Metal-Stabilized Thiyl Radicals Design Inspired by Elemental Periodic Extension Notion for Ligand-Based Alkene Addition.

Inspired by alkene addition to the Ru and Re tris(thiolate) complexes via carbon-sulfur bond formation/cleavage reactions along with a periodic extension catalysis notion, a comparative study of the electronic structures, mechanisms, and reactivities for ethylene addition to the Os and Tc tris(thiolate) complexes was performed by DFT and high-level ab initio quantum calculations. The oxidized Os and Tc complexes were revealed to exhibit sufficient radical characters on the ligands to support their reaction with ethylene, whereas neutral Tc tris(thiolate) complex featuring little thiyl radical character renders no reactivity toward ethylene. Differential reactivities of these tris(thiolate) complexes was deemed to derive from the synergy of the thiyl radical character, the electronegativity, the row, and the charge. Extending from Ru and Re tris(thiolate) complexes to their Os and Tc counterparts can help us to get insightful rationales that would promote further research on alkene addition to metal-stabilized thiyl radicals.

Human-robot facial coexpression.

Large language models are enabling rapid progress in robotic verbal communication, but nonverbal communication is not keeping pace. Physical humanoid robots struggle to express and communicate using facial movement, relying primarily on voice. The challenge is twofold: First, the actuation of an expressively versatile robotic face is mechanically challenging. A second challenge is knowing what expression to generate so that the robot appears natural, timely, and genuine. Here, we propose that both barriers can be alleviated by training a robot to anticipate future facial expressions and execute them simultaneously with a human. Whereas delayed facial mimicry looks disingenuous, facial coexpression feels more genuine because it requires correct inference of the human's emotional state for timely execution. We found that a robot can learn to predict a forthcoming smile about 839 milliseconds before the human smiles and, using a learned inverse kinematic facial self-model, coexpress the smile simultaneously with the human. We demonstrated this ability using a robot face comprising 26 degrees of freedom. We believe that the ability to coexpress simultaneous facial expressions could improve human-robot interaction.

Anti-fogging/dry-dust transparent superhydrophobic surfaces based on liquid-like molecule brush modified nanofiber cluster structures.

Transparent protective coatings capable of preventing fog and dust accumulation have broad application prospect in photovoltaic systems, optical devices and consumer electronics. Although a number of superhydrophobic coatings have been developed for self-cleaning purpose over the past three decades, there is still a lack of surfaces that can simultaneously possess high transparency, remarkable superhydrophobicity, and excellent fog and dust resistance. In this study, we have prepared surfaces featuring sub-wavelength nanofiber cluster structures through a facile plasma etching method, and further modified the surface with liquid-like perfluoropolyether (PFPE) brushes. The prepared PFPE modified nanofibrous surface (PFPE-NS) exhibits superior optical transparency (transmittance 90.4 % ± 0.7 %) and water repellency, with a water contact angle as high as 171.0° ± 0.6° and sliding angle down to 0.5° ± 0.1° (5 µL). More importantly, benefitted from the nanofiber cluster structures and the slippery liquid-like surface chemistry, the adhesion and accumulation of fog droplets and dust particles on PFPE-NS is greatly inhibited. As a consequence, PFPE-NS can keep excellent optical clearness after 2 h fogging test and maintain an average transmittance above 87 % after 24 h dusting test. Our study provides a promising strategy through constructing liquid-like nanofibrous coating for optical protection that could be applicable in practical rainy, foggy, and dusty environments.

Design of highly robust super-liquid-repellent surfaces that can resist high-velocity impact of low-surface-tension liquids.

Super-liquid-repellent surfaces capable of preventing wetting with various liquids have tremendous application. However, high liquid repellency relies on surface texturing to minimize the solid-liquid interfacial contact, which generally results in impaired interface robustness and pressure resistance. Consequently, the surface tends to undergo a Cassie-Baxter to Wenzel wetting transition and loses liquid repellency under high-velocity liquid impact, especially for low-surface-tension liquids. Here, surface design through combining the nanoscale effect and doubly reentrant structure is demonstrated to solve the above challenge. By utilizing a facile colloidal lithography process, robust liquid repellent surfaces featuring nanoscale doubly reentrant (NDR) structures are constructed. The nanoscale features ensure sufficient triple contact line density at a low solid-liquid contact fraction to enhance the capillary force for liquid suspension. In conjunction with the doubly reentrant topography that maximizes the upward component of capillary force, such NDR surfaces enable an extremely robust solid-liquid-gas composite interface. As a result, the prepared NDR surface maintain excellent repellency upon high-velocity impact of various liquids, including ethylene glycol drops with a Weber number (We) above 306 and ethanol drops with a We of 57. The above findings can help the development of super-liquid-repellent surfaces applicable to harsh conditions of high-velocity liquid impact or high hydrostatic pressure.

Whether and When Superhydrophobic/Superoleophobic Surfaces Are Fingerprint Repellent.

Driven by the ever-increasing demand for fingerprint-resistant techniques in modern society, numerous researches have proposed to develop innovative antifingerprint coatings based on superhydrophobic/superoleophobic surface design. However, whether superhydrophobic/superoleophobic surfaces have favorable repellency to the microscopic fingerprint is in fact an open question. Here, we establish a reliable method that enables evaluating the antifingerprint capability of various surfaces in a quantitative way. We show that superhydrophobicity is irrelevant with fingerprint repellency. Regarding superoleophobic surfaces, two distinct wetting states of microscopic fingerprint residues, i.e., the "repellent" and the "collapsed" states, are revealed. Only in the "repellent" state, in which the fingerprint residues remain atop surface textures upon being pressed, superoleophobic surfaces can bring about favorable antifingerprint repellency, which correlates positively with their receding contact angles. A finger-deformation-dependent intrusion mechanism is proposed to account for the formation of different fingerprint wetting states. Our findings offer important insights into the mechanism of fingerprint repellency and will help the design of high-performance antifingerprint surfaces for diverse applications.

Superhydrophobic and superoleophilic porous reduced graphene oxide/polycarbonate monoliths for high-efficiency oil/water separation.

Superhydrophobic and superoleophilic porous reduced graphene oxide/polycarbonate (RGO/PC) monoliths with novel micro-nanoscale binary structure were first fabricated by thermally impacted nonsolvent induced phase separation (TINIPS) method. Owing to the unique pore structure, the porous monoliths possessed high specific surface area (137.19m2/g) and porosity (91.3%). The superhydrophobic RGO/PC monoliths exhibited excellent capability to selectively adsorb a wide range of oils and organic solvents from water. Furthermore, the monoliths could keep a stable repellency against corrosive mediums (e.g., acidic and alkali solutions). Based on these superior properties, porous RGO/PC monoliths will be a promising candidate for high-efficiency oil/water separation to deal with water pollution.