Accelerated Exploration of Empty Material Compositional Space: Mg–Fe–B Ternary Metal Borides
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Zhang, Zhen↗
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Results for “Composite Material”
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Apparatuses and methods involving thermally tuned composite material
An apparatus includes a substrate, at least one type of tuning material, and a composite material. The substrate has an interface surface or material that manifests, in response to light in a color spectrum, a particular color and a first thermal load. The particular color is associated with the first thermal load. The at least one type of tuning material manifests, in response to light in the color spectrum, the particular color and a second thermal load. The particular color is associated with the second thermal load. The first thermal load is different from the second thermal load. The composite material includes the interface surface or material and the at least one type of tuning material. The composite material manifests, in response to light in the color spectrum, the particular color and a tuned thermal load which is different than the first thermal load and the second thermal load.
Li, Wei↗
Materials laboratories of the future for alloys, amorphous, and composite materials
In alignment with the Materials Genome Initiative and as the product of a workshop sponsored by the US National Science Foundation, we define a vision for materials laboratories of the future in alloys, amorphous materials, and composite materials; chart a roadmap for realizing this vision; identify technical bottlenecks and barriers to access; and propose pathways to equitable and democratic access to integrated toolsets in a manner that addresses urgent societal needs, accelerates technological innovation, and enhances manufacturing competitiveness. Spanning three important materials classes, this article summarizes the areas of alignment and unifying themes, distinctive needs of different materials research communities, key science drivers that cannot be accomplished within the capabilities of current materials laboratories, and open questions that need further community input. Here, we provide a broader context for the workshop, synopsize the salient findings, outline a shared vision for democratizing access and accelerating materials discovery, highlight some case studies across the three different materials classes, and identify significant issues that need further discussion.
36 MATERIALS SCIENCE↗
Physically constrained 3D diffusion for inverse design of fiber-reinforced polymer composite materials
Designing fiber-reinforced polymer composites (FRPCs) with a tailored nonlinear stress-strain response is crucial for applications such as energy absorption in crash structures, flexible robotics, and impact-resistant protective gear. However, the inherent complexities of composite materials and the multitude of parameters involved, render traditional design and optimization methods inadequate for achieving effective inverse design of composites. In this paper, we present an AI-based inverse design framework that effectively and efficiently generates FRPCs with targeted nonlinear stress-strain responses. We introduce a physically constrained diffusion model (PC3D_Diffusion) capable of managing the complexities of composite materials and producing detailed, high-quality designs. We propose a loss-guided, learning-free approach to generate physically feasible microstructure designs by explicitly enforcing physical constraints during the generation process. For training purposes, 1.35 million FRPC samples were created, and their corresponding stress-strain curves were computed using established physics-based computational models. The results show that PC3D_Diffusion consistently generates high-quality designs with tailored mechanical behaviors, while guaranteeing compliance with the physical constraints. PC3D_Diffusion advances FRPC inverse design and may facilitate the inverse design of other 3D materials, offering potential applications in industries reliant on materials with custom mechanical properties.
Xu, Pei [Clemson Univ., SC (United States)]↗
Markforged Continuous Fiber Composite Material Testing
Continuous fiber composite 3D printing promises to greatly expand the design space of polymer additive manufacturing (AM). A series of mechanical tests were performed to attempt to fully characterize the composite materials built from feedstock provided by the Markforged company. These tests included tensile, compression, Charpy impact, three point bending, coefficient of thermal expansion, and calorimetry tests. Specimens were prepared on the Mark Two 3D printer at LANL during the spring and summer of 2019. These samples were then shipped to New Mexico Institute of Mining and Technology’s Thermo-Mechanical Lab for testing during the summer and fall of 2019. Test data are reported and analyzed for each of the tests.
