Jing Wang

Microbial colony analysis is routinely used in clinical microbiology, pharmaceutical quality control, food safety, and environmental monitoring. Colony enumeration remains challenging because real-world plates frequently show crowding, size variation, background debris, and plate-rim interference. Low contrast on membrane or filter media, weak colony boundaries, and ultra-dense or too-numerous-to-count (TNTC) growth further complicate analysis. These conditions increase counting variability and limit rule-based counters. This review examines artificial intelligence (AI)-enabled colony analysis and links recurrent plate-reading challenges to method selection and validation requirements. We examine traditional threshold- and morphology-based pipelines, object detection, semantic segmentation, instance segmentation, and density- or keypoint-based estimation. Current evidence is stronger for plate-level triage and semi-quantitative interpretation than for direct colony enumeration. However, evidence supporting routine quantitative colony-forming unit (CFU) reporting across laboratories remains limited. Reliable deployment requires methods suited to plate format, organism, imaging conditions, and intended use, with validation in the target workflow.

Hydrogels are attractive for flexible electronics and wearable sensors, yet their performance is severely limited at subzero temperatures due to ice crystallization, dehydration, and mechanical embrittlement. Here, we report a CaCl2-enhanced double-network (DN) hydrogel (BNP-x) that integrates excellent anti-freezing, mechanical, and adhesive properties with reliable strain-sensing capabilities. The hydrogel combines a covalently crosslinked P(NIPAm-co-HEA) network and an ionically coordinated poly(acrylic acid) network, in which Ca2+ ions regulate water states and suppress ice formation. The optimized BNP-6 hydrogel exhibits excellent low-temperature performance, maintaining a tensile strength of 0.16 MPa and an elongation at break of ∼849% at –30 °C with minimal mass loss and stable properties over repeated freeze–thaw cycles. Owing to the synergistic DN structure and mobile Ca2+ ions, BNP-6 retains high ionic conductivity (44.1 mS cm–1 at –10 °C), representing only a 17.9% decrease compared to its room-temperature value. Moreover, the hydrogel demonstrates stable adhesion, rapid strain response, and reliable sensing performance under subzero conditions—even during cyclic deformation and self-healing processes—highlighting its potential for robust low-temperature wearable electronics and bioelectronic interfaces operating in harsh environments.

Grasping objects such as handles, mice, and phones plays a central role in human-machine interaction, yet the contact surfaces of the hand, despite their exquisite tactile sensitivity, are rarely exploited as channels for information transfer. Here, we introduce transdermal all-directional targeting (TADT), a static-contact interface design strategy that converts passive grip surfaces into active tactile displays, allowing users to grasp stably while receiving spatially and temporally evolving information on the fingertips. TADT enhances sub-actuator-pitch energy delivery by integrating a microtextured skin-coupling interface with phase-controlled vibrotactile actuation, thereby generating steerable three-dimensional tactile foci beneath the skin, enabling >200-hertz vibration and sub-actuator-pitch spatial super-resolution. Psychophysical experiments show that TADT lowers detection thresholds by 30% and reduces power consumption by 80% compared with designs without TADT. Using static grip alone, users reliably identified six directional cues and completed nonvisual indoor navigation and virtual reality interaction tasks, demonstrating a compact, energy-efficient modality for expressive tactile communication.

The integration of efficient anti-solid fouling and high-performance microwave absorption into a single material platform remains a critical challenge, limiting advancements in radar stealth, aerospace, and Arctic infrastructures. Herein, we present a self-lubricating composite with embedded hydroxylated Fe₃O₄-reduced graphene oxide (rGO@Fe₃O₄) hybrids that overcomes this challenge through a synergistic hierarchical architecture. This composite exhibits unprecedented multifunctionality: simultaneous anti-fouling and de-icing, self-healing, exceptional low-temperature adaptability (down to -60 °C), and ultra-broadband microwave absorption. Leveraging the synergistic design of dielectric and magnetic losses, the composite achieves an effective absorption bandwidth of 6.6 GHz and a minimum reflection loss of -41.3 dB. Radar cross-section measurements reveal an average reduction of 8.15 dBsm and 5.5 dBsm under vertical and horizontal polarizations, respectively. Furthermore, the incorporation of rGO@Fe₃O₄ significantly enhances the composite's adhesive strength across various substrates. Notably, the incorporation of a dynamically regenerating paraffin lubrication phase does not compromise microwave absorption, resolving a long-standing trade-off between anti-solid fouling and electromagnetic impedance matching. This synergistic coupling enables stable broadband absorption performance even under repeated fouling, de-icing, and lubrication-regeneration cycles. These findings highlight the multifunctional composite's potential for practical applications in all-weather anti-solid adhesion and radar stealth, paving a new pathway for advanced surface engineering.

