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At least 91 records · Page 5

Controlled release of hydrogen from composite nanoparticles

Multi-functional materials for use in reversible, high-capacity hydrogen separation and/or storage are described. Also described are systems incorporating the materials. The multi-functional materials combine a hydrogen absorbing material with a high-efficiency and anon-contact energy absorbing material in a composite nanoparticle. The non-contact energy absorbing material include magnetic and/or plasmonic materials. The magnetic or plasmonic materials of the composite nanoparticles can provide localized heating to promote release of hydrogen from the hydrogen storage component of the composite nanoparticles.

08 HYDROGEN↗

Controlled release of hydrogen from composite nanoparticles

Multi-functional materials for use in reversible, high-capacity hydrogen separation and/or storage are described. Also described are systems incorporating the materials. The multi-functional materials combine a hydrogen-absorbing material with a high-efficiency and a non-contact energy-absorbing material in a composite nanoparticle. The non-contact energy-absorbing material include magnetic and/or plasmonic materials. The magnetic or plasmonic materials of the composite nanoparticles can provide localized heating to promote release of hydrogen from the hydrogen storage component of the composite nanoparticles.

Murph, Simona H.↗

Automated path planning for functionally graded materials considering phase stability and solidification behavior: Application to the Mo-Nb-Ta-Ti system

Functionally graded materials have the potential to improve upon monolithic parts by locally tailoring compositions to surrounding environmental conditions. Difficulties arise when designing composition gradients as incompatible materials can result in detrimental phase formation and failure of the gradient joint. As many alloys are multi-component, designing a composition gradient free of detrimental phases is difficult due to the large composition space available to explore. A framework was developed that improves the path planning algorithm and surrogate models with adaptive sampling schemes specific to their problem definition. A cost function was created to minimize a property (such as cracking susceptibility) along a path. This framework was applied to the Mo-Nb-Ta-Ti system as a case study to showcase the efficiency in building the surrogate models and in iterating different optimal compositionally graded paths.

36 MATERIALS SCIENCE↗

(U) Validation and Optimization of a 1-Dimensional Quasi-Isentropic Compression Model Using a Functionally Graded Material Flyer Plate

The fields studying highly compressed materials have been around for many years. These fields have given birth to better understandings of the solar fusion cycle and the liquid-metallic core of Jupiter. The highest pressures achieved have been at the National Ignition Facility (NIF) and more recently, the Z-Machine. One method to achieve higher levels of compression is to use quasi-isentropic (QI) compression. In practice, this means minimizing the amount of temperature increase of the target material. In their paper, J.H. Nguyen et. al. manufactured a functionally graded material (FGM) in order to help them achieve QI compression. The aim of the study described in this paper is to validate a 1-dimensional (1D) FLAG model that uses an FGM flyer to compress a copper (Cu) target. Once validated, the density/composition profile of the FGM is varied and optimized using Markov Chain Monte Carlo, specifically using a Metropolis-Hastings algorithm to find the optimal FGM profile that minimizes the temperature increase in the copper.

36 MATERIALS SCIENCE↗

Design of an additively manufactured functionally graded material of 316 stainless steel and Ti-6Al-4V with Ni-20Cr, Cr, and V intermediate compositions

This study presents a method for designing a computationally informed gradient pathway to fabricate a functionally graded material (FGM) with terminal alloys of 316 stainless steel (SS316) and Ti-6Al-4V via directed energy deposition additive manufacturing with powder feedstock. In this work, the grading is accomplished through the introduction of intermediate elements and alloys (Ni-20Cr, Cr, and V) to avoid the brittle Fe-Ti intermetallic phases that form in the direct liquid phase joining of Ti-alloys and stainless steels. Using a combination of equilibrium calculations and Scheil-Gulliver simulations, a compositional pathway was designed to avoid deleterious phases. FGM samples were fabricated and experimentally characterized to determine the viability of the pathway. A change in phases from fcc to bcc was predicted to occur within the Ni-20Cr/Cr gradient region, and this was validated through experimental characterization. No detrimental phases (intermetallic, Laves, or σ phases) formed along the gradient path, demonstrating a successful computationally-informed design and fabrication of an FGM from SS316 to Ti-6Al-4V.

