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Understanding the void defect formation mechanism and simultaneous predicting the tool service life in friction stir welding are critical for optimizing the welding parameters. However, the void defect formation mechanism in friction stir welding is not yet elucidated. In this study, a novel integrated thermal-fluid-structure coupling model of the friction stir welding process was proposed for simultaneous prediction of the weld formation and tool service life. A new non-uniform distribution model of the tool-workpiece contact pressure was proposed to describe the interaction between the tool and the workpiece. The void defect formation mechanism was quantitatively studied using the proposed integrated thermal-fluid-structure coupling model. The results show that the plastic material flows in the horizontal direction and can completely fill the cavity behind the tool for the welding condition of forming a sound weld. While the tool-workpiece contact interfacial frictional shear stress in the rear of the tool is decreased significantly which leads to a severe decrease in the plastic material flow velocity. Therefore, after bypassing the tool from the retreating side, the plastic material at the bottom of the weld stagnates, and void defect forms in the middle and lower part of the weld at the advancing side. The difference between the maximum and the minimum tool-workpiece contact pressure could serve as a numerical criterion to predict void defects. A sound joint is formed when the difference is lower than the critical value of 15 MPa, while a void defect is formed in the weld if it is higher than this critical value. The maximum equivalent stress acting on the tool is located at the pin root with severe stress concentration at a high welding speed. The front of the tool is subjected to tensile stress while its rear is subjected to compressive stress, therefore the tool is apt to fracture at its root under an inappropriate welding condition. The average normal stress of the tool varies periodically with its period consistent with the rotation period of the tool. The service life of the tool is decreased with the increase in welding speed and the decrease in rotation speed. The model is validated by experimental results.
Microplastics are a ubiquitous yet long-overlooked component of airborne particulate matter. The surface of these plastic particles provides a unique niche for microorganisms, collectively known as the plastisphere. The plastisphere in aquatic and terrestrial ecosystems harbors microbial communities with distinct compositions, structures, and functional profiles, posing potential planetary health risks. The characteristics, fate, and impacts of the microbiome associated with airborne microplastics, however, remain largely unknown. In this review, we fill the knowledge gaps by exploring how airborne microplastics serve as key habitats for microorganisms and the potential planetary health implications. We show that microplastics are expected to carry and sustain microorganisms over long distances and timescales in air, potentially dispersing pathogens, antibiotic-resistance genes, and other bioactive agents across ecosystems. These interactions may perturb ecological processes and biological health on a planetary scale. Interdisciplinary research and innovative methodologies are urgently required to better understand and mitigate the airborne plastisphere risks.
The development of all-solid-state lithium metal batteries (ASSLMBs) has pushed beyond the energy density limit of conventional liquid systems. However, stress concentration remains a critical yet poorly understood cause of degradation in ASSLMBs, particularly in widely used polycrystalline (PC) Ni-rich cathode systems. Herein, we design cavity-contained PC LiNi0.9Co0.05Mn0.05O2 (NCM) cathode particles to resolve the stress concentration problem in particle-electrode-battery multiscale by bottom-up stress management. Synchrotron X-ray tomography and multiscale finite element simulations disclose the cathode reaction heterogeneity initiates stress concentration and particle-electrode-battery multiscale mechanical-electrochemical degradation. Compared to cavity-free and multi-cavity NCM, central-cavity NCM suppressed cracking within the particles through shortened ionic transport distances and a built-in stress-relief space, enhanced (de)lithiation depth and uniformity at the cathode, reduced porosity and fracture in the electrolyte, and inhibited lithium dendrite formation at the anode, suggesting significantly improved stress uniformity in particle-electrode-battery levels. Consequently, ASSLMBs using the central-cavity NCM delivers a superior cycling stability (86.4% after 200 cycles and 81.5% after 400 cycles), outperforming both the traditional cavity-free NCM (51.6% after 200 cycles) and highly anticipated single crystal NCM (44.2% after 400 cycles). This work links particle-electrode-battery multiscale mechanical-electrochemical behavior, providing valuable insights for designing ASSLMBs with long lifespan from a holistic perspective.
