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At least 829 records · Page 46

Green solvent-processable poly(3-hexylthiophene) derivative maintains high hole mobility in diodes

The development of environmentally sustainable fabrication methods for organic solar cells (OSCs) is critical to enable their large-scale adoption. Conventional solution-processed OSCs often rely on halogenated, toxic solvents that pose health and environmental risks, limiting their scalability. This is because π-conjugated polymers tend to have a low solubility in non-halogenated solvents. A common strategy to enhance solubility in alternative solvents is through the incorporation of polar solubilizing groups, often on every repeat unit of at least one monomer. However, too many polar side chains tend to disrupt favorable morphology and decrease charge transport properties. In this study, we demonstrate that a minimal degree of side chain functionalization can improve green solvent processability while preserving electrical performance. We tested this hypothesis using our previously reported random copolymer derivative of poly(3-hexylthiophene) (P3HT) where ∼10 mol% of the side chains are 6-pentanoatehexyl side chains. We find that this low-level functionalization significantly broadens the solvents that can be used to process P3HT to less toxic solvents such as o-xylene and anisole. Furthermore, the copolymer processed from greener solvents showed high hole mobilities (∼10⁻ 3 cm 2 /Vs by the Space-Charge Limiting Current method in diodes), comparable to P3HT films cast from toxic chloroform. These findings suggest that minimal side-chain modification is a viable strategy for expanding green solvent compatibility while preserving electrical performance, paving the way toward more sustainable organic semiconductor designs.

36 MATERIALS SCIENCE↗

Low Threshold Voltages Electrochemically Drive Gold Migration in Halide Perovskite Devices

The constituent ions of halide perovskite materials are mobile in the solid state and known to participate in reduction/oxidation reactions. Yet few parameters related to electrochemical processes occurring within devices have been carefully determined. Here, we characterize such reactions in model MAPbI3 perovskite devices, and we quantify threshold voltages for key reactions. Gold is oxidized and mobilized under nitrogen, in the dark, at the MAPbI3/Au interface at 0.8 V. When this interface is buffered with the organic hole transport material (HTM), 2,2',7,7'-tetrakis(N,N-di-p-methoxyphenylamino)-9,9'-spirobifluorene, MAPbI3 begins to degrade at 1.2 V; degradation liberates ions that subsequently enable Au migration. Thresholds are insensitive to MAPbI3 thickness or choice of organic HTM or oxide cathode, which suggests that these reactions are driven electrochemically; the electric field across the device is less important. These results have profound implications for understanding in operando degradation pathways of optoelectronic perovskite devices that are varied in terms of interface structures, active material compositions, and ranges of external stressors.

42 ENGINEERING↗

Assessment of impinged flame structure in high-pressure direct diesel injection

Spray impingement often occurs during cold-start in direct-injection diesel engines, affecting the subsequent combustion process by altering the local flow condition. This work has investigated the impinged flame structure by examining local expansion distance and planar curvature of the boundary in details. The experiments were carried out in a constant volume combustion chamber. The injection pressure and ambient density were varied from 120 to 180 MPa and 14.8 to 30.0 kg/m 3 under non-vaporizing conditions, respectively. For reacting conditions, the injection pressure and ambient density were fixed at 150 MPa and 22.8 kg/m 3 but with different ambient temperatures from 800 to 1000 K. Unlike orthogonal spray impingement, the profile of expansion distance along the radial direction at the 60° impinging angle is non-uniform but the profile is comparable between the non-vaporizing and reacting conditions under the same injection pressure and ambient density. With the help of Intensity-aXial-Time method, the most intensive soot luminosity region and Mie scattering intensity region are identified and the region has been found to be along the impinged spray axial direction. Outmost boundary of an impinged flame is found to have wrinkles attributed to air entrainment. The temporal level of flame wrinkles is higher in reacting conditions than in non-vaporizing conditions. The scatter distribution of the boundary curvature and near-field soot formation illustrates an inverted “S” shape correlation with time. High flame luminosity is found to be formed in concave regions while less soot is formed in convex regions. This inverted S-shape is a new finding of the state relationship at the solid–liquid–gas impinged flame propagation. Finally, heat flux measurement through the plate is examined.

