Searching for superconductivity in high entropy oxide Ruddlesden?Popper cuprate films
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Abstract Controlling the surface composition of shaped bimetallic nanoparticles could offer precise tunability of geometric and electronic surface structure for new nanocatalysts. To achieve this goal, a platform for studying the intermixing process in a shaped nanoparticle was designed, using multilayered Pd‐Ni‐Pt core–shell nanocubes as precursors. Under mild conditions, the intermixing between Ni and Pt could be tuned by changing layer thickness and number, triggering intermixing while preserving nanoparticle shape. Intermixing of the two metals is monitored using transmission electron microscopy. The surface structure evolution is characterized using electrochemical methanol oxidation. DFT calculations suggest that the low‐temperature mixing is enhanced by shorter diffusion lengths and strain introduced by the layered structure. The platform and insights presented are an advance toward the realization of shape‐controlled multimetallic nanoparticles tailored to each potential application.
Controlling the surface composition of shaped bimetallic nanoparticles could offer precise tunability of geometric and electronic surface structure for new nanocatalysts. To achieve this goal, a platform for studying the intermixing process in a shaped nanoparticle was designed, using multilayered Pd-Ni-Pt core–shell nanocubes as precursors. Under mild conditions, the intermixing between Ni and Pt could be tuned by changing layer thickness and number, triggering intermixing while preserving nanoparticle shape. Intermixing of the two metals is monitored using transmission electron microscopy. The surface structure evolution is characterized using electrochemical methanol oxidation. DFT calculations suggest that the low-temperature mixing is enhanced by shorter diffusion lengths and strain introduced by the layered structure. The platform and insights presented are an advance toward the realization of shape-controlled multimetallic nanoparticles tailored to each potential application.
Strain engineering in perovskite oxides provides for dramatic control over material structure, phase, and properties, but is restricted by the discrete strain states produced by available high-quality substrates. Here, using the ferroelectric BaTiO3, production of precisely strain-engineered, substrate-released nanoscale membranes is demonstrated via an epitaxial lift-off process that allows the high crystalline quality of films grown on substrates to be replicated. In turn, fine structural tuning is achieved using interlayer stress in symmetric trilayer oxide-metal/ferroelectric/oxide-metal structures fabricated from the released membranes. Additionally, in devices integrated on silicon, the interlayer stress provides deterministic control of ordering temperature (from 75 to 425 °C) and releasing the substrate clamping is shown to dramatically impact ferroelectric switching and domain dynamics (including reducing coercive fields to <10 kV cm-1 and improving switching times to <5 ns for a 20 µm diameter capacitor in a 100-nm-thick film). In devices integrated on flexible polymers, enhanced room-temperature dielectric permittivity with large mechanical tunability (a 90% change upon ±0.1% strain application) is demonstrated. This approach paves the way toward the fabrication of ultrafast CMOS-compatible ferroelectric memories and ultrasensitive flexible nanosensor devices, and it may also be leveraged for the stabilization of novel phases and functionalities not achievable via direct epitaxial growth.
Interface plays a critical role in determining the physical properties and device performance of heterostructures. Traditionally, lattice mismatch, resulting from the different lattice constants of the heterostructure, can induce epitaxial strain. Over past decades, strain engineering has been demonstrated as a useful strategy to manipulate the functionalities of the interface. However, mismatch of crystal symmetry at the interface is relatively less studied due to the difficulty of atomically structural characterization, particularly for the epitaxy of low symmetry correlated materials on the high symmetry substrates. Overlooking those phenomena restrict the understanding of the intrinsic properties of the as- determined heterostructure, resulting in some long-standing debates including the origin of magnetic and ferroelectric dead layers. Here, perovskite LaCoO 3 -SrTiO 3 superlattice (SL) is used as a model system to show that the crystal symmetry effect can be isolated by the existing interface strain. Combining the state-of-art diffraction and electron microscopy, it is found that the symmetry mismatch of LaCoO 3 -SrTiO 3 SL can be tuned by manipulating the SrTiO 3 layer thickness to artificially control the magnetic properties. Furthermore, the work suggests that crystal symmetry mismatch can also be designed and engineered to act as an effective strategy to generate functional properties of perovskite oxides.
