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Auricular reconstruction in children with microtia is one of the more complex procedures in plastic surgery. Obtaining sufficient native material to build an ear requires harvesting large fragments of rib cartilage in children. Herein, we investigated how to optimize autologous chondrocyte isolation, expansion and re-implantation using polyglycolic acid (PGA) scaffolds for generating enough cartilage to recapitulate a whole ear starting from a small ear biopsy. Ear chondrocytes isolated from human microtia subjects grew slower than microtia rib or healthy ear chondrocytes and displayed a phenotypic shift due to the passage number. Rabbit ear chondrocytes co-cultured with mesenchymal stem cells (MSC) at a 50 : 50 ratio recapitulated the cartilage biological properties in vitro. However, PGA scaffolds with different proportions of rabbit chondrocytes and MSC did not grow substantially in two months when subcutaneously implanted in immunosuppressed mice. In contrast, rabbit chondrocyte-seeded PGA scaffolds implanted in immunocompetent rabbits formed a cartilage 10 times larger than the original PGA scaffold. This cartilage mimicked the biofunctional and mechanical properties of an ear cartilage. These results indicate that autologous chondrocyte-seeded PGA scaffolds fabricated following our optimized procedure have immense potential as a solution for obtaining enough cartilage for auricular reconstruction and opens new avenues to redefine autologous cartilage replacement., European Regional Development Fund; Instituto de Salud Carlos III; Ministerio de Ciencia e Innovación; National Institutes of Health

A planar two-dimensional computational analysis is presented to qualify traditional and fractal vane-in-cup geometries for accurate rheometry of simple viscoplastic fluids with and without slip. Numerical simulations based on an adaptive augmented Lagrangian scheme are used to study the two-dimensional flow field of yield-stress fluids within and around vane tools with N=3 to 24 arms for a wide range of Bingham numbers, B (i.e. the ratio of the yield stress over the characteristic viscous stress). This allows for accurate calculations of the velocity and stress fields around vanes with various geometries, as well as direct comparison to experimental observations of the output torque measured by a rheometer, revealing sources of variation and error. We describe the impact of the vane structure on the fluid velocity field, from few-arm cruciform vanes (N < 6) that significantly perturb the flow away from ideal azimuthal kinematics, to many-arm fractal vanes (N > 12) in which the internal structural features are successfully ``cloaked" by a yield surface. This results in the shearing of an almost-circular ring of viscoplastic fluid that is indistinguishable from the annular ring of fluid deformed around a slip-free rotating cylindrical bob and leads to more accurate rheometric measurements of the material flow curve. Moreover, in direct comparison with data from previous literature, we show that slip conditions on the vane surface do not impact the velocity field or measured overall torque T, whereas slip conditions on the smooth outer wall have significant impact on data, even when using a vane geometry. Finally, we describe the impact of vane topography and Bingham number, B, on the measured torque and rheometric accuracy of vane-in-cup geometries for ``simple" (inelastic) yield-stress fluids described by either the Bingham plastic or Herschel-Bulkley constitutive model.

Crystal nucleation and growth is a fundamental pillar of materials design. To advance our understanding of the underlying mechanisms, in situ visual observation plays an important role by providing dynamic information unavailable through conventional postgrowth analysis. Such information includes nucleation and growth rates, diffusion phenomena, phase transformation kinetics, strain relaxation mechanisms, and defect formation. Here, we review the contributions of ultra-high vacuum transmission electron microscopy (UHV-TEM) to our = understanding of dynamic crystal growth phenomena. We describe the vacuum, sample handling, and deposition capabilities essential for quantitative studies of reactive metals and semiconductors, and discuss how these capabilities are achieved while preserving the imaging performance of the microscope. We then show examples of growth processes explored using UHV-TEM, where the high spatial and temporal resolution provides unique insights into nanocrystal nucleation, thin film microstructure evolution, and oxidation in controlled environments. We assess these past accomplishments in the context of recent advances in transmission electron microscopy, discussing how aberration correction, modified sample environments, fast and sensitive detectors, and data science are unlocking powerful opportunities for atomic and temporal resolution measurements using UHV-TEM. We conclude by discussing the challenges and future perspectives for scientific advances using this technique., MIT Energy Initiative, Independent Research Fund Denmark

Consolidating published research on aluminum alloys into insights about microstructure–property relationships can simplify and reduce the costs involved in alloy design. One critical design consideration for many heat-treatable alloys deriving superior properties from precipitation are phases as key microstructure constituents because they can have a decisive impact on the engineering properties of alloys. Here, we present a computational framework for high-throughput extraction of phases and their impact on properties from scientific papers. Our framework includes transformer-based and large language models to identify sentences with phase-property information in papers, recognize phase and property entities, and extract phase-property relationships and their “sentiment.” We demonstrate the application of our framework on aluminum alloys, for which we build a database of 7,675 phase–property relationships extracted from a corpus of almost 5000 full-text papers. We comment on the extracted relationships based on common metallurgical knowledge.

This groundbreaking research delves into the intricate molecular interactions between MXene and trihalomethanes (THs) through a comprehensive theoretical study employing density-functional theory (DFT). Trihalomethanes are common carcinogenic chlorination byproducts found in water sanitation systems. This study focuses on a pristine MXene [Mn+1·Xn] monolayer and its various terminal [Tx] functional groups [Mn+1·XnTx], strategically placed on the surface for enhanced performance. Our investigation involves a detailed analysis of the adsorption energies of THs on different MXene types, with the MXene-Cl layer emerging as the most compatible variant. This specific MXene-Cl layer exhibits remarkable properties, including a total dipole moment (TDM) of 12.443 Debye and a bandgap of 0.570 eV, achieved through meticulous geometry optimization and computational techniques. Notably, THs such as trichloromethane (CHCl3), bromide-chloromethane (CHBrCl2), and dibromochloromethane (CHBr2Cl) demonstrate the highest TDM values, indicating substantial changes in electronic and optical parameters, with TDM values of 16.363, 15.998, and 16.017 Debye, respectively. These findings highlight the potential of the MXene-Cl layer as an effective adsorbent and detector for CHF3, CHClF2, CHCl3, CHBrCl2, and CHBr2Cl. Additionally, we observe a proportional increase in the TDM and bandgap energy, indicative of conductivity, for various termination atom combinations, such as Mxene-O-OH, Mxene-O-F, Mxene-O-Cl, Mxene-OH-F, Mxene-F-Cl, and Mxene-OH-Cl, with bandgap energies measured at 0.734, 0.940, 1.120, 0.835, and 0.927 eV, respectively. Utilizing DFT, we elucidate the adsorption energies of THs on different MXene surfaces. Our results conclusively demonstrate the significant influence of the termination atom nature and quantity

Understanding lattice deformations is crucial in determining the properties of nanomaterials, which can become more prominent in future applications ranging from energy harvesting to electronic devices. However, it remains challenging to reveal unexpected deformations that crucially affect material properties across a large sample area. Here, we demonstrate a rapid and semi-automated unsupervised machine learning approach to uncover lattice deformations in materials. Our method utilizes divisive hierarchical clustering to automatically unveil multi-scale deformations in the entire sample flake from the diffraction data using four-dimensional scanning transmission electron microscopy (4D-STEM). Our approach overcomes the current barriers of large 4D data analysis without a priori knowledge of the sample. Using this purely data-driven analysis, we have uncovered different types of material deformations, such as strain, lattice distortion, bending contour, etc., which can significantly impact the band structure and subsequent performance of nanomaterials-based devices. We envision that this data-driven procedure will provide insight into materials’ intrinsic structures and accelerate the discovery of materials.