Engineering↗

Combining synchrotron X-ray diffraction, mechanistic modeling and machine learning for in situ subsurface temperature quantification during laser melting

Laser melting, such as that encountered during additive manufacturing, produces extreme gradients of temperature in both space and time, which in turn influence microstructural development in the material. Qualification and model validation of the process itself and the resulting material necessitate the ability to characterize these temperature fields. However, well established means to directly probe the material temperature below the surface of an alloy while it is being processed are limited. To address this gap in characterization capabilities, a novel means is presented to extract subsurface temperature-distribution metrics, with uncertainty, from in situ synchrotron X-ray diffraction measurements to provide quantitative temperature evolution data during laser melting. Temperature-distribution metrics are determined using Gaussian process regression supervised machine-learning surrogate models trained with a combination of mechanistic modeling (heat transfer and fluid flow) and X-ray diffraction simulation. The trained surrogate model uncertainties are found to range from 5 to 15% depending on the metric and current temperature. The surrogate models are then applied to experimental data to extract temperature metrics from an Inconel 625 nickel superalloy wall specimen during laser melting. The maximum temperatures of the solid phase in the diffraction volume through melting and cooling are found to reach the solidus temperature as expected, with the mean and minimum temperatures found to be several hundred degrees less. The extracted temperature metrics near melting are determined to be more accurate because of the lower relative levels of mechanical elastic strains. However, uncertainties for temperature metrics during cooling are increased due to the effects of thermomechanical stress.

36 MATERIALS SCIENCE↗

Biogas Biocatalysis

Biogas derived from anaerobic digestion of waste streams such as biorefinery wastewater, animal, agricultural, and municipal solid waste, offers a versatile renewable energy source. Total domestic methane potential from landfill material, animal manure, wastewater, and organic waste, combined with biogas generated from AD of lignocellulosic biomass, is estimated to offer >4 quadrillion Btu potential energy. This energy could displace nearly half of current domestic natural gas consumption in the electric power sector and all consumption in the transportation sector. However, despite this promise of this feedstock, its gaseous state prevents facile integration with extant transportation and industrial infrastructure. Microbial conversion of biogas to liquid fuel and chemical intermediates offers valorization potential. However, biogas biocatalysis is currently limited by poor substrate gas-to-liquid mass transfer, low conversion efficiencies, and incomplete biogas utilization. To this end, the Biogas Biocatalysis AOP aims to develop a carbon- and energy-efficient biogas bioconversion process via techno-economic-informed strain and fermentation engineering strategies. Efforts here will improve both process economics and sustainability via process-intensified, carbon-efficient biogas bioconversion to value-added platform molecules, enabling bolt-on deployment for valorization of biogas derived from standalone AD infrastructure.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗

Significance of Dynamic and Transient Analysis in the Design and Operation of Hybrid Energy Systems

