Brain inspired iontronic fluidic memristive and memcapacitive device for self-powered electronics.

Ionic fluidic devices are gaining interest due to their role in enabling self-powered neuromorphic computing systems. In this study, we present an approach that integrates an iontronic fluidic memristive (IFM) device with low input impedance and a triboelectric nanogenerator (TENG) based on ferrofluid (FF), which has high input impedance. By incorporating contact separation electromagnetic (EMG) signals with low input impedance into our FF TENG device, we enhance the FF TENG's performance by increasing energy harvesting, thereby enabling the autonomous powering of IFM devices for self-powered computing.

A specific turn-on fluorescence probe for determination of nitazoxanide based on feasible oxidation reaction with hypochlorite: Applying cobalt ferrite nanoparticles for pre-concentration and extraction of its metabolite from real urine samples.

Nitazoxanide is an antimicrobial compound that was originally developed as an antiprotozoal drug. Recently nitazoxanide has been identified as broad-spectrum antiviral agent and redirected for the remediation of some respiratory tract viral infections. In this study, the spectrofluorimetric technique has been applied to determine Nitazoxanide (NTX) in tablets or its metabolite, tizoxanide (TZD), in human urine samples.

RRAM-based CAM combined with time-domain circuits for hyperdimensional computing.

Content addressable memory (CAM) for search and match operations demands high speed and low power for near real-time decision-making across many critical domains. Resistive RAM (RRAM)-based in-memory computing has high potential in realizing an efficient static CAM for artificial intelligence tasks, especially on resource-constrained platforms. This paper presents an XNOR-based RRAM-CAM with a time-domain analog adder for efficient winning class computation.