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At least 775 records · Page 43

Protein Assembly by Design

Proteins are nature’s primary building blocks for the construction of sophisticated molecular machines and dynamic materials, ranging from protein complexes such as photosystem II and nitrogenase that drive biogeochemical cycles to cytoskeletal assemblies and muscle fibers for motion. Such natural systems have inspired extensive efforts in the rational design of artificial protein assemblies in the last two decades. As molecular building blocks, proteins are highly complex, in terms of both their three-dimensional structures and chemical compositions. To enable control over the self-assembly of such complex molecules, scientists have devised many creative strategies by combining tools and principles of experimental and computational biophysics, supramolecular chemistry, inorganic chemistry, materials science, and polymer chemistry, among others. Owing to these innovative strategies, what started as a purely structure-building exercise two decades ago has, in short order, led to artificial protein assemblies with unprecedented structures and functions and protein-based materials with unusual properties. Furthermore, our goal in this review is to give an overview of this exciting and highly interdisciplinary area of research, first outlining the design strategies and tools that have been devised for controlling protein self-assembly, then describing the diverse structures of artificial protein assemblies, and finally highlighting the emergent properties and functions of these assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterizing The Internal Morphology of Transition Regions in Large-Scale Extrusion Deposition Additive Manufacturing

A dual-hopper feed system that was developed for the Big Area Additive Manufacturing (BAAM) system allows for transitioning between different materials while maintaining continuous deposition. This technique creates a step-change in material feedstock by switching the pellet feeding system to alternate which hopper is currently supplying material, allowing for multi-material construction. The step-change in feedstock material produces a transition region that is characterized by a compositional gradient and blended internal morphology. Initial cross-sectional imaging of the transition region revealed a non-homogenous blend of materials with distinct domains of each material, likely due to incomplete mixing within the screw. This study used a carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS) and an unfilled ABS to characterize the internal structure and to correlate it to mechanical performance by tracking microhardness across cross-sections of the transition region.

Brackett, James↗

Modeling Single and Two-Phase Transport in Thin Porous Layers Using a Composite Continuum-Pore Network Formulation

In this work, a composite continuum-pore network formulation is presented to model single and two-phase transport thin porous layers, such as gas diffusion layers in polymer electrolyte fuel cells (PEFCs) and active electrodes in redox flow batteries (RFBs). The formulation can be integrated into CFD codes, thus combining the ease of implementation of continuum-based modeling and the computational power of pore-network modeling. The composite model includes a control volume (CV) mesh at the layer scale, which embeds a cubic pore network [1,2]. The pore-network model is used to determine analytically local anisotropic effective transport properties (local effective diffusivity and permeability), which are mapped onto the CV mesh to simulate transport in the porous transport layer [3,4]. Good agreement is found between the predicted global effective transport properties (global effective diffusivity and permeability) under dry and wet conditions and previous experimental data reported in the literature for Toray TGP-H series carbon paper. Water saturation distributions are also compared with results obtained using X-ray computed tomography [4]. [1] P.A. García-Salaberri, I.V. Zenyuk, J.T. Gostick, A.Z. Weber, Modeling Gas Diffusion Layer in Polymer Electrolyte Fuel Cells Using a Continuum-Based Pore-Network Formulation, ECS Trans. 97 (2020) 615. [2] P.A. García-Salaberri, Modeling diffusion and convection in thin porous transport layers using a composite continuum-network model: Application to gas diffusion layers in polymer electrolyte fuel cells, Int J. Heat Mass Transf. (2020), submitted. [3] P.A. García-Salaberri, J.T. Gostick, G. Hwang, A.Z. Weber, M. Vera, Effective diffusivity in partially-saturated carbon-fiber gas diffusion layers: Effect of local saturation and application to macroscopic continuum models, J. Power Sources 296 (2015) 440–453. [4] P.A. García-Salaberri, G. Hwang, M. Vera, A.Z. Weber, J.T. Gostick, Effective diffusivity in partially-saturated carbon-fiber gas diffusion layers: Effect of through-plane saturation distribution, Int. J. Heat Mass Transf. 86 (2015) 319–333.

