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At least 271 records · Page 15

Chemical and Electrochemical O 2 Reduction on Earth-Abundant M-N-C Catalysts and Implications for Mediated Electrolysis

M-N-C catalysts, incorporating non-precious-metal ions (e.g. M = Fe, Co) within a nitrogen-doped carbon support, have been the focus of broad interest for electrochemical O 2 reduction and aerobic oxidation reactions. The present study explores the mechanistic relationship between the O 2 reduction mechanism under electrochemical and chemical conditions. In this work, chemical O 2 reduction is investigated via the aerobic oxidation of a hydroquinone, in which the O–H bonds supply the protons and electrons needed for O 2 reduction to water. Mechanistic studies have been conducted to elucidate whether the M-N-C catalyst couples two independent half-reactions (IHR), similar to electrode-mediated processes, or mediates a direct inner-sphere reaction (ISR) between O 2 and the organic molecule. Kinetic data support the latter ISR pathway. This conclusion is reinforced by rate/potential correlations that reveal significantly different Tafel slopes, implicating different mechanisms for chemical and electrochemical O 2 reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ultrafine-grained Fe-TiB 2 high-modulus nanocomposite steel with high strength and isotropic mechanical properties by laser powder bed fusion

Fe-TiB 2 metal matrix composite, also called high-modulus steels (HMSs), are of great interest for applications in fuel-efficient transportation infrastructure, aerospace, and wear industries due to their high specific stiffness and yield strength. However, conventional cast Fe-TiB 2 HMSs often contain coarse and sharp-edged TiB 2 particles which easily trigger premature cracking during loading. Here, we synthesized a Fe-TiB 2 nanocomposite HMS via laser powder bed fusion (LPBF) additive manufacturing of mixed micro-sized powders of Fe, Ti, and Fe 2 B. We investigated the microstructure formation and mechanical behavior of the Fe-TiB 2 HMS. We found that in situ chemical reaction of Ti and Fe 2 B enables the formation of TiB 2 particles at nanoscale during rapid solidification of LPBF. These nanoscale TiB 2 particles can serve as heterogeneous nucleation sites and promote the formation of ultrafine and equiaxed α-Fe grains with random crystallographic textures, which differ from many other additively manufactured (AM) metal alloys characteristic of strong crystallographic textures. As such, isotropic mechanical properties were achieved in the AM Fe-TiB 2 nanocomposite HMS with a high elastic modulus of ~ 240 GPa, an exceptional yield strength of ~ 1450 MPa, and a large plasticity of ~ 20% under compression. Quantitative analysis reveals that the high yield strength primarily originates from strengthening contributions of the ultrafine grains with an average grain size of ~450 nm, the nanoscale TiB 2 reinforcing particles of 20–180 nm, and a high density of printing-induced dislocations of the order of 10 15 m –2 . In situ synchrotron high-energy X-ray diffraction unveils the load partitioning from the softer α-Fe matrix to the stiffer and stronger TiB 2 nanoparticles, contributing to the sustained strain hardening during compression. Our work not only provides a general pathway for achieving high-performance metal matrix nanocomposites by in situ chemical reaction and precipitation of ceramic nanoparticles during additive manufacturing, but also offers mechanistic insights into the deformation mechanism of nanoparticle-reinforced HMS composites.

36 MATERIALS SCIENCE↗

Economic competitiveness of pultruded fiber composites for wind turbine applications

Pultrusion manufacturing of fiber reinforced polymers has been shown to yield some of the highest mechanical properties for unidirectional composites, having a high degree of fiber alignment with consistent performance. Pultrusions offer a low-cost manufacturing approach for producing unidirectional composites with a constant cross-section and are used in many applications, including spar caps of wind turbine blades. However, as an intermediate processing step for wind blades, the additional cost of manufacturing pultrusions must be accompanied by sufficient increases in mechanical performance and system benefits. Wind turbine blades are manufactured using vacuum-assisted resin transfer molding with infused unidirectional fiberglass or carbon pultrusions for the spar cap. Infused fiberglass composites are among the most cost-effective structural materials available and replacing this material in the cost-driven wind industry has proven challenging, where infused fiberglass spar caps are still the predominant material system in use. To evaluate alternative material systems in a pultruded composite form, it is necessary to understand the costs for this additional manufacturing step which are shown to add 33%–55% on top of the material costs. A pultrusion cost model has been developed and used to quantify cost sensitivities to various processing parameters. The mechanical performance for pultruded composites is improved versus resin-infusion manufacturing with a 17% increase in design strength at a constant fiber volume fraction, but also enables higher achievable fiber volume fractions. The cost-specific mechanical performance is compared as a function of processing parameters for pultruded composites to identify the opportunities for alternative material and manufacturing approaches for wind turbine spar caps. Finally, four materials are compared in a representative wind turbine blade model to assess the performance of pultruded carbon fiber systems and pultruded fiberglass relative to infused fiberglass, where the pultruded systems produce lower weight blades with various cost distinctions.

