Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Transfer function design”

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 253 records · Page 14

Machine learning for accuracy in density functional approximations

Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine learning approaches hold the potential to boost the predictive power of computationally efficient electronic structure methods, such as density functional theory, to chemical accuracy and to correct for fundamental errors in density functional approaches. In this paper, recent progress in applying machine learning to improve the accuracy of density functional and related approximations is reviewed. Promises and challenges in devising machine learning models transferable between different chemistries and materials classes are discussed with the help of examples applying promising models to systems far outside their training sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Light-Emitting Organic Semiconductor-Incorporated Perovskites: Fundamental Properties and Device Applications

Recently, organic semiconductor-incorporated perovskites (OSiPs) have emerged as a new subclass of next-generation organic–inorganic hybrid materials. OSiPs combine the advantages of organic semiconductors, such as large design windows and tunable optoelectronic functionalities, with the excellent charge-transport properties of the inorganic metal-halide counterparts. OSiPs provide a new materials platform for the exploitation of charge and lattice dynamics at the organic–inorganic interfaces for various applications. This Perspective reviews recent achievements in OSiPs highlighting the benefits from organic semiconductor incorporation and elucidates the fundamental light-emitting mechanism, energy transfer, as well as band alignment structures at the organic–inorganic interface. Finally, insights on the emission tunability lead toward a discussion of the potential of OSiPs in light-emitting applications, such as perovskite light-emitting diodes or lasing systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Conceptual Fuel Element Design Candidates for Conversion of High Flux Isotope Reactor with Low-Enriched Uranium Silicide Dispersion Fuel

Engineering design studies are underway to assess the feasibility of converting the High Flux Isotope Reactor (HFIR) to operate with low-enriched uranium (LEU) silicide dispersion (U3Si2-Al) fuel. These studies are supported by the U.S. Department of Energy National Nuclear Security Administration’s Office of Material Management and Minimization. A systematic approach employing neutronic and thermal-hydraulic analyses have been performed with the ORNL Shift and HFIR Steady State Heat Transfer Code tools, respectively, to predict reactor performance and thermal safety margins for proposed LEU3Si2-Al fuel designs. The design process was initiated by generating an optimized design with fabrication features identified from previous studies that result in excellent performance and safety metrics. The approach continued by substituting a single fabrication feature anticipated to be difficult to manufacture with another feature expected to perform an analogous function to that of the removed feature. Four conceptual fuel element design candidates, with various fabrication features, for conversion of HFIR with 4.8 gU/cm3 LEU3Si2-Al fuel have been generated and shown to meet pre-defined performance and safety metrics. Results to date indicate that HFIR could convert with the subject fuel system and meet performance and safety requirements if, among other considerations, fabrication of the specific design features are demonstrated and qualification of the fuel is complete under HFIR-specific conditions.

Chandler, David↗

Modeling the co-assembly of binary nanoparticles

Abstract In this work, we present a binary assembly model that can predict the co-assembly structure and spatial frequency spectra of monodispersed nanoparticles with two different particle sizes. The approach relies on an iterative algorithm based on geometric constraints, which can simulate the assembly patterns of particles with two distinct diameters, size distributions, and at various mixture ratios on a planar surface. The two-dimensional spatial-frequency spectra of the modeled assembles can be analyzed using fast Fourier transform analysis to examine their frequency content. The simulated co-assembly structures and spectra are compared with assembled nanoparticles fabricated using transfer coating method are in qualitative agreement with the experimental results. The co-assembly model can also be used to predict the peak spatial frequency and the full-width at half-maximum bandwidth, which can lead to the design of the structure spectra by selection of different monodispersed particles. This work can find applications in fabrication of non-periodic nanostructures for functional surfaces, light extraction structures, and broadband nanophotonics.

Mohanty, Saurav (ORCID:0009000302592855)↗

From Structured Solvents to Hybrid Materials (SS2HM) for Chemically Selective Capture and Electromagnetic Release of CO 2 : Mechanisms, Stability and Interfaces (Final Report)

The goal of this research program was to develop high capacity sorbents amenable for alternative regeneration approaches for direct air capture (DAC) of CO 2 . In particular, the research aimed to develop an understanding of CO 2 binding mechanism, thermal and oxidative stability, and regeneration energetics of functionalized ionic liquids (ILs), deep eutectic solvents (DESs), and porous materials. ILs and DESs are high-dielectric solvents with structural tunability that permits the rational-design for energy-efficient regeneration approaches based on electromagnetic (EM) field and moisture-swing. By further incorporating these solvents into polymeric capsules and other structural supports, multi-scale interfaces for targeted CO 2 and energy transfers were achieved. Aspects related to CO 2 capacity, selectivity, stability, dielectric properties, and binding energies were examined through experimental and computational design to identify molecular descriptors to inform future design of structured solvents and hybrid materials for DAC. Enclosed final report details the key findings, science advancements, and workforce development efforts from this project.

