Kinetic monitoring of molecular interactions during surfactant-driven self-propelled droplet motion by high spatial resolution waveguide sensing.

HYPOTHESIS: Self-driven actions, like motion, are fundamental characteristics of life. Today, intense research focuses on the kinetics of droplet motion. Quantifying macroscopic motion and exploring the underlying mechanisms are crucial in self-structuring and self-healing materials, advancements in soft robotics, innovations in self-cleaning environmental processes, and progress within the pharmaceutical industry. Usually, the driving forces inducing macroscopic motion act at the molecular scale, making their real-time and high-resolution investigation challenging. Label-free surface sensitive measurements with high lateral resolution could in situ measure both molecular-scale interactions and microscopic motion. EXPERIMENTS: We employ surface-sensitive label-free sensors to investigate the kinetic changes in a self-assembled monolayer of the trimethyl(octadecyl)azanium chloride surfactant on a substrate surface during the self-propelled motion of nitrobenzene droplets. The adsorption-desorption of the surfactant at various concentrations, its removal due to the moving organic droplet, and rebuilding mechanisms at droplet-visited areas are all investigated with excellent time, spatial, and surface mass density resolution. FINDINGS: We discovered concentration dependent velocity fluctuations, estimated the adsorbed amount of surfactant molecules, and revealed multilayer coverage at high concentrations. The desorption rate of surfactant (18.4 s-1) during the microscopic motion of oil droplets was determined by in situ differentiating between droplet visited and non-visited areas.

Boron-doped diamond composites for durable oxygen evolution.

The urgent need to develop efficient, durable, and cost-effective oxygen evolution reaction (OER) catalysts for energy conversion and storage has prompted extensive research. Currently available commercial noble metal-based OER catalysts are expensive and exhibit limited long-term stability. In this study, boron-doped diamond composites (BDDCs) consisting of CoFe and CoFe2C nanoparticles supported by boron-doped diamond (BDD) particles have been prepared. The BDDC catalyst, prepared through a straightforward annealing process, exhibits exceptional durability (up to 72 h at 10 mA cm-2), a low overpotential (306 mV at 10 mA cm-2), and modest Tafel slope (58 mV dec-1). The coherent interfaces between CoFe/CoFe2C nanoparticles and the BDD substrate are essential for enhancing the OER performance. The fabrication method and composite structures presented in this study may facilitate the design and production of promising catalysts.

Wimpled thin films via multiple motions of a bubble decorated with surface-active molecules.

HYPOTHESIS: Thin liquid films play a crucial role in various systems and applications. Understanding the mechanisms that regulate their morphology is a scientific challenge with obvious implications for application optimization. Thin liquid films trapped between bubbles and air-liquid interface can show various configurations influenced by their deformation history and system characteristics. EXPERIMENTS: The morphology of thin liquid films formed in the presence of surface-active molecules is here studied with interferometric techniques. Three different systems with varying interfacial properties are investigated to understand their influence on film morphology. Specific deformation histories are applied to the films to generate complex film structures. FINDINGS: We achieve the creation of a rather stable wimple by implementing controlled bubble motions against the air-liquid interface. We provide a criterion for wimple formation based on lubrication theory. The long-term stability of the wimple is also investigated, and more complex multi-wimple structures are experimentally produced building upon the achieved wimple stability.

Exploring the Impact of In Situ-Formed Solid-Electrolyte Interphase on the Cycling Performance of Aluminum Metal Anodes.

