such as finding alternative photocatalysts, photodetectors, and high-work-function (WF) 2D-metal contacts.

2-dimensional systems↗

A reduced order sulfuric acid decomposition model for a nuclear-powered hybrid sulfur cycle

A reduced order model of sulfuric acid decomposition within a bayonet chemical reactor was developed to support the U. S. Department of Energy Integrated Energy System program, and address the lack of knowledge in scaling and integration for joint chemical and nuclear processes. Sulfuric acid decomposition within a bayonet reactor was modeled to provide chemical and thermodynamic data relevant to advanced nuclear reactor-driven integrated energy systems based on desired operational scale and operational conditions. The temperature range required for high-temperature advanced nuclear reactor integrated energy systems, 750-850 °C, was shown to produce reasonable agreement (within a few percent relative error) with past models and experimental data, and yielded good efficiency results for bayonet reactor operations. The results of the reduced order model agreed with previous work from Savannah River National Labs within a maximum of 3.4% error on the decomposition of sulfur trioxide, and on previous Hybrid Sulfur flowsheets from Gorensek and Summers that showed operational temperature, pressure, and composition ranges for efficiency which made the Hybrid Sulfur cycle competitive with water electrolysis. Here, the agreement with previous high-fidelity models provided a framework for future Integrated Energy System grid evaluations with an advanced nuclear reactor and large-scale hydrogen production using a mathematical model to represent chemical operations.

08 HYDROGEN↗

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

42 ENGINEERING↗

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

14 SOLAR ENERGY↗

Hydrostatic pressure mapping of barium titanate phase transitions with quenched FeRh

We report a pressure study of the metamagnetic/ferroelectric hybrid heterostructure of a quenched FeRh thin film (25nm) grown on single crystal barium titanate (BTO). It has been previously reported that when the BTO undergoes a crystal transition a massive magnetization and coercivity change is triggered in the highly strain sensitive quenched FeRh thin film. Therefore quenched FeRh makes for an ideal probe for mapping a materials structural phase transitions. In this work we demonstrate this effect as a function of both temperature and hydrostatic pressure. As a result, we present the pressure dependence of the hybrid material which aligns identically with the BTO substrates pressure dependence reported in literature. The concept of combining a structural phase transitional (SPT) material with a magnetostrictive magnetic metal has been shown with vanadium oxides and our findings here prove that this methodology can be extended to strain sensitive metamagnetic materials systems in thin film, and possibly in bulk, heterostructures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Autonomous Output‐Oriented Aerosol Jet Printing Enabled by Hybrid Machine Learning

Additive manufacturing (AM) is rapidly revolutionizing modern manufacturing with recent progress in advanced printing methods and improved properties of printed materials. However, traditional AM methods are limited by their input‐oriented nature, which demands tedious trial‐and‐error tuning of printing parameters to achieve desired output properties. Here, in this work, an output‐oriented artificial intelligence‐integrated AM (AIAM) method is reported that enables an user to specify desired output properties while the printer autonomously discovers the optimal input printing parameters by integrating hybrid machine learning models and in situ measurements. Based on a predictive mapping between the input printing parameters and the output properties of interests established with <20 experiments designed by active learning, inverse design tasks are performed to intelligently generate the printing parameter settings that lead to desired outcomes using reinforcement learning. This method is demonstrated by autonomous aerosol jet printing (AJP) of conductive polymer films and achieving user‐defined electrical resistances with an ultralow error of 3.7%. The AIAM method, with its output‐oriented nature, holds the potential to significantly improve the autonomy, predictability, efficiency, and accessibility of the AM processes, which will unlock new possibilities in the autonomous and intelligent printing of a broad range of functional materials and devices.