36 MATERIALS SCIENCE↗

Ab Initio Evaluation of Uranium Carbide S(α,β) and Thermal Neutron Cross Sections

Uranium Carbide (UC) is a nuclear fuel material which offers better neutron economy and lower fuel-cycle costs compared to conventional mixed-oxide fuels. UC’s lattice binding and dynamical properties impact thermal neutron scattering and low temperature epithermal resonance absorption. The Thermal Scattering Law (TSL) describes the scattering system available energy and momentum transfer states. There is no TSL evaluation for UC in the ENDF/B-VIII.0 database; herein, ab-initio lattice dynamics (AILD) techniques are invoked to calculate the phonon spectrum for UC using spin-orbit-coupling density functional theory (DFT). The TSLs, inelastic and elastic thermal scattering cross sections for Uranium and Carbon in UC, respectively, are calculated in FLASSH for use in higher fidelity reactor design calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Revealing the Influence of Binding Motifs on Electron Transfer and Recombination Kinetics for CdSe Quantum Dots Functionalized with a Modified Viologen

Anchoring of molecules to the surfaces of semiconductor nanocrystals (NCs) presents an opportunity to leverage the precise synthetic tunability of molecular function and the remarkable light harvesting properties of NCs to drive photochemical reactions. However, charge transfer between the two species depends not only on the energy level alignments but also on the details of their binding interactions, which are difficult to probe. Here, in this work, we characterize the binding between CdSe quantum dots (QDs) and a new phosphonated derivative of the electron acceptor methyl viologen, designed to attach to the QD surface via the phosphonate group. We use isothermal titration calorimetry to probe the thermodynamics of the QD–molecule interaction and use the parameters determined therein to analyze transient absorption spectroscopy measurements of forward and back electron transfer from QDs to the viologen. We find that the ligand-like phosphonate binding leads to an electron-transfer rate constant that is 3 orders of magnitude smaller than that for the face-on binding of the bipyridine ring of methyl viologen. Back electron transfer is also significantly slower in the derivative. Interestingly, a minor fraction of the phosphonated derivative also binds in the face-on configuration, with similar forward and back electron transfer kinetics as methyl viologen. Numerical simulations show that the ligand-like binding will lead to significantly improved quantum yields of photocatalysis over a wide range of reaction rates. By independently characterizing binding thermodynamics and charge transfer kinetics, this work reveals how the complexities underlying electron transfer at the NC–molecule interface determine photocatalytic outcomes. This work also represents a step toward controlling forward and back electron transfer kinetics via rational molecular design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dual-Responsive Macromolecular Surfaces with Binary Patterns

The development of nanopatterned interfaces incorporating multiple stimuli-responsive polymers has great potential for advancing smart sensors and molecular capture devices, yet it remains challenging due to limitations in patterning techniques and “grafting from” methods. Here, we present a binary-patterned surface featuring honeycomb-shaped photothermal polypyrrole (PPy) and thermally responsive poly(ethylene glycol methyl ether acrylate-co-poly(ethylene glycol) methyl ether acrylate) [poly(EGMEA-co-PEGMEA)] brushes within the cavities, fabricated using colloidal lithography and surface-initiated photoinduced electron transfer-reversible addition–fragmentation chain transfer (SI-PET-RAFT) polymerization. The morphology of the surface can be precisely tuned by adjusting the height of each domain. This design integrates unique topographical features with the stimuli-responsiveness of the polymer, enabling the collapse of the copolymer brushes through direct heating or photothermal conversion of PPy under near-IR light. In conclusion, this innovative system offers potential capture-release functionality, providing versatility for diverse applications and enhancing adaptability across different functional scenarios.

Copolymers↗

Control over emergence and alignment of transient blisters in thermo-responsive gels using hierarchically patterned substrates