36 MATERIALS SCIENCE↗

Machine Learning for Additive Manufacturing of Functionally Graded Materials

Additive Manufacturing (AM) is a transformative manufacturing technology enabling direct fabrication of complex parts layer-by-layer from 3D modeling data. Among AM applications, the fabrication of Functionally Graded Materials (FGMs) has significant importance due to the potential to enhance component performance across several industries. FGMs are manufactured with a gradient composition transition between dissimilar materials, enabling the design of new materials with location-dependent mechanical and physical properties. This study presents a comprehensive review of published literature pertaining to the implementation of Machine Learning (ML) techniques in AM, with an emphasis on ML-based methods for optimizing FGMs fabrication processes. Through an extensive survey of the literature, this review article explores the role of ML in addressing the inherent challenges in FGMs fabrication and encompasses parameter optimization, defect detection, and real-time monitoring. The article also provides a discussion of future research directions and challenges in employing ML-based methods in the AM fabrication of FGMs.

36 - MATERIALS SCIENCE↗

Stress-controlled medium-amplitude oscillatory shear (MAOStress) of PVA–Borax

We report the first-ever complete measurement of MAOStress material functions, which reveal that stress can be more fundamental than strain or strain rate for understanding linearity limits as a function of Deborah number. The material used is a canonical viscoelastic liquid with a single dominant relaxation time: polyvinyl alcohol (PVA) polymer solution cross-linked with tetrahydroborate (Borax) solution. We outline experimental limit lines and their dependence on geometry and test conditions. These MAOStress measurements enable us to observe the frequency dependence of the weakly nonlinear deviation as a function of stress amplitude. The observed features of MAOStress material functions are distinctly simpler than MAOStrain, where the frequency dependence is much more dramatic. The strain-stiffening transient network model was used to derive a model-informed normalization of the nonlinear material functions that accounts for their scaling with linear material properties. Moreover, we compare the frequency dependence of the critical stress, strain, and strain-rate for the linearity limit, which are rigorously computed from the MAOStress and MAOStrain material functions. While critical strain and strain-rate change by orders of magnitude throughout the Deborah number range, critical stress changes by a factor of about 2, showing that stress is a more fundamental measure of nonlinearity strength. This work extends the experimental accessibility of the weakly nonlinear regime to stress-controlled instruments and deformations, which reveal material physics beyond linear viscoelasticity but at conditions that are accessible to theory and detailed simulation.

Mechanics↗

DED Additively Manufactured HEAs Optimized via Parametric Study of Functionally Graded Materials

Complex concentrated alloys (CCAs) are a system of alloys composition of nearly equiatomic elements, creating a state of high configurational entropy in the material. These alloys are of interest for various industrial applications due to their high strength and hardness, wide operational temperature range, creep and diffusion resistance, and radiation resistance. In the current work CoCrFeNi-base CCAs are synthesize by combining three commonly industrial alloys: IN718, SS316L, and 70Co30Cr (commercially known as Stellite 21), in-situ utilizing directed energy deposition (DED) additive manufacturing (AM). One bulk specimen is fabricated with a 1:1:1 ratio of IN718, SS316L, and 70Co30Cr where IN718 is a source of nickel and chrome, SS316 is a source of iron and chrome, and 70Co30Cr is a source of cobalt and supplemental chrome. Additionally, a functionally graded material (FGM) of the identified CCA system from SS316 was fabricated with 10 layers, where the initial five layers are the base material of SS316L and graded by steps of 20% to transition to the CCA system. Overall build quality, microstructure, compositional distribution, phases analysis, and microhardness were studied by laser optical microscopy, scanning election microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction analysis (XRD), and Vickers microhardness techniques. Overall build quality showed a successful bulk build with acceptable density, however unmelted particles are observed in the as-built alloy. Compositional results show that the system meets the Boltzmann’s hypothesis definition of an HEA, and that an FCC CCA was produced with increased hardness, small grain size, and superior hardness properties to the SS316L substrate. While initial XRD results show predominately FCC structure, EDS analysis of interdendritic regions show the existence of Laves phases in the material. The fabrication of an FGM CCA allowed for potential screening of additional alloy mixes which may be of interest to explore in future research, and the resulting composition is compared to predicted values. This novel method of CCA fabrication results in substantial cost savings of these CCA systems over traditional methods.

