Proposal for Manipulating Functional Interface Properties of Composite Organic Semiconductors with Addition of Designed Macromolecules
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bio-inspired↗
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Long-term warming in a Mediterranean-type grassland affects soil bacterial functional potential but not bacterial taxonomic composition
Abstract Climate warming is known to impact ecosystem composition and functioning. However, it remains largely unclear how soil microbial communities respond to long-term, moderate warming. In this study, we used Illumina sequencing and microarrays (GeoChip 5.0) to analyze taxonomic and functional gene compositions of the soil microbial community after 14 years of warming (at 0.8–1.0 °C for 10 years and then 1.5–2.0 °C for 4 years) in a Californian grassland. Long-term warming had no detectable effect on the taxonomic composition of soil bacterial community, nor on any plant or abiotic soil variables. In contrast, functional gene compositions differed between warming and control for bacterial, archaeal, and fungal communities. Functional genes associated with labile carbon (C) degradation increased in relative abundance in the warming treatment, whereas those associated with recalcitrant C degradation decreased. A number of functional genes associated with nitrogen (N) cycling (e.g., denitrifying genes encoding nitrate-, nitrite-, and nitrous oxidereductases) decreased, whereas nifH gene encoding nitrogenase increased in the warming treatment. These results suggest that microbial functional potentials are more sensitive to long-term moderate warming than the taxonomic composition of microbial community.
59 BASIC BIOLOGICAL SCIENCES↗
Atomic Origins of the Self-Healing Function in Cement–Polymer Composites
Motivated by recent advances in self-healing cement and epoxy polymer composites, we present a combined ab initio molecular dynamics and sum frequency generation (SFG) spectroscopy study of a calcium-silicate-hydrate/polymer interface. On stable, low-defect surfaces, the polymer only weakly adheres through coordination and hydrogen bonding interactions and can be easily mobilized towards defected surfaces. Conversely, on fractured surfaces, the polymer strongly anchors through ionic Ca-O bonds resulting from the deprotonation of polymer hydroxyl groups. In addition, polymer S-S groups are turned away from the cement/polymer interface, allowing for the self-healing function within the polymer. The overall elasticity and healing properties of these composites stem from a flexible hydrogen bonding network that can readily adapt to surface morphology. The theoretical vibrational signals associated with the proposed cement-polymer interfacial chemistry were confirmed experimentally by SFG spectroscopy.
ab initio molecular 8 dynamics↗
Simple polyol route to synthesize heptanoic acid coated magnetite (Fe{sub 3}O{sub 4}) nanoparticles
Highlights: ► Heptanoic acid@Fe{sub 3}O{sub 4} nanocomposite has been prepared via simple polyol. ► Heptanoic acid used as both surfactant and solvents. ► Magneto polymer composite with adjustable Ea has a potential usage as functional composites. - Abstract: Magnetite (Fe{sub 3}O{sub 4}) nanoparticles were prepared via polyol method by using FeCl{sub 2} as only source of iron. As-prepared samples were characterized by powder X-ray diffractometer (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), thermal gravimetric analyzer (TGA) and vibrating sample magnetometer (VSM). Crystalline phase was identified as Fe{sub 3}O{sub 4} and the crystallite sizes were calculated as 19.1 ± 1.1 and 22 ± 1.3 nm for uncalcinated and calcinated products from X-ray line profile fitting. The capping of heptanoic acid around Fe{sub 3}O{sub 4} nanoparticles was confirmed by FT-IR spectroscopy, the interaction being via bridging oxygen's of the carboxylate and the nanoparticle surface and also by TG analysis. VSM measurements showed that both samples exhibited typical superparamagnetic behavior at room temperature with different Ms values. The ε′ decreases with increasing frequency for both composites and permeability has almost same values for all temperatures at higher frequencies. As synthesized and calcinated samples conductivity increase linearly with the temperature.