Surfaces with tunable microscale textures are vital in a large variety of technological applications, including heat transfer, antifouling and adhesion. To facilitate such broad-scale use, there is a need to create surfaces that undergo reconfigurable changes in topology and thus, enable switchable functionality. To date, there is a relative dearth of methods for engineering surfaces that can be actuated to change topography over a range of length scales, and hence, form tunable hierarchically structured layers. Combining modeling and experiments, we design a geometrically patterned, thermo-responsive poly (N-isopropylacrylamide) gel film that undergoes controllable hierarchical changes in topology with changes in temperature. At the bottom, the film is covalently bound to a solid, curved substrate; at the top, the film encompasses longitudinal rectangular ridges that are oriented perpendicular to the underlying cylindrical curves. At temperatures below lower critical solution temperature (LCST), the swollen gel exhibits 3D variations in polymer density and thickness defined by the gel's top and bottom topography. As the temperature rises above LCST, the interplay between the upper ridges and lower curves in the gel drives non-uniform, directional solvent transport, the nucleation and propagation of a phase-separated higher-density skin layer, and the resulting pressure buildup within the film. These different, interacting kinetic processes lead to an instability, which produces transient microscopic blisters in the film. Through simulations, we show how tuning the width of the ridges modifies the propagation of a skin layer and creates localized pressure build-up points, which enables control over the emergence, distribution, and alignment of the microscopic blisters. Futhermore, we provide a simple argument to predict the size of such microscopic features. Experiments confirm our predictions and further highlight how our computational model enables the rational design of topographical transitions in these tunable films. The development of actuatable, hierarchically structured films provides new routes for achieving switchable functionality in actuators, drug release systems and adhesives.

42 ENGINEERING↗

A Novel Three Phase Oak Ridge DC / AC Converter for Wireless Grid Tied Applications

In this study, a novel three phase oak ridge dc to ac converter is introduced for wireless mobility energy storage (WMES) applications to support the grid demand during peak times. The proposed topology can be used in a bi-directional operation between ac grid and dc terminals of energy storage by accomplishing unity power factor. Inherent merit of the technology can directly merge dc input to the high frequency and 60 Hz grid frequency by superimposing through the wireless coils. Theoretical and simulation results are validated by the simulation analysis for 20 kW output power. The functionality of the proposed three phase system is established by using 6 inches air gap between the couplers with the input of 675 V DC and output of 277 V AC, RMS . The system overall design analysis is demonstrated for simulation analysis and simulation results are presented achieving 3% current total harmonic distortion (THD) and 0.99 power factor (PF) at full load 20 kW wireless power transfer.

Asa, Erdem↗

Non-bonding interaction of dual atom catalysts for enhanced oxygen reduction reaction

Here, we demonstrate the design of graphene-supported dual atom catalysts (DACs) for the four-electron oxygen reduction reaction (ORR), by utilizing the non-bonding interaction of counterpart metals (M) that synergistically tune the electronic properties and catalytic activity of the Fe active site in FeMN 6 -DAC and FeMN 8 -DAC systems, where M stands for Fe, Co, Ni, Cu, and Zn. More specifically, for Fe-M distances below 15Å, the non-bonding interaction is significant, making the system act as the DAC. We predicted that FeNiN 6 -DAC and FeNiN 8 -DAC exhibit a low ORR overpotential (η ORR ) of 0.28 V and 0.47 V, respectively, which are at the summits of volcano plots. This low η ORR originates from the high Bader charge transfer coupled with high spin density at the Fe site in both the FeNiN 6 -DAC and FeNiN 8 -DAC systems, which weakens the adsorption of OH* intermediate while enhancing its desorption to H 2 O. Guided by these density functional theory (DFT) computational results, we synthesized FeCoN 8 -DAC and FeNiN 8 -DAC along with N-doped graphene and confirmed their structures with scanning transmission electron microscopy (STEM), X-ray photoelectron spectroscopy (XPS), X-ray absorption near-edge structure (XANES), extended X-ray absorption fine structure (EXAFS), and electron spin resonance (ESR). We verify experimentally the catalytic activities and find that FeNiN 8 -DAC has the low experimental overpotential of 0.39 V with a Tafel slope of 47 mVdec -1 . Based on these results, we propose a DFT-guided strategy to tune the charge transfer and spin population of the active site toward designing DACs for electrochemical ORR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Rise of Neural Networks for Materials and Chemical Dynamics

Machine learning (ML) is quickly becoming a premier tool for modeling chemical processes and materials. ML-based force fields, trained on large data sets of high-quality electron structure calculations, are particularly attractive due their unique combination of computational efficiency and physical accuracy. This Perspective summarizes some recent advances in the development of neural network-based interatomic potentials. Designing high-quality training data sets is crucial to overall model accuracy. One strategy is active learning, in which new data are automatically collected for atomic configurations that produce large ML uncertainties. Another strategy is to use the highest levels of quantum theory possible. Transfer learning allows training to a data set of mixed fidelity. A model initially trained to a large data set of density functional theory calculations can be significantly improved by retraining to a relatively small data set of expensive coupled cluster theory calculations. These advances are exemplified by applications to molecules and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Programmable Gene Knockdown in Diverse Bacteria Using Mobile‐CRISPRi

