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At least 199 records · Page 11

Multilayered Ordered Protein Arrays Self-Assembled from a Mixed Population of Virus-like Particles

Biology shows many examples of spatially controlled assembly of cells and biomacromolecules into hierarchically organized structures, to which many of the complex biological functions are attributed. While such biological structures have inspired the design of synthetic materials, it is still a great challenge to control the spatial arrangement of individual building blocks when assembling multiple types of components into bulk materials. Here, in this study, we report self-assembly of multilayered, ordered protein arrays from mixed populations of virus-like particles (VLPs). We systematically tuned the magnitude of the surface charge of the VLPs via mutagenesis to prepare four different types of VLPs for mixing. A mixture of up to four types of VLPs selectively assembled into higher-order structures in the presence of oppositely charged dendrimers during a gradual lowering of the ionic strength of the solution. The assembly resulted in the formation of three-dimensional ordered VLP arrays with up to four distinct layers including a central core, with each layer comprising a single type of VLP. A coarse-grained computational model was developed and simulated using molecular dynamics to probe the formation of the multilayered, core-shell structure. Our findings establish a simple and versatile bottom-up strategy to synthesize multilayered, ordered materials by controlling the spatial arrangement of multiple types of nanoscale building blocks in a one-pot fabrication.

59 BASIC BIOLOGICAL SCIENCES↗

Carbon aerogels with integrated engineered macroporous architectures for improved mass transport

Carbon aerogels (CAs) combine unique properties including ultra-high surface area, high electrical conductivity, corrosion resistance, and robust mechanical properties making them ideal materials for electrochemical applications. Traditional CA synthesis results in isotropic, random nanoporous networks that work well for applications relying on diffusional mass transport. However, many applications would benefit from integration of engineered macroporous network structures that enable directed pressure-gradient-driven mass transport. In this study, we report on using 3D-printed sacrificial polymeric templates to generate templated CAs (t-CAs) with integrated engineered nonrandom macroporous network structures. Specifically, we used projection micro-stereo-lithography (PμSL) and two-photon polymerization direct laser writing (2PP-DLW) to fabricate millimeter-to-centimeter-sized 3D sacrificial polymeric templates with features ranging from tens of microns (PμSL) to 100s of nanometers (2PP-DLW). T-CAs were fabricated by infiltrating the templates with resorcinol-formaldehyde (RF) precursor solution, followed by carbonization at 1050 °C to simultaneously convert the RF gel to a CA and decompose the 3D-printed template, leaving an embedded templated macroporous network structure behind. X-ray computer tomography confirms integration of the macroporous architecture defined by the template. The templated macroporous architecture improves mass transport in t-CAs compared to traditional bulk CA as demonstrated by more uniform activation and their response in electrochemical cyclic voltammetry and galvanostatic charge-discharge tests.

36 MATERIALS SCIENCE↗

Lone-Electron-Pair Micelles Strengthen Bond Anharmonicity in MnPb16Sb14S38 Complex Sulfosalt Leading to Ultra-Low Thermal Conductivity

Designing crystalline solids in which intrinsic extremely low lattice thermal conductivity mainly arises from its unique bonding nature rather than structure complexity and/or atomic disorder could promote thermal energy manipulation and utilization for applications ranging from thermoelectric energy conversion to thermal barrier coatings. Here, we report an extremely low lattice thermal conductivity of ~0.34 W m-1 K-1 at 300 K in the new complex sulfosalt MnPb16Sb14S38. We attribute the ultra-low lattice thermal conductivity to a synergistic combination of scattering mechanisms involving (1) strong bond anharmonicity in various structural building units, owing to the presence of stereoactive lone-electron-pair (LEP) micelles, and (2) phonon scattering at the interfaces between building units of increasing size and complexity. Remarkably, low-temperature heat capacity measurement revealed a Cp value of 0.206 J g-1 K-1 at T > 300 K, which is 22% lower than the Dulong-Petit value (0.274 J g-1 K-1). Further analysis of the Cp data and sound velocity (ν = 1834 m/s) measurement yielded Debye temperature values of 161 K and 187 K, respectively. Here, the resulting Grüneisen parameter, γ = 1.65, further supports strong bond anharmonicity as the dominant mechanism responsible for the observed extremely low lattice thermal conductivity.