Granular hydrogel matrices have emerged as promising candidates for cell encapsulation, bioprinting, and tissue engineering. However, it remains challenging to design and optimize these materials given their broad compositional and processing parameter space. Here, we combine experimentation and computation to create granular matrices composed of alginate-based bioblocks with controlled structure, rheological properties, and injectability profiles. A custom machine learning pipeline is applied after each phase of experimentation to automatically map the multidimensional input-output patterns into condensed data-driven models. These models are used to assess generalizable predictability and define high-level design rules to guide subsequent phases of development and characterization. Our integrated, modular approach opens new avenues to understanding and controlling the behavior of complex soft materials.

Heterogeneous integration of single-crystal materials offers great opportunities for advanced device platforms and functional systems1. Although substantial efforts have been made to co-integrate active device layers by heteroepitaxy, the mismatch in lattice polarity and lattice constants has been limiting the quality of the grown materials2. Layer transfer methods as an alternative approach, on the other hand, suffer from the limited availability of transferrable materials and transfer-process-related obstacles3. Here, we introduce graphene nanopatterns as an advanced heterointegration platform that allows the creation of a broad spectrum of freestanding single-crystalline membranes with substantially reduced defects, ranging from non-polar materials to polar materials and from low-bandgap to high-bandgap semiconductors. Additionally, we unveil unique mechanisms to substantially reduce crystallographic defects such as misfit dislocations, threading dislocations and antiphase boundaries in lattice- and polarity-mismatched heteroepitaxial systems, owing to the flexibility and chemical inertness of graphene nanopatterns. More importantly, we develop a comprehensive mechanics theory to precisely guide cracks through the graphene layer, and demonstrate the successful exfoliation of any epitaxial overlayers grown on the graphene nanopatterns. Thus, this approach has the potential to revolutionize the heterogeneous integration of dissimilar materials by widening the choice of materials and offering flexibility in designing heterointegrated systems.

Sr(Ti,Fe)O3−y perovskite solid solutions are relevant functional materials for energy conversion and electronic devices such as solid oxide fuel and photoelectrochemical cells, electrolyzers, oxygen sensors, resistive random access memories or synaptic transistors. The Raman spectra and vibrational characteristics of the Sr(Ti,Fe)O3−y materials class are suitable for describing their defect chemistry and the iron valence state, which governs a multitude of its mixed ionic–electronic transport and other characteristics. We synthesize a standard range of compositions containing 1–75 mol% of iron including the end members in the form of macrocrystalline bulk pellets, nanocrystalline poly- and single crystalline thin films. Through the change in both iron substitution level and microstructure, we directly see the effect of defect chemistry such as its phase, transition metal ion valence and oxygen nonstoichiometry on the Raman spectra. These are discussed in terms of in and ex situ experiments under oxidizing/reducing atmosphere. In contrast to long range structural X-ray diffraction measurements, Raman spectroscopy provides valuable insights into oxygen vacancy ordering and oxygen nonstoichiometry for the Sr(Ti,Fe)O3−y material class., Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

The design of soft magnetic hydrogels with high concentrations of magnetic particles is complicated by weak retention of the iron oxide particles in the hydrogel scaffold. Here, we propose a design strategy that circumvents this problem through the in situ mineralization of iron oxide nanoparticles within polymer hydrogels functionalized with strongly iron-coordinating nitrocatechol groups. The mineralization process facilitates the synthesis of a high concentration of large iron oxide nanoparticles (up to 57 wt % dry mass per single cycle) in a simple one-step process under ambient conditions. The resulting hydrogels are soft (kPa range) and viscoelastic and exhibit strong magnetic actuation. This strategy offers a pathway for the energy-efficient design of soft, mechanically robust, and magneto-responsive hydrogels for biomedical applications.

Atomic vibrations influence a variety of phenomena in solids and molecules, ranging from thermal transport to chemical reactions. These vibrations can be decomposed into normal modes, often known as phonons, which are collective motions of atoms vibrating at certain frequencies; this provides a rigorous basis for understanding atomic motion and its effects on material phenomena, since phonons can be detected and excited experimentally. Unfortunately, traditional theories such as the phonon gas model do not allow for the general study of vibrational modes since they only apply to ideal crystals where modes have a wave-like characteristic. Traditional computational methods based on molecular dynamics (MD) simulations allow for the study of phonons in more general systems with disorder, where the modes are less wave-like, but traditional methods do not simulate mode interactions and energy transfer between modes. Here we present, for the first time, a theory and massively parallel open-source software for modeling vibrational modes and simulating their interactions, or energy transfers, in large systems (>103 atoms) using MD. This is achieved by rewriting the atomic equations of motion in mode coordinates, from which analytical expressions for anharmonic mode coupling constants arise. Hamiltonian mechanics then provides a simple expression for calculating power transfer between modes. As a simple application of this theory, we perform MD simulations of phonon-interface scattering in a silicon–germanium superlattice and show the various pathways of energy transfer that occur. We also highlight that while many interaction pathways exist, only a tiny fraction of these pathways transfer significant amounts of energy, which is surprising. The approach allows for the prediction and simulation of mode/phonon interactions, thus unveiling the real-time dynamics of phonon behavior and energy transport.

To describe a new method for the automatic generation of process parameters for fused filament fabrication (FFF) across varying machines and materials. We use an instrumented extruder to fit a function that maps nozzle pressures across varying flow rates and temperatures for a given machine and material configuration. We then develop a method to extract real parameters for flow rate and temperature using relative pressures and temperature offsets. Our method allows us to successfully find process parameters, using one set of input parameters, across all of the machine and material configurations that we tested, even in materials that we had never printed before. Rather than using direct parameters in FFF printing, which is time-consuming to tune and modify, it is possible to deploy machine-generated data that captures the fundamental phenomenology of FFF to automatically select parameters.

Magic-angle twisted bilayer graphene, consisting of two graphene layers stacked at a special angle, exhibits superconductivity due to the maximized density of states at the energy of the flat band. Generally, experiments on twisted bilayer graphene have been performed using micrometer-scale samples. Here we report the fabrication of twisted bilayer graphene with an area exceeding 3 × 5 mm2 by transferring epitaxial graphene onto another epitaxial graphene, and observation of a flat band and large bandgap using angle-resolved photoemission spectroscopy. Our results suggest that the substrate potential induces both the asymmetrical doping in large angle twisted bilayer graphene and the electron doped nature of the flat band in magic-angle twisted bilayer graphene.