42 ENGINEERING↗

Unearthing principal strengthening factors tuning the additive manufactured 15-5 PH stainless steel

Additive manufactured (AM) materials exhibit enhanced performance, while post-processing is essential to reinforce its properties. Controlling the tunable factors and the underlying strengthening mechanisms during the post-processing are a key to answering the calls from the industry and end users. We identified the principal strengthening factors that contribute to AM stainless steel under heat-treatment and weighed their importance. The as-built sample exhibited a unique microstructure with a heterogeneous grain size distribution, a small amount of retained austenite, high dislocation density, and dispersed oxide particles. The strengthening primarily by dislocation forest and additionally by heterogeneous grain size contributed to the as-built sample. Although aging slightly decreased dislocation strengthening, superior aging enhancement was achieved by Cu-precipitates. The solid-solutionizing not only increased the effective grain size but also reduced the dislocation density by eliminating the heterogeneous microstructure, which deteriorated the precipitation hardenability. Our findings shed light on the performance optimization of AM metals.

36 MATERIALS SCIENCE↗

Mechanochemically responsive polymer enables shockwave visualization

Abstract Understanding the physical and chemical response of materials to impulsive deformation is crucial for applications ranging from soft robotic locomotion to space exploration to seismology. However, investigating material properties at extreme strain rates remains challenging due to temporal and spatial resolution limitations. Combining high-strain-rate testing with mechanochemistry encodes the molecular-level deformation within the material itself, thus enabling the direct quantification of the material response. Here, we demonstrate a mechanophore-functionalized block copolymer that self-reports energy dissipation mechanisms, such as bond rupture and acoustic wave dissipation, in response to high-strain-rate impacts. A microprojectile accelerated towards the polymer permanently deforms the material at a shallow depth. At intersonic velocities, the polymer reports significant subsurface energy absorption due to shockwave attenuation, a mechanism traditionally considered negligible compared to plasticity and not well explored in polymers. The acoustic wave velocity of the material is directly recovered from the mechanochemically-activated subsurface volume recorded in the material, which is validated by simulations, theory, and acoustic measurements. This integration of mechanochemistry with microballistic testing enables characterization of high-strain-rate mechanical properties and elucidates important insights applicable to nanomaterials, particle-reinforced composites, and biocompatible polymers.

Science & Technology - Other Topics↗

1,4-cineole: a bio-derived solvent for highly stable graphene nanoplatelet suspensions and well-dispersed UHMWPE nanocomposite fibers

The exceptional properties of carbon nanoparticles, such as graphene, promise to expand the performance and functionality of many materials. The reinforcement of polymers is of keen interest due to their low density and flexible manufacturing methods. However, dispersing graphene in them has proven to be an enduring challenge due to the particles’ propensity to form performance degrading agglomerations. Furthermore, effective solvents for nanoparticle dispersion are commonly harmful, non-renewable, petrochemicals. In this work, a bio-derived solvent, 1,4-cineole, is demonstrated as a renewable alternative to these solvents that can be used to form highly stable graphene nanoplatelet (GnP) suspensions and used to gel spin well-dispersed UHMWPE/GnP nanocomposite fibers. The GnP concentration in the fibers was varied across three orders of magnitude, 0.01 wt% to 1 wt%, to examine its effect on fiber microstructure and properties. At low concentrations the particles act as point defects without affecting the fiber microstructure, and poor particle/matrix interfacial adhesion results in significantly reduced mechanical properties. At 1 wt% GnPs, a network effect takes hold thereby reinforcing the fibers, but the particles also impede the growth and orientation of crucial load-carrying crystalline structures in the fiber. Furthermore, unveiling the microstructural effects of GnPs on highly oriented and crystalline polymers in this study provides crucial insights for future work developing high-performance polymer nanocomposite fibers.