36 MATERIALS SCIENCE↗

Fibrous anisotropy and mineral gradients within the radula stylus of chiton: Controlled stiffness and damage tolerance in a flexible biological composite

Over hundreds of millions of years, organisms have evolved architected structures via precise control over hierarchically assembled components, including the integration of dissimilar materials. One such example is found in the radula system of chitons, intertidal mollusks that feed on algae growing on the rock. Their radula consists of multiple rows of ultrahard teeth, each integrated with a foldable belt-like substrate via a stiff, yet flexible stylus, which is essential for efficient rasping during the feeding process. Here, we investigate the nano and micro-scale components and architectures as well as regional mechanical properties of the stylus, and their subsequent role during the rasping of Cryptochiton stelleri. Three important factors were determined to contribute to the regio-specific stiffness of the stylus: the presence of mineral components, highly oriented chitinous fibers, and a chemically cross-linked protein matrix. All these factors are varied throughout the stylus. There is a high mineral content on the trailing edge close to the tooth and a cross-linked matrix on the leading edge, both with orientational specific oriented chitin fibers that provide force transduction to the tooth. Conversely, there is a significant lack of mineral or cross-linked matrix in the proximal end as well as a low degree of fiber orientation, resulting in a flexible region that can accommodate torsion and flexure during rasping. Understanding the graded composite structure of the stylus and applying this unique design to various engineering fields such as soft robotics, biotechnology, and the medical industry, can inspire the production of high-performance materials.

Lee, Jung-Eun↗

High-Resolution, Lightweight, and Low-cost X-Ray Optics for the Lynx Observatory

We describe an approach to build an x-ray mirror assembly that can meet Lynx’s requirements of high-angular resolution, large effective area, light weight, short production schedule, and low-production cost. Adopting a modular hierarchy, the assembly is composed of 37,492 mirror segments, each of which measures ∼100 mm × 100 mm × 0.5 mm. These segments are integrated into 611 modules, which are individually tested and qualified to meet both science performance and spaceflight environment requirements before they in turn are integrated into 12 metashells. The 12 metashells are then integrated to form the mirror assembly. This approach combines the latest precision polishing technology and the monocrystalline silicon material to fabricate the thin and lightweight mirror segments. Because of the use of commercially available equipment and material and because of its highly modular and hierarchical building-up process, this approach is highly amenable to automation and mass production to maximize production throughput and to minimize production schedule and cost. As of fall 2018, the basic elements of this approach, including substrate fabrication, coating, alignment, and bonding, have been validated by the successful building and testing of single-pair mirror modules. In the next few years, the many steps of the approach will be refined and perfected by repeatedly building and testing mirror modules containing progressively more mirror segments to fully meet science performance, spaceflight environments, as well as programmatic requirements of the Lynx mission and other proposed missions, such as AXIS.

Zhang, William W.↗

A High-Speed Rotational Diamond Anvil Cell for In Situ Analysis of Hierarchical Microstructural Evolution of Metallic Alloys during Extreme Shear Deformation

High speed shear deformation is ubiquitous in engineering applications, ranging from material processing methods such as friction stir processing/extrusion and in tribological contacts. However, analyzing the microstructural evolution of materials while they are undergoing high speed shear deformation have been a long-standing challenge. This led to predominant reliance on ex situ microscopy before and after shear deformation. But ex situ microscopy lacks the ability to analyze dynamic and transient hierarchical microstructural evolution mechanisms that could occur during shear deformation of materials. Therefore, to better understand the dynamic mechanisms of mass and energy transfer in materials under shear deformation, we developed a first of its kind high-speed rotational diamond anvil cell (HS-RDAC) for synchrotron-based in situ high-energy x-ray diffraction (XRD). We studied the time resolved lattice strain evolution, XRD peak broadening and changes in spatial variation of shear deformation induced alloying in pure metal and metal alloy sheets and powder mixture using the HS-RDAC. These in situ results were combined with detailed ex situ microstructural characterization before and after the shear deformation using transmission electron microscopy and atom probe tomography, which revealed the different stages of evolution of a shear deformation induced hierarchical nanostructure. Multiscale computational simulations including computational fluid dynamics, crystal plasticity, molecular dynamic simulation and density functional theory uncovered the mechanisms behind morphological changes, evolution of defect structures and changes in driving force for shear deformation induced intermixing. In conclusion, this in situ HS-RDAC capability, in combination with ex situ microstructural characterization and computational simulations, can provide new insights into the hierarchical microstructural evolution pathway during shear deformation.