Energy systems were historically designed and operated with a specific energy conversion objective, while managing loads and resources. In the recent years, the increased utilization of non-dispatchable renewable sources such as wind and solar has played a role in power quality and the reliability of power systems. In order to mitigate the risk associated with the non-dispatchable resources an integrated approach, such as Hybrid Energy Systems (HES), has to be taken, integrating the loads and resource management between the traditional thermal power plants and the non-dispatchable resources. As our electric energy becomes more diverse in its generation resources, the HES with its operational control system, its real-time view and its dynamic decisions making will become an essential part of the integrated energy systems and improve the overall grid reliability. The operational constraints of the energy sources on both the thermal power plants and the non-dispatchable resources in HES, plays a vital role in the planning and design stage. It is an established fact that the choice of energy source depends on the available natural resources and possible infrastructure. A critical component of decision-making depends on the complementary nature and controllability of the energy sources to supply the load demands with high reliability. Controllability of complex HES to achieve desired performance and flexibility is implemented via coordinated control systems while simultaneously generating electricity and other useful products such as useful heat or hydrogen. These systems are based on instrumentation, signal processing, control theory, and engineering system design. The entire HES along with the control systems are characterized by widely varying time constants. Hence, for a well-coordinated control and operation, we propose physics based modeling of the subsystems to assist in a dynamic and transient analysis. Dynamic and transient analysis in real and non-real time domain of the potential sources is capable of providing satisfactory results at the feasibility analysis stage. A simplified HES consisting of complementary energy sources is used to demonstrate the proposed approach. Suitable real time simulations to perform dynamic and transient analysis will be performed to verify results from the non-real time analysis. The role of such analyses, especially the real time dynamic and transient analysis for manual controls is elaborated. It is also discussed that faster than real time simulation will pave the future for controller rooms and hence manual control procedures. Multiple tools such as Real Time Simulator, Matlab®, Simulink®, PSCAD®, MOOSE, etc. are expected to be used for the HES analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Time‐Lapse Image Classification Using a Diffractive Neural Network

Diffractive deep neural networks (D 2 NNs), comprised of spatially engineered passive surfaces, collectively process optical input information at the speed of light propagation through a thin diffractive volume, without any external computing power. Diffractive networks were demonstrated to achieve all‐optical object classification and perform universal linear transformations. Herein, a “time‐lapse” image classification scheme using a diffractive network is demonstrated for the first time, significantly advancing its classification accuracy and generalization performance on complex input objects by using the lateral movements of the input objects and/or the diffractive network, relative to each other. In a different context, such relative movements of the objects and/or the camera are routinely being used for image super‐resolution applications; inspired by their success, a time‐lapse diffractive network is designed to benefit from the complementary information content created by controlled or random lateral shifts. The design space and performance limits of time‐lapse diffractive networks are numerically explored, revealing a blind testing accuracy of 62.03% on the optical classification of objects from the CIFAR‐10 dataset. This constitutes the highest inference accuracy achieved so far using a single diffractive network on the CIFAR‐10 dataset. Time‐lapse diffractive networks will be broadly useful for the spatiotemporal analysis of input signals using all‐optical processors.

36 MATERIALS SCIENCE↗

An updated Lagrangian LBM–DEM–FEM coupling model for dual-permeability fissured porous media with embedded discontinuities

Many engineering applications and geological processes involve embedded discontinuities in porous media across multiple length scales (e.g. rock joints, grain boundaries, deformation bands and faults). Understanding the multiscale path-dependent hydro-mechanical responses of these interfaces across length scales is of ultimate importance for applications such as CO 2 sequestration, hydraulic fracture and earthquake rupture dynamics. While there exist mathematical frameworks such as extended finite element and assumed strain to replicate the kinematics of the interfaces, modeling the cyclic hydro-mechanical constitutive responses of the interfaces remains a difficult task. Here this paper presents a semi-data-driven multiscale approach that obtains both the traction-separation law and the aperture-porosity–permeability relation from micro-mechanical simulations performed on representative elementary volumes in the finite deformation range. To speed up multiscale simulations, the incremental constitutive updates of the mechanical responses are obtained from discrete element simulations at the representative elementary volume whereas the hydraulic responses are generated from a neural network trained with data from lattice Boltzmann simulations. These responses are then linked to a macroscopic dual-permeability model. This approach allows one to bypass the need of deriving multi-physical phenomenological laws for complex loading paths. More importantly, it enables the capturing of the evolving anisotropy of the permeabilities of the macro- and micro-pores. A set of numerical experiments are used to demonstrate the robustness of the proposed model.

