A comprehensive review of electrospinning block copolymers

Electrospinning provides a versatile and cost-effective route for the generation of continuous nanofibres with high surface area-to-volume ratio from various polymers. In parallel, block copolymers (BCPs) are promising candidates for many diverse applications, where nanoscale operation is exploited, owing to their intrinsic self-assembling behaviour at these length scales. Judicious combination of BCPs (with their ability to make nanosized domains at equilibrium) and electrospinning (with its ability to create nano- and microsized fibres and particles) allows one to create BCPs with high surface area-to-volume ratio to deliver higher efficiency or efficacy in their given application. Here, we give a comprehensive overview of the wide range of reports on BCP electrospinning with focus placed on the use of molecular design alongside control over specific electrospinning type and post-treatment methodologies to control the properties of the resultant fibrous materials. Particular attention is paid to the applications of these materials, most notably, their use as biomaterials, separation membranes, sensors, and electronic materials

Binary shape-stabilized phase change materials based on poly(ethylene glycol)/polyurethane composite with dual-phase transition

Novel binary shape-stabilized composite phase change materials (CPCMs) have been successfully prepared using a crosslinked polyurethane (PU) copolymer with a solid–solid phase transition as the supporting framework for loading additional (‘free’) poly(ethylene glycol) (PEG). The PU copolymer was synthesized by a two-step method using 2-hydroxypropyl-β-cyclodextrin (Hp-β-CD) as a chain extender and PEG as a soft segment. The composition, morphology, phase transition behavior and thermal properties of the prepared CPCMs have been elucidated by a wide range of techniques. Investigation of FTIR spectra and SEM images reveal that the ‘free’ PEG and the PU copolymer network within the CPCMs have good compatibility and high affinity due to the noncovalent interactions. Polarized light optical microscopy shows that the CPCMs produce smaller spherulites than pristine PEG, and homogeneous nucleation was prevalent during the crystallization process. Due to the dual-phase transition of the CPCMs (the solid–liquid phase transition of ‘free’ PEG and solid–solid phase transition of the PU matrix) occurring within the same, narrow temperature window, the CPCMs have far higher heat storage density compared with that of traditional shape-stabilized PCMs with the same ‘free’ PEG content. Importantly, thermal cycling and thermogravimetric analyses show that the CPCMs have good reusability and excellent thermal stability for potential use in thermoregulation or energy storage applications

X-VoE: Measuring eXplanatory Violation of Expectation in Physical Events

Intuitive physics is pivotal for human understanding of the physical world, enabling prediction and interpretation of events even in infancy. Nonetheless, replicating this level of intuitive physics in artificial intelligence (AI) remains a formidable challenge. This study introduces X-VoE, a comprehensive benchmark dataset, to assess AI agents' grasp of intuitive physics. Built on the developmental psychology-rooted Violation of Expectation (VoE) paradigm, X-VoE establishes a higher bar for the explanatory capacities of intuitive physics models. Each VoE scenario within X-VoE encompasses three distinct settings, probing models' comprehension of events and their underlying explanations. Beyond model evaluation, we present an explanation-based learning system that captures physics dynamics and infers occluded object states solely from visual sequences, without explicit occlusion labels. Experimental outcomes highlight our model's alignment with human commonsense when tested against X-VoE. A remarkable feature is our model's ability to visually expound VoE events by reconstructing concealed scenes. Concluding, we discuss the findings' implications and outline future research directions. Through X-VoE, we catalyze the advancement of AI endowed with human-like intuitive physics capabilities.Comment: 19 pages, 16 figures, selected for an Oral presentation at ICCV 2023. Project link: https://pku.ai/publication/intuitive2023iccv

Rinse-resistant superhydrophobic block copolymer fabrics by electrospinning, electrospraying and thermally-induced self-assembly

An inherent problem that restricts the practical application of superhydrophobic materials is that the superhydrophobic property is not sustainable; it can be diminished, or even lost, when the surface is physically damaged. In this work, we present an efficient approach for the fabrication of superhydrophobic fibrous fabrics with great rinse-resistance where a block copolymer has been electrospun into a nanofibrous mesh while micro-sized beads have been subsequently electrosprayed to give a morphologically composite material. The intricate nano- and microstructure of the composite was then fixed by thermally annealing the block copolymer to induce self-assembly and interdigitation of the microphase separated domains. To demonstrate this approach, a polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (SEBS) nanofibrous scaffold was produced by electrospinning before SEBS beads were electrosprayed into this mesh to form a hierarchical micro/nanostructure of beads and fibers. The effects of type and density of SEBS beads on the surface morphology and wetting properties of composite membranes were studied extensively. Compared with a neat SEBS fibrous mesh, the composite membrane had enhanced hydrophobic properties. The static water contact angle increased from 139° (±3°) to 156° (±1°), while the sliding angle decreased to 8° (±1°) from nearly 90°. In order to increase the rinse-resistance of the composite membrane, a thermal annealing step was applied to physically bind the fibers and beads. Importantly, after 200 hours of water flushing, the hierarchical surface structure and superhydrophobicity of the composite membrane were well retained. This work provides a new route for the creation of superhydrophobic fabrics with potential in self-cleaning applications