Garcia-Salaberri, Pablo↗

The Role of Titania Surface Coating by Atomic Layer Deposition in Improving Osteogenic Differentiation and Hard Tissue Formation of Dental Pulp Stem Cells

Recent studies have focused on modifying implant surface properties to improve bone regeneration and osseointegration. Herein, the role of titania surface coating in enabling dental pulp stem cells (DPSCs) differentiation and hard tissue formation is studied. Atomic layer deposition is applied at lower temperature to coat a nanolayer of titania onto hard and soft polybutadiene substrates without altering their moduli, to probe the effects of surface chemistry and substrate modulus. In the absence of titania, DPSCs prefer to attach and proliferate on the hard substrate, where particle-like biomineralization is present after 28 days in culture, whereas no biomineralization is observed on the soft substrate. Applying titania surface coating results in the improvement of adhesion and proliferation, regardless of substrate modulus, whereas cell and substrate moduli remain the same as control without titania coating. Furthermore, templated biomineralization is observed given the bone-like tissue composition by Raman analysis, in consistent with real time-polymerase chain reaction (RT-PCR) results showing upregulation of osteopontin (OPN) and bone sialoprotein (BSP), representing osteogenic differentiation. Furthermore, the results indicate that titania surface coating improved the ability to nucleate banded collagen fibers which in turn templated mineral deposits, and further induced the osteogenesis of DPSCs, regardless of its substrate modulus.

36 MATERIALS SCIENCE↗

W-induced morphological modification of NiFe layered double hydroxides as efficient electrocatalysts for overall water splitting

Layered double hydroxides (LDHs) are one of the most efficient electrocatalysts for water splitting due to their nanosheet features and compositional flexibilities. This work explored the impact of W precursor concentration (0 ~ 10 mM) on LDH morphologies and performance in hydrogen production. Using an electrodeposition W-doping process, W-induced NiFe LDHs (NiFeW-LDHs) were in-situ grown on carbon fiber papers for water splitting. A performance peak was found at a W doping of 5 mM with well-aligned nanosheets, which not only boosted the charge transfer ability and gas evolution but also offered more than a four-fold electrochemical surface area increase compared to film-like NiFe hydroxides. The NiFeW-LDHs exhibited remarkable performance compared to NiFe hydroxides, showing decreased overpotentials of 31 mV and 114 mV for the oxygen evolution reactions (OERs) and hydrogen evolution reactions (HERs) at 10 mA/cm 2 and -10 mA/cm 2 , respectively, in alkaline media. The performance enhancement at 5 mM W-doping was linked to the well-aligned NiFeW-LDH nanosheets; smaller, less-textured nanosheets were observed with lower or higher W precursor concentrations (2.5 mM or >7.5 mM), leading to inferior OER and HER performances. Hence, an appropriate W doping is crucial to generating the morphologies that contribute to the higher performance of NiFeW-LDHs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A low-cost sulfate-based all iron redox flow battery

Redox flow batteries (RFBs) are promising choices for stationary electric energy storage. Nevertheless, commercialization is impeded by high-cost electrolyte and membrane materials. Here, we report a low-cost all-iron RFB that features inexpensive FeSO 4 electrolytes, microporous membrane along with a glass fiber separator. The addition of 0.1 м 1-ethyl-3-methylimidazolium chloride (EMIC) overcomes the low solubility of FeSO 4 in water which is raised to 2.2 м. DFT calculations demonstrate that EMI + can strengthen the interaction between sulfate anions and water molecules. This electrolyte composition also allows both anode and cathode reactions to operate without actively maintaining a pH gradient between them, thus eliminating the need for expensive ion exchange membranes. The all-iron RFB demonstrates stable operation at a current density of 20 mA cm –2 for more than 800 cycles via a simple, periodic regeneration process. Furthermore, the system cost of FeSO 4 /EMIC RFBs is projected to be $ 50 per kWh due to its low-cost active materials and the inexpensive microporous membrane. Finally, this low-cost, high-concentration all-iron RFB is a promising stationary energy–storage system for storing renewable energy.

25 ENERGY STORAGE↗

Nonequilibrium spherulitic magnetite in the Ryugu samples

Here, we have investigated several particles collected during each of two touchdowns of the Hayabusa2 spacecraft at the surface of the C-type asteroid 162173 Ryugu using various electron microscope techniques. Our detailed transmission electron microscopy study shows the presence of magnetite with various morphologies coexisting in close proximity. This is characteristic of CI chondrite-like materials and consistent with the mineral assemblages and compositions in the Ryugu parent body. We describe the microstructural characteristics of magnetite with different morphologies, which could have resulted from the chemical conditions (growth vs. diffusion rate) during their formation. Furthermore, we describe the presence of magnetites with a spherulitic structure composed of individual radiating fibers that are characterized by pervasive, homogeneously distributed euhedral to subhedral pores that have not been described in previous chondrite studies. This particular spherulitic structure is consistent with crystallization under nonequilibrium conditions. Additionally, the presence of a high density of defects within the magnetite fibers, the high surface/volume ratio of this morphology, and the presence of amorphous materials in several pores and at the edges of the acicular fibers further support their formation under nonequilibrium conditions. We suggest that the growth processes that lead to this structure result from the solution reaching a supersaturated state, resulting in an adjustment to a lower free energy condition via nucleation and rapid growth.

