Img2Logo: Generating Golden Ratio Logos from Images

Logos are one of the most important graphic design forms that use an abstracted shape to clearly represent the spirit of a community. Among various styles of abstraction, a particular golden-ratio design is frequently employed by designers to create a concise and regular logo. In this context, designers utilize a set of circular arcs with golden ratios (i.e., all arcs are taken from circles whose radii form a geometric series based on the golden ratio) as the design elements to manually approximate a target shape. This error-prone process requires a large amount of time and effort, posing a significant challenge for design space exploration. In this work, we present a novel computational framework that can automatically generate golden ratio logo abstractions from an input image. Our framework is based on a set of carefully identified design principles and a constrained optimization formulation respecting these principles. We also propose a progressive approach that can efficiently solve the optimization problem, resulting in a sequence of abstractions that approximate the input at decreasing levels of detail. We evaluate our work by testing on images with different formats including real photos, clip arts, and line drawings. We also extensively validate the key components and compare our results with manual results by designers to demonstrate the effectiveness of our framework. Moreover, our framework can largely benefit design space exploration via easy specification of design parameters such as abstraction levels, golden circle sizes, etc.     

A large scale parallel fluid-structure interaction computing platform for simulating structural responses to a detonation shock

Due to the intrinsic nature of multi-physics, it is prohibitively complex to design and implement a simulation software platform for study of structural responses to a detonation shock. In this article, a partitioned fluid-structure interaction computing platform is designed for parallel simulating structural responses to a detonation shock. The detonation and wave propagation are modeled in an open-source multi-component solver based on OpenFOAM and blastFoam, and the structural responses are simulated through the finite element library deal.II. To capture the interaction dynamics between the fluid and the structure, both solvers are adapted to preCICE. For improving the parallel performance of the computing platform, the inter-solver data is exchanged by peer-to-peer communications and the intermediate server in conventional multi-physics software is eliminated. Furthermore, the coupled solver with detonation support has been deployed on a computing cluster after considering the distributed data storage and load-balancing between solvers. The 3D numerical result of structural responses to a detonation shock is presented and analyzed. On 256 processor cores, the speedup ratio of the simulations for a detonation shock reach 178.0 with 5.1 million of mesh cells and the parallel efficiency achieve 69.5%. The results demonstrate good potential of massively parallel simulations. Overall, a general-purpose fluid-structure interaction software platform with detonation support is proposed by integrating open source codes. And this work has important practical significance for engineering application in fields of construction blasting, mining, and so forth.     

Surface Growth of Boron Nitride Nanotubes through Boron Source Design

Boron nitride nanotubes (BNNTs) are promising materials due to their unique physical and chemical properties. Fabrication technologies based on gas-phase reactions reduce the control and collection efficiency of BNNTs due to reactant and product dispersion within the reaction vessel. A surface growth method that allows for controllable growth of BNNTs in certain regions using a preburied boron source is introduced. This work leverages the high solubility of boron in metals to create a boronized layer on the surface which serves as the boron source to confine the growth of BNNTs. Dense and uniform BNNTs are obtained after loading catalysts onto the boronized substrate and annealing under ammonia. Confirmatory experiments demonstrate that the boride layer provides boron for BNNTs growth. Furthermore, the patterned growth of BNNTs is realized by patterning the boronizing region, demonstrating the controllability of this method. In addition, the Ni substrate with BNNTs growth exhibits better performance in corrosion resistance and thermal conductivity than pure Ni. This study introduces an alternative strategy for the surface growth of BNNTs based on boron source design, which offers new possibilities for the controllable preparation of BNNTs for various applications.     

Functional 2D Phases in Mixed Dimensional Perovskite Photovoltaics

Organic-inorganic hybrid perovskite solar cells (PSCs) with unique properties exhibit their powerful competitiveness in the photovoltaic field over the past few years. However, the challenges of stability for perovskite devices limit the commercialization and further development. The 2D/3D hybrid structures combine the superior efficiency of bulk perovskites and the superior stability of layered perovskites and gradually get hotspots of the photovoltaic field. In addition, there remains a lack of comprehensive understanding and systematic summary of the function of 2D perovskite attributed to the complex nature of 2D/3D structures. Here, the latest progress of 2D/3D hybrid structures and focus on the functionality of 2D phases in mixed structures and the underlying mechanism from the perspective of their different distributions in the perovskite layer is summarized. Then, the insight and vital factors for overall improvements in the stability of 2D/3D structures are thoroughly discussed. Finally, it is expected that this review will contribute to the present challenges and future research prospects in the photovoltaic industry.     

Self-Adhesive Polydimethylsiloxane Foam Materials Decorated with MXene/Cellulose Nanofiber Interconnected Network for Versatile Functionalities

Polydimethylsiloxanes (PDMS) foam as one of next-generation polymer foam materials shows poor surface adhesion and limited functionality, which greatly restricts its potential applications. Fabrication of advanced PDMS foam materials with multiple functionalities remains a critical challenge. In this study, unprecedented self-adhesive PDMS foam materials are reported with worm-like rough structure and reactive groups for fabricating multifunctional PDMS foam nanocomposites decorated with MXene/cellulose nanofiber (MXene/CNF) interconnected network by a facile silicone foaming and dip-coating strategy followed by silane surface modification. Interestingly, such self-adhesive PDMS foam produces strong interfacial adhesion with the hybrid MXene/CNF nano-coatings. Consequently, the optimized PDMS foam nanocomposites have excellent surface super-hydrophobicity (water contact angle of ≈159^o), tunable electrical conductivity (from 10⁻⁸ to 10 S m⁻¹), stable compressive cyclic reliability in both wide-temperature range (from −20 to 200 ^oC) and complex environments (acid, sodium, and alkali conditions), outstanding flame resistance (LOI value of >27% and low smoke production rate), good thermal insulating performance and reliable strain sensing in various stress modes and complex environmental conditions. It provides a new route for the rational design and development of advanced PDMS foam nanocomposites with versatile multifunctionalities for various promising applications such as intelligent healthcare monitoring and fire-safe thermal insulation.     

