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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 307 records · Page 17

Potential-induced wetting and dewetting in pH-responsive block copolymer membranes for mass transport control

Wetting and dewetting behavior in channel-confined hydrophobic volumes is used in biological membranes to effect selective ion/molecular transport. Artificial biomimetic hydrophobic nanopores have been devised utilizing wetting and dewetting, however, tunable mass transport control utilizing multiple transport modes is required for applications such as controllable release/transport, water separation/purification and energy conversion. Here, we investigate the potential-induced wetting and dewetting behavior in a pH-responsive membrane composed of a polystyrene-b-poly(4-vinylpyridine) (PS-b-P4VP) block copolymer (BCP) when fabricated as a hierarchically-organized sandwich structure on a nanopore electrode array (NEA), i.e. BCP@NEA. At pH < pK a (P4VP) (pK a ~ 4.8), the BCP acts as an anion-exchange membrane due to the hydrophilic, protonated P4VP cylindrical nanodomains, but at pH > pK a (P4VP), the P4VP domains exhibit charge-neutral, hydrophobic and collapsed structures, blocking mass transport via the hydrophobic membrane. However, when originally prepared in a dewetted condition, mass transport in the BCP membrane may be switched on if sufficiently negative potentials are applied to the BCP@NEA architecture. When the hydrophobic BCP membrane is introduced on top of 2-electrode-embedded nanopore arrays, electrolyte solution in the nanopores is introduced, then isolated, by exploiting the potential-induced wetting and dewetting transitions in the BCP membrane. The potential-induced wetting/dewetting transition and the effect on cyclic voltammetry in the BCP@NEA structures is characterized as a function of the potential, pH and ionic strength. Additionally chronoamperometry and redox cycling experiments are used to further characterize the potential response. The multi-modal mass transport system proposed in this work will be useful for ultrasensitive sensing and single-molecule studies, which require long-time monitoring to explore reaction dynamics as well as molecular heterogeneity in nanoconfined volumes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A cellulose-derived supramolecule for fast ion transport

Supramolecular frameworks have been widely synthesized for ion transport applications. However, conventional approaches of constructing ion transport pathways in supramolecular frameworks typically require complex processes and display poor scalability, high cost, and limited sustainability. Here, we report the scalable and cost-effective synthesis of an ion-conducting (e.g., Na + ) cellulose-derived supramolecule (Na-CS) that features a three-dimensional, hierarchical, and crystalline structure composed of massively aligned, one-dimensional, and ångström-scale open channels. Using wood-based Na-CS as a model material, we achieve high ionic conductivities (e.g., 0.23 S/cm in 20 wt% NaOH at 25 °C) even with a highly dense microstructure, in stark contrast to conventional membranes that typically rely on large pores (e.g., submicrometers to a few micrometers) to obtain comparable ionic conductivities. This synthesis approach can be universally applied to a variety of cellulose materials beyond wood, including cotton textiles, fibers, paper, and ink, which suggests excellent potential for a number of applications such as ion-conductive membranes, ionic cables, and ionotronic devices.

36 MATERIALS SCIENCE↗

A Multiscale Inelastic Internal State Variable Corrosion Model

We present a corrosion internal state variable (ISV) damage model based upon the integrated computational materials engineering (ICME) hierarchical multiscale paradigm. Structure–property experiments for magnesium alloys were used where the only inputs were the volume fractions of each element of the periodic table. This macroscale ISV corrosion model finds its basis in Horstemeyer’s mechanical damage model, which includes three separate ISVs for damage nucleation, growth, and coalescence, as well as Walton’s inclusion of corrosion, which introduces five new ISVs for pit nucleation, growth, and coalescence, along with general corrosion and intergranular corrosion. While Walton’s corrosion ISVs are phenomenological in nature, herein we develop a multiscale physical basis for the corrosion ISVs. The parameters for the macroscale corrosion ISVs were garnered from the mesoscale Butler–Volmer equations. Pure magnesium with differing amounts of aluminum were used in corrosion tests to exemplify the different pitting, general corrosion, and intergranular corrosion rates, and the macroscale ISV model was calibrated with said data, in which the only inputs to the model are the volume percentages of the elements magnesium and aluminum. Although magnesium alloys were used to motivate and calibrate the model, the model is abstract enough to possibly capture other material systems as well.

