Investigation of mechanical and frictional performance for bismaleimide composites reinforced by hyperbranched polysiloxane-cyclophosphazene functionalized rGO/MoS2
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Chen, Zhengyan (ORCID:0000000278866651)↗
SEARCH · Engineering Papers
Results for “composition and function”
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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Hierarchical Ion Interactions in the Direct Air Capture of CO 2 at Air/Aqueous Interfaces
The direct air capture (DAC) of CO 2 using aqueous solvents is plagued by slow kinetics and interfacial barriers that limit effectiveness in combating climate change. Functionalizing air/aqueous surfaces with charged amphiphiles shows promise in accelerating DAC; however, insight into these interfaces and how they evolve in time remains poorly understood. Specifically, competitive ion interactions between DAC reagents and reaction products feedback onto the interfacial structure, thereby modulating interfacial chemical composition and overall function. In this work, we probe the role of glycine amino acid anions (Gly - ), an effective CO 2 capture reagent, that promotes the organization of cationic oligomers at air/aqueous interfaces. These surfaces are probed with vibrational sum frequency generation spectroscopy and molecular dynamics simulations. Our findings demonstrate that the competition for surface sites between Gly - and captured carbonaceous anions (HCO 3 - , CO 3 2 -, carbamates) drives changes in surface hydration, which in turn tunes oligomer ordering. This phenomenon is related to a hierarchical ordering of anions at the surface that are electrostatically attracted to the surface and their ability to compete for interfacial water. These results point to new ways to tune interfaces for DAC via stratification of ions based on relative surface propensities and specific ion effects.
54 ENVIRONMENTAL SCIENCES↗
Coupled cluster spectroscopic properties of the coinage metal nitrosyls, M–NO (M = Cu, Ag, Au)
Ab initio near-equilibrium potential energy and dipole moment surfaces for the bent CuNO, AgNO, and AuNO molecules have been calculated under the Feller-Peterson-Dixon (FPD) composite framework at the coupled cluster level of theory including complete basis set extrapolation, outer-core correlation, scalar relativistic effects, and spin-orbit coupling. The Brueckner coupled cluster doubles with perturbative triples method, BCCD(T), was used to greatly improve upon CCSD(T), which was particularly problematic for CuNO. In the latter case the BCCD(T) vibrational frequencies showed significant differences compared to CCSD(T), e.g., nearly 65 cm -1 for the NO stretching frequency, and BCCD(T) also resulted in much better agreement with the available experimental frequencies. A full range of ro-vibrational spectroscopic constants are given for all three molecules of this study using the accurate composite potential energy functions and employing 2nd-order vibrational perturbation theory.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'
This package archives the core data used for analysis and inference in 'Abiotic influences on continuous conifer forest structure across a subalpine watershed' (Worsham et al., 2025). All data were collected in the East River, Washington Gulch, Slate River, and Coal Creek watersheds of Colorado. In the paper, we quantified the relative influence of climate, topographic, edaphic, and geologic factors on conifer stand structure and composition, and their functional relationships, at the watershed scale. We used waveform LiDAR data to derive spatially continuous stand structure metrics. We fused these with a species-level classification map to estimate tree species abundance. We applied generalized additive and generalized boosted models to evaluate the covariability of structural and compositional metrics with abiotic variables. The package contains the essential products required for reproducing our analysis and the tables and figures reported in the publication. The products comprise four classes: (1) geospatial data, (2) tabular data used for inferential analysis, (3) tabular data describing analytical results and performance statistics, and (4) a data user guide. (1) includes discretized waveform LiDAR data, locations and attributes of individual tree crowns, sampling locations and domain boundaries, a canopy height model, and raster files of estimated forest structural and compositional metrics at 100 m grid scale. (2) includes all response and explanatory variable values applied in inferential models. Response variables include conifer forest stand density, basal area, 95th percentile height, quadratic mean diameter, and others. Explanatory variables include climatic water deficit, actual evapotranspiration, elevation, heat load, soil available water content, and others. (3) includes results of training and testing several individual tree detection (ITD) algorithms, as well as inferential modeling results. (4) is a PDF user guide for this data package, including detailed descriptions and data dictionaries for all files. The data package root contains 17 assets: 8 compressed tape archive (.tar.gz) files, 5 comma-separated values (.csv) files, 3 Geographic Tagged Image File Format (GeoTIFF) (.tif) files, and 1 Portable Document Format (.pdf) file. The compressed .tar.gz archives contain ESRI shapefiles (.shp) .tif, compressed LASer (.laz), and .csv files. The archives must first be decompressed using the widely distributed command-line software utility TAR. All other files, including constituent files within the .tar.gz archives, can be opened in the open-source R statistical computing environment. Alternatively, .csv files may also be read in any simple text editor software or Microsoft Excel. Geospatial files including .shp and .tif files can also be opened in GIS software, such as QGIS (open-source) or ESRI ArcGIS (proprietary). The .pdf Data User Guide can be read with Adobe Acrobat Reader or other compatible readers.