36 MATERIALS SCIENCE↗

The living interface between synthetic biology and biomaterial design

Recent far-reaching advances in synthetic biology have yielded exciting tools for the creation of new materials. Conversely, advances in the fundamental understanding of soft-condensed matter, polymers and biomaterials offer new avenues to extend the reach of synthetic biology. The broad and exciting range of possible applications have substantial implications to address grand challenges in health, biotechnology and sustainability. Despite the potentially transformative impact that lies at the interface of synthetic biology and biomaterials, the two fields have, so far, progressed mostly separately. This Perspective provides a review of recent key advances in these two fields, and a roadmap for collaboration at the interface between the two communities. Here we highlight the near-term applications of this interface to the development of hierarchically structured biomaterials, from bioinspired building blocks to 'living' materials that sense and respond based on the reciprocal interactions between materials and embedded cells.

59 BASIC BIOLOGICAL SCIENCES↗

Hierarchical Screening for Li-Based Solid Electrolytes Using Fast, Interpretable Machine-Learned Potentials

Li-based solid-state electrolyte materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates.

Materials discovery↗

Vapor-phase pillarization of MXenes for engineering hierarchical interlayer porosity

MXenes, a family of two-dimensional (2D) multilamellar materials, possess excellent thermal and electronic properties for a range of applications. Their use in heterogeneous catalysis, however, is limited by the low surface area resulting from stacked layers. Pillarization with inorganic oxides can create more open, mesoporous MXene structures, improving accessibility for guest species to diffuse, reside or react in the space between 2D layers. A previous liquid-phase pillarization method, however, involves excessive use of solvent-based precursors and multiple processing steps. Here, we report a vapor-phase pillarization (VPP) strategy to introduce pillars, exemplified by silica pillars, with high pillar precursor usage efficiency and a simplified processing workflow. The resulting silica-pillared mesoporous MXene exhibits significantly increased surface area and porosity. These textural properties can be easily tuned by the VPP synthesis conditions. When applied as a ruthenium (Ru) catalyst support for the hydrogenolysis of low-density polyethylene (LDPE), the silica-pillared MXene enabled high Ru dispersion and catalytic activity. This study highlights the potential of the VPP method for engineering mesoporous, 2D MXene materials and demonstrates the effectiveness of mesoporous MXene as a catalyst support in overcoming mass transport and active-site accessibility challenges in heterogeneous catalysis involving bulky substances, such as plastics upcycling.

Luo, Song [University of Delaware, Newark, DE (Uni↗

Synthesis of nanograined zirconium diboride microsphere powder feedstock via emulsification of suspensions

Ceramic nanograined materials have desirable characteristics compared to their macroparticle counterparts but are rarely used in industrial applications due to issues with poor handleability and health hazards. Due to interparticle forces that become more dominant as the particle size decreases, it is difficult to use nanomaterials to fill dies, spread on surfaces, or flow through hoppers found in various manufacturing processes. In this work, we report a scalable gelcasting solution and unique emulsification process to create microspheres composed of nanoscale powders to enhance the flowability and handleability of nanomaterials. The gelcasting solution and emulsification process can be used with any nanoparticle composition that can be suspended in a liquid phase. This paper reports the effects of various parameters on zirconium diboride microsphere formation, such as surfactant content and mixing conditions. The microspheres maintain the nano-scale characteristics of the powder but improve its flowability by using cross-linked polyvinyl alcohol to combine irregularly shaped zirconium diboride nanoparticles with a particle diameter of 60 nm into larger spherical particles with a d 50 ~25 μm. This hierarchical feedstock engineering design combine the positive characteristics of materials across both length scales and improve the flowability of the feedstock from a Hausner Ratio of 1.56 to 1.19. The materials produced using this technique can be used in thermal plasma spray, die filling for hot pressing or spark plasma sintering, and binder jet printing applications.