The integration of metallic contacts with two-dimensional (2D) semiconductors is routinely required for the fabrication of nanoscale devices. However, nanometer-scale variations in the 2D/metal interface can drastically alter the local optoelectronic properties. Here, we map local excitonic changes of the 2D semiconductor MoS2 in contact with Au. We utilize a suspended and epitaxially grown 2D/metal platform that allows correlated electron energy-loss spectroscopy (EELS) and angle resolved photoelectron spectroscopy (nanoARPES) mapping. Spatial localization of MoS2 excitons uncovers an additional EELS peak related to the MoS2/Au interface. NanoARPES measurements indicate that Au–S hybridization decreases substantially with distance from the 2D/metal interface, suggesting that the observed EELS peak arises due to dielectric screening of the excitonic Coulomb interaction. Our results suggest that increasing the van der Waals distance could optimize excitonic spectra of mixed-dimensional 2D/3D interfaces and highlight opportunities for Coulomb engineering of exciton energies by the local dielectric environment or moiré engineering.

Epitaxial lift-off techniques, which aim to separate ultrathin single-crystalline epitaxial layers off of the substrate, are becoming increasingly important due to the need of lightweight and flexible devices for heterogeneously integrated ultracompact semiconductor platforms and bioelectronics. Remote epitaxy is a relatively newly discovered epitaxial lift-off technique that allows substrate-seeded epitaxial growth of ultrathin films through few layers of graphene. This universal epitaxial lift-off technique allows freestanding single-crystal membrane fabrication very quickly at low cost. However, the conventional method of remote epitaxy requires transfer of graphene grown on another substrate to the target single-crystalline substrate, which results in organic and metallic residues as well as macroscopic defects such as cracks and wrinkles, significantly reducing the yield of remote epitaxy. Here, we show that direct growth of thick graphene on the target single-crystalline substrate (SrTiO3 for this study) followed by atomic layer etching (ALE) of the graphene layers create a defect- and residue-free graphene surface for high yield remote epitaxy. We find that the ALE efficiently removes one atomic layer of graphene per cycle, while also clearing multi-dots (clumps of carbon atoms) that form during nucleation of the graphene layers. Our results show that direct-grown graphene on the desired substrate accompanied by ALE might potentially be an ideal pathway toward commercialization of remote epitaxy.

Visual question answering (VQA) is a task that generates or predicts an answer to a question in human language about visual images. VQA is an active field combining two AI branches: NLP and computer vision. VQA in the medical field is still at an early stage, and it needs vast efforts and exploration to reach practical usage. This paper proposes two models that are utilized in the latest vision and NLP transformers that outperform the SOTA and have not yet been utilized in medical VQA. The ELECTRA-base transformer is used for textual feature extraction, whereas SWIN is used for visual feature extraction. In the SOTA medical VQA, selecting the model is based on the model that achieves the highest validation accuracy or the last model in training. The first proposed model, the best-value-based model, is selected based on the highest validation accuracy. The second model, the greedy-soup-based model, uses a greedy soup technique based on the fusion of multiple fine-tuned models to set the model parameters. The greedy soup selects the model parameters by fusing the model parameters that have significant performance on the validation accuracy in training. The greedy-soup-based model outperforms the best-value-based model, and both proposed models outperform the SOTA, which has an accuracy of 83.49%. The greedy-soup-based model is optimized with batch size and learning rate. During the optimization, seven extra models exceed the SOTA accuracy. The best model trained with a learning rate of 1.0×10−4 and batch size 16 achieves an accuracy of 87.41%.

In the last decade, robotic-mediated rehabilitation has emerged as a potential solution to improve repetitive task training. Each device in this field has a unique development history shaped by engineers’ expertise in specific programming languages or platforms. In this work we adopt an approach that tries to abstract from the final implementation with the aim to make control logic more shareable and understandable. The authors will present the outcomes of the application of a Rapid Control Prototyping strategy to an upper-limb robotic exoskeleton. A model-based design approach implemented on a real-time target machine is presented. This modern design approach was explored with several control strategies and was used to test the exoskeleton’s performances. The proposed method highlights how it is possible to develop the entire control architecture in a single programming environment.

The concept of a Deborah number is widely used in the study of viscoelastic materials to represent the ratio of a material relaxation time to the time scale of observation and to demarcate transitions between predominantly viscous or elastic material responses. However, this construct does not help quantify the importance of long transients and nonmonotonic stress jumps that are often observed in more complex time-varying systems. Many of these nonintuitive effects are lumped collectively under the term thixotropy; however, no proper nouns are associated with the key phenomena observed in such materials. Thixotropy arises from the ability of a complex structured fluid to remember its prior deformation history, so it is natural to name the dimensionless group representing such behavior with respect to the ability to remember. In Greek mythology, Mnemosyne was the mother of the nine Muses and the goddess of memory. We, thus, propose the definition of a Mnemosyne number as the dimensionless product of the thixotropic time scale and the imposed rate of deformation. The Mnemosyne number is, thus, a measure of the flow strength compared to the thixotropic time scale. Since long transient responses are endemic to thixotropic materials, one also needs to consider the duration of flow. The relevant dimensionless measure of this duration can be represented in terms of a mutation number, which compares the time scale of experiment/observation to the thixotropic time scale. Collating the mutation number and the Mnemosyne number, we can construct a general two-dimensional map that helps understand thixotropic behavior. We quantify these ideas using several of the simplest canonical thixotropic models available in the literature.

Designing efficient catalysts that possess large number of active sites, high catalytic activity and selectivity while also exhibiting strong antimicrobial activity is a challenging task because of poor control over material fabrication. Therefore, developing new and innovative approaches for the synthesis of catalytic materials is crucial for addressing these challenges. Here, we report the controlled fabrication of GQDs/Y-doped MgO nanoparticles achieved by co doping of yttrium (Y) and graphene quantum dots (GQDs) in magnesium oxide (MgO) based nanostructures (NSs) using the co-precipitation method. The co-doping of GQDs and Y was controlled by manipulating the ratio of precursors where introduction of GQD resulted in higher surface area and enhanced conductivity while the doping of Y enhanced the number of active sites in the final product. The GQDs/Y-doped MgO exhibited an average particle size of similar to 50 nm and a bandgap of 3.6 eV. Owing to these excellent characteristics, the GQDs/Y-doped MgO was utilized as a catalyst for treatment of the organic pollutants from water as well as antibacterial activity. The modified GQDs/Y-doped MgO nanostructure exhibited excellent activity of over 99.9 % for dye removal and versatility in a broad range of pH which clearly indicated the application in a range of different environments. Furthermore, the GQDs/Y-doped MgO exhibited excellent antibacterial activity against Escherichia Coli (E. Coli) bacteria. To gain further insights into the origins of this excellent activity response, the molecular docking simulations (MDS) is utilized against DNA gyrase and FabI (two enzymes critical to nucleic acid and fatty acid biosynthesis, respectively), to uncover the mechanism behind the observed antibacterial effects. In summary, the

The present paper reports a remote carbon-to-carbon boryl migration via an intramolecular 1,4-B/Cu shift, which establishes an in situ stereospecific electrophilic trap on the alkene moiety. The synthetic application is developed to prepare functionalized cyclopentenes by means of a palladium-catalyzed regioselective intramolecular coupling that completes a strategic cyclopropanation and generates valuable structural bicyclic systems. The mechanism is characterized by DFT (density functional theory) calculations which showed that the 1,4-migration proceeds through an intramolecular, nucleophilic attack of the copper-alkyl moiety on the boron atom bonded to the C(sp2), leading to a 5-membered boracycle structure. The computation of the 1,3- and 1,4-B/Cu shifts is also compared as is the impact of the endo- or exocyclic alkene on the reaction kinetics.The intramolecular 1,4-B/Cu shift justifies the observed remote carbon-to-carbon boryl migration, which makes stereoselective electrophilic trapping on the alkene moiety possible. Subsequent palladium-catalyzed regioselective intramolecular coupling enables functionalized cyclopentenes to be prepared that complete strategic cyclopropanation and deliver structurally valuable bicyclic systems. DFT mechanistic studies show that remote boryl migration occurs efficiently through 5-membered boracycle intermediates. image