2018 NEON and 2025 CHESS Campaigns↗
Understanding Twinning and Deformation in High Entropy Alloys
A combination of high strength and high ductility has been observed in multi-principal element alloys due to twin formation attributed to low stacking fault energy (SFE). In the pursuit of low SFE alloys, a key bottleneck is the lack of understanding of the composition–SFE cor- relations that would guide tailoring SFE via alloy composition. Using density functional theory (DFT), we show that dopant radius, which have been postulated as a key descriptor for SFE in dilute alloys, does not fully explain SFE trends across different host metals. Instead, charge density is a much more central descriptor. It allows us to (1) explain contrasting SFE trends in Ni and Cu host metals due to various dopants in dilute concentrations, (2) explain the large SFE variations observed in the literature even within a given alloy composition due to the nearest neighbor environments in “model” concentrated alloys, and (3) develop a machine learning model that can be used to predict SFEs in multi-elemental alloys. This model opens a possibility to use charge density as a descriptor for predicting SFE in alloys. Furthermore, a descriptor-less machine learning (ML) model based only on charge density images extracted from density functional theory (DFT) is developed to predict stacking fault energies (SFE) in concentrated alloys. The model is based on convolutional neural networks (CNNs) as one of the promising ML techniques for dealing with complex images and data. Identification of correct descriptors is a key bottleneck to develop ML models for predicting materials properties. Often, in most ML models, textbook physical descriptors such as atomic radius, valence charge and electronegativity are used as descriptors which have limitations because these properties change in concentrated alloys when multiple elements are mixed to form a solid solution. We illustrate that, within the scope of DFT, the search for descriptors can be circumvented by electronic charge density, which is the backbone of the Kohn-Sham DFT and describes the system completely. The performance of our model is demonstrated by predicting SFE of concentrated alloys with an RMSE and R2 of 6.18 mJ/m2 and 0.87, respectively, validating the accuracy of the proposed approach.
36 MATERIALS SCIENCE↗
Polymer composites for fused filament fabrication and methods of making the same
Disclosed are compositions of a fused filament fabrication (FFF) composite filament having embedded functional materials in a thermoplastic matrix. Methods of making the composite filaments are also disclosed. In one example, a FFF composite filament incorporates a MOF, in an amount greater than 10% by mass, dispersed in a matrix polymer. One example of a method of synthesizing FFF composite filaments involves mixing a suspension that has a MOF with a matrix polymer solution to yield a polymer-MOF mixture. The mixture is cast and dried into a solid composite material, which is formed a FFF composite filament having the MOF in an amount greater than 10% by mass.
36 MATERIALS SCIENCE↗
Minority carrier lifetime and photoluminescence of mid-wave infrared InAsSbBi
Time-resolved photoluminescence measurements are reported for InAsSbBi alloys grown by molecular beam epitaxy with Bi mole fractions ranging from 0 to 0.8%, yielding minority carrier lifetimes on the order of hundreds of nanoseconds. The minority carrier lifetimes extracted from the time-resolved photoluminescence measurements are comparable to those of lattice-matched InAsSb grown at the same respective temperatures. Nomarski imaging shows that smooth, droplet-free surface morphologies are obtained in 1 μm thick InAsSbBi epilayers grown at temperatures between 360 and 380 °C. The alloy composition-dependent bandgap energies for the InAsSbBi samples are determined from temperature-dependent steady-state photoluminescence measurements and compared with the tetragonal distortion measured by x-ray diffraction to determine the Sb and Bi mole fractions of each sample. The minority carrier lifetime and the achievable extension of the InAsSb(Bi) cut-off wavelength are analyzed as functions of alloy composition and compared with the performance of InAsSb layers with similar growth parameters.