36 MATERIALS SCIENCE↗
Analysis of the functional gene structure and metabolic potential of microbial community in high arsenic groundwater
Microbial functional potential in high arsenic (As) groundwater ecosystems remains largely unknown. In this study, the microbial community functional composition of nineteen groundwater samples was investigated using a functional gene array (GeoChip 5.0). Samples were divided into low and high As groups based on the clustering analysis of geochemical parameters and microbial functional structures. The results showed that As related genes (arsC, arrA), sulfate related genes (dsrA and dsrB), nitrogen cycling related genes (ureC, amoA, and hzo) and methanogen genes (mcrA, hdrB) in groundwater samples were correlated with As, SO 4 2- , NH 4 + or CH 4 concentrations, respectively. Canonical correspondence analysis (CCA) results indicated that some geochemical parameters including As, total organic content, SO 4 2- , NH 4 + , oxidation-reduction potential (ORP) and pH were important factors shaping the functional microbial community structures. Alkaline and reducing conditions with relatively low SO 4 2- , ORP, and high NH 4 + , as well as SO 4 2- and Fe reduction and ammonification involved in microbially-mediated geochemical processes could be associated with As enrichment in groundwater. This study provides an overall picture of functional microbial communities in high As groundwater aquifers, and also provides insights into the critical role of microorganisms in As biogeochemical cycling.
59 BASIC BIOLOGICAL SCIENCES↗
A High-Entropy Oxide as High-Activity Electrocatalyst for Water Oxidation
High-entropy materials are an emerging pathway in the development of high-activity (electro)catalysts because of the inherent tunability and coexistence of multiple potential active sites, which may lead to earth-abundant catalyst materials for energy-efficient electrochemical energy storage. In this report, we identify how the multication composition in high-entropy perovskite oxides (HEO) contributes to high catalytic activity for the oxygen evolution reaction (OER), i.e., the key kinetically limiting half-reaction in several electrochemical energy conversion technologies, including green hydrogen generation. We compare the activity of the (001) facet of LaCr 0.2 Mn 0.2 Fe 0.2 Co 0.2 Ni 0.2 O 3-δ with the parent compounds (single B-site in the ABO 3 perovskite). While the single B-site perovskites roughly follow the expected volcano-type activity trends, the HEO clearly outperforms all of its parent compounds with 17 to 680 times higher currents at a fixed overpotential. As all samples were grown as an epitaxial layer, our results indicate an intrinsic composition–function relationship, avoiding the effects of complex geometries or unknown surface composition. In-depth X-ray photoemission studies reveal a synergistic effect of simultaneous oxidation and reduction of different transition metal cations during the adsorption of reaction intermediates. The surprisingly high OER activity demonstrates that HEOs are a highly attractive, earth-abundant material class for high-activity OER electrocatalysts, possibly allowing the activity to be fine-tuned beyond the scaling limits of mono- or bimetallic oxides.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Genesis of a novel high-rate composite manufacturing process using large-scale additive manufacturing – compression molding (AM-CM) system: Possibilities and limitations
Oak Ridge National Laboratory (ORNL) has developed a highly automated manufacturing process for thermoplastic composites that combines the benefits of Additive Manufacturing and Compression Molding (AM-CM) to produce high-performance functional composite structures at automotive production rates. Here, the AM-CM process creates highly precise preforms by additively placing extruded fiber-filled polymers (with controlled fiber orientations and multi-material configurations) in the desired mold location before undergoing a secondary compression molding process immediately before the preform cools down. Preforms can be in the form of short, long-chopped, or continuous fiber-filled thermoplastic polymers (e.g., CF/GF-filled ABS, PC, LM-PAEK, etc.). The AM-CM process combines the benefits of controlled fiber alignment, that is only achievable in AM-printed parts with the classical CM process, which eliminates porosity and good surface finish. A preform created using AM-CM can integrate various materials to enable additional architectural functionalities, including over-molding, selective stiffening, and the incorporation of electrically or thermally conductive channels. All these advantages come with a fast part production cycle time. The AM-CM process can manufacture multi-material, multi-functional parts in under 3 min, starting from raw material (pellets) to the final product. The novel AM-CM process offers superior microstructural control and enhanced multi-functionality previously unattainable with any other traditional high-rate thermoplastic composite manufacturing method. This work covers the manufacturing concept, system development, materials and applications of AM-CM process in detail.
