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Results for “Hierarchical Materials”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Facile Fabrication of Hierarchical MOF–Metal Nanoparticle Tandem Catalysts for the Synthesis of Bioactive Molecules

Multifunctional metal–organic frameworks (MOFs) that possess permanent porosity are promising catalysts in organic transformation. Herein, we report the construction of a hierarchical MOF functionalized with basic aliphatic amine groups and polyvinylpyrrolidone-capped platinum nanoparticles (Pt NPs). The postsynthetic covalent modification of organic ligands increases basic site density in the MOF and simultaneously introduces mesopores to create a hierarchically porous structure. The multifunctional MOF is capable of catalyzing a sequential Knoevenagel condensation–hydrogenation–intramolecular cyclization reaction. The unique selective reduction of the nitro group to intermediate hydroxylamine by Pt NPs supported on MOF followed by intramolecular cyclization with a cyano group affords an excellent yield (up to 92%) to the uncommon quinoline N-oxides over quinolines. The hierarchical MOF and polyvinylpyrrolidone capping agent on Pt NPs synergistically facilitate the enrichment of substrates and thus lead to high activity in the reduction–intramolecular cyclization reaction. The bioactivity assay indicates that the synthesized quinoline N-oxides evidently inhibit the proliferation of lung cancer cells. Finally, our findings demonstrate the feasibility of MOF-catalyzed direct synthesis of bioactive molecules from readily available compounds under mild conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Hierarchical Nanomaterials Assembled from Peptoids and Other Sequence-Defined Synthetic Polymers

In nature, the self-assembly of sequence-specific biopolymers into hierarchical structures plays an essential role in the construction of functional biomaterials. To develop synthetic materials that can mimic and surpass the function of these natural counterparts, various sequence-defined bio- and biomimetic polymers have been developed and exploited as building blocks for hierarchical self-assembly. This review summarizes the recent advances in the molecular self-assembly of hierarchical nanomaterials based on peptoids (or poly-N-substituted glycines) and other sequence-defined synthetic polymers. Modern techniques to monitor the assembly mechanisms and characterize the physicochemical properties of these self-assembly systems are highlighted. In addition, discussions about their potential applications in biomedical sciences and renewable energy are also included. Furthermore, this review aims to highlight essential features of sequence-defined synthetic polymers (e.g., high stability and protein-like high-information content) and how these unique features enable the construction of robust biomimetic functional materials with high programmability and predictability, with an emphasis on peptoids and their self-assembled nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Monomer-scale design of functional protein polymers using consensus repeat sequences

Protein-based polymers possess chemically defined sequences that can encode diverse properties and functions into a new class of biopolymeric materials. However, sequence variation that emerges from evolution can obscure the sequence–function relationships of naturally derived polymers. One strategy to clarify these relationships is to identify common sequences between proteins with similar functions. These conserved sequences often emerge from repeat proteins, and “consensus repeat sequences” provide a convenient platform for systematic investigations of biopolymer sequence–property relationships. In this review, we highlight recent approaches to engineer tunable polymeric materials using monomer-scale design of consensus repeat proteins. Here, we explore established and emerging protein-based materials with mechanical resilience, thermodynamic phase behavior, chemical responsiveness, biomolecular transport, and hierarchical structure. Overall, recent advances in the monomer-scale design of repetitive protein polymers present exciting fundamental and translational opportunities for polymer scientists and engineers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development and assessment of hierarchical multi-reward reinforcement learning based potential for silicene with state-of-the-art models

We develop a new interatomic force field for Silicene, a 2D material with a buckled hexagonal lattice structure with high polymorphism. We introduce new parameterizations of a Tersoff model using a hierarchical multi-reward reinforcement learning (RL) methodology coupled with a continuous Monte Carlo Tree Search optimization. Our model significantly outperforms existing methods by enhancing the accuracy of predictions for the structural and thermodynamic properties of seven silicene polymorphs-including structure, energy, equation of state, elasticity, and phonon dispersion-when compared to established models. We further make a comprehensive comparison of the various models in predicting the mechanical and thermal properties of silicene. We trace the origin of the improved performance to the description of the angular dependence in the bond-order term, suggesting that modifying the angular terms in short-range models is essential to capture the structural diversity in low dimensional systems.