Petluru, Priyanka (ORCID:0000000257154284)↗
Dynamic microbial assembly processes correspond to soil fertility in sustainable paddy agroecosystems
1. Microorganisms underpin the sustainability of agroecosystems, but we have a poor understanding of how the assembly processes that govern microbial community structure interact through time to maintain soil fertility. 2. Ancient rice paddies have a history of cultivation spanning hundreds or thousands of years and provide an ideal opportunity to explore relationships between community assembly processes and long-term agroecosystem sustainability. We used statistical null models to evaluate temporal patterns of bacterial community assembly processes across rice cultivation years and their associations with increases in soil fertility in paddy agroecosystems. 3. We found that stochasticity was a persistent force structuring paddy soil microbial communities, putatively due to frequent flooding that facilities dispersal. However, determinism gradually increased over centuries of agriculture and corresponded to increases in soil fertility. Accordingly, multifunctionality, calculated using enzymes catalyzing key soil functions in carbon, nitrogen, phosphorous and sulfur cycling significantly increased along rice cultivation years. We therefore propose that balanced assembly processes preserve a diverse array of traits that can dominate under various circumstances (stochasticity) while allowing for traits relevant to soil fertility to be selected for by soil fertility (determinism), thus supporting multifunctionality that underlies sustainable agroecosystems. 4. In total, our results highlight that knowledge on temporal microbial assembly processes, community composition, and ecological function in context of soil fertility is key to understanding ecological mechanisms maintaining agroecosystems sustainability.
Liu, Wenjing↗
Benchtop Autonomous Electrochemical Characterization System for Combinatorial Thin-Film Solid Oxide Electrodes
The design of materials for electrochemical energy conversion is complicated by a vast search space of candidate materials and multifaceted property requirements: multicarrier conductivity, stability, and catalytic activity are all necessary but rarely intersect. Although self-driving laboratories are rapidly rising to address such material optimization problems, the required infrastructure for integrated, large-scale robotic facilities can be cost-prohibitive. Here we develop and evaluate a closed-loop measurement system for efficient screening of proton-conducting oxide electrodes for ceramic fuel cells and electrolyzers, building on top of an existing benchtop instrument and integrating techniques for rapid impedance measurement and automated analysis. This system exemplifies a “minimum viable” self-driving implementation that can deliver substantial benefits with relatively simple infrastructure. Combinatorial thin-film microelectrode libraries are characterized with a recently developed joint time-domain and frequency-domain impedance measurement technique, which provides an order-of-magnitude acceleration relative to conventional impedance spectroscopy. The distribution of relaxation times is extracted from impedance data and analyzed without human intervention. These results feed an active learning and Bayesian optimization process that learns to predict electrochemical impedance as a function of material composition, measurement temperature, oxygen partial pressure, and electrical bias, which further reduces the screening time by tenfold with optimized experimental sequences. We apply this system to Ba(Co,Fe,Zr,Y)O 3−𝛿 combinatorial libraries and evaluate its effectiveness for learning material property trends and optimizing expensive-to-evaluate properties such as activation energy. This offers insights into key methodological aspects of practical autonomous experimentation, including surrogate model validation, cost-aware acquisition functions, and high-throughput data interpretation. Our results demonstrate the efficacy of the system for rapidly gathering information, but also highlight real-world experimental challenges of thin-film degradation and numerical instability in surrogate models.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Performance of Base and Noble Metals for Electrocatalytic Hydrogenation of Bio-Oil-Derived Oxygenated Compounds
Electrocatalytic hydrogenation is a particularly attractive approach for converting the most unstable compounds in biogenic feedstocks at ambient conditions without external hydrogen. Here, we synthesized a variety of carbon-supported transition metal catalysts and characterized their activity for the electrocatalytic hydrogenation of a series of model compounds and pyrolysis oil. Carbonyl compounds, especially aromatic aldehydes, such as furfural and benzaldehyde, are particularly inclined to hydrogenation driven by an applied current. This was verified with pure solutions of the model compounds and with pyrolysis oil, where we achieved stable and steady continuous operation on Pd. By choosing the optimal catalyst composition, the conversion of benzaldehyde shifted from alcohol production (e.g., on Pd and Cu) to dimerization (e.g., on Co, Ni, and Zn). Pd and Cu were shown to offer the best compromise between reaction rates and efficiency although, in general, base metals offer similar conversions but better efficiencies that noble metals. Thus, the present work offers foundational results and guidelines for choosing the optimal metal catalyst and the applied potential for processing organic feedstocks as a function of its composition.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Charge-density based evaluation and prediction of stacking fault energies in Ni alloys from DFT and machine learning
A combination of high strength and high ductility has been observed in multi-principal element alloys due to twin formation attributed to low stacking fault energy (SFE). In the pursuit of low SFE alloys, a key bottleneck is the lack of understanding of the composition–SFE correlations that would guide tailoring SFE via alloy composition. Using density functional theory (DFT), we show that dopant radius, which have been postulated as a key descriptor for SFE in dilute alloys, does not fully explain SFE trends across different host metals. Instead, charge density is a much more central descriptor. It allows us to (1) explain contrasting SFE trends in Ni and Cu host metals due to various dopants in dilute concentrations, (2) explain the large SFE variations observed in the literature even within a given alloy composition due to the nearest neighbor environments in “model” concentrated alloys, and (3) develop a machine learning model that can be used to predict SFEs in multi-elemental alloys. Further, this model opens a possibility to use charge density as a descriptor for predicting SFE in alloys.
