Youngkyoo Kim

Facile detection of reactive oxygen species (ROS) is crucial for early-stage diagnosis and disease prediction, including cancer. Here, it is demonstrated that quercetin (QCT), a naturally derived polyphenol, forms nanoscale aggregates (clusters) within the matrix of the conjugated polymer, poly(3-hexylthiophene) (P3HT), and acts as a key material for sensing ROS in organic field-effect transistors (OFETs). To investigate the influence of QCT loading, the QCT content was varied from 0 to 70 wt % in the 50 nm-thick P3HT:QCT sensing channel layers for OFETs. Morphological analysis revealed that submicron-size QCT aggregates (up to ∼600 nm) were formed in the P3HT:QCT films. The basic transistor test showed that the best performance could be achieved at QCT = 30 wt % (abbreviated as QCT30-OFET). In the perfusion test that enables steady-state flow of ROS solutions, QCT30-OFETs could detect a wide range of ROS concentrations from 20 pM to 1 mM. The QCT30-OFETs were able to detect ROS systematically even under consecutive repeated injections of ROS solutions. A simple drop test demonstrated that droplets of ROS solutions could be easily detected by the present QCT30-OFET sensors, supporting the effectiveness and practicability of the QCT-based ROS sensing concept.

Achieving high-performance sodium-based solid-state electrolytes (SSEs) through environmentally friendly processes is crucial to establishing a solid foundation for safe and inexpensive energy storage devices. Here we demonstrate nonflammable sodium cation-transporting SSEs prepared from aqueous solutions of branched poly(ethylene imine) (bPEI), sodium hydroxide (NaOH), and sodium hexametaphosphate (SHMP). The bPEI:NaOH:SHMP (PNaS) SSEs exhibited an outstanding ion conductivity of ~1 mS/cm at SHMP = 20 mol%, which is 5 times higher than 0.18 mS/cm for the bPEI:NaOH (PNa) SSEs, due to the SHMP-induced morphology optimization for efficient Na ⁺ transport. The optimum PNaS SSEs could deliver the output voltage of 4.4 V by galvanostatic charging at 0.5 mA/g, exhibiting long-term retention characteristics (>1000 s). The PNaS supercapacitors exhibited stable operation with 99.68% capacitance retained during 2000 charging/discharging cycles, while the PNaS films were considerably stable without burning upon the flammability test.

Neuromorphic devices, mimicking the human brain's neural system, are considered an important hardware component to realize parallel computing processes for big data and artificial intelligence (AI)‐based humanoid robots. Organic synaptic transistors (OSTRs), one of the viable neuromorphic devices for futuristic soft AI systems, can be fabricated via solution‐based coating processes and offer huge advantages in shape design. Here OSTRs with polymer memory gate‐insulating layers (mGILs) are reported consisting of crosslinked poly(vinyl alcohol) (X‐PVA), in the presence of poly(2‐acrylamido‐2‐methyl‐1‐propanesulfonic acid) (PAMPSA) as a catalyst, which is controlled by adjusting the thermal annealing time at 150 ℃. Results show that thermal annealing for 10 min at 150 ℃ can almost complete the crosslinking reaction of PVA chains and deliver the optimum hysteresis and retention characteristics leading to high‐performing OSTRs that can be operated at low pulse voltages (≤ −2 V). The fine‐tuning of gate pulse conditions enables the present OSTRs to recognize with an accuracy of 96% by simulations of artificial neural network (ANN) matrix platforms, supporting strong potential as a unit transistor for neuromorphic array devices.

Polymeric solid‐state electrolytes (SSEs) with environmentally friendly processes deliver safer and cleaner energy storage devices without fires and leakages than conventional liquid electrolytes. Here, water‐processable halogen‐free polymeric SSEs are demonstrated with high ion conductivity (≈6 mS cm ⁻¹ ), prepared from aqueous solutions consisting of branched poly(ethylene imine) (bPEI), lithium hydroxide (LiOH), and poly(4‐styrene sulfonic acid) (PSSA). The bPEI:LiOH:PSSA (PLP) SSEs with various PSSA molar ratios are applied to asymmetric supercapacitors with graphite‐based anodes and indium tin oxide (ITO) counter electrodes. The PSSA molar ratio strongly affected the ion conductivity of PLP SSEs, leading to a maximum at PSSA = 40 mol%, owing to the role of PSSA in controlling the size of LiOH domains for better Li ⁺ transport pathways. The enhanced ion conductivity enabled PLP‐supercapacitors to build a high potential of 2.24 V at PSSA = 40 mol%, compared to 1.64 V at 0 mol%, upon galvanostatic charge/discharge at a current density of 0.2 mA g ⁻¹ . The endurance test shows that the supercapacitors with the PLP SSEs (PSSA = 40 mol%) can function stably with high capacitance retention (96.2%) for more than 5000 cycles, and ≈80% capacitance retention at 80 °C, supporting their practical use in high‐safety supercapacitors and batteries.

Achieving high retention of memory state is crucial in artificial synapse devices for neuromorphic computing systems. Of various memorizing methods, a charge‐trapping method provides fast response times when it comes to the smallest size of electrons. Here, for the first time, it is demonstrated that trivalent molecular bridges with three ionic bond sites in the polymeric films can efficiently trap electrons in the organic synaptic transistors (OSTRs). A water‐soluble polymer with sulfonic acid groups, poly(2‐acrylamido‐2‐methyl‐1‐propanesulfonic acid) (PAMPSA), is reacted with melamine (ML) to make trivalent molecular bridges with three ionic bond sites for the application of charge‐trapping and gate‐insulating layer in all‐solid‐state OSTRs. The OSTRs with the PAMPSA:ML layers are operated at low voltages (≤5 V) with pronounced hysteresis and high memory retention characteristics (ML = 25 mol%) and delivered excellent potentiation/depression performances under modulation of gate pulse frequency. The optimized OSTRs could successfully process analog (Morse/Braile) signals to synaptic current datasets for recognition/prediction logics with an accuracy of >95%, supporting strong potential as all‐solid‐state synaptic devices for neuromorphic systems in artificial intelligence applications.