Unwanted processes in metal anode batteries, e.g., non-uniform metal electrodeposition, electrolyte decomposition, and/or short-circuiting, are not fully captured by the electrolyte bulk solvation structure but rather defined by the electrode-electrolyte interface and its changes induced by cycling conditions. Specifically, for aluminum-ion batteries (AIBs), the role of the solid-electrolyte interphase (SEI) on the Al0 electrodeposition mechanism and associated changes during resting or cycling remain unclear. Here, we investigated the current-dependent changes at the electrified aluminum anode/ionic liquid electrolyte interface to reveal the conditions of the SEI formation leading to irreversible cycling in the AIBs. We identified that the mechanism of anode failure depends on the nature of the counter electrode, where the areal capacity and cycling current for Al0 electrodeposition dictates the number of successful cycles. Notwithstanding the differences behind unstable aluminum anode cycling in symmetrical cells and AIBs, the uniform removal of electrochemically inactive SEI components, e.g., oxide-rich or solvent-derived organic-rich interphases, leads to more efficient cycling behavior. These understandings raise the importance of using specific conditioning protocols for efficient cycling of the aluminum anode in conjugation with different cathode materials.

Interfacial Stress Transfer and Fracture in van der Waals Heterostructures.

Artificially stacking 2D materials (2DMs) into vdW heterostructures creates materials with properties not present in nature that offer great potential for various applications such as flexible electronics. Properties of such stacked structures are controlled largely by the interfacial interactions and the structural integrity of the 2DMs. In spite of their crucial roles, interfacial stress transfer and the failure mechanisms of the vdW heterostructures, particularly during deformation, have not been well addressed so far. In this work, the interfacial stress transfer and failure mechanisms of a MoS2/graphene vdW heterostructure are studied, through the strain distributions both laterally in individual 2DMs and vertically across different 2DMs revealed in-situ. The fracture of the MoS2 and the associated states of stress and strain are monitored experimentally. This enables various interfacial properties, such as the interfacial shear strength and interfacial fracture energy, to be estimated. Based only on the measured strength and interfacial properties of a single vdW heterostructure, a failure criterion is proposed to predict the failure mechanisms of similar vdW heterostructures with any lateral dimensions. This work provides an insight to the deformation micromechanics of vdW heterostructures that are of great value for their miniaturization and applications, especially in flexible electronics.

Imaging magnetic spiral phases, skyrmion clusters, and skyrmion displacements at the surface of bulk Cu2OSeO3.

Surfaces - by breaking bulk symmetries, introducing roughness, or hosting defects - can significantly influence magnetic order in magnetic materials. Determining their effect on the complex nanometer-scale phases present in certain non-centrosymmetric magnets is an outstanding problem requiring high-resolution magnetic microscopy. Here, we use scanning SQUID microscopy to image the surface of bulk Cu2OSeO3 at low temperature and in a magnetic field applied along 100 . Real-space maps measured as a function of applied field reveal the microscopic structure of the magnetic phases and their transitions. In low applied field, we observe a magnetic texture consistent with an in-plane stripe phase, pointing to the existence of a distinct surface state. In the low-temperature skyrmion phase, the surface is populated by clusters of disordered skyrmions, which emerge from rupturing domains of the tilted spiral phase. Furthermore, we displace individual skyrmions from their pinning sites by applying an electric potential to the scanning probe, thereby demonstrating local skyrmion control at the surface of a magnetoelectric insulator.

Investigating Material Interface Diffusion Phenomena through Graph Neural Networks in Applied Materials.

Understanding and predicting interface diffusion phenomena in materials is crucial for various industrial applications, including semiconductor manufacturing, battery technology, and catalysis. In this study, we propose a novel approach utilizing Graph Neural Networks (GNNs) to investigate and model material interface diffusion. We begin by collecting experimental and simulated data on diffusion coefficients, concentration gradients, and other relevant parameters from diverse material systems. The data are preprocessed, and key features influencing interface diffusion are extracted. Subsequently, we construct a GNN model tailored to the diffusion problem, with a graph representation capturing the atomic structure of materials. The model architecture includes multiple graph convolutional layers for feature aggregation and update, as well as optional graph attention layers to capture complex relationships between atoms. We train and validate the GNN model using the preprocessed data, achieving accurate predictions of diffusion coefficients, diffusion rates, concentration profiles, and potential diffusion pathways. Our approach offers insights into the underlying mechanisms of interface diffusion and provides a valuable tool for optimizing material design and engineering. Additionally, our method offers possible strategies to solve the longstanding problems related to materials interface diffusion.