Electrohydrodynamic (EHD) jet printing of solvent-based inks or melts allows for the producing of polymeric fiber-based two- and three-dimensional structures with sub-micrometer features, with or without conductive nanoparticles or functional materials. While solvent-based inks possess great material versatility, the stability of the EHD jetting process using such inks remains a major challenge that must be overcome before this technology can be deployed beyond research laboratories. Herein, we study the parameters that affect the stability of the EHD jet printing of polyethylene oxide (PEO) patterns using solvent-based inks. To gain insights into the evolution of the printing process, we simultaneously monitor the drop size, the jet ejection point, and the jet speed, determined by superimposing a periodic electrostatic deflection. We observe printing instabilities to be associated with changes in drop size and composition and in the jet's ejection point and speed, which are related to the evaporation of the solvent and the resulting drying of the drop surface. Thus, stabilizing the printing process and, particularly, the drop size and its surface composition require minimizing or controlling the solvent evaporation rate from the drop surface by using appropriate solvents and by controlling the printing ambient. For stable printing and improved jet stability, it is essential to use polymers with a high molecular weight and select solvents that slow down the surface drying of the droplets. Additionally, adjusting the needle voltages is crucial to prevent instabilities in the jet ejection mode. Although this study primarily utilized PEO, the general trends observed are applicable to other polymers that exhibit similar interactions between solvent and polymer.

Carbon-based nanomaterials are key to developing high-performing electrochemical sensors with improved sensitivity and selectivity. Nonetheless, limitations in their fabrication and integration into devices often constrain their practical applications. Moreover, carbon nanomaterials-based electrochemical devices still face problems such as large background currents, poor stability, and slow kinetics. To advance towards a new class of carbon nanostructured electrochemical transducers, we propose the in-situ polymerization and carbonization of furfuryl alcohol (FA) on porous silicon (pSi) to produce a tailored and highly stable transducer. The thin layer of polyfurfuryl alcohol (PFA) that conformally coats the pSi scaffold transforms into nanoporous carbon when subjected to pyrolysis above 600 °C. The morphological and chemical properties of PFA-pSi were characterized by scanning electron microscopy, and Raman and X-ray photoelectron spectroscopies. Their stability and electrochemical performance were investigated by cyclic voltammetry and electrochemical impedance spectroscopy in [Fe(CN)6]3-/4-, [Ru(NH3)6]2+/3+, and hydroquinone. PFA-pSi showed superior electrochemical performance compared to screen-printed carbon electrodes while also surpassing glassy carbon electrodes in specific aspects. Besides, PFA-pSi has the additional advantage of easy tuning of the electroactive surface area. To prove its potential for biosensing purposes, a DNA sensor based on quantifying the partial pore blockage of the pSi upon target hybridization was built on PFA-pSi. The sensor showed a limit of detection of 1.4 pM, outperforming other sensors based on the same sensing mechanism.

Cyanide salts are currently used as leaching agents in gold extraction processes despite their toxicity. Thiosulfate is a greener choice, but its employment is constrained by the difficulty at recovering gold thiosulfate from the leachate using activated carbon, which in contrast, works well for gold-cyanide adsorption. Aiming to solve this problem, activated carbon has been covalently functionalized with thiol groups (-SH) through a peptide bond formation with cysteamine, as thiol-carrier molecule. The functionalized carbon accomplishes up to 100% Au recovery (with 2 and 25 ppm Au solution) in 8 h contact and its performance seems independent on the solution's pH. In-depth solid characterization techniques (XPS, TOF-SIMS, FTIR, PXRD, TEM, N₂ physisorption, elemental analysis) have been used to unravel the interactions between Au thiosulfate and thiol functions and two different gold adsorption mechanisms have been demonstrated: under acid conditions, the formation of Au1+- S chains has been proven. Under basic conditions, Au⁰ species have been detected in addition to Au1+- S chains. Elution of the gold loaded samples has been accomplished at a 71% level using Na₂S₂O₃ and NH₄OH as eluents.

The production of dimethyl carbonate (DMC) from CO2 and methanol (MeOH) is an attractive route for CO2 capture and utilization. In this process, the separation of DMC from the reaction medium is critical to maximize the conversion of CO2. However, DMC and MeOH form an azeotropic mixture that is difficult to separate. This work investigates the possibility of using task-specific ionic liquids (TSILs) in the form of supported ionic liquid membranes (SILMs) to separate and purify DMC by using pervaporation. Two tertiary amine ILs, i.e., 1-octyl-3-methylimidazolium bromide ([Omim][Br]) and 1-octyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide ([Omim][NTf2]), and one cyclic quaternary ionic liquid, i.e., 1-octyl-1,4-diazabicyclo[2.2.2]octanium bromide ([ODABCO][Br]), were prepared. The structure and purity of the synthesized ILs were confirmed by NMR and FTIR, and the as-synthesized ILs along with one commercial quaternary ammonium IL, tetrabutylammonium bromide ([TBA][Br]), were further characterized using TGA/DSC. SEM-EDX, tensile tests and stability tests were also performed to characterize the SILMs. During the pervaporation experiments, the SILMs showed an initial decrease in DMC and MeOH permeance over time, followed by a gradual stabilization, with a relatively stable DMC/MeOH selectivity as pure liquids. In addition, an increase in temperature is shown to have negative effect on DMC and MeOH permeance because sorption, which is an exothermic process, governed the transport of molecules across the membrane. The studied SILMs exhibited higher selectivity at low temperatures, especially at 30 °C. Furthermore, the COSMO-RS model provided insights of the effect of IL structures on the separation of DMC from MeOH at molecular level.

A conceptual challenge toward more versatile direct methanol fuel cell (DMFC) is the design of a single material electrocatalyst with high activity and durability for both oxygen reduction reaction (ORR) and methanol oxidation reaction (MOR). This requires to conciliate methanol tolerance not to hinder ORR at the cathode with a good MOR activity at the anode. This is especially incompatible with Pt materials. We tackled this challenge by deriving a supramolecular concept where surface-grafted molecular ligands regulate the Pt-catalyst reactivity. ORR and MOR activities of newly reported Pt-calix[4]arenes nanocatalysts (PtCF3NPs/C) are compared to commercial benchmark PtNPs/C. PtCF3NPs/C exhibit a remarkable methanol tolerance without losing the MOR reactivity along with outstanding durability and chemical stability. Beyond designing single-catalyst material, operable in DMFC cathodic and anodic compartments, the results highlight a promising strategy for tuning interfacial properties.