36 MATERIALS SCIENCE↗
Final Technical Report for project entitled Highly Active, Durable, and Ultra-Low PGM NSTF Thin Film ORR Catalysts and Support
In this project, the objective was to develop new oxygen reduction reaction (ORR) electrocatalysts for proton exchange membrane fuel cells (PEMFCs) which could exceed all of the Department of Energy (DOE) 2020 targets listed in DE-FOA-0001224, Subtopic 1b, Table I. The expected outcome was development of one or more electrocatalysts which are substantially improved over the current state-of-the-art in terms of overall activity, durability, and cost, and are suitable for automotive traction and stationary fuel cell applications. This report summarizes this project’s progress towards meeting the stated objectives and includes a summary of key findings and conclusions. The development activities towards new highly active and durable thin film electrocatalysts has led to the discovery of several electrocatalysts which approached or exceeded several DOE 2020 targets for activity, durability, and performance in proton exchange membrane fuel cell (membrane electrode assemblies (MEAs). In this project, electrocatalyst development focused on systematic physical and electrochemical characterization of electrocatalyst activity, durability, and performance in MEAs as a function of electrocatalyst fabrication, compositional and structural variables. The project approach was to develop relationships between the catalyst functional responses (activity, durability and performance) with catalyst physical properties and catalyst fabrication methods. Additionally, the thin film catalysts were integrated onto the unique and durable 3M Nanostructured Thin Film (NSTF) support, consisting of arrays of self-assembled organic crystalline whiskers. The catalysts were evaluated against the project targets via extensive electrochemical characterization in MEA format at 3M, advanced structural and compositional microscopy at Oak Ridge National Laboratory (ORNL), and atomic structure analysis via XAFS at Argonne National Laboratory (ANL). The extensive electrochemical and physical characterization resulted in development of several trends which correlate the catalysts’ electrochemical properties to their physical properties, including composition, structure, and method of fabrication. The development was guided by density functional theory (DFT) modeling at Purdue University and kinetic Monte Carlo (kMC) modeling at Johns Hopkins University. The catalyst simulations provided key insights into the observed experimental activity and durability trends, and additionally were utilized to assess new electrocatalyst concepts prior to or coincident with physical catalyst development. This development has led to several electrocatalyst candidates with activity and durability which approach or exceed DOE targets. One class of catalysts, based on nm-scale thin layers of Pt on Ir, met or exceeded 6 of the 6 DOE targets the project addressed.
08 HYDROGEN↗
Lattice-Mismatched van der Waals Epitaxy and Photoluminescence of Two-Dimensional GaxIn1-xSe Alloys on Si(111)
GaxIn1-xSe (GIS) alloys are two-dimensional (2D) layered materials with band gaps and lattice parameters of interest for many energy and electronic applications. They can be fabricated using van der Waals epitaxy, which is an emerging technique that offers unprecedented opportunities for 2D optoelectronic devices and epitaxy processes. This work has demonstrated van der Waals epitaxy of GIS alloys for the first time. Films with x compositions of 0, 0.062, 0.164, 0.680, 0.894, and 1 and tunable lattice constants were grown on Si(111) substrates, and characterized by X-ray diffraction pole figure and transmission electron microscope analysis. In spite of the lattice mismatches (InSe is 4.1% too large and GaSe is 2.8% too small), these alloys grow epitaxially, with Si(111) || GIS(001) and Si[1-10] || GIS[100] orientation. Photoluminescence was used to measure tunable band gaps in the absorber-relevant 1.3-2.0 eV range as a function of x composition and showed GIS did not degrade after capping with Se and prolonged storage. Therefore, GIS alloys exhibit a technologically advantageous combination of tunable band gap and photoluminescence with relaxed lattice parameter and rotational registry with the substrate.