Primary chemomechanical impacts of confinement on hydrogen storage performance are studied using a nanolaminate structure where reduced graphene oxide (rGO) encapsulates palladium (Pd) nanoparticles. Three contributing factors are identified that can alter the reaction enthalpy: nanosizing, chemical interaction with the encapsulant, and mechanical stress induced strain from a combination of clamping force and lateral pulling force exerted on the Pd nanoparticles. The mechanical contributions are quantified by combining transmission electron microscopy, ab initio computation, and continuum elasticity theory, from which the encapsulation is found to exert an additional strain of 4.96% and 2.99% before and after hydrogen absorption, respectively, increasing the Pd and Pd hydride (PdH x ) reaction enthalpy by 1.3–2.8 kJ (mol H 2 ) -1 . The effect of the chemical interaction with rGO also raises the reaction enthalpy by up to 1.6 kJ (mol H 2 ) -1 , while the nanosizing effect decreases the reaction enthalpy. The three contributing factors to the reaction enthalpy are found to be similar in magnitude, where the net effect is in agreement with the measured enthalpy increase of 3.7 kJ (mol H 2 ) -1 from the bulk value. Hydrogen absorption kinetics and capacity also improved, which is attributed to facile nucleation of the hydrogen-rich phase enabled by the inhomogeneous strain distribution over the encapsulated PdHx nanoparticles. These results demonstrate that the chemomechanical effect can be controlled in the nanolaminate structure, providing an ideal template for tuning hydrogen storage performance.
Using the first-principles calculations, we systematically investigated magnetic properties of a MnBi 2 Te 4 (MBT) monolayer in contact with III 2 -VI 3 two-dimensional ferroelectric substrates. As the electric polarization in the ferroelectric films is switched, a semiconductor to half-metal transition occurs in MBT, and its magnetic easy axis in several cases reorients. As an example, the Curie temperature of MBT/In 2 Se 3 can be enhanced to 21.5 or 32 K under the influence of electric polarization and biaxial strain, much higher than that of the pristine MBT monolayer, which is 14.5 K in our calculations. Our results in this work suggest effective ways to tune magnetic properties of MBT and provide useful insights for the further development of these important van der Waals functional materials.
Shape memory alloys (SMAs) are a unique class of materials with several remarkable properties including shape recovery, superelasticity, etc. Nickel-titanium (NiTi) based alloys are the most widely studied of this class, with compositions including ternary, quaternary, or higher additions being considered. Especially important for many NASA applications is the ability to tune the martensitic phase transition temperature of NiTi alloys by varying the alloy composition and processing conditions. In addition, low hysteresis and an acceptable recoverable transformation strain are required. Over the past several years, a significant database of SMA properties has been assembled by NASA researchers. Such a database is ideal for data science-based approaches. We present results from our machine learning approach for designing new SMAs with target properties within our range of interest. Our developed models are capable of accurately predicting the transition temperature, hysteresis, and transformation strain of SMAs across a wide range of compositions. This approach has the potential to significantly accelerate the discovery and design of new SMA materials.
Background Protein language models (PLMs) have revolutionized protein fitness prediction, yet their application to rapidly evolving viral pathogens is often confounded by extreme sequence homology. This homology leads to “data leakage” in standard random validation splits, yielding inflated performance metrics that fail to translate into real-world biosurveillance utility. Results We present Protein Representation Inference for Mutation Evaluation (PRIME), a framework that integrates domain-specific fine-tuning with a rigorous position-stratified validation protocol to evaluate viral threats. Using a dataset of 347,432 SARS-CoV-2 receptor binding domain (RBD) sequences, we demonstrate that while random training data split yields deceptive R 2 values (> 0.90), they fail to generalize to novel mutational sites. By benchmarking models up to 650 M parameters, we show that domain-specific fine-tuning of the ESM-C 600 M model with correctly stratified data provides an initial demonstration of predictive signal for binding affinity and expression at unseen mutational sites of binding affinity and expression on unseen sites (R 2 ~0.23), a significant advancement over base foundation models which exhibit no predictive power (R 2 <0). PRIME’s embedding-based clustering identified 3.03% of bat coronavirus sequences as candidates for further experimental prioritization based on their functional similarity to human-infective strains in embedding space, offering a perspective complementary to traditional phylogenetic methods. Conclusion PRIME establishes a new benchmark for the application of PLMs in pathogen surveillance. Our findings demonstrate that state-of-the-art models and fine-tuning, when paired with stratified validation, provide biologically meaningful insights into pathogen evolution and zoonotic risk.