36 MATERIALS SCIENCE↗

Project 7.3 Characterization of Kevlar®-reinforced Composites for Predictive Simulation

The IACMI 7.3 project between DuPont and Purdue University required the mechanical testing of a 2x2 twill Kevlar® weave with Hexion EPIKOTE resin. The tension, shear, flexure, and compressive behavior of this material system was characterized, and the results can be seen in Table 1. These material properties can now be further evaluated for use in performance simulations of automotive components to represent the properties of composites based on woven materials containing Kevlar. This report will provide details regarding the effort required to arrive at these material properties.

36 MATERIALS SCIENCE↗

A study of adhesive bonding in metal–metal, metal–CFRP, and CFRP–CFRP material combinations under shear deformation: Fracture morphologies and damage mechanisms

Safe design of adhesive joining in multi-materials in engineered structures requires the accumulation of numerous experimental data on the failure behavior of various adhesively-bonded material combinations under different loading conditions. The deep understanding of mechanical performance, fracturing morphologies, and main damage mechanisms is also quintessential for accelerating the development of proper physics-based and multi-scale models for assisting the design. Towards this goal, this work presents a comprehensive characterization of the failure behavior of adhesively-bonded metal–metal, metal–CFRP, and CFRP–CFRP material combinations under global shear deformation via single lap shear testing. Thanks to a synergistic combination of measurement methods by using Digital Imaging Correlation (DIC) and 3D optical profilometry, adhesive features on the adherend after failure were quantified and the main progressive damage mechanisms were identified. The characterization performed in this work provides quantitative data that contributes to a better understanding of shear failure in adhesive bonding across different bi-material combinations. Finally, the obtained results have practical implications, including the potential to enhance adhesive bonding design, identify failure causes in adhesive joints, and develop or validate computational models capable of capturing the observed behavior in various adhesively-bonded materials under global shear deformation.

36 MATERIALS SCIENCE↗

Comparing Parallel Plastic‐to‐X Pathways and Their Role in a Circular Economy for PET Bottles

Abstract The United States generates the most plastic waste of any country and is a top contributor to global plastic pollution. Multiple end‐of‐life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different lifetimes and utilities. Herein, they present a material flow model equipped with consequential life cycle assessment, cost analysis, and a plastic circularity indicator that considers product quality and lifetime. The model is used to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) bottle mechanical downcycling to lower‐quality resin, closed‐loop glycolysis to food‐grade PET, upcycling to glass fiber‐reinforced plastic, and conversion to non‐plastic products (electricity, oil) on a United States economy‐wide basis for the year 2020. A brute force algorithm suggests that a combination of 68% glycolysis, 11% mechanical recycling, 6% upcycling, 9% landfilling, and 5% incineration can minimize the cost and GHG emissions and maximize the circularity of the current PET economy. However, uncertainty around transportation distances, materials recovery facility efficiencies, and recycling yields can result in different “optimal” pathway mixes. This flexible framework enables informed decision‐making to move toward a cost‐ and environment‐conscious circular economy for plastic.

09 BIOMASS FUELS↗

Thermal Analysis of Large Area Additive Manufacturing Resistance Heating Composites for Out of Oven/Autoclave Applications

Additive Manufacturing (AM) of carbon fiber (CF) reinforced composite has received growing attention because of the design flexibility, superior mechanical properties, improved thermal properties, and weight reduction. Autoclave tooling was proven to be a successful application for large scale AM technology. The capital cost, and cost associated with heating, and cycle time in a conventional autoclave process is relatively high. Thus, an innovative design of AM mold with an efficient heating scheme is essential. This study represents an innovative method of the resistive heating of composite molds which does not require a room size oven for heating during the curing processing. Therefore, it has the potential to reduce the operating cost drastically. For the design validation and feasibility study, we performed a numerical analysis of the wire embedded and AM mold parts. The goal of this study is to determine and optimize the thermal behavior of the printed mold with embedded wire technology. It is anticipated that the larger distance between the embedded wires along the printing direction (z-direction) increase the cold spot, on the other hand, a close distance of the wire can create the unwanted localize heating, thus melting. Constant thermal properties of the 20 wt.% short CF reinforced acrylonitrile butadiene styrene (ABS) was used for the simulation purpose. Thermal characterization was set to 100°C to avoid the thermal deformation or bulging on the part surface.

