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.     

Hyperelastic,Robust, Fire-Safe Multifunctional MXene Aerogels with Unprecedented Electromagnetic Interference Shielding Efficiency

MXene aerogels have shown great potential for many important functional applications, in particular electromagnetic interference (EMI) shielding. However, it has been a grand challenge to create mechanically hyperelastic, air-stable, and durable MXene aerogels for enabling effective EMI protection at low concentrations due to the difficulties in achieving tailorable porous structures, excellent mechanical elasticity, and desired antioxidation capabilities of MXene in air. Here, a facile strategy for fabricating MXene composite aerogels by co-assembling MXene and cellulose nanofibers during freeze-drying followed by surface encapsulation with fire-retardant thermoplastic polyurethane (TPU) is reported. Because of the maximum utilization of pore structures of MXene, and conductive loss enhanced by multiple internal reflections, as-prepared aerogel with 3.14 wt% of MXene exhibits an exceptionally high EMI shielding effectiveness of 93.5 dB, and an ultra-high MXene utilization efficiency of 2977.71 dB g g⁻¹, tripling the values in previous works. Owing to the presence of multiple hydrogen bonding and the TPU elastomer, the aerogel exhibits a hyperelastic feature with additional strength, excellent stability, superior durability, and high fire safety. This study provides a facile strategy for creating multifunctional aerogels with great potential for applications in EMI protection, wearable devices, thermal management, pressure sensing, and intelligent fire monitoring.     

Fitting objects with implicit polynomials by deep neural network

Implicit polynomials (IPs) are considered as a powerful tool for object curve fitting tasks due to their simplicity and fewer parameters. The traditional linear methods, such as 3L, MinVar, and MinMax, often achieve good performances in fitting simple objects, but usually work poorly or even fail to obtain closed curves of complex object contours. To handle the complex fitting issues, taking the advantages of deep neural networks, we designed a neural network model continuity-sparsity constrained network (CSC-Net) with encoder and decoder structure to learn the coefficients of IPs. Further, the continuity constraint is added to ensure the obtained curves are closed, and the sparseness constraint is added to reduce the spurious zero sets of the fitted curves. The experimental results show that better performances have been obtained on both simple and complex object fitting tasks.     

基于特征融合的无监督跨模态哈希

已有的无监督跨模态哈希（UCMH）方法主要关注构造相似矩阵和约束公共表征空间的结构,忽略了2个重要问题：一是它们为不同模态的数据提取独立的表征用以检索,没有考虑不同模态之间的信息互补;二是预提取特征的结构信息不完全适用于跨模态检索任务,可能会造成一些错误信息的迁移。针对第一个问题,提出一种多模态表征融合结构,通过对不同模态的嵌入特征进行融合,从而有效地综合来自不同模态的信息,提高哈希码的表达能力,同时引入跨模态生成机制,解决检索数据模态缺失的问题;针对第二个问题,提出一种相似矩阵动态调整策略,在训练过程中用学到的模态嵌入自适应地逐步优化相似矩阵,减轻预提取特征对原始数据集的偏见,使其更适应跨模态检索,并有效避免过拟合问题。基于常用数据集Flickr25k和NUS-WIDE进行实验,结果表明,通过该方法构建的模型在Flickr25k数据集上3种哈希位长检索的平均精度均值较DGCPN模型分别提高1.43%、1.82%和1.52%,在NUS-WIDE数据集上分别提高3.72%、3.77%和1.99%,验证了所提方法的有效性。     

Biomimetic Aerogel for Moisture-Induced Energy Harvesting and Self-Powered Electronic Skin

