Efficient Removal and Recovery of Ag from Wastewater Using Charged Polystyrene-Polydopamine Nanocoatings and Their Sustainable Catalytic Application in 4‑Nitrophenol Reduction

This study addresses the long-standing challenges of removing and recovering trace silver (Ag) ions from wastewater while promoting their sustainable catalysis utilization. We innovatively developed a composite material by combining charged sulfonated polystyrene (PS) with a PDA coating. This composite serves a dual purpose: effectively removing and recovering trace Ag+ from wastewater and enabling reused Ag for sustainable applications, particularly in the catalytic reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP). The PS–PDA demonstrated exceptional selectivity to trace Ag+ recycling, which is equal to 14 times greater than the commercial ion exchanger. We emphasize the distinct roles of different charged functional groups in Ag+ removal and catalytic reduction performance. The negatively charged SO3H groups exhibited the remarkable ability to rapidly enrich trace Ag ions from wastewater, with a capacity 2–3 times higher than that of positively-N+(CH3)3Cl and netural-CH2Cl-modified composites; this resulted in an impressive 96% conversion of 4-NP to 4-AP within just 25 min. The fixed-bed application further confirmed the effective treatment capacity of approximately 4400 L of water per kilogram of adsorbent, while maintaining an extremely low effluent Ag+ concentration of less than 0.1 mg/L. XPS investigations provided valuable insights into the conversion of Ag+ ions into metallic Ag through the enticement of negatively charged SO3H groups and the in situ reduction facilitated by PDA. This breakthrough not only facilitates the efficient extraction of Ag from wastewater but also paves the way for its environmentally responsible utilization in catalytic reactions

A broad range triboelectric stiffness sensor for variable inclusions recognition

With the development of artificial intelligence, stiffness sensors are extensively utilized in various fields, and their integration with robots for automated palpation has gained significant attention. This study presents a broad range self-powered stiffness sensor based on the triboelectric nanogenerator (Stiff-TENG) for variable inclusions in soft objects detection. The Stiff-TENG employs a stacked structure comprising an indium tin oxide film, an elastic sponge, a fluorinated ethylene propylene film with a conductive ink electrode, and two acrylic pieces with a shielding layer. Through the decoupling method, the Stiff-TENG achieves stiffness detection of objects within 1.0 s. The output performance and characteristics of the TENG for different stiffness objects under 4 mm displacement are analyzed. The Stiff-TENG is successfully used to detect the heterogeneous stiffness structures, enabling effective recognition of variable inclusions in soft object, reaching a recognition accuracy of 99.7%. Furthermore, its adaptability makes it well-suited for the detection of pathological conditions within the human body, as pathological tissues often exhibit changes in the stiffness of internal organs. This research highlights the innovative applications of TENG and thereby showcases its immense potential in healthcare applications such as palpation which assesses pathological conditions based on organ stiffness.</p

Data_Sheet_1_Epidural combined optical and electrical stimulation induces high-specificity activation of target muscles in spinal cord injured rats.docx

IntroductionEpidural electrical stimulation (EES) has been shown to improve motor dysfunction after spinal cord injury (SCI) by activating residual locomotor neural networks. However, the stimulation current often spreads excessively, leading to activation of non-target muscles and reducing the accuracy of stimulation regulation.ObjectivesNear-infrared nerve stimulation (nINS) was combined with EES to explore its regulatory effect on lower limb muscle activity in spinal-cord-transected rats.MethodsIn this study, stimulation electrodes were implanted into the rats’ L3–L6 spinal cord segment with T8 cord transected. Firstly, a series of EES parameters (0.2–0.6 mA and 20–60 Hz) were tested to determine those that specifically regulate the tibialis anterior (TA) and medial gastrocnemius (MG). Subsequently, to determine the effect of combined optical and electrical stimulation, near-infrared laser with a wavelength of 808 nm was used to irradiate the L3–L6 spinal cord segment while EES was performed. The amplitude of electromyography (EMG), the specific activation intensity of the target muscle, and the minimum stimulus current intensity to induce joint movement (motor threshold) under a series of optical stimulation parameters (power: 0.0–2.0 W; pulse width: 0–10 ms) were investigated and analyzed.ResultsEES stimulation with 40 Hz at the L3 and L6 spinal cord segments specifically activated TA and MG, respectively. High stimulation intensity (>2 × motor threshold) activated non-target muscles, while low stimulation frequency (ConclusionThe study demonstrates the feasibility of epidural combined electrical and optical stimulation for highly specific regulation of muscle activity after SCI, and provides a new strategy for improving motor dysfunction caused by SCI.</p

Supplementary information files for A broad range triboelectric stiffness sensor for variable inclusions recognition

Supplementary files for article A broad range triboelectric stiffness sensor for variable inclusions recognitionWith the development of artificial intelligence, stiffness sensors are extensively utilized in various fields, and their integration with robots for automated palpation has gained significant attention. This study presents a broad range self-powered stiffness sensor based on the triboelectric nanogenerator (Stiff-TENG) for variable inclusions in soft objects detection. The Stiff-TENG employs a stacked structure comprising an indium tin oxide film, an elastic sponge, a fluorinated ethylene propylene film with a conductive ink electrode, and two acrylic pieces with a shielding layer. Through the decoupling method, the Stiff-TENG achieves stiffness detection of objects within 1.0 s. The output performance and characteristics of the TENG for different stiffness objects under 4 mm displacement are analyzed. The Stiff-TENG is successfully used to detect the heterogeneous stiffness structures, enabling effective recognition of variable inclusions in soft object, reaching a recognition accuracy of 99.7%. Furthermore, its adaptability makes it well-suited for the detection of pathological conditions within the human body, as pathological tissues often exhibit changes in the stiffness of internal organs. This research highlights the innovative applications of TENG and thereby showcases its immense potential in healthcare applications such as palpation which assesses pathological conditions based on organ stiffness.</p