Preparation of Graphene Materials and Their Applications in the Field of Electrochemistry

In the development of modern society, many new materials and technologies have been integrated into the development of various industries. As a new type of two-dimensional carbon nanomaterials, graphene has great advantages in physical and chemical properties and is widely used in various fields of development. Among them, the electrochemical method is one of the important ways to prepare graphene materials, which has the characteristics of quickness and environmental protection, and can effectively produce a large amount of high-quality graphene and its composite materials. Based on this, the paper introduces the preparation method of graphene materials and studies the application of graphene materials in the field of electrochemistry

Preparation and Properties of Graphene-based Inorganic Nanocomposites

Graphene is a two-dimensional hexagonal monoatomic layer crystal composed of carbon atoms, which exhibits the shape of a honeycomb and plays an important role in the fields of optics and mechanics. It also has the advantages of high specific surface area, strong chemical stability and special planar structure. It is an ideal carrier for carrying various inorganic compounds and is suitable for the development of high performance graphene-based inorganic nanocomposites.[1] Based on this, the paper introduces the characteristics of graphene, expounds the related content of graphene-based inorganic nanocomposites, and studies the preparation methods and properties of graphene-based inorganic nanocomposites

TeCH: Text-guided Reconstruction of Lifelike Clothed Humans

Despite recent research advancements in reconstructing clothed humans from a single image, accurately restoring the "unseen regions" with high-level details remains an unsolved challenge that lacks attention. Existing methods often generate overly smooth back-side surfaces with a blurry texture. But how to effectively capture all visual attributes of an individual from a single image, which are sufficient to reconstruct unseen areas (e.g., the back view)? Motivated by the power of foundation models, TeCH reconstructs the 3D human by leveraging 1) descriptive text prompts (e.g., garments, colors, hairstyles) which are automatically generated via a garment parsing model and Visual Question Answering (VQA), 2) a personalized fine-tuned Text-to-Image diffusion model (T2I) which learns the "indescribable" appearance. To represent high-resolution 3D clothed humans at an affordable cost, we propose a hybrid 3D representation based on DMTet, which consists of an explicit body shape grid and an implicit distance field. Guided by the descriptive prompts + personalized T2I diffusion model, the geometry and texture of the 3D humans are optimized through multi-view Score Distillation Sampling (SDS) and reconstruction losses based on the original observation. TeCH produces high-fidelity 3D clothed humans with consistent & delicate texture, and detailed full-body geometry. Quantitative and qualitative experiments demonstrate that TeCH outperforms the state-of-the-art methods in terms of reconstruction accuracy and rendering quality. The code will be publicly available for research purposes at https://huangyangyi.github.io/TeCHComment: Project: https://huangyangyi.github.io/TeCH, Code: https://github.com/huangyangyi/TeC

TADA! Text to Animatable Digital Avatars

We introduce TADA, a simple-yet-effective approach that takes textual descriptions and produces expressive 3D avatars with high-quality geometry and lifelike textures, that can be animated and rendered with traditional graphics pipelines. Existing text-based character generation methods are limited in terms of geometry and texture quality, and cannot be realistically animated due to inconsistent alignment between the geometry and the texture, particularly in the face region. To overcome these limitations, TADA leverages the synergy of a 2D diffusion model and an animatable parametric body model. Specifically, we derive an optimizable high-resolution body model from SMPL-X with 3D displacements and a texture map, and use hierarchical rendering with score distillation sampling (SDS) to create high-quality, detailed, holistic 3D avatars from text. To ensure alignment between the geometry and texture, we render normals and RGB images of the generated character and exploit their latent embeddings in the SDS training process. We further introduce various expression parameters to deform the generated character during training, ensuring that the semantics of our generated character remain consistent with the original SMPL-X model, resulting in an animatable character. Comprehensive evaluations demonstrate that TADA significantly surpasses existing approaches on both qualitative and quantitative measures. TADA enables creation of large-scale digital character assets that are ready for animation and rendering, while also being easily editable through natural language. The code will be public for research purposes

Optimizing electric adjustment mechanism using the combination of multi-body dynamics and control

Abstract : Optimization was carried out on the electric adjustment mechanism for transplanter by using the multidisciplinary design with weight, transmission efficiency, vibration frequency, and control error as the optimization goals. Then, a collaborative optimization model for the multidisciplinary design of a mechanism system was constructed. Based on ISIGHT software, the multidisciplinary design integration platform for the electric adjustment mechanism was built. A hybrid algorithm comprising the dual sequential quadratic programming method and the multi-island genetic algorithm was used to calculate the model. Optimization results show that the weight of the electric adjustment mechanism drops by 13.10%, its vibration frequency decreases by 27.71%, its transmission efficiency increases by 20.26%, and the control error decreases by 36.98%. Under the mutual coordination and balance of all discipline goals, the optimal values of the design variables of the electric adjustment mechanism indicate overall optimal performance

Enhancing Faraday and Kerr rotations based on toroidal dipole mode in an all-dielectric magneto-optical metasurface

