Entanglement Network Research Articles

Regulating Entanglement Networks of Fibrillatable Binders for Sub-20-µm Thick, Robust, Dry-Processed Solid Electrolyte Membranes in All-Solid-State Batteries.

Despite significant advancements in all-solid-state batteries (ASSBs), the reliance on thick solid electrolyte (SE) membranes hinders their commercial viability. Although the dry process using polytetrafluoroethylene (PTFE) binder is proposed for thin SE membranes, a comprehensive understanding of the correlation between PTFE fibrillation and SE membrane quality remains lacking. Here an important guidance is provided for producing durable SE membranes that can be reduced to sub-20-µm thickness by regulating the entanglement networks of PTFE. While establishing fabrication parameters; shear time and shear temperature, a dominant effect of the number-average molecular weight (Mn) on PTFE fibrillation is revealed for the first time. Moreover, the degree of PTFE fibrillation is quantified using systematic X-ray diffraction (XRD) analysis. The SE membrane utilizing the high-Mn PTFE binder that achieves a maximum fibrillation degree (≈98%) and thus forms highly entangled fibrous PTFE network interweaving SE particles, exhibited superior toughness. Consequently, the 18 µm thick SE membrane with 0.5wt% high-Mn PTFE shows a considerably higher areal conductance. The ASSB using this durable, ultrathin SE membrane outperforms its counterparts that used flimsy SE membranes or pure SE pellets. Finally, uniquely thin ASSBs demonstrate significantly improved cell-level energy densities, showcasing the promising potential for practical ASSB fabrication.

Federated learning with tensor networks: a quantum AI framework for healthcare

Abstract The healthcare industries frequently handle sensitive and proprietary data, and due to strict
privacy regulations, they are often reluctant to share data directly. In today’s context, Federated
Learning (FL) stands out as a crucial remedy, facilitating the rapid advancement of distributed machine
learning while effectively managing critical concerns regarding data privacy and governance.
The fusion of federated learning and quantum computing represents a groundbreaking interdisciplinary
approach with immense potential to revolutionize various industries, from healthcare to
finance. In this work, we propose a federated learning framework based on quantum tensor networks
that takes advantage of the principles of many-body quantum physics. Currently, there are
no known classical tensor networks implemented in federated settings. Furthermore, we investigated
the effectiveness and feasibility of the proposed framework by conducting a differential privacy analysis
to ensure the security of sensitive data across healthcare institutions. Experiments on popular
medical image datasets show that the federated quantum tensor network model achieved a mean
receiver-operator characteristic area under the curve (ROC-AUC) of 91-98%, outperforming several
state-of-the-art federated learning methods while using fewer parameters. Experimental results
demonstrate that the quantum federated global model, consisting of highly entangled tensor network
structures, showed better generalization and robustness and achieved higher testing accuracy,
surpassing the performance of locally trained clients under unbalanced data distributions among
healthcare institutions.

Tobacco stalk nanofibrillated cellulose: An eco-friendly binder on fluidized bed granulation

The search for new excipients that provide formulation alternatives over existing ones and that are derived from natural resources has advanced over the years. Emerging from this scenario, an important alternative to traditional excipients is nanofibrillated cellulose (NFC), which is generally obtained from agricultural wastes and is a cellulose-rich material. Most of the time, the nanofibers are presented in aqueous dispersions that form a highly entangled network of fibrous particles that exhibit gel-like behavior. Therefore, the present work aimed to explore the gel-like behavior of NFC from tobacco stalks to evaluate it as a binder in a fluid bed granulation process for further application as a pharmaceutical ingredient. The granulation process was carried out using top spray mode with an inlet air temperature of 80 °C, airflow between 9 and 11 mm3 h−1, and atomizing air pressure of 0.7 bar. Povidone (PVP) was used as a standard binder for comparison purposes. The binder systems were sprayed on the powder blend of theophylline and maltodextrin at a feed rate of 3.05 mL⋅min−1. Granule properties, such as yield, moisture content, morphology, label-free Raman imaging, particle size distribution, drug content, and flow properties, were evaluated. The process using NFC provided granules with excellent drug uniformity, low moisture content (<2 %), high yield (>92 %), and passable flow properties. Their behavior was comparable to that of granules prepared with the classical PVP binder system. Therefore, this study opens a perspective for the reuse of NFC from tobacco stalk, an agricultural waste, as an alternative binder for the granulation process, contributing to environmental sustainability.