Identifcation of ontogenetic age classes plays an important role in the felds of zoology, palaeontology and archaeology, where accurate age classifcations of (sub)fossil remains are a crucial component for the reconstruction of past life. Textural ageing—the identifcation of age-related bone surface textures—provides a size-independent method for age assessment of vertebrate material. However, most of the work so far is limited to qualitative results. While qualitative approaches provide helpful insights on textural ageing patterns, they are heavily subject to observer bias and fall short of quantitative data relevant for detailed statistical analyses and cross-comparisons. Here, we present a pilot study on the application of 3D surface digital microscopy to quantify bone surface textures on the long bones of the grey heron (Ardea cinerea) and the Canada goose (Branta canadensis) using internationally verifed roughness parameters. Using a standardised measuring protocol, computed roughness values show a strong correlation with qualitative descriptions of textural patterns. Overall, higher roughness values correspond to increased numbers of grooves and pits and vice versa. Most of the roughness parameters allowed distinguishing between diferent ontogenetic classes and closely followed the typical sigmoidal animal growth curve. Our results show that bone texture quantifcation is a feasible approach to identifying ontogenetic age classes.

We provide a canonical introduction to dual-junction-functionality associative polymer networks, which combine high and low functionality ( f) dynamic cross-link junctions to impart load-bearing, dissipation, and self-repairing ability to the network. This unique type of network configuration offers an alternative to traditional dual-junction networks consisting of covalent and reversible cross-links. The high- f junctions can provide load-bearing abilities similar to a covalent cross-link while retaining the ability to self-repair and concurrently confer stimuli-responsive properties arising from the high- f junction species. We demonstrate the mechanical properties of this design motif using metal-coordinating polymer hydrogel networks, which are dynamically cross-linked by different ratios of metal nanoparticle (high- f) and metal ion (low- f) cross-link junctions. We also demonstrate the spontaneous self-assembly of nanoparticle-cross-linked polymers into anisotropic sheets, which may be generalizable for designing dual-junction-functionality associative networks with low volume fraction percolated high- f networks.

The aim of this study was to compare bond strength resin composites to porcelain laminate veneers in the indirect repair method to composite resins used in the direct repair method for cases of porcelain veneer fracture of zirconia-based fixed dental prostheses. In the study, the groups were formed with different percentages of areas to be repaired to mimic porcelain fractures in the mouth. The experimental group of veneered zirconia were as follows: Group A = 100% Zr surface; Group B = 70% Zr, 30% porcelain surface; Group C = 50% Zr, 50% porcelain surface; Group D = 30% Zr, 70% porcelain surface; Group E = 100% porcelain surface. The repairs of the specimens were made using composite resin systems in half of the groups and using porcelain laminate veneers in the other half. Specimens were embedded in acrylic blocks before surface treatments and repairs were applied. After surface conditioning, laminate veneers were applied to the first half of the groups, and composite repair systems were applied to the second half of the groups. After all specimens were aged by thermal cycling, their bond strength values were measured using a Universal Testing Machine, and the obtained data were recorded. The specimens were examined with a stereomicroscope and classified according to failure types (adhesive/cohesive/mixed). Bond strength values were evaluated based on independent-samples t-test statistics. According to the comparisons among the groups, the bond strength of the indirect repairs made with the laminate material was higher than the bond strength of the repairs made with the composite. There was a statistically significant difference in favor of the indirect repair groups among all groups except for Group C. The highest bond strength was found in Group A in the indirect repair method, while the lowest bond was found in the direct repair method in Group E. Adhesive failure was mostly seen in the groups that were repaired with the composite.

Piezoelectric nanomaterials have become increasingly popular in the field of biomedical applications due to their high biocompatibility and ultrasound-mediated piezocatalytic properties. In addition, the ability of these nanomaterials to disaggregate amyloid proteins, which are responsible for a range of diseases resulting from the accumulation of these proteins in body tissues and organs, has recently gained considerable attention. However, the use of nanoparticles in biomedicine poses significant challenges, including targeting and uncontrolled aggregation. To address these limitations, our study proposes to load these functional nanomaterials on a multifunctional mobile microrobot This microrobot is designed by coating magnetic and piezoelectric barium titanate nanoparticles on helical biotemplates, allowing for the combination of magnetic navigation and ultrasound-mediated piezoelectric effects to target amyloid disaggregation. Our findings demonstrate that acoustically actuated PiezoBOTs can effectively reduce the size of aggregated amyloid proteins by over 80% in less than 10 minutes by shortening and dissociating constituent amyloid fibrils. Moreover, the PiezoBOTs can be easily magnetically manipulated to actuate the piezocatalytic nanoparticles to specific amyloidosis-affected tissues or organs, minimizing side effects. These biocompatible PiezoBOTs offer a promising non-invasive therapeutic approach for amyloidosis diseases by targeting and breaking down protein aggregates at specific organ or tissue sites.

Speech elicits brain activity time-locked to its amplitude envelope. The resulting speech-brain synchrony (SBS) is thought to be crucial to speech parsing and comprehension. It has been shown that higher speech-brain coherence is associated with increased speech intelligibility. However, studies depending on the experimental manipulation of speech stimuli do not allow conclusion about the causality of the observed tracking. Here, we investigate whether individual differences in the intrinsic propensity to track the speech envelope when listening to speech-in-quiet is predictive of individual differences in speech-recognition-in-noise, in an independent task. We evaluated the cerebral tracking of speech in source-localized magnetoencephalography, at timescales corresponding to the phrases, words, syllables and phonemes. We found that individual differences in syllabic tracking in right superior temporal gyrus and in left middle temporal gyrus (MTG) were positively associated with recognition accuracy in an independent words-in-noise task. Furthermore, directed connectivity analysis showed that this relationship is partially mediated by top-down connectivity from premotor cortex—associated with speech processing and active sensing in the auditory domain—to left MTG. Thus, the extent of SBS—even during clear speech—reflects an active mechanism of the speech processing system that may confer resilience to noise.

We show how to combine in a natural way (i.e., without any test nor switch) the conservative and non-conservative formulations of an hyperbolic system that has a conservative form. This is inspired from two different classes of schemes: the residual distribution one (Abgrall in Commun Appl Math Comput 2(3): 341–368, 2020), and the active flux formulations (Eyman and Roe in 49th AIAA Aerospace Science Meeting, 2011; Eyman in active flux. PhD thesis, University of Michigan, 2013; Helzel et al. in J Sci Comput 80(3): 35–61, 2019; Barsukow in J Sci Comput 86(1): paper No. 3, 34, 2021; Roe in J Sci Comput 73: 1094–1114, 2017). The solution is globally continuous, and as in the active flux method, described by a combination of point values and average values. Unlike the “classical” active flux methods, the meaning of the point-wise and cell average degrees of freedom is different, and hence follow different forms of PDEs; it is a conservative version of the cell average, and a possibly non-conservative one for the points. This new class of scheme is proved to satisfy a Lax-Wendroff-like theorem. We also develop a method to perform non-linear stability. We illustrate the behaviour on several benchmarks, some quite challenging.