Outlier Detection of Time Series with A Novel Hybrid Method in Cloud Computing

In the wake of the development in science and technology, Cloud Computing has obtained more attention in different field. Meanwhile, outlier detection for data mining in Cloud Computing is playing more and more significant role in different research domains and massive research works have devoted to outlier detection, which includes distance-based, density-based and clustering-based outlier detection. However, the existing available methods spend high computation time. Therefore, the improved algorithm of outlier detection, which has higher performance to detect outlier is presented. In this paper, the proposed method, which is an improved spectral clustering algorithm (SKM++), is fit for handling outliers. Then, pruning data can reduce computational complexity and combine distance-based method Manhattan Distance (distm) to obtain outlier score. Finally, the method confirms the outlier by extreme analysis. This paper validates the presented method by experiments with a real collected data by sensors and comparison against the existing approaches, the experimental results turn out that our proposed method precedes the existing

Self-assembly-driven electrospinning:the transition from fibers to intact beaded morphologies

Polymer beads have attracted considerable interest for use in catalysis, drug delivery, and photo­nics due to their particular shape and surface morphology. Electrospinning, typically used for producing nanofibers, can also be used to fabricate polymer beads if the solution has a sufficiently low concentration. In this work, a novel approach for producing more uniform, intact beads is presented by electrospinning self-assembled block copolymer (BCP) solutions. This approach allows a relatively high polymer concentration to be used, yet with a low degree of entanglement between polymer chains due to microphase separation of the BCP in a selective solvent system. Herein, to demonstrate the technology, a well-studied polystyrene-poly(ethylene butylene)–polystyrene triblock copolymer is dissolved in a co-solvent system. The effect of solvent composition on the characteristics of the fibers and beads is intensively studied, and the mechanism of this fiber-to-bead is found to be dependent on microphase separation of the BCP

Detection of splice junctions from paired-end RNA-seq data by SpliceMap

Alternative splicing is a prevalent post-transcriptional process, which is not only important to normal cellular function but is also involved in human diseases. The newly developed second generation sequencing technique provides high-throughput data (RNA-seq data) to study alternative splicing events in different types of cells. Here, we present a computational method, SpliceMap, to detect splice junctions from RNA-seq data. This method does not depend on any existing annotation of gene structures and is capable of finding novel splice junctions with high sensitivity and specificity. It can handle long reads (50–100 nt) and can exploit paired-read information to improve mapping accuracy. Several parameters are included in the output to indicate the reliability of the predicted junction and help filter out false predictions. We applied SpliceMap to analyze 23 million paired 50-nt reads from human brain tissue. The results show at this depth of sequencing, RNA-seq can support reliable detection of splice junctions except for those that are present at very low level. Compared to current methods, SpliceMap can achieve 12% higher sensitivity without sacrificing specificity

Interfacial “Single‐Atom‐in‐Defects” Catalysts Accelerating Li + Desolvation Kinetics for Long‐Lifespan Lithium‐Metal Batteries

The lithium-metal anode is a promising candidate for realizing high-energy-density batteries owing to its high capacity and low potential. However, several rate-limiting kinetic obstacles, such as the desolvation of Li+ solvation structure to liberate Li$^+$, Li$^0$ nucleation, and atom diffusion, cause heterogeneous spatial Li-ion distribution and fractal plating morphology with dendrite formation, leading to low Coulombic efficiency and depressive electrochemical stability. Herein, differing from pore sieving effect or electrolyte engineering, atomic iron anchors to cation vacancy-rich Co$_{1−xS}$ embedded in 3D porous carbon (SAFe/CVRCS@3DPC) is proposed and demonstrated as catalytic kinetic promoters. Numerous free Li ions are electrocatalytically dissociated from the Li$^+$ solvation complex structure for uniform lateral diffusion by reducing desolvation and diffusion barriers via SAFe/CVRCS@3DPC, realizing smooth dendrite-free Li morphologies, as comprehensively understood by combined in situ/ex situ characterizations. Encouraged by SAFe/CVRCS@3DPC catalytic promotor, the modified Li-metal anodes achieve smooth plating with a long lifespan (1600 h) and high Coulombic efficiency without any dendrite formation. Paired with the LiFePO$_4$ cathode, the full cell (10.7 mg cm$^{−2}$) stabilizes a capacity retention of 90.3% after 300 cycles at 0.5 C, signifying the feasibility of using interfacial catalysts for modulating Li behaviors toward practical applications

Detailed structural insights into the p97-Npl4-Ufd1 interface.

Accepted versio