A Dual-Stream-Modulated Learning Framework for Illuminating and Super-Resolving Ultra-Dark Images.

Enhancement of image resolution for scenes captured under extremely dim conditions represents a practical yet challenging problem that has received little attention. In such low-light scenarios, the limited lighting and minimal signal clarity tend to intensify issues such as diminished detail visibility and altered color accuracy, which are often more severe during the image enhancement process than in scenarios with adequate lighting. Consequently, standard methods for enhancing low-light images or improving their resolution, whether implemented independently or through a combined approach, generally face challenges in effectively restoring luminance, preserving color integrity, and detailing intricate features. To conquer these issues, this article introduces an innovative dual-stream (DS) modulated learning framework designed to tackle the real-world coupled degradation issues in super-resolution (SR) under low-light conditions. Leveraging natural image color characteristics, we introduce a self-regularized luminance constraint to specifically target uneven illumination. We develop illumination-semantic dual modulator (ISDM), a refinement middleware embedded in the decoding stage to bridge illumination and semantic features concurrently, aimed at safeguarding the integrity of lighting and color details at the feature level. Our approach replaces simple upsampling methods with the resolution-sensitive merging upsampler (RSMU) module, which integrates diverse sampling techniques to effectively reduce artifacts and halo effects. Comprehensive experiments on three benchmarks showcase the applicability and generalizability of our approach to diverse and challenging ultra-poorly lit settings, outperforming state-of-the-art methods with a notable improvement. The code and benchmark are publicly available at https://github.com/moriyaya/UltraIS.

PVDF-HFP/PAN/PDA@LLZTO Composite Solid Electrolyte Enabling Reinforced Safety and Outstanding Low-Temperature Performance for Quasi-Solid-State Lithium Metal Batteries.

Lithium-ion batteries (LIBs) have achieved a triumph in the market of portable electronic devices since their commercialization in the 1990s due to their high energy density. However, safety issue originating from the flammable, volatile, and toxic organic liquid electrolytes remains a long-standing problem to be solved. Alternatively, composite solid electrolytes (CSEs) have gradually become one of the most promising candidates due to their higher safety and stable electrochemical performance. However, the uniform dispersity of ceramic filler within the polymer matrix remains to be addressed. Generally, all-solid-state lithium metal batteries without any liquid components suffer from poor interfacial contact and low ionic conductivity, which seriously affect the electrochemical performance. Here we report a CSE consisting of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI), polydopamine (PDA) coated Li6.4La3Zr1.4Ta0.6O12 (LLZTO) (denoted as PDA@LLZTO) microfiller, polyacrylonitrile (PAN), and poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP). Introducing only 4 µL of liquid electrolyte at the electrode|electrolyte interface, the CSE-based cells exhibit high ionic conductivity (0.4 × 10-3 S cm-1 at 25 °C), superior cycle stability, and excellent thermal stability. Even under low temperatures, the impressive electrochemical performance (78.8% of capacity retention after 400 cycles at 1 C, 0 °C, and decent capacities delivered even at low temperature of -20 °C) highlights the potential of such quasi-solid-state lithium metal batteries as a viable solution for the next-generation high-performance lithium metal batteries.

Towards ultra-wide operation range and high sensitivity: Graphene film based pressure sensors for fingertips.

Remarkable research efforts have been devoted to replicate the tactile sensitivity of human skin. Unfortunately, so far flexible pressure sensors reported barely fit the tactile requirements for fingertips, which could endure a pressure over 100 kPa and also can sense a gentle touch. It is vital to develop flexible pressure sensors which can ensure high sensitivity and wide operation range simultaneously, to satisfy the demands of mimicking the pressure sensing function of fingertips. In this work, a mini-size, light-weight but high-performance graphene film based pressure sensor is presented. Owing to the advanced structure with fluctuations on surface and fluffy-layered structure in cross-section of the graphene film, this pressure sensor shows an extraordinary performance of high sensitivity of 10.39 kPa-1 (0-2 kPa), ultra-wide operation range up to 200 kPa, impressively stable repeatability, high working frequency, rapid response and recovery time. Moreover, the demonstrated results of the detection of traditional Chinese medicine wrist-pulse waveform and the bionic fingertip tactile sensors, suggest the great application potential of the obtain device in biomedical field and bionic skins field.