36 MATERIALS SCIENCE↗

Designing hierarchical nanoporous membranes for highly efficient gas adsorption and storage

Nanoporous membranes with two-dimensional materials such as graphene oxide have attracted attention in volatile organic compounds (VOCs) and H 2 adsorption because of their unique molecular sieving properties and operational simplicity. However, agglomeration of graphene sheets and low efficiency remain challenging. Therefore, we designed hierarchical nanoporous membranes (HNMs), a class of nanocomposites combined with a carbon sphere and graphene oxide. Hierarchical carbon spheres, prepared following Murray’s law using chemical activation incorporating microwave heating, act as spacers and adsorbents. Hierarchical carbon spheres preclude the agglomeration of graphene oxide, while graphene oxide sheets physically disperse, ensuring structural stability. The obtained HNMs contain micropores that are dominated by a combination of ultramicropores and mesopores, resulting in high VOCs/H 2 adsorption capacity, up to 235 and 352 mg/g at 200 ppmv and 3.3 weight % (77 K and 1.2 bar), respectively. Our work substantially expands the potential for HNMs applications in the environmental and energy fields.

42 ENGINEERING↗

Uncertainty Analysis of Composite Structures

A two-phase approach and a computational procedure are presented for predicting the variability in the nonlinear response of composite structures associated with variations in the geometric and material parameters of the structure. In the first phase, hierarchical sensitivity analysis is used to identify the major parameters, which have the most effect on the response quantities of interest. In the second phase, the major parameters are taken to be fuzzy parameters, and a fuzzy set analysis is used to determine the range of variation of the response, associated with preselected variations in the major parameters. The effectiveness of the procedure is demonstrated by means of a numerical example of a cylindrical panel with four T-shaped stiffeners and a circular cutout.

Noor, Ahmed K.↗

Nonlinear Thermomechanical Response of Composite Panels with Continuous and Terminated Stiffeners

A two-phase approach and a computational procedure are used for predicting the variability of the response of stiffened composite panels associated with variations in the geometric and material parameters of the structures. In the first phase, hierarchical sensitivity analysis is used to identify the major parameters that have the most effect on the response quantities of interest. In the second phase, the major parameters are taken to be fuzzy parameters, and a fuzzy set analysis is used to determine the range of variation of the response, associated with preselected variations in the major parameters. Numerical results are presented showing the variability of the response of panels with both continuous and terminated stiffeners associated with variations in the micro mechanical and geometric parameters. Both flat and curved panels are considered.

Noor, Ahmed K.↗

Thermomechanical Modeling of Woven Materials With Particle-Based, Explicit-Fiber Simulations

Fiber-based materials are extensively used to protect spacecraft during entry. Insulative fibers, often in a fiber network or woven, provide rigidity, strength, and control of material anisotropy and density. Woven thermal protection materials, such as ADEPT (Adaptable, Deployable Entry and Placement Technology), 3D-MAT (3-Dimensional Multifunctional Ablative Thermal Protection), and 3MDCP (3D Woven Mid-Density Carbon Phenolic), enable missions with stronger and denser materials for entry profiles with high shear and heat flux. Vulnerabilities to woven thermal protection materials include manufacturing-induced material property variation, and impact from micrometeoroids. Simulating woven materials under these conditions require models that can resolve hierarchal structures, thermomechanical behavior, and failure. To address this, we simulate weave thermal conduction and mechanical deformation. We simulate the full weave with a coarse-grained yarn model is presented. The model combines a validated, high-resolution single 3MDCP yarn model and phenolic resin model. Instead of modeling every fiber, each yarn ply with order 10, instead of order 1000, fibers. The discrete element bonded particle model (DEM-BPM) of fibers captures the thermal and mechanical behavior within and between fibers. We study the proportion of heat transfer and stress via the contact network, fiber bonds, and overall weave geometry.

bonded particle↗

Deformation-enhanced hierarchical multiscale structure heterogeneity in a Pd-Si bulk metallic glass

Here, the multiscale structures in a Pd 82 Si 18 binary bulk metallic glass before and after deformation were studied using electron microscopies, high-energy synchrotron X-ray diffraction, and small-angle scattering techniques. The experimental results revealed an enhancement of hierarchical structure heterogeneities on multiple length scales after deformation. Hierarchical multiple shear bands of high number density were observed after bending, introducing complex but periodically distributed residual strain. Pair distribution function analysis revealed that the connectivity of the short-range clusters on the medium-range scale determines the packing density difference between the tension side and the compression side in the sample after bending. In-situ synchrotron X-ray diffraction study also revealed a transformation of connection modes among short-range clusters under uniaxial tension and compression, which is consistent with those of triaxial tension/compression parts upon bending in Pd 82 Si 18 glassy alloys. The nanoscale heterogeneities for metallic glasses after deformation observed by small-angle scattering and transmission electron microscopy may be attributed to the nanoscale amorphous phase separation and interacting multiple shear bands enhanced by plastic deformation. Our findings suggested that the enhancement of hierarchical heterogeneous structure on multiple length scales may explain the excellent plasticity of Pd-Si glassy alloys, deepening the understanding of structure-property relation during plastic deformation in metallic glasses.