billah, Kazi↗

Thermal Analysis of Large Area Additive Manufacturing Resistance Heating Composites for Out of Oven/Autoclave Applications

Additive Manufacturing (AM) of carbon fiber (CF) reinforced composite has received growing attention because of the design flexibility, superior mechanical properties, improved thermal properties, and weight reduction. Autoclave tooling was proven to be a successful application for large scale AM technology. The capital cost, and cost associated with heating, and cycle time in a conventional autoclave process is relatively high. Thus, an innovative design of AM mold with an efficient heating scheme is essential. This study represents an innovative method of the resistive heating of composite molds which does not require a room size oven for heating during the curing processing. Therefore, it has the potential to reduce the operating cost drastically. For the design validation and feasibility study, we performed a numerical analysis of the wire embedded and AM mold parts. The goal of this study is to determine and optimize the thermal behavior of the printed mold with embedded wire technology. It is anticipated that the larger distance between the embedded wires along the printing direction (z-direction) increase the cold spot, on the other hand, a close distance of the wire can create the unwanted localize heating, thus melting. Constant thermal properties of the 20 wt.% short CF reinforced acrylonitrile butadiene styrene (ABS) was used for the simulation purpose. Thermal characterization was set to 100°C to avoid the thermal deformation or bulging on the part surface.

billah, Kazi↗

Thermal Analysis of Large Area Additive Manufacturing Resistance Heating Composites for Out of Oven/Autoclave Applications

Additive Manufacturing (AM) of carbon fiber (CF) reinforced composite has received growing attention because of the design flexibility, superior mechanical properties, improved thermal properties, and weight reduction. Autoclave tooling was proven to be a successful application for large scale AM technology. The capital cost, and cost associated with heating, and cycle time in a conventional autoclave process is relatively high. Thus, an innovative design of AM mold with an efficient heating scheme is essential. This study represents an innovative method of the resistive heating of composite molds which does not require a room size oven for heating during the curing processing. Therefore, it has the potential to reduce the operating cost drastically. For the design validation and feasibility study, we performed a numerical analysis of the wire embedded and AM mold parts. The goal of this study is to determine and optimize the thermal behavior of the printed mold with embedded wire technology. It is anticipated that the larger distance between the embedded wires along the printing direction (z-direction) increase the cold spot, on the other hand, a close distance of the wire can create the unwanted localize heating, thus melting. Constant thermal properties of the 20 wt.% short CF reinforced acrylonitrile butadiene styrene (ABS) was used for the simulation purpose. Thermal characterization was set to 100°C to avoid the thermal deformation or bulging on the part surface.

billah, Kazi↗

Artificial-intelligence-driven shot reduction in quantum measurement

Variational Quantum Eigensolver (VQE) provides a powerful solution for approximating molecular ground state energies by combining quantum circuits and classical computers. However, estimating probabilistic outcomes on quantum hardware requires repeated measurements (shots), incurring significant costs as accuracy increases. Optimizing shot allocation is thus critical for improving the efficiency of VQE. Current strategies rely heavily on hand-crafted heuristics requiring extensive expert knowledge. This paper proposes a reinforcement learning (RL)-based approach that automatically learns shot assignment policies to minimize total measurement shots while achieving convergence to the minimum of the energy expectation in VQE. The RL agent assigns measurement shots across VQE optimization iterations based on the progress of the optimization. This approach reduces VQE's dependence on static heuristics and human expertise. When the RL-enabled VQE is applied to a small molecule, a shot reduction policy is learned. The policy demonstrates transferability across systems and compatibility with other wavefunction Ansätze. In addition to these specific findings, this work highlights the potential of RL for automatically discovering efficient and scalable quantum optimization strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fiber Orientation Evaluation in Reinforced Composites using Digital Image Correlation

This paper presents an innovative nondestructive evaluation (NDE) approach to evaluate fiber orientation in fiber reinforced composites utilizing digital image correlation (DIC). Fiber orientation is a crucial factor that influences the mechanical and thermal properties of the composite. Conventional methods for fiber orientation evaluation and measurement are either destructive, which are typically laborious. NDE methods such as micro computed tomography are expensive and limited in sample size. In this work, we evaluate two methods of excitation of the composite, namely-quasistatic mechanical loading and thermal cycling. Digital Image Correlation (DIC) has been employed in conjunction for fiber orientation measurements. The DIC system is able to measure the fiber orientation by capturing 19x higher strain in the transverse direction of the reinforced fiber axis during excitation. The larger strain occurs in the transverse direction due to larger elongation in the surrounding polymer matrix than the fiber which resists elongation. This innovative method is within the preliminary stage and has been developed to fill the gap/limitations of other NDE methods.