36 MATERIALS SCIENCE↗

Polyester functional graphenic materials as a mechanically enhanced scaffold for tissue regeneration

Traditional metal implants such as titanium, cobalt, and chromium have found wide utility in medicine; however, these come with a risk of toxicity. To overcome metal-related toxicity and enable degradability, polyesters including polycaprolactone (PCL), polylactic acid (PLA), and polyglycolic acid (PGA) show promise for the replacement of various biomedical applications of metals due to their accepted biocompatibility and FDA approval. However, polyesters are less stiff than their metallic counterparts, limiting their application to non-load bearing injury sites, such as fixation hardware for fingers. To improve mechanical properties, graphene oxide (GO)-polyester composites are a promising class of biodegradable scaffolds. Initial reports of these composites are encouraging, but mechanical properties still fall short. Traditional composites rely on non-covalent association between GO and the polyesters, which often leads to failure at the interface and weakens the overall strength of the material. Herein, we present a strategy for attachment of these FDA-approved polyesters onto a derivative of GO using a robust covalent bond. By covalently functionalizing the graphenic backbone with polyesters and without metal catalysts, we create functional graphenic materials (FGMs) to not only simultaneously retain biodegradability and compatibility, but also mechanically strengthen PCL, PLA, and PGA; we observed an average increase in the Young's modulus of over 140% compared to the graphenic backbone. These polyester-functionalized FGMs are a promising platform technology for tissue implants.

60 APPLIED LIFE SCIENCES↗

Featureless adaptive optimization accelerates functional electronic materials design

Electronic materials that exhibit phase transitions between metastable states (e.g., metal-insulator transition materials with abrupt electrical resistivity transformations) are challenging to decode. For these materials, conventional machine learning methods display limited predictive capability due to data scarcity and the absence of features that impede model training. In this article, we demonstrate a discovery strategy based on multi-objective Bayesian optimization to directly circumvent these bottlenecks by utilizing latent variable Gaussian processes combined with high-fidelity electronic structure calculations for validation in the chalcogenide lacunar spinel family. We directly and simultaneously learn phase stability and bandgap tunability from chemical composition alone to efficiently discover all superior compositions on the design Pareto front. Previously unidentified electronic transitions also emerge from our featureless adaptive optimization engine. Our methodology readily generalizes to optimization of multiple properties, enabling co-design of complex multifunctional materials, especially where prior data is sparse.

36 MATERIALS SCIENCE↗

Control of polarization in bulk ferroelectrics by mechanical dislocation imprint

Defects are essential to engineering the properties of functional materials ranging from semiconductors and superconductors to ferroics. Whereas point defects have been widely exploited, dislocations are commonly viewed as problematic for functional materials and not as a microstructural tool. In this work, we developed a method for mechanically imprinting dislocation networks that favorably skew the domain structure in bulk ferroelectrics and thereby tame the large switching polarization and make it available for functional harvesting. The resulting microstructure yields a strong mechanical restoring force to revert electric field–induced domain wall displacement on the macroscopic level and high pinning force on the local level. This induces a giant increase of the dielectric and electromechanical response at intermediate electric fields in barium titanate [electric field–dependent permittivity (ε 33 ) ≈ 5800 and large-signal piezoelectric coefficient ( d 33 *) ≈ 1890 picometers/volt]. Dislocation-based anisotropy delivers a different suite of tools with which to tailor functional materials.

36 MATERIALS SCIENCE↗

Additively manufactured Ni-20Cr to V functionally graded material: Computational predictions and experimental verification of phase formations

Throughout this work, a database for the Cr-Ni-V system was constructed by modeling the binary Cr-V and ternary Cr-Ni-V systems using the CALPHAD approach aided by density functional theory (DFT)-based first-principles calculations and ab initio molecular dynamics (AIMD) simulations. To validate this new database, a functionally graded material (FGM) using Ni-20Cr and elemental V was fabricated using directed energy deposition additive manufacturing (DED AM) and experimentally characterized. The deposited Ni-20Cr was pure fcc phase, while increasing the amount of V across the gradient resulted in the formation of sigma phase, followed by the bcc phase. The experimentally measured phase data was compared with computational predictions made using a Cr-Ni-V thermodynamic database from the literature as well as the database developed in the present work. The newly developed database was shown to better predict the experimentally observed phases due to its accurate modeling of binary systems within the database and the ternary liquid phase, which is critical for accurate Scheil calculations.