42 ENGINEERING↗

Fundamental Advancements in Pre-Chamber Spark Ignition and Emissions Control for Natural Gas Engines

Argonne National Laboratory, the National Renewable Energy Laboratory, Oak Ridge National Laboratory, and Sandia National Laboratories collaborated on research to address barriers for natural gas engine efficiency. This research project focuses on early stage research focusing on pre-chamber spark-ignition (PCSI) to achieve diesel-like efficiency in medium- and heavy-duty natural gas engines by extending the lean dilution limit and/or exhaust gas recirculation (EGR) dilution limit, as well as shortening burn duration, with integrated aftertreatment. This project integrates experimental and simulation based tasks to address four key barriers to market penetration of PCSI for medium- and heavy-duty natural gas engines. These include Inadequate science base and simulation tools to describe/predict the fluid-mechanical and chemical-kinetic processes governing PCSI to enable engineers in industry to optimize designs for efficiency, noise, reliability, pollutant formation, emissions control integration, and drivability; limited ability to extend EGR and/or lean dilution limits at higher loads; increased propensity for PCSI hot-spot pre-ignition at high loads relative to spark ignition; and ineffective methane catalysts for the high engine-out unburned fuel concentrations coupled with low exhaust temperatures (<<400 degrees C) of high efficiency engines.

33 ADVANCED PROPULSION SYSTEMS↗

Effectiveness of multi-stage cooling processes in improving the CH 4 -hydrate saturation uniformity in sandy laboratory samples

Laboratory-created samples of methane hydrate (MH)-bearing media are a necessity because of the rarity and difficulty of obtaining naturally-occurring samples. The hypothesis that the inevitable heterogeneity in the phase saturations of the laboratory samples may lead to unreliable and non-repeatable results provided the impetus for us to undertake this study, which aimed to determine the conditions under which maximum uniformity can be achieved. To that end, we designed four experiments involving different multi-stage cooling regimes (in terms of their duration and number of stages) to induce MH formation under excess-water conditions. In the absence of direct visualization capabilities, we analysed the experimental results by means of numerical simulation, which provided high-resolution predictions of the spatial distributions of the phase saturations in the cores and enabled the estimation of the parameters controlling the kinetic MH-formation behaviour through history-matching. Analysis of the numerical results indicated that, under the conditions of the experiments and with the design of the reactor, significant heterogeneities in phase saturation distributions were observed in all cases, leading to the conclusion that it is not possible to obtain cores with uniform phase saturation. Additionally, contrary to expectations, heterogeneities increased with the number of cooling stages and the duration of cooling, and this was attributed to imperfect insulation of the upper part of the reactor. A set of simulations involving perfect insulation of the reactor top confirmed the validity of this assumption: (a) predicting the formation of high-uniformity MH-bearing cores that became more homogeneous as the number of cooling stages and the length of the cooling period increased; and (b) providing important information for the improvement of the standard design of the experimental apparatus for the laboratory creation of MH-bearing cores using the excess water method.

42 ENGINEERING↗

Computational Fermi Level Engineering and Doping-Type Conversion of Ga2O3 Via Three-Step Processing

Ga2O3 is being actively explored for power electronics, and other applications due to its ultra- wide bandgap and low projected fabrication cost of high-quality crystals. N-type doping of Ga2O3 can be achieved and tuned, but p-type doping faces fundamental obstacles. Successful engineering of Ga2O3 based devices requires critical control of doping density, Fermi level position, providing opportunities for predictive process simulation. We use first-principles defect equilibrium calculations to simulate a 3-step growth- annealing-quench protocol for hydrogen assisted Mg doping in Ga2O3, taking into account the hydrogen- oxygen-water gas phase equilibrium. We predict type conversion to a net p-type regime following O-rich annealing after growth under reducing conditions in the presence of H2. We show that there is an optimal temperature that maximizes the net acceptor density during the equilibrium annealing step for a given Mg doping level. Quenching of non-equilibrium annealed samples then results in a Fermi level EF below mid-gap down to about EV +1.5 eV, creating a significant number of uncompensated neutral MgGa0 acceptors. This type converted Ga2O3 can create significant built-in field in a p-n junction with an adjoining n-type material and could enable vertical MOSFETs.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,M↗