Multiscale Defective Interfaces for Realizing Na-CO2 Batteries With Ultralong Lifespan.

Despite their favorable high energy density and potential for CO2 recycling, Na-CO2 batteries have been held back by limitations in cycling capability, stemming from the sluggish CO2 reduction/evolution reaction (CO2RR/CO2ER) kinetics at CO2 cathode and unmanageable deposition/stripping of metallic Na at the anode upon cycling. Herein, a "two-in-one" electrode with multiscale defective FeCu interfaces (CP@FeCu) is presented, which is capable of improving the CO2RR/CO2ER kinetics of CO2-breathing cathode, while modulating sodium deposition behavior. Experimental and theoretical investigations reveal multiscale defective FeCu interfaces are responsible for the enhancement of sodiophilicity and catalytic properties. The defect and valence oscillation effects originate in multiscale defective FeCu interfaces, effectively facilitating the adsorption of reactants and decomposition of Na2CO3 during CO2RR/CO2ER processes, along with exceptional cycling stability of 2400 cycles (4800 h) at 5 µA cm-2. Meanwhile, the CP@FeCu with sodium affinity creates a uniform electric field and robust adsorption for Na, making initial nucleation sites more conducive to Na deposition and achieving dendrite-resistant and durable anodes. This work offers a scientific insight into the functionalization design of "two-in-one" electrodes, which is essential for a unified solution to the challenges in sodium anodes and CO2 cathodes.

Human in the collaborative loop: a strategy for integrating human activity recognition and non-invasive brain-machine interfaces to control collaborative robots.

Human activity recognition (HAR) and brain-machine interface (BMI) are two emerging technologies that can enhance human-robot collaboration (HRC) in domains such as industry or healthcare. HAR uses sensors or cameras to capture and analyze the movements and actions of humans, while BMI uses human brain signals to decode action intentions. Both technologies face challenges impacting accuracy, reliability, and usability. In this article, we review the state-of-the-art techniques and methods for HAR and BMI and highlight their strengths and limitations. We then propose a hybrid framework that fuses HAR and BMI data, which can integrate the complementary information from the brain and body motion signals and improve the performance of human state decoding. We also discuss our hybrid method's potential benefits and implications for HRC.

An Angstrom-Scale Protective Skin Grown In Situ on Perovskite Oxide to Enhance Stability in Water.

The utilization of perovskite oxide as a catalyst for aqueous reactions is promising but challenging in stability. Here, we propose an in situ growth strategy that constructs an ultrathin protective skin on the Sr0.9Fe0.81Ta0.09Ni0.1O3-δ perovskite surface and thus effectively solves the stability issue. Using a spherical aberration-corrected transmission electron microscope, we observe the coexistence of an angstrom-scale (~7 Å) Fe2O3 protective skin and FeNi alloy nanoparticles. A number of alloy nanoparticles grow along with the skin and uniformly take root on the skin surface. Such a hierarchical structure can reconstruct the surface electronic structure and suppress the ion leaching of perovskite oxide in water. Benefiting from this unique structure, the catalyst has experienced a substantial increase (800 h, more than three orders of magnitude) in its stable operation time in water (for example, in a hydrogen evolution reaction). These results provide valuable insight into solid-solid phase transitions and have substantial implications for using structural defects at surfaces to modulate mass transport and transformation kinetics. Our strategy is sufficiently simple and can be used to subtly manipulate the catalyst structures to improve the performance of perovskite-based catalysts and potentially other oxide catalysts for a wide range of reactions.

Operando Freezing Cryogenic Electron Microscopy of Active Battery Materials.