Abstract Facile bacterial genome sequencing has unlocked a veritable treasure trove of novel genes awaiting functional exploration. To make the most of this opportunity requires powerful genetic tools that can target all genes in diverse bacteria. CRISPR interference (CRISPRi) is a programmable gene‐knockdown tool that uses an RNA‐protein complex comprised of a single guide RNA (sgRNA) and a catalytically inactive Cas9 nuclease (dCas9) to sterically block transcription of target genes. We previously developed a suite of modular CRISPRi systems that transfer by conjugation and integrate into the genomes of diverse bacteria, which we call Mobile‐CRISPRi. Here, we provide detailed protocols for the modification and transfer of Mobile‐CRISPRi vectors for the purpose of knocking down target genes in bacteria of interest. We further discuss strategies for optimizing Mobile‐CRISPRi knockdown, transfer, and integration. We cover the following basic protocols: sgRNA design, cloning new sgRNA spacers into Mobile‐CRISPRi vectors, Tn 7 transfer of Mobile‐CRISPRi to Gram‐negative bacteria, and ICE Bs1 transfer of Mobile‐CRISPRi to Bacillales. © 2020 The Authors. Basic Protocol 1 : sgRNA design Basic Protocol 2 : Cloning of new sgRNA spacers into Mobile‐CRISPRi vectors Basic Protocol 3 : Tn 7 transfer of Mobile‐CRISPRi to Gram‐negative bacteria Basic Protocol 4 : ICE Bs1 transfer of Mobile‐CRISPRi to Bacillales Support Protocol 1 : Quantification of CRISPRi repression using fluorescent reporters Support Protocol 2 : Testing for gene essentiality using CRISPRi spot assays on plates Support Protocol 3 : Transformation of E. coli by electroporation Support Protocol 4 : Transformation of CaCl 2 ‐competent E. coli

59 BASIC BIOLOGICAL SCIENCES↗

A Vibrational Probe of Electrical Doping in N2200 and Fermi-Level Alignment at Polymer Cathode/Metal Cocatalyst/Electrolyte Junctions

Hybrid (photo)­cathodes consisting of conjugated polymer and hydrogen evolution reaction (HER) cocatalysts are an emerging platform for low-cost solar fuel generation. Poly­{[N,N′-bis­(2-octyldodecyl)-naphthalene-1,4,5,8-bis­(dicarboximide)-2,6-diyl]-alt-5,5′-(2,2′-bithiophene)}, known as P­(NDI2OD-T2) or N2200, is a promising electron accepting material for bulk heterojunction photocathodes. Unlike inorganic (photo)­electrodes, much less is known about the energetic alignment of conjugated polymer electrode/metal/electrolyte junctions. Here, in this work, we investigate the electrical doping behavior in an N2200 cathode and its Fermi-level alignment with gold nanoparticles, which is used here as a model for the hydrogen evolution metal cocatalyst. Through UV/visible, Raman, and attenuated total-reflectance infrared spectroelectrochemistry, we observe the impact of electrical doping on the vibrational frequencies of neutral, anion, and dianion species in N2200, which suggests that electron density changes within the corresponding naphthalene-diimide (NDI) units. Upon one-electron reduction, the $C=O$ stretching frequency of the NDI anion unit (polaron) shows a red shift by ∼ 68 cm –1 . Additionally, the $C=O$ stretching frequency of neutral units in the doped N2200 shows a minor red shift of ∼ 5 cm –1 , suggesting charge transfer from neighboring polaron units. Surface-enhanced Raman spectroscopy measurements of a gold nanoparticle-functionalized N2200 electrode revealed that the Au Fermi level only shifts with that of N2200 upon polaron formation; thus, the formal potential of polymer polaron formation determines the behavior of the catalyst Fermi level, which we posit will modulate reaction capability. This mechanistic study provides a new approach for understanding the nanometer-scale energetics at the conjugated polymer/cocatalyst junction and provides critical insights for the future design of HER (photo)­cathodes.

charge transfer↗

Impedance-Based Prediction of SSR-Generated Harmonics in Doubly-Fed Induction Generators