Process Simulation Role in the Development of New Alloys Based on Integrated Computational Material Science and Engineering

To accelerate the introduction of new materials and components, the development of metal casting processes requires the teaming between different disciplines, as multi-physical phenomena have to be considered simultaneously for the process design and optimization of mechanical properties. The required models for physical phenomena as well as their validation status for metal casting are reviewed. The data on materials properties, model validation, and relevant microstructure for materials properties are highlighted. One vehicle to accelerate the development of new materials is through combined experimental-computational efforts. Integrated computational/experimental practices are reviewed; strengths and weaknesses are identified with respect to metal casting processes. Specifically, the examples are given for the knowledge base established at Oak Ridge National Laboratory and computer models for predicting casting defects and microstructure distribution in aluminum alloy components.

Sabau, Adrian S↗

Composite Structures with Emissive Quantum Dots for Light Enhancement

Since their inception, quantum dots have proven to be advantageous for light management applications due to their high brightness and well-controlled absorption, scattering, and emission properties. As quantum dots become commercially available at large scale, the need for robust, stable, and flexible optical components continues to drive the development of robust and flexible quantum dot composite materials. In this review, after a thorough introduction to quantum dots, discussion delves into methods for fabricating quantum dot loaded composite optical elements such as thin films, microfabricated patterns, and microstructures. The importance of surface chemistry and ligand engineering, host matrixes, wet processing, and unique patterning methodologies is presented by considering photostability, aggregation, and phase separation of quantum dots in corresponding composites. With regard to prospective optical applications of quantum dot materials, emphasis is placed on light emitting and guiding composite materials for lasing applications, specifically whispering gallery mode-based photonic microsystems. These developments will enable novel flexible, portable, and miniaturized optoelectronic devices such as light-emitting diodes, flexible pixelated displays, solar cells, large-area microwaveguides, omnidirectional micromirrors, optical metasurfaces, and directional microlasers.

36 MATERIALS SCIENCE↗

Topochemical Understanding of Lignin Distribution During Hydrothermal Flowthrough Pretreatment

Changes in surface properties during biomass pretreatments are important parameters to understand and engineer biological biomass conversion processes. In particular, different influences on the surface of biomass are expected between flowthrough and batch pretreatments. In this paper, for a better understanding of biomass surface changes by hydrothermal flowthrough pretreatment, the mechanism by which the surface of biomass is altered in terms of cellulose and lignin was investigated using time-of-flight secondary ion mass spectrometry (ToF-SIMS) and compared with the bulk chemical composition and the results from scanning electron microscope (SEM). ToF-SIMS analysis results provide semi-quantitative information of cellulose and lignin and support the other observation from SEM and bulk compositional analyses. In brief, more lignin was observed on the surface of biomass at the early stage hydrothermal pretreatment, while the lignin mainly located at the cell corners was reduced by extended pretreatment time. Finally, unlike batch pretreatment, pseudo-lignin formation was not observed on the poplar surface during the flowthrough process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Delaunay walk for fast nearest neighbor: accelerating correspondence matching for ICP

Point set registration algorithms such as Iterative Closest Point (ICP) are commonly utilized in time-constrained environments like robotics. Finding the nearest neighbor of a point in a reference 3D point set is a common operation in ICP and frequently consumes at least 90% of the computation time. We introduce a novel approach to performing the distance-based nearest neighbor step based on Delaunay triangulation. This greedy algorithm finds the nearest neighbor of a query point by traversing the edges of the Delaunay triangulation created from a reference 3D point set. Our work integrates the Delaunay traversal into the correspondences search of ICP and exploits the iterative aspect of ICP by caching previous correspondences to expedite each iteration. An algorithmic analysis and comparison is conducted showing an order of magnitude speedup for both serial and vector processor implementation.