The magneto-optical Faraday and Kerr effects are widely used in modern optical devices. In this letter, we propose an all-dielectric metasurface composed of perforated magneto-optical thin films, which can support the highly confined toroidal dipole resonance and provide full overlap between the localized electromagnetic field and the thin film, and consequently enhance the magneto-optical effects to an unprecedented degree. The numerical results based on finite element method show that the Faraday and Kerr rotations can reach -13.59${\deg}$ and 8.19${\deg}$ in the vicinity of toroidal dipole resonance, which are 21.2 and 32.8 times stronger than those in the equivalent thickness of thin films, respectively. In addition, we design an environment refractive index sensor based on the resonantly enhanced Faraday and Kerr rotations, with sensitivities of 62.96 nm/RIU and 73.16 nm/RIU, and the corresponding maximum figures of merit 132.22${\deg}$/RIU and 429.45${\deg}$/RIU, respectively. This work provides a new strategy for enhancing the magneto-optical effects at nanoscale, and paves the way for the research and development of magneto-optical metadevices such as sensors, memories, and circuits

Integrating a dual-silicon photoelectrochemical cell into a redox flow battery for unassisted photocharging

Solar rechargeable flow cells (SRFCs) provide an attractive approach for in situ capture and storage of intermittent solar energy via photoelectrochemical regeneration of discharged redox species for electricity generation. However, overall SFRC performance is restricted by inefficient photoelectrochemical reactions. Here we report an efficient SRFC based on a dual-silicon photoelectrochemical cell and a quinone/bromine redox flow battery for in situ solar energy conversion and storage. Using narrow bandgap silicon for efficient photon collection and fast redox couples for rapid interface charge injection, our device shows an optimal solar-to-chemical conversion efficiency of similar to 5.9% and an overall photon-chemical-electricity energy conversion efficiency of similar to 3.2%, which, to our knowledge, outperforms previously reported SRFCs. The proposed SRFC can be self-photocharged to 0.8V and delivers a discharge capacity of 730 mAhl(-1). Our work may guide future designs for highly efficient solar rechargeable devices

A novel ZRS variant causes preaxial polydactyly type I by increased sonic hedgehog expression in the developing limb bud.

PurposePreaxial polydactyly (PPD) is a common congenital hand malformation classified into four subtypes (PPD I-IV). Variants in the zone of polarizing activity regulatory sequence (ZRS) within intron 5 of the LMBR1 gene are linked to most PPD types. However, the genes responsible for PPD I and the underlying mechanisms are unknown.MethodsA rare large four-generation family with isolated PPD I was subjected to genome-wide genotyping and sequence analysis. In vitro and in vivo functional studies were performed in Caco-2 cells, 293T cells, and a knockin transgenic mouse model.ResultsA novel g.101779T>A (reference sequence: NG_009240.2; position 446 of the ZRS) variant segregates with all PPD I-affected individuals. The knockin mouse with this ZRS variant exhibited PPD I phenotype accompanying ectopic and excess expression of Shh. We confirmed that HnRNP K can bind the ZRS and SHH promoters. The ZRS mutant enhanced the binding affinity for HnRNP K and upregulated SHH expression.ConclusionOur results identify the first PPD I disease-causing variant. The variant leading to PPD I may be associated with enhancing SHH expression mediated by HnRNP K. This study adds to the ZRS-associated syndromes classification system for PPD and clarifies the underlying molecular mechanisms

High-Fidelity Clothed Avatar Reconstruction from a Single Image

This paper presents a framework for efficient 3D clothed avatar reconstruction. By combining the advantages of the high accuracy of optimization-based methods and the efficiency of learning-based methods, we propose a coarse-to-fine way to realize a high-fidelity clothed avatar reconstruction (CAR) from a single image. At the first stage, we use an implicit model to learn the general shape in the canonical space of a person in a learning-based way, and at the second stage, we refine the surface detail by estimating the non-rigid deformation in the posed space in an optimization way. A hyper-network is utilized to generate a good initialization so that the convergence o f the optimization process is greatly accelerated. Extensive experiments on various datasets show that the proposed CAR successfully produces high-fidelity avatars for arbitrarily clothed humans in real scenes

Deciphering the effects of genotype and climatic factors on the performance, active ingredients and rhizosphere soil properties of Salvia miltiorrhiza

IntroductionSalvia miltiorrhiza Bunge is an important medicinal herb, which is widely cultivated in most parts of China. It has attracted considerable attention because of its pharmacological properties and potential health benefits.MethodsWe used a field experiment to determine the effects of different genotypes and climatic factors on the performance (plant biomass, morphological parameters), active ingredients, rhizosphere soil physicochemical properties and microbial composition of S. miltiorrhiza at five cultivation locations.ResultsThe results showed that these parameters were significantly different in the six different genotypes of S. miltiorrhiza from five producing areas. Genotype and soil physicochemical properties were the main factors affecting the growth traits of S. miltiorrhiza, while genotype, climate and soil physicochemical properties were the main factors affecting the content of active components of S. miltiorrhiza. Microbial phospholipid fatty acid analysis showed that the biomass of Gram-positive and Gram-negative bacteria was affected by the genotypes of S. miltiorrhiza plants, while the biomass of arbuscular mycorrhizal fungi, fungi, Gram-positive and Gram-negative bacteria was affected by climate factors.DiscussionBased on the main results, DS993 was the most suitable genotype for S. miltiorrhiza in the five producing areas from the perspective of comprehensive growth traits and medicinal components, while DS993 and DS2000 were suitable for planting in Shandong province from the perspective of origin. DS996 is not suitable for all of the above production areas. These results are helpful to understand the ecological adaptability of different genotypes of S. miltiorrhiza resources, and to select appropriate S. miltiorrhiza genotypes for specific planting areas, so as to maximize yield and quality