Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “hybrids”

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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Single Ru Atoms Stabilized by Hybrid Amorphous/Crystalline FeCoNi Layered Double Hydroxide for Ultraefficient Oxygen Evolution

Abstract In view of the sluggish kinetics suppressing the oxygen evolution reaction (OER), developing efficient and robust OER catalysts is urgent and essential for developing efficient energy conversion technologies. Herein, hybrid amorphous/crystalline FeCoNi layered double hydroxide (LDH)‐supported single Ru atoms (Ru SAs/AC‐FeCoNi) are developed for enabling a highly efficient electrocatalytic OER. The amorphous outer layer in Ru SAs/AC‐FeCoNi is composed of abundant defect sites and unsaturated coordination sites, which can serve as anchoring sites to stabilize single Ru atoms. The crystalline inner has a highly symmetric rigid structure, thereby strengthening the stability of support for a long‐lasting OER. The synergistic effects endow this hybrid catalyst with extremely low overpotential (205 mV at 10 mA cm −2 ). Density functional theory calculation indicates that single Ru atoms stabilized by hybrid amorphous/crystalline FeCoNi LDH facilitate the formation of Ru–O* (rate‐determining step), thus accelerating the OER process.

Hu, Yidong↗
DOE OSTI2023

Porous and Water Stable 2D Hybrid Metal Halide with Broad Light Emission and Selective H 2 O Vapor Sorption

Abstract In this work we report a strategy for generating porosity in hybrid metal halide materials using molecular cages that serve as both structure‐directing agents and counter‐cations. Reaction of the [2.2.2] cryptand (DHS) linker with Pb II in acidic media gave rise to the first porous and water‐stable 2D metal halide semiconductor (DHS) 2 Pb 5 Br 14 . The corresponding material is stable in water for a year, while gas and vapor‐sorption studies revealed that it can selectively and reversibly adsorb H 2 O and D 2 O at room temperature (RT). Solid‐state NMR measurements and DFT calculations verified the incorporation of H 2 O and D 2 O in the organic linker cavities and shed light on their molecular configuration. In addition to porosity, the material exhibits broad light emission centered at 617 nm with a full width at half‐maximum (FWHM) of 284 nm (0.96 eV). The recorded water stability is unparalleled for hybrid metal halide and perovskite materials, while the generation of porosity opens new pathways towards unexplored applications ( e.g . solid‐state batteries) for this class of hybrid semiconductors.

Azmy, Ali↗
DOE OSTI2023

Porous and Water Stable 2D Hybrid Metal Halide with Broad Light Emission and Selective H 2 O Vapor Sorption

Here, in this work we report a strategy for generating porosity in hybrid metal halide materials using molecular cages that serve as both structure-directing agents and counter-cations. Reaction of the [2.2.2] cryptand (DHS) linker with Pb II in acidic media gave rise to the first porous and water-stable 2D metal halide semiconductor (DHS) 2 Pb 5 Br 14 . The corresponding material is stable in water for a year, while gas and vapor-sorption studies revealed that it can selectively and reversibly adsorb H 2 O and D 2 O at room temperature (RT). Solid-state NMR measurements and DFT calculations verified the incorporation of H 2 O and D 2 O in the organic linker cavities and shed light on their molecular configuration. In addition to porosity, the material exhibits broad light emission centered at 617 nm with a full width at half-maximum (FWHM) of 284 nm (0.96 eV). The recorded water stability is unparalleled for hybrid metal halide and perovskite materials, while the generation of porosity opens new pathways towards unexplored applications (e.g. solid-state batteries) for this class of hybrid semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Cellular Phosphate Sensing and Anion Binding by an Azacrown‐Calixpyrrole Hybrid

A hybrid receptor-sensor for anions originating from the merging of positively charged ammonium moieties for electrostatic attraction/stronger binding of azacrowns with directionality of calixpyrrole hydrogen bond donors for selectivity is investigated. As demonstrated this hybrid receptor-sensor shows a remarkable selectivity for orthophosphate even in the presence of other phosphates and anions found in cellular materials (K assoc H 2 PO 4 − >H 2 P 2 O 7 2− >AMP − ≫ADP 2− or ATP 3− over halides, nitrate, or hydrogen sulfate; all Na + salts in water) but also cellular polyphosphate or phospholipids. This selectivity is harnessed in a real-time monitoring of cell lysis by lysozyme, which releases orthophosphate and other phosphates and anions from the cells. This sensitive (LOD 0.4 μM) fluorescence-based microscale method compares favorably with the state-of-the-art techniques but can easily be practiced in a high-throughput screening (HTS) manner. The anion binding and selectivity in aqueous solutions were investigated by NMR and put in context with phosphate binding of the parent calix[4]pyrrole. The microscopic understanding of anion binding by the hybrid receptor was then obtained from a combination of density functional theory (DFT), classical molecular dynamics (MD) with explicit water solvation, and ab initio MD (AIMD) simulations. Correlating the NMR and fluorescence binding data with studies of solvation of the receptor, phosphate anion, and the resulting complex confirms the binding is largely driven by entropic component (TΔS) associated with receptor and anion desolvation.