3d point cloud processing↗

Mechanical and Thermal Characterization of Additively Manufactured Carbon/Nylon 12 and Carbon/PEEK Composites

This study explores additive manufacturing of carbon fiber-reinforced thermoplastic composites using the Composite-Based Additive Manufacturing (CBAM) process. Carbon/Nylon 12 and Carbon/PEEK composites were fabricated and evaluated through mechanical (compression, tensile, flexural, and impact) and thermal (DSC and TGA) tests. Carbon/PEEK exhibited superior mechanical performance, with 97.5% higher tensile strength, 79.8% higher elastic modulus, and 59.6% higher flexural strength compared to Carbon/Nylon 12. Thermal testing showed that Carbon/PEEK had higher thermal stability, beginning degradation at 350 °C versus 298 °C for Carbon/Nylon. These results indicate that CBAM-fabricated Carbon/PEEK composites are suitable for applications requiring high strength and temperature resistance.

Additive manufacturing↗

Self-organized criticality in multi-pulse gamma-ray bursts

The variability in multi-pulse gamma-ray bursts (GRBs) may help to reveal the mechanism of underlying processes from the central engine. To investigate whether the self-organized criticality (SOC) phenomena exist in the prompt phase of GRBs, we statistically study the properties of GRBs with more than 3 pulses in each burst by fitting the distributions of several observed physical variables with a Markov Chain Monte Carlo approach, including the isotropic energy E iso , the duration time T, and the peak count rate P of each pulse. Our sample consists of 454 pulses in 93 GRBs observed by the CGRO/BATSE satellite. The best-fitting values and uncertainties for these power-law indices of the differential frequency distributions are: α$^{d}_{E}$ = 1.54±0.09, α$^{d}_{T}$ = 1.82±$^{+0.14}_{0.15}$ and α$^{d}_{P}$ = 2.09$^{+0.18}_{–0.19}$, while the power-law indices in the cumulative frequency distributions are: α$^{c}_{E}$ = 1.44$^{+0.08}_{–0.10}$, α$^{c}_{T}$ = 1.75$^{+0.141}_{–0.13}$ and α$^{c}_{P}$ = 1.99$^{+0.16}_{–0.19}$. We find that these distributions are roughly consistent with the physical framework of a Fractal-Diffusive, Self-Organized Criticality (FD-SOC) system with the spatial dimension S = 3 and the classical diffusion β=1. The results of this study support that the jet responsible for the GRBs should be magnetically dominated and magnetic instabilities (e.g., kink model, or tearing-model instability) lead the GRB emission region into the SOC state.

79 ASTRONOMY AND ASTROPHYSICS↗

Time-Dependent 600 °C Post-Weld Heat Treatment Response of Laser-Wire-Directed Energy Deposited Austenitic Stainless Steel Claddings on Carbon Steel

Austenitic stainless steel overlay claddings are often used to protect nuclear reactor pressure vessels from corrosion. Arc welding processes are traditionally employed, which require a high heat input to bond the dissimilar metals, creating a large heat-affected zone and high residual stress that demands a lengthy stress-relieving post-weld heat treatment, up to 48 hours. High energy beam (e.g., laser, electron beam) directed energy deposition-based overlay cladding processes show promise for fabricating claddings with superior performance compared to arc welded ones because of their localized heat input; however, their necessity and time of post-weld heat treatment are currently unclear. In this research, we investigate the time dependence of a 600 C stress-relieving post-weld heat treatment of austenitic stainless steel clad on low carbon steel by laser-wire-directed energy deposition, comparing the microstructure and mechanical properties of the as-fabricated condition to 2-, 10-, and 48-hour heat treatment times. Diffusion simulations and microscopy show a gradual carburization of the stainless steel cladding and decarburization of the heat-affected zone/base metal. Nanoindentation testing shows up to a 1.8–2.69 embrittlement in the cladding and a 0.33 to 0.69 softening in the heat-affected zone after the 48-hour post-weld heat treatment. Tensile testing of the cladding composites reveals that increasing post-weld heat treatment time raises clad cracking susceptibility due to intergranular carbide formation and shows that laser-wire-directed energy deposition claddings may not require post-weld heat treatment.

Coating↗