Bacterial infections have been a serious threat to mankind throughout history. Natural antimicrobial peptides (AMPs) and their membrane-disruption mechanism have generated an immense interest in the design and development of synthetic mimetics that could overcome the intrinsic drawbacks of AMPs, such as their susceptibility to proteolytic degradation. Herein, by exploiting the self-assembly and pore-forming capabilities of sequence-defined peptoids, we discovered a new family of low molecular weight peptoid antibiotics that exhibit excellent broad-spectrum activity and high selectivity toward a panel of clinically significant Gram-positive and Gram-negative bacterial strains, including vancomycin-resistant E. faecalis (VREF), methicillin-resistant S. aureus (MRSA), methicillin-resistant S. epidermidis (MRSE), E. coli, P. aeruginosa, and K. pneumoniae. Tuning peptoid sidechain chemistry and structure enabled us to tune the efficacy of antimicrobial activity. Mechanistic studies using Transmission Electron Microscopy (TEM), bacterial membrane depolarization and lysis, and time-kill kinetics assays along with molecular dynamics simulations reveal that these peptoids kill both Gram-positive and Gram-negative bacteria through a membrane-disruption mechanism. In conclusion, these robust and biocompatible peptoid-based antibiotics can provide a valuable tool for combating the emerging drug resistance.
When materials are deformed at extreme strain rates, >10 6 s -1 , a counterintuitive mechanical response is seen where the strength and hardness of pure metals increases with increasing temperature. This anti-thermal hardening is due to dislocations meeting resistance to their motion from phonons in the crystal lattice. However, here, using optically-driven microballistic impact testing to measure dynamic strength and hardness, we show that when the composition is systematically varied away from high purity, the mechanical response of metals transitions from phonon drag of dislocations back to thermally activated pinning of dislocations, even at the highest strain rates. This boundary from “hotter-is-stronger” to “hotter-is-softer” is observed and mapped for nickel, titanium and gold. Furthermore, the ability to tune between deformation mechanisms with very different temperature dependencies speaks to new directions for alloy design in extreme conditions.
Converting measurements of ice-sheet surface elevation change to mass change requires measurements of accumulation and knowledge of the evolution of the density profile in the firn. Most firn-densification models are tuned using measured depth-density profiles, a method which is based on an assumption that the density profile in the firn is invariant through time. Here we present continuous measurements of firn-compaction rates in 12 boreholes near the South Pole over a two-year period. To our knowledge, these are the first continuous measurements of firn compaction on the Antarctic Plateau. We use the data to derive a new firn-densification algorithm framed as a constitutive relationship. We also compare our measurements to compaction rates predicted by several existing firn densification models. Results indicate that an activation energy of 60 kJ mol (−1), a value within the range used by current models, best predicts the seasonal cycle in compaction rates on the Antarctic Plateau. Our results suggest models can predict firn-compaction rates with at best 7% uncertainty and cumulative firn compaction on a two year timescale with at best 8% uncertainty.
The severe, long-lasting harm caused by plastic pollution to marine ecosystems and coastal economies has led to the development of biodegradable plastics; however, their limited decomposition in marine environments remains a challenge. Here, technologies are presented for creating 3D-bioprinted living materials as a proof of concept for bioplastic degradation, with specific use in marine environments. The approach developed here integrates the halotolerant bioplastic-degrading bacterium Bacillus sp. NRRL B- 14911 into alginate-based bio-ink to print an engineered living material (ELM) termed a “bio-sticker.” Quantification of bacteria viability reveals that bioprinted marine bacteria survive within biostickers for more than 3 weeks. The rate at which the biostickers degrade the bioplastic polyhydroxybutyrate (PHB) can be tuned by altering biosticker biomass concentration, bioplastic concentration, or incubation temperature. Biostickers that are transferred to a different PHB sample still retain high biodegradation activity, demonstrating their reusability. Strain sweep oscillatory tests demonstrate that the biostickers display predominantly viscoelastic behavior. Monotonic tensile tests indicate that the elastic modulus and the adhesion of the biostickers are not negatively impacted by bacteria growth or incubation temperature. This work paves the way for the development of ELMs to facilitate the inclusion of bioplastics within the blue economy, promoting the emergence of more sustainable and ecofriendly materials.
Spherical and hollow molecular cages based on planar triazine (C 3 N 3 ) hubs and aromatic phenylene connectors have been developed. The cages exhibit topologies akin to C 20 , C 60 , and C 70 fullerenes with diameters that range from 2.3 to 4.9 nm. Apertures into the cage interiors are tuned by varying the aromatic connectors situated between the C 3 N 3 -units. The stabilities of the C 3 N 3 cages increase with size owing to reduced bending strain of planar nodes and connectors that make up the spherical aromatic networks. Doping of the cages with Li + reveals the capacity of the cages for significant adsorption of gaseous H 2 and CO 2 . The design of graphene-like spherical cages is also discussed.