Electrical Tissue Adhesives for Strain‐Insensitive In‐situ Biosensing

In‐situ biosensing, a rapidly evolving field that focuses on the development of biosensors capable of on‐site detection of biomolecules directly from local tissue regions, holds the potential to revolutionize medicine through real‐time monitoring, personalized diagnosis, and targeted therapies. However, interfacing rigid, nonstretchable biosensors with soft, deformable tissues presents significant challenges due to their fundamentally contradictory properties. Herein, an electrical tissue adhesive featuring an entangled adhesive polymer network interpenetrated with a sacrificial dissipative polymer network is developed, which can rapidly and robustly adhere electrochemical biosensors with biological tissues, enabling strain‐insensitive physiological monitoring. The electrical tissue adhesive achieves a high fracture toughness of up to 3000 J m−2, a low Young's modulus of around 20 kPa, superior stretchability up to 15 times its initial length, and an overall biosensor‐tissue interfacial toughness of up to 500 J m−2. Using an electrochemical glucose sensor as one example, it is demonstrated that the electrical tissue adhesive can maintain resilient glucose sensing under various stress states and stretch levels. Additionally, the application of the electrical tissue adhesive for in‐situ monitoring of exercise and diet in subjects with various BMIs is demonstrated by measuring glucose concentration in sweat.

Shape Memory Polymer Foam Based on Nanofibrillar Composites of Polylactide/Polyamide.

This paper presents the novel development of a shape memory polymer foam based on polymer-polymer nanocomposites. Herein, polylactide (PLA)/biosourced polyamide (PA) foams are fabricated by in situ fibrillation of polymer blends and a subsequent supercritical CO2 foaming technique. In this system, PLA serves as a shape memory polymer to endow this foam with a shape memory effect (SME), and in situ generated PA nanofibers are employed to reinforce the PLA cell walls and provide an additional permanent phase. A concentration of PA, 5 wt.%, was chosen to form an entangled nanofibrillar network. Foams of PLA/PA nanoblends with the same content of constituents were fabricated to reveal the effect of minor phase morphology on the cell structure and shape memory behavior of polymer foams. Profiting from the reinforcing effect of PA nanofibers, the PLA/PA nanocomposite foam exhibits smaller foam cells, a narrower cell size distribution and a comparable cell concentration than the PLA/PA nanoblend foam. In addition, PA nanofibers, unlike PA nanodroplets, favor the shape fixation ratio and recovery ratio and shorten the shape recovery time.

Effect of Proteins on the Vulcanized Natural Rubber Crosslinking Network Structure and Mechanical Properties.

Proteins are important factors affecting the properties of natural rubber. Therefore, investigating the effect of free and bonded proteins on the structure and mechanical properties of the vulcanized crosslinking network of natural rubber would provide a theoretical basis for the production of high mechanical resistance natural rubber. Herein, natural rubbers with different protein contents and types were prepared by high-speed centrifugation. And, the effects on their network structure, vulcanization, tensile strength, tearing strength and dynamic mechanical properties were investigated. The results showed that the reduction in protein content led to the decrement in the entanglement networks, crosslinking density and tensile and tear strengths of the vulcanized natural rubber. Moreover, the bonded proteins had an obvious influence on the vulcanization process, while free proteins played an important role in the crosslink densities. These results reveal that both bonded and free proteins are involved in the vulcanization process and the construction of the vulcanized crosslinking network structure of natural rubber, which enhances the mechanical properties such as the modulus and tensile strength of vulcanized natural rubber.