Kumar, Vipin [Oak Ridge National Laboratory (ORNL)↗
Coal polymer composites prepared by fused deposition modeling (FDM) 3D printing
Coal is a vital energy resource worldwide, but pollutants and greenhouse gases from its combustion cause environmental problems. To explore the non-combustion approach to use and valorize coal, anthracite and lignite were blended with polyamide 12 (PA 12) through FDM printing in this work and compared in the composites. By adding lignite, Young’s modulus improved with increasing loading to 50 wt% while tensile strength leveled off among the composites, compared to that of PA 12. By contrast, the addition of anthracite decreased the tensile performance at all loadings. Rheology tests and morphology analyses suggested that the interactions between fillers (anthracite and lignite) and PA 12 may cause differences in tensile properties. In addition, the printed lignite composites showed improved thermal conductivity (~ twofold), indicating lignite demonstrates the potential to build functional composites. This work provides a strategy to use lignite in composites by 3D printing for value-added products and reduces the demand for petroleum-based polymers. Overall, our approach diverts lignite from combustion processes and alleviates the negative impact of lignite use on the environment.
36 MATERIALS SCIENCE↗
MicroFisher: Fungal taxonomic classification for metatranscriptomic and metagenomic data using multiple short hypervariable markers
AbstractProfiling the taxonomic and functional composition of microbes using metagenomic (MG) and metatranscriptomic (MT) sequencing is advancing our understanding of microbial functions. However, the sensitivity and accuracy of microbial classification using genome– or core protein-based approaches, especially the classification of eukaryotic organisms, is limited by the availability of genomes and the resolution of sequence databases. To address this, we propose the MicroFisher, a novel approach that applies multiple hypervariable marker genes to profile fungal communities from MGs and MTs. This approach utilizes the hypervariable regions of ITS and large subunit (LSU) rRNA genes for fungal identification with high sensitivity and resolution. Simultaneously, we propose a computational pipeline (MicroFisher) to optimize and integrate the results from classifications using multiple hypervariable markers. To test the performance of our method, we applied MicroFisher to the synthetic community profiling and found high performance in fungal prediction and abundance estimation. In addition, we also used MGs from forest soil and MTs of root eukaryotic microbes to test our method and the results showed that MicroFisher provided more accurate profiling of environmental microbiomes compared to other classification tools. Overall, MicroFisher serves as a novel pipeline for classification of fungal communities from MGs and MTs.