We present a study directly measuring the electron-beam-induced plasticity of amorphous Al 2 O 3 coatings. Core–shell nanostructures are employed as small-scale model systems for two-dimensional coatings made by atomic layer deposition (ALD). Copper nanowires (NWs) are used as substrates for ALD deposition, representing a model system for interconnects commonly found in integrated circuits. Experiments are performed in situ in a transmission electron microscope (TEM) and further analyzed with electron energy loss spectroscopy (EELS). Our in situ TEM tensile experiments reveal the highly plastic behavior of the ALD shell, which withstands a maximum strain of 188%. Comparable samples under beam-off conditions show a brittle fracture, which underlines the effect of electron irradiation. The electron-beam-activated bond switching within the amorphous network enables compensation of the applied tensile strain, leading to viscous flow. By incorporating an intermediate nanocrystalline layer within the Al 2 O 3 shell, the plasticity is suppressed and brittle fracture occurs. This work directly demonstrates the tuning of mechanical properties in amorphous ALD structures through electron irradiation.
Many research groups have considered whether decreasing photosynthetic antenna content in cyanobacteria can improve photosynthetic oxygen evolution and biomass accumulation. In this work, we describe a genetic strategy for truncating light harvesting antennae based on engineered alterations in the expression of NblA, a native protein naturally used by cyanobacteria to disassemble phycobilisomes antennae in response to environmental changes. We show that if enforced overexpression is fine-tuned, it is possible to realize gains in photosynthesis in a model cyanobacterium Synechococcus elongatus PCC 7942. We also show that antennae truncation helps protect cells from photodamage and that a strain overexpressing NblA can outcompete wild type in a mixed population. We propose approaches for future applications of these findings.
To advance a strategy of polymer-to-polymer upcycling of waste polyolefin by dehydrogenation then functionalization, we report successful hydroesterification of polycyclooctene (PCOE), an analogue for partially unsaturated polyethylene. Here, we convert PCOE to a linear analog for poly(ethylene-co-ethyl acrylate) (EEA) across a range of ethyl acrylate incorporations (0 to 18 mol % of ethylene units). The ester incorporation was well controlled by reaction time, and the remaining C=C bonds were subsequently hydrogenated. Here, the bulky ethyl acrylate groups did not incorporate into orthorhombic PE crystals, decreasing the crystallinity, crystallite size, and melting temperature with increasing functionalization. Additionally, hydroesterification tuned the dynamic mechanical properties, decreasing both the glass transition temperature and the storage modulus in the rubbery regime with greater functionalization. The linear EEA analogs reported here achieve remarkable extensibility (strain > 4000%) and high toughness, comparable to commercial random and branched EEA. Ultimately, we demonstrate successful conversion of an analogue to dehydrogenated PE to a linear EEA with favorable mechanical properties.
Biomimetic surface coatings based on plant polyphenols and catecholamines have been used broadly in a variety of applications. However, the lack of a rational cost-effective platform for screening these coatings and their properties limits the true potential of these functional materials to be unleashed. Here, we investigated the oxidation behavior and coating formation ability of a library consisting of 45 phenolic compounds and catecholamines. UV–vis spectroscopy demonstrated significant acceleration of oxidation and polymerization under UV irradiation. We discovered that several binary mixtures resulted in non-additive behavior (synergistic or antagonistic effect) yielding much thicker or thinner coatings than individual compounds measured by ellipsometry. To investigate the properties of coatings derived from new combinations, we used a miniaturized high-throughput strategy to screen 2,532 spots coated with single, binary, and ternary combinations of coating precursors in one run. We evaluated the use of machine learning models to learn the relation between the chemical structure of the precursors and the thickness of the nanocoatings. Formation and stability of nanocoatings were investigated in a high-throughput manner via discontinuous dewetting. 30 stable combinations (hits) were used to tune the surface wettability and to form water droplet microarray and spot size gradients of water droplets on the coated surface. No toxicity was observed against eukaryotic HeLa cells and Pseudomonas aeruginosa (strain PA30) bacteria after 24 h incubation at 37 C. The strategy introduced here for high-throughput screening of nanocoatings derived from combinations of coating precursors enables the discovery of new functional materials for various applications in science and technology in a cost-effective miniaturized manner.