Understanding structural and chemical evolution of battery materials during operation is critical to achieving safe, efficient, and long-lasting energy storage. Cryogenic electron microscopy (cryo-EM) has become a valuable tool in battery characterization, leveraging low temperatures to improve stability of sensitive materials under electron beam irradiation. However, typical cryo-EM sample preparations leave extended time between the electrochemical point of interest and ex situ freezing of samples, during which active structures may relax, degrade, or otherwise evolve. Here, we detail a method for operando freezing cryo-EM to preserve and characterize native electrode and interfacial structures that arise during battery cycling, based on an operando plunge freezer and cold sample removal process. We validate the method on multiple electrode materials and quantify and discuss the freezing rate achieved. Operando freezing cryo-EM can be used to directly visualize transient features that arise at active electrochemical interfaces, to enable deeper understanding of structural evolution and interfacial chemistry in batteries and other electrochemical systems.

Exploring the Efficacy of Artificial Intelligence: A Comprehensive Analysis of CHAT-GPT's Accuracy and Completeness in Addressing Urinary Incontinence Queries.

BACKGROUND: Artificial intelligence models are increasingly gaining popularity among patients and healthcare professionals. While it is impossible to restrict patient's access to different sources of information on the Internet, healthcare professional needs to be aware of the content-quality available across different platforms. OBJECTIVE: To investigate the accuracy and completeness of Chat Generative Pretrained Transformer (ChatGPT) in addressing frequently asked questions related to the management and treatment of female urinary incontinence (UI), compared to recommendations from guidelines. METHODS: This is a cross-sectional study. Two researchers developed 14 frequently asked questions related to UI. Then, they were inserted into the ChatGPT platform on September 16, 2023. The accuracy (scores from 1 to 5) and completeness (score from 1 to 3) of ChatGPT's answers were assessed individually by two experienced researchers in the Women's Health field, following the recommendations proposed by the guidelines for UI. RESULTS: Most of the answers were classified as "more correct than incorrect" (n = 6), followed by "incorrect information than correct" (n = 3), "approximately equal correct and incorrect" (n = 2), "near all correct" (n = 2, and "correct" (n = 1). Regarding the appropriateness, most of the answers were classified as adequate, as they provided the minimum information expected to be classified as correct. CONCLUSION: These results showed an inconsistency when evaluating the accuracy of answers generated by ChatGPT compared by scientific guidelines. Almost all the answers did not bring the complete content expected or reported in previous guidelines, which highlights to healthcare professionals and scientific community a concern about using artificial intelligence in patient counseling.

Quantitative Advantages of Corrosion Sensing Using Fluorescence, Microscopy, and Single-Molecule Detection.

The corrosion of metals and alloys is a fundamental issue in modern society. Understanding the mechanisms that cause and prevent corrosion is integral to saving millions of dollars each year and to ensure the safe use of infrastructure subject to the hazardous degrading effects of corrosion. Despite this, corrosion detection techniques have lacked precise, quantitative information, with industries taking a top-down, macroscale approach to analyzing corrosion with tests that span months to years and yield qualitative information. Fluorescence, a well-established optical method, can fill the niche of early-stage, quantitative corrosion detection and can be employed for both bulk and localized testing over time. The latter, fluorescence microscopy, can be pushed to greater levels of detail with single-molecule microscopy, achieving nanometer spatial and subsecond temporal resolutions of corrosion that allow for the extraction of dynamic information and kinetics. This review will present how fluorescence microscopy can provide researchers with a molecular view into the chemical mechanisms of corrosion at interfaces and allow for faster, quantitative studies of how to detect and prevent corrosion.

Tailored Nanoarchitectures: MoS2/Graphene and MoS2/Graphene Oxide thin Films via Liquid-Liquid Interfacial Route.