36 MATERIALS SCIENCE↗
Impacts of A‐Site Composition on the Cation Dissolution‐Mediated Surface Restructuring of Layered Nickelate Oxide Electrocatalysts During Alkaline Oxygen Evolution Reaction
The oxygen evolution reaction (OER) is a key anodic counter‐reaction for electrochemical production of fuels and chemicals. It is hindered by sluggish four‐electron transfer kinetics requiring highly oxidative operating potentials to achieve commercially relevant rates. NiFeO x H y electrocatalysts are among the most promising for OER in alkaline electrolytes. The Ni(OH) 2 /NiOOH redox couple has been reported as the active phase in Ni‐based electrocatalysts; however, its activity is often hindered by deactivation arising from the formation of OER‐inactive insulating species. Limited strategies exist for mitigating this deactivation. This study aims to address this by interrogating the evolution of OER active sites as a function of precatalyst composition and structural properties using a series of layered, crystalline Ni‐based Ruddlesden–Popper (RP) oxides (A 2 NiO 4+δ ). In situ evolution of the active NiO x H y surface is probed through Ni‐site OER turnover frequency analysis, and electrochemical impedance spectroscopy coupled with scanning transmission electron microscopy. We show that the stability of layered nickelate oxide electrocatalysts is governed by the dynamic competition between cation dissolution and Ni‐site reversibility, which can be tuned through the A‐site composition of RP oxides. These findings yield insights toward engineering OER oxide precatalysts that optimize the stability of in situ‐generated OER active phases.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Nanomorphology of eco-friendly colloidal inks, relating non-fullerene acceptor surface energy to structure formation
Nanoengineered, eco-friendly, solution-processable electroactive materials are in demand for the growing field of printed electronics, and these material requirements can be achieved by the development of waterborne colloidal dispersions. Functionality in these composite materials can be tuned by thermodynamically modifying the material nanomorphology, often by creation of kinetically stabilized aqueous nanoparticle dispersions. In this work we demonstrate that the internal structure of organic nanoparticles is controlled by the surface energy difference between the polymeric donor material and the non-fullerene acceptor (NFA) material. Nanoparticles of the following donor–acceptor combinations, suitable for printed organic photovoltaics, have been synthesized: TQ1:N2200, TQ1:PNDIT10, P3HT:N2200, P3HT:o-IDTBR and P3HT:eh-IDTBR. Advanced synchrotron-based X-ray spectroscopy and microscopy are used to correlate the formation of core–shell nanoparticle morphology to the material surface energy. We subsequently present a viable avenue for customizing the blended nanoparticle structure into (i) core–shell, (ii) molecularly intermixed, or (iii) inverted shell–core structures. Our results showed that TQ1:PNDIT10 and P3HT:o-IDTBR nanoparticles were comprised of a donor-rich shell and an NFA-rich core, however, interestingly we show a reversal to the inverse NFA shell/donor core structure for TQ1:N2200, P3HT:N2200 and P3HT:eh-IDTBR nanoparticles, driven by the low surface energy of N2200 (23.7 mJ m –2 ) and eh-IDTBR (18.3 mJ m –2 ). This article is the first report of a flipped nanoparticle core–shell morphology comprising an NFA-rich shell for the miniemulsion synthesis route. The composition of the shells and cores was able to be controlled by the differential mismatch in the surface energy of the donor and acceptor materials, with ΔG surface > 0, ΔG surface = 0, and ΔG surface < 0 for acceptor core–donor shell, molecularly intermixed, and acceptor shell–donor core, respectively. Accordingly, we introduce an entirely overlooked new figure of merit (FoM) for customizing nanoparticulate colloidal inks: tunable surface energy of non-fullerene-based semiconductors. Finally, the establishment of this FoM opens up electroactive material design to a wide range of functional printing applications with varying device and ink structure requirements, thereby reshaping the nanoengineering toolkit for waterborne colloidal dispersions and hence printed electronics.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Au x Pd (300‐ x ) Alloy Nanoparticles for the Oxygen Reduction Reaction in Alkaline Media