36 MATERIALS SCIENCE↗
COWALKER:EFFECTIVE TRANSPORT PROPERTIES OF COMPOSITE MATERIALS
SF-23-026 This software computes effective transport properties of composite materials involving fibers and nanoparticles using a random-walk algorithm that efficiently scales to an arbitrary number of processes and cores. Effective transport properties (thermal, electrical) are key to bridge the microstructure of complex materials with its macroscopic behavior. Traditional approaches either use effective medium approximations (closed mathematical expressions that are approximation for certain conditions) or continuum simulation models such as finite element or finite volume, which require the generation of a mesh for each configuration explored. cowalker leverages the equivalence between laplacian or heat equation-based models and random walks to compute the asymptotic transport properties from an ensemble of first sojourn times of a random walker moving through the composite material. This allows us to directly define a composite material as a collection of particles and use algorithms developed for molecular dynamics to quickly compute the intersection of the walker with the different interfaces in the material. cowalker is developed in C++, and it relies on the GNU Scientific Library for random generation. cowalker is currently delivered as source code, so the GSL library is not included in cowalker's distribution. A more userfriendly version, cowalker.jl is currently in development and will be released as part of cowalker.
YANGUAS-GIL, ANGEL↗
Manufacturing control systems and logic for prognosis of defects in composite materials
Presented are manufacturing control systems for composite-material structures, methods for assembling/operating such systems, and transfer molding techniques for predicting and ameliorating void conditions in fiber-reinforced polymer panels. A method for forming a composite-material construction includes receiving a start signal indicating a fiber-based preform is inside a mold cavity, and transmitting a command signal to inject pressurized resin into the mold to induce resin flow within the mold cavity and impregnate the fiber-based preform. An electronic controller receives, from a distributed array of sensors attached to the mold, signals indicative of pressure and/or temperature at discrete locations on an interior face of the mold cavity. The controller determines a measurement deviation between a calibrated baseline value and the pressure and/or temperature values for each of the discrete locations. If any one of the respective measurement deviations exceeds a calibrated threshold, a void signal is generated to flag a detected void condition.
36 MATERIALS SCIENCE↗
Composite materials with adjustable spectral properties
Composite materials with adjustable spectral properties comprised of IR-reflecting micro-domains overlaying an IR-transparent elastomeric matrix, and capable of dynamically controlling IR radiation transmission are described, as well as methods of fabrication thereof. Systems with capabilities to regulate IR radiation (including heat) transmission based thereon, and methods of regulating IR radiation transmission (including thermal regulation) using the same are also provided.
Source record↗
Processing Compressed Expanded Natural Graphite for Phase Change Material Composites
Phase change materials (PCMs) are used in various thermal energy storage applications but are limited by their low thermal conductivity. One method to increase conductivity involves impregnating organic PCMs into highly porous conductive matrix materials. Of these materials, compressed expanded natural graphite (CENG) matrices have received the most attention. Despite this attention, the effect that CENG processing has on PCM saturation and overall matrix thermal conductivity has not been fully investigated. Therefore, the effect of the heat treatment process used to expand intercalated graphite flakes is evaluated here. Higher heat treatment temperatures yielded higher saturation rates and overall saturation at similar matrix porosities. For example, increasing temperature from 300 °C to 700 °C resulted in approximately 60%-70% increase in pore saturation after 100 minutes of soaking. The exposure time to heat treatment had less of an effect on PCM saturation. The exposure time had negligible effect above 30 min and above 500 °C heating temperatures. However, because the expanded graphite was found to oxidize around 700 °C, the use of longer exposure time in manufacturing applications can be beneficial if a shortened impregnation time is needed. Heat treatment conditions did not impact thermal conductivity. The composite latent heat of fusion was also reduced approximately proportionally to the PCM mass fraction. A local maximum in axial thermal conductivity was observed at around 83% porosity, which is similar to previous studies. The observed conductivity at this maximum was a factor of 81 times greater than the conductivity of the PCM.