58 GEOSCIENCES↗

Designing 1D multiheme peptide amphiphile assemblies reminiscent of natural systems

We discuss protein assemblies that bind and organize ordered arrays of cofactors yield function structures. Multiheme assemblies found in nature yield electronically conductivity 1D nanoscale fibers and are employed in anaerobic respiration. To understand the fundamental characteristics of these organized arrays, the design of peptide amphiphiles that assemble into 1D nanostructures and yield metalloporphyrin binding sites is presented. One challenge with this class of peptide amphiphiles is identifying the correct sequence composition for high affinity binding with high heme density. Here, the peptide c16-AH(Kx)n-CO 2 H is explored to identify the impact of sequence length (n) and amino acid identity (x = L, I, or F) on binding affinity and midpoint potential. When n = 2, the peptide assembly yields the greatest affinity. The resulting nanoscale assemblies yield ordered arrays of the redox active molecule heme and have potential utility in the development of supramolecular bioelectronic materials useful in sensing as well as the development of enzymatic materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Effects of feruloyl-CoA 6'-hydroxylase 1 overexpression on lignin and cell wall characteristics in transgenic hybrid aspen

In plant cell walls, lignin, cellulose, and the hemicelluloses form intricate three-dimensional structures. Owing to its complexity, lignin often acts as a bottleneck for the efficient utilization of polysaccharide components as biochemicals and functional materials. A promising approach to mitigate and/or overcome lignin recalcitrance is the qualitative and quantitative modification of lignin by genetic engineering. Feruloyl-CoA 6'-hydroxylase (F6'H1) is a 2-oxoglutarate-dependent dioxygenase that catalyzes the conversion of feruloyl-CoA, one of the intermediates of the lignin biosynthetic pathway, into 6'-hydroxyferuloyl-CoA, the precursor of scopoletin (7-hydroxy-6-methoxycoumarin). In a previous study with Arabidopsis thaliana, we demonstrated that overexpression of F6'H1 under a xylem-preferential promoter led to scopoletin incorporation into the cell wall. This altered the chemical structure of lignin without affecting lignin content or saccharification efficiency. In the present study, the same F6'H1 construct was introduced into hybrid aspen (Populus tremula × tremuloides T89), a model woody plant, and its effects on plant morphology, lignin chemical structure, global gene expression, and phenolic metabolism were examined. The transgenic plants successfully overproduced scopoletin while exhibiting severe growth retardation, a phenotype not previously observed in Arabidopsis. Scopoletin accumulation was most pronounced in the secondary walls of tracheary elements and the compound middle lamella, with low levels in the fiber cell walls. Overexpression of F6'H1 also affected the metabolism of aromatics, including lignin precursors. Heteronuclear single-quantum coherence (HSQC) NMR spectroscopy revealed that scopoletin in cell walls was bound to lignin, leading to a reduction in lignin content and changes in its monomeric composition and molar mass distribution. Furthermore, the enzymatic saccharification efficiency of the transgenic cell walls was more than three times higher than that of the wild-type plants, even without pretreatment. Although addressing growth inhibition remains a priority, incorporating scopoletin into lignin demonstrates significant potential for improving woody biomass utilization.

59 BASIC BIOLOGICAL SCIENCES↗

Multi deep learning-based stochastic microstructure reconstruction and high-fidelity micromechanics simulation of time-dependent ceramic matrix composite response

A multi deep learning-based framework is developed for efficient, automated microstructure reconstruction and generation of stochastic representative volume elements (SRVEs) with periodic boundary conditions (PBCs) for accurate modeling of ceramic matrix composite (CMC) response. The methodology comprises a convolutional neural network coupled with regression layers to act as a vanilla regression network for semantic segmentation of the microstructure, allowing accurate characterization of the phases and their distributions at the microscale. Scanning electron microscope and confocal microscope are used to obtain C/SiNC and SiC/SiNC CMCs micrographs for vanilla regression testing. Microstructure variability in terms of fiber volume fraction and porosity are quantified through the output regression layer, ensuring accurate representation of material variability in SRVE construction. Generative adversarial network (GAN) and its variants are designed to produce high-fidelity SRVE, spanning CMCs microstructure variability space. A circular padding algorithm is developed to generate SRVEs with PBCs during training of GANs. The accuracy of the generated SRVEs is established through micromechanics simulations, where an efficient formulation of the high-fidelity generalized methods of cells (HFGMC) approach is used to compute the effective mechanical properties. Furthermore, an iterative algorithm is implemented in the HFGMC solver to simulate time-dependent deformation of SiC/SiNC subjected to creep loading conditions.