Chemistry↗

Hierarchical porous metals with deterministic 3D morphology and shape via de-alloying of 3D printed alloys

The present disclosure relates to a method for forming a three dimensional, hierarchical, porous metal structure with deterministically controlled 3D multiscale pore architectures. The method may involve providing a feedstock able to be applied in an additive manufacturing process, and using an additive manufacturing process to produce a three dimensional (3D) structure using the feedstock. The method may involve further processing the 3D structure through at least a de-alloying operation to form a metallic 3D structure having an engineered, digitally controlled macropore morphology with integrated nanoporosity.

Qi, Zhen↗

Crystallization pathways and interfacial drivers for the formation of hierarchical architectures

The development of structural hierarchy on various length scales during crystallization process is ubiquitous in biological systems and is also observed in synthetic nanomaterials. The driving forces for the formations of complex architectures range from local interfacial interactions, that modify interfacial speciation, local supersaturation, and nucleation barriers, to macroscopic interparticle forces. Although it is enticing to interpret the formation of hierarchical architectures as the assembly of independently nucleated building blocks, often crystallization pathways follow monomer-by-monomer addition with structural complexity arising from interfacial chemical coupling and strongly correlated fluctuation dynamics in the electric double layers. Here, the mechanism of the development of structural hierarchy through heterogeneous nucleation, coupled interfacial nucleation and assembly, and oriented attachment of independently nucleated particles is discussed. In this article, the emphasis is made on the discussion of the underlying interfacial forces and chemical coupling that drives crystallization pathways towards the formation of structural hierarchy.

36 MATERIALS SCIENCE↗

Hierarchical Truncations for Many-Body Expansion Potentials

In this work, a new strategy to truncate high-order terms in the many-body expansion (MBE) is proposed. This new approach, which we call a hierarchical many-body expansion (HMBE), is based on a hierarchical partition of the system into multitier fragments and can in principle be applied to any large molecular system. Numerical tests on a series of (H 2 O) 64 structures are presented, demonstrating satisfactory relative energies between the clusters and binding energies of individual clusters compared with full-cluster calculations, with significantly fewer high-order terms computed than conventional MBE. The hierarchical truncation can be augmented by certain many-body terms for fragments at the interface between the partitions (called “Schengen terms”) to further improve accuracy. This work establishes the HMBE scheme as a promising framework to model very large systems (e.g., proteins), which are naturally built on a hierarchical structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-throughput investigation of structural evolution upon solid-state in Cu–Cr–Co combinatorial multilayer thin-film

Cu-Cr-Co combinatorial multilayer thin-films were prepared by a high-throughput ion beam sputtering system. Based on the thickness ratio among the individual nanoscale monolayers (Cu, Cr, Co), the resulting stoichiometry covered the entire phase diagram. The chemical composition and structure of Cu-Cr-Co combinatorial chip upon solid-state reaction were studied by lab-based micro-X-ray fluorescence (mu-XRF) and high-throughput synchrotron X-ray diffraction (XRD), respectively. A composition-structure map for Cu-Cr-Co combinatorial chip was developed through automated data analysis employing hierarchical clustering techniques. The structural evolution of Cu-Cr-Co combinatorial chip as a function of heat-treatment temperature, time, and modulation period were studied systematically. Furthermore, the effect of the elemental distribution in-depth direction was investigated to gain more insights regarding phase transformation. This work provides an efficient method and new perspectives for the design and optimization of the composition and structure of high-performance thin-films.

36 MATERIALS SCIENCE↗

Memory effect and phase transition in a hierarchical trap model for spin glasses

Here, we introduce an efficient dynamical tree method that enables us to explicitly demonstrate the thermoremanent magnetization memory effect in a hierarchical energy landscape. Our simulation nicely reproduces the nontrivial waiting-time and waiting-temperature dependences in this nonequilibrium phenomenon. We further investigate the condensation effect, in which a small set of microstates dominates the thermodynamic behavior in the multilayer trap model. Importantly, a structural phase transition of the multilayer tree model is shown to coincide with the onset of the condensation phenomenon. Our results underscore the importance of hierarchical structure and demonstrate the intimate relation between the glassy behavior and structure of barrier trees.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Hierarchical microstructures: a potential route to enhanced stability in structural materials for advanced nuclear reactors

The drive to increase efficiency in nuclear energy systems is leading to the need for materials that operate at higher temperatures and stress levels for extended periods, while maintaining stable microstructures to ensure their performance is not compromised. A novel route to producing materials that can perform well in such environments is the creation of hierarchical microstructures. A hierarchical microstructure is a microstructure in which features are present at multiple length scales simultaneously. In this work, a hierarchical microstructure is fabricated in a nickel-base superalloy, featuring nanometer-size gamma precipitates inside larger gamma-prime particles, which are in turn embedded in the gamma matrix phase. The hierarchical features of the microstructure lead to enhanced stability of the gamma-prime precipitates during annealing; the particle size does not follow the expected t^(1/3) growth law predicted by the classic LSW theory. Phase-field simulations are used to understand the unexpected stability of the gamma-prime precipitates.