2D materials↗
DOE OSTI2025

High-throughput computational framework for high-order anharmonic thermal transport in cubic and tetragonal crystals

Accurate first-principles prediction of lattice thermal conductivity (κL) remains challenging in identifying materials with extreme thermal behavior. While the harmonic approximation with three-phonon scattering (HA + 3ph) is now routine, reliable κL prediction often requires higher-order anharmonic effects, including self-consistent phonon renormalization, three- and four-phonon scattering, and off-diagonal heat flux (SCPH + 3, 4ph + OD). We present a state-of-the-art high-throughput workflow that unifies these effects and apply it to 773 cubic and tetragonal crystals spanning diverse chemistries and structures. From 562 dynamically stable compounds, we assess the hierarchical impacts of higher-order anharmonicity. For around 60% of materials, HA + 3ph predictions closely match those from SCPH + 3, 4ph + OD. SCPH generally increases κ L , by over 8 times in extreme cases, whereas four-phonon scattering universally suppresses κ L , sometimes to 15% of the HA + 3ph value. Off-diagonal contributions are negligible in high-κ L systems but can rival diagonal terms in highly anharmonic low-κ L compounds. We highlight four case studies, Rb 2 TlAlH 6 , Cu 3 VSe 4 , CuBr, and KTlCl 4 , that exhibit distinct extreme behaviors. This work delivers not only a robust workflow for high-fidelity κL dataset but also a quantitative framework to determine when higher-order effects are essential. The hierarchy of κ L results, from the HA + 3ph to SCPH + 3, 4ph + OD level, offers a scalable, interpretable route to discovering next-generation extreme thermal materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tailoring Hierarchical Structure and Rare Earth Affinity of Compositionally Identical Polymers via Sequence Control

Macromolecule sequence, structure, and function are inherently intertwined. While well-established relationships exist in proteins, they are more challenging to define for synthetic polymer nanoparticles due to their molecular weight, sequence, and conformational dispersities. Furthermore, to explore the impact of sequence on nanoparticle structure, we synthesized a set of 16 compositionally identical, sequence-controlled polymers with distinct monomer patterning of dimethyl acrylamide and a bioinspired, structure-driving di(phenylalanine) acrylamide (FF). Sequence control was achieved through multiblock polymerizations, yielding unique ensembles of polymer sequences which were simulated by kinetic Monte Carlo simulations. Systematic analysis of the global (tertiary- and quaternary-like) structure in this amphiphilic copolymer series revealed the effect of multiple sequence descriptors: the number of domains, the hydropathy of terminal domains, and the patchiness (density) of FF within a domain, each of which impacted both chain collapse and the distribution of single- and multichain assemblies. Furthermore, both the conformational freedom of chain segments and local-scale, β-sheet-like interactions were sensitive to the patchiness of FF. To connect sequence, structure, and target function, we evaluated an additional series of nine sequence-controlled copolymers as sequestrants for rare earth elements (REEs) by incorporating a functional acrylic acid monomer into select polymer scaffolds. We identified key sequence variables that influence the binding affinity, capacity, and selectivity of the polymers for REEs. Collectively, these results highlight the potential of and boundaries of sequence control via multiblock polymerizations to drive primary sequence ensembles hierarchical structures, and ultimately the functionality of compositionally identical polymeric materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Machine learning approaches for intentional materials engineering

In this article, the development of nanoporous metals and metallic composites through dealloying processes presents significant opportunities in materials engineering. However, designing multicomponent precursor alloys and establishing corresponding processing methods that yield predictable compositions and nanostructures remain a complex challenge. This article explores how machine learning (ML)-augmented computational and experimental methodologies can tackle these challenges by predicting precursor alloy compositions, final nanoporous structures, and mechanical properties, while integrating ML-enabled autonomous experimentation for material design and quantification. We highlight recent advancements in applying ML to nanostructured materials design via dealloying and discuss how techniques from other nanomaterial designs can be adapted for improved control over morphological and compositional outcomes in nanoporous and nanocomposite materials. Furthermore, we explore the role of ML in autonomous synchrotron x-ray experimentation, enabling real-time feedback between modeling and experimental setups. ML-driven approaches to microstructure characterization and mechanical property prediction are also examined, with a focus on modeling and advanced imaging techniques such as three-dimensional nanotomography. Finally, this article outlines future directions for ML-enhanced materials science, emphasizing the exploration of high-dimensional parameter spaces and the incorporation of materials kinetics into processing and property evaluation, ultimately advancing the design of nanoporous structures and materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Leveraging peptide–cellulose interactions to tailor the hierarchy and mechanics of peptide–polymer hybrids