36 MATERIALS SCIENCE↗
Machine-learning-assisted deciphering of microstructural effects on ionic transport in composite materials: A case study of Li 7 La 3 Zr 2 O 12 -LiCoO 2
The effective diffusivity of ionic species in multiphase materials is critical for the design and function of composite materials for electrochemical energy storage. In practice, effective diffusivity depends sensitively not only on the intrinsic diffusivities of constituting materials but also on their topological arrangement; nevertheless, these coupled contributions are oversimplified in most analytical models. Here, we combine atomistically informed mesoscale modeling and machine learning (ML) analysis to unravel how such features affect effective diffusivity in two-phase composites. Using the Li 7 La 3 Zr 2 O 12 -LiCoO 2 composite solid-state battery cathode as a model system, we compute effective diffusivity for 600 distinct dense polycrystalline microstructures with different topological configurations of grains, grain boundaries, and heterointerfaces. We verify that in addition to atomic-scale variabilities, microstructural feature diversity can significantly impact effective transport properties. Across the ensemble of test microstructures, this often results in bimodal distributions of effective diffusivity that encompass two qualitatively distinct operating mechanisms, which we identify via flux analysis. An ML approach reveals that the most critical determining factors for effective diffusivity are the connectivity of bulk phases and their heterointerfaces. The role of ionic mobility at the heterointerfaces is also discussed. These insights highlight the combined importance of microstructure and interface engineering in tuning the transport properties of ionic species in composite materials. In conclusion, our framework can also be extended for understanding generic microstructure-property relationships in other complex multiphase materials.
25 ENERGY STORAGE↗
Evaluation of Composite Materials for Heliostat Cost Reduction
This is an evaluation of composite materials for heliostat cost reduction, including the motivation, reference heliostat model, characteristic wind loads, selection of pultruded structural composites, and technoeconomic analysis using equivalent deformation.
composite materials↗
hashin_shtrikman_mp: a package for the optimal design and discovery of multi-phase composite materials
hashin_shtrikman_mp is a tool for composites designers who have desired composite properties in mind, but who do not yet have an underlying formulation. The library utilizes the tightest theoretical bounds on the effective properties of composite materials with unspecified microstructure – the Hashin-Shtrikman bounds – to identify candidate theoretical materials, find real materials that are close to the candidates, and determine the optimal volume fractions for each of the constituents in the resulting composite. Its features include (i) leveraging of materials in the Materials Project database, (ii) integration with the Materials Project API, (iii) use of genetic machine-learning, (iv) agnosticism to underlying microstructure, and (v) ultimate engineering application, make it a tool with much broader applications than its predecessors.
97 MATHEMATICS AND COMPUTING↗
Intelligent Manufacturing Support: Specialized LLMs for Composite Material Processing and Equipment Operation
Engineering educational curriculum and standards cover many material and manufacturing options. However, engineers and designers are often unfamiliar with certain composite materials or manufacturing techniques. Large language models (LLMs) could potentially bridge the gap. Their capacity to store and retrieve data from large databases provides them with a breadth of knowledge across disciplines. However, their generalized knowledge base can lack targeted, industry-specific knowledge. To this end, we present two LLM-based applications based on the GPT-4 architecture: (1) The Composites Guide: a system that provides expert knowledge on composites material and connects users with research and industry professionals who can provide additional support and (2) The Equipment Assistant: a system that provides guidance for manufacturing tool operation and material characterization. By combining the knowledge of general AI models with industry-specific knowledge, both applications are intended to provide more meaningful information for engineers. In this paper, we discuss the development of the applications and evaluate it through a benchmark and two informal user studies. The benchmark analysis uses the Rouge and Bertscore metrics to evaluate our models’ performance against GPT-4o. The results show that GPT-4o and the proposed models perform similarly or better on the ROUGE and BERTScore metrics. The two user studies supplement this quantitative evaluation by asking experts to provide qualitative and open-ended feedback about our model’s performance on a set of domain-specific questions. The results of both studies highlight a potential for more detailed and specific responses with the Composites Guide and the Equipment Assistant.