36 MATERIALS SCIENCE↗

Analysis of the performance of a hybrid CPU/GPU 1D2D coupled model for real flood cases

Coupled 1D2D models emerged as an efficient solution for a two-dimensional (2D) representation of the floodplain combined with a fast one-dimensional (1D) schematization of the main channel. At the same time, high-performance computing (HPC) has appeared as an efficient tool for model acceleration. In this work, a previously validated 1D2D Central Processing Unit (CPU) model is combined with an HPC technique for fast and accurate flood simulation. Due to the speed of 1D schemes, a hybrid CPU/GPU model that runs the 1D main channel on CPU and accelerates the 2D floodplain with a Graphics Processing Unit (GPU) is presented. Since the data transfer between sub-domains and devices (CPU/GPU) may be the main potential drawback of this architecture, the test cases are selected to carry out a careful time analysis. Here, the results reveal the speed-up dependency on the 2D mesh, the event to be solved and the 1D discretization of the main channel. Additionally, special attention must be paid to the time step size computation shared between sub-models. In spite of the use of a hybrid CPU/GPU implementation, high speed-ups are accomplished in some cases.

54 ENVIRONMENTAL SCIENCES↗

Nanoscale Size Effects on Push–Pull Fe–O Hybridization through the Multiferroic Transition of Perovskite ϵ-Fe 2 O 3

Multiferroics have tremendous potential to revolutionize logic and memory devices through new functionalities and energy efficiencies. To reach their optimal capabilities will require better understanding and enhancement of the ferroic orders and couplings. In this work, we use ϵ-Fe 2 O 3 as a model system with a simplifying single magnetic ion. Using 15, 20, and 30 nm nanoparticles, we identify that a modified and size-dependent Fe–O hybridization changes the spin–orbit coupling and strengthens it via longer octahedra chains. Fe–O hybridization is modified through the incommensurate phase, with a unique two-step rearrangement of the electronic environment through this transition with attraction and then repulsion of electrons around tetrahedral Fe. Interestingly, size effects disappear in the high-temperature phase where the strongest Fe–O hybridization occurs. By manipulating this hybridization, we tune and control the multiferroic properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Nonuniform Ionic and Electronic Transport of Ceramic and Polymer/Ceramic Hybrid Electrolyte by Nanometer-Scale Operando Imaging for Solid-State Battery

Replacing the liquid electrolyte in lithium batteries with solid-state ion conductor is promising for next-generation energy storage that is safe and has high energy density. In this work, nanometer-resolution ionic and electronic transport imaging of Li 3 PS 4 (LPS), a solid-state electrolyte (SSE), is reported. This nm resolution is achieved by using a logarithm-scale current amplifier that enhances the current sensitivity to the fA range. Large fluctuations of ion current—one to two orders of magnitude on the LPS and on the LPS region of a polymer/LPS bulk hybrid SSE—that must be mitigated to eliminate Li dendrite formation and growth, are found. This ion current fluctuation is understood in terms of highly anisotropic transport kinetic barriers along the different crystalline axes due to different grain orientations in the polycrystalline and glass ceramic materials. The results on the bulk hybrid SSE show a sharp transition of ionic and electronic transport at the LPS/polymer boundary and decreases in average ionic current with decreasing polyimine particle size and with extensive cycling. The results elucidate the mechanism of polyimine extension into interparticles to prevent Li dendrite growth. This work opens up novel characterization of charge transport, which relates to Li plating and stripping for solid-state-batteries.

Li3PS4↗

Giant Topological Hall Effect in van der Waals Heterostructures of CrTe 2 /Bi 2 Te 3

Discoveries of the interfacial topological Hall effect (THE) provide an ideal platform for exploring the physics arising from the interplay between topology and magnetism. The interfacial topological Hall effect is closely related to the Dzyaloshinskii-Moriya interaction (DMI) at an interface and topological spin textures. However, it is difficult to achieve a sizable THE in heterostructures due to the stringent constraints on the constituents of THE heterostructures, such as strong spin-orbit coupling (SOC). Here, we report the observation of a giant THE signal of 1.39 mu Omega.cm in the van der Waals heterostructures of CrTe 2 /Bi 2 Te 3 fabricated by molecular beam epitaxy, a prototype of two-dimensional (2D) ferromagnet (FM)/topological insulator (TI). This large magnitude of THE is attributed to an optimized combination of 2D ferromagnetism in CrTe 2 , strong SOC in Bi 2 Te 3 , and an atomically sharp interface. Furthermore, our work reveals CrTe 2 /Bi 2 Te 3 as a convenient platform for achieving large interfacial THE in hybrid systems, which could be utilized to develop quantum science and high-density information storage devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