Low biodegradability of graphene derivatives and related health risks are the main limiting factors for their in vivo biomedical applications. Here, we present the synthesis of enzyme-functionalized graphene sheets with self-degrading properties under physiological conditions and their applications in Tumor therapy. The synergistic enzyme cascade glucose oxidase and myeloperoxidase are covalently conjugated to the surface of graphene sheets and two-dimensional (2D) platforms are obtained that can produce sodium hypochlorite from glucose. The enzyme-functionalized graphene sheets with up to 289 nm average size are degraded into small pieces (≤40 nm) by incubation under physiological conditions for 24 h. Biodegradable graphene sheets are further loaded with doxorubicin and their ability for Tumor therapy is evaluated in vitro and in vivo. The laser-triggered release of doxorubicin in combination with the enzymatic activity of the functionalized graphene sheets results in a synergistic antitumor activity.
Taking advantage of their neutrophil-like activity, fast biodegradability, high photo- and chemotherapeutic effects, the novel two-dimensional nanoplatforms can be used for tumor therapeutic applications.
A modern day light microscope has evolved from a tool devoted to making primarily empirical observations to what is now a sophisticated, quantitative device that is an integral part of both physical and life science research. Nowadays, microscopes are found in nearly every experimental laboratory. However, despite their prevalent use in capturing and quantifying scientific phenomena, neither a thorough understanding of the principles underlying quantitative imaging techniques nor appropriate knowledge of how to calibrate, operate and maintain microscopes can be taken for granted. This is clearly demonstrated by the well-documented and widespread difficulties that are routinely encountered in evaluating acquired data and reproducing scientific experiments. Indeed, studies have shown that more than 70% of researchers have tried and failed to repeat another scientist’s experiments, while more than half have even failed to reproduce their own experiments1. One factor behind the reproducibility crisis of experiments published in scientific journals is the frequent underreporting of imaging methods caused by a lack of awareness and/or a lack of knowledge of the applied technique2,3. Whereas quality control procedures for some methods used in biomedical research, such as genomics (e.g., DNA sequencing, RNA-seq) or cytometry, have been introduced (e.g. ENCODE4), this issue has not been tackled for optical microscopy instrumentation and images. Although many calibration standards and protocols have been published, there is a lack of awareness and agreement on common Standards and guidelines for quality assessment and reproducibility5.
In April 2020, the QUality Assessment and REProducibility for instruments and images in Light Microscopy (QUAREP-LiMi) initiative6 was formed. This initiative comprises imaging scientists from academia and industry who share a common interest in achieving a better understanding of the performance and limitations of microscopes and improved quality control (QC) in light microscopy. The ultimate goal of the QUAREP-LiMi initiative is to establish a set of common QC standards, guidelines, metadata models7,8, and tools9,10, including detailed protocols, with the ultimate aim of improving reproducible advances in scientific research.
This White Paper 1) summarizes the major obstacles identified in the field that motivated the launch of the QUAREP-LiMi initiative; 2) identifies the urgent need to address these obstacles in a grassroots manner, through a community of Stakeholders including, researchers, imaging scientists11, bioimage analysts, bioimage informatics developers, corporate partners, Funding agencies, standards organizations, scientific publishers, and observers of such; 3) outlines the current actions of the QUAREPLiMi initiative, and 4) proposes future steps that can be taken to improve the dissemination and acceptance of the proposed guidelines to manage QC.
To summarize, the principal goal of the QUAREP-LiMi initiative is to improve the overall quality and reproducibility of light microscope image data by introducing broadly accepted standard practices and accurately captured image data metrics.
Interfacing artificial devices with the human brain is the central goal of neurotechnology. Yet, our imaginations are often limited by currently available paradigms and technologies. Suggestions for brain−machine interfaces have changed over time, along with the available technology.