Oriented crystalline structure in melt-drawn ultrahigh-molecular-weight polyethylene induced by entanglement networks

In this study, we focused on the unique structure with oblique periodicity formed by the melt-drawing of metallocene-catalyzed ultrahigh-molecular-weight polyethylene (UHMW-PE) to clarify the relationship between tight entanglements that cannot be disentangled during melt-drawing and the formation of the periodic structure. In situ X-ray measurements during the heating of the melt-drawn UHMW-PE film revealed that the disappearance of the characteristic oblique streaks that appeared tilted from the drawing direction and the orthorhombic-to-hexagonal phase transition occurred simultaneously, suggesting that the change in the tension state of extended-chain crystals due to the orthorhombic-to-hexagonal phase transition and the disappearance of order in the structure resulting in oblique streaks are related behaviors. This indicates the presence of the network structure including oriented amorphous chains in which molecular chains are fixed by tight entanglements in metallocene-catalyzed UHMW-PE melt-drawn film.

Simultaneous processing of both handheld biomixing and biowriting of kombucha cultured pre-crosslinked nanocellulose bioink for regeneration of irregular and multi-layered tissue defects

The nanocellulosic pellicle derived from the symbiotic culture of bacteria and yeast (Kombucha SCOBY) is an important biomaterial for 3D bioprinting in tissue engineering. However, this nanocellulosic hydrogel has a highly entangled gel network. This needs to be partially modified to improve its processability and extrusion ability for its applications in the 3D bioprinting area. To control its mechanical and biological properties for direct 3D bioprinting applications, uniform reinforcement of nanocellulose-interacting polymers and nanoparticles in such a prefabricated gel network is essential. In this study, the hydrogel network is partially hydrolyzed with organic acid and subsequently transformed into a 3D bioprintable polyelectrolyte complex with chitosan and kaolin nanoparticles without any chemical crosslinker using a handheld 3D bioprinter. This handheld bioprinter ensures homogeneity in both biomixing and bioprinting of chitosan and kaolin within the modified nanocellulose network for multi-layered bioprinted scaffolds through an extensional shear mechanism. The biomixing simulation, mechanical (static, dynamic, and cyclic), 3D bioprinting, and cellular studies confirm the homogeneous biomixing of kaolin nanoparticles and live cells in this nanocellulose-chitosan polyelectrolyte hydrogel. The combination of SCOBY-derived nanocellulose-chitosan bioink with kaolin nanoparticles and a screw-driven handheld extrusion bioprinter demonstrates a promising platform for layer-by-layer regeneration of complex tissues with homogeneous cell/particle distribution with high cell viability.

Mechanistic elucidation of the molecular weight dependence of corrosion inhibition afforded by polyetherimide coatings

Corrosion of critical metal components exacts a heavy toll in terms of maintenance and replacement costs and damage to ecosystems upon failure. Polymeric barrier coatings protect against corrosion; however, design principles for modulating polymer structure to improve corrosion inhibition remain contested and elusive. Here, we examine molecular-weight-dependent differences in the efficacy of corrosion inhibition on aluminum substrates afforded by polyetherimide (PEI) coatings. Analyses of coated substrates evidence a clear trend denoting improved corrosion inhibition for higher weighted-average molecular weight (MW) PEI. The more rigid and entangled macromolecular network of higher-MW variants exhibit stable impedance values, |Z|0.01 Hz ca. 1010 Ω/cm2, upon extended immersion in brine media, whereas lower-MW variants are readily hydrated and disentangled resulting in a significant reduction in impedance values. Results illuminate mechanistic understanding of molecular-weight-dependence in corrosion inhibition, advance a framework for considering the dynamical evolution of secondary structure, and exemplify generalizable design principles for corrosion inhibition.

Effect of Phase Structure on the Viscoelasticity and Mechanical Properties of Isotactic Polypropylene Multicomponents Polymerized with Non-Conjugated α,ω-Diene.