36 MATERIALS SCIENCE↗

Fulcrum House – Towards a Sustainable Composite Architecture

In the last decades, the accessibility to digital fabrication technologies positioned composites as an affordable, structurally efficient and low-maintenance alternative to traditional mineral-based and high-energy materials. Of special interest are carbon nanotubes (CNT) and carbon foam (CFoam) from methane and coal pyrolysis respectively, as an environmentally friendly substitute to glass and carbon fiber. This paper presents the design of a principled single-family house, as a first case study to identify the constraints of such a material system, including technology gap, techno-economic and life cycle assessment, as well as building code requirements. In turn, the investigation proposes a suitable design-to-fabrication workflow, which potentially could bring CNT and CFoam materials to the construction of buildings.

01 COAL, LIGNITE, AND PEAT↗

Carbon fiber synthesis from pitch: Insights from ReaxFF based molecular dynamics simulations

Despite the potential to lowering fabrication costs of pitch-based carbon fiber (CF) compared to polyacrylonitrile-based CF, large scale utilization is currently limited by the complexity in manufacturing. This is mainly due to the lack of consistency between the pitch structure/chemistry and CF properties under different processing conditions. Here, we employed full atomistic simulations based on reactive force fields to investigate the conversion of pitch precursors to CFs. Additionally, it was found that at the carbonization stage, the consumption rates of precursors, gas formations, and solid yields (carbonized CFs) are all dependent on the composition and arrangement of molecular moieties in the precursor. Specifically, precursors with sp 3 carbons in the cata-condensed core area have limited decomposition pathways (i.e., limited reaction sites), which leads to the formation of carbonized CFs with similar compositions. Furthermore, carbonized CFs possess distinct structural characteristics, and finally lead to the formation of CFs with different moduli. By analyzing CF crystallinity and elemental composition, general rationales are proposed for the selection of optimal precursors and processing conditions, and thus shed lights on parameter screening during industrial CF synthesis. For instance, inclusion of sp 3 carbons in cata- condensed rings can be preferred over the presence of sp 3 carbons on side chains.

01 COAL, LIGNITE, AND PEAT↗

Composite energy-absorbing assembly

An energy-absorbing assembly includes a housing and a plurality of discrete energy-absorbing elements. The housing includes a first wall and a second wall. The first wall and the second wall are spaced apart from one another to at least partially define an interior compartment. Each element of the plurality of energy-absorbing elements includes a polymer and a plurality of reinforcing fibers. The plurality of energy-absorbing elements is at least partially disposed within the interior compartment and fixed to the housing. Each energy-absorbing element of the plurality of energy-absorbing elements includes an elongated hollow structure extending between a first end and a second end. Each elongated hollow structure defines a longitudinal axis extending nonparallel to at least one of the first wall and the second wall. In various alternative aspects, each energy-absorbing element may include a transverse wall.

Rodgers, William R.↗

Phase-Field Modeling of Damage Evolution in Ceramic Matrix Composite (CMC) and Environmental Barrier Coating (EBC)

Ceramic matrix composites (CMCs) protected by environmental barrier coatings (EBCs) present a promising materials solution for next generation gas turbines. Developments of more robust and efficient EBCs and mechanically tougher CMCs are thus of significant technological importance. Here we develop a phase-field modeling framework that incorporates the thermally grown oxide (TGO), recognized as a critical factor for degradation and failure of EBCs. We simulate crack growth in the TGO and the potential extension into the bond coat / CMC substrate. The model efficiently takes account of the large inelastic deformation induced by the severe volume expansion of TGO, thanks to our recently developed, so-called incremental realization of inelastic deformation (IRID) algorithm. A phase-field model is built for damage evolution in CMCs including crack growth and interfacial sliding. The effects of fiber layout and interfacial sliding on the macroscopic toughness of CMCs are revealed by large-scale simulations and compared to experiments.

advanced energy systems and materials↗

The Impact of Carbonation Curing on the Fatigue Behavior of Polyvinyl Alcohol Engineered Cementitious Composites (PVA-ECC)