Wang, Haihua↗
Climate Effects on Plant Range Distributions and Community Structure of Pacific Northwest Prairies
Pacific Northwest (PNW) prairies are an imperiled ecosystem that contain a large number of plant species with high fidelity to this habitat. The few remaining high-quality PNW prairies harbor a number of sensitive, rare, and endangered plant species that may be further at-risk with climate change. Thus, PNW prairies are an excellent model system to examine how climate change will affect the distribution of native plant species in grassland sites. Our experimental objectives were to determine: (i) how climate change will affect the range distribution of native plant species; (ii) what life history stages are most sensitive to climate change in a group of key indicator native species; (iii) the robustness of current restoration techniques and suites of species to changing climate, and in particular, the relative competitiveness of native species versus exotic invasive species; and (iv) the effects of climate change on carbon and nutrient cycling and soil-microbial-plant feedbacks. We addressed these objectives by experimentally increasing temperature 2.5 to 3.0 ºC above ambient with overhead infrared lamps and increasing wet-season precipitation by 20% above ambient in three upland prairie sites in central-western Washington, central-western Oregon, and southwestern Oregon from fall 2010 through 2012. Additional precipitation was applied within 2 weeks of when it fell so precipitation intensity was increased, particularly during the winter rainy season but with minimal additions during the summer dry season. These three sites also represent a 520-km natural climate gradient of increasing degree of severity of Mediterranean climate from north to south. After removing the extant vegetation, we planted a diverse suite of 12 native species that have their northern range limit someplace within the PNW in each experimental plot. An additional 20 more wide-spread native species were also planted into each plot. We found that recruitment of plant species within their ranges was negatively impacted by increased temperatures, but for species planted north of their current range, increased temperature was neutral. However, for surviving plants climate treatments and site-specific factors (e.g., nutrient availability) were the strongest predictors of plant growth and seed set. When recruitment and plant growth are considered together, increased temperatures are negative within a species current range but beyond this range they become positive. Germination was the most critical stage for plant response across all sites and climate treatments. Our results underscore the importance of including plant vital rates into models that are examining climate change effects on plant ranges. Warming altered plant community composition, decreased diversity, and increased total cover, with warmed northern communities over time becoming more like ambient communities further south. In particular, warming increased the cover of annual introduced species, suggesting that the observed biogeographic pattern of increasing invasion by this plant functional group in US West Coast prairies as one moves further south is at least in part due to climate. Our results suggest that with the projected increase in drought severity with climate change, Pacific Northwest prairies may face an increase of invasion by annuals, similar to what has been observed in California, resulting in novel species assemblages and shifts in functional composition, which in turn may alter ecosystem function. Warming generally increased nutrient availability and plant productivity across all sites. The seasonality of soil respiration responses to heating were strongly dependent on the Mediterranean climate gradient in the PNW, with heating responses being generally positive during periods of adequate soil moisture and becoming neutral to negative during periods of low soil moisture. The asynchrony between temperature and precipitation may make soils less sensitive to warming. Precipitation effects were minimal for all measured responses indicating the importance of increased temperatures in driving biotic responses to climate change in Mediterranean ecosystems. However, substantially increased precipitation during the dry season would almost certainly have profound effects, but the opposite is predicted by current climate change models for the PNW. A manipulative climate change experiment embedded within a natural climate gradient provides unique insights into the degree to which biotic responses to climate change are regionally consistent and site-dependent. Perhaps surprisingly, most climatic effects that we observed were either consistent in the three sites or could be readily interpreted in terms of the gradient of increasing intensity of the Mediterranean climate from north to south.
54 ENVIRONMENTAL SCIENCES↗
Dynamic Composition Determination in Heterogeneous Ensembles using Angular Autocorrelation Functions as Signatures
Signatures of heterogeneous ensembles composed of multiple types of random oriented particles are represented by the angular autocorrelation functions of the systems. These signatures are retrieved by averaging oversampled angular correlation functions calculated from high throughput X-ray diffraction patterns. Using a component signature matrix, the composition of the heterogeneous system will be directly calculated from the signature of the ensemble. This is the first attempt to determine dynamic composition of a heterogeneous ensemble by fluctuation X-ray scattering using the angular autocorrelation functions as signatures.