The nanostructured assembly of different two-dimensional (2D) materials in specific organization is crucial for developing materials with synergistic properties. In this study, we present a general methodology to prepare thin, transparent and self-assembled films of 2D/2D composites based on molybdenum sulfide (MoS2)/graphene oxide (GO) or MoS2/reduced graphene oxide (rGO), through the liquid/liquid interfacial route. Different nanoarchitectures are obtained by changing simple experimental parameters during the thin film preparation steps. The films were characterized by UV-Vis and Raman spectroscopy, scanning electron microscopy and cyclic voltammetry, evidencing that the experimental route used plays a role in the organization and properties of the assembled nanoarchitectures. Likewise, nanostructures of MoS2/GO and MoS2/rGO prepared through the same route have different organizations due to the different interactions between the materials. This showcases the potential of the technique to prepare tailored nanoarchitectures with specific properties for various applications, paving the way for innovative nanotechnology and materials science applications.

Brain-Controlled Augmented Hearing for Spatially Moving Conversations in Multi-Talker Environments.

Focusing on a specific conversation amidst multiple interfering talkers is challenging, especially for those with hearing loss. Brain-controlled assistive hearing devices aim to alleviate this problem by enhancing the attended speech based on the listener's neural signals using auditory attention decoding (AAD). Departing from conventional AAD studies that relied on oversimplified scenarios with stationary talkers, a realistic AAD task that involves multiple talkers taking turns as they continuously move in space in background noise is presented. Invasive electroencephalography (iEEG) data are collected from three neurosurgical patients as they focused on one of the two moving conversations. An enhanced brain-controlled assistive hearing system that combines AAD and a binaural speaker-independent speech separation model is presented. The separation model unmixes talkers while preserving their spatial location and provides talker trajectories to the neural decoder to improve AAD accuracy. Subjective and objective evaluations show that the proposed system enhances speech intelligibility and facilitates conversation tracking while maintaining spatial cues and voice quality in challenging acoustic environments. This research demonstrates the potential of this approach in real-world scenarios and marks a significant step toward developing assistive hearing technologies that adapt to the intricate dynamics of everyday auditory experiences.

Facile Synthesis of Potassium Decahydrido-Monocarba-closo-Decaborate Imidazole Complex Electrolyte for All-Solid-State Potassium Metal Batteries.

All-solid-state potassium metal batteries have caught increasing interest owing to their abundance, cost-effectiveness, and high energy/power density. However, their development is generally constrained by the lack of suitable solid-state electrolytes. Herein, we report a new complex KCB9H10·2C3H4N2, synthesized by grinding and heating the mixture of potassium decahydrido-monocarba-closo-decaborate (KCB9H10) and imidazole (C3H4N2) under mild conditions, to achieve the K-ion superionic solid-state electrolyte. The crystal structure was revealed as an orthorhombic lattice with the space group of Pna21 by FOX software. The diffusion properties for K+ in the crystal structure were calculated using the climbing image nudged elastic band (CI-NEB) method. KCB9H10·2C3H4N2 exhibited a high ionic conductivity of 1.3 × 10-4 S cm-1 at 30 °C, four orders of magnitude higher than that of KCB9H10. This ionic conductivity is also the highest value of hydridoborate-based K+ conductors reported. Moreover, KCB9H10·2C3H4N2 demonstrated a K+ transference number of 0.96, an electrochemical stability window of 1.2 to 3.2 V vs. K/K+, and good stability against the K metal coated by a layer of potassium imidazolate (KIm). These great performances make KCB9H10·2C3H4N2 a promising K-ion solid-state electrolyte.

The Effect of Hydrophobic Modified Block Copolymers on Water-Oil Interfacial Properties and the Demulsification of Crude Oil Emulsions.

The demulsification effect of three types of block copolymers, BP123, BPF123, and H123, with the same PEO and PPO segments but different hydrophobic modification groups on crude oil emulsions and the properties of oil-water interfaces were investigated using demulsification experiments, an interfacial tensiometer, and surface viscoelastic and zeta potential instruments in this paper. The results showed that the hydrophobic modification group of the block copolymers had great effects on the demulsification performance. The H123 block copolymers with the strongest hydrophobicity had the best demulsification effect on the crude oil emulsions. The properties of the oil-water interfaces indicated that the modified block copolymers achieved the demulsification of crude oil emulsions by reducing the strength of the oil-water interfacial film and the interfacial tension.