Use of Engineered Cementitious Composites (ECC) has been proven to enhance structural fatigue resistance and reduce the use-phase emissions for transportation infrastructure. Carbonation curing offers an opportunity to reduce the embodied carbon of ECC via direct CO 2 sequestration. In this study, the impact of carbonation curing on ECC’s fatigue resistance was examined. ECC’s CO 2 uptake, static flexural behavior, flexural fatigue performance, and single fiber pull-out behavior were studied experimentally. Midspan deflection up to 3 million cycles under fatigue load, fatigue stress-life relationship, and failure mechanism for carbonation-cured and air-cured ECC were investigated. Carbonation curing was found to significantly improved the fatigue life of ECC and lowered the midspan deflection under the same stress. Further, CO 2 -cured ECC can achieve >20% CO 2 uptake per cement mass after 24-hour carbonation curing. Carbonation curing increased ECC’s flexural strength by 32% and promoted crack width control capability, with maximum post-fatigue crack width reduced from 148 μm to 76 μm. As a result, the positive impact of carbonation curing on the fatigue behavior of ECC simultaneously lowers the embodied and operational carbon of ECC structural members subjected to fatigue loading during service.

36 MATERIALS SCIENCE↗

Probabilistic modeling and prediction of out-of-plane unidirectional composite lamina properties

Computational simulation provides an efficient means to predict the behavior of customized hybrid material configurations using validated, physics-based models. One limitation to this approach is the quality and quantity of available data to characterize the many constituent input properties. Therefore, a systematic approach to identify the most influential parameters on the hybrid behavior and quantify the corresponding uncertainty in predictive capabilities is required. Here, an approach using Bayesian multimodel inference and imprecise global sensitivity analysis is presented to investigate the effects of sparse constituent data on the prediction of composite material properties. The methodology allows the identification, using quantified uncertainties, of the most influential constituent material parameters for specified homogenized properties. This sensitivity analysis further enables a dimension reduction when assessing the influence of uncertainties on material properties and can be used to inform testing programs of the constituent properties that require additional testing/data collection in order to minimize uncertainty in macro-scale composite properties. The methodology is specifically demonstrated on the prediction and sensitivity analysis of out-of-plane mechanical properties of a unidirectional lamina.

36 MATERIALS SCIENCE↗

Remaining Useful Strength (RUS) Prediction of SiCf-SiCm Composite Materials Using Deep Learning and Acoustic Emission

Prognosis techniques for prediction of remaining useful life (RUL) are of crucial importance to the management of complex systems for they can lead to appropriate maintenance interventions and improvements in reliability. While various data-driven methods have been introduced to predict the remaining useful life (RUL) of machinery systems or batteries, no research has been reported on the remaining useful strength (RUS) prediction of silicon carbide fiber reinforced silicon carbide matrix (SiCf-SiCm) materials with pivotal role in its potential usage as a structural material in nuclear reactors and turbine engines. Knowledge of its degradation process is of the utmost importance to the manufacturers. For this purpose, two approaches based on the machine-learning techniques of random-forest (RF) and convolutional neural network (CNN) are proposed to predict the RUS of SiCf-SiCm using only acoustic emission (AE) signals generated during the material’s stress applying process. Experimental results show that the CNN models achieved better predictive performance than the RF models but the latter with expert-engineered features achieves better prediction for AE signals in the early stage of degradation. Additionally, our results demonstrate that both models can correctly predict the SiCf-SiCm RUS as evaluated by our robust testing method from which the best average root mean square error (RMSE) and Pearson correlation coefficient of 3.55 ksi units and 0.85 were obtained.

36 MATERIALS SCIENCE↗

Single-Cell Metabolomics with Rapid Determination of Chemical Formulas from Isotopic Fine Structures

Metabolomic measurements can provide functional readouts of cellular states and phenotypes. Here, we present a protocol for single-cell metabolomics that permits direct untargeted detection of a broad number of metabolites under ambient conditions, without the need for sample processing, and with high confidence in the discovery and identification of the molecular formulas for detected metabolites. This protocol describes combining fiber-based laser ablation electrospray ionization (f-LAESI) with a 21 Tesla Fourier transform ion cyclotron resonance mass spectrometer (21T-FTICR-MS) to obtain high confidence molecular formula information about detected metabolites. The f-LAESI source utilizes mid-infrared laser ablation through a sharp optical fiber tip, affording direct ambient analysis of cells without the need for sample processing. Using the 21T-FTICR-MS as a mass analyzer enabled measurement of the isotopic fine structure (IFS) for numerous metabolites simultaneously from single cells, and the IFSs were in turn computationally processed to rapidly determine the corresponding elemental compositions. This metabolomics technique complements other single cell omics measurement methods, helping to resolve complex molecular interactions that take place within cells unattainable from single cell transcriptomic and proteomics methods.

mass spectrometry, FTICR, FTMS, ultrahigh mass res↗