Spencer, Ryan↗

Predicting Microstructural Void Nucleation in Discontinuous Fiber Composites through Coupled in-situ X-ray Tomography Experiments and Simulations

Composite materials have become widely used in engineering applications, in order to reduce the overall weight of structures while retaining their required strength. In this work, a composite material consisting of discontinuous glass fibers in a polypropylene matrix is studied at the microstructural level through coupled experiments and simulations, in order to uncover the mechanisms that cause damage to initiate in the microstructure under macroscopic tension. Specifically, we show how hydrostatic stresses in the matrix can be used as a metric to explain and predict the exact location of microvoid nucleation that occurs during damage initiation within the composite’s microstructure. Furthermore, this work provides evidence that hydrostatic stresses in the matrix can lead to coupled microvoid nucleation and early fiber breakage, and that small fragments of fibers can play an important role in the process of microvoid nucleation. These results significantly improve our understanding of the mechanics that drive the initiation of damage in the complex microstructures of discontinuous fiber reinforced thermoplastics, while also allowing scientists and engineers to predict the microstructural damage behavior of these composites at sub-fiber resolution and with high accuracy.

36 MATERIALS SCIENCE↗

Entanglement engineering of optomechanical systems by reinforcement learning

Entanglement is fundamental to quantum information science and technology, yet controlling and manipulating entanglement—so-called entanglement engineering—for arbitrary quantum systems remains a formidable challenge. There are two difficulties: the fragility of quantum entanglement and its experimental characterization. We develop a model-free deep reinforcement-learning (RL) approach to entanglement engineering, in which feedback control together with weak continuous measurement and partial state observation is exploited to generate and maintain desired entanglement. We employ quantum optomechanical systems with linear or nonlinear photon–phonon interactions to demonstrate the workings of our machine-learning-based entanglement engineering protocol. In particular, the RL agent sequentially interacts with one or multiple parallel quantum optomechanical environments, collects trajectories, and updates the policy to maximize the accumulated reward to create and stabilize quantum entanglement over an arbitrary amount of time. The machine-learning-based model-free control principle is applicable to the entanglement engineering of experimental quantum systems in general.

97 MATHEMATICS AND COMPUTING↗

Addressing amorphization and transgranular fracture of B 4 C through Si doping and TiB 2 microparticle reinforcing

Over the last two decades, many studies have contributed to improving our understanding of the brittle failure mechanisms of boron carbide and provided a road map for inhibiting the underlying mechanisms and improving the mechanical response of boron carbide. This paper provides a review of the design and processing approaches utilized to address the amorphization and transgranular fracture of boron carbide, which are mainly based on what we have found through 9 years of work in the field of boron carbides as armor ceramics.

36 MATERIALS SCIENCE↗

3D-printing methacrylate/chitin nanowhiskers composites via stereolithography: Mechanical and thermal properties

We report on the mechanical and thermal properties of stereolithography (SLA) 3D-printed methacrylate (MA) resin reinforced by chitin nanowhiskers (CNWs). CNWs were synthesized by acid hydrolysis of crab shell chitin and nanocomposites with 0 wt%, 0.5 wt%, 1.0 wt%, and 1.5 wt% CNWs loading were prepared by slurry compounding method. The obtained CNWs (diameter = 23 ± 5 nm, length = 253 ± 100 nm, and aspect ratio = 11 ± 3) are well dispersed within the bulk of MA at 1.0 wt% loading, implying good interfacial adhesion between the nanofiller and the resin matrix possibly due to hydrogen bonding interactions. The addition of up to 1.0 wt% CNWs to neat MA enhances the tensile strength, strain at break, modulus, and maximum thermal degradation temperatures of the nanocomposites. Moreover, the incorporation of CNWs not only improves the mechanical and thermal properties, but also preserves the excellent resolution and accuracy of 3D-printed MA/CNWs nanocomposites.

36 MATERIALS SCIENCE↗