Privacy Preserving distributed smart grid system based on Hyperledger Fabric and Wireguard

Smart grid has drawn a lot of attention and investment in recent years, which not only helps the modern generation and distribution of traditional power but also highly widens the application of renewable energy sources. However, the main challenges in the application of smart grid are 1. the privacy preservation of users' information and 2. the trustful transmission channel among peers. In order to solve these problems, VPN and blockchain can be considered since they have some features perfectly suitable for these situations. In this paper, we propose a smart grid system based on WireGuard and Hyperledger Fabric to solve the problems mentioned above. And we also implement the whole system and give a view by web application. What's more, all the functionalities are displayed and tested, including building a smart device simulator, deploying data visualization and making some performance evaluations about transactions and WireGuard communication. Experiment results show that the introduction of WireGuard into network infrastructure does not cause too much loss of bandwidth and delay, but it ensures a certain degree of communication security. And Fabric provides the consistency and traceability of transactions in smart grid system.     

An Artificial Autonomic Nervous System That Implements Heart and Pupil as Controlled by Artificial Sympathetic and Parasympathetic Nerves

The autonomic nervous system maintains homeostasis in organisms through complex neural pathways and responds adaptively to changes in the external and internal environment. The fabrication of an artificial autonomic nervous system is reported that replicates combined effects of sympathetic and parasympathetic nerves on cardiac activity and pupillary control, to mimic the regulation of autonomic nervous system to external changes. The artificial autonomic nerve-controlled pupil contraction and relaxation, modulating the rate of heartbeats for normal cardiac rhythm and arrhythmia as reflected by blink rates of a signal indicator. These functions are switched by using a parallel-channeled synaptic transistor with a special n-i-p heterostructure that has a 2D h-BN insulator in the middle to provide barrier against ion injection into the 2D MoS₂ bottom n-channel and enable short-term plasticity as induced by acetylcholine, and the electrochemical doping reaction occurred at the P3HT nanowire p-channels on top to enable relatively long-term plasticity as induced by noradrenaline. Low-energy consumption down to femtojoule and an ultrahigh paired-pulse facilitation index up to ≈455% are demonstrated. An artificial neural network based on device characteristics achieves a high recognition accuracy for electrocardiogram patterns. This study extends insights into artificial nerves-inspired biological signal processing and recognition.     

19.28% Efficiency and Stable Polymer Solar Cells Enabled by Introducing an NIR-Absorbing Guest Acceptor

Here, a near-infrared (NIR)-absorbing small-molecule acceptor (SMA) Y-SeNF with strong intermolecular interaction and crystallinity is developed by combining selenophene-fused core with naphthalene-containing end-group, and then as a custom-tailor guest acceptor is incorporated into the binary PM6:L8-BO host system. Y-SeNF shows a 65 nm red-shifted absorption compared to L8-BO. Thanks to the strong crystallinity and intermolecular interaction of Y-SeNF, the morphology of PM6:L8-BO:Y-SeNF can be precisely regulated by introducing Y-SeNF, achieving improved charge-transporting and suppressed non-radiative energy loss. Consequently, ternary polymer solar cells (PSCs) offer an impressive device efficiency of 19.28% with both high photovoltage (0.873 V) and photocurrent (27.88 mA cm⁻²), which is one of the highest efficiencies in reported single-junction PSCs. Notably, ternary PSC has excellent stability under maximum-power-point tracking for even over 200 h, which is better than its parental binary devices. The study provides a novel strategy to construct NIR-absorbing SMA for efficient and stable PSCs toward practical applications.     

Femtosecond Laser 4D Printing of Light-Driven Intelligent Micromachines

Intelligent micromachines that respond to external light stimuli have a broad range of potential applications, such as microbots, biomedicine, and adaptive optics. However, artificial light-driven intelligent micromachines with a low actuation threshold, rapid responsiveness, and designable and precise 3D transformation capability remain unachievable to date. Here, a single-material and one-step 4D printing strategy are proposed to enable the nanomanufacturing of agile and low-threshold light-driven 3D micromachines with programmable shape-morphing characteristics. The as-developed carbon nanotube-doped composite hydrogel simultaneously enhanced the light absorption, thermal conductivity, and mechanical modulus of the crosslinked network, thus significantly increasing the light sensitivity and response speed of micromachines. Moreover, the structural design and assembly of asymmetric microscale mechanical metamaterial unit cells enable the highly efficient additive nanomanufacturing of 3D shape-morphable micromachines with large dynamic modulation and spatiotemporal controllability. Using this strategy, the world's smallest artificial beating heart with programmable light-stimulus responsiveness for the cardiac cycle is successfully printed. This 4D printing method paves the way for the construction of multifunctional intelligent micromachines for bionics, drug delivery, integrated microsystems, and other fields.