Anions↗
DOE OSTI2020

Hybrid Carbon Dioxide Reduction Photocatalysts Consisting of Macrocyclic Cobalt(III) Complexes Deposited on Semiconductor Surfaces

Hybrid photocatalysts can be prepared by coupling metal ligand complexes with light-harvesting semiconductors. It is often challenging and time consuming to derivatize ligands with anchoring groups to effectively attach onto surfaces. In this study, we synthesized hybrid carbon dioxide reduction photocatalysts by directly depositing two macrocyclic Co(III) complexes on three different semiconductor surfaces (TiO 2 , N-Ta 2 O 5 and C 3 N 4 ). The resulting hybrid photocatalysts were characterized with various techniques and tested in CO 2 reduction reactions under different light conditions. Excellent visible-light CO 2 -reduction activity was obtained using C 3 N 4 as the light-harvesting semiconductor. Furthermore, density functional theory calculations were conducted to help understand interactions between the cobalt complexes with a model TiO 2 surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Free‐Standing α‐MoO 3 / Ti 3 C 2 MXene Hybrid Electrode in Water‐in‐Salt Electrolytes

While transition‐metal oxides such as α‐MoO 3 provide high capacity, their use is limited by modest electronic conductivity and electrochemical instability in aqueous electrolytes. Two‐dimensional (2D) MXenes, offer metallic conductivity, but their capacitance is limited in aqueous electrolytes. Insertion of partially solvated cations into Ti 3 C 2 MXene from lithium‐based water‐in‐salt (WIS) electrolytes enables charge storage at positive potentials, allowing a wider potential window and higher capacitance. Herein, we demonstrate that α‐MoO 3 /Ti 3 C 2 hybrids combine the high capacity of α‐MoO 3 and conductivity of Ti 3 C 2 in WIS (19.8 m LiCl) electrolyte in a wide 1.8 V voltage window. Cyclic voltammograms reveal multiple redox peaks from α‐MoO 3 in addition to the well‐separated peaks of Ti 3 C 2 in the hybrid electrode. This leads to a higher specific charge and a higher rate capability compared to a carbon and binder containing α‐MoO 3 electrode. These results demonstrate that the addition of MXene to less conductive oxides eliminates the need for conductive carbon additives and binders, leads to a larger amount of charge stored, and increases redox capacity at higher rates. In addition, MXene encapsulated α‐MoO 3 showed improved electrochemical stability, which was attributed to the suppressed dissolution of α‐MoO 3 . The work suggests that oxide/MXene hybrids are promising for energy storage.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fabrication and characterization of dextran/zein hybrid electrospun fibers with tailored properties for controlled release of curcumin

Abstract BACKGROUND In recent years, there has been considerable interest in the use of biopolymer electrospun nanofibers for various food applications due to the biocompatibility, biodegradability, and high loading capacity. Herein, we fabricated and characterized novel hybrid electrospun fibers from dextran (50%, w/v ) and zein (0–30%, w/v ) solutions, and the effects of various zein concentrations on the properties of the hybrid electrospun fibers were investigated. RESULTS When zein was added at low concentrations (5% and 10%), dextran and zein showed poor miscibility, as reflected by significantly decreased viscosity of the solutions, and the poor mechanical properties of the derived fiber membranes. When zein was added at medium concentrations (15–25%), hydrogen bonds were formed between dextran and zein molecules, as indicated by the red shift of Fourier‐transform infrared bands and β‐sheet to α‐helix structural transformations. The fiber membranes electrospun from a solution with 25% zein showed the most hydrophobic surface, with a water contact angle of 116.9°. The homogenous dispersion of dextran and zein resulted in improved mechanical properties for fibers electrospun from a solution with 30% zein. Curcumin encapsulating dextran/zein electrospun fibers exhibited effective radical scavenging activity and ferric reducing power, along with the desired controlled release behavior for curcumin delivery. CONCLUSION Food grade dextran/zein hybrid electrospun fibers demonstrated tunable properties, and appear to be promising as delivery systems for bioactive and edible antimicrobial food packaging. © 2021 Society of Chemical Industry.