Increasing of rubber content in isotactic polypropylene/ethylene-propylene rubber (iPP/EPR) alloys can extend the applications of this kind of polyolefin. The EPR content and phase structure of isotactic polypropylene multicomponents have great effect on the viscoelasticity and mechanical properties. iPP/EPR in-reactor alloys with a high EPR content were obtained through the in situ crosslinking of EPR chains with α,ω-diene. The morphological observation results indicate that the crosslinked iPP/EPR in-reactor alloys have a good spherical shape with clean and rough external surfaces. The high EPR content is finely dispersed in the crosslinked iPP/EPR alloys in areas ranging in size from tens of nanometers to several micrometers, which implies that a sufficient crosslinking degree of EPR chains can effectively prevent their aggregation and restrict macro-phase separation. The rheological results show a clear plateau in the terminal region, which reveals an entangled polymer chain network in the crosslinked iPP/EPR alloys. The well-dispersed EPR and the bi-continuous phase structure have a great effect on the mechanical properties of the isotactic polypropylene multicomponent which were assessed.

Directly Printable, Non‐Smearable and Stretchable Conductive Ink Enabled by Liquid Metal Microparticles Interstitially Engineered in Highly Entangled Elastomeric Matrix

AbstractLiquid metal or liquid metal microparticles (LMP) based conductive inks, though promising for fabrication of circuits for use in soft and stretchable electronics, are constrained by a few drawbacks such as need for encapsulation, need for sintering to induce conductivity, and smearing. To address these issues, herein, a stretchable conductive composite ink is developed by combining LMPs with carbon black (CB) in highly entangled polysiloxane elastomer. LMP‐dispersed elastomer lacks conductivity because of its non‐percolated network, however, the CB can interconnect LMPs to act as a bridge, thereby imparting conductivity to the elastomer. Due to presence of fluidic LMPs, the LMPs‐dispersed elastomer lies in soft regime with initial conductivity of 5.6 S m−1, aided by the presence of CB in the interstitial spaces between the LMPs. The highly entangled molecular network of the encapsulating elastomer endows the resulting composite with high stretchability (≈286%) and softness (0.648 MPa) and its long pot life enables rheological modulation of the ink to achieve pressure‐driven direct printed non‐smearing traces. The LMPs‐based conductive ink developed in this work is expected to be further utilized in the fabrication of soft robotics and electronic skin and integrated into electronic modules by facile direct 3D printing.

Interstellar computation their challenges and approaches in interplanetary cloud systems and data transmission

With the advancement of human civilisation beyond the confines of Earth's atmosphere, there has been an increasing need for efficient data processing and transmission in extraterrestrial environments. The article explores innovative strategies for resolving intricate computational challenges encountered in the context of interplanetary distances. The purpose of this study is to investigate the impact of issues such as latency, data corruption, and power consumption on classical computing paradigms in space. We examine the concept of "interplanetary cloud systems", which use distributed computation and data storage to tackle these issues. The article also covers advanced techniques for sending data, including communication systems using quantum entanglement and deep space networks. The article integrates the disciplines of astronomy, computer science, and space exploration to provide a holistic perspective on the issue. It is crucial to emphasise that the implementation of fault-tolerant systems, adaptive algorithms, and robust networking protocols is essential for the success of extrasolar computing programs. The article thoroughly explores the potential and risks that arise when space travel, astronomy, and computer science intersect. We explore the potential future of interplanetary data processing and communication technologies via the examination of fault tolerance, adaptive algorithms, and resilient networking. The importance of resolving computational issues in space increases as humanity extends its presence in the cosmos. The study results have significant ramifications for the development of forthcoming technology enabling interplanetary data transfer, hence facilitating human colonisation and scientific exploration beyond Earth.