A Recyclable Ionogel with High Mechanical Robustness Based on Covalent Adaptable Networks.

Ionogels are an emerging class of soft materials for flexible electronics, with high ionic conductivity, low volatility, and mechanical stretchability. Recyclable ionogels are recently developed to address the sustainability crisis of current electronics, through the introduction of non-covalent bonds. However, this strategy sacrifices mechanical robustness and chemical stability, severely diminishing the potential for practical application. Here, covalent adaptable networks (CANs) are incorporated into ionogels, where dynamic covalent crosslinks endow high strength (11.3 MPa tensile strength), stretchability (2396% elongation at break), elasticity (energy loss coefficient of 0.055 at 100% strain), and durability (5000 cycles of 150% strain). The reversible nature of CANs allows the ionogel to be closed-loop recyclable for up to ten times. Additionally, the ionogel is toughened by physical crosslinks between conducting ions and polymer networks, breaking the common dilemma in enhancing mechanical properties and electrical conductivity. The ionogel demonstrates robust strain sensing performance under harsh mechanical treatments and is applied for reconfigurable multimodal sensing based on its recyclability. This study provides insights into improving the mechanical and electrical properties of ionogels toward functionally reliable and environmentally sustainable bioelectronics.

Binocularly incongruent, multifrequency-coded SSVEP in VR: feasibility and characteristics.

Objective.Steady-state visual evoked potentials (SSVEPs) in response to flickering stimuli are popular in brain-computer interfacing but their implementation in virtual reality (VR) offers new opportunities also for clinical applications. While traditional SSVEP target selection relies on single-frequency stimulation of both eyes simultaneously, further called congruent stimulation, recent studies attempted to improve the information transfer rate by using dual-frequency-coded SSVEP where each eye is presented with a stimulus flickering at a different frequency, further called incongruent stimulation. However, few studies have investigated incongruent multifrequency-coded SSVEP (MultiIncong-SSVEP).Approach.This paper reports on a systematical investigation of incongruent dual-, triple-, and quadruple-frequency-coded SSVEP for use in VR, several of which are entirely novel, and compares their performance with that of congruent dual-frequency-coded SSVEP.Main results.We were able to confirm the presence of a summation effect when comparing monocular- and binocular single-frequency congruent stimulation, and a suppression effect when comparing monocular- and binocular dual-frequency incongruent stimulation, as both tap into the binocular vision capabilities which, when hampered, could signal amblyopia.Significance.In sum, our findings not only evidence the potential of VR-based binocularly incongruent SSVEP but also underscore the importance of paradigm choice and decoder design to optimize system performance and user comfort.

Recent progress on smart lower prosthetic limbs: a comprehensive review on using EEG and fNIRS devices in rehabilitation.

The global rise in lower limb amputation cases necessitates advancements in prosthetic limb technology to enhance the quality of life for affected patients. This review paper explores recent advancements in the integration of EEG and fNIRS modalities for smart lower prosthetic limbs for rehabilitation applications. The paper synthesizes current research progress, focusing on the synergy between brain-computer interfaces and neuroimaging technologies to enhance the functionality and user experience of lower limb prosthetics. The review discusses the potential of EEG and fNIRS in decoding neural signals, enabling more intuitive and responsive control of prosthetic devices. Additionally, the paper highlights the challenges, innovations, and prospects associated with the incorporation of these neurotechnologies in the field of rehabilitation. The insights provided in this review contribute to a deeper understanding of the evolving landscape of smart lower prosthetic limbs and pave the way for more effective and user-friendly solutions in the realm of neurorehabilitation.