Luo, Shiyuan↗
DOE OSTI2026

Trigonometric continuous-variable gates and hybrid quantum simulations of the sine-Gordon model

Hybrid qubit-qumode quantum computing platforms provide a natural setting for simulating interacting bosonic quantum field theories. However, existing continuous-variable gate constructions rely predominantly on polynomial functions of canonical quadratures. In this work, we introduce a complementary universality paradigm based on trigonometric continuous-variable gates, which enable a Fourier-like representation of bosonic operators and are particularly well suited for periodic and non-perturbative interactions. We present an ancilla-based framework for implementing trigonometric gates with arguments given by arbitrary Hermitian functions of qumode quadratures. The protocol yields unitary gates deterministically, and non-unitary gates through probabilistic post-selection. As a concrete application, we develop a hybrid qubit-qumode quantum simulation of the lattice sine-Gordon model. Using these gates, we prepare ground states via quantum imaginary-time evolution, simulate real-time dynamics, compute time-dependent vertex two-point correlation functions, and extract quantum kink profiles under topological boundary conditions. Our results demonstrate that trigonometric continuous-variable gates provide a physically natural framework for simulating interacting field theories on near-term hybrid quantum hardware, while establishing a parallel route to universality beyond polynomial gate constructions. We expect that the trigonometric gates introduced here to find broader applications, including quantum simulations of condensed matter systems, quantum chemistry, and biological models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

A novel additive manufacturing compression overmolding process for hybrid metal polymer composite structures

Metal polymer composites combining low density, high strength composites with highly ductile and tough metals have gained traction over the last few decades as lightweight and high-performance materials for industrial applications. However, the mechanical properties are limited by the interfacial bonding strength between metals and polymers achieved through adhesives, welding, and surface treatment processes. In this paper, a novel manufacturing process combining additive manufacturing and compression molding to obtain hybrid metal polymer composites with enhanced mechanical properties is presented. Additive manufacturing enabled deposition of polymeric material with fibers in a predetermined pattern to form tailored charge or preform for compression molding. Here, a grade 300 maraging steel triangular lattice is first fabricated using AddUp FormUp350 laser powder bed system and compression overmolded with additively manufactured long carbon fiber-reinforced polyamide-6,6 (40% wt. CF/PA66) preform. The fabricated hybrid metal polymer composites showed high stiffness and tensile strength. The stiffness and failure characteristics determined from the uniaxial tensile tests were correlated to a finite element model within 20% deviation. Fractographic analyses was performed using microscopy to investigate failure mechanisms of the hybrid structures.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Pre- and post-coppice production and biomass chemistry of eastern cottonwood and hybrid poplars in the southeastern US

Sustainably grown feedstocks for bioenergy and bioproducts are important tools to fight climate change, provide ecosystem services, and sequester carbon. Populus species including hybrid poplars have been utilized around the world, and in the southeastern US native eastern cottonwood (P. deltoides) is often favored due to its resistance to stem cankers. However, P. deltoides has historically been grown in single stem production and its relative performance in short rotation coppice production, prevalent in Europe, is not well documented. Therefore, this study's goals were to evaluate eastern cottonwood (D × D) and hybrid poplar (P. deltoides × P. maximowiczii (D × M) and P. deltoides × P. trichocarpa (D × T) taxa) productivity under a two-year establishment and two-year coppice cycle, analyze biomass chemistry properties, identify drivers of productivity, and select clones suited for marginal vs. optimal sites. We found that D × M and D × D grew best in both establishment and coppice rotation with production increasing after coppice. Taxa and clones exhibited few differences in select biomass chemistry properties despite differences in growth rate and stem size. Across years and sites, production was correlated with the soil's carbon to nitrogen ratio, percentage of sand, and shrink-swell potential of the soil. A D × M clone ‘9709’ tended to perform better than other tested clones on marginal sites and had the highest survival rate after four years. Overall, this research suggests that Populus species can be grown in coppice rotation in the southeastern US with the potential for hybrid poplars to be successful on certain sites in the region although longer term studies are necessary to confirm these results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

High-performance aqueous zinc-ion hybrid capacitors based on 3D printed metal-organic framework cathodes