Featured Application: Electrical and electronic devices that experience long-term vibrations. Electrical boards, also called printed circuit boards, constitute the basis of most electronic devices. These boards are mainly fabricated of thin copper films bonded to fiber epoxy laminates, such as FR4. Being the most important functional component of these devices, they sometimes undergo mechanical stresses such as shock and vibration during transport and operation that can induce electrical failure and malfunction; hence, studies addressing the effects of vibrations on their electrical properties have important applications. In this paper, small cantilever samples made of bare copper bonded to FR4 with three isolated rectangular zones were studied to analyze, for the first time, variations in electrical properties such as sheet resistance and resistivity before and after 200 k, 500 k, and 800 k vibration cycles at three different temperatures (25, 35, and 45 °C). A significant rise in resistance equivalent to 1657% of the initial value was observed from 0 to 800 k vibration cycles. These changes were accompanied by a 95% decrease in conductivity, from 4.1 × 107 to 2.3 × 106 S/m, whereas very little change in the electrical properties was observed due to temperature rise. Surface analysis by ESEM showed cracks ~1 µm in width and several millimeters in length with a crack density of ~8 cracks per mm after 800 k cycles. The surface composition (100% copper) was not altered even upon a high number of vibration cycles, and static drop contact angle measurements of 117–119 degrees indicated an increase in the hydrophobicity of the surface attributed to increased surface roughness and the accumulation of very small air bubbles on the cracks.

To solve real-life problems for different smart city applications, using deep Neural Network, such as parking occupancy detection, requires fine-tuning of these networks. For large parking, it is desirable to use a cenital-plane camera located at a high distance that allows the monitoring of the entire parking space or a large parking area with only one camera. Today’s most popular object detection models, such as YOLO, achieve good precision scores at real-time speed. However, if we use our own data different from that of the general-purpose datasets, such as COCO and ImageNet, we have a large margin for improvisation. In this paper, we propose a modified, yet lightweight, deep object detection model based on the YOLO-v5 architecture. The proposed model can detect large, small, and tiny objects. Specifically, we propose the use of a multi-scale mechanism to learn deep discriminative feature representations at different scales and automatically determine the most suitable scales for detecting objects in a scene (i.e., in our case vehicles). The proposed multi-scale module reduces the number of trainable parameters compared to the original YOLO-v5 architecture. The experimental results also demonstrate that precision is improved by a large margin. In fact, as shown in the experiments, the results show a small reduction from 7.28 million parameters of the YOLO-v5-S profile to 7.26 million parameters in our model. In addition, we reduced the detection speed by inferring 30 fps compared to the YOLO-v5-L/X profiles. In addition, the tiny vehicle detection performance was significantly improved by 33% compared to the YOLO-v5-X profile.

The design of stimuli-responsive lignin nanoparticles (LNPs) for advanced applications has hitherto been limited to the preparation of lignin-grafted polymers in which usually the lignin content is low (<25 wt.%) and its role is debatable. Here, the preparation of O2-responsive LNPs exceeding 75 wt.% in lignin content is shown. Softwood Kraft lignin (SKL) is coprecipitated with a modified SKL fluorinated oleic acid ester (SKL-OlF) to form colloidal stable hybrid LNPs (hy-LNPs). The hy-LNPs with a SKL-OlF content ranging from 10 to 50 wt.% demonstrated a reversible swelling behavior upon O2/N2 bubbling, increasing their size – ≈35% by volume – and changing their morphology from spherical to core-shell. Exposition of hy-LNPs to O2 bubbling promotes a polarity change on lignin-fluorinated oleic chains, and consequently their migration from the inner part to the surface of the particle, which not only increases the particle size but also endows hy-LNPs with enhanced stability under harsh conditions (pH < 2.5) by the hydration barrier effect. Furthermore, it is also demonstrated that these new stimuli-responsive particles as gas tunable nanoreactors for the synthesis of gold nanoparticles. Combining a straightforward preparation with their enhanced stability and responsiveness to O2 gas these new LNPs pave the way for the next generation of smart lignin-based nanomaterials.

This work produces a unique microfluidic device that acts as a “lab on a chip,” conducting separation, mixing, and concentration of microparticles similar to that required by cell sorting flow cytometry applications. The passive two-dimensional device shows to be successful at separating polystyrene (PS) beads between 5 and 20 µm in diameter, mixing them with an external media, and concentrating them by 250% continuously with minimal sample preparation, while still being inexpensive, and effective. By implementing the microfluidic device, the processing steps are done within seconds due to its high throughput of 2 mL min−1, wherein different hydrodynamic phenomena such as Dean's forces, inertial lift forces, and enhanced diffusion are taken advantage of.

Morphological integration and modularity refer to the degree of covariation between the different components of an anatomical structure. Modularity refers to structures that have components which covary strongly, but at the same time are relatively independent. Integration refers to the coordinated variation of the components of a functional anatomical structure. The hindlimb basipodium is a complex functional structure. The integration of its parts must arise from a coordinated development and functionality. Our objective in this study was to study the levels of integration of two modules on the calcaneum in domestic sheep. The calcaneum develops from two different centres. One gives rise to the body and its process while the other gives rise to the distal half of the bone. The hypothesis of modularity of two parts of the calcaneum was tested using the Escoufier RV coefficient and an analysis of two blocks of Partial Least Squares. These allowed us to evaluate the level of morphological integration. For this purpose, digital images of the medial aspect of complete calcanea of 47 domestic sheep (Ovis aries) were used. Twenty 2D coordinates of homologous anatomical landmarks (4 for the body and the process and 16 for the distal half of the bone) were collected as morphometric data. These were studied using geometric morphometrics. The results indicated good evidence of modular organization and a medium morphological integration between the two modules. Thus, according to our results, the two modules seem to exist and behave in a rather independent way. They appear to share functions rather than precursors of development. This study is important in order to elucidate the underlying factors in the processes of the development of the sheep calcaneum.

We investigate in-band pumping of a Tm,Ho,Lu:CaGdAlO4 laser using a Raman-shifted Er-fiber laser (1678 nm), in the continuous-wave (CW) and mode-locked (ML) regimes. A maximum output power of 524 mW is obtained in the CW regime with a 5% output coupler at an absorbed pump power of 2.04 W, corresponding to a slope efficiency of 27.9%. A maximum CW wavelength tuning range of 160 nm at the zero level, from 1984 to 2144 nm, is obtained with a 0.2% output coupler. In the ML regime, pumping with 5.5 W (unpolarized), the average output power (0.2% output coupler) reaches 148 mW at a repetition rate of similar to 96 MHz. The output spectrum is centered at 2071.5 nm with a FWHM of 21.5 nm (sigma-polarization). The pulse duration amounts to 218 fs (time-bandwidth product equal to 0.327).

Asphalt is an essential material in the construction of asphalt pavements. Due to its high demand and dependence on petroleum, it is crucial to use greener materials that can fully or partially replace petroleum-based binders. The characteristics of asphalt cause the bio-binder obtained through a hydrothermal liquefaction process from swine manure to have great potential to be used as a modifier due to its similarities with asphalt, contributing to the construction of more sustainable roads. Thus, this paper characterizes an asphalt binder modified with a new bio-binder obtained from swine manure at different rates (0%, 10%, and 20%). Several characterization tests were performed, including penetration, ring and ball, Fraass, viscosity, Cleveland open cup, and the UCL method. Furthermore, the possible leaching of the bio-binder was studied, showing no environmental problems. Results from the rheological tests showed that as the content of bio-binder increases, the softening temperature, Fraass breaking point, and viscosity of the bio-modified asphalt binder decrease, indicating the lower consistency of the bio-modified binder and its greater thermal susceptibility.