36 MATERIALS SCIENCE↗

Automated Process Planning for Embossing and Functionally Grading Materials via Site-Specific Control in Large-Format Metal-Based Additive Manufacturing

The potential for site-specific, process-parameter control is an attribute of additive manufacturing (AM) that makes it highly attractive as a manufacturing process. The research interest in the functionally grading material properties of numerous AM processes has been high for years. However, one of the issues that slows developmental progress in this area is process planning. It is not uncommon for manual programming methods and bespoke solutions to be utilized for site-specific control efforts. This article presents the development of slicing software that contains a fully automated process planning approach for enabling through-thickness, process-parameter control for a range of AM processes. The technique includes the use of parent and child geometries for controlling the locations of site-specific parameters, which are overlayed onto unmodified toolpaths, i.e., a vector-based planning approach is used in which additional information, such as melt pool size for large-scale metal AM processes, is assigned to the vectors. This technique has the potential for macro- and micro-structural modifications to printed objects. A proof-of-principle experiment is highlighted in which this technique was used to generate dynamic bead geometries that were deposited to induce a novel surface embossing effect, and additional software examples are presented that highlight software support for more complex objects.

36 MATERIALS SCIENCE↗

Optimization of Functionally Graded Materials Using Additive Manufacturing: An Integrated Experimental and Computational Approach (Abbreviated Final Report)

Many advanced technologies, such as next-generation energy systems, aerospace vehicles, and defense platforms, require materials that can withstand extreme environments, including high temperatures, corrosion, and radiation, while remaining strong and lightweight. Traditionally, joining different materials to achieve these properties introduces weak, failure-prone interfaces and defects that limit performance. Our research aimed to overcome this challenge by using additive manufacturing, specifically directed energy deposition, to create functionally graded materials—components with smooth transitions between different metals. This approach eliminates sharp boundaries and allows for tailored material properties throughout a part.

36 MATERIALS SCIENCE↗

Unconventional Materials Processing Using Spark Plasma Sintering

Spark plasma sintering (SPS) has gained recognition in the last 20 years for its rapid densification of hard-to-sinter conventional and advanced materials, including metals, ceramics, polymers, and composites. Herein, we describe the unconventional usages of the SPS technique developed in the field. The potential of various new modifications in the SPS technique, from pressureless to the integration of a novel gas quenching system to extrusion, has led to SPS’ evolution into a completely new manufacturing tool. The SPS technique’s modifications have broadened its usability from merely a densification tool to the fabrication of complex-shaped components, advanced functional materials, functionally gradient materials, interconnected materials, and porous filter materials for real-life applications. The broader application achieved by modification of the SPS technique can provide an alternative to conventional powder metallurgy methods as a scalable manufacturing process. The future challenges and opportunities in this emerging research field have also been identified and presented.

36 MATERIALS SCIENCE↗

Beyond Pristine Metal–Organic Frameworks: Preparation of Hollow MOFs and Their Composites for Catalysis, Sensing, and Adsorption Removal Applications

Metal–organic frameworks (MOFs) have been broadly applied to numerous domains with a substantial surface area, tunable pore size, and multiple unsaturated metal sites. Recently, hollow MOFs have greatly attracted the scientific community due to their internal cavities and gradient pore structures. Hollow MOFs have a higher tunability, faster mass-transfer rates, and more accessible active sites when compared to traditional, solid MOFs. Hollow MOFs are also considered to be candidates for some functional material carriers. For example, composite materials such as hollow MOFs and metal nanoparticles, metal oxides, and enzymes have been prepared. These composite materials integrate the characteristics of hollow MOFs with functional materials and are broadly used in many aspects. This review describes the preparation strategies of hollow MOFs and their composites as well as their applications in organic catalysis, electrochemical sensing, and adsorption separation. Finally, we hope that this review provides meaningful knowledge about hollow-MOF composites and their derivatives and offers many valuable references to develop hollow-MOF-based applied materials.

36 MATERIALS SCIENCE↗