The zinc-ion hybrid capacitor is a promising energy storage device, but current overall capacity is limited by the capacitance of the carbon cathode. We have produced a hierarchically porous, nitrogen-doped carbon cathode with good cycling and mechanical stability by 3D printing and pyrolysis of the zinc-based metal–organic framework ZIF-8. When incorporated into a zinc-ion hybrid capacitor, we achieved an areal capacitance of 16.9 F cm -2 and energy density of 7.23 mW h cm -2 , outperforming zinc-ion hybrid capacitors based on conventional cathodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Stress-hybrid virtual element method on six-noded triangular meshes for compressible and nearly-incompressible linear elasticity

In this paper, we present a first-order Stress-Hybrid Virtual Element Method (SH-VEM) on six-noded triangular meshes for linear plane elasticity. Here, we adopt the Hellinger–Reissner variational principle to construct a weak equilibrium condition and a stress based projection operator. In each element, the stress projection operator is expressed in terms of the nodal displacements, which leads to a displacement based formulation. This stress-hybrid approach assumes a globally continuous displacement field while the stress field is discontinuous across each element. The stress field is initially represented by divergence-free tensor polynomials based on Airy stress functions, but we also present a formulation that uses a penalty term to enforce the element equilibrium conditions, referred to as the Penalty Stress-Hybrid Virtual Element Method (PSH-VEM). Numerical results are presented for PSH-VEM and SH-VEM, and we compare their convergence to the composite triangle FEM and B-bar VEM on benchmark problems in linear elasticity. The SH-VEM converges optimally in the L 2 norm of the displacement, energy seminorm, and the L 2 norm of hydrostatic stress. Furthermore, the results reveal that PSH-VEM converges in most cases at a faster rate than the expected optimal rate, but it requires the selection of a suitably chosen penalty parameter.

42 ENGINEERING↗
DOE OSTI2022

Rolling Optimization of Transmission Network Recovery and Load Restoration Considering Hybrid Wind-Storage System and Cold Load Pickup

A common solution to deal with the stochasticity introduced by fast-ramping wind power integration is to equip wind farms (WFs) with energy storage systems (ESSs) to formulate hybrid WF-ESSs. In addition to leveling off wind power fluctuations during normal operations, a hybrid WF-ESS can be a flexible power source to accumulate the power system restoration. In this paper, we propose a rolling optimization model for transmission network recovery and load restoration considering the contributions of WF-ESSs. The proposed model is formulated as a mixed integer linear programming problem that simultaneously optimizes the amount and location of restorable load blocks as well as the restoration lines. The cold load pickup features of interrupted loads considering the outage duration are modeled in detail. A chance-constrained method is employed to deal with the uncertainty of wind power, and a rolling horizon-based framework is adopted to reduce the influence of forecast error. Case studies are conducted on both New England 39-bus system and part of a provincial power system in China. The results show that the load restoration process can be significantly accelerated by employing the proposed method and contributions of hybrid WF-ESSs to power system restoration are validated.

chance-constrained optimization↗
DOE OSTI2023

A hybrid deep neural operator/finite element method for ice-sheet modeling

One of the most challenging and consequential problems in climate modeling is to provide probabilistic projections of sea level rise. A large part of the uncertainty of sea level projections is due to uncertainty in ice sheet dynamics. At the moment, accurate quantification of the uncertainty is hindered by the cost of ice sheet computational models. In this work we develop a hybrid approach to approximate existing ice sheet models at a fraction of their cost. Our approach consists of replacing the finite element model for the momentum equations for the ice velocity, the most expensive part of an ice sheet model, with a Deep Operator Network, while we retain a classic finite element discretization for the evolution of the ice thickness. We show that the resulting hybrid model is very accurate and it is an order of magnitude faster than the traditional finite element model. Further, a distinctive feature of the proposed model, compared to other neural network approaches, is that it can handle high-dimensional parameter spaces (parameter fields) such as the basal friction at the bed of the glacier and can therefore be used for generating samples for uncertainty quantification. Further, we study the impact of hyper-parameters, number of unknowns and correlation length of the parameter distribution on the training and accuracy of the Deep Operator Network on a synthetic ice sheet model. We then target the evolution of the Humboldt glacier in Greenland and show that our hybrid model can provide accurate statistics of the glacier mass loss and can be effectively used to accelerate the quantification of uncertainty.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Core-shell metallic alloy nanopillars-in-dielectric hybrid metamaterials with magneto-plasmonic coupling