Doubly-fed induction generators (DFIGs) are prone to subsynchronous resonance (SSR) with series-compensated transmission lines and experiencing SSR-generated harmonics of wide-ranging magnitudes. This paper presents a large-signal impedance-based approach for the prediction of the magnitude of SSR-generated harmonics in DFIGs. Note that the large-signal impedance of a network shows variation in its impedance response with the magnitude of perturbation at its terminals. It is discovered in this paper that the impedance of a series-compen- sated transmission line starts changing with the magnitude of SSR because of the metal-oxide varistor-based protection of series capacitors in the line. The changing line impedance halts the growth of the SSR beyond a certain point, where the DFIG forms a limit-cycle mode and emits harmonics at the SSR frequency. The discovered role of the protection of series capacitors in SSR not only enables the prediction of SSR-generated harmonics but also can be used for the timely detection of an SSR event to avoid system disruption and sudden loss of bulk generation. The large- signal impedance-based prediction of SSR-generated harmonics in DFIG-based wind and hydro generators is demonstrated using numerical simulations of a 2.5-MVA, 690-V DFIG supplying to a series-compensated transmission line.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Synergistic learning with multi-task DeepONet for efficient PDE problem solving

Multi-task learning (MTL) is an inductive transfer mechanism designed to leverage useful information from multiple tasks to improve generalization performance compared to single-task learning. It has been extensively explored in traditional machine learning to address issues such as data sparsity and overfitting in neural networks. In this work, we apply MTL to problems in science and engineering governed by partial differential equations (PDEs). However, implementing MTL in this context is complex, as it requires task-specific modifications to accommodate various scenarios representing different physical processes. To this end, we present a multi-task deep operator network (MT-DeepONet) to learn solutions across various functional forms of source terms in a PDE and multiple geometries in a single concurrent training session. We introduce modifications in the branch network of the vanilla DeepONet to account for various functional forms of a parameterized coefficient in a PDE. Additionally, we handle parameterized geometries by introducing a binary mask in the branch network and incorporating it into the loss term to improve convergence and generalization to new geometry tasks. Our approach is demonstrated on three benchmark problems: (1) learning different functional forms of the source term in the Fisher equation; (2) learning multiple geometries in a 2D Darcy Flow problem and showcasing better transfer learning capabilities to new geometries; and (3) learning 3D parameterized geometries for a heat transfer problem and demonstrate the ability to predict on new but similar geometries. Finally, our MT-DeepONet framework offers a novel approach to solving PDE problems in engineering and science under a unified umbrella based on synergistic learning that reduces the overall training cost for neural operators.

42 ENGINEERING↗

A modified model parametrization algorithm for solving a special type of heat and mass transfer systems

A new method for solving nonlinear heat and mass transfer design tasks was considered. Systems using the Number of Transfer Units (NTU) method are a special type of mathematical model of heat and mass exchangers. It was observed, that the NTU models in a form of differential-algebraic equations (DAEs) cannot be directly solved with higher values of NTU. The requirements for consistent initial conditions, as well as numerical limitations of DAEs solvers, result, that the solution to the considered design problems that cannot be obtained by a classical direct shooting procedure. To overcome the presented difficulties, the αDAE model optimization algorithm was adjusted for solving NTU-based models. The new approach consists of 3 main steps: 1) task discretization by a multiple-shooting approach, 2) design an appropriate function $f_{NTU}$(α) to effectively influence the variability of the state variables described by dynamical relations, 3) the iterative numerical optimization algorithm for the new parametrized system. Moreover, computations can be performed by a chosen numerical optimization approach, which can be communicated with an available outer procedure for solving differential-algebraic equations. The presented algorithm was implemented and applied to solve the design task with the NTU model of a counter-flow exchanger. Here, the new approach was used to modify the system dynamics to influence the difficulty of the considered problem. Finally, the presented method enabled failure-free numerical computations for the higher values of the NTU parameter.

97 MATHEMATICS AND COMPUTING↗

Thiol- and Disulfide-Functionalized Polycyclooctene: Metathesis Polymerization, Degradation, and Reformation

The enormous global production and use of polymers and plastics, combined with slower and less efficient disposal and recycling methods, have led to a worldwide growth in plastic waste. Here, we describe an approach that builds degradability into macromolecular polyolefins through the design of telechelic oligomers with reactive functional groups that enables control over polymer deconstruction and reconstruction. Our work exploits disulfide-containing polymers that have emerged as promising cyclable materials due to their dynamic reversibility (bond formation and cleavage) driven by redox chemistry under mild conditions. Specifically, we describe the synthesis of a telechelic α,ω-dithiopolycyclooctene (PCOE) by ring-opening metathesis polymerization using a dithioacetate chain transfer agent, followed by deprotection to convert the chain-end thioacetates to thiols. This process was studied towards control over the degree of oxidation to yield disulfide-containing PCOE, followed by an evaluation of reductive degradation and oxidative repolymerization. Overall, this approach facilitates the production of disulfide-containing unsaturated polyolefins and the integration of degradable and reformable moieties into soluble, processable, metathesis-derived polymers.

Lee, Kyoungwon↗