Kapoor, Gunnika [Oak Ridge National Laboratory (OR↗
Wind Turbine Materials Recycling Prize Phase 2 (Commercialization of Wind Turbine Blade Waste (WTBW)-Based, Lightweight, Cementitious Composite Materials): Cooperative Research and Development Final Report, CRADA Number CRD-24-31305
The National Laboratory of the Rockies (NLR) and AltiSora, LLC., will develop new lightweight cementitious composite material technologies that will utilize wind turbine blade waste as a raw material to; (1) allow a high value addition (2) at low cost, enabling (3) a significant waste consumption volume; while (4) consuming the entire wind turbine blade, without (5) creating any waste or emissions and to also (6) offer specific benefits to communities involved.
17 WIND ENERGY↗
Convergent laser beam shapes: Unveiling the dynamics of Laser-induced elastic waves in composite materials
Overcoming the low signal-to-noise ratio (SNR) in laser ultrasonic testing of composite materials remains a significant challenge. Current efforts focus on enhancing SNR by inserting more energy into the material through temporal and/or spatial modulation of the laser beam. However, potential SNR improvements through wave convergence and wave energy manipulation have been overlooked. This paper addresses this gap by demonstrating the convergence of different wave types to a designated point and by showing the feasibility of directing absorbed laser energy into a specific wave type through spatial modulation of the laser beam. To achieve this, mathematical expressions for the convergent laser beams are derived. Various laser beam profiles are then introduced to the thermoelastic equations and solved using the finite element method. The sample under investigation is a transversely isotropic unidirectional carbon fiber reinforced plastic, characterized by anisotropic thermal expansion coefficients and thermal conductivities. Results reveal pronounced convergence of the intended wave type at the center due to laser beam shaping. This study showcases the ability to direct absorbed laser energy toward a specific wave type through spatial modulation of the laser beam and highlights the role of material anisotropy in energy focusing.
composite materials↗
Volatile organic compound emissions from 4D printing: Effects of material composition and external stimulus
4D printing of stimuli-responsive materials extends 3D printing by enabling the fabricated structures to transform their shapes and properties over time in response to external stimuli. Numerous research efforts have been dedicated to developing new smart materials, enhancing material printability, and ensuring time-evolving properties. Meanwhile, the use of smart materials and external stimuli in 4D printing has introduced the possibility of air emissions that can potentially deteriorate the indoor air quality at the workplace and pose continuous health hazards to users during the production and use phases. These potential air emissions caused by 4D printing have not yet been assessed in current literature, leading to unknown occupational hazards and human health effects. This study focuses on stereolithography-based 4D printing with constrained thermo-mechanics and builds an emission model to quantify the volatile organic compound emissions from printing, shape programming, and shape recovery stages. The established model mathematically links the emission characteristics with material compositional design and stimuli-response mechanisms. Additionally, shape fixity and recovery abilities are considered to analyze the trade-off between the air emissions and stimuli-response performance of 4D printed parts. Case study results suggest that the methacrylate-based thermo-responsive material with higher glass transition temperature leads to higher air emissions, surpassing the permissible exposure level in the indoor environment. By altering the thermo-temporal conditions, a 61.29% reduction in emission yield can be achieved while ensuring a satisfactory shape memory performance.
36 MATERIALS SCIENCE↗
Compendium of Material Composition Data for Radiation Transport Modeling
In 2011, Pacific Northwest National Laboratory (PNNL) produced a document known as the Materials Compendium, or Compendium of Material Composition Data for Radiation Transport Modeling, PNNL 15870, Rev. 1, that contains material information useable for modeling purposes for properties of 372 materials. This information is used in several modeling programs used by the radiological/nuclear community, though it is primarily tailored for the Monte-Carlo-N-Particle code produced by Los Alamos National Laboratory. This new document Revision 2 includes a complete review and update of all materials data and references, addressing discrepancies and changes in materials data or references that have occurred since the first revision, an additional 40 materials have been added, primarily newer detector materials developed since the last revision, and isotopic specificity.
07 ISOTOPE AND RADIATION SOURCES↗
Nanostructured lithium-ion battery electrode composite materials via conformal graphene dispersion
Composites comprising anode and cathode active materials conformally coupled to few-layered graphene, corresponding electrodes and related methods of preparation.
Hersam, Mark C.↗