Inspired by spider silk's hierarchical diversity, we leveraged peptide motifs with the capability to tune structural arrangement for controlling the mechanical properties of a conventional polymer framework. The addition of nanofiller with hydrogen bonding sites was used as another pathway towards hierarchical tuning via matrix–filler interactions. Specifically, peptide–polyurea hybrids (PPUs) were combined with cellulose nanocrystals (CNCs) to develop mechanically-tunable nanocomposites via tailored matrix–filler interactions (or peptide–cellulose interactions). In this material platform, we explored the effect of these matrix–filler interactions on the secondary structure, hierarchical ordering, and mechanical properties of the peptide hybrid nanocomposites. Interactions between the peptide matrix and CNCs occur in all of the PPU/CNC nanocomposites, preventing α-helical ordering, but promoting inter-molecular hydrogen bonded β-sheet formation. Depending on peptide and CNC content, the Young's modulus varies from 10 to 150 MPa. Unlike conventional cellulose-reinforced polymer nanocomposites, the mechanical properties of these composite materials are dictated by a balance of CNC reinforcement, peptidic ordering, and microphase-separated morphology. This research highlights that leveraging peptide–cellulose interactions is a strategy to create materials with targeted mechanical properties for a specific application using a limited selection of building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Three-dimensional hierarchical nanoporous copper via direct ink writing and dealloying

Three-dimensional (3D) hierarchical nanoporous Cu (3DHNP-Cu) is synthesized using a combination of direct ink writing (DIW) based 3D printing, thermal sintering, and chemical dealloying of Mn–Cu alloys. Through tuning processing conditions such as ink composition and cooling rate (after sintering), with consideration of Mn loss during sintering, 3DHNP-Cu with fully bicontinuous nanostructures and negligible residual Mn can be produced after dealloying. The 3DHNP-Cu is comprised of structural features that span seven orders of magnitude, where DIW digitally controls macroscale porous features, thermal sintering and degradation of the binding polymer determines microscale porous features, and dealloying gives rise to nanoscale pores.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Hierarchical Epoxy Structures via Tunable Polymerization-Induced Phase Separation Combined with Additive Manufacturing

Polymerization-induced phase separation (PIPS) allows for the control of thermoset morphologies and properties, enabling the tuning of domain sizes and thermomechanical response. However, its use in generating substructural features in additively manufactured materials has been limited. In this work, we combine epoxy PIPS with UV curable acrylate and rheological modifiers to print nano- to macro-phase separating materials via a two-step, dual-cure approach. This method enables direct ink write printing of hierarchical structures with both controlled morphologies through phase separation and macroscale architecture through print design. We find that formulations for phase-separating materials require judicious incorporation of additives to enable printability and to provide sufficient green strength. Atomic force microscopy-nano infrared mapping reveals tunable, reticulated nano- to micron-scale domains of the resultant multiphase materials and their morphology changes due to additives, resulting in alterations to thermomechanical and tensile properties. Shape memory behavior is also demonstrated through multimaterial additive manufacturing of epoxies with functionally graded internal morphology using active mixing techniques, highlighting this method’s ability to fabricate complex architectures with controlled morphologies and thermomechanical response.

Van Meter, Kylie E [Organic Materials Science, San↗
DOE OSTI2020

Keratin-derived functional carbon with superior charge storage and transport for high-performance supercapacitors