Nano/micromotors (NMs) are tiny structures capable of converting various forms of energy into mechanical motion at the micro and nanoscale. These motors operate in environments characterized by low inertia and low Reynolds numbers. The potential applications of NMs are vast, particularly in the fields of biomedicine and environmental science. One of the most intriguing developments in this field is the integration of NMs with surface-enhanced Raman scattering (SERS) spectroscopy. SERS is a powerful analytical technique that enhances the Raman intensity of molecules, allowing for highly sensitive detection and analysis of trace amounts of substances. This integration offers highly precise and localized ultrasensing capabilities. The combination of NMs with SERS can also facilitate real-time imaging inside living organisms. This has immense potential in chemical and cell biology and medical diagnostics and prognosis. Herein this review describes the types of NMs and their fabrication, the incorporation of plasmonic nanostructures, capable of creating strong electromagnetic fields when illuminated by light, which in turn enhances the Raman signals significantly, their applications, and their future prospects in areas such as precision medicine, environmental monitoring, and possibly even in new realms like microscale robotics and targeted therapeutics.This review investigates the synergistic integration of SERS and nano/micromotors, showcasing their combined applications in bioanalytical sensing, environmental monitoring, and nanoscale imaging. Furthermore, future prospects and challenges are discussed, emphasizing the crucial role of ongoing research in fully realizing the potential of SERS and nano/micromotors.image

Mixed zinc-zirconium oxides, ZnZrOx, are highly selective and stable catalysts for CO2 hydrogenation to methanol, a pivotal energy vector. However, their activity remains moderate, and descriptors to design improved systems are lacking. This work applies flame spray pyrolysis (FSP), a one-step and scalable method, to synthesize a series of ZnZrOx catalysts, and systematically compares them to coprecipitated (CP) analogs to establish deeper synthesis-structure-performance relationships. FSP systems (up to 5 mol%) generally display a threefold higher methanol productivity compared to their CP counterparts. In-depth characterization and theoretical simulations show that, unlike CP, FSP maximizes the surface area and formation of atomically dispersed Zn2+ sites incorporated in lattice positions within the ZrO2 surface, which is key to improving performance. Analysis by in situ electron paramagnetic resonance (EPR) spectroscopy reveals that the specific architecture of the flame-made catalyst markedly fosters the generation of oxygen vacancies. Together with surrounding Zn and Zr-O atoms, the oxygen vacancies create active ensembles that favor methanol formation through the formate path while suppressing undesired CO production, as confirmed by kinetic modeling. This study elucidates the nature of active sites and their working mechanism, pushing forward ZnZrOx-catalyzed methanol synthesis by providing a new benchmark for this cost-effective and earth-abundant catalyst family.

Impedance spectroscopy (IS) is an effective characterization technique used to probe and distinguish charge dynamics occurring at different timescales in optoelectronic and electric devices. With the rapid rise of research being conducted on perovskite solar cells (PSCs), IS has significantly contributed to the understanding of their device performance and degradation mechanisms, including metastable effects such as current–voltage hysteresis. The ionic–electronic behavior of PSCs and the presence of a wide variety of perovskite compositions and cell architectures add complexity to the accurate interpretation of the physical processes occurring in these devices. In this review, the most common IS protocols are explained to help perform accurate impedance measurements on PSC devices. It critically reviews the most commonly used equivalent circuits alongside drift-diffusion modeling as a complementary technique to analyze the impedance response of PSCs. As an emerging method for characterizing the interfacial recombination between the perovskite layer and selective contacts, light intensity modulated impedance spectroscopy technique is further discussed. Lastly, important works on the application of IS measurement protocols for PSCs are summarized followed by a detailed discussion, providing a critical perspective and outlook on the growing topic of IS on PSCs.

Biomaterials are omnipresent in today's healthcare services and are employed in various applications, including implants, sensors, healthcare accessories, and drug delivery systems. Unfavorable host immunological responses frequently jeopardize the efficacy of biomaterials. As a result, surface modification has received much attention in controlling inflammatory responses since it helps camouflage the biomaterial from the host immune system, influencing the foreign body response (FBR) from protein adsorption to fibrous capsule formation. Surfaces with controlled nanotopography and chemistry, among other surface modification methodologies, have effectively altered the immune response to biomaterials. However, the field is still in its early stages, with only a few studies showing a synergistic effect of surface chemistry and nanotopography on inflammatory and wound healing pathways. Therefore, this review will concentrate on the individual and synergistic effects of surface chemistry and nanotopography on FBR modulation and the molecular processes known to modulate these responses. This review will also provide insights into crucial research gaps and advancements in various tactics for modulating FBR, opening new paths for future research. This will further aid in improving our understanding of the immune response to biomaterials, developing advanced surface modification techniques, designing immunomodulatory biomaterials, and translating discoveries into clinical applications.

In recent years, an increasing number of diverse Engineered Nano-Materials (ENMs), such as nanoparticles and nanotubes, have been included in many technological applications and consumer products. The desirable and unique properties of ENMs are accompanied by potential hazards whose impacts are difficult to predict either qualitatively or in a quantitative and predictive manner. Alongside established methods for experimental and computational characterisation, physics-based modelling tools like molecular dynamics are increasingly considered in Safe and Sustainability-by-design (SSbD) strategies that put user health and environmental impact at the centre of the design and development of new products. Hence, the further development of such tools can support safe and sustainable innovation and its regulation. This paper stems from a community effort and presents the outcome of a four-year-long discussion on the benefits, capabilities and limitations of adopting physics-based modelling for computing suitable features of nanomaterials that can be used for toxicity assessment of nanomaterials in combination with data-based models and experimental assessment of toxicity endpoints. We review modern multiscale physics-based models that generate advanced system-dependent (intrinsic) or time- and environment-dependent (extrinsic) descriptors/features of ENMs (primarily, but not limited to nanoparticles, NPs), with the former being related to the bare NPs and the latter to their dynamic fingerprinting upon entering biological media. The focus is on (i) effectively representing all nanoparticle attributes for multicomponent nanomaterials, (ii) generation and inclusion of intrinsic nanoform properties, (iii) inclusion of selected extrinsic properties, (iv) the necessity of considerin

To overcome the limitations of ZnO as a photocatalyst, the present work reports a ternary nanocomposite (ZnO–TiO2/rGO) with a high photocatalytic activity under direct natural solar light irradiation. Reduced graphene oxide (rGO) was obtained after bio-reduction of GO using pomegranate peels. Techniques of FE-SEM, TEM, XRD, FTIR, UV–Vis DRS, Raman and PL were used for characterization purpose. The ternary nanocomposite exhibited a high photocatalytic activity towards the degradation of indigo carmine dye, resulting in an efficiency of 92% within 150 min under sunlight illumination. Accordingly, the hybridization of ZnO with TiO2 and rGO improves light absorption, promotes high separation of photogenerated charges, and solves the photocorrosion drawback of ZnO, leading to a better stability and reusability of the nanocomposite. Particularly, the prepared rGO allowed certain hydrophilicity and a better surface hydroxylation. In view of that, a comprehensive photocatalytic mechanism was proposed and discussed, referred to experiments showing the effect of holes and •OH scavengers. The findings revealed that the developed rGO hybridized with ZnO–TiO2 heterojunction can be a promising candidate for removing environmental contaminations using natural solar light.