composition determination, angular correlation fun↗
Metagenomics Reveals Pervasive Bacterial Populations and Reduced Community Diversity across the Alaska Tundra Ecosystem
How soil microbial communities contrast with respect to taxonomic and functional composition within and between ecosystems remains an unresolved question that is central to predicting how global anthropogenic change will affect soil functioning and services. In particular, it remains unclear how small-scale observations of soil communities based on the typical volume sampled (1-2 g) are generalizable to ecosystem-scale responses and processes. This is especially relevant for remote, northern latitude soils, which are challenging to sample and are also thought to be more vulnerable to climate change compared to temperate soils. Here, we employed well-replicated shotgun metagenome and 16S rRNA gene amplicon sequencing to characterize community composition and metabolic potential in Alaskan tundra soils, combining our own datasets with those publically available from distant tundra and temperate grassland and agriculture habitats. We found that the abundance of many taxa and metabolic functions differed substantially between tundra soil metagenomes relative to those from temperate soils, and that a high degree of OTU-sharing exists between tundra locations. Tundra soils were an order of magnitude less complex than their temperate counterparts, allowing for near-complete coverage of microbial community richness (~92% breadth) by sequencing, and the recovery of 27 high-quality, almost complete ( > 80% completeness) population bins. These population bins, collectively, made up to ~10% of the metagenomic datasets, and represented diverse taxonomic groups and metabolic lifestyles tuned toward sulfur cycling, hydrogen metabolism, methanotrophy, and organic matter oxidation. Several population bins, including members of Acidobacteria, Actinobacteria, and Proteobacteria, were also present in geographically distant (~100-530 km apart) tundra habitats (full genome representation and up to 99.6% genome-derived average nucleotide identity). Collectively, our results revealed that Alaska tundra microbial communities are less diverse and more homogenous across spatial scales than previously anticipated, and provided DNA sequences of abundant populations and genes that would be relevant for future studies of the effects of environmental change on tundra ecosystems.
climate change↗
Roll-to-Roll Processing of Silicon Carbide Nanoparticle-Deposited Carbon Fiber for Multifunctional Composites
This work provides a proof of principle that a high volume, continuous throughput fiber coating process can be used to integrate semiconducting nanoparticles on carbon fiber surfaces to create multifunctional composites. By embedding silicon carbide nanoparticles in the fiber sizing, subsequent composite fabrication methods are used to create unidirectional fiber-reinforced composites with enhanced structural health monitoring (SHM) sensitivity and increased interlaminar strength. Additional investigations into the mechanical damping behavior of these functional composites reveal a significantly increased loss factor at the glass-transition temperature ranging from a 65 to 257% increase. Composites with both increased interlaminar strength and SHM sensitivity are produced from a variety of epoxy and silicon carbide nanoparticle concentrations. Overall, the best performing composite in terms of combined performance shows an increase of 47.5% in SHM sensitivity and 7.7% increase in interlaminar strength. Finally, this work demonstrates successful and efficient integration of nanoparticle synthesis into large-scale, structural applications.
36 MATERIALS SCIENCE↗
PanFP: Pangenome-based functional profiles for microbial communities
For decades there has been increasing interest in understanding the relationships between microbial communities and ecosystem functions. Current DNA sequencing technologies allows for the exploration of microbial communities in two principle ways: targeted rRNA gene surveys and shotgun metagenomics. For large study designs, it is often still prohibitively expensive to sequence metagenomes at both the breadth and depth necessary to statistically capture the true functional diversity of a community. Although rRNA gene surveys provide no direct evidence of function, they do provide a reasonable estimation of microbial diversity, while being a very cost effective way to screen samples of interest for later shotgun metagenomic analyses. However, there is a great deal of 16S rRNA gene survey data currently available from diverse environments, and thus a need for tools to infer functional composition of environmental samples based on 16S rRNA gene survey data. As a result, we present a computational method called pangenome based functional profiles (PanFP), which infers functional profiles of microbial communities from 16S rRNA gene survey data for Bacteria and Archaea. PanFP is based on pangenome reconstruction of a 16S rRNA gene operational taxonomic unit (OTU) from known genes and genomes pooled from the OTU s taxonomic lineage. From this lineage, we derive an OTU functional profile by weighting a pangenome s functional profile with the OTUs abundance observed in a given sample. We validated our method by comparing PanFP to the functional profiles obtained from the direct shotgun metagenomic measurement of 65 diverse communities via Spearman correlation coefficients. These correlations improved with increasing sequencing depth, within the range of 0.8 0.9 for the most deeply sequenced Human Microbiome Project mock community samples. PanFP is very similar in performance to another recently released tool, PICRUSt, for almost all of survey data analysed here. But, our method is unique in that any OTU building method can be used, as opposed to being limited to closed reference OTU picking strategies against specific reference sequence databases. In conclusion, we developed an automated computational method, which derives an inferred functional profile based on the 16S rRNA gene surveys of microbial communities. The inferred functional profile provides a cost effective way to study complex ecosystems through predicted comparative functional metagenomes and metadata analysis. All PanFP source code and additional documentation are freely available online at GitHub.