In this work, we report a scalable method to synthesize hierarchically porous, hetero-atom doped activated carbon nanosheet from waste biomass-human hair, and demonstrates the use of this carbon as an ultra-high performance electrode material for supercapacitor applications. Microscopic analyses reveal that sheet size ranges from 50 to 200 nm having a thickness of 15–27 nm. As-synthesized, carbon nanosheets possess a hierarchical porous structure having a specific surface area of 1548 m 2 g -1 . Heteroatom concentration (nitrogen, oxygen, and sulfur) of around 25% is confirmed from XPS analysis. Therefore, the novel interconnected hierarchical porous nanosheets structure enables fast adsorption and transportation of ions during electrochemical processes. Also, the abundant chemically available electroactive heteroatom species in the material enhance the wettability of ions and contribute to pseudocapacitance. The electrochemical analyses through cyclic voltammetry and galvanostatic charge-discharge measurements in 6 M KOH reveal the quasi-EDLC behavior of the activated carbons due to the presence of heteroatoms. A reprensentative KOH activated carbon shows an excellent specific capacitance value of 999 F g -1 at a current density of 1 A g -1 . Furthermore, the symmetrically assembled two-electrode device also delivers a maximum energy density of 32 W h Kg -1 at a power density of 325 W Kg -1 . In addition, excellent cyclic stability of 98% capacitance retention is observed after 10,000 continuous GCD cycles even at a high current density of 5 A g -1 . Symmetric flexible supercapacitor device using KOH-PVA-K3FeCN6 as redox gel polymer electrolyte shows a synergistic specific capacitance of 145 mF cm -1 at a current density of 0.8 mA cm -1 exhibiting very less deviation in bending mode. Therefore, this waste biomass derived heteroatom doped hierarchical porous carbon nanosheets can be a promising material for cost-effective high- performance supercapacitor.

42 ENGINEERING↗
DOE OSTI2024

Hierarchical Composites Patterned via 3D Printed Cellular Fluidics

Additive manufacturing of freeform structures containing multiple materials with deterministic spatial arrangement and interactions remains a challenge for most 3D printing processes, due to complex fabrication tool requirements and limitations in printability of some material classes. Here, in this paper, a versatile method is reported to produce architected composites using the concept of cellular fluidics, in which lattices of unit cells are used as templating scaffolds to guide flowable infill materials in a programmed spatial pattern, upon which they are cured in place to produce a deterministically ordered multimaterial solid. The lattice design relies on the unit cell size, type, strut diameter, surface wetting, and distribution of cellular structures to control liquid flow and retention. Individual unit cells are tuned to achieve reliable infilling and combined into higher-order architectures to achieve multiscale composite materials with disparate mechanical properties, including those considered non-printable. Lattice design considerations for leveraging capillary phenomena and demonstrate several methods of patterning polymers in 3D-printed cellular fluidic structures are presented. The concept of tuning the compressive response of an architected composite using a flexible-elastomer as the lattice and a stiff-epoxy as the infill material is illustrated.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Extreme shear-deformation-induced modification of defect structures and hierarchical microstructure in an Al–Si alloy

Abstract Extreme shear deformation is used for several material processing methods and is unavoidable in many engineering applications in which two surfaces are in relative motion against each other while in physical contact. The mechanistic understanding of the microstructural evolution of multi-phase metallic alloys under extreme shear deformation is still in its infancy. Here, we highlight the influence of shear deformation on the microstructural hierarchy and mechanical properties of a binary as-cast Al-4 at.% Si alloy. Shear-deformation-induced grain refinement, multiscale fragmentation of the eutectic Si-lamellae, and metastable solute saturated phases with distinctive defect structures led to a two-fold increase in the flow stresses determined by micropillar compression testing. These results highlight that shear deformation can achieve non-equilibrium microstructures with enhanced mechanical properties in Al–Si alloys. The experimental and computational insights obtained here are especially crucial for developing predictive models for microstructural evolution of metals under extreme shear deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hierarchically ordered porous transition metal compounds from one-pot type 3D printing approaches

Solution-based soft matter self-assembly (SA) promises unique material structures and properties from approaches including additive manufacturing/three-dimensional (3D) printing. The 3D printing of periodically ordered porous functional inorganic materials through SA unfolding during printing remains a major challenge, however, due to the often vastly different ordering kinetics of separate processes at different length scales. Here, we report a “one-pot” direct ink writing process to produce hierarchically porous transition metal nitrides and precursor oxides from block copolymer (BCP) SA. Heat treatment protocols identified in various environments enable mesostructure retention in the final crystalline materials with periodic lattices on three distinct length scales. Moreover, embedded printing enables the first BCP directed mesoporous non-self-supporting helical oxides and nitrides. Resulting nitrides are superconducting, with record nanoconfinement-induced upper critical fields correlated with BCP molar mass and record surface areas for compound superconductors. Results suggest scalable porous functional inorganic material formation approaches for applications including catalysis, sensing, and microelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Endowing low fatigue for elastocaloric effect by refined hierarchical microcomposite in additive manufactured NiTiCuCo alloy