Moisture–electric generator (MEG)-based blue energy is widely studied. There is still a significant challenge in improving the power of the MEGs system and expanding its application in self-powered electronic skin. Inspired by the structure of ferns, a biomimetic moisture–electric aerogel is designed to collect energy. Polyvinyl alcohol dendritic colloids act as “roots” and “stems” to provide support and channels to transport water molecules. Meanwhile, “leaf-like” graphene oxide sheets generate electricity through direct interaction with water. Besides, based on the above biomimetic structure, this work further enhances the output performance of MEGs by increasing the specific surface area (120.4 m² g⁻¹) and introducing an ultra-high ion density gradient (from −35 to +37 mV). Meanwhile, due to the excellent water absorption, the MEGs show good salt resistance and cyclic stability. By constructing unique biomimetic structures, ultra-high ion density gradient, and regulating environmental conditions, a high-performance MEG is obtained, including ultra-high open-circuit voltage (1.9 V) and short-circuit current (82.5 µA), the industry-leading power density among MEGs with continuous output is reported in the literature (22.55 µW cm⁻²). Besides, the MEGs can accurately respond to environmental and pressure changes, showing its application potential in self-powered electronic skin.     

Skin-like Omnidirectional Stretchable Platform with Negative Poisson's Ratio for Wearable Strain–Pressure Simultaneous Sensor

Conventional elastomeric polymers used as substrates for wearable platforms have large positive Poisson's ratios (≈0.5) that cause a deformation mismatch with human skin that is multidirectionally elongated under bending of joints. This causes practical problems in elastomer-based wearable devices, such as delamination and detachment, leading to poorly reliable functionality. To overcome this issue, auxetic-structured mechanical reinforcement with glass fibers is applied to the elastomeric film, resulting in a negative Poisson's ratio (NPR), which is a skin-like stretchable substrate (SLSS). Several parameters for determining the materials and geometrical dimensions of the auxetic-structured reinforcing fillers are considered to maximize the NPR. Based on numerical simulation and digital image correlation analysis, the deformation tendencies and strain distribution of the SLSS are investigated and compared with those of the pristine elastomeric substrate. Owing to the strain-localization characteristics, an independent strain-pressure sensing system is fabricated using SLSS with a Ag-based elastomeric ink and a carbon nanotube-based force-sensitive resistor. Finally, it is demonstrated that the SLSS-based sensor platform can be applied as a wearable device to monitor the physical burden on the wrist in real time.     

Fast Li+ Transport via Silica Network-Driven Nanochannels in Ionomer-in-Framework for Lithium Metal Batteries

For the development of all-solid-state lithium metal batteries (LMBs), a high-porous silica aerogel (SA)-reinforced single-Li⁺ conducting nanocomposite polymer electrolyte (NPE) is prepared via two-step selective functionalization. The mesoporous SA is introduced as a mechanical framework for NPE as well as a channel for fast lithium cation migration. Two types of monomers containing weak-binding imide anions and Li⁺ cations are synthesized and used to prepare NPEs, where these monomers are grafted in SA to produce SA-based NPEs (SANPEs) as ionomer-in-framework. This hybrid SANPE exhibits high ionic conductivities (≈10⁻³ S cm⁻¹), high modulus (≈10⁵ Pa), high lithium transference number (0.84), and wide electrochemical window (>4.8 V). The resultant SANPE in the lithium symmetric cell possesses long-term cyclic stability without short-circuiting over 800 h under 0.2 mA cm⁻². Furthermore, the LiFePO₄|SANPE|Li solid-state batteries present a high discharge capacity of 167 mAh g⁻¹ at 0.1 C, good rate capability up to 1 C, wide operating temperatures (from −10 to 40 °C), and a stable cycling performance with 97% capacity retention and 100% coulombic efficiency after 75 cycles at 1 C and 25 °C. The SANPE demonstrates a new design principle for solid-state electrolytes, allowing for a perfect complex between inorganic silica and organic polymer, for high-energy-density LMBs.     