Deterministic and multiuser quantum teleportation network of continuous-variable polarization states

Quantum teleportation is widely applied as a key ingredient in quantum information science, and quantum network provides unique abilities for upscaling its applications. Polarization state of light is a vital degree of freedom with the advantages of remote transfer and direct light-atom interaction. To construct a multiuser quantum network, deterministic quantum teleportation of polarization state in more users' network remains challenging. Compared with photonic quantum state, the deterministic quantum teleportation network of polarization state is realized with a single set of continuous-variable entangled states. The key techniques include only one set of quadrature entangled network, single quadrature controller, and active polarization controller. Arbitrary polarization state is deterministically and controllably teleported in such a system involving four or three users. This system is deterministic and scalable with user number, which enables the potential application in deterministic metropolitan quantum network. Published by the American Physical Society 2024

Additive manufacturing of highly entangled polymer networks.

Incorporation of polymer chain entanglements within a single network can synergistically improve stiffness and toughness, yet attaining such dense entanglements through vat photopolymerization additive manufacturing [e.g., digital light processing (DLP)] remains elusive. We report a facile strategy that combines light and dark polymerization to allow constituent polymer chains to densely entangle as they form within printed structures. This generalizable approach reaches high monomer conversion at room temperature without the need for additional stimuli, such as light or heat after printing, and enables additive manufacturing of highly entangled hydrogels and elastomers that exhibit fourfold- to sevenfold-higher extension energies in comparison to that of traditional DLP. We used this method to print high-resolution and multimaterial structures with features such as spatially programmed adhesion to wet tissues.

Jellyfish-Inspired Visual and Sensory Bubbling Robots with Automatic 3D Morphable Films for Underwater Environmental Interactions.

Coelenterates, such as Atolla jellyfish, are capable of integrating color, communication, and motion in a sophisticated manner, thereby enabling them to function as intelligent biological systems that can adapt to the challenges of the underwater environment. Extensive efforts have been dedicated to exploiting underwater visual, sensory, actuating, or combined systems. However, current biomimetic soft systems are still limited by the lack of comprehensive, integrated functional skins that can automatically deform, dynamically sense, and further send color signals when diving into underwater conditions. Here, we propose the synthetic soft skins composed of assembled entangled carbon nanotube networks and fluorescent unit-embedded elastomers which can be applied in a suspended form to allow autonomic 3D deformation, real-time perception, and dynamic fluorescence color transformation. The capabilities of the sensory and color display thresholds were controlled through the entanglement density of carbon nanotubes and the suspended area. As a demonstration, the soft thin skin was integrated into an artificial jellyfish robot, enabling the realization of a closed-loop feedback system for dynamic sensory processing, signal processing, and further 3D morphing-induced fluorescent color change, demonstrating significant potentials in underwater visual display, danger warning, and environmental exploration.

Efficient and secure quantum secret sharing for eight users

Quantum secret sharing (QSS) has emerged as a promising avenue for storing secret with quantum-enhanced security. However, practical applications are hindered by the challenge for simultaneously implementing high-efficiency, high-security, and high-flexibility QSS with multiple users. Here we present an efficient, secure, and flexible QSS involving eight users with a continuous-variable eight-partite bound entanglement (BE) state, where only two nondegenerated optical parameter amplifiers are required. Such abilities are attributed to the generation of the eight-partite BE state with precise phase controlling systems and a large entanglement network, and fiber distribution with polarization-division multiplexing. In the QSS, a higher key rate can be demonstrated, when a secret is extracted through flexible combinations of more collaborative users. Our system may pave the way for the spatially separated multiuser quantum communications, while minimizing quantum hardware. Published by the American Physical Society 2024

Quantum Networks: A New Platform for Aerospace

The ability to distribute entanglement between quantum nodes may unlock new capabilities in the future that include teleporting information across multinode networks, higher resolution detection via entangled sensor arrays, and measurements beyond the quantum limit enabled by networked atomic clocks. These new quantum networks also hold promise for the Aerospace community in areas such as deep space exploration, improved satellite communication, and synchronizing drone swarms. Although exciting, these applications are a long way off from providing a “real-world” benefit, as they have only been theoretically explored or demonstrated in small-scale experiments. An outstanding challenge is to identify near-term use cases for quantum networks; this may be an intriguing new area of interest for the aerospace community, as the quantum networking field would benefit from more multidisciplinary collaborations. This paper introduces quantum networking, discusses the difficulties in distributing entanglement within these networks, highlights recent progress toward this endeavor, and features two current case studies on mobile quantum nodes and an entangled clock network, both of which are relevant to the aerospace community.