16S rRNA survey↗
Improved chemical and isotopic labeling of biomembranes in Bacillus subtilis by leveraging CRISPRi inhibition of beta-ketoacyl-ACP synthase (fabF)
Assessing the structure of living microbial cell membranes is a challenging analytical goal. The cell membrane is defined by its transverse structure, an approximately 5 nm-thick selectively permeable bilayer that serves many important cellular functions. Compositionally complex, dynamic, and organized in both the transverse and lateral dimensions, understanding the cell membrane structure—and the role that structure plays in cellular function, communication, and environmental sensing is an active scientific effort. Previously, we have devised a novel isotopic labeling approach for membrane lipids to enable direct in vivo structural studies of the cell membrane in the Gram-positive bacterium, Bacillus subtilis , using small-angle neutron scattering. This was accomplished through a genetic inhibition of fatty acid (FA) degradation (Δ fadN ) and a chemical inhibition of FA biosynthesis using cerulenin, an irreversible inhibitor of type II fatty acid synthases. Here, we improve upon the previous system by introducing a dCas9/sgRNA- fabF complex that blocks transcription of the essential fabF gene when under xylose induction. This leads to greater sensitivity to cerulenin in the mutant strain (JEBS102) and more robust cell growth when supplementary FAs are introduced to the culture medium. A subtle change in FA uptake is noted when compared to the prior labeling strategy. This is seen in the gas chromatography/mass spectrometry (GC/MS) data as a higher ratio of n 16:0 to a 15:0, and manifests in an apparent increase in the membrane thickness determined via neutron scattering. This represents an improved method of isotopic labeling for the cell membrane of Bacillus subtilis; enabling improved investigations of cellular uptake and utilization of FAs, cell membrane structure and organization as a phenotypic response to metabolic and environmental changes.
59 BASIC BIOLOGICAL SCIENCES↗
SISGR: Chemomechanics of Far-From-Equilibrium Interfaces (COFFEI)
Portable, reliable, and deployable devices for energy storage and conversion require fundamental changes in design of solid-state composites comprising ceramics and metals. These materials comprise the electrodes and electrolytes of next-generation solid-oxide fuel cells and all solid-state batteries, forming solid-state functional composites. The advent of solid-state batteries – which replace liquid electrolytes with solid electrolytes capable of lithium ion transport for reliable energy storage in portable batteries – and the increased demand space for all solid-state fuel cells capable of oxygen reduction at intermediate temperatures remain important challenges for improved material stability and decreased system cost. However, little is understood about three fundamental facets of materials that enable such solid-state energy applications. First, how do such materials deform, fracture, or delaminate under operando conditions? Second, how does such mechanical deformation limit or facilitate electronic and ionic transport within and across such material interfaces? Third, how we can predictably design interface-rich composites to engineer both structural and electrochemical stability? This COFFEI Group comprised expertise from Materials Science & Engineering and Nuclear Science & Engineering to integrate unique in situ experiments, simulations, and fabricated interfaces that address these fundamental questions in solid-state interfaces of nanoscale composites that will guide solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric materials that enable such applications. In particular, we built on COFFEI’s understanding of chemomechanical coupling among defect concentrations, ionic transport, electron transport, and stored elastic energy that is particularly acute in the far-from-equilibrium conditions typical of energy device applications. By tailoring our focus to solid-state interfaces, we addressed these important issues by (a) developing and applying advanced in situ and ex situ characterization tools to characterize model materials and interfaces synthesized with molecular-level control, under both laboratory-controlled and extreme environments representative of energy device operation; and (b) employing computational modeling and simulation frameworks to predict transport mechanisms, reactivity and stability of these model materials and interfaces under significant chemical strains typical of energy device