The need for integrated passive devices (IPDs) emerges from the increasing consumer demand for electronic product miniaturization. Metal-insulator-metal (MIM) capacitors are vital components of IPD systems. Developing new materials and technologies is essential for advancing capacitor characteristics and co-integrating with other electronic passives. Here we present an innovative electrochemical technology joined with the sputter-deposition of Al and Zr layers to synthesize novel planar nanocomposite metal-oxide dielectrics consisting of ZrO2 nanorods self-embedded into the nanoporous Al2O3 matrix such that its pores are entirely filled with zirconium oxide. The technology is utilized in MIM capacitors characterized by modern surface and interface analysis techniques and electrical measurements. In the 95-480 nm thickness range, the best-achieved MIM device characteristics are the one-layer capacitance density of 112 nF center dot cm(-2), the loss tangent of 4 center dot 10(-3) at frequencies up to 1 MHz, the leakage current density of 40 pA center dot cm(-2), the breakdown field strength of up to 10 MV center dot cm(-1), the energy density of 100 J center dot cm(-3), the quadratic voltage coefficient of capacitance of 4 ppm center dot V-2, and the temperature coefficient of capacitance of 480 ppm center dot K-1 at 293-423 K at 1 MHz. The outstanding performance, stability, and tunable capacitors' characteristics allow for their application in low-pass filters, coupling/decoupling/bypass circuits, RC oscillators, energy-storage devices, ultrafast charge/discharge units, or high-precision analog-to-digital converters. The capacitor technology based on the non-porous planar anodic-oxide dielectrics complements the electrochemical conception of IPDs that combined, until no

Hydrophobic/oleophilic nanoporous anodic alumina substrates were fabricated by two-step anodization method following of chemical modification with 1H, 1H, 2H, 2H-perfluorooctyltrichlorosilane (FOTS). Surface morphology was characterized using a scanning electron microscopy. The influence of the topography and the pore size of the surface in the contact angle measurements with different solvents have been studied. The water repellence capacity of the nanoporous anodic alumina structure as fabricated depends on pore diameter but, there is a critical value of pore size beyond which the water contact angle decrease. After chemical modification of the surface, this effect is not observed. The porous topography of the material is not an advantage for the oleophibicity. The CA values for the non-porous surface using different solvents are lower than the structured surface. The results obtained in this study can be used to desire wettability properties. Modified NAA exhibit hydrophobicity and at the same time permeability for solvents with low surface tension.

Mealworm, TM (Tenebrio molitor), and black soldier fly, BSF (Hermetia illucens) are of special interest for food and feed applications due to their environmental benefits such as low water and land requirements, low greenhouse gas emissions, and high feed-conversion efficiency. This study assesses the use of ultrafiltration (UF) to fractionate protein concentrates from TM and BSF (TMPC, BSFPC) in order to enhance emulsifying and foaming properties. A 30 kDa regenerated cellulose acetate membrane enabled the separation of concentrate and permeate fractions for both insect proteins from two different initial feed concentrations (10 and 7.5 g/L). Permeate flux and protein transmission behave differently depending on the insect type and the initial concentration; while for TMPC permeate flux increases with a decrease in the initial protein concentration, it is not affected for BSFPC. The existing membrane cleaning protocols are suitable for recovering water flux after UF of insect proteins, enabling membrane re-use. Emulsifying activity is maintained for all the TMPC fractions, but it is significantly lower for the permeate fractions of BSFPC. Foaming properties are maintained for all the UF fractions of BSFPC and the ones from 7.5 g/L TMPC. Acidic solubilization leads to a fraction with enhanced emulsifying capacity and one with higher foaming capacity than the original for BSFPC. This study opens the door to membrane technology for insect protein fractionation, which has not been studied so far and has already provided useful solutions for other animal and plant proteins.

This article proposes using recycled aluminum, generating hydrogen in situ at low pressure, to power a 250 W electric bicycle with a fuel cell (FC), to increase the average speed and autonomy compared to a conventional electric bicycle with a battery. To generate hydrogen, the aluminum-water reaction with a 6 M NaOH solution is used as a catalyst. This article details the parts of the generation system, the electronic configuration used, the aluminum- and reagent-loading procedure and the by-products obtained, as well as the results of the operation without pedaling, with a resistance equivalent to a flat terrain and at maximum power of the accelerator for one and two loads of about 100 g of aluminum each. This allows us to observe different hybrid strategies, with a low-capacity battery in each case. The goal is to demonstrate that it is possible to store energy in a long-lasting, transportable, low-pressure, and sustainable manner, using recycled-aluminum test tubes, and to apply this to mobility.

In this paper, multiple reconfigurable intelligent surface (RIS) boards are deployed to enhance millimeter wave (mmWave) communication in a harsh blockage environment, where mmWave line-of-sight (LoS) link is completely blocked. Herein, RIS-user association should be considered to maximize the users' achievable data rate while assuring load balance among the installed RIS panels. However, maximum received power (MRP) based RIS-user association will overload some of the RIS boards while keeping others unloaded, which causes RIS load to unbalance and decreases the users' achievable data rate. Instead, in this paper, an online learning methodology using centralized multi-player multi-armed bandit (MP-MAB) with arms' load balancing is proposed. In this formulation, mmWave users, RIS boards, and achievable users' rates act as the bandit game players, arms, and rewards. During the MAB game, the users learn how to avoid associating with the heavily loaded RIS boards, maximizing their achievable data rates, and balancing the RIS loads. Three centralized MP-MAB algorithms with arms' load balancing are proposed from the family of upper confidence bound (UCB) MAB algorithms. These algorithms are UCB1, Kullback-Leibler divergence UCB (KLUCB), and Minimax optimal stochastic strategy (MOSS) with arms' load balancing, i.e., UCB1-LB, KLUCB-LB, and MOSS-LB. Numerical analysis ensures the superior performance of the proposed algorithms over MRP-based RIS-user association and other benchmarks.

Nowadays, CO2 electroreduction is gaining special interest as achieving net zero CO2 emissions is not going to be enough to avoid or mitigate the negative effects of climate change. However, the cost of CO2 electroreduction is still very high because of the low efficiency of conversion (around 20%). Therefore, it is necessary to optimize the reaction conditions. Thus, a miniaturized novel membrane reactor was designed and manufactured in this study, with a shorter distance between the electrodes and a reduced volume, compared with CNC-manufactured reactors, using novel stereolithography-based 3D printing. The reduced distance between the two electrodes reduced the electrical resistance and therefore lowered the overpotential necessary to trigger the reaction from −1.6 V to −1.2 V, increasing the efficiency. In addition, the reduction in the volume of the reactor increased the catalyst area/volume ratio, which also boosted the concentration of the products (from FE 18% to FE 21%), allowing their better identification. Furthermore, the smaller volume and reduced complexity of the reactor also improved the testing capacity and decreased the cost of experimentation. The novel miniaturized reactor can help researchers to perform more experiments in a cost/time-effective way, facilitating the optimization of the reaction conditions.