Developing highly flame-retardant PA6-based composites via in-situ PPS nanofiber network

This study investigates the enhancement of flame-retardant properties in polyamide 6 (PA6) composites through the incorporation of nanofibrillated polyphenylene sulfide (PPS) and a flame retardant, ammonium sulfamate (AS). By strategically combining a fibrillar PPS component (15 wt%) with a minimal AS concentration (1 wt%), the composite achieves a UL 94-V0 rating and a heightened limiting oxygen index (LOI) of 33.8 %. Rheological analyses reveal the formation of an entangled fibril network, contributing to a solid-like response that effectively suppresses flame propagation and prevents dripping. Micro-combustion calorimetry (MCC) results demonstrate a synergistic effect between the PPS nanofibril network and AS, leading to a significant 17 % reduction in peak heat release rate (PHRR) in PA6-nanofibrillated PPS-AS composites, showcasing improved flame-retardant properties compared to neat PA6. Despite a trade-off in mechanical properties, this research presents a promising strategy for enhancing the flame-retardant performance of PA6 composites, offering valuable insights for addressing fire safety challenges in PA6 applications.

Structural, topological, and rheological characteristics of entangled short-chain branched polymer melts under shear flow in comparison with the linear analog

We present a detailed analysis of the general influence of short branches on the structural, topological, and rheological behaviors of entangled short-chain branched (SCB) polyethylene (PE) melt systems under shear flow via direct comparison with the corresponding linear analogs using extensive atomistic nonequilibrium molecular dynamics (NEMD) simulations, for a wide range of flow strengths. In comparison with the linear melt, the SCB systems generally exhibit more compact chain structures and larger dynamic resistance, in response to an imposed flow field at all flow strengths. These features essentially arise from (i) the increased chain stiffness due to the torsional restriction of backbone atoms around the branch points and (ii) the fast random Brownian motion of short branches via their very short characteristic relaxation time. We analyzed various structural and rheological properties, such as anisotropic chain dimension and orientation and their detailed distributions, topological characteristics of the entanglement network, material functions, chain rotation dynamics, and flow birefringence. Distinctive physical characteristics of the entangled SCB systems exposed by these individual properties can be consistently understood based on the fundamental structural and dynamical roles of short branches. These findings are considered informative in our systematic understanding and prediction for the general rheological behaviors of long entangled SCB polymer systems under flow, and in tuning the material properties of SCB polymers in practical applications.

Head pose estimation with particle swarm optimization‐based contrastive learning and multimodal entangled GCN

AbstractHead pose estimation is an especially challenging task due to the complexity nonlinear mapping from 2D feature space to 3D pose space. To address the above issue, this paper presents a novel and efficient head pose estimation framework based on particle swarm optimized contrastive learning and multimodal entangled graph convolution network. Firstly, a new network, the region and difference‐aware feature pyramid network (RD‐FPN), is proposed for 2D keypoints detection to alleviate the background interference and enhance the feature expressiveness. Then, particle swarm optimized contrastive learning is constructed to alternatively match 2D and 3D keypoints, which takes the multimodal keypoints matching accuracy as the optimization objective, while considering the similarity of cross‐modal positive and negative sample pairs from contrastive learning as a local contrastive constraint. Finally, multimodal entangled graph convolution network is designed to enhance the ability of establishing geometric relationships between keypoints and head pose angles based on second‐order bilinear attention, in which point‐edge attention is introduced to improve the representation of geometric features between multimodal keypoints. Compared with other methods, the average error of our method is reduced by 8.23%, indicating the accuracy, generalization, and efficiency of our method on the 300W‐LP, AFLW2000, BIWI datasets.