Selenium Substitution in Bithiophene Imide Polymer Semiconductors Enables High-Performance n-Type Organic Thermoelectric

Designing n-type polymers with high electrical conductivity remains a major challenge for organic thermoelectrics (OTEs). Herein, by devising a novel selenophene-based electron-deficient building block, the pronounced advantages of selenium substitution in simultaneously enabling advanced n-type polymers is demonstrated with high mobility (≈2 orders of magnitude higher versus their sulfur-based analogues due to both intensified intra- and inter-chain interactions) and much improved n-doping efficiency (enabled by the largely lowered LUMO level with a ≈0.2 eV margin) of the resulting polymers. Via side chain optimization and donor engineering, the selenium-substituted polymer, f-BSeI2TEG-FT, achieves a highest conductivity of 103.5 S cm⁻¹ and power factor of 70.1 µW m⁻¹ K⁻², which are among the highest values reported in literature for n-type polymers, and f-BSeI2TEG-FT greatly outperformed the sulfur-based analogue polymer by 40% conductivity increase. These results demonstrate that selenium substitution is a very effective strategy for improving n-type performance and provide important structure-property correlations for developing high-performing n-type OTE materials.     

Plasmon-Assisted Self-Encrypted All-Optical Memory

All-optical responsive nanomaterials, which can rapidly switch between two stable states, have been regarded as the next-generation memories due to their potential to realize binary information storage and implement on-chip, integrated photonic neuromorphic systems. Rare earth oxides are preeminent candidates owing to their extraordinary luminescent stability and narrow optical transitions. However, due to the lack of simple and effective optical switches, it is difficult to realize all-optical data storage, encoding, and retrieval by pure rare earth-doped luminescent nanoparticles. Here, a rapid and high-contrast of 10⁴ luminescent switching of Y₂O₃:Eu³⁺ nanoparticle between the enhancement and quenching states is achieved by employing the strong light confinement and ultrafast thermal response of localized surface plasmon resonance. A self-encrypted all-optical memory is presented with optical information writing, encryption, reading, and re-writing, and a high-sensitivity synaptic response of emitters to frequency and light intensity flux, which can be harnessed to encrypt information flows and promote convenient and high-security information encryption. Such a convenient and secure plasmonic thermally assisted self-encrypting luminescent switch paves the way for constructing high-performance stimuli-responsive rare earth oxide crystals on demand and expanding their applications in various data encryption, anti-counterfeiting, and rewritable colouration devices.     

Mo-Modified ZnIn2S4@NiTiO3 S-Scheme Heterojunction with Enhanced Interfacial Electric Field for Efficient Visible-Light-Driven Hydrogen Evolution

Designing and developing visible-light-responsive materials for solar to chemical energy is an efficient and promising approach to green and sustainable carbon-neutral energy systems. Herein, a facile in situ growth hydrothermal strategy using Mo-modified ZnIn₂S₄ (Mo-ZIS) nanosheets coupled with NiTiO₃ (NTO) microrods to synthesize multifunctional Mo-modified ZIS wrapped NTO microrods (Mo-ZIS@NTO) photocatalyst with enhanced interfacial electric field (IEF) effect and typical S-scheme heterojunction is reported. Mo-ZIS@NTO catalyst possesses wide-spectrum light absorption properties, excellent visible light-to-thermal energy effect, electron mobility, charges transfer, and strong IEF and exhibits excellent solar-to-chemical energy conversion for efficient visible-light-driven photocatalytic hydrogen evolution. Notably, the engineered Mo_1.4-ZIS@NTO catalyst exhibits superior performance with H₂ evolution rate of up to 14.06 mmol g⁻¹ h^{− 1} and the apparent quantum efficiency of 44.1% at 420 nm. The scientific explorations provide an in-depth understanding of microstructure, S-scheme heterojunction, enhanced IEF, Mo-dopant facilitation effect. Moreover, the theoretical simulations verify the critical role of Mo element in promoting the adsorption and activation of H₂O molecules, modulating the H adsorption behavior on active S sites, and thus accelerating the overall catalytic efficiency. The photocatalytic hydrogen evolution mechanism via S-scheme heterojunction with adjustable IEF regulation over Mo_1.4-ZIS@NTO is also demonstrated.