Abstract Au x Pd (300‐ x ) nanoalloys were prepared using a dendrimer‐templating method and their electrocatalytic efficiencies towards the oxygen reduction reaction (ORR) were analyzed in alkaline media. The composition‐dependent PdO x reduction potentials of the Au x Pd (300‐ x ) nanoalloys were correlated to the oxygen‐binding (O‐binding) energy of the catalysts. Multiple PdO x reduction peaks were present for the Au 150 Pd 150 and Au 50 Pd 250 catalysts. These peaks were assigned to the alloyed and bulk‐like Pd active sites on the alloyed surface. The results described here are significant because modulation of the O‐binding energies improved the ORR activity on the nanoalloys. Specifically, a linear trend in O‐binding energies of Au x Pd (300‐ x ) dendrimers (DENs) as a function of Pd composition resulted in a volcano‐shaped trend in ORR activity. The optimal O‐binding energy of Au 50 Pd 250 resulted in an approximate 89 mV shift in PdO x reduction relative to Pd 300 and a shift of approximately 76 mV in ORR peak potential.
Trindell, Jamie A.↗
Full-Field Strain Measurement Integrated with Two Dimension Regression Analysis to Evaluate the Bi-Modulus Elastic Properties of Isotropic and Transversely Isotropic Materials
Background: Measuring the physical properties of shale is critical for optimizing engineering activities such as geothermal energy generation and hydraulic fracturing. Shale is a transversely isotropic material. Furthermore, this material can also include micro and macro cracks at different locations and orientations that cause it to behave differently under tensile or compressive loading. Objective: In this work, a combined experimental–numerical approach is proposed to evaluate the bi-modulus elastic properties of isotropic and transversely isotropic materials. Methods: Full-field strain measurements for a circular disk under diametral compression are integrated with a regression analysis technique to evaluate the elastic properties of bi-modulus materials subjected to tensile and compressive loads using two loading configurations on the same specimen. Digital Image Correlation (DIC) is used to measure the full-field strains. Subsequently, in the case of an isotropic material, a linear least-squares approach is utilized to process the experimentally determined strains in conjunction with analytical expressions of the stress fields (in terms of far-field loading) to determine the elastic modulus E, the shear modulus G, and the Poisson’s ratio $v$. In the case of a transversely isotopic material, such as shale, a finite element model is implemented to determine the stress fields (again in terms of far-field loading), which is followed by repeating the previous regression analysis in an iterative process to estimate the elastic parameters. Results: The results show that the proposed technique successfully provides a complete set of elastic properties as a function of both the loading condition and the principal material directions. The technique is validated by measurements on a known isotropic material and then applied to determine the properties of shale. Conclusion: In this work, the proposed approach is successfully used to calculate the bi-modulus elastic response of poly(methyl meth- acrylate) (PMMA) and shale. As expected, PMMA exhibits an isotropic response with no bi-modulus effect, however, shale exhibits both transverse isotropy and a bi-modulus effect. Therefore, this approach holds promise for investigating the elastic properties of materials like rocks and fiber-reinforced composite laminates as functions of the principal material directions and the loading conditions.
42 ENGINEERING↗
Mechanical adaptation of brachiopod shells via hydration-induced structural changes
The function-optimized properties of biominerals arise from the hierarchical organization of primary building blocks. Alteration of properties in response to environmental stresses generally involves time-intensive processes of resorption and reprecipitation of mineral in the underlying organic scaffold. Here, we report that the load-bearing shells of the brachiopod Discinisca tenuis are an exception to this process. These shells can dynamically modulate their mechanical properties in response to a change in environment, switching from hard and stiff when dry to malleable when hydrated within minutes. Using ptychographic X-ray tomography, electron microscopy and spectroscopy, we describe their hierarchical structure and composition as a function of hydration to understand the structural motifs that generate this adaptability. Key is a complementary set of structural modifications, starting with the swelling of an organic matrix on the micron level via nanocrystal reorganization and ending in an intercalation process on the molecular level in response to hydration.
36 MATERIALS SCIENCE↗