The scaling of transistors is approaching its physical limits, making the future direction of transistor development a topic of global significance. Low-dimensional materials (LDMs), which exhibit superior properties compared to bulk materials, are emerging as a driving force for transformative advancements across various industries. What do LDMs signify for the future of transistors? Where do the challenges and opportunities lie? This perspective concludes with an overview of the transistor development roadmap, highlighting key technological milestones for LDMs, and proposes three pathways for integrating LDMs into future transistors across near-, mid-, and long-term horizons. Graphical Abstract

This review delves into the cutting-edge advancements in the bioinspired flexible tactile sensors and their transformative role in enabling smart soft robots with embodied intelligence. Drawing inspiration from the multifunctionality of human skin, tactile sensors are desired to include similar mechanoreceptor, proprioception, and environmental responsiveness. This review begins by outlining fundamental design principles that mimic the hierarchical structure and distributed sensing networks of human skin. The biomimetic design and sensing principles of different flexible tactile sensors are then explained and compared, including pressure, temperature, and strain sensors. The state-of-the-art manufacturing methods, including direct ink writing, fused deposition modeling, digital light processing and material jet printing, are also introduced. By summarizing typical applications of these tactile sensors in smart soft robots, delicate object manipulation, human-robot collaboration, medical prosthetics, and adaptive locomotion are primarily discussed. Finally, it is promising to integrate innovations in fatigue-resistant elastomers, nanometer-scale 3-dimensional manufacturing, and artificial intelligence as potential elements to create next-generation of tactile sensors in the near future. By bridging biomimetic design, soft materials and robotics, this review aims to equip researchers and engineers with the knowledge to develop the tactile systems that push the boundaries of autonomy, safety, and interaction in soft robotics.

Double‐network (DN) gels have been demonstrated to possess enhanced toughness and fatigue resistance when compared to their single‐network counterparts. Nevertheless, these gels lack the specific directional orientation inherent in the anisotropic ordered structures characteristic of natural materials, thereby restricting their applicability within the domain of biomimetics. Herein, inspired by muscle stretching, we propose a facile strategy to prepare a single‐network anisotropic eutectic gel through an innovative approach that integrates solution replacement with circuit mechanical training. This strategy mimics the mechanism of muscle strengthening to form comprehensively reinforced gel muscles and skins for soft robots. The resultant gels exhibit unexceptionable mechanical and electrical properties compared to conventional single‐network gels, surpassing even the performance metrics of DN gels. Attributable to the anisotropic nanofibrous structures, which incorporate crystalline polymer frameworks and a high density of hydrogen bonds, these gels exhibit comprehensive mechanical properties of high strength (> 8.5 MPa), high toughness (∼20 MJ/m ³ ), and high fatigue resistance (> 1100 J/m ² ), and also resistance to drying and freezing. Additionally, upon eutectic liquid infusion, these gels achieve a high electrical conductivity (∼350 mS/m) and display sensitivity to temperature, strain, and pressure variations. Such properties position the toughened gel as a highly promising candidate for actuators and sensors in soft robotics, enabling high‐output actuation and multi‐modal sensing integration.

The core of atomic force microscopy (AFM) lies in the ultra-precise scanning between the tip and sample, which is enabled by nanopositioners. State-of-the-art AFMs generate the scanning motion using direct-drive nanopositioners, possessing either long range or high bandwidth, but not both. Here we show that with a triple-phase controller, the high-bandwidth (up to 363 Hz) nano-precision scanning can also be performed with a typical stick-slip nanopositioner. More importantly, by leveraging the displacement accumulation in the stepping mode, the same system achieved a 3 mm × 3 mm XY working range, 1-2 orders of magnitude larger than those direct-drive nanopositioners with a similar bandwidth. We further developed a versatile stick-slip AFM and demonstrated high-line-rate AFM imaging at 40 Hz over millimeter-scale areas. This work expands the functional scope of stick-slip nanopositioners, traditionally limited to static nanopositioning or long-range coarse positioning, and offers a cross-scale, high-bandwidth solution for next-generation AFMs.