operation. Recent progress provided insights to additional materials systems and electrochemomechanical fatigue and fracture that were not fully envisioned when the program was initiated. Specifically, in the final three years of COFFEI we pursued two integrated thrusts, with complementary focus. Thrust I focused on failure-resistant electrochemomechanical composites, while Thrust II focused on strain-modulated conductivity and reactivity across interfaces. In contrast to our initial COFFEI focus, these thrusts concentrated wholly on solid-state material interfacial interactions and included greater integration of multiscale visualization including in situ electron microscopy of strained structures/interactions and mesoscale simulations. Successful development of functionally superior and long-lived battery and fuel cell systems and stress adaptable oxides requires a deeper, fundamental understanding of the coupling among the historically important subfields of solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric metal oxide electrodes. In this program, the understanding and the application of chemomechanical coupling of defect concentrations, ionic transport, electro-catalytic activity and stored elastic energy, particularly acute in the far-from-equilibrium conditions typical of energy device applications, are being refined and implications for device operation clarified, including for miniaturized solid-state batteries and fuel cells.
36 MATERIALS SCIENCE↗
Magnetic properties of friction stir processed composite
There are many existing inspection systems each with their own advantages and drawbacks. These usually comprise of semi-remote sensors which frequently causes difficulty in reaching complex areas of a component. This study proposes to overcome that difficulty by developing embedded functional composites. Through this route, embedding can be achieved in virtually any component part and can be periodically interrogated by a reading device. The “reinforcement rich” processed areas can then be utilized to record properties like strain, temperature, stress state etc. depending on the reinforcement material. In this work, friction stir processing (FSP) was utilized to fabricate a magnetostrictive composite by embedding galfenol particles into a nonmagnetic aluminum (Al) matrix. It targets to develop a composite that produces strain in a varying magnetic field. Reinforcements were observed to be distributed uniformly in the matrix. Magnetization curves were studied using a vibrating sample magnetometer (VSM). A simple and cheap setup was developed to measure the magnetostrictive strain of the composites. Important factors affecting the magnetic properties were identified and ways to improve the magnetic properties discussed.
Das, Shamiparna↗
Colloidal Gelation in Liquid Metals Enables Functional Nanocomposites of 2D Metal Carbides (MXenes) and Lightweight Metals
Nanomaterials dispersed in different media, such as liquids or polymers, generate a variety of functional composites with synergistic properties. In this work, we discuss liquid metals as the nanomaterials' dispersion media. For example, 2D transition-metal carbides and nitrides (MXenes) can be efficiently dispersed in liquid Ga and lightweight alloys of Al, Mg, and Li. We show that the Lifshitz theory predicts strong van der Waals attraction between nanoscale objects interacting through liquid metals. However, a uniform distribution of MXenes in liquid metals can be achieved through colloidal gelation, where particles form self-supporting networks stable against macroscopic phase segregation. This network acts as a reinforcement boosting mechanical properties of the resulting metal-matrix composite. By choosing Mg-Li alloy as an example of ultralightweight metal matrix and Ti 3 C 2 T x MXene as a nanoscale reinforcement, we apply a liquid metal gelation technique to fabricate functional nanocomposites with an up to 57% increase in the specific yield strength without compromising the matrix alloy's plasticity. MXenes largely retain their phase and 2D morphology after processing in liquid Mg-Li alloy at 700 degrees C. The 2D morphology enables formation of a strong semicoherent interface between MXene and metal matrix, manifested by biaxial strain of the MXene lattice inside the metal matrix. Finally, this work expands applications for MXenes and shows the potential for developing MXene-reinforced metal matrix composites for structural alloys and other emerging applications with metal-MXene interfaces, such as batteries and supercapacitors.
36 MATERIALS SCIENCE↗