Abstract NiTiCu-based shape memory alloys have been considered as ideal materials for solid-state refrigeration due to their superb cycling stability for elastocaloric effect. However, the embrittlement and deterioration caused by secondary phase and coarse grains restrict their applications, and it is still challenging since the geometric components are required. Here, bulk NiTiCuCo parts with excellent forming quality were fabricated by laser powder bed fusion (LPBF) technique. The as-fabricated alloy exhibits refined three-phases hierarchical microcomposite formed based on the rapid cooling mode of LPBF, composed of intricate dendritic Ti 2 Ni–NiTi composite and nano Ti 2 Cu embedded inside the NiTi-matrix. This configuration endows far superior elastocaloric stability compared to the as-cast counterpart. The low fatigue stems from the strong elastic coupling between the interphases with reversible martensite transformation, revealed byin-situsynchrotron high-energy x-ray diffraction. The fabrication of NiTiCuCo alloy via LPBF fills the bill of complex geometric structures for elastocaloric NiTiCu alloys. The understanding of interphase micro-coupling could provide the guide for designing LPBF fabricated shape memory-based composites, enabling their applications for special demands on other functionalities.

Engineering↗
DOE OSTI2023

Multi–Step Nucleation of a Crystalline Silicate Framework via a Structurally Precise Prenucleation Cluster

Hierarchical nucleation pathways are ubiquitous in the synthesis of minerals and materials. In the case of zeolites and metal–organic frameworks, pre-organized multi-ion “secondary building units” (SBUs) have been proposed as fundamental building blocks. However, detailing the progress of multi-step reaction mechanisms from monomeric species to stable crystals and defining the structures of the SBUs remains an unmet challenge. Furthermore, combining in situ nuclear magnetic resonance, small-angle X-ray scattering, and atomic force microscopy, we show that crystallization of the framework silicate, cyclosilicate hydrate, occurs through an assembly of cubic octameric Q 3 8 polyanions formed through cross-linking and polymerization of smaller silicate monomers and other oligomers. These Q 3 8 are stabilized by hydrogen bonds with surrounding H 2 O and tetramethylammonium ions (TMA + ). When Q 3 8 levels reach a threshold of ≈32 % of the total silicate species, nucleation occurs. Further growth proceeds through the incorporation of [(TMA) x (Q 3 8 )•n H 2 O] (x–8) clathrate complexes into step edges on the crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Radiative cooling textiles using industry-standard particle-free nonporous micro-structured fibers

Abstract Thermal radiation is a major dissipative pathway for heat generated by the human body and offers a significant thermoregulation mechanism over a wide range of conditions. We could use this in garment design to enhance personal cooling, which can improve the wearing comfort of garments or even result in energy savings in buildings. At present, however, radiative cooling has received insufficient attention in commercial design and production of textiles for wearable garments. Textiles that efficiently transmit the radiative heat were recently demonstrated, but either do not utilize standard weaving and knitting processes for wearable garments or require substantial process modifications. Here, we demonstrate the design and implementation of large-scale radiative cooling textiles for localized cooling management and enhanced thermal comfort using industry-standard particle-free nonporous micro-structured fibers that are fully compatible with standard textile materials and production methods. The micro-structured fibers, yarns and fabrics are part of a hierarchical photonic structure design that renders the textiles highly infrared transparent (up to > 0.8) while assuring visual opacity (up to 0.99). We design radiative cooling textiles with first-principles electromagnetic methods and fabricate them using commercial textile materials and formation facilities. Our “fabless” approach is confirmed by very good quantitative agreement between design and measurements. The resulting fabrics exhibit wearability properties expected of wearable textiles, and lower skin temperature by ≥ 3 °C compared to conventional textiles, which offers the potential for > 30 % energy savings in buildings and increases wearing comfort by significantly reducing the reliance on latent heat dissipation for thermoregulation.

Catrysse, Peter B.↗