36 MATERIALS SCIENCE↗

Sol-gel processing of a covalent organic framework for the generation of hierarchically porous monolithic adsorbents

Covalent organic frameworks (COFs) have emerged as a versatile material platform for such applications as chemical separations, chemical reaction engineering, and energy storage. Their inherently low mechanical stability, however, frequently renders existing methods of pelletization ineffective, contributing to pore collapse, pore blockage, or insufficient densification of crystallites. Here, we present a process for the shaping and densifying of COFs into robust centimeter-scale porous monoliths without the need for templates, additives, or binders. This process minimizes mechanical damage from shear-induced plastic deformation and further provides a network of interparticle mesopores that we exploit in accessing analyte capacities above those achievable from the intrinsic COF structure. Using a lattice-gas model, we accurately capture the monolithic structure across the mesoporous range and tie pore architecture to performance in both gas-storage and -separation applications. Collectively, these results represent a substantial step in the practical applicability of COFs and other mechanically weak porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hierarchical microstructure of Yb-filled skutterudites through ultrasonically atomized spherical powders for enhanced thermoelectric performance

Hierarchical microstructures are widely explored as a strategy to reduce lattice thermal conductivity in thermoelectric materials while preserving favorable electronic transport. Here we demonstrate that ultrasonic atomization of precursor powders provides an intrinsic pathway to generate such architectures in n-type Yb0.3Co4Sb12 skutterudites. Materials were synthesized by both conventional sealed-ampoule and ultrasonic atomization routes, each yielding essentially single-phase skutterudite after densification. However, the atomized spherical powders undergo a distinct reaction-driven microstructural evolution during thermal treatment prior to densification. Electron microscopy reveals that the skutterudite phase within the particles induces swelling, cracking, and fragmentation of the droplets before consolidation. Multimodal structural and microstructural characterizations show that densification of these fragmented powders produces a hierarchical microstructure consisting of submicron grains, micrometer-scale faceted crystallites, and powder-derived domains separated by oxide-decorated boundaries. Comprehensive thermoelectric transport measurements evidence that this multiscale architecture lowers the lattice thermal conductivity while maintaining favorable electronic transport, leading to an average ~10% enhancement in the thermoelectric figure of merit. Complementary 121Sb Mössbauer spectroscopy further indicates lattice softening in the atomized material. These results demonstrate that ultrasonic atomization provides an effective route to engineer hierarchical microstructures in skutterudite thermoelectrics and offers a promising strategy for tailoring thermal transport in energy-conversion materials.

Bouteiller, Hugo [ORNL] (ORCID:0009000421322962)↗

Accurate and uncertainty-aware multi-task prediction of HEA properties using prior-guided deep Gaussian processes

Surrogate modeling techniques have become indispensable in accelerating the discovery and optimization of high-entropy alloys (HEAs), especially when integrating computational predictions with sparse experimental observations. This study systematically evaluates the training and testing performance of four prominent surrogate models—conventional Gaussian processes (cGP), Deep Gaussian processes (DGP), encoder-decoder neural networks for multi-output regression and eXtreme Gradient Boosting (XGBoost)—applied to a hybrid dataset of experimental and computational properties of the 8-component HEA system Al-Co-Cr-Cu-Fe-Mn-Ni-V. We specifically assess their capabilities in predicting correlated material properties, including yield strength, hardness, modulus, ultimate tensile strength, elongation, and average hardness under dynamic/quasi-static conditions, alongside auxiliary computational properties. The comparison highlights the strengths of hierarchical deep modeling approaches in handling heteroscedastic, heterotopic, and incomplete data commonly encountered in materials science. Our findings illustrate that combined surrogate models such as DGPs infused with machine-learned priors outperform other surrogates by effectively capturing inter-property correlations and by assimilating prior knowledge. This enhanced predictive accuracy positions the combined surrogate models as powerful tools for robust and data-efficient materials design.

36 MATERIALS SCIENCE↗