Mechanical levers and cable winches were used to move parts of the brain during the mechanical age. Sophisticated electronic wiring and remote control have arisen during the electronic age, ultimately leading to plug-and-play computer interfaces. Nonetheless, our brains are so complex that these visions, until recently, largely remained unreachable dreams. The general problem, thus far, is that most of our technology is mechanically and/or electrically engineered, whereas the brain is a living, dynamic entity. As a result, these worlds are difficult to interface with one another. Nanotechnology, which encompasses engineered solid-state objects and integrated circuits, excels at small length scales of single to a few hundred nanometers and, thus, matches the sizes of biomolecules, biomolecular assemblies, and parts of cells. Consequently, we envision nanomaterials and nanotools as opportunities to interface with the brain in alternative ways. Here, we review the existing literature on the use of nanotechnology in brain−machine interfaces and look forward in discussing perspectives and limitations based on the authors’ expertise across a range of complementary disciplines from neuroscience, engineering, physics, and chemistry to biology and medicine, computer science and mathematics, and social science and jurisprudence. We focus on nanotechnology but also include information from related fields when useful and complementary.
Heterogeneous Oxysulfide@Fluoride Core/ Shell Nanocrystals for Upconversion-Based Nanothermometry
(2022)
Lanthanide (Ln3+)-doped upconversion nanoparticles (UCNPs) often suffer from weak luminescence, especially when their sizes are ultrasmall (less than 10 nm). Enhancing the upconversion luminescence (UCL) efficiency of ultrasmall UCNPs has remained a challenge that must be undertaken if any practical applications are to be envisaged. Herein, we present a Ln3+-doped oxysulfide@fluoride core/shell heterostructure which shows efficient UCL properties under 980nm excitation and good stability in solution. Through epitaxial heterogeneous growth, a ∼4 nm optically inert β-NaYF4 shell was coated onto ∼5 nm ultrasmall Gd2O2S:20%Yb,1%Tm. These Gd2O2S:20%Yb,1%Tm@NaYF4 core/shell UCNPs exhibit a more than 800-fold increase in UCL intensity compared to the unprotected core, a 180-fold increase in luminescence decay time of the 3H4 → 3H6 Tm3+ transition from 5 to 900 μs, and an upconversion quantum yield (UCQY) of 0.76% at an excitation power density of 155 W/cm2. Likewise, Gd2O2S:20%Yb,2%Er@NaYF4 core/shell UCNPs show a nearly 5000-fold
increase of their UCL intensity compared to the Gd2O2S:20%Yb,2%Er core and a maximum UCQY of 0.61%. In the Yb/Er core−shell UCNP system, the observed variation of luminescence intensity ratio seems to originate from a change in lattice strain as the temperature is elevated. For nanothermometry applications, the thermal sensitivities based on thermally coupled levels are estimated for both Yb/Tm and Yb/Er doped Gd2O2S@NaYF4 core/shell UCNPs.
High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling materials screening, property database generation, and training of “universal” machine learning models. While several software frameworks have emerged to support these computational efforts, new developments such as machine learned force fields have increased demands for more flexible and programmable workflow solutions. This manuscript introduces atomate2, a comprehensive evolution of our original atomate framework, designed to address existing limitations in computational materials research infrastructure. Key features include the support for multiple electronic structure packages and interoperability between them, along with generalizable workflows that can be written in an abstract form irrespective of the DFT package or machine learning force field used within them. Our hope is that atomate2's improved usability and extensibility can reduce technical barriers for high-throughput research workflows and facilitate the rapid adoption of emerging methods in computational material science.
An assessment of the elastic-plastic buckling limit state for multi-strake wind turbine support towers poses a particular challenge for the modern finite element analyst, who must competently navigate numerous modelling choices related to the tug-of-war between meshing and computational cost, the use of solvers that are robust to highly nonlinear behaviour, the potential for multiple near-simultaneously critical failure locations, the complex issue of imperfection sensitivity and finally the interpretation of the data into a safe and economic design.
This paper reports on an international ‘round-robin’ exercise conducted in 2022 aiming to take stock of the computational shell buckling expertise around the world which attracted 29 submissions. Participants were asked to perform analyses of increasing complexity on a standardised benchmark of an 8-MW multi-strake steel wind turbine support tower segment, from a linear elastic stress analysis to a linear bifurcation analysis to a geometrically and materially nonlinear buckling analysis with imperfections. The results are a showcase of the significant shell buckling expertise now available in both industry and academia.
This paper is the first of a pair. The second paper presents a detailed reference solution to the benchmark, including an illustration of the Eurocode-compliant calibration of two important imperfection forms.