Combining plasmonic and magnetic properties, namely magneto-plasmonic coupling, inspires great research interest and the search for magneto-plasmonic nanostructure becomes considerably critical. In this work, we designed a nanopillar-in-matrix structure with core–shell alloyed nanopillars for both BaTiO 3 (BTO)-Au 0.5 Co 0.5 (AuCo) and BTO-Au 0.25 Cu 0.25 Co 0.25 Ni 0.25 (AuCuCoNi) hybrid systems, i.e., ferromagnetic alloy cores (e.g., Co or CoNi) with plasmonic shells (e.g., Au or Au/Cu). These core–shell alloy nanopillars are uniformly embedded into a dielectric BTO matrix to form a vertically aligned nanocomposite (VAN) structure. Both hybrid systems present excellent epitaxial quality and interesting multi-functionality, e.g., high magnetic anisotropy, magneto-optical coupling response, tailorable plasmonic resonance wavelength, tunable hyperbolic properties and strong optical anisotropy. These alloyed nanopillars-in-matrix designs provide enormous potential for complex hybrid material designs with multi-functionality and demonstrate strong interface enabled magneto-plasmonic coupling along with plasmonic and magnetic performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Alignment of the CLAS12 central hybrid tracker with a Kalman Filter

Several factors can contribute to the difficulty of aligning the sensors of tracking detectors, including a large number of modules, multiple types of detector technologies, and non-linear strip patterns on the sensors. All three of these factors apply to the CLAS12 CVT, which is a hybrid detector consisting of planar silicon sensors with non-parallel strips, and cylindrical micromegas sensors with longitudinal and arc-shaped strips located within a 5 T superconducting solenoid. To align this detector, we used the Kalman Alignment Algorithm, which accounts for correlations between the alignment parameters without requiring the time-consuming inversion of large matrices. This is the first time that this algorithm has been adapted for use with hybrid technologies, non-parallel strips, and curved sensors. We present the results for the first alignment of the CLAS12 CVT using straight tracks from cosmic rays and from a target with the magnetic field turned off. After running this procedure, we achieved alignment at the level of 10 µm, and the widths of the residual spectra were greatly reduced. These results attest to the flexibility of this algorithm and its applicability to future use in the CLAS12 CVT and other hybrid or curved trackers, such as those proposed for the future Electron-Ion Collider.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A deep learning-based battery sizing optimization tool for hybridizing generation plants

Hybrid generation and energy storage systems offer the ability to increase flexibility of the combined asset. This flexibility can be used to increase provision of services already provided by the generation asset, such as timing sale of electricity to the energy market during high price periods, and also enable provision of additional services, such as ancillary services or contribute to resource adequacy. From a generation asset owner perspective, the decision to hybridize includes selecting an energy storage system that, among other factors, maximizes financial performance of the energy storage investment. Yet, existing tools to optimize energy storage sizing are either too rudimentary (i.e., based on “rules of thumb”) or too complex to implement (i.e., require specialized engineering and software knowledge and a high-performance computer to run). This work presents a novel deep learning-based battery sizing optimization tool that is designed to help generation asset owners easily assess preliminary sizing considerations for potential battery investments to hybridize their generation facility. The tool uses deep learning to predict revenue over a broad search space of potential battery sizes, estimates capital and operating costs (including accounting for battery degradation), and computes financial performance of each potential battery system investment, recommending a system with maximum financial performance. The tool is tested and validated for hydropower assets. Finally, this tool will help a greater cross-section of industry consider investments in battery systems, increasing their revenue and helping them compete in rapidly evolving electrify markets.

13 HYDRO ENERGY↗
DOE OSTI2024

Tribological behavior of hybrid Aluminum-TiB 2 metal matrix composites for brake rotor applications

Here, this research investigates the feasibility of hybrid aluminum metal matrix composites (MMC) incorporating TiB 2 particles for brake rotor applications. The composites were produced by incorporating both in-situ, submicron-sized TiB 2 particles and regular micron-sized TiB 2 powders via stir and squeeze casting techniques into A206 aluminum alloy matrix. Systematic adjustments in the fractions of in-situ and ex-situ TiB 2 particles were conducted to evaluate their impact on wear behavior and mechanisms. Combination of both particle types allowed composites with up to 10 vol% of reinforcements. Composites with higher proportions of ex-situ particles demonstrated increased wear resistance compared to those solely composed of in-situ particles, control specimens without TiB 2 , and conventional cast iron counterparts. The lowest wear rate for the hybrid composites sliding against phenolic brake pads was 1.1 × 10 -5 mm 3 /Nm, signifying a 3-fold reduction relative to cast iron sliding against the same pads. Wear analysis elucidated distinctive mechanisms within the hybrid composites, characterized by mild fragmented abrasive wear, adhesive wear, and plastic deformation, accompanied by the formation of an intermixed tribo-oxide layer.

42 ENGINEERING↗