36 MATERIALS SCIENCE↗

Hierarchical microstructures: a potential route to enhanced stability in structural materials for advanced nuclear reactors

The drive to increase efficiency in nuclear energy systems is leading to the need for materials that operate at higher temperatures and stress levels for extended periods, while maintaining stable microstructures to ensure their performance is not compromised. A novel route to producing materials that can perform well in such environments is the creation of hierarchical microstructures. A hierarchical microstructure is a microstructure in which features are present at multiple length scales simultaneously. In this work, a hierarchical microstructure is fabricated in a nickel-base superalloy, featuring nanometer-size gamma precipitates inside larger gamma-prime particles, which are in turn embedded in the gamma matrix phase. The hierarchical features of the microstructure lead to enhanced stability of the gamma-prime precipitates during annealing; the particle size does not follow the expected t^(1/3) growth law predicted by the classic LSW theory. Phase-field simulations are used to understand the unexpected stability of the gamma-prime precipitates.

36 - MATERIALS SCIENCE↗

A multi-phase-field model of topological pattern formation during electrochemical dealloying of binary alloys

Porous metal structures produced by electrochemical dealloying have been extensively studied for use in various applications that require high surface areas. A new comprehensive multi-phase-field (MPF) model is proposed to study topological porous patterns formed by spontaneously etching a bulk binary alloy that involves electrochemical reactions, bulk and surface diffusion, ion transport, applied electrode potential, and charge conservation. The governing equations for the alloy-porous cluster-electrolyte system account for a generalized Butler-Volmer electrochemical reaction and are in accordance with the classical nucleation theory. Based on a quantitative examination of the effects of electrode potential and precursor composition, the simulation results reproduce typical phenomena including passive surface dealloying, active porosity evolution, critical potential, and characteristic length scale in two-dimension (2-D) and three-dimension (3-D). To consider more complicated dealloying systems, the evolutions of a bimodal porous metal structure, nanocomposite, and nested porous network with a structured hierarchy are investigated. Finally, the proposed model can be a useful tool for understanding and predicting the morphology evolution of diverse porous structures during electrochemical dealloying.

Hierarchical porous structure↗

Unraveling the advances of trace doping engineering for potassium ion battery anodes via tomography

Doping have been considered as a prominent strategy to stabilize crystal structure of battery materials during the insertion and removal of alkali ions. The instructive knowledge and experience acquired from doping strategies predominate in cathode materials, but doping principle in anodes remains unclear. Here, we demonstrate that trace element doping enables stable conversion-reaction and ensures structural integrity for potassium ion battery (PIB) anodes. With a synergistic combination of X-ray tomography, structural probes, and charge reconfiguration, we encode the physical origins and structural evolution of electro-chemo-mechanical degradation in PIB anodes. By the multiple ion transport pathways created by the orderly hierarchical pores from “surface to bulk” and the homogeneous charge distribution governed in doped nanodomains, the anisotropic expansion can be significantly relieved with trace isoelectronic element doping into the host lattice, maintaining particle mechanical integrity. Our work presents a close relationship between doping chemistry and mechanical reliability, projecting a new pathway to reengineering electrode materials for next-generation energy storage.

25 ENERGY STORAGE↗

Petaloid-shaped ZnO coated carbon felt as a controllable host to construct hierarchical Li composite anode

Prestoring Li metal into the 3D host via thermal infusion strategy has been considered as an effective approach on suppressing Li dendrites growth of Li-metal anode during cycling. However, the fast Li infusing process generally induces uncontrollable and undesirable structures during the formation of composite Li metal anode. It is widely accepted that both physical and chemical interactions between the molten Li and the hosts provide driving forces for Li infusing into the host, but which one plays the dominant role has not been explored clearly. In this work, a 3D carbon felt coated by petaloid zinc oxide (CFZO) is designed as a controllable host for prestoring Li metal via thermal infusion method. It is revealed that the morphology induced physical driving force plays a more important role than the chemical reaction between ZnO and molten Li in the thermal infusion process. The physical driving force originates from the capillarity effect, depending on the roughness of the host according to Wenzel's model. An adjustable Li infusing process can be controlled to fabricate the Li composite electrode with a hierarchical structure (with dense Li-rich layer and porous Li-poor layer). The unique structure of the CFZO-Li not only provides enough spaces for Li deposition, but also disperses local current density to induce a uniform Li deposition behavior, thus Li dendrites can be suppressed effectively. As a result, CFZO-Li anode exhibits promising cycle stability when coupled with both Li-containing (LiNi 0.8 Co 0.15 Al 0.05 O 2 ) and Li-free (sulfur) cathodes.

25 ENERGY STORAGE↗

HLA-Clus: HLA class I clustering based on 3D structure

In a previous paper, we classified populated HLA class I alleles into supertypes and subtypes based on the similarity of 3D landscape of peptide binding grooves, using newly defined structure distance metric and hierarchical clustering approach. Compared to other approaches, our method achieves higher correlation with peptide binding specificity, intra-cluster similarity (cohesion), and robustness. Here we introduce HLA-Clus, a Python package for clustering HLA Class I alleles using the method we developed recently and describe additional features including a new nearest neighbor clustering method that facilitates clustering based on user-defined criteria. The HLA-Clus pipeline includes three stages: First, HLA Class I structural models are coarse grained and transformed into clouds of labeled points. Second, similarities between alleles are determined using a newly defined structure distance metric that accounts for spatial and physicochemical similarities. Finally, alleles are clustered via hierarchical or nearest-neighbor approaches. We also interfaced HLA-Clus with the peptide:HLA affinity predictor MHCnuggets. By using the nearest neighbor clustering method to select optimal allele-specific deep learning models in MHCnuggets, the average accuracy of peptide binding prediction of rare alleles was improved. The HLA-Clus package offers a solution for characterizing the peptide binding specificities of a large number of HLA alleles. This method can be applied in HLA functional studies, such as the development of peptide affinity predictors, disease association studies, and HLA matching for grafting. HLA-Clus is freely available at our GitHub repository (https://github.com/yshen25/HLA-Clus).

59 BASIC BIOLOGICAL SCIENCES↗

Local Structure Analysis and Modelling of Lignin‐Based Carbon Composites through the Hierarchical Decomposition of the Radial Distribution Function

Abstract Carbonized lignin has been proposed as a sustainable and domestic source of activated, amorphous, graphitic, and nanostructured carbon for many industrial applications as the structure can be tuned through processing conditions. However, the inherent variability of lignin and its complex physicochemical structure resulting from feedstock and pulping selection make the Process‐Structure‐Property‐Performance (PSPP) relationships hard to define. In this work, radial distribution functions (RDFs) from synchrotron X‐ray and neutron scattering of lignin‐based carbon composites (LBCCs) are investigated using the Hierarchical Decomposition of the Radial Distribution Function (HDRDF) modelling method to characterize the local atomic environment and develop quantitative PSPP relationships. PSPP relationships for LBCCs defined by this work include crystallite size dependence on lignin feedstock as well as increasing crystalline volume fraction, nanoscale composite density, and crystallite size with increasing reduction temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design and characterization of hierarchical aluminosilicate composite materials for Cs entrapment: Adsorption efficiency tied to microstructure

The growing quantity of nuclear waste and the serious threats to the environment challenge researchers to innovate and target new waste form technologies. In the past decades, considerable efforts have been devoted to developing highly selective sorbents followed by safe disposal with the assurance of chemical stability and robust retention performance. Zeolite-containing geopolymers are regarded as a possible 2-in-1 material able to both capture and sequester elements such as Cs in bed fixed column application perspective. Here, these composites show promise for combining extraction properties of zeolite powder due to its crystalline structure (high capacity and selective adsorption), with the tunable microstructure and the shaping feasibility of the geopolymer binder. For the development of materials devoted to Cs immobilization, porous zeolite/geopolymer composites were prepared by dispersing NaY zeolite particles in a geopolymer binder. The influence of the structural properties of such composites on their ability to entrap a large amount of Cs by an ionic exchange process was notably studied. Composites' compositions, porosities, morphologies and crystallinity were analyzed by scanning electron microscopy coupled with energy dispersive x-ray spectroscopy (SEM-EDX), x-ray diffraction analysis (XRD) and nitrogen adsorption/desorption studies. Experimental Cs sorption in batch mode was used to follow the ionic exchange phenomenon in these materials. Along with 5 wt% amount of zeolite in geopolymer improves the Cs adsorption performance offering multiple new adsorption sites. Additionally, the geopolymer mesopores are beneficial facilitating the access of Cs and its role as a binder is advantageous to tailor granular hierarchical structure for safer industrial application.

36 MATERIALS SCIENCE↗