A huge challenge for developing self-healing materials is achieving a good compromisation between mechanical properties and self-healing efficiency. For this purpose, a facile route by introducing N-(hydroxymethyl)­acrylamide (NMA) as a thermal-catalyzed self-cross-linker as well as a self-healing material into a soft polymer system for tuning the mechanical properties in an easy way, resulting in elastic and self-healing properties through a covalent and dynamic network simultaneously, represents an exciting avenue for the development of self-healing materials. Specifically, we propose a simple strategy to synthesize a self-cross-linkable poly­{(n-butyl acrylate)-co-[N-(hydroxymethyl)­acrylamide]} (PBA x -co-PNMA y ) amphiphilic copolymer prepared by radical polymerization method, where x and y are BA and NMA ratios, respectively, based on the monomer composition in the obtained copolymer. The mechanical properties and self-healing efficiency of the copolymer can be easily tuned by controlling the monomer ratios and varying the self-cross-linking reaction conditions. PBA0.8-co-PNMA0.2 in bulk solid state possesses a stretchability of up to 191%, maximum stress of 571 kPa, and a self-healing efficiency of 90% in ambient conditions without any interventions. Owing to the hydrophobic nature of PBA in the copolymer system, self-healing can be triggered even underwater. Furthermore, a microscale thin film bestowed with identical self-healing and mechanical properties can be fabricated and the behavior of the copolymer in thin-film form was inspected using a pseudofreestanding tensile tester machine. This work provides insight into the future design of materials with elastic, self-cross-linking, and self-healing properties, which are adjustable depending on the desired applications.

Artificial synaptic thin-film transistor (TFT) devices have recently attracted considerable attention because they can emulate biological synapses, which enables the devices to process and store information like the human brain [1] wherein computation and storage are executed simultaneously-thereby enabling spatiotemporal information processing through timedependent neuron interconnections. Synapses play a major role linking signals transmitted between pre-and postneurons, thereby enabling the brain to function. Neuronal connectivity strength, also known as "plasticity," determines the brain's cognitive intelligence. Adjusting neuronal plasticity enables the brain to concurrently process and store information. [2] Inspired by this collective and adaptive property of human memory, researchers have dedicated considerable effort to developing and implementing neuromorphic computational systems to emulate the brain's strategy of parallel information processing and storage. [3] Such a device would be highly promising for rapidly advancing artificial intelligence [4] because replacing inefficient and high-power-consuming traditional von Neumann-architecture-based computers with separate processor and memory units is feasible. [2c,e,5] To date, synaptic TFT devices have demonstrated their suitability for many practical applications including artificial tactile sensory organs, neurological electronic skin, wearable intelligent electronics, and neuromorphic vision systems. [4a,6] However, fully implementing current devices is limited by numerous challenges. First, most reported devices exhibit sophisticated architectures involving complex fabrication procedures, [1a,5b] which can render such devices expensive and ineffective. In addition, because most reported synaptic devices are electrically operated, they may be limited by the bandwidth/connection-density tradeoff and may exhibit lowspeed signal transmission. [5b,7] Photonic-modulated synaptic devices, on the other hand, have rarely been reported. However, such devices operate based on focused light stimuli exhibiting Although synaptic devices have already demonstrated their operability through electric or photonic signals or a combination thereof, current challenges include developing a single hardware synaptic device that is independently fully operational through either photonic or electric signals to improve device versatility. Additionally, most previously reported devices are fabricated using multiple technical processes-which impede device implementation-while the low-output current triggered in most such devices limits the possible integration of auxiliary gadgets. Therefore, by spontaneously wrapping a conjugated block copolymer around single-walled carbon nanotubes (SWCNTs), a thin-film transistor memory device comprising single-layered poly(9,9-dioctylfluorene)-b-polyisoprene (PF-b-PI)-wrapped-SWCNTs-which function as both a semiconductor and an electret layer-to simplify the device structure and fabrication is designed. Owing to the robust SWCNT ...

In article number 2101506, Yu-Cheng Chiu and colleagues present single-layered design of conjugated polymer-wrapped single-walled carbon nanotubes for a high-mobility synaptic transistor. The proposed simplified device independently exhibits both voltage-and lightcontrollable switching, thereby mimicking biological synaptic behavior such as short-and long-term plasticity, spike-time, and spike-rate-dependent plasticity.

Conjugated polymer sorting is currently the best method to select large-diameter single-walled carbon nanotubes (SWCNTs) with tunable narrow chirality in the adaption of highly desired electronics applications. The acceleration on conjugated polymers-SWCNTs interaction with long-term stability through different molecular designs; for example, longer alkyl side-chains or conjugation moieties have been extensively developed in recent years. However, the importance of the macromolecules with abundant van der Waals (VDW) interaction in the conjugated-based block copolymer system acting during SWCNTs sorting is not clearly demonstrated. In this work, a conjugated diblock copolymer involving polyisoprene (PI) and highly dense -interaction of poly (9,9-dioctylfluorene) (PFO) is utilized to investigate the impact of natural rubber PI physical interaction on sorting effectiveness and stability. Through the rational design of diblock copolymer, PFO with ≈1200 isoprene units can remarkably enhance SWCNTs sorting ability and selected few chiralities with a diameter of ≈0.83-1.1 nm and highly stable solution for more than 1 year. The introduction of long-chain PI system is attributed not only to form weak VDW force with SWCNTs and strengthen the wrapping of PFO around the semiconducting SWCNTs but also to act as a barrier among nanotubes to prevent reaggregation of sorted SWCNTs.

The π–π interaction between the conjugated polymer and single‐walled carbon nanotubes (SWCNTs) is the key to dispersion and selection of semiconducting nanotubes. High molecular weight (Mw > 10 000 Da) conjugated moieties usually form the main chain of the copolymers designed for sorting to ensure strong π–π interaction. However, low Mw conjugated polymers are sorting‐ineffective because they do not interact with SWCNTs. Additionally, sorted nanotubes in solution aggregate during storage or at low temperatures, possibly due to loss of wrapping ability of the dispersant, and stability of the sorted solution is rarely reported. Here, the effectiveness of polyisoprene with hydrogen‐bonding to induce superior sorting and solution stability in a low Mw conjugated polymer is demonstrated. A vinyl‐terminated‐poly(9,9‐dioctylfluorene) (vinyl‐PFO, Mw ≈ 4500) copolymerized with polyisoprene with hydrogen‐bond containing pendant; Poly(2[[(Butylamino) carbonyl]oxy]ethyl‐acrylate, can select large‐diameter semiconducting nanotubes (1.17 nm), and the sorted solution remains stable as observed by UV spectroscopy and thin‐film transistors, for over a year and at low temperatures; 4, −20, and −80 °C. Furthermore, solution can fabricate ambipolar transistors with averaged charge carrier mobility; 48 cm2 V–1 s–1 for p‐type, and 32 cm2 V–1 s